From cf11daf139dac57de3b921c55a953398edd8311c Mon Sep 17 00:00:00 2001 From: daiyuxin Date: Fri, 1 Apr 2022 11:33:26 +0800 Subject: [PATCH] update markdown files for 1.5 and 1.6 --- .../mindspore/1.5/advancedeast_icpr2018.md | 62 ++++++++++++++ mshub_res/assets/mindspore/1.5/albert_mnli.md | 63 +++++++++++++++ .../assets/mindspore/1.5/albert_squadv1.1.md | 63 +++++++++++++++ mshub_res/assets/mindspore/1.5/albert_sst2.md | 63 +++++++++++++++ .../assets/mindspore/1.5/alexnet_cifar10.md | 79 ++++++++++++++++++ .../mindspore/1.5/alexnet_imagenet2012.md | 79 ++++++++++++++++++ .../assets/mindspore/1.5/arcface_ms1mv2.md | 62 ++++++++++++++ .../assets/mindspore/1.5/attgan_G_celeba.md | 62 ++++++++++++++ .../mindspore/1.5/autoaugment_cifar10.md | 79 ++++++++++++++++++ .../mindspore/1.5/autodeeplab_cityscapes.md | 62 ++++++++++++++ .../assets/mindspore/1.5/avacifar_cifar10.md | 58 +++++++++++++ .../mindspore/1.5/bertbase_cnnews128.md | 80 ++++++++++++++++++ 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/dev/null +++ b/mshub_res/assets/mindspore/1.5/advancedeast_icpr2018.md @@ -0,0 +1,62 @@ +# advanced_east + +--- + +model-name: advanced_east + +backbone-name: advanced_east + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: icpr2018 + +evaluation: F1acc61.52 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 29da691de69194138d3ab0f74ae62299cff4e3d7432e6e511f70706c238edc9e + +license: Apache2.0 + +summary: advanced_east is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of advanced_east from the MindSpore model zoo on Gitee at research/cv/advanced_east. + +advanced_east is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/advanced_east](https://gitee.com/mindspore/models/blob/r1.5/research/cv/advanced_east/README.md). + +All parameters in the module are trainable. + +## Citation + +EAST:An Efficient and Accurate Scene Text Detector. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/albert_mnli.md b/mshub_res/assets/mindspore/1.5/albert_mnli.md new file mode 100644 index 0000000..6fc828a --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/albert_mnli.md @@ -0,0 +1,63 @@ +# albert + +--- + +model-name: albert + +backbone-name: albert + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: mnli + +evaluation: acc82.25 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: ec4f2c5302b299d7751a60615a1d0f4316527146a6909c5d86b9afa5720bcc7a + +license: Apache2.0 + +summary: albert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of albert from the MindSpore model zoo on Gitee at research/nlp/albert. + +albert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [research/nlp/albert](https://gitee.com/mindspore/models/blob/r1.5/research/nlp/albert/README.md). + +All parameters in the module are trainable. + +## Citation + +1. Lan, Z., Chen, M., Goodman, S., Gimpel, K., Sharma, P., & Soricut, R. (2020). ALBERT: A Lite BERT for Self-supervised Learning of Language Representations. ArXiv, abs/1909.11942. +2. Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv preprint arXiv:1810.04805. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/albert_squadv1.1.md b/mshub_res/assets/mindspore/1.5/albert_squadv1.1.md new file mode 100644 index 0000000..b0f5a77 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/albert_squadv1.1.md @@ -0,0 +1,63 @@ +# albert + +--- + +model-name: albert + +backbone-name: albert + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: squadv1.1 + +evaluation: exactmatch80.88 | F1score88.71 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c60cc45a88fbf85bac9bc4bc3edced7d31281511bd6f70c6e13fb3ccc8e2ec09 + +license: Apache2.0 + +summary: albert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of albert from the MindSpore model zoo on Gitee at research/nlp/albert. + +albert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [research/nlp/albert](https://gitee.com/mindspore/models/blob/r1.5/research/nlp/albert/README.md). + +All parameters in the module are trainable. + +## Citation + +1. Lan, Z., Chen, M., Goodman, S., Gimpel, K., Sharma, P., & Soricut, R. (2020). ALBERT: A Lite BERT for Self-supervised Learning of Language Representations. ArXiv, abs/1909.11942. +2. Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv preprint arXiv:1810.04805. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/albert_sst2.md b/mshub_res/assets/mindspore/1.5/albert_sst2.md new file mode 100644 index 0000000..ea26a74 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/albert_sst2.md @@ -0,0 +1,63 @@ +# albert + +--- + +model-name: albert + +backbone-name: albert + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: sst2 + +evaluation: acc89.11 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 84769afa38111286e320c55c220a0cdf3c68a4f45239576e610ac9fd195ad190 + +license: Apache2.0 + +summary: albert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of albert from the MindSpore model zoo on Gitee at research/nlp/albert. + +albert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [research/nlp/albert](https://gitee.com/mindspore/models/blob/r1.5/research/nlp/albert/README.md). + +All parameters in the module are trainable. + +## Citation + +1. Lan, Z., Chen, M., Goodman, S., Gimpel, K., Sharma, P., & Soricut, R. (2020). ALBERT: A Lite BERT for Self-supervised Learning of Language Representations. ArXiv, abs/1909.11942. +2. Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv preprint arXiv:1810.04805. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/alexnet_cifar10.md b/mshub_res/assets/mindspore/1.5/alexnet_cifar10.md new file mode 100644 index 0000000..9f49c0f --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/alexnet_cifar10.md @@ -0,0 +1,79 @@ +# alexnet + +--- + +model-name: alexnet + +backbone-name: alexnet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cifar10 + +evaluation: acc89.38 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 84569e4934f9a49093d50ba43f851a761fb35a8dad72c991ae928e0646a261c7 + +license: Apache2.0 + +summary: alexnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of alexnet from the MindSpore model zoo on Gitee at official/cv/alexnet. + +alexnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/alexnet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/alexnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/alexnet_cifar10" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Krizhevsky A, Sutskever I, Hinton G E. ImageNet Classification with Deep ConvolutionalNeural Networks. *Advances In Neural Information Processing Systems*. 2012. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/alexnet_imagenet2012.md b/mshub_res/assets/mindspore/1.5/alexnet_imagenet2012.md new file mode 100644 index 0000000..e6d9213 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/alexnet_imagenet2012.md @@ -0,0 +1,79 @@ +# alexnet + +--- + +model-name: alexnet + +backbone-name: alexnet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc57.45 | top5acc80 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 363ce17938585048f0725d57372bcef2d167b4e4346cb39f1128434686f2b69f + +license: Apache2.0 + +summary: alexnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of alexnet from the MindSpore model zoo on Gitee at official/cv/alexnet. + +alexnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/alexnet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/alexnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/alexnet_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Krizhevsky A, Sutskever I, Hinton G E. ImageNet Classification with Deep ConvolutionalNeural Networks. *Advances In Neural Information Processing Systems*. 2012. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/arcface_ms1mv2.md b/mshub_res/assets/mindspore/1.5/arcface_ms1mv2.md new file mode 100644 index 0000000..c09fb72 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/arcface_ms1mv2.md @@ -0,0 +1,62 @@ +# arcface + +--- + +model-name: arcface + +backbone-name: arcface + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: ms1mv2 + +evaluation: ijbb95.06 | ijbc96.39 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5897d6d1b98411e170625377871b1daf658f6ba477765ba3c9872a24097a629f + +license: Apache2.0 + +summary: arcface is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of arcface from the MindSpore model zoo on Gitee at research/cv/arcface. + +arcface is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/arcface](https://gitee.com/mindspore/models/blob/r1.5/research/cv/arcface/README.md). + +All parameters in the module are trainable. + +## Citation + +Deng J , Guo J , Zafeiriou S . ArcFace: Additive Angular Margin Loss for Deep Face Recognition[J]. 2018. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/attgan_G_celeba.md b/mshub_res/assets/mindspore/1.5/attgan_G_celeba.md new file mode 100644 index 0000000..ced87f6 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/attgan_G_celeba.md @@ -0,0 +1,62 @@ +# AttGAN + +--- + +model-name: AttGAN + +backbone-name: AttGAN + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: celeba + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: cc3c9f53714cafa0279d3856f50d164dd8245b8a67fb0f60e72a36012fef2026 + +license: Apache2.0 + +summary: AttGAN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of AttGAN from the MindSpore model zoo on Gitee at research/cv/AttGAN. + +AttGAN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/AttGAN](https://gitee.com/mindspore/models/blob/r1.5/research/cv/AttGAN/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Zhenliang He, Wangmeng Zuo, Meina Kan, Shiguang Shan, Xilin Chen, et al. AttGAN: Facial Attribute Editing by Only Changing What You Want[C]// 2017 CVPR. IEEE + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/autoaugment_cifar10.md b/mshub_res/assets/mindspore/1.5/autoaugment_cifar10.md new file mode 100644 index 0000000..53f510f --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/autoaugment_cifar10.md @@ -0,0 +1,79 @@ +# autoaugment + +--- + +model-name: autoaugment + +backbone-name: autoaugment + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cifar10 + +evaluation: acc97.22 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 3dfbe4b3bfca01c359c016f09377eb157dfd3c569543e52f483b8b451b652d2d + +license: Apache2.0 + +summary: autoaugment is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of autoaugment from the MindSpore model zoo on Gitee at research/cv/autoaugment. + +autoaugment is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/autoaugment](https://gitee.com/mindspore/models/blob/r1.5/research/cv/autoaugment/README_CN.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/autoaugment_cifar10" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Cubuk, Ekin D., et al. "Autoaugment: Learning augmentation strategies from data." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/autodeeplab_cityscapes.md b/mshub_res/assets/mindspore/1.5/autodeeplab_cityscapes.md new file mode 100644 index 0000000..fb8300b --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/autodeeplab_cityscapes.md @@ -0,0 +1,62 @@ +# Auto-DeepLab + +--- + +model-name: Auto-DeepLab + +backbone-name: Auto-DeepLab + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cityscapes + +evaluation: 0.5macc75 | 1.0macc77 | 1.5macc78 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: acf76d476fc4e42dc078ff8ab2050bdff34cdb8280fb6e2778c48c628c00e39f + +license: Apache2.0 + +summary: Auto-DeepLab is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of Auto-DeepLab from the MindSpore model zoo on Gitee at research/cv/Auto-DeepLab. + +Auto-DeepLab is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/Auto-DeepLab](https://gitee.com/mindspore/models/blob/r1.5/research/cv/Auto-DeepLab/README.md). + +All parameters in the module are trainable. + +## Citation + +Chenxi Liu, Liang-Chieh Chen, Florian Schroff, Hartwig Adam, Wei Hua, Alan L. Yuille, Li Fei-Fei; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, pp. 82-92 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/avacifar_cifar10.md b/mshub_res/assets/mindspore/1.5/avacifar_cifar10.md new file mode 100644 index 0000000..eb80c80 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/avacifar_cifar10.md @@ -0,0 +1,58 @@ +# AVA_cifar + +--- + +model-name: AVA_cifar + +backbone-name: AVA_cifar + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cifar10 + +evaluation: top1acc90.87 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 955f6c567108af733ea82f8efb1eec0accd44cbc79a41b2d216ca83d09a646c6 + +license: Apache2.0 + +summary: AVA_cifar is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of AVA_cifar from the MindSpore model zoo on Gitee at research/cv/AVA_cifar. + +AVA_cifar is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/AVA_cifar](https://gitee.com/mindspore/models/blob/r1.5/research/cv/AVA_cifar/README.md). + +All parameters in the module are trainable. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/bertbase_cnnews128.md b/mshub_res/assets/mindspore/1.5/bertbase_cnnews128.md new file mode 100644 index 0000000..8b5aa2f --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/bertbase_cnnews128.md @@ -0,0 +1,80 @@ +# bert + +--- + +model-name: bert + +backbone-name: bert + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cnnews128 + +evaluation: loss1.5 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5320e958731641eb26cad931a23ff7f462745877ddee89480daef239f0e2fa68 + +license: Apache2.0 + +summary: bert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of bert from the MindSpore model zoo on Gitee at official/nlp/bert. + +bert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/bert](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/bert/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/bertbase_cnnews128" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv preprint arXiv:1810.04805. +2. Junqiu Wei, Xiaozhe Ren, Xiaoguang Li, Wenyong Huang, Yi Liao, Yasheng Wang, Jiashu Lin, Xin Jiang, Xiao Chen, Qun Liu. NEZHA: Neural Contextualized Representation for Chinese Language Understanding. arXiv preprint arXiv:1909.00204. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/bertfinetuning_classifier_cola.md b/mshub_res/assets/mindspore/1.5/bertfinetuning_classifier_cola.md new file mode 100644 index 0000000..0ea6061 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/bertfinetuning_classifier_cola.md @@ -0,0 +1,80 @@ +# bert + +--- + +model-name: bert + +backbone-name: bert + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cola + +evaluation: acc55.71 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 954952abff015a8686840dca6920282d75c20ee2b75eee341d4151e3c84e5d66 + +license: Apache2.0 + +summary: bert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of bert from the MindSpore model zoo on Gitee at official/nlp/bert. + +bert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/bert](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/bert/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/bertfinetuning_classifier_cola" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova.BERT：深度双向Transformer语言理解预训练). arXiv preprint arXiv:1810.04805. +2. Junqiu Wei, Xiaozhe Ren, Xiaoguang Li, Wenyong Huang, Yi Liao, Yasheng Wang, Jiashu Lin, Xin Jiang, Xiao Chen, Qun Liu.NEZHA：面向汉语理解的神经语境表示. arXiv preprint arXiv:1909.00204. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/bertfinetuning_nercrf_cluener.md b/mshub_res/assets/mindspore/1.5/bertfinetuning_nercrf_cluener.md new file mode 100644 index 0000000..3d32e5c --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/bertfinetuning_nercrf_cluener.md @@ -0,0 +1,80 @@ +# bert + +--- + +model-name: bert + +backbone-name: bert + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cluener + +evaluation: acc92.48 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 2dbc96564c533fab13e185e03e7a50861d25824a72562b263a7f36df107f43b8 + +license: Apache2.0 + +summary: bert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of bert from the MindSpore model zoo on Gitee at official/nlp/bert. + +bert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/bert](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/bert/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/bertfinetuning_nercrf_cluener" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova.BERT：深度双向Transformer语言理解预训练). arXiv preprint arXiv:1810.04805. +2. Junqiu Wei, Xiaozhe Ren, Xiaoguang Li, Wenyong Huang, Yi Liao, Yasheng Wang, Jiashu Lin, Xin Jiang, Xiao Chen, Qun Liu.NEZHA：面向汉语理解的神经语境表示. arXiv preprint arXiv:1909.00204. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/bertfinetuning_nersoftmax_cluener.md b/mshub_res/assets/mindspore/1.5/bertfinetuning_nersoftmax_cluener.md new file mode 100644 index 0000000..fecd977 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/bertfinetuning_nersoftmax_cluener.md @@ -0,0 +1,80 @@ +# bert + +--- + +model-name: bert + +backbone-name: bert + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cluener + +evaluation: acc93.75 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: e895a7e6d1d8d1aa3bb6c869136038416560714c30651801be6a93a4425aa4f3 + +license: Apache2.0 + +summary: bert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of bert from the MindSpore model zoo on Gitee at official/nlp/bert. + +bert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/bert](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/bert/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/bertfinetuning_nersoftmax_cluener" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova.BERT：深度双向Transformer语言理解预训练). arXiv preprint arXiv:1810.04805. +2. Junqiu Wei, Xiaozhe Ren, Xiaoguang Li, Wenyong Huang, Yi Liao, Yasheng Wang, Jiashu Lin, Xin Jiang, Xiao Chen, Qun Liu.NEZHA：面向汉语理解的神经语境表示. arXiv preprint arXiv:1909.00204. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/bertfinetuning_squad_squadv1.1.md b/mshub_res/assets/mindspore/1.5/bertfinetuning_squad_squadv1.1.md new file mode 100644 index 0000000..34bef32 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/bertfinetuning_squad_squadv1.1.md @@ -0,0 +1,80 @@ +# bert + +--- + +model-name: bert + +backbone-name: bert + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: squadv1.1 + +evaluation: F1score88.45 | exactmatch81 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 9e4e1a8e0cd905f9d7caf5d04fec1b0e94fcd210682f21c8bfbb354f3660bc97 + +license: Apache2.0 + +summary: bert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of bert from the MindSpore model zoo on Gitee at official/nlp/bert. + +bert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/bert](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/bert/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/bertfinetuning_squad_squadv1.1" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova.BERT：深度双向Transformer语言理解预训练). arXiv preprint arXiv:1810.04805. +2. Junqiu Wei, Xiaozhe Ren, Xiaoguang Li, Wenyong Huang, Yi Liao, Yasheng Wang, Jiashu Lin, Xin Jiang, Xiao Chen, Qun Liu.NEZHA：面向汉语理解的神经语境表示. arXiv preprint arXiv:1909.00204. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/bertlarge_cnnews128.md b/mshub_res/assets/mindspore/1.5/bertlarge_cnnews128.md new file mode 100644 index 0000000..f506507 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/bertlarge_cnnews128.md @@ -0,0 +1,75 @@ +# bert_thor + +--- + +model-name: bert_thor + +backbone-name: bert_thor + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cnnews128 + +evaluation: acc71.21 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 05ea53283419af7fb9358fccf99a8b5a47e2ed09a8592d9d4be62e1f1c0e77d5 + +license: Apache2.0 + +summary: bert_thor is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of bert_thor from the MindSpore model zoo on Gitee at official/nlp/bert_thor. + +bert_thor is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/bert_thor](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/bert_thor/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/bertlarge_cnnews128" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/bgcf_amazonbeauty.md b/mshub_res/assets/mindspore/1.5/bgcf_amazonbeauty.md new file mode 100644 index 0000000..277b101 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/bgcf_amazonbeauty.md @@ -0,0 +1,79 @@ +# bgcf + +--- + +model-name: bgcf + +backbone-name: bgcf + +module-type: gnn + +fine-tunable: True + +model-version: 1.5 + +train-dataset: amazonbeauty + +evaluation: recall20acc15.32 | ndcg20acc9.16 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 1ba27594e030d343d1c71cb5bc7ae6323d39c8d187226c88e9931d96ad786ba1 + +license: Apache2.0 + +summary: bgcf is used for gnn + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of bgcf from the MindSpore model zoo on Gitee at official/gnn/bgcf. + +bgcf is a gnn network. More details please refer to the MindSpore model zoo on Gitee at [official/gnn/bgcf](https://gitee.com/mindspore/models/blob/r1.5/official/gnn/bgcf/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/bgcf_amazonbeauty" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Sun J, Guo W, Zhang D, et al. A Framework for Recommending Accurate and Diverse Items Using Bayesian Graph Convolutional Neural Networks[C]//Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2020: 2030-2039. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/c3d_hmdb51.md b/mshub_res/assets/mindspore/1.5/c3d_hmdb51.md new file mode 100644 index 0000000..6f63690 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/c3d_hmdb51.md @@ -0,0 +1,62 @@ +# c3d + +--- + +model-name: c3d + +backbone-name: c3d + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: hmdb51 + +evaluation: top1acc49.67 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 76ca14dbd7c499255af90cee53f9df858632989a6deef1be0a56f63d319b9789 + +license: Apache2.0 + +summary: c3d is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of c3d from the MindSpore model zoo on Gitee at official/cv/c3d. + +c3d is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/c3d](https://gitee.com/mindspore/models/blob/r1.5/official/cv/c3d/README.md). + +All parameters in the module are trainable. + +## Citation + +Learning Spatiotemporal Features with 3D Convolutional Networks + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/centerface_widerface.md b/mshub_res/assets/mindspore/1.5/centerface_widerface.md new file mode 100644 index 0000000..1f8c8c1 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/centerface_widerface.md @@ -0,0 +1,79 @@ +# centerface + +--- + +model-name: centerface + +backbone-name: centerface + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: widerface + +evaluation: easy92.4 | medium91.7 | hard77.9 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 9e2809d1561c0450a0ef063cbacd7690f688931a8bce4fdc6579aa26237de908 + +license: Apache2.0 + +summary: centerface is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of centerface from the MindSpore model zoo on Gitee at official/cv/centerface. + +centerface is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/centerface](https://gitee.com/mindspore/models/blob/r1.5/official/cv/centerface/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/centerface_widerface" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +CenterFace: Joint Face Detection and Alignment Using Face as Point. Xu, Yuanyuan(Huaqiao University) and Yan, Wan(StarClouds) and Sun, Haixin(Xiamen University) and Yang, Genke(Shanghai Jiaotong University) and Luo, Jiliang(Huaqiao University) + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/centernet_coco2017.md b/mshub_res/assets/mindspore/1.5/centernet_coco2017.md new file mode 100644 index 0000000..8bb40a8 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/centernet_coco2017.md @@ -0,0 +1,79 @@ +# centernet + +--- + +model-name: centernet + +backbone-name: centernet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: mAP51.9 | AP50acc78.8 | AP75acc55.5 | medium44.5 | large63.9 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 9c6fbfe8d3e47807d63f3c59726201bff036ddcdbb011a73e6276a4364a4c041 + +license: Apache2.0 + +summary: centernet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of centernet from the MindSpore model zoo on Gitee at research/cv/centernet. + +centernet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/centernet](https://gitee.com/mindspore/models/blob/r1.5/research/cv/centernet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/centernet_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Objects as Points. 2019. Xingyi Zhou(UT Austin) and Dequan Wang(UC Berkeley) and Philipp Krahenbuhl(UT Austin) + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/centernetdet_coco2017.md b/mshub_res/assets/mindspore/1.5/centernetdet_coco2017.md new file mode 100644 index 0000000..e180fc3 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/centernetdet_coco2017.md @@ -0,0 +1,62 @@ +# centernet_det + +--- + +model-name: centernet_det + +backbone-name: centernet_det + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: mAP41.5 | AP50acc59.8 | AP75acc59.8 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 39ccffb7eae3cbcf2821fe093e3f48c9acde272669a7d9f90a2f08964514f4fd + +license: Apache2.0 + +summary: centernet_det is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of centernet_det from the MindSpore model zoo on Gitee at research/cv/centernet_det. + +centernet_det is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/centernet_det](https://gitee.com/mindspore/models/blob/r1.5/research/cv/centernet_det/README.md). + +All parameters in the module are trainable. + +## Citation + +Objects as Points. 2019. Xingyi Zhou(UT Austin) and Dequan Wang(UC Berkeley) and Philipp Krahenbuhl(UT Austin) + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/centernetresnet101_coco2017.md b/mshub_res/assets/mindspore/1.5/centernetresnet101_coco2017.md new file mode 100644 index 0000000..bddbe2a --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/centernetresnet101_coco2017.md @@ -0,0 +1,79 @@ +# centernet_resnet101 + +--- + +model-name: centernet_resnet101 + +backbone-name: centernet_resnet101 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: mAP33.9 | AP50acc52 | AP75acc36 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c8fe163020a1498f69b00317f6d6bd21a05dc47ddef3d36942a01aa575d92122 + +license: Apache2.0 + +summary: centernet_resnet101 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of centernet_resnet101 from the MindSpore model zoo on Gitee at research/cv/centernet_resnet101. + +centernet_resnet101 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/centernet_resnet101](https://gitee.com/mindspore/models/blob/r1.5/research/cv/centernet_resnet101/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/centernetresnet101_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Objects as Points. 2019. Xingyi Zhou(UT Austin) and Dequan Wang(UC Berkeley) and Philipp Krahenbuhl(UT Austin) + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/centernetresnet50v1_coco2017.md b/mshub_res/assets/mindspore/1.5/centernetresnet50v1_coco2017.md new file mode 100644 index 0000000..6315b6c --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/centernetresnet50v1_coco2017.md @@ -0,0 +1,62 @@ +# centernet_resnet50_v1 + +--- + +model-name: centernet_resnet50_v1 + +backbone-name: centernet_resnet50_v1 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: mAP30.8 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: a3bf9973d423847b59a2fc56d17e630650e95fb6862019c29b9a7bb92268c962 + +license: Apache2.0 + +summary: centernet_resnet50_v1 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of centernet_resnet50_v1 from the MindSpore model zoo on Gitee at research/cv/centernet_resnet50_v1. + +centernet_resnet50_v1 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/centernet_resnet50_v1](https://gitee.com/mindspore/models/blob/r1.5/research/cv/centernet_resnet50_v1/readme.md). + +All parameters in the module are trainable. + +## Citation + +Objects as Points. 2019. Xingyi Zhou(UT Austin) and Dequan Wang(UC Berkeley) and Philipp Krahenbuhl(UT Austin) + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/cgan_G_mnist.md b/mshub_res/assets/mindspore/1.5/cgan_G_mnist.md new file mode 100644 index 0000000..b524af3 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/cgan_G_mnist.md @@ -0,0 +1,62 @@ +# CGAN + +--- + +model-name: CGAN + +backbone-name: CGAN + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: mnist + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 360a455b190fc1a56cfb487ed25278794e86ea615458cf3066ca06e3b8ad3d41 + +license: Apache2.0 + +summary: CGAN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of CGAN from the MindSpore model zoo on Gitee at research/cv/CGAN. + +CGAN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/CGAN](https://gitee.com/mindspore/models/blob/r1.5/research/cv/CGAN/README.md). + +All parameters in the module are trainable. + +## Citation + +Conditional Generative Adversarial Nets. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/cnnctc_mjstiiit.md b/mshub_res/assets/mindspore/1.5/cnnctc_mjstiiit.md new file mode 100644 index 0000000..be2f8e8 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/cnnctc_mjstiiit.md @@ -0,0 +1,79 @@ +# cnnctc + +--- + +model-name: cnnctc + +backbone-name: cnnctc + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: mjstiiit + +evaluation: acc85.97 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 3468204da46492286ed466c9bab9572443b4e7d359396a5e38b42ceb3d0a6c6f + +license: Apache2.0 + +summary: cnnctc is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of cnnctc from the MindSpore model zoo on Gitee at official/cv/cnnctc. + +cnnctc is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/cnnctc](https://gitee.com/mindspore/models/blob/r1.5/official/cv/cnnctc/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/cnnctc_mjstiiit" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +J. Baek, G. Kim, J. Lee, S. Park, D. Han, S. Yun, S. J. Oh, and H. Lee, “What is wrong with scene text recognition model comparisons? dataset and model analysis,” ArXiv, vol. abs/1904.01906, 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/cnndirectionmodel_fsns.md b/mshub_res/assets/mindspore/1.5/cnndirectionmodel_fsns.md new file mode 100644 index 0000000..7cc667d --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/cnndirectionmodel_fsns.md @@ -0,0 +1,75 @@ +# cnn_direction_model + +--- + +model-name: cnn_direction_model + +backbone-name: cnn_direction_model + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: fsns + +evaluation: acc91 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 7dffb4205b94d111f5a0d60065cbd78912013645926c8960813ce4b1fe13725c + +license: Apache2.0 + +summary: cnn_direction_model is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of cnn_direction_model from the MindSpore model zoo on Gitee at official/cv/cnn_direction_model. + +cnn_direction_model is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/cnn_direction_model](https://gitee.com/mindspore/models/blob/r1.5/official/cv/cnn_direction_model/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/cnndirectionmodel_fsns" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/crnn_synth.md b/mshub_res/assets/mindspore/1.5/crnn_synth.md new file mode 100644 index 0000000..9e761be --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/crnn_synth.md @@ -0,0 +1,79 @@ +# crnn + +--- + +model-name: crnn + +backbone-name: crnn + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: synth + +evaluation: svtacc80.83 | iiit5kacc79.73 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 640dd154c7d4bbf93de2103f5e58e3595e0085d6fcd07731669666dc9d0745fd + +license: Apache2.0 + +summary: crnn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of crnn from the MindSpore model zoo on Gitee at official/cv/crnn. + +crnn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/crnn](https://gitee.com/mindspore/models/blob/r1.5/official/cv/crnn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/crnn_synth" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Baoguang Shi, Xiang Bai, Cong Yao, "An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition", ArXiv, vol. abs/1507.05717, 2015. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/crnnseq2seqocr_fsns.md b/mshub_res/assets/mindspore/1.5/crnnseq2seqocr_fsns.md new file mode 100644 index 0000000..4760084 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/crnnseq2seqocr_fsns.md @@ -0,0 +1,75 @@ +# crnn_seq2seq_ocr + +--- + +model-name: crnn_seq2seq_ocr + +backbone-name: crnn_seq2seq_ocr + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: fsns + +evaluation: annotationprecision74 | characterprecision96 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 2261862bb3757d491428eef42ec30a6898b6fc9b87ca43cf50522dfc55d8bd96 + +license: Apache2.0 + +summary: crnn_seq2seq_ocr is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of crnn_seq2seq_ocr from the MindSpore model zoo on Gitee at official/cv/crnn_seq2seq_ocr. + +crnn_seq2seq_ocr is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/crnn_seq2seq_ocr](https://gitee.com/mindspore/models/blob/r1.5/official/cv/crnn_seq2seq_ocr/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/crnnseq2seqocr_fsns" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/ctpn_icdar2013.md b/mshub_res/assets/mindspore/1.5/ctpn_icdar2013.md new file mode 100644 index 0000000..f5f28fa --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/ctpn_icdar2013.md @@ -0,0 +1,79 @@ +# ctpn + +--- + +model-name: ctpn + +backbone-name: ctpn + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: icdar2013 + +evaluation: precision90 | recall86 | Fmeasure88 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: a1cfaecc174c435683a889aef141e6edcb5b35535666f683c7f57d35c827565a + +license: Apache2.0 + +summary: ctpn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ctpn from the MindSpore model zoo on Gitee at official/cv/ctpn. + +ctpn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/ctpn](https://gitee.com/mindspore/models/blob/r1.5/official/cv/ctpn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/ctpn_icdar2013" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Zhi Tian, Weilin Huang, Tong He, Pan He, Yu Qiao, "Detecting Text in Natural Image with Connectionist Text Proposal Network", ArXiv, vol. abs/1609.03605, 2016. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/cyclegan_GA_apple2orange.md b/mshub_res/assets/mindspore/1.5/cyclegan_GA_apple2orange.md new file mode 100644 index 0000000..95ea644 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/cyclegan_GA_apple2orange.md @@ -0,0 +1,62 @@ +# CycleGAN + +--- + +model-name: CycleGAN + +backbone-name: CycleGAN + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: apple2orange + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 44bc99276b91d5113636c37a03e75d15daf6c836e6cc59be07507223f69f9a5d + +license: Apache2.0 + +summary: CycleGAN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of CycleGAN from the MindSpore model zoo on Gitee at research/cv/CycleGAN. + +CycleGAN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/CycleGAN](https://gitee.com/mindspore/models/blob/r1.5/research/cv/CycleGAN/README.md). + +All parameters in the module are trainable. + +## Citation + +Zhu J Y , Park T , Isola P , et al. Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks[J]. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/cyclegan_GA_horse2zebra.md b/mshub_res/assets/mindspore/1.5/cyclegan_GA_horse2zebra.md new file mode 100644 index 0000000..5e2224b --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/cyclegan_GA_horse2zebra.md @@ -0,0 +1,62 @@ +# CycleGAN + +--- + +model-name: CycleGAN + +backbone-name: CycleGAN + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: horse2zebra + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 36b004b573f32132802b4dab55b80e9acb56cd7b9f49ffa48e13032c9315b296 + +license: Apache2.0 + +summary: CycleGAN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of CycleGAN from the MindSpore model zoo on Gitee at research/cv/CycleGAN. + +CycleGAN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/CycleGAN](https://gitee.com/mindspore/models/blob/r1.5/research/cv/CycleGAN/README.md). + +All parameters in the module are trainable. + +## Citation + +Zhu J Y , Park T , Isola P , et al. Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks[J]. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/cyclegan_GB_apple2orange.md b/mshub_res/assets/mindspore/1.5/cyclegan_GB_apple2orange.md new file mode 100644 index 0000000..5c90345 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/cyclegan_GB_apple2orange.md @@ -0,0 +1,62 @@ +# CycleGAN + +--- + +model-name: CycleGAN + +backbone-name: CycleGAN + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: apple2orange + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: f10f714fd074dafdcdf0428d5d3c1e1e708cb7825a3105faf4b45ac905847b72 + +license: Apache2.0 + +summary: CycleGAN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of CycleGAN from the MindSpore model zoo on Gitee at research/cv/CycleGAN. + +CycleGAN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/CycleGAN](https://gitee.com/mindspore/models/blob/r1.5/research/cv/CycleGAN/README.md). + +All parameters in the module are trainable. + +## Citation + +Zhu J Y , Park T , Isola P , et al. Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks[J]. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/cyclegan_GB_horse2zebra.md b/mshub_res/assets/mindspore/1.5/cyclegan_GB_horse2zebra.md new file mode 100644 index 0000000..1708a88 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/cyclegan_GB_horse2zebra.md @@ -0,0 +1,62 @@ +# CycleGAN + +--- + +model-name: CycleGAN + +backbone-name: CycleGAN + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: horse2zebra + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 7e674623287672c6c221f9a7914429f60c02cd510ba662de36df6ed49ac035a5 + +license: Apache2.0 + +summary: CycleGAN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of CycleGAN from the MindSpore model zoo on Gitee at research/cv/CycleGAN. + +CycleGAN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/CycleGAN](https://gitee.com/mindspore/models/blob/r1.5/research/cv/CycleGAN/README.md). + +All parameters in the module are trainable. + +## Citation + +Zhu J Y , Park T , Isola P , et al. Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks[J]. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/deepfm_criteo.md b/mshub_res/assets/mindspore/1.5/deepfm_criteo.md new file mode 100644 index 0000000..0605368 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/deepfm_criteo.md @@ -0,0 +1,79 @@ +# deepfm + +--- + +model-name: deepfm + +backbone-name: deepfm + +module-type: recommend + +fine-tunable: True + +model-version: 1.5 + +train-dataset: criteo + +evaluation: acc80.5 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 57e11deb538dd32a8612ee655c14fe1438afe993ecd1a98c6ba6cf9e9c73e22d + +license: Apache2.0 + +summary: deepfm is used for recommend + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of deepfm from the MindSpore model zoo on Gitee at official/recommend/deepfm. + +deepfm is a recommend network. More details please refer to the MindSpore model zoo on Gitee at [official/recommend/deepfm](https://gitee.com/mindspore/models/blob/r1.5/official/recommend/deepfm/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/deepfm_criteo" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, Xiuqiang He. DeepFM: A Factorization-Machine based Neural Network for CTR Prediction + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/deeplabv3s16_voc2012.md b/mshub_res/assets/mindspore/1.5/deeplabv3s16_voc2012.md new file mode 100644 index 0000000..3cf0e89 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/deeplabv3s16_voc2012.md @@ -0,0 +1,79 @@ +# deeplabv3 + +--- + +model-name: deeplabv3 + +backbone-name: deeplabv3 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: voc2012 + +evaluation: acc78.68 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 46e997f97de3d6d4e35405be59bbb621c12d3ce62a688939f9046179473bfd9e + +license: Apache2.0 + +summary: deeplabv3 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of deeplabv3 from the MindSpore model zoo on Gitee at official/cv/deeplabv3. + +deeplabv3 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/deeplabv3](https://gitee.com/mindspore/models/blob/r1.5/official/cv/deeplabv3/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/deeplabv3s16_voc2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Chen L C, Papandreou G, Schroff F, et al. Rethinking atrous convolution for semantic image segmentation[J]. arXiv preprint arXiv:1706.05587, 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/deeplabv3s8r2_voc2012.md b/mshub_res/assets/mindspore/1.5/deeplabv3s8r2_voc2012.md new file mode 100644 index 0000000..0c60734 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/deeplabv3s8r2_voc2012.md @@ -0,0 +1,79 @@ +# deeplabv3 + +--- + +model-name: deeplabv3 + +backbone-name: deeplabv3 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: voc2012 + +evaluation: s8acc78.51 | ns8mul79.26 | ns8mulflip79.37 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: bb00c4455d1b1eaf91ed8c8f1e755b68cfdf8b2c0d5f8a32a611caaa5ae91b0d + +license: Apache2.0 + +summary: deeplabv3 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of deeplabv3 from the MindSpore model zoo on Gitee at official/cv/deeplabv3. + +deeplabv3 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/deeplabv3](https://gitee.com/mindspore/models/blob/r1.5/official/cv/deeplabv3/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/deeplabv3s8r2_voc2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Chen L C, Papandreou G, Schroff F, et al. Rethinking atrous convolution for semantic image segmentation[J]. arXiv preprint arXiv:1706.05587, 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/deeptext_icdar2013_scutforu_cocotextv2.md b/mshub_res/assets/mindspore/1.5/deeptext_icdar2013_scutforu_cocotextv2.md new file mode 100644 index 0000000..35ed674 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/deeptext_icdar2013_scutforu_cocotextv2.md @@ -0,0 +1,79 @@ +# deeptext + +--- + +model-name: deeptext + +backbone-name: deeptext + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: icdar2013_scutforu_cocotextv2 + +evaluation: F1score85 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 0ac5e5cbfd40ddcd16e30b7baa1904ac7ec20c5e3f8f8850aa20fac9baf03f37 + +license: Apache2.0 + +summary: deeptext is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of deeptext from the MindSpore model zoo on Gitee at official/cv/deeptext. + +deeptext is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/deeptext](https://gitee.com/mindspore/models/blob/r1.5/official/cv/deeptext/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/deeptext_icdar2013_scutforu_cocotextv2" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Zhuoyao Zhong, Lianwen Jin, Shuangping Huang, South China University of Technology (SCUT), Published in ICASSP 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/dem_att_cub.md b/mshub_res/assets/mindspore/1.5/dem_att_cub.md new file mode 100644 index 0000000..59b7f9f --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/dem_att_cub.md @@ -0,0 +1,79 @@ +# dem + +--- + +model-name: dem + +backbone-name: dem + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cub + +evaluation: acc59.63 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: b355ea64eabc6f4ba8462c952a8973885dcbb06623879a921f11b3e9d14ff474 + +license: Apache2.0 + +summary: dem is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of dem from the MindSpore model zoo on Gitee at research/cv/dem. + +dem is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/dem](https://gitee.com/mindspore/models/blob/r1.5/research/cv/dem/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/dem_att_cub" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Li Zhang, Tao Xiang, Shaogang Gong."Learning a Deep Embedding Model for Zero-Shot Learning" *Proceedings of the CVPR*.2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/densenet121_imagenet2012.md b/mshub_res/assets/mindspore/1.5/densenet121_imagenet2012.md new file mode 100644 index 0000000..1e2cec0 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/densenet121_imagenet2012.md @@ -0,0 +1,79 @@ +# densenet + +--- + +model-name: densenet + +backbone-name: densenet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc75.54 | top5acc92.73 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 032146e64d981fcc6c08925adcb348e50a3b6b8f653226b5147ef76560d4367a + +license: Apache2.0 + +summary: densenet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of densenet from the MindSpore model zoo on Gitee at official/cv/densenet. + +densenet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/densenet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/densenet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/densenet121_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Densely Connected Convolutional Networks + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/dgcn_citeseer.md b/mshub_res/assets/mindspore/1.5/dgcn_citeseer.md new file mode 100644 index 0000000..bb3c059 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/dgcn_citeseer.md @@ -0,0 +1,62 @@ +# dgcn + +--- + +model-name: dgcn + +backbone-name: dgcn + +module-type: gnn + +fine-tunable: True + +model-version: 1.5 + +train-dataset: citeseer + +evaluation: acc72.2 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 773432ed4ccfcf8945cfee10c5c7c72d209820efb523565459594445237aa953 + +license: Apache2.0 + +summary: dgcn is used for gnn + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of dgcn from the MindSpore model zoo on Gitee at research/gnn/dgcn. + +dgcn is a gnn network. More details please refer to the MindSpore model zoo on Gitee at [research/gnn/dgcn](https://gitee.com/mindspore/models/blob/r1.5/research/gnn/dgcn/readme_CN.md). + +All parameters in the module are trainable. + +## Citation + +Dual Graph Convolutional Networks for Graph-Based Semi-Supervised Classification[C]// the 2018 World Wide Web Conference. 2018. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/dgcn_cora.md b/mshub_res/assets/mindspore/1.5/dgcn_cora.md new file mode 100644 index 0000000..219451d --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/dgcn_cora.md @@ -0,0 +1,62 @@ +# dgcn + +--- + +model-name: dgcn + +backbone-name: dgcn + +module-type: gnn + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cora + +evaluation: acc82.8 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: a1b1bfb3d76afdcb4a19751db7ecb246c9fb736bca08b1231bf681d10a2cf368 + +license: Apache2.0 + +summary: dgcn is used for gnn + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of dgcn from the MindSpore model zoo on Gitee at research/gnn/dgcn. + +dgcn is a gnn network. More details please refer to the MindSpore model zoo on Gitee at [research/gnn/dgcn](https://gitee.com/mindspore/models/blob/r1.5/research/gnn/dgcn/readme_CN.md). + +All parameters in the module are trainable. + +## Citation + +Dual Graph Convolutional Networks for Graph-Based Semi-Supervised Classification[C]// the 2018 World Wide Web Conference. 2018. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/dgcn_pubmed.md b/mshub_res/assets/mindspore/1.5/dgcn_pubmed.md new file mode 100644 index 0000000..bdc6b89 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/dgcn_pubmed.md @@ -0,0 +1,62 @@ +# dgcn + +--- + +model-name: dgcn + +backbone-name: dgcn + +module-type: gnn + +fine-tunable: True + +model-version: 1.5 + +train-dataset: pubmed + +evaluation: acc80.3 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 76ea88b1ab45abbea81c99a6ae0eb5bb64da64f5bba04dbc5ae1a5c87e7de3fd + +license: Apache2.0 + +summary: dgcn is used for gnn + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of dgcn from the MindSpore model zoo on Gitee at research/gnn/dgcn. + +dgcn is a gnn network. More details please refer to the MindSpore model zoo on Gitee at [research/gnn/dgcn](https://gitee.com/mindspore/models/blob/r1.5/research/gnn/dgcn/readme_CN.md). + +All parameters in the module are trainable. + +## Citation + +Dual Graph Convolutional Networks for Graph-Based Semi-Supervised Classification[C]// the 2018 World Wide Web Conference. 2018. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/dgu_udc.md b/mshub_res/assets/mindspore/1.5/dgu_udc.md new file mode 100644 index 0000000..1f2cbe9 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/dgu_udc.md @@ -0,0 +1,58 @@ +# dgu + +--- + +model-name: dgu + +backbone-name: dgu + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: udc + +evaluation: R1acc82.14 | R2acc90.45 | R5acc97.75 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: ef323d57071720e70df35c28d0d8cffcfafdefdfe694ca4c39b21d013f2b8542 + +license: Apache2.0 + +summary: dgu is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of dgu from the MindSpore model zoo on Gitee at official/nlp/dgu. + +dgu is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/dgu](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/dgu/README_CN.md). + +All parameters in the module are trainable. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/dncnn_bsd500.md b/mshub_res/assets/mindspore/1.5/dncnn_bsd500.md new file mode 100644 index 0000000..fd29ccf --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/dncnn_bsd500.md @@ -0,0 +1,62 @@ +# DnCNN + +--- + +model-name: DnCNN + +backbone-name: DnCNN + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: bsd500 + +evaluation: bsd68acc29 | set12acc30 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: e02c3010a0e6f8b5750e5de1fb5c12fa98ab932133cb1dbb62dfdd77f69607cd + +license: Apache2.0 + +summary: DnCNN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of DnCNN from the MindSpore model zoo on Gitee at research/cv/DnCNN. + +DnCNN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/DnCNN](https://gitee.com/mindspore/models/blob/r1.5/research/cv/DnCNN/README.md). + +All parameters in the module are trainable. + +## Citation + +K. Zhang, W. Zuo, Y. Chen, D. Meng and L. Zhang, "Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising," in IEEE Transactions on Image Processing, vol. 26, no. 7, pp. 3142-3155, July 2017, doi: 10.1109/TIP.2017.2662206. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/dpn_imagenet2012.md b/mshub_res/assets/mindspore/1.5/dpn_imagenet2012.md new file mode 100644 index 0000000..929ac37 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/dpn_imagenet2012.md @@ -0,0 +1,79 @@ +# dpn + +--- + +model-name: dpn + +backbone-name: dpn + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc78.81 | top5acc94.34 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 3fa441570f3a6ca0b8cc03dc4205bd881dafad4d8780daf153beec501947b9b2 + +license: Apache2.0 + +summary: dpn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of dpn from the MindSpore model zoo on Gitee at official/cv/dpn. + +dpn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/dpn](https://gitee.com/mindspore/models/blob/r1.5/official/cv/dpn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/dpn_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Yunpeng Chen, Jianan Li, Huaxin Xiao, Xiaojie Jin, Shuicheng Yan, Jiashi Feng. "Dual Path Networks" (NIPS17). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/east_icdar2015.md b/mshub_res/assets/mindspore/1.5/east_icdar2015.md new file mode 100644 index 0000000..6fa21c6 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/east_icdar2015.md @@ -0,0 +1,62 @@ +# east + +--- + +model-name: east + +backbone-name: east + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: icdar2015 + +evaluation: acc81 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 4fa8a1a81a9d49db853cb483b2763e06219726158a8db96dcccbcd36d5d9ee52 + +license: Apache2.0 + +summary: east is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of east from the MindSpore model zoo on Gitee at official/cv/east. + +east is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/east](https://gitee.com/mindspore/models/blob/r1.5/official/cv/east/README.md). + +All parameters in the module are trainable. + +## Citation + +Xinyu Zhou, Cong Yao, He Wen, Yuzhi Wang, Shuchang Zhou, Weiran He, and Jiajun Liang Megvii Technology Inc., Beijing, China, Published in CVPR 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/efficientnetb0_imagenet2012.md b/mshub_res/assets/mindspore/1.5/efficientnetb0_imagenet2012.md new file mode 100644 index 0000000..462e31d --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/efficientnetb0_imagenet2012.md @@ -0,0 +1,62 @@ +# efficientnet-b0 + +--- + +model-name: efficientnet-b0 + +backbone-name: efficientnet-b0 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc76 | top5acc93 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 729e24f509546b149120624ed7577274ba9ed26ba06d1a88e11989ac1c9df344 + +license: Apache2.0 + +summary: efficientnet-b0 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of efficientnet-b0 from the MindSpore model zoo on Gitee at research/cv/efficientnet-b0. + +efficientnet-b0 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/efficientnet-b0](https://gitee.com/mindspore/models/blob/r1.5/research/cv/efficientnet-b0/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Mingxing Tan, Quoc V. Le. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/efficientnetb2_imagenet2012.md b/mshub_res/assets/mindspore/1.5/efficientnetb2_imagenet2012.md new file mode 100644 index 0000000..2dcee79 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/efficientnetb2_imagenet2012.md @@ -0,0 +1,62 @@ +# efficientnet-b2 + +--- + +model-name: efficientnet-b2 + +backbone-name: efficientnet-b2 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc79 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 55799d18a7c55199bc733257d548bbe9ed6341278f9c0af7dc88edc22ee9d386 + +license: Apache2.0 + +summary: efficientnet-b2 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of efficientnet-b2 from the MindSpore model zoo on Gitee at research/cv/efficientnet-b2. + +efficientnet-b2 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/efficientnet-b2](https://gitee.com/mindspore/models/blob/r1.5/research/cv/efficientnet-b2/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Mingxing Tan, Quoc V. Le. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/efficientnetb3_imagenet2012.md b/mshub_res/assets/mindspore/1.5/efficientnetb3_imagenet2012.md new file mode 100644 index 0000000..622cd94 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/efficientnetb3_imagenet2012.md @@ -0,0 +1,62 @@ +# efficientnet-b3 + +--- + +model-name: efficientnet-b3 + +backbone-name: efficientnet-b3 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc80 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 1409576e02e431ab6b71e1f96c3aa56ebb8b87a1f6d3fd96a1973c64b917c0b9 + +license: Apache2.0 + +summary: efficientnet-b3 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of efficientnet-b3 from the MindSpore model zoo on Gitee at research/cv/efficientnet-b3. + +efficientnet-b3 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/efficientnet-b3](https://gitee.com/mindspore/models/blob/r1.5/research/cv/efficientnet-b3/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Mingxing Tan, Quoc V. Le. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/emotect_baidu.md b/mshub_res/assets/mindspore/1.5/emotect_baidu.md new file mode 100644 index 0000000..9d08c4b --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/emotect_baidu.md @@ -0,0 +1,58 @@ +# emotect + +--- + +model-name: emotect + +backbone-name: emotect + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: baidu + +evaluation: acc90.44 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5b0ddb04f17f27d706007353d15faf93b627dcaf0ce7fcfcf1b61d4f2ddc228b + +license: Apache2.0 + +summary: emotect is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of emotect from the MindSpore model zoo on Gitee at official/nlp/emotect. + +emotect is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/emotect](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/emotect/README_CN.md). + +All parameters in the module are trainable. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/faceattribute_fairface_rwmfd.md b/mshub_res/assets/mindspore/1.5/faceattribute_fairface_rwmfd.md new file mode 100644 index 0000000..7a19f49 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/faceattribute_fairface_rwmfd.md @@ -0,0 +1,62 @@ +# FaceAttribute + +--- + +model-name: FaceAttribute + +backbone-name: FaceAttribute + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: fairface_rwmfd + +evaluation: age49 | gender90 | mask99 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 6301d259829abf1fc2fcd1cf537b411ff6ab4aaf31fa9abf0d0160b7f08bde3c + +license: Apache2.0 + +summary: FaceAttribute is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of FaceAttribute from the MindSpore model zoo on Gitee at research/cv/FaceAttribute. + +FaceAttribute is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/FaceAttribute](https://gitee.com/mindspore/models/blob/r1.5/research/cv/FaceAttribute/README.md). + +All parameters in the module are trainable. + +## Citation + +Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. "Deep Residual Learning for Image Recognition" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/facedetection_widerface.md b/mshub_res/assets/mindspore/1.5/facedetection_widerface.md new file mode 100644 index 0000000..255d318 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/facedetection_widerface.md @@ -0,0 +1,79 @@ +# FaceDetection + +--- + +model-name: FaceDetection + +backbone-name: FaceDetection + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: widerface + +evaluation: mAP75 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: ce9c845efe2145a71dcadca8e5f7721f2edd27b0560f186f16c34d22001923d5 + +license: Apache2.0 + +summary: FaceDetection is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of FaceDetection from the MindSpore model zoo on Gitee at research/cv/FaceDetection. + +FaceDetection is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/FaceDetection](https://gitee.com/mindspore/models/blob/r1.5/research/cv/FaceDetection/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/facedetection_widerface" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +YOLOv3: An Incremental Improvement. Joseph Redmon, Ali Farhadi, University of Washington + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/facequalityassessment_300wlp.md b/mshub_res/assets/mindspore/1.5/facequalityassessment_300wlp.md new file mode 100644 index 0000000..3457ad2 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/facequalityassessment_300wlp.md @@ -0,0 +1,79 @@ +# FaceQualityAssessment + +--- + +model-name: FaceQualityAssessment + +backbone-name: FaceQualityAssessment + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: 300wlp + +evaluation: IPN19 | MAE18 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 07e44357d9a9a2b30677479e6bfce8a867d8333a16a20f22eca6e08d9f35a4c6 + +license: Apache2.0 + +summary: FaceQualityAssessment is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of FaceQualityAssessment from the MindSpore model zoo on Gitee at research/cv/FaceQualityAssessment. + +FaceQualityAssessment is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/FaceQualityAssessment](https://gitee.com/mindspore/models/blob/r1.5/research/cv/FaceQualityAssessment/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/facequalityassessment_300wlp" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. "Deep Residual Learning for Image Recognition" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/facerecognition_ms1mv2.md b/mshub_res/assets/mindspore/1.5/facerecognition_ms1mv2.md new file mode 100644 index 0000000..b887c84 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/facerecognition_ms1mv2.md @@ -0,0 +1,79 @@ +# FaceRecognition + +--- + +model-name: FaceRecognition + +backbone-name: FaceRecognition + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: ms1mv2 + +evaluation: acc90 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: fcbaed741e5f4e3360d058afcee3276455a958f06a84f3cfc96445d88f6f236a + +license: Apache2.0 + +summary: FaceRecognition is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of FaceRecognition from the MindSpore model zoo on Gitee at research/cv/FaceRecognition. + +FaceRecognition is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/FaceRecognition](https://gitee.com/mindspore/models/blob/r1.5/research/cv/FaceRecognition/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/facerecognition_ms1mv2" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. "Deep Residual Learning for Image Recognition" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/facerecognitionfortracking_lfw.md b/mshub_res/assets/mindspore/1.5/facerecognitionfortracking_lfw.md new file mode 100644 index 0000000..0e7e6a7 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/facerecognitionfortracking_lfw.md @@ -0,0 +1,79 @@ +# FaceRecognitionForTracking + +--- + +model-name: FaceRecognitionForTracking + +backbone-name: FaceRecognitionForTracking + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: lfw + +evaluation: FAR0.1recall62 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: e1ff7aab52774fea4d997b7afb83de5ec3a9aef5f49657111df8d3220c69cf05 + +license: Apache2.0 + +summary: FaceRecognitionForTracking is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of FaceRecognitionForTracking from the MindSpore model zoo on Gitee at research/cv/FaceRecognitionForTracking. + +FaceRecognitionForTracking is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/FaceRecognitionForTracking](https://gitee.com/mindspore/models/blob/r1.5/research/cv/FaceRecognitionForTracking/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/facerecognitionfortracking_lfw" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. "Deep Residual Learning for Image Recognition" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/fasterrcnnresnetv1101_coco2017.md b/mshub_res/assets/mindspore/1.5/fasterrcnnresnetv1101_coco2017.md new file mode 100644 index 0000000..36f5602 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/fasterrcnnresnetv1101_coco2017.md @@ -0,0 +1,79 @@ +# faster_rcnn + +--- + +model-name: faster_rcnn + +backbone-name: faster_rcnn + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: mAP40.2 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: bda0ddecfca47b953c2bc701ecc58846b0883d8218fa12f5ea484e6f8f7299d9 + +license: Apache2.0 + +summary: faster_rcnn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of faster_rcnn from the MindSpore model zoo on Gitee at official/cv/faster_rcnn. + +faster_rcnn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/faster_rcnn](https://gitee.com/mindspore/models/blob/r1.5/official/cv/faster_rcnn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/fasterrcnnresnetv1101_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Ren S , He K , Girshick R , et al. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 39(6). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/fasterrcnnresnetv1152_coco2017.md b/mshub_res/assets/mindspore/1.5/fasterrcnnresnetv1152_coco2017.md new file mode 100644 index 0000000..f688bf1 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/fasterrcnnresnetv1152_coco2017.md @@ -0,0 +1,79 @@ +# faster_rcnn + +--- + +model-name: faster_rcnn + +backbone-name: faster_rcnn + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: mAP41.1 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 8bdce4abb45407ae395369a8cb0c2c1e78694d136e5e7f6332a604ff7c2d8007 + +license: Apache2.0 + +summary: faster_rcnn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of faster_rcnn from the MindSpore model zoo on Gitee at official/cv/faster_rcnn. + +faster_rcnn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/faster_rcnn](https://gitee.com/mindspore/models/blob/r1.5/official/cv/faster_rcnn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/fasterrcnnresnetv1152_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Ren S , He K , Girshick R , et al. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 39(6). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/fasterrcnnresnetv150_coco2017.md b/mshub_res/assets/mindspore/1.5/fasterrcnnresnetv150_coco2017.md new file mode 100644 index 0000000..6160745 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/fasterrcnnresnetv150_coco2017.md @@ -0,0 +1,79 @@ +# faster_rcnn + +--- + +model-name: faster_rcnn + +backbone-name: faster_rcnn + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: mAP@.5IoU60.6 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: f8efcd9fe8900ee6b6cd9bab1c7b6f650c290e8d70a3557e619404fd828dfa9f + +license: Apache2.0 + +summary: faster_rcnn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of faster_rcnn from the MindSpore model zoo on Gitee at official/cv/faster_rcnn. + +faster_rcnn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/faster_rcnn](https://gitee.com/mindspore/models/blob/r1.5/official/cv/faster_rcnn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/fasterrcnnresnetv150_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Ren S , He K , Girshick R , et al. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 39(6). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/fastscnn_cityspaces.md b/mshub_res/assets/mindspore/1.5/fastscnn_cityspaces.md new file mode 100644 index 0000000..c8722c2 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/fastscnn_cityspaces.md @@ -0,0 +1,62 @@ +# fastscnn + +--- + +model-name: fastscnn + +backbone-name: fastscnn + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cityspaces + +evaluation: acc54 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 74f4e5fb01d4ae9384fa9cd5da5f92fbc804cade3c8d0df608f41998af0e1889 + +license: Apache2.0 + +summary: fastscnn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of fastscnn from the MindSpore model zoo on Gitee at official/cv/fastscnn. + +fastscnn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/fastscnn](https://gitee.com/mindspore/models/blob/r1.5/official/cv/fastscnn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Poudel R , Liwicki S , Cipolla R . Fast-SCNN: Fast Semantic Segmentation Network[J]. 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/fasttext_agnews.md b/mshub_res/assets/mindspore/1.5/fasttext_agnews.md new file mode 100644 index 0000000..81ec806 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/fasttext_agnews.md @@ -0,0 +1,79 @@ +# fasttext + +--- + +model-name: fasttext + +backbone-name: fasttext + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: agnews + +evaluation: acc92.58 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 067f30b7b6cd19bb8a79601f1da365a1189881a3050f82d610b4f107c4d75d97 + +license: Apache2.0 + +summary: fasttext is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of fasttext from the MindSpore model zoo on Gitee at official/nlp/fasttext. + +fasttext is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/fasttext](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/fasttext/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/fasttext_agnews" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +"Bag of Tricks for Efficient Text Classification", 2016, A. Joulin, E. Grave, P. Bojanowski, and T. Mikolov + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/fasttext_dbpedia.md b/mshub_res/assets/mindspore/1.5/fasttext_dbpedia.md new file mode 100644 index 0000000..e29f030 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/fasttext_dbpedia.md @@ -0,0 +1,79 @@ +# fasttext + +--- + +model-name: fasttext + +backbone-name: fasttext + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: dbpedia + +evaluation: acc98.62 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 3798190b1dbb78c4e76baac2b1228bab6c0e5ba5dfdede664fab47abc02d0b1e + +license: Apache2.0 + +summary: fasttext is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of fasttext from the MindSpore model zoo on Gitee at official/nlp/fasttext. + +fasttext is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/fasttext](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/fasttext/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/fasttext_dbpedia" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +"Bag of Tricks for Efficient Text Classification", 2016, A. Joulin, E. Grave, P. Bojanowski, and T. Mikolov + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/fasttext_yelp.md b/mshub_res/assets/mindspore/1.5/fasttext_yelp.md new file mode 100644 index 0000000..35254c2 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/fasttext_yelp.md @@ -0,0 +1,79 @@ +# fasttext + +--- + +model-name: fasttext + +backbone-name: fasttext + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: yelp + +evaluation: acc95.86 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c6156d218c0e9ee484c273558e709c6f733528b0a14fdefdde1117db4dfe35c0 + +license: Apache2.0 + +summary: fasttext is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of fasttext from the MindSpore model zoo on Gitee at official/nlp/fasttext. + +fasttext is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/fasttext](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/fasttext/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/fasttext_yelp" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +"Bag of Tricks for Efficient Text Classification", 2016, A. Joulin, E. Grave, P. Bojanowski, and T. Mikolov + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/fatdeepffm_criteo.md b/mshub_res/assets/mindspore/1.5/fatdeepffm_criteo.md new file mode 100644 index 0000000..ee4ae17 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/fatdeepffm_criteo.md @@ -0,0 +1,62 @@ +# Fat-DeepFFM + +--- + +model-name: Fat-DeepFFM + +backbone-name: Fat-DeepFFM + +module-type: recommend + +fine-tunable: True + +model-version: 1.5 + +train-dataset: criteo + +evaluation: acc80.91 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c347768ae3632983113fdf0583aa766db4300cd9abd9653699d135bfcd8dc938 + +license: Apache2.0 + +summary: Fat-DeepFFM is used for recommend + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of Fat-DeepFFM from the MindSpore model zoo on Gitee at research/recommend/Fat-DeepFFM. + +Fat-DeepFFM is a recommend network. More details please refer to the MindSpore model zoo on Gitee at [research/recommend/Fat-DeepFFM](https://gitee.com/mindspore/models/blob/r1.5/research/recommend/Fat-DeepFFM/README.md). + +All parameters in the module are trainable. + +## Citation + +Junlin Zhang , Tongwen Huang , Zhiqi Zhang FAT-DeepFFM: Field Attentive Deep Field-aware Factorization Machine + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/fcn4_musictagging.md b/mshub_res/assets/mindspore/1.5/fcn4_musictagging.md new file mode 100644 index 0000000..212bda4 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/fcn4_musictagging.md @@ -0,0 +1,79 @@ +# fcn-4 + +--- + +model-name: fcn-4 + +backbone-name: fcn-4 + +module-type: audio + +fine-tunable: True + +model-version: 1.5 + +train-dataset: musictagging + +evaluation: acc90.89 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: bdb7116d2dc25ae80381a882b9d8a75f857e53a920561015e3a9245cf469d284 + +license: Apache2.0 + +summary: fcn-4 is used for audio + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of fcn-4 from the MindSpore model zoo on Gitee at research/audio/fcn-4. + +fcn-4 is a audio network. More details please refer to the MindSpore model zoo on Gitee at [research/audio/fcn-4](https://gitee.com/mindspore/models/blob/r1.5/research/audio/fcn-4/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/fcn4_musictagging" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +"Keunwoo Choi, George Fazekas, and Mark Sandler, “Automatic tagging using deep convolutional neural networks,” in International Society of Music Information Retrieval Conference. ISMIR, 2016." + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/fcn8s_voc2012.md b/mshub_res/assets/mindspore/1.5/fcn8s_voc2012.md new file mode 100644 index 0000000..ff0dd46 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/fcn8s_voc2012.md @@ -0,0 +1,79 @@ +# FCN8s + +--- + +model-name: FCN8s + +backbone-name: FCN8s + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: voc2012 + +evaluation: meanIoU64.57 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: e941446770369cad03e60a4154c3a6dc8e8ab20c19fa37ce2bd6f59fb9b97663 + +license: Apache2.0 + +summary: FCN8s is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of FCN8s from the MindSpore model zoo on Gitee at official/cv/FCN8s. + +FCN8s is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/FCN8s](https://gitee.com/mindspore/models/blob/r1.5/official/cv/FCN8s/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/fcn8s_voc2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Long, Jonathan, Evan Shelhamer, and Trevor Darrell. "Fully convolutional networks for semantic segmentation." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/fishnet99_imagenet2012.md b/mshub_res/assets/mindspore/1.5/fishnet99_imagenet2012.md new file mode 100644 index 0000000..1c645f0 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/fishnet99_imagenet2012.md @@ -0,0 +1,62 @@ +# fishnet99 + +--- + +model-name: fishnet99 + +backbone-name: fishnet99 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc77.88 | top5acc93.88 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 95e536ca3b4b1f1fa9061b5f9cf75bdc15fb2a1fc8e1a820442516c980ebf7d3 + +license: Apache2.0 + +summary: fishnet99 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of fishnet99 from the MindSpore model zoo on Gitee at research/cv/fishnet99. + +fishnet99 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/fishnet99](https://gitee.com/mindspore/models/blob/r1.5/research/cv/fishnet99/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +FishNet: a versatile backbone for image, region, and pixel level prediction. In Proceedings of the 32nd International Conference on Neural Information Processing Systems (NIPS'18). Curran Associates Inc., Red Hook, NY, USA, 762–772. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/gan_G_mnist.md b/mshub_res/assets/mindspore/1.5/gan_G_mnist.md new file mode 100644 index 0000000..3a03126 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/gan_G_mnist.md @@ -0,0 +1,62 @@ +# gan + +--- + +model-name: gan + +backbone-name: gan + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: mnist + +evaluation: likelihood220.47 | se2.33 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 78dd2421ad81e2088cbb43ee11a019eb3ac74c27e1e75fff597cb3f659840c6b + +license: Apache2.0 + +summary: gan is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of gan from the MindSpore model zoo on Gitee at research/cv/gan. + +gan is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/gan](https://gitee.com/mindspore/models/blob/r1.5/research/cv/gan/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Goodfellow I, Pouget-Abadie J, Mirza M, et al. Generative adversarial nets[J]. Advances in neural information processing systems, 2014, 27. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/gat_citeseer.md b/mshub_res/assets/mindspore/1.5/gat_citeseer.md new file mode 100644 index 0000000..9ea4c01 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/gat_citeseer.md @@ -0,0 +1,79 @@ +# gat + +--- + +model-name: gat + +backbone-name: gat + +module-type: gnn + +fine-tunable: True + +model-version: 1.5 + +train-dataset: citeseer + +evaluation: acc72.4 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 19500c505053c4c7491d303f729bbc8d757fb44993b9c1fdfa97d1551ff4f1e4 + +license: Apache2.0 + +summary: gat is used for gnn + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of gat from the MindSpore model zoo on Gitee at official/gnn/gat. + +gat is a gnn network. More details please refer to the MindSpore model zoo on Gitee at [official/gnn/gat](https://gitee.com/mindspore/models/blob/r1.5/official/gnn/gat/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/gat_citeseer" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Veličković, P., Cucurull, G., Casanova, A., Romero, A., Lio, P., & Bengio, Y. (2017).Graph attention networks. arXiv preprint arXiv:1710.10903. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/gat_cora.md b/mshub_res/assets/mindspore/1.5/gat_cora.md new file mode 100644 index 0000000..ca80edd --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/gat_cora.md @@ -0,0 +1,79 @@ +# gat + +--- + +model-name: gat + +backbone-name: gat + +module-type: gnn + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cora + +evaluation: acc83.3 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 366b1211c0cbd2e101b7ae5ab1969dd0bc1f09d41a2b646c0c56f3e50b3627c3 + +license: Apache2.0 + +summary: gat is used for gnn + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of gat from the MindSpore model zoo on Gitee at official/gnn/gat. + +gat is a gnn network. More details please refer to the MindSpore model zoo on Gitee at [official/gnn/gat](https://gitee.com/mindspore/models/blob/r1.5/official/gnn/gat/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/gat_cora" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Veličković, P., Cucurull, G., Casanova, A., Romero, A., Lio, P., & Bengio, Y. (2017).Graph attention networks. arXiv preprint arXiv:1710.10903. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/gcn_citesser.md b/mshub_res/assets/mindspore/1.5/gcn_citesser.md new file mode 100644 index 0000000..824dc7d --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/gcn_citesser.md @@ -0,0 +1,79 @@ +# gcn + +--- + +model-name: gcn + +backbone-name: gcn + +module-type: gnn + +fine-tunable: True + +model-version: 1.5 + +train-dataset: citesser + +evaluation: acc71.9 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 00cc8132de8f255591564040dbd655fc23e5826e0f6e350bd4e20ec85e910bf3 + +license: Apache2.0 + +summary: gcn is used for gnn + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of gcn from the MindSpore model zoo on Gitee at official/gnn/gcn. + +gcn is a gnn network. More details please refer to the MindSpore model zoo on Gitee at [official/gnn/gcn](https://gitee.com/mindspore/models/blob/r1.5/official/gnn/gcn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/gcn_citesser" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Thomas N. Kipf, Max Welling. 2016. Semi-Supervised Classification with Graph Convolutional Networks. In ICLR 2016. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/gcn_cora.md b/mshub_res/assets/mindspore/1.5/gcn_cora.md new file mode 100644 index 0000000..aa29b06 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/gcn_cora.md @@ -0,0 +1,79 @@ +# gcn + +--- + +model-name: gcn + +backbone-name: gcn + +module-type: gnn + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cora + +evaluation: acc82.7 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5bf8a58e7129d0191c4e6c16d3eb346b6eb8885d5b7754b88fb8e959c9ae9876 + +license: Apache2.0 + +summary: gcn is used for gnn + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of gcn from the MindSpore model zoo on Gitee at official/gnn/gcn. + +gcn is a gnn network. More details please refer to the MindSpore model zoo on Gitee at [official/gnn/gcn](https://gitee.com/mindspore/models/blob/r1.5/official/gnn/gcn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/gcn_cora" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Thomas N. Kipf, Max Welling. 2016. Semi-Supervised Classification with Graph Convolutional Networks. In ICLR 2016. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/genetres50_minux_imagenet2012.md b/mshub_res/assets/mindspore/1.5/genetres50_minux_imagenet2012.md new file mode 100644 index 0000000..2bb342b --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/genetres50_minux_imagenet2012.md @@ -0,0 +1,62 @@ +# GENet_Res50 + +--- + +model-name: GENet_Res50 + +backbone-name: GENet_Res50 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc77.75 | top5acc93.64 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 6b568bebdf808db1bdfd9d013bd45ecd132f5788275d4bd0a4b30884165015bd + +license: Apache2.0 + +summary: GENet_Res50 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of GENet_Res50 from the MindSpore model zoo on Gitee at research/cv/GENet_Res50. + +GENet_Res50 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/GENet_Res50](https://gitee.com/mindspore/models/blob/r1.5/research/cv/GENet_Res50/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/genetres50_plus_imagenet2012.md b/mshub_res/assets/mindspore/1.5/genetres50_plus_imagenet2012.md new file mode 100644 index 0000000..1768939 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/genetres50_plus_imagenet2012.md @@ -0,0 +1,62 @@ +# GENet_Res50 + +--- + +model-name: GENet_Res50 + +backbone-name: GENet_Res50 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc78.4 | top5acc94.14 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 407565a9b390e6daded58219afccc2352ecde06ce4dc4a4b89e3b9ae95030e53 + +license: Apache2.0 + +summary: GENet_Res50 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of GENet_Res50 from the MindSpore model zoo on Gitee at research/cv/GENet_Res50. + +GENet_Res50 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/GENet_Res50](https://gitee.com/mindspore/models/blob/r1.5/research/cv/GENet_Res50/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/genetres50_theta_imagenet2012.md b/mshub_res/assets/mindspore/1.5/genetres50_theta_imagenet2012.md new file mode 100644 index 0000000..feb6ac5 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/genetres50_theta_imagenet2012.md @@ -0,0 +1,62 @@ +# GENet_Res50 + +--- + +model-name: GENet_Res50 + +backbone-name: GENet_Res50 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc78.07 | top5acc93.93 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 44826193cafce1e97018e6b77712ecd077e2d5af4a03b2f3034b9772be80563d + +license: Apache2.0 + +summary: GENet_Res50 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of GENet_Res50 from the MindSpore model zoo on Gitee at research/cv/GENet_Res50. + +GENet_Res50 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/GENet_Res50](https://gitee.com/mindspore/models/blob/r1.5/research/cv/GENet_Res50/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/ghostnet_imagenet2012.md b/mshub_res/assets/mindspore/1.5/ghostnet_imagenet2012.md new file mode 100644 index 0000000..8b2ac7c --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/ghostnet_imagenet2012.md @@ -0,0 +1,62 @@ +# ghostnet + +--- + +model-name: ghostnet + +backbone-name: ghostnet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc73.81 | top5acc91.77 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 612f2fee612654057734283a50ff9eb9c967ee838c1b2f3b9b555e1689f53851 + +license: Apache2.0 + +summary: ghostnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ghostnet from the MindSpore model zoo on Gitee at research/cv/ghostnet. + +ghostnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ghostnet](https://gitee.com/mindspore/models/blob/r1.5/research/cv/ghostnet/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Kai Han, Yunhe Wang, Qi Tian."GhostNet: More Features From Cheap Operations" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/gloreres200_imagenet2012.md b/mshub_res/assets/mindspore/1.5/gloreres200_imagenet2012.md new file mode 100644 index 0000000..a4d6298 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/gloreres200_imagenet2012.md @@ -0,0 +1,62 @@ +# glore_res200 + +--- + +model-name: glore_res200 + +backbone-name: glore_res200 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc79.95 | top5acc94.89 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 106bba976cc6f7d5d59a74a63062d5600165090763fcfebc96af507b15c24dfb + +license: Apache2.0 + +summary: glore_res200 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of glore_res200 from the MindSpore model zoo on Gitee at research/cv/glore_res200. + +glore_res200 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/glore_res200](https://gitee.com/mindspore/models/blob/r1.5/research/cv/glore_res200/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Yunpeng Chenyz, Marcus Rohrbachy, Zhicheng Yany, Shuicheng Yanz, Jiashi Fengz, Yannis Kalantidisy + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/gloreres50_imagenet2012.md b/mshub_res/assets/mindspore/1.5/gloreres50_imagenet2012.md new file mode 100644 index 0000000..a37289a --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/gloreres50_imagenet2012.md @@ -0,0 +1,62 @@ +# glore_res50 + +--- + +model-name: glore_res50 + +backbone-name: glore_res50 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc78.32 | top5acc94.02 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: b2ee8e5bdf5059b9229d539c485c8da1437b23c7b5554970808ca99610631efd + +license: Apache2.0 + +summary: glore_res50 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of glore_res50 from the MindSpore model zoo on Gitee at research/cv/glore_res50. + +glore_res50 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/glore_res50](https://gitee.com/mindspore/models/blob/r1.5/research/cv/glore_res50/README.md). + +All parameters in the module are trainable. + +## Citation + +Yupeng Chen, Marcus Rohrbach, Zhicheng Yan, Shuicheng Yan, Jiashi Feng, Yannis Kalantidis."Deep Residual Learning for Image Recognition" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/gnmtv2_wmtende.md b/mshub_res/assets/mindspore/1.5/gnmtv2_wmtende.md new file mode 100644 index 0000000..88e1a49 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/gnmtv2_wmtende.md @@ -0,0 +1,79 @@ +# gnmt_v2 + +--- + +model-name: gnmt_v2 + +backbone-name: gnmt_v2 + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: wmtende + +evaluation: acc24 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 48546b769601e39e380c2ec3916930501195e200fe84f1ef04d91725b4380e1a + +license: Apache2.0 + +summary: gnmt_v2 is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of gnmt_v2 from the MindSpore model zoo on Gitee at official/nlp/gnmt_v2. + +gnmt_v2 is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/gnmt_v2](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/gnmt_v2/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/gnmtv2_wmtende" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/googlenet_cifar10.md b/mshub_res/assets/mindspore/1.5/googlenet_cifar10.md new file mode 100644 index 0000000..b168619 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/googlenet_cifar10.md @@ -0,0 +1,79 @@ +# googlenet + +--- + +model-name: googlenet + +backbone-name: googlenet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cifar10 + +evaluation: acc92.53 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: b2f7fe14782a3ab88ad3534ed5f419b4bbc3b477706258bd6ed8f90f529775e7 + +license: Apache2.0 + +summary: googlenet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of googlenet from the MindSpore model zoo on Gitee at official/cv/googlenet. + +googlenet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/googlenet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/googlenet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/googlenet_cifar10" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich. "Going deeper with convolutions." *Proceedings of the IEEE conference on computer vision and pattern recognition*. 2015. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/googlenet_imagenet2012.md b/mshub_res/assets/mindspore/1.5/googlenet_imagenet2012.md new file mode 100644 index 0000000..1b5205c --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/googlenet_imagenet2012.md @@ -0,0 +1,79 @@ +# googlenet + +--- + +model-name: googlenet + +backbone-name: googlenet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc72.97 | top5acc90.97 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c35b3baff0b4413988a95fa3691733a58d1695b66bf2ae47030c41e539885240 + +license: Apache2.0 + +summary: googlenet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of googlenet from the MindSpore model zoo on Gitee at official/cv/googlenet. + +googlenet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/googlenet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/googlenet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/googlenet_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich. "Going deeper with convolutions." *Proceedings of the IEEE conference on computer vision and pattern recognition*. 2015. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/gpt3_openweb.md b/mshub_res/assets/mindspore/1.5/gpt3_openweb.md new file mode 100644 index 0000000..7faffea --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/gpt3_openweb.md @@ -0,0 +1,79 @@ +# gpt + +--- + +model-name: gpt + +backbone-name: gpt + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: openweb + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: e4d4e4d4023b7475972250d8126a4e183eb60f3d87f11df1f1e09d414c58e448 + +license: Apache2.0 + +summary: gpt is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of gpt from the MindSpore model zoo on Gitee at official/nlp/gpt. + +gpt is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/gpt](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/gpt/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/gpt3_openweb" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Tom B.Brown, Benjamin Mann, Nick Ryder et al. Language Models are Few-Shot Learners. arXiv preprint arXiv:2005.14165 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/gru_muti30k.md b/mshub_res/assets/mindspore/1.5/gru_muti30k.md new file mode 100644 index 0000000..582b65a --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/gru_muti30k.md @@ -0,0 +1,81 @@ +# gru + +--- + +model-name: gru + +backbone-name: gru + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: muti30k + +evaluation: acc30 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 4d0e2582626ed286b9753b8e2b79dcd1c54dc87170f3ddae050796edb5ce8eeb + +license: Apache2.0 + +summary: gru is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of gru from the MindSpore model zoo on Gitee at official/nlp/gru. + +gru is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/gru](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/gru/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/gru_muti30k" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. "Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation", 2014, Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, Yoshua Bengio +2. "Sequence to Sequence Learning with Neural Networks", 2014, Ilya Sutskever, Oriol Vinyals, Quoc V. Le +3. "Neural Machine Translation by Jointly Learning to Align and Translate", 2014, Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/hardnet_imagenet2012.md b/mshub_res/assets/mindspore/1.5/hardnet_imagenet2012.md new file mode 100644 index 0000000..823db7a --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/hardnet_imagenet2012.md @@ -0,0 +1,62 @@ +# hardnet + +--- + +model-name: hardnet + +backbone-name: hardnet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc77.61 | top5acc93.61 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 9bda86bcba49a46f9f986431dba148f266437dd0196f0ebe50e3192cf4f01b0f + +license: Apache2.0 + +summary: hardnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of hardnet from the MindSpore model zoo on Gitee at research/cv/hardnet. + +hardnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/hardnet](https://gitee.com/mindspore/models/blob/r1.5/research/cv/hardnet/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Chao P , Kao C Y , Ruan Y , et al. HarDNet: A Low Memory Traffic Network[C]// 2019 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2020. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/ibnnet_imagenet2012.md b/mshub_res/assets/mindspore/1.5/ibnnet_imagenet2012.md new file mode 100644 index 0000000..b96ec78 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/ibnnet_imagenet2012.md @@ -0,0 +1,62 @@ +# ibnnet + +--- + +model-name: ibnnet + +backbone-name: ibnnet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc77.13 | top5acc93.59 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c9ab6f1198b1b930fb2df92715134de798e103c1dd66bca06f3ee826b1a9983e + +license: Apache2.0 + +summary: ibnnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ibnnet from the MindSpore model zoo on Gitee at research/cv/ibnnet. + +ibnnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ibnnet](https://gitee.com/mindspore/models/blob/r1.5/research/cv/ibnnet/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Pan X , Ping L , Shi J , et al. Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net[C]// European Conference on Computer Vision. Springer, Cham, 2018. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/icnet_cityscapes.md b/mshub_res/assets/mindspore/1.5/icnet_cityscapes.md new file mode 100644 index 0000000..53d06d1 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/icnet_cityscapes.md @@ -0,0 +1,62 @@ +# ICNet + +--- + +model-name: ICNet + +backbone-name: ICNet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cityscapes + +evaluation: avgmiou69.54 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 2a16822fefb0627b455c73a57321a9da24e2483b11487e173bcdc6c07841d867 + +license: Apache2.0 + +summary: ICNet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ICNet from the MindSpore model zoo on Gitee at research/cv/ICNet. + +ICNet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ICNet](https://gitee.com/mindspore/models/blob/r1.5/research/cv/ICNet/README.md). + +All parameters in the module are trainable. + +## Citation + +ICNet for Real-Time Semantic Segmentation on High-Resolution Images + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/inceptionresnetv2_imagenet2012.md b/mshub_res/assets/mindspore/1.5/inceptionresnetv2_imagenet2012.md new file mode 100644 index 0000000..a029181 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/inceptionresnetv2_imagenet2012.md @@ -0,0 +1,62 @@ +# inception_resnet_v2 + +--- + +model-name: inception_resnet_v2 + +backbone-name: inception_resnet_v2 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc80.04 | top5acc94.54 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: cf282d78635945173a79accf2068b0c651aff1253eeae556f31428190b7e3dbd + +license: Apache2.0 + +summary: inception_resnet_v2 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of inception_resnet_v2 from the MindSpore model zoo on Gitee at research/cv/inception_resnet_v2. + +inception_resnet_v2 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/inception_resnet_v2](https://gitee.com/mindspore/models/blob/r1.5/research/cv/inception_resnet_v2/README.md). + +All parameters in the module are trainable. + +## Citation + +Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, Alex Alemi. Computer Vision and Pattern Recognition[J]. 2016. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/inceptionv3_imagenet2012.md b/mshub_res/assets/mindspore/1.5/inceptionv3_imagenet2012.md new file mode 100644 index 0000000..7aefaad --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/inceptionv3_imagenet2012.md @@ -0,0 +1,79 @@ +# inceptionv3 + +--- + +model-name: inceptionv3 + +backbone-name: inceptionv3 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc78.69 | top5acc94.3 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c3b6bd7fb0394255d8d96fde238face46e79b6a3a130c9a71135a1d8552536b4 + +license: Apache2.0 + +summary: inceptionv3 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of inceptionv3 from the MindSpore model zoo on Gitee at official/cv/inceptionv3. + +inceptionv3 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/inceptionv3](https://gitee.com/mindspore/models/blob/r1.5/official/cv/inceptionv3/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/inceptionv3_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Min Sun, Ali Farhadi, Steve Seitz. Ranking Domain-Specific Highlights by Analyzing Edited Videos[J]. 2014. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/inceptionv4_imagenet2012.md b/mshub_res/assets/mindspore/1.5/inceptionv4_imagenet2012.md new file mode 100644 index 0000000..8f161eb --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/inceptionv4_imagenet2012.md @@ -0,0 +1,79 @@ +# inceptionv4 + +--- + +model-name: inceptionv4 + +backbone-name: inceptionv4 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc79.95 | top5acc94.83 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: da517828508f915ef06b3f33c45b8d52e0eaa019bbb86080de7f4beea30377f1 + +license: Apache2.0 + +summary: inceptionv4 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of inceptionv4 from the MindSpore model zoo on Gitee at official/cv/inceptionv4. + +inceptionv4 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/inceptionv4](https://gitee.com/mindspore/models/blob/r1.5/official/cv/inceptionv4/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/inceptionv4_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, Alex Alemi. Computer Vision and Pattern Recognition[J]. 2016. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/learningtoseeinthedark_sony.md b/mshub_res/assets/mindspore/1.5/learningtoseeinthedark_sony.md new file mode 100644 index 0000000..7aeb55f --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/learningtoseeinthedark_sony.md @@ -0,0 +1,62 @@ +# LearningToSeeInTheDark + +--- + +model-name: LearningToSeeInTheDark + +backbone-name: LearningToSeeInTheDark + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: sony + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 039f394fe9dff0ed09600179f0135bffebf7699f64152993778bfeb72fcd5f20 + +license: Apache2.0 + +summary: LearningToSeeInTheDark is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of LearningToSeeInTheDark from the MindSpore model zoo on Gitee at research/cv/LearningToSeeInTheDark. + +LearningToSeeInTheDark is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/LearningToSeeInTheDark](https://gitee.com/mindspore/models/blob/r1.5/research/cv/LearningToSeeInTheDark/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Chen C, Chen Q, Xu J, et al. Learning to See in the Dark[C]// 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. IEEE, 2018. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/lenet_mnist.md b/mshub_res/assets/mindspore/1.5/lenet_mnist.md new file mode 100644 index 0000000..9298f31 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/lenet_mnist.md @@ -0,0 +1,79 @@ +# lenet + +--- + +model-name: lenet + +backbone-name: lenet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: mnist + +evaluation: acc98.49 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: f0734abb1f74d3e4d96ed9baf3fd6f17596943d58cbb17509506fae4518fceef + +license: Apache2.0 + +summary: lenet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of lenet from the MindSpore model zoo on Gitee at official/cv/lenet. + +lenet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/lenet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/lenet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/lenet_mnist" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Y.Lecun, L.Bottou, Y.Bengio, P.Haffner. Gradient-Based Learning Applied to Document Recognition. *Proceedings of the IEEE*. 1998. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/lenetquant_mnist.md b/mshub_res/assets/mindspore/1.5/lenetquant_mnist.md new file mode 100644 index 0000000..53e13b8 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/lenetquant_mnist.md @@ -0,0 +1,79 @@ +# lenet_quant + +--- + +model-name: lenet_quant + +backbone-name: lenet_quant + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: mnist + +evaluation: acc98.79 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 92c14388fdf4ea90811de5031652b2e58570a5abf7c3653b0e958fb0e30f3546 + +license: Apache2.0 + +summary: lenet_quant is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of lenet_quant from the MindSpore model zoo on Gitee at official/cv/lenet_quant. + +lenet_quant is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/lenet_quant](https://gitee.com/mindspore/models/blob/r1.5/official/cv/lenet_quant/Readme.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/lenetquant_mnist" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Y.Lecun, L.Bottou, Y.Bengio, P.Haffner. Gradient-Based Learning Applied to Document Recognition. *Proceedings of the IEEE*. 1998. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/lstm_aclimdbv1.md b/mshub_res/assets/mindspore/1.5/lstm_aclimdbv1.md new file mode 100644 index 0000000..f394204 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/lstm_aclimdbv1.md @@ -0,0 +1,62 @@ +# lstm + +--- + +model-name: lstm + +backbone-name: lstm + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: aclimdbv1 + +evaluation: acc86.18 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 7cc4125a91a2e792037cb17da99c2662c1b62ac9a4cc73f65fa6f43ba07e8ac6 + +license: Apache2.0 + +summary: lstm is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of lstm from the MindSpore model zoo on Gitee at official/nlp/lstm. + +lstm is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/lstm](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/lstm/README.md). + +All parameters in the module are trainable. + +## Citation + +Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, Christopher Potts. Learning Word Vectors for Sentiment Analysis. Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies. 2011 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/maskrcnn_coco2017.md b/mshub_res/assets/mindspore/1.5/maskrcnn_coco2017.md new file mode 100644 index 0000000..7610bb1 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/maskrcnn_coco2017.md @@ -0,0 +1,79 @@ +# maskrcnn + +--- + +model-name: maskrcnn + +backbone-name: maskrcnn + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: acc32.9 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5fa5a1e12cf64538c26a984cd4e1cdd418a5629bfe15b265bb7b49536a6a8a99 + +license: Apache2.0 + +summary: maskrcnn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of maskrcnn from the MindSpore model zoo on Gitee at official/cv/maskrcnn. + +maskrcnn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/maskrcnn](https://gitee.com/mindspore/models/blob/r1.5/official/cv/maskrcnn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/maskrcnn_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Kaiming He, Georgia Gkioxari, Piotr Dollar and Ross Girshick. "MaskRCNN" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/mass_newscrawl_gigaword_cornell.md b/mshub_res/assets/mindspore/1.5/mass_newscrawl_gigaword_cornell.md new file mode 100644 index 0000000..11d4209 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/mass_newscrawl_gigaword_cornell.md @@ -0,0 +1,79 @@ +# mass + +--- + +model-name: mass + +backbone-name: mass + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: newscrawl_gigaword_cornell + +evaluation: RG1acc51.77 | RG2acc34.46 | RGL49.89 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 98414b2c2e27d7b8ee51754e5bf251fedb10f8700ed86ce25503df9b976b63ce + +license: Apache2.0 + +summary: mass is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of mass from the MindSpore model zoo on Gitee at official/nlp/mass. + +mass is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/mass](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/mass/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/mass_newscrawl_gigaword_cornell" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Song, Kaitao, Xu Tan, Tao Qin, Jianfeng Lu and Tie-Yan Liu.“MASS: Masked Sequence to Sequence Pre-training for Language Generation.”ICML (2019). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/mnasnet_imagenet2012.md b/mshub_res/assets/mindspore/1.5/mnasnet_imagenet2012.md new file mode 100644 index 0000000..c603917 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/mnasnet_imagenet2012.md @@ -0,0 +1,79 @@ +# mnasnet + +--- + +model-name: mnasnet + +backbone-name: mnasnet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc73.98 | top5acc91.68 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d72b9a520a7687c0017289dc80cb480f84c01d8542fee1fa367ab914467f69c2 + +license: Apache2.0 + +summary: mnasnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of mnasnet from the MindSpore model zoo on Gitee at research/cv/mnasnet. + +mnasnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/mnasnet](https://gitee.com/mindspore/models/blob/r1.5/research/cv/mnasnet/README_CN.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/mnasnet_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, Mark Sandler, Andrew Howard, Quoc V. Le. MnasNet: Platform-Aware Neural Architecture Search for Mobile 2018. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/mobilenetv1_cifar10.md b/mshub_res/assets/mindspore/1.5/mobilenetv1_cifar10.md new file mode 100644 index 0000000..8987373 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/mobilenetv1_cifar10.md @@ -0,0 +1,79 @@ +# mobilenetv1 + +--- + +model-name: mobilenetv1 + +backbone-name: mobilenetv1 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cifar10 + +evaluation: top1acc93.17 | top5acc99.81 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 88aa89d6183c7268981ca7b0f4f7e17b851a1e0c4870a852f81252ae3a4b5057 + +license: Apache2.0 + +summary: mobilenetv1 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of mobilenetv1 from the MindSpore model zoo on Gitee at official/cv/mobilenetv1. + +mobilenetv1 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/mobilenetv1](https://gitee.com/mindspore/models/blob/r1.5/official/cv/mobilenetv1/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/mobilenetv1_cifar10" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Howard A G , Zhu M , Chen B , et al. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications[J]. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/mobilenetv1_imagenet2012.md b/mshub_res/assets/mindspore/1.5/mobilenetv1_imagenet2012.md new file mode 100644 index 0000000..e9b77f6 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/mobilenetv1_imagenet2012.md @@ -0,0 +1,79 @@ +# mobilenetv1 + +--- + +model-name: mobilenetv1 + +backbone-name: mobilenetv1 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc71.96 | top5acc90.44 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: b0c379792495cce4c253e7e042f3ce80eddd353de61082bf35c1ac14012f5cde + +license: Apache2.0 + +summary: mobilenetv1 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of mobilenetv1 from the MindSpore model zoo on Gitee at official/cv/mobilenetv1. + +mobilenetv1 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/mobilenetv1](https://gitee.com/mindspore/models/blob/r1.5/official/cv/mobilenetv1/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/mobilenetv1_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Howard A G , Zhu M , Chen B , et al. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications[J]. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/mobilenetv2quant_imagenet2012.md b/mshub_res/assets/mindspore/1.5/mobilenetv2quant_imagenet2012.md new file mode 100644 index 0000000..6b2e7d5 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/mobilenetv2quant_imagenet2012.md @@ -0,0 +1,79 @@ +# mobilenetv2_quant + +--- + +model-name: mobilenetv2_quant + +backbone-name: mobilenetv2_quant + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc71 | top5acc90 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 159439c2a76851460f42d66087f12558c8a0a7ec781c2ec4978e8684ae29887f + +license: Apache2.0 + +summary: mobilenetv2_quant is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of mobilenetv2_quant from the MindSpore model zoo on Gitee at official/cv/mobilenetv2_quant. + +mobilenetv2_quant is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/mobilenetv2_quant](https://gitee.com/mindspore/models/blob/r1.5/official/cv/mobilenetv2_quant/Readme.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/mobilenetv2quant_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Howard, Andrew, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang et al. "Searching for MobileNetV2." In Proceedings of the IEEE International Conference on Computer Vision, pp. 1314-1324. 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/mobilenetv3large_imagenet2012.md b/mshub_res/assets/mindspore/1.5/mobilenetv3large_imagenet2012.md new file mode 100644 index 0000000..9b79730 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/mobilenetv3large_imagenet2012.md @@ -0,0 +1,62 @@ +# mobilenetv3_large + +--- + +model-name: mobilenetv3_large + +backbone-name: mobilenetv3_large + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc74.55 | top5acc91.76 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 7f979e6256886df0070f9f4286ec0b32f21119b1430a127afddefeb10dd7bc31 + +license: Apache2.0 + +summary: mobilenetv3_large is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of mobilenetv3_large from the MindSpore model zoo on Gitee at research/cv/mobilenetv3_large. + +mobilenetv3_large is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/mobilenetv3_large](https://gitee.com/mindspore/models/blob/r1.5/research/cv/mobilenetv3_large/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Howard, Andrew, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang et al."Searching for mobilenetv3."In Proceedings of the IEEE International Conference on Computer Vision, pp. 1314-1324.2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/mobilenetv3smallx10_imagenet2012.md b/mshub_res/assets/mindspore/1.5/mobilenetv3smallx10_imagenet2012.md new file mode 100644 index 0000000..4005c5e --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/mobilenetv3smallx10_imagenet2012.md @@ -0,0 +1,62 @@ +# mobilenetV3_small_x1_0 + +--- + +model-name: mobilenetV3_small_x1_0 + +backbone-name: mobilenetV3_small_x1_0 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc67 | top5acc87 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 76d176503f5a18bf60b5ee0ad23f150b36306b616c5798aef4df4ff917538a5f + +license: Apache2.0 + +summary: mobilenetV3_small_x1_0 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of mobilenetV3_small_x1_0 from the MindSpore model zoo on Gitee at research/cv/mobilenetV3_small_x1_0. + +mobilenetV3_small_x1_0 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/mobilenetV3_small_x1_0](https://gitee.com/mindspore/models/blob/r1.5/research/cv/mobilenetV3_small_x1_0/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Howard, Andrew, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang et al."Searching for mobilenetv3."In Proceedings of the IEEE International Conference on Computer Vision, pp. 1314-1324.2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/naml_mindlarge.md b/mshub_res/assets/mindspore/1.5/naml_mindlarge.md new file mode 100644 index 0000000..372fd9e --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/naml_mindlarge.md @@ -0,0 +1,79 @@ +# naml + +--- + +model-name: naml + +backbone-name: naml + +module-type: recommend + +fine-tunable: True + +model-version: 1.5 + +train-dataset: mindlarge + +evaluation: acc67 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 9d553eae6ce96f019148b69ed4ce3ebb665503d7f1eda7c4907e23242479cdce + +license: Apache2.0 + +summary: naml is used for recommend + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of naml from the MindSpore model zoo on Gitee at official/recommend/naml. + +naml is a recommend network. More details please refer to the MindSpore model zoo on Gitee at [official/recommend/naml](https://gitee.com/mindspore/models/blob/r1.5/official/recommend/naml/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/naml_mindlarge" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Chuhan Wu, Fangzhao Wu, Mingxiao An, Jianqiang Huang, Yongfeng Huang and Xing Xie: Neural News Recommendation with Attentive Multi-View Learning, IJCAI 2019 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/nasnet_imagenet2012.md b/mshub_res/assets/mindspore/1.5/nasnet_imagenet2012.md new file mode 100644 index 0000000..dbf6755 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/nasnet_imagenet2012.md @@ -0,0 +1,62 @@ +# nasnet + +--- + +model-name: nasnet + +backbone-name: nasnet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc74.05 | top5acc91.59 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 9f84e8d6305d05ce9bc72d62d424364b4888b217e6eb25acc0557595c9cc70c6 + +license: Apache2.0 + +summary: nasnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of nasnet from the MindSpore model zoo on Gitee at official/cv/nasnet. + +nasnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/nasnet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/nasnet/README.md). + +All parameters in the module are trainable. + +## Citation + +Barret Zoph, Vijay Vasudevan, Jonathon Shlens, Quoc V. Le. Learning Transferable Architectures for Scalable Image Recognition. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/ncf_movielens.md b/mshub_res/assets/mindspore/1.5/ncf_movielens.md new file mode 100644 index 0000000..020df50 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/ncf_movielens.md @@ -0,0 +1,79 @@ +# ncf + +--- + +model-name: ncf + +backbone-name: ncf + +module-type: recommend + +fine-tunable: True + +model-version: 1.5 + +train-dataset: movielens + +evaluation: hr70.25 | ndcg42.23 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: ff7bd040b8e269a8a81b1dcc2f96e157bc4c279c7ecc84fe9c9a9f166690e99d + +license: Apache2.0 + +summary: ncf is used for recommend + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ncf from the MindSpore model zoo on Gitee at official/recommend/ncf. + +ncf is a recommend network. More details please refer to the MindSpore model zoo on Gitee at [official/recommend/ncf](https://gitee.com/mindspore/models/blob/r1.5/official/recommend/ncf/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/ncf_movielens" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +He X, Liao L, Zhang H, et al. Neural collaborative filtering[C]//Proceedings of the 26th international conference on world wide web. 2017: 173-182. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/ntsnet_cub2002011.md b/mshub_res/assets/mindspore/1.5/ntsnet_cub2002011.md new file mode 100644 index 0000000..b82dd52 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/ntsnet_cub2002011.md @@ -0,0 +1,79 @@ +# ntsnet + +--- + +model-name: ntsnet + +backbone-name: ntsnet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cub2002011 + +evaluation: acc87 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 4b29c87a6402cab44efcc499e46dcec2eddf2f35c84002434c4f66be8b0968cc + +license: Apache2.0 + +summary: ntsnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ntsnet from the MindSpore model zoo on Gitee at research/cv/ntsnet. + +ntsnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ntsnet](https://gitee.com/mindspore/models/blob/r1.5/research/cv/ntsnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/ntsnet_cub2002011" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Z. Yang, T. Luo, D. Wang, Z. Hu, J. Gao, and L. Wang, Learning to navigate for fine-grained classification, in Proceedings of the European Conference on Computer Vision (ECCV), 2018. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/openpose_coco2017.md b/mshub_res/assets/mindspore/1.5/openpose_coco2017.md new file mode 100644 index 0000000..c8c4fce --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/openpose_coco2017.md @@ -0,0 +1,79 @@ +# openpose + +--- + +model-name: openpose + +backbone-name: openpose + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: mAP40.29 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 60d785f9834508e9144286cb14c5e0ce28303d7dee58f5dcc7610be9db30c81f + +license: Apache2.0 + +summary: openpose is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of openpose from the MindSpore model zoo on Gitee at official/cv/openpose. + +openpose is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/openpose](https://gitee.com/mindspore/models/blob/r1.5/official/cv/openpose/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/openpose_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Zhe Cao,Tomas Simon,Shih-En Wei,Yaser Sheikh,"Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields",The IEEE Conference on Computer Vision and Pattern Recongnition(CVPR),2017 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/pgan_G_celeba.md b/mshub_res/assets/mindspore/1.5/pgan_G_celeba.md new file mode 100644 index 0000000..502988c --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/pgan_G_celeba.md @@ -0,0 +1,62 @@ +# PGAN + +--- + +model-name: PGAN + +backbone-name: PGAN + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: celeba + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 2abeb89fdc788de05ea01d151f54b7b0fdd8c75dd079ff42b0fc9bb4f175e60e + +license: Apache2.0 + +summary: PGAN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of PGAN from the MindSpore model zoo on Gitee at research/cv/PGAN. + +PGAN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/PGAN](https://gitee.com/mindspore/models/blob/r1.5/research/cv/PGAN/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Progressive Growing of GANs for Improved Quality, Stability, and Variation//2018 ICLR + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/pix2pix_G_facades.md b/mshub_res/assets/mindspore/1.5/pix2pix_G_facades.md new file mode 100644 index 0000000..20129dc --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/pix2pix_G_facades.md @@ -0,0 +1,62 @@ +# Pix2Pix + +--- + +model-name: Pix2Pix + +backbone-name: Pix2Pix + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: facades + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 185b0679425ec6ac60b1d393023ec7b3f0c760feaa49e7d2a23c157a96a25b8d + +license: Apache2.0 + +summary: Pix2Pix is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of Pix2Pix from the MindSpore model zoo on Gitee at research/cv/Pix2Pix. + +Pix2Pix is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/Pix2Pix](https://gitee.com/mindspore/models/blob/r1.5/research/cv/Pix2Pix/README.md). + +All parameters in the module are trainable. + +## Citation + +Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A. Efros. "Image-to-Image Translation with Conditional Adversarial Networks", in CVPR 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/pix2pix_G_maps.md b/mshub_res/assets/mindspore/1.5/pix2pix_G_maps.md new file mode 100644 index 0000000..a096e20 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/pix2pix_G_maps.md @@ -0,0 +1,62 @@ +# Pix2Pix + +--- + +model-name: Pix2Pix + +backbone-name: Pix2Pix + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: maps + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 39aa394d029b5c8b727c8c478fb14ffd48f11564a8b395e9b123ea28e2a8f324 + +license: Apache2.0 + +summary: Pix2Pix is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of Pix2Pix from the MindSpore model zoo on Gitee at research/cv/Pix2Pix. + +Pix2Pix is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/Pix2Pix](https://gitee.com/mindspore/models/blob/r1.5/research/cv/Pix2Pix/README.md). + +All parameters in the module are trainable. + +## Citation + +Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A. Efros. "Image-to-Image Translation with Conditional Adversarial Networks", in CVPR 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/pointnet2_modelnet40.md b/mshub_res/assets/mindspore/1.5/pointnet2_modelnet40.md new file mode 100644 index 0000000..9dd179a --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/pointnet2_modelnet40.md @@ -0,0 +1,62 @@ +# pointnet2 + +--- + +model-name: pointnet2 + +backbone-name: pointnet2 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: modelnet40 + +evaluation: acc91.83 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d0dfc830f9b5635e7ee0d433b29626ec765374b3f408bbe533282822e5ab8dbb + +license: Apache2.0 + +summary: pointnet2 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of pointnet2 from the MindSpore model zoo on Gitee at research/cv/pointnet2. + +pointnet2 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/pointnet2](https://gitee.com/mindspore/models/blob/r1.5/research/cv/pointnet2/README.md). + +All parameters in the module are trainable. + +## Citation + +Qi, Charles R., et al. "Pointnet++: Deep hierarchical feature learning on point sets in a metric space." arXiv preprint arXiv:1706.02413 (2017). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/posenet_kingscollege.md b/mshub_res/assets/mindspore/1.5/posenet_kingscollege.md new file mode 100644 index 0000000..5e282fd --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/posenet_kingscollege.md @@ -0,0 +1,62 @@ +# posenet + +--- + +model-name: posenet + +backbone-name: posenet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: kingscollege + +evaluation: 2.2m | 3.44d + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d882ceb3f8dc68db7064732e3a0da7b6c37766e054cf7ad60c049aef987331cc + +license: Apache2.0 + +summary: posenet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of posenet from the MindSpore model zoo on Gitee at official/cv/posenet. + +posenet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/posenet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/posenet/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Kendall A, Grimes M, Cipolla R. "PoseNet: A convolutional network for real-time 6-dof camera relocalization."*In IEEE International Conference on Computer Vision (pp. 2938–2946), 2015. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/posenet_stmaryschurch.md b/mshub_res/assets/mindspore/1.5/posenet_stmaryschurch.md new file mode 100644 index 0000000..a396219 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/posenet_stmaryschurch.md @@ -0,0 +1,62 @@ +# posenet + +--- + +model-name: posenet + +backbone-name: posenet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: stmaryschurch + +evaluation: 2.0m | 5.93d + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: ae1db1bd49928839b6c295fbe50115ca43860c02c46b0542103e66a944c44e33 + +license: Apache2.0 + +summary: posenet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of posenet from the MindSpore model zoo on Gitee at official/cv/posenet. + +posenet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/posenet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/posenet/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Kendall A, Grimes M, Cipolla R. "PoseNet: A convolutional network for real-time 6-dof camera relocalization."*In IEEE International Conference on Computer Vision (pp. 2938–2946), 2015. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/protonet_omniglot.md b/mshub_res/assets/mindspore/1.5/protonet_omniglot.md new file mode 100644 index 0000000..fe79f41 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/protonet_omniglot.md @@ -0,0 +1,62 @@ +# ProtoNet + +--- + +model-name: ProtoNet + +backbone-name: ProtoNet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: omniglot + +evaluation: acc99.63 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: f2494972445dbe2c26d5d66dbe94cca5d047a6870aa28f5c42900c5e4562376a + +license: Apache2.0 + +summary: ProtoNet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ProtoNet from the MindSpore model zoo on Gitee at research/cv/ProtoNet. + +ProtoNet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ProtoNet](https://gitee.com/mindspore/models/blob/r1.5/research/cv/ProtoNet/README.md). + +All parameters in the module are trainable. + +## Citation + +Prototypical Networks for Few-shot Learning + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/psenet_icdar2015.md b/mshub_res/assets/mindspore/1.5/psenet_icdar2015.md new file mode 100644 index 0000000..4340a8c --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/psenet_icdar2015.md @@ -0,0 +1,79 @@ +# psenet + +--- + +model-name: psenet + +backbone-name: psenet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: icdar2015 + +evaluation: acc81 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 06b2b0a90ecb0be4202db2c28a4672ecdab78d8995829da53bafd61ac18b77cf + +license: Apache2.0 + +summary: psenet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of psenet from the MindSpore model zoo on Gitee at official/cv/psenet. + +psenet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/psenet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/psenet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/psenet_icdar2015" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wenhai Wang, Enze Xie, Xiang Li, Wenbo Hou, Tong Lu, Gang Yu, Shuai Shao; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, pp. 9336-9345 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/r2plus1d_ucf101.md b/mshub_res/assets/mindspore/1.5/r2plus1d_ucf101.md new file mode 100644 index 0000000..e1c33ef --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/r2plus1d_ucf101.md @@ -0,0 +1,62 @@ +# r2plus1d + +--- + +model-name: r2plus1d + +backbone-name: r2plus1d + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: ucf101 + +evaluation: acc96 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 04bc87e418054af98902bb2c6d2470107e1ab952208230951670a597782ffac8 + +license: Apache2.0 + +summary: r2plus1d is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of r2plus1d from the MindSpore model zoo on Gitee at research/cv/r2plus1d. + +r2plus1d is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/r2plus1d](https://gitee.com/mindspore/models/blob/r1.5/research/cv/r2plus1d/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Du T , Wang H , Torresani L , et al. A Closer Look at Spatiotemporal Convolutions for Action Recognition[C]// IEEE/CVF Conference on Computer Vision and Pattern Recognition. 0. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/resnet101_imagenet2012.md b/mshub_res/assets/mindspore/1.5/resnet101_imagenet2012.md new file mode 100644 index 0000000..adafa4f --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/resnet101_imagenet2012.md @@ -0,0 +1,81 @@ +# resnet + +--- + +model-name: resnet + +backbone-name: resnet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc78.55 | top5acc94.34 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d0ad1bb5fbd692b8fbfb7b6304560197bd4003e5c88f77ab1cee4141f302b936 + +license: Apache2.0 + +summary: resnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnet from the MindSpore model zoo on Gitee at official/cv/resnet. + +resnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/resnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/resnet101_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun."Deep Residual Learning for Image Recognition" +2. Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu."Squeeze-and-Excitation Networks" +3. Tong He, Zhi Zhang, Hang Zhang, Zhongyue Zhang, Junyuan Xie, Mu Li."Bag of Tricks for Image Classification with Convolutional Neural Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/resnet152_imagenet2012.md b/mshub_res/assets/mindspore/1.5/resnet152_imagenet2012.md new file mode 100644 index 0000000..b989265 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/resnet152_imagenet2012.md @@ -0,0 +1,81 @@ +# resnet + +--- + +model-name: resnet + +backbone-name: resnet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc78.72 | top5acc94.32 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 76d176503f5a18bf60b5ee0ad23f150b36306b616c5798aef4df4ff917538a5f + +license: Apache2.0 + +summary: resnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnet from the MindSpore model zoo on Gitee at official/cv/resnet. + +resnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/resnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/resnet152_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun."Deep Residual Learning for Image Recognition" +2. Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu."Squeeze-and-Excitation Networks" +3. Tong He, Zhi Zhang, Hang Zhang, Zhongyue Zhang, Junyuan Xie, Mu Li."Bag of Tricks for Image Classification with Convolutional Neural Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/resnet18_cifar10.md b/mshub_res/assets/mindspore/1.5/resnet18_cifar10.md new file mode 100644 index 0000000..85172a3 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/resnet18_cifar10.md @@ -0,0 +1,81 @@ +# resnet + +--- + +model-name: resnet + +backbone-name: resnet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cifar10 + +evaluation: acc94.02 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: e668e52ba28d5a90d8eb4166457f506c49b08d6fbc331823766a7ea3ea92fdcc + +license: Apache2.0 + +summary: resnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnet from the MindSpore model zoo on Gitee at official/cv/resnet. + +resnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/resnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/resnet18_cifar10" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun."Deep Residual Learning for Image Recognition" +2. Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu."Squeeze-and-Excitation Networks" +3. Tong He, Zhi Zhang, Hang Zhang, Zhongyue Zhang, Junyuan Xie, Mu Li."Bag of Tricks for Image Classification with Convolutional Neural Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/resnet18_imagenet2012.md b/mshub_res/assets/mindspore/1.5/resnet18_imagenet2012.md new file mode 100644 index 0000000..4d6edb9 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/resnet18_imagenet2012.md @@ -0,0 +1,81 @@ +# resnet + +--- + +model-name: resnet + +backbone-name: resnet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc70.47 | top5acc89.61 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 22a181090f89f52442a43fc0a59b0d6029257c129f2722d11a25c9023ba95942 + +license: Apache2.0 + +summary: resnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnet from the MindSpore model zoo on Gitee at official/cv/resnet. + +resnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/resnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/resnet18_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun."Deep Residual Learning for Image Recognition" +2. Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu."Squeeze-and-Excitation Networks" +3. Tong He, Zhi Zhang, Hang Zhang, Zhongyue Zhang, Junyuan Xie, Mu Li."Bag of Tricks for Image Classification with Convolutional Neural Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/resnet34_imagenet2012.md b/mshub_res/assets/mindspore/1.5/resnet34_imagenet2012.md new file mode 100644 index 0000000..8494314 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/resnet34_imagenet2012.md @@ -0,0 +1,81 @@ +# resnet + +--- + +model-name: resnet + +backbone-name: resnet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc73.83 | top5acc91.61 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: b8303354c68c55560d1f1bb04dce4dfd62dd1f02a417c05bfa6b0a920396522c + +license: Apache2.0 + +summary: resnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnet from the MindSpore model zoo on Gitee at official/cv/resnet. + +resnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/resnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/resnet34_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun."Deep Residual Learning for Image Recognition" +2. Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu."Squeeze-and-Excitation Networks" +3. Tong He, Zhi Zhang, Hang Zhang, Zhongyue Zhang, Junyuan Xie, Mu Li."Bag of Tricks for Image Classification with Convolutional Neural Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/resnet50_imagenet2012.md b/mshub_res/assets/mindspore/1.5/resnet50_imagenet2012.md new file mode 100644 index 0000000..cc9d73e --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/resnet50_imagenet2012.md @@ -0,0 +1,81 @@ +# resnet + +--- + +model-name: resnet + +backbone-name: resnet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc76.97 | top5acc93.44 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 41c1479844f6f848d4caf902cf940ebe4727df559495ed45885892fc55a2738f + +license: Apache2.0 + +summary: resnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnet from the MindSpore model zoo on Gitee at official/cv/resnet. + +resnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/resnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/resnet50_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun."Deep Residual Learning for Image Recognition" +2. Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu."Squeeze-and-Excitation Networks" +3. Tong He, Zhi Zhang, Hang Zhang, Zhongyue Zhang, Junyuan Xie, Mu Li."Bag of Tricks for Image Classification with Convolutional Neural Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/resnet50_quadruplet_sop.md b/mshub_res/assets/mindspore/1.5/resnet50_quadruplet_sop.md new file mode 100644 index 0000000..930f535 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/resnet50_quadruplet_sop.md @@ -0,0 +1,63 @@ +# metric_learn + +--- + +model-name: metric_learn + +backbone-name: metric_learn + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: sop + +evaluation: acc74 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 9897589daa93d4fbb80959f59b4c5319ff12ed495e7bfcd4cf3c895e6d1c3c21 + +license: Apache2.0 + +summary: metric_learn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of metric_learn from the MindSpore model zoo on Gitee at research/cv/metric_learn. + +metric_learn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/metric_learn](https://gitee.com/mindspore/models/blob/r1.5/research/cv/metric_learn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +1. CVPR2015 F Schroff, Kalenichenko D,Philbin J."FaceNet: A Unified Embedding for Face Recognition and Clustering" +2. CVPR2017 Chen W, Chen X, Zhang J."Beyond triplet loss: A deep quadruplet network for person re-identification" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/resnet50_triplet_sop.md b/mshub_res/assets/mindspore/1.5/resnet50_triplet_sop.md new file mode 100644 index 0000000..2b9b56d --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/resnet50_triplet_sop.md @@ -0,0 +1,63 @@ +# metric_learn + +--- + +model-name: metric_learn + +backbone-name: metric_learn + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: sop + +evaluation: acc73 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 7f5122938bfc0e9f372eda4901259009f6b71520fb1d75feb42f10efefc7550f + +license: Apache2.0 + +summary: metric_learn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of metric_learn from the MindSpore model zoo on Gitee at research/cv/metric_learn. + +metric_learn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/metric_learn](https://gitee.com/mindspore/models/blob/r1.5/research/cv/metric_learn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +1. CVPR2015 F Schroff, Kalenichenko D,Philbin J."FaceNet: A Unified Embedding for Face Recognition and Clustering" +2. CVPR2017 Chen W, Chen X, Zhang J."Beyond triplet loss: A deep quadruplet network for person re-identification" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/resnet50quant_imagenet2012.md b/mshub_res/assets/mindspore/1.5/resnet50quant_imagenet2012.md new file mode 100644 index 0000000..cdf54bd --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/resnet50quant_imagenet2012.md @@ -0,0 +1,79 @@ +# resnet50_quant + +--- + +model-name: resnet50_quant + +backbone-name: resnet50_quant + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc76 | top5acc92 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 621460f6d626d2c4643d8afd45bc62588580ed0faabc31a678ec00b8aacf9b5b + +license: Apache2.0 + +summary: resnet50_quant is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnet50_quant from the MindSpore model zoo on Gitee at official/cv/resnet50_quant. + +resnet50_quant is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnet50_quant](https://gitee.com/mindspore/models/blob/r1.5/official/cv/resnet50_quant/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/resnet50quant_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun."Deep Residual Learning for Image Recognition." He, Kaiming , et al. "Deep Residual Learning for Image Recognition." IEEE Conference on Computer Vision & Pattern Recognition IEEE Computer Society, 2016. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/resnet50thor_imagenet2012.md b/mshub_res/assets/mindspore/1.5/resnet50thor_imagenet2012.md new file mode 100644 index 0000000..5a39e40 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/resnet50thor_imagenet2012.md @@ -0,0 +1,75 @@ +# resnet_thor + +--- + +model-name: resnet_thor + +backbone-name: resnet_thor + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc76.08 | top5acc92.81 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: ad9b3b0bef58cbc204493b84dd0da3972acdceb4d273233a99f890adbc905ffc + +license: Apache2.0 + +summary: resnet_thor is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnet_thor from the MindSpore model zoo on Gitee at official/cv/resnet_thor. + +resnet_thor is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnet_thor](https://gitee.com/mindspore/models/blob/r1.5/official/cv/resnet_thor/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/resnet50thor_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/resnetv2101_cifar10.md b/mshub_res/assets/mindspore/1.5/resnetv2101_cifar10.md new file mode 100644 index 0000000..090f80b --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/resnetv2101_cifar10.md @@ -0,0 +1,62 @@ +# resnetv2 + +--- + +model-name: resnetv2 + +backbone-name: resnetv2 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cifar10 + +evaluation: acc95.15 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 183f9e5feaef51c792c45f55ccafb2dd0467ae8809aee7537827d674c26633f5 + +license: Apache2.0 + +summary: resnetv2 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnetv2 from the MindSpore model zoo on Gitee at research/cv/resnetv2. + +resnetv2 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/resnetv2](https://gitee.com/mindspore/models/blob/r1.5/research/cv/resnetv2/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. "Identity Mappings in Deep Residual Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/resnetv2152_cifar10.md b/mshub_res/assets/mindspore/1.5/resnetv2152_cifar10.md new file mode 100644 index 0000000..b2fee64 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/resnetv2152_cifar10.md @@ -0,0 +1,62 @@ +# resnetv2 + +--- + +model-name: resnetv2 + +backbone-name: resnetv2 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cifar10 + +evaluation: acc95.61 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 63c4f1fc267ede99ce4006bfba643d1732f0a8f55400ec8d6f9f3af72f559647 + +license: Apache2.0 + +summary: resnetv2 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnetv2 from the MindSpore model zoo on Gitee at research/cv/resnetv2. + +resnetv2 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/resnetv2](https://gitee.com/mindspore/models/blob/r1.5/research/cv/resnetv2/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. "Identity Mappings in Deep Residual Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/resnetv250_cifar10.md b/mshub_res/assets/mindspore/1.5/resnetv250_cifar10.md new file mode 100644 index 0000000..27fe944 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/resnetv250_cifar10.md @@ -0,0 +1,62 @@ +# resnetv2 + +--- + +model-name: resnetv2 + +backbone-name: resnetv2 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cifar10 + +evaluation: acc95.2 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d88993343168c69ee523052b7cd605fd0c7cb426dff6f033d7e2be068d05a9a3 + +license: Apache2.0 + +summary: resnetv2 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnetv2 from the MindSpore model zoo on Gitee at research/cv/resnetv2. + +resnetv2 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/resnetv2](https://gitee.com/mindspore/models/blob/r1.5/research/cv/resnetv2/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. "Identity Mappings in Deep Residual Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/resnext101_imagenet2012.md b/mshub_res/assets/mindspore/1.5/resnext101_imagenet2012.md new file mode 100644 index 0000000..3660655 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/resnext101_imagenet2012.md @@ -0,0 +1,79 @@ +# resnext + +--- + +model-name: resnext + +backbone-name: resnext + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc79.39 | top5acc94.62 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 83a09de8e7399c48d76fad179577da52bab3d0e667ec3d4501e5cdf1cbfc26d7 + +license: Apache2.0 + +summary: resnext is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnext from the MindSpore model zoo on Gitee at official/cv/resnext. + +resnext is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnext](https://gitee.com/mindspore/models/blob/r1.5/official/cv/resnext/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/resnext101_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Xie S, Girshick R, Dollár, Piotr, et al. Aggregated Residual Transformations for Deep Neural Networks. 2016. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/resnext15264x4d_imagenet2012.md b/mshub_res/assets/mindspore/1.5/resnext15264x4d_imagenet2012.md new file mode 100644 index 0000000..fc0929c --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/resnext15264x4d_imagenet2012.md @@ -0,0 +1,62 @@ +# resnext152_64x4d + +--- + +model-name: resnext152_64x4d + +backbone-name: resnext152_64x4d + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc79.94 | top5acc94.66 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 8045c5d89d7d2fbc0019bd4f519aba5e57e4d0d2a8fb55906718374b9a0792f0 + +license: Apache2.0 + +summary: resnext152_64x4d is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnext152_64x4d from the MindSpore model zoo on Gitee at research/cv/resnext152_64x4d. + +resnext152_64x4d is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/resnext152_64x4d](https://gitee.com/mindspore/models/blob/r1.5/research/cv/resnext152_64x4d/README.md). + +All parameters in the module are trainable. + +## Citation + +Xie S, Girshick R, Dollár, Piotr, et al. Aggregated Residual Transformations for Deep Neural Networks. 2016. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/resnext50_imagenet2012.md b/mshub_res/assets/mindspore/1.5/resnext50_imagenet2012.md new file mode 100644 index 0000000..47af598 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/resnext50_imagenet2012.md @@ -0,0 +1,79 @@ +# resnext + +--- + +model-name: resnext + +backbone-name: resnext + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc78.51 | top5acc94.18 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 22857131a4cc5186af07582907888c7cf0d8361aeb78545ca20bace4e8f3961e + +license: Apache2.0 + +summary: resnext is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnext from the MindSpore model zoo on Gitee at official/cv/resnext. + +resnext is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnext](https://gitee.com/mindspore/models/blob/r1.5/official/cv/resnext/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/resnext50_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Xie S, Girshick R, Dollár, Piotr, et al. Aggregated Residual Transformations for Deep Neural Networks. 2016. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/retinanet_coco2017.md b/mshub_res/assets/mindspore/1.5/retinanet_coco2017.md new file mode 100644 index 0000000..12c5b35 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/retinanet_coco2017.md @@ -0,0 +1,79 @@ +# retinanet + +--- + +model-name: retinanet + +backbone-name: retinanet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: acc35 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 2fda03174122089d884f7fde4115d51145a25d44cca6f9c02f0653a83d17cab6 + +license: Apache2.0 + +summary: retinanet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of retinanet from the MindSpore model zoo on Gitee at official/cv/retinanet. + +retinanet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/retinanet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/retinanet/README_CN.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/retinanet_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Lin T Y , Goyal P , Girshick R , et al. Focal Loss for Dense Object Detection[C]// 2017 IEEE International Conference on Computer Vision (ICCV). IEEE, 2017:2999-3007. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/retinanetresnet101_coco2017.md b/mshub_res/assets/mindspore/1.5/retinanetresnet101_coco2017.md new file mode 100644 index 0000000..d8e9cde --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/retinanetresnet101_coco2017.md @@ -0,0 +1,62 @@ +# retinanet_resnet101 + +--- + +model-name: retinanet_resnet101 + +backbone-name: retinanet_resnet101 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: acc36.39 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c58400d46600ce74f4cb1f28f513ead9defb7ad4fe100a7dada92d5a77d313c7 + +license: Apache2.0 + +summary: retinanet_resnet101 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of retinanet_resnet101 from the MindSpore model zoo on Gitee at research/cv/retinanet_resnet101. + +retinanet_resnet101 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/retinanet_resnet101](https://gitee.com/mindspore/models/blob/r1.5/research/cv/retinanet_resnet101/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Lin T Y , Goyal P , Girshick R , et al. Focal Loss for Dense Object Detection[C]// 2017 IEEE International Conference on Computer Vision (ICCV). IEEE, 2017:2999-3007. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/rotate_wn18rr.md b/mshub_res/assets/mindspore/1.5/rotate_wn18rr.md new file mode 100644 index 0000000..34f80ef --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/rotate_wn18rr.md @@ -0,0 +1,62 @@ +# rotate + +--- + +model-name: rotate + +backbone-name: rotate + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: wn18rr + +evaluation: MRR47 | MR3340 | HITS@1acc42 | HITS@3acc49 | HITS@10acc57 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d78bb8cb987c632060262a5de793fbb6c27dbc17241bd343e2d0a15fa3b76609 + +license: Apache2.0 + +summary: rotate is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of rotate from the MindSpore model zoo on Gitee at research/nlp/rotate. + +rotate is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [research/nlp/rotate](https://gitee.com/mindspore/models/blob/r1.5/research/nlp/rotate/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Zhiqing Sun, Zhi-Hong Deng, Jian-Yun Nie, Jian Tang: RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/senet_imagenet2012.md b/mshub_res/assets/mindspore/1.5/senet_imagenet2012.md new file mode 100644 index 0000000..529f81e --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/senet_imagenet2012.md @@ -0,0 +1,62 @@ +# SE-Net + +--- + +model-name: SE-Net + +backbone-name: SE-Net + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc77.75 | top5acc93.84 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 3abfaa11d0d9ef240641050df3a8c26a3e0f31e9484d10404a37246d7dc5f31c + +license: Apache2.0 + +summary: SE-Net is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of SE-Net from the MindSpore model zoo on Gitee at research/cv/SE-Net. + +SE-Net is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/SE-Net](https://gitee.com/mindspore/models/blob/r1.5/research/cv/SE-Net/README.md). + +All parameters in the module are trainable. + +## Citation + +Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu. "Squeeze-and-Excitation Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/seresnet50_imagenet2012.md b/mshub_res/assets/mindspore/1.5/seresnet50_imagenet2012.md new file mode 100644 index 0000000..2006e88 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/seresnet50_imagenet2012.md @@ -0,0 +1,81 @@ +# resnet + +--- + +model-name: resnet + +backbone-name: resnet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc76.75 | top5acc93.43 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: fae985bd431915d4f743375fced2bad4ad5f40aadd31b3c840151e11528d8d60 + +license: Apache2.0 + +summary: resnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnet from the MindSpore model zoo on Gitee at official/cv/resnet. + +resnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/resnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/seresnet50_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun."Deep Residual Learning for Image Recognition" +2. Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu."Squeeze-and-Excitation Networks" +3. Tong He, Zhi Zhang, Hang Zhang, Zhongyue Zhang, Junyuan Xie, Mu Li."Bag of Tricks for Image Classification with Convolutional Neural Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/seresnext50_imagenet2012.md b/mshub_res/assets/mindspore/1.5/seresnext50_imagenet2012.md new file mode 100644 index 0000000..751cd71 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/seresnext50_imagenet2012.md @@ -0,0 +1,62 @@ +# SE_ResNeXt50 + +--- + +model-name: SE_ResNeXt50 + +backbone-name: SE_ResNeXt50 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc79 | top5acc94 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: ba9443c3aa8ca6aa55fe4cbd23afb3aedd94573c1cea8d613ffad810baed55a6 + +license: Apache2.0 + +summary: SE_ResNeXt50 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of SE_ResNeXt50 from the MindSpore model zoo on Gitee at research/cv/SE_ResNeXt50. + +SE_ResNeXt50 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/SE_ResNeXt50](https://gitee.com/mindspore/models/blob/r1.5/research/cv/SE_ResNeXt50/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu."Squeeze-and-Excitation Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/shufflenetv1_imagenet2012.md b/mshub_res/assets/mindspore/1.5/shufflenetv1_imagenet2012.md new file mode 100644 index 0000000..91e0305 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/shufflenetv1_imagenet2012.md @@ -0,0 +1,79 @@ +# shufflenetv1 + +--- + +model-name: shufflenetv1 + +backbone-name: shufflenetv1 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc73.83 | top5acc91.54 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 9e484f77bf133ba65ecc6ac28c04d76e45fc822fdf4fb1636fd83dd30de0e462 + +license: Apache2.0 + +summary: shufflenetv1 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of shufflenetv1 from the MindSpore model zoo on Gitee at official/cv/shufflenetv1. + +shufflenetv1 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/shufflenetv1](https://gitee.com/mindspore/models/blob/r1.5/official/cv/shufflenetv1/README_CN.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/shufflenetv1_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Xiangyu Zhang, Xinyu Zhou, Mengxiao Lin, Jian Sun. "ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices." *Proceedings of the IEEE conference on computer vision and pattern recognition*. 2018. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/shufflenetv2_imagenet2012.md b/mshub_res/assets/mindspore/1.5/shufflenetv2_imagenet2012.md new file mode 100644 index 0000000..3d01ece --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/shufflenetv2_imagenet2012.md @@ -0,0 +1,79 @@ +# shufflenetv2 + +--- + +model-name: shufflenetv2 + +backbone-name: shufflenetv2 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc69.63 | top5acc88.72 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: e1100bc808f1cbb37664d776085b4d82b19b5c9853c44f143366d76f6414bcbb + +license: Apache2.0 + +summary: shufflenetv2 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of shufflenetv2 from the MindSpore model zoo on Gitee at official/cv/shufflenetv2. + +shufflenetv2 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/shufflenetv2](https://gitee.com/mindspore/models/blob/r1.5/official/cv/shufflenetv2/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/shufflenetv2_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Ma, N., Zhang, X., Zheng, H. T., & Sun, J. (2018). Shufflenet v2: Practical guidelines for efficient cnn architecture design. In Proceedings of the European conference on computer vision (ECCV) (pp. 116-131). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/siamfc_ilsvrc2015vid.md b/mshub_res/assets/mindspore/1.5/siamfc_ilsvrc2015vid.md new file mode 100644 index 0000000..42fd304 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/siamfc_ilsvrc2015vid.md @@ -0,0 +1,62 @@ +# SiamFC + +--- + +model-name: SiamFC + +backbone-name: SiamFC + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: ilsvrc2015vid + +evaluation: acc58.6 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 082586450b38aa49f4794fde27bb1368d65a515f9e9549ef78a37d74ff7e36aa + +license: Apache2.0 + +summary: SiamFC is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of SiamFC from the MindSpore model zoo on Gitee at research/cv/SiamFC. + +SiamFC is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/SiamFC](https://gitee.com/mindspore/models/blob/r1.5/research/cv/SiamFC/README.md). + +All parameters in the module are trainable. + +## Citation + +Luca Bertinetto Jack Valmadre Jo˜ao F. Henriques Andrea Vedaldi Philip H. S. Torr Department of Engineering Science, University of Oxford + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/simclr_encoder_cifar10.md b/mshub_res/assets/mindspore/1.5/simclr_encoder_cifar10.md new file mode 100644 index 0000000..a6548c8 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/simclr_encoder_cifar10.md @@ -0,0 +1,62 @@ +# simclr + +--- + +model-name: simclr + +backbone-name: simclr + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cifar10 + +evaluation: acc84.96 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 1a1c57d30a456fe89cb7a873f41632cc65147b4e2a2e93a0c2a8f31ebadfc71e + +license: Apache2.0 + +summary: simclr is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of simclr from the MindSpore model zoo on Gitee at official/cv/simclr. + +simclr is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/simclr](https://gitee.com/mindspore/models/blob/r1.5/official/cv/simclr/README.md). + +All parameters in the module are trainable. + +## Citation + +Ting Chen and Simon Kornblith and Mohammad Norouzi and Geoffrey Hinton. A Simple Framework for Contrastive Learning of Visual Representations. *arXiv preprint arXiv:2002.05709*. 2020. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/simclr_linearclassifier_cifar10.md b/mshub_res/assets/mindspore/1.5/simclr_linearclassifier_cifar10.md new file mode 100644 index 0000000..2431234 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/simclr_linearclassifier_cifar10.md @@ -0,0 +1,62 @@ +# simclr + +--- + +model-name: simclr + +backbone-name: simclr + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cifar10 + +evaluation: acc84.96 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 24e2b2afcb09694808fb2226e32c436eb63964dfe8e4504f0f23240c9a7f83cb + +license: Apache2.0 + +summary: simclr is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of simclr from the MindSpore model zoo on Gitee at official/cv/simclr. + +simclr is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/simclr](https://gitee.com/mindspore/models/blob/r1.5/official/cv/simclr/README.md). + +All parameters in the module are trainable. + +## Citation + +Ting Chen and Simon Kornblith and Mohammad Norouzi and Geoffrey Hinton. A Simple Framework for Contrastive Learning of Visual Representations. *arXiv preprint arXiv:2002.05709*. 2020. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/simplebaselines_coco2017.md b/mshub_res/assets/mindspore/1.5/simplebaselines_coco2017.md new file mode 100644 index 0000000..48bc216 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/simplebaselines_coco2017.md @@ -0,0 +1,62 @@ +# simple_baselines + +--- + +model-name: simple_baselines + +backbone-name: simple_baselines + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: acc72.3 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 31ad53e844b3a5301b8663e9b228c4eecdb904494ab605a1e9886f3956fbd00c + +license: Apache2.0 + +summary: simple_baselines is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of simple_baselines from the MindSpore model zoo on Gitee at research/cv/simple_baselines. + +simple_baselines is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/simple_baselines](https://gitee.com/mindspore/models/blob/r1.5/research/cv/simple_baselines/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Bin Xiao, Haiping Wu, Yichen Wei."Simple baselines for human pose estimation and tracking" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/simplepose_coco2017.md b/mshub_res/assets/mindspore/1.5/simplepose_coco2017.md new file mode 100644 index 0000000..6d80525 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/simplepose_coco2017.md @@ -0,0 +1,79 @@ +# simple_pose + +--- + +model-name: simple_pose + +backbone-name: simple_pose + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: acc70 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 206c944b9a756c17475c97864469cfb3c5e56b8737ecf6dccaf544b9fc75f0df + +license: Apache2.0 + +summary: simple_pose is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of simple_pose from the MindSpore model zoo on Gitee at official/cv/simple_pose. + +simple_pose is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/simple_pose](https://gitee.com/mindspore/models/blob/r1.5/official/cv/simple_pose/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/simplepose_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +B. Xiao, H. Wu, and Y. Wei, “Simple baselines for human pose estimation and tracking,” in Proc. Eur. Conf. Comput. Vis., 2018, pp. 472–487. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/singlepathnas_imagenet2012.md b/mshub_res/assets/mindspore/1.5/singlepathnas_imagenet2012.md new file mode 100644 index 0000000..970c8c0 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/singlepathnas_imagenet2012.md @@ -0,0 +1,58 @@ +# single_path_nas + +--- + +model-name: single_path_nas + +backbone-name: single_path_nas + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc74.22 | top5acc91.73 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 692cfdf824de2958ed92ffc178c9e55738ecd6c60a474e7d76ec99a4f0aa15ae + +license: Apache2.0 + +summary: single_path_nas is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of single_path_nas from the MindSpore model zoo on Gitee at research/cv/single_path_nas. + +single_path_nas is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/single_path_nas](https://gitee.com/mindspore/models/blob/r1.5/research/cv/single_path_nas/README_CN.md). + +All parameters in the module are trainable. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/skipgram_text8.md b/mshub_res/assets/mindspore/1.5/skipgram_text8.md new file mode 100644 index 0000000..e5d9b06 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/skipgram_text8.md @@ -0,0 +1,80 @@ +# skipgram + +--- + +model-name: skipgram + +backbone-name: skipgram + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: text8 + +evaluation: acc35.78 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5ce385cfc638b6ab2f10309fb4980792513458db4dfa1cc5adb2b2c382b1457a + +license: Apache2.0 + +summary: skipgram is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of skipgram from the MindSpore model zoo on Gitee at research/nlp/skipgram. + +skipgram is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [research/nlp/skipgram](https://gitee.com/mindspore/models/blob/r1.5/research/nlp/skipgram/README_CN.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/skipgram_text8" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Mikolov T, Chen K, Corrado G, et al. Efficient estimation of word representations in vector space[J]. arXiv preprint arXiv:1301.3781, 2013. +2. Mikolov T, Sutskever I, Chen K, et al. Distributed representations of words and phrases and their compositionality[J]. arXiv preprint arXiv:1310.4546, 2013. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/sknet_cifar10.md b/mshub_res/assets/mindspore/1.5/sknet_cifar10.md new file mode 100644 index 0000000..0ec107a --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/sknet_cifar10.md @@ -0,0 +1,62 @@ +# sknet + +--- + +model-name: sknet + +backbone-name: sknet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cifar10 + +evaluation: acc94 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 278db3c641d1be970d4fce82478f5e5b56f62ce4cbc8f122743a4093ba84014a + +license: Apache2.0 + +summary: sknet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of sknet from the MindSpore model zoo on Gitee at research/cv/sknet. + +sknet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/sknet](https://gitee.com/mindspore/models/blob/r1.5/research/cv/sknet/README.md). + +All parameters in the module are trainable. + +## Citation + +Xiang Li, Wenhai Wang, Xiaolin Hu, Jian Yang. "Selective Kernel Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/squeezenet11_imagenet2012.md b/mshub_res/assets/mindspore/1.5/squeezenet11_imagenet2012.md new file mode 100644 index 0000000..6de0354 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/squeezenet11_imagenet2012.md @@ -0,0 +1,62 @@ +# squeezenet1_1 + +--- + +model-name: squeezenet1_1 + +backbone-name: squeezenet1_1 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc58.51 | top5acc80.82 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c50c0293a9efbe2a9338bf41df6e8c399c4ef40511e9d27a5ebef83deea61252 + +license: Apache2.0 + +summary: squeezenet1_1 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of squeezenet1_1 from the MindSpore model zoo on Gitee at research/cv/squeezenet1_1. + +squeezenet1_1 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/squeezenet1_1](https://gitee.com/mindspore/models/blob/r1.5/research/cv/squeezenet1_1/README.md). + +All parameters in the module are trainable. + +## Citation + +Forrest N. Iandola and Song Han and Matthew W. Moskewicz and Khalid Ashraf and William J. Dally and Kurt Keutzer. "SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/squeezenet_cifar10.md b/mshub_res/assets/mindspore/1.5/squeezenet_cifar10.md new file mode 100644 index 0000000..d6f3a2d --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/squeezenet_cifar10.md @@ -0,0 +1,79 @@ +# squeezenet + +--- + +model-name: squeezenet + +backbone-name: squeezenet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cifar10 + +evaluation: top1acc83.6 | top5acc99.31 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 6c40f21ad01c31a3e528a31e19d5c9a6890db0f17fa1475183e1a04641d223f7 + +license: Apache2.0 + +summary: squeezenet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of squeezenet from the MindSpore model zoo on Gitee at official/cv/squeezenet. + +squeezenet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/squeezenet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/squeezenet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/squeezenet_cifar10" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Forrest N. Iandola and Song Han and Matthew W. Moskewicz and Khalid Ashraf and William J. Dally and Kurt Keutzer. "SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/squeezenetresidual_cifar10.md b/mshub_res/assets/mindspore/1.5/squeezenetresidual_cifar10.md new file mode 100644 index 0000000..017e227 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/squeezenetresidual_cifar10.md @@ -0,0 +1,79 @@ +# squeezenet + +--- + +model-name: squeezenet + +backbone-name: squeezenet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cifar10 + +evaluation: top1acc87.25 | top5acc99.57 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5451da81fe3644f6ed2cae202aed49d08780de576b81828db2bfd3f293096e93 + +license: Apache2.0 + +summary: squeezenet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of squeezenet from the MindSpore model zoo on Gitee at official/cv/squeezenet. + +squeezenet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/squeezenet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/squeezenet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/squeezenetresidual_cifar10" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Forrest N. Iandola and Song Han and Matthew W. Moskewicz and Khalid Ashraf and William J. Dally and Kurt Keutzer. "SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/squeezenetresidual_imagenet2012.md b/mshub_res/assets/mindspore/1.5/squeezenetresidual_imagenet2012.md new file mode 100644 index 0000000..60f7f5e --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/squeezenetresidual_imagenet2012.md @@ -0,0 +1,79 @@ +# squeezenet + +--- + +model-name: squeezenet + +backbone-name: squeezenet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc60.81 | top5acc82.55 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 1de97504c15df754cd37738b6b5bb89bdbe87a722c90c5e250e277985b075e35 + +license: Apache2.0 + +summary: squeezenet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of squeezenet from the MindSpore model zoo on Gitee at official/cv/squeezenet. + +squeezenet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/squeezenet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/squeezenet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/squeezenetresidual_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Forrest N. Iandola and Song Han and Matthew W. Moskewicz and Khalid Ashraf and William J. Dally and Kurt Keutzer. "SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/srcnn_ilsvrc2013.md b/mshub_res/assets/mindspore/1.5/srcnn_ilsvrc2013.md new file mode 100644 index 0000000..4eea474 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/srcnn_ilsvrc2013.md @@ -0,0 +1,62 @@ +# srcnn + +--- + +model-name: srcnn + +backbone-name: srcnn + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: ilsvrc2013 + +evaluation: set5acc36.65 | set14acc32.57 | bsd200acc33.77 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: a55d5c782c1d131cefca86ad0c823fcbe610496429a552a39e0276b47428f212 + +license: Apache2.0 + +summary: srcnn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of srcnn from the MindSpore model zoo on Gitee at official/cv/srcnn. + +srcnn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/srcnn](https://gitee.com/mindspore/models/blob/r1.5/official/cv/srcnn/README.md). + +All parameters in the module are trainable. + +## Citation + +Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang. Image Super-Resolution Using Deep Convolutional Networks. 2014. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/srgan_div2k.md b/mshub_res/assets/mindspore/1.5/srgan_div2k.md new file mode 100644 index 0000000..b340a79 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/srgan_div2k.md @@ -0,0 +1,62 @@ +# SRGAN + +--- + +model-name: SRGAN + +backbone-name: SRGAN + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: div2k + +evaluation: psnr27.22 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5ec7e2e43b4e9abdee38e5bdb8f3703571c884f4827629065bd504822641ecc9 + +license: Apache2.0 + +summary: SRGAN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of SRGAN from the MindSpore model zoo on Gitee at research/cv/SRGAN. + +SRGAN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/SRGAN](https://gitee.com/mindspore/models/blob/r1.5/research/cv/SRGAN/README.md). + +All parameters in the module are trainable. + +## Citation + +Christian Ledig, Lucas thesis, Ferenc Huszar, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, Wenzhe Shi Twitter. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/ssd300_coco2017.md b/mshub_res/assets/mindspore/1.5/ssd300_coco2017.md new file mode 100644 index 0000000..5e08420 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/ssd300_coco2017.md @@ -0,0 +1,79 @@ +# ssd + +--- + +model-name: ssd + +backbone-name: ssd + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: acc23 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d0b0449bab807e03528c88498425921a7a43a8d97fdd92bed6cf25d5b3379b07 + +license: Apache2.0 + +summary: ssd is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ssd from the MindSpore model zoo on Gitee at official/cv/ssd. + +ssd is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/ssd](https://gitee.com/mindspore/models/blob/r1.5/official/cv/ssd/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/ssd300_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg.European Conference on Computer Vision (ECCV), 2016 (In press). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/ssdghostnet_coco2017.md b/mshub_res/assets/mindspore/1.5/ssdghostnet_coco2017.md new file mode 100644 index 0000000..8f71b6d --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/ssdghostnet_coco2017.md @@ -0,0 +1,79 @@ +# ssd_ghostnet + +--- + +model-name: ssd_ghostnet + +backbone-name: ssd_ghostnet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: acc24.26 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: a1893fc926f7d721952733e7c42557520e7933060b5eb35bb0fec31d0b19dd1a + +license: Apache2.0 + +summary: ssd_ghostnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ssd_ghostnet from the MindSpore model zoo on Gitee at research/cv/ssd_ghostnet. + +ssd_ghostnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ssd_ghostnet](https://gitee.com/mindspore/models/blob/r1.5/research/cv/ssd_ghostnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/ssdghostnet_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg.European Conference on Computer Vision (ECCV), 2016 (In press). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/ssdmobilenetv1fpn_coco2017.md b/mshub_res/assets/mindspore/1.5/ssdmobilenetv1fpn_coco2017.md new file mode 100644 index 0000000..8389d4b --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/ssdmobilenetv1fpn_coco2017.md @@ -0,0 +1,79 @@ +# ssd + +--- + +model-name: ssd + +backbone-name: ssd + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: acc35.11 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5ff919cd507500f18f184c9174d66336edd2afcf8e18d6d9fc85a6d5bd59d4a8 + +license: Apache2.0 + +summary: ssd is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ssd from the MindSpore model zoo on Gitee at official/cv/ssd. + +ssd is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/ssd](https://gitee.com/mindspore/models/blob/r1.5/official/cv/ssd/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/ssdmobilenetv1fpn_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg.European Conference on Computer Vision (ECCV), 2016 (In press). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/ssdmobilenetv2_coco2017.md b/mshub_res/assets/mindspore/1.5/ssdmobilenetv2_coco2017.md new file mode 100644 index 0000000..dda259e --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/ssdmobilenetv2_coco2017.md @@ -0,0 +1,62 @@ +# ssd_mobilenetV2 + +--- + +model-name: ssd_mobilenetV2 + +backbone-name: ssd_mobilenetV2 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: acc24 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 6da31f6eeee4d350e9bb658efbd697342d28f6a3b13fd5cb3e6aca2dc64707bb + +license: Apache2.0 + +summary: ssd_mobilenetV2 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ssd_mobilenetV2 from the MindSpore model zoo on Gitee at research/cv/ssd_mobilenetV2. + +ssd_mobilenetV2 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ssd_mobilenetV2](https://gitee.com/mindspore/models/blob/r1.5/research/cv/ssd_mobilenetV2/README.md). + +All parameters in the module are trainable. + +## Citation + +Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg.European Conference on Computer Vision (ECCV), 2016 (In press). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/ssdmobilenetv2fpnlite_coco2017.md b/mshub_res/assets/mindspore/1.5/ssdmobilenetv2fpnlite_coco2017.md new file mode 100644 index 0000000..5361d2f --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/ssdmobilenetv2fpnlite_coco2017.md @@ -0,0 +1,62 @@ +# ssd_mobilenetV2_FPNlite + +--- + +model-name: ssd_mobilenetV2_FPNlite + +backbone-name: ssd_mobilenetV2_FPNlite + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: acc25.53 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 3cd83784a509fb83ea85a86277f61e1b3a90e17f86b826153a3ffcd3bd0d8b11 + +license: Apache2.0 + +summary: ssd_mobilenetV2_FPNlite is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ssd_mobilenetV2_FPNlite from the MindSpore model zoo on Gitee at research/cv/ssd_mobilenetV2_FPNlite. + +ssd_mobilenetV2_FPNlite is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ssd_mobilenetV2_FPNlite](https://gitee.com/mindspore/models/blob/r1.5/research/cv/ssd_mobilenetV2_FPNlite/README.md). + +All parameters in the module are trainable. + +## Citation + +Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg.European Conference on Computer Vision (ECCV), 2016 (In press). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/ssdresnet50_coco2017.md b/mshub_res/assets/mindspore/1.5/ssdresnet50_coco2017.md new file mode 100644 index 0000000..6d6790e --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/ssdresnet50_coco2017.md @@ -0,0 +1,79 @@ +# ssd_resnet50 + +--- + +model-name: ssd_resnet50 + +backbone-name: ssd_resnet50 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: acc32.2 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: fa1e8c98113823174646d933ffa5f0edae7f7da0f66ca6eca697d7b6008e9226 + +license: Apache2.0 + +summary: ssd_resnet50 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ssd_resnet50 from the MindSpore model zoo on Gitee at research/cv/ssd_resnet50. + +ssd_resnet50 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ssd_resnet50](https://gitee.com/mindspore/models/blob/r1.5/research/cv/ssd_resnet50/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/ssdresnet50_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg.European Conference on Computer Vision (ECCV), 2016 (In press). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/ssdresnet50fpn_coco2017.md b/mshub_res/assets/mindspore/1.5/ssdresnet50fpn_coco2017.md new file mode 100644 index 0000000..6fa1d36 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/ssdresnet50fpn_coco2017.md @@ -0,0 +1,79 @@ +# ssd + +--- + +model-name: ssd + +backbone-name: ssd + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: acc37.56 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5bf0dc1251ceca4bccc7fa1c42b972188901bf668c4fdf08b0856f6fb3a2bcd1 + +license: Apache2.0 + +summary: ssd is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ssd from the MindSpore model zoo on Gitee at official/cv/ssd. + +ssd is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/ssd](https://gitee.com/mindspore/models/blob/r1.5/official/cv/ssd/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/ssdresnet50fpn_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg.European Conference on Computer Vision (ECCV), 2016 (In press). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/ssdvgg16_coco2017.md b/mshub_res/assets/mindspore/1.5/ssdvgg16_coco2017.md new file mode 100644 index 0000000..9cf464b --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/ssdvgg16_coco2017.md @@ -0,0 +1,79 @@ +# ssd + +--- + +model-name: ssd + +backbone-name: ssd + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: acc23.39 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 03ee602a3dcecd3999fc8b3bec633467e8a7ce72de02a214e654d2c51430a4fa + +license: Apache2.0 + +summary: ssd is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ssd from the MindSpore model zoo on Gitee at official/cv/ssd. + +ssd is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/ssd](https://gitee.com/mindspore/models/blob/r1.5/official/cv/ssd/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/ssdvgg16_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg.European Conference on Computer Vision (ECCV), 2016 (In press). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/stackedhourglass_mpii.md b/mshub_res/assets/mindspore/1.5/stackedhourglass_mpii.md new file mode 100644 index 0000000..c49e303 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/stackedhourglass_mpii.md @@ -0,0 +1,62 @@ +# StackedHourglass + +--- + +model-name: StackedHourglass + +backbone-name: StackedHourglass + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: mpii + +evaluation: acc87.7 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 61919979915eb5083883e241aa92585b55a8c09f44f5f36c9e18022af6e9f6d6 + +license: Apache2.0 + +summary: StackedHourglass is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of StackedHourglass from the MindSpore model zoo on Gitee at research/cv/StackedHourglass. + +StackedHourglass is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/StackedHourglass](https://gitee.com/mindspore/models/blob/r1.5/research/cv/StackedHourglass/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Stacked Hourglass Networks for Human Pose Estimation + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/stargan_G_celeba.md b/mshub_res/assets/mindspore/1.5/stargan_G_celeba.md new file mode 100644 index 0000000..b548bac --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/stargan_G_celeba.md @@ -0,0 +1,62 @@ +# StarGAN + +--- + +model-name: StarGAN + +backbone-name: StarGAN + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: celeba + +evaluation: no + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d3784354455957b431cd751e093c9645d27f4a225279011d69f894811aff558e + +license: Apache2.0 + +summary: StarGAN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of StarGAN from the MindSpore model zoo on Gitee at research/cv/StarGAN. + +StarGAN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/StarGAN](https://gitee.com/mindspore/models/blob/r1.5/research/cv/StarGAN/README.md). + +All parameters in the module are trainable. + +## Citation + +StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/stgcn_cheb15_pemsd7m.md b/mshub_res/assets/mindspore/1.5/stgcn_cheb15_pemsd7m.md new file mode 100644 index 0000000..bb35560 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/stgcn_cheb15_pemsd7m.md @@ -0,0 +1,62 @@ +# stgcn + +--- + +model-name: stgcn + +backbone-name: stgcn + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: pemsd7m + +evaluation: mae2.22 | mape5.27 | rmse4.05 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 72a56d2a94902b3e39bd4f7209d03fdbb7297c9fea7b4a962dc9e3bdfbc27ebb + +license: Apache2.0 + +summary: stgcn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of stgcn from the MindSpore model zoo on Gitee at research/cv/stgcn. + +stgcn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/stgcn](https://gitee.com/mindspore/models/blob/r1.5/research/cv/stgcn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Bing yu, Haoteng Yin, and Zhanxing Zhu. "Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting." Proceedings of the 27th International Joint Conference on Artificial Intelligence. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/stgcn_cheb30_pemsd7m.md b/mshub_res/assets/mindspore/1.5/stgcn_cheb30_pemsd7m.md new file mode 100644 index 0000000..42cf223 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/stgcn_cheb30_pemsd7m.md @@ -0,0 +1,62 @@ +# stgcn + +--- + +model-name: stgcn + +backbone-name: stgcn + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: pemsd7m + +evaluation: mae2.89 | mape7.35 | rmse5.43 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 8ff99b5672b05a8df426d9a2c465cbcb2cdfffaf6234408ab917c4c1e946563d + +license: Apache2.0 + +summary: stgcn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of stgcn from the MindSpore model zoo on Gitee at research/cv/stgcn. + +stgcn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/stgcn](https://gitee.com/mindspore/models/blob/r1.5/research/cv/stgcn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Bing yu, Haoteng Yin, and Zhanxing Zhu. "Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting." Proceedings of the 27th International Joint Conference on Artificial Intelligence. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/stgcn_cheb45_pemsd7m.md b/mshub_res/assets/mindspore/1.5/stgcn_cheb45_pemsd7m.md new file mode 100644 index 0000000..0f4db71 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/stgcn_cheb45_pemsd7m.md @@ -0,0 +1,62 @@ +# stgcn + +--- + +model-name: stgcn + +backbone-name: stgcn + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: pemsd7m + +evaluation: mae3.22 | mape8.37 | rmse6.09 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 75da728efa227e2c6333d5a529d190c8dfb14eea475c7e4dc780d08acd0d2645 + +license: Apache2.0 + +summary: stgcn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of stgcn from the MindSpore model zoo on Gitee at research/cv/stgcn. + +stgcn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/stgcn](https://gitee.com/mindspore/models/blob/r1.5/research/cv/stgcn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Bing yu, Haoteng Yin, and Zhanxing Zhu. "Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting." Proceedings of the 27th International Joint Conference on Artificial Intelligence. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/stgcn_gcn15_pemsd7m.md b/mshub_res/assets/mindspore/1.5/stgcn_gcn15_pemsd7m.md new file mode 100644 index 0000000..d1dd325 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/stgcn_gcn15_pemsd7m.md @@ -0,0 +1,62 @@ +# stgcn + +--- + +model-name: stgcn + +backbone-name: stgcn + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: pemsd7m + +evaluation: mae2.22 | mape5.38 | rmse4.06 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 1db5f527a97596ee870cacd2029dd87d8a61b70ab32d10ed13ef5bf97e72103e + +license: Apache2.0 + +summary: stgcn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of stgcn from the MindSpore model zoo on Gitee at research/cv/stgcn. + +stgcn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/stgcn](https://gitee.com/mindspore/models/blob/r1.5/research/cv/stgcn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Bing yu, Haoteng Yin, and Zhanxing Zhu. "Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting." Proceedings of the 27th International Joint Conference on Artificial Intelligence. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/stgcn_gcn30_pemsd7m.md b/mshub_res/assets/mindspore/1.5/stgcn_gcn30_pemsd7m.md new file mode 100644 index 0000000..c2a6233 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/stgcn_gcn30_pemsd7m.md @@ -0,0 +1,62 @@ +# stgcn + +--- + +model-name: stgcn + +backbone-name: stgcn + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: pemsd7m + +evaluation: mae2.88 | mape7.22 | rmse5.38 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 25f13d7b960f9c9838737efeada659b09ff8109b3a3b78b33da270a1c4f7c617 + +license: Apache2.0 + +summary: stgcn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of stgcn from the MindSpore model zoo on Gitee at research/cv/stgcn. + +stgcn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/stgcn](https://gitee.com/mindspore/models/blob/r1.5/research/cv/stgcn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Bing yu, Haoteng Yin, and Zhanxing Zhu. "Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting." Proceedings of the 27th International Joint Conference on Artificial Intelligence. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/stgcn_gcn45_pemsd7m.md b/mshub_res/assets/mindspore/1.5/stgcn_gcn45_pemsd7m.md new file mode 100644 index 0000000..8e6716d --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/stgcn_gcn45_pemsd7m.md @@ -0,0 +1,62 @@ +# stgcn + +--- + +model-name: stgcn + +backbone-name: stgcn + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: pemsd7m + +evaluation: mae3.2 | mape8.32 | rmse6.08 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: f649e6cd1537acdc2759c33615b85373227b2b4153cec27fc708012bc9783ca7 + +license: Apache2.0 + +summary: stgcn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of stgcn from the MindSpore model zoo on Gitee at research/cv/stgcn. + +stgcn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/stgcn](https://gitee.com/mindspore/models/blob/r1.5/research/cv/stgcn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Bing yu, Haoteng Yin, and Zhanxing Zhu. "Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting." Proceedings of the 27th International Joint Conference on Artificial Intelligence. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/tacotron2_ljspeech1.1.md b/mshub_res/assets/mindspore/1.5/tacotron2_ljspeech1.1.md new file mode 100644 index 0000000..6432671 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/tacotron2_ljspeech1.1.md @@ -0,0 +1,62 @@ +# tacotron2 + +--- + +model-name: tacotron2 + +backbone-name: tacotron2 + +module-type: audio + +fine-tunable: True + +model-version: 1.5 + +train-dataset: ljspeech1.1 + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 12176c49d868e86841b96f9f6517f1e28287a203ec67137b76d59bfdc1e19a62 + +license: Apache2.0 + +summary: tacotron2 is used for audio + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of tacotron2 from the MindSpore model zoo on Gitee at research/audio/tacotron2. + +tacotron2 is a audio network. More details please refer to the MindSpore model zoo on Gitee at [research/audio/tacotron2](https://gitee.com/mindspore/models/blob/r1.5/research/audio/tacotron2/README.md). + +All parameters in the module are trainable. + +## Citation + +Jonathan, et al. Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/textcnn_moviereview.md b/mshub_res/assets/mindspore/1.5/textcnn_moviereview.md new file mode 100644 index 0000000..2f2ecac --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/textcnn_moviereview.md @@ -0,0 +1,79 @@ +# textcnn + +--- + +model-name: textcnn + +backbone-name: textcnn + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: moviereview + +evaluation: acc77.44 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c3f83fae12202952e0b0f12abb9032208bb0c55d9c001e383d5e005cc256f052 + +license: Apache2.0 + +summary: textcnn is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of textcnn from the MindSpore model zoo on Gitee at official/nlp/textcnn. + +textcnn is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/textcnn](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/textcnn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/textcnn_moviereview" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Kim Y. Convolutional neural networks for sentence classification[J]. arXiv preprint arXiv:1408.5882, 2014. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/textcnn_sst2.md b/mshub_res/assets/mindspore/1.5/textcnn_sst2.md new file mode 100644 index 0000000..50a6915 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/textcnn_sst2.md @@ -0,0 +1,79 @@ +# textcnn + +--- + +model-name: textcnn + +backbone-name: textcnn + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: sst2 + +evaluation: acc82.91 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 7130c9d6d615f72caf1e27340de952f907ebe31a98886a57c0c38779c2eee6b7 + +license: Apache2.0 + +summary: textcnn is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of textcnn from the MindSpore model zoo on Gitee at official/nlp/textcnn. + +textcnn is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/textcnn](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/textcnn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/textcnn_sst2" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Kim Y. Convolutional neural networks for sentence classification[J]. arXiv preprint arXiv:1408.5882, 2014. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/textcnn_subj.md b/mshub_res/assets/mindspore/1.5/textcnn_subj.md new file mode 100644 index 0000000..f931c64 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/textcnn_subj.md @@ -0,0 +1,79 @@ +# textcnn + +--- + +model-name: textcnn + +backbone-name: textcnn + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: subj + +evaluation: acc90.17 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 104ce6ddf0555a1c10b1dc21204e7071e3d68141b3380a573517245d0ef819fb + +license: Apache2.0 + +summary: textcnn is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of textcnn from the MindSpore model zoo on Gitee at official/nlp/textcnn. + +textcnn is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/textcnn](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/textcnn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/textcnn_subj" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Kim Y. Convolutional neural networks for sentence classification[J]. arXiv preprint arXiv:1408.5882, 2014. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/textcrnn_gru_polarity_moviereview.md b/mshub_res/assets/mindspore/1.5/textcrnn_gru_polarity_moviereview.md new file mode 100644 index 0000000..6fb83cb --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/textcrnn_gru_polarity_moviereview.md @@ -0,0 +1,79 @@ +# textrcnn + +--- + +model-name: textrcnn + +backbone-name: textrcnn + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: polarity_moviereview + +evaluation: acc81.05 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 24768f71515678d7ce0c525896a990652f79148d8ebcfa6f21a3b31a4d12826b + +license: Apache2.0 + +summary: textrcnn is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of textrcnn from the MindSpore model zoo on Gitee at research/nlp/textrcnn. + +textrcnn is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [research/nlp/textrcnn](https://gitee.com/mindspore/models/blob/r1.5/research/nlp/textrcnn/readme.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/textcrnn_gru_polarity_moviereview" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Siwei Lai, Liheng Xu, Kang Liu, Jun Zhao: Recurrent Convolutional Neural Networks for Text Classification. AAAI 2015: 2267-2273 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/textcrnn_lstm_polarity_moviereview.md b/mshub_res/assets/mindspore/1.5/textcrnn_lstm_polarity_moviereview.md new file mode 100644 index 0000000..dd88384 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/textcrnn_lstm_polarity_moviereview.md @@ -0,0 +1,79 @@ +# textrcnn + +--- + +model-name: textrcnn + +backbone-name: textrcnn + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: polarity_moviereview + +evaluation: acc80.76 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5f9d9fbf78b31fb4f51d3b5c9e92f1a97b0e4388b11b060ad4001307e1615e74 + +license: Apache2.0 + +summary: textrcnn is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of textrcnn from the MindSpore model zoo on Gitee at research/nlp/textrcnn. + +textrcnn is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [research/nlp/textrcnn](https://gitee.com/mindspore/models/blob/r1.5/research/nlp/textrcnn/readme.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/textcrnn_lstm_polarity_moviereview" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Siwei Lai, Liheng Xu, Kang Liu, Jun Zhao: Recurrent Convolutional Neural Networks for Text Classification. AAAI 2015: 2267-2273 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/tgcn_losloop.md b/mshub_res/assets/mindspore/1.5/tgcn_losloop.md new file mode 100644 index 0000000..1bf427a --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/tgcn_losloop.md @@ -0,0 +1,62 @@ +# tgcn + +--- + +model-name: tgcn + +backbone-name: tgcn + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: losloop + +evaluation: acc91.21 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 0b3162244fffca2e0ca5658e59ac4d80aaecf216dd4b4cf16c962e82da9cd26c + +license: Apache2.0 + +summary: tgcn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of tgcn from the MindSpore model zoo on Gitee at research/cv/tgcn. + +tgcn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/tgcn](https://gitee.com/mindspore/models/blob/r1.5/research/cv/tgcn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +3848-3858.Zhao L, Song Y, Zhang C, et al. T-gcn: A temporal graph convolutional network for traffic prediction[J]. IEEE Transactions on Intelligent Transportation Systems, 2019, 21(9): 3848-3858. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/tgcn_sztaxi.md b/mshub_res/assets/mindspore/1.5/tgcn_sztaxi.md new file mode 100644 index 0000000..58b4a1e --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/tgcn_sztaxi.md @@ -0,0 +1,62 @@ +# tgcn + +--- + +model-name: tgcn + +backbone-name: tgcn + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: sztaxi + +evaluation: acc71.56 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c79c54aff6d58c82d097fc3754788017cd03ca916a585a775b6c692a7c9a0d41 + +license: Apache2.0 + +summary: tgcn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of tgcn from the MindSpore model zoo on Gitee at research/cv/tgcn. + +tgcn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/tgcn](https://gitee.com/mindspore/models/blob/r1.5/research/cv/tgcn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Zhao L, Song Y, Zhang C, et al. T-gcn: A temporal graph convolutional network for traffic prediction[J]. IEEE Transactions on Intelligent Transportation Systems, 2019, 21(9): 3848-3858. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/tinybert_enwiki128_mnli.md b/mshub_res/assets/mindspore/1.5/tinybert_enwiki128_mnli.md new file mode 100644 index 0000000..32a05a9 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/tinybert_enwiki128_mnli.md @@ -0,0 +1,79 @@ +# tinybert + +--- + +model-name: tinybert + +backbone-name: tinybert + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: enwiki128_mnli + +evaluation: acc81.31 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 71dc99d4f2c9a369760fe1620bd2a48e611bbc7bbe15bfd564e69f4d0fee6d82 + +license: Apache2.0 + +summary: tinybert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of tinybert from the MindSpore model zoo on Gitee at official/nlp/tinybert. + +tinybert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/tinybert](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/tinybert/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/tinybert_enwiki128_mnli" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, Qun Liu. TinyBERT: Distilling BERT for Natural Language Understanding. arXiv preprint arXiv:1909.10351. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/tinybert_enwiki128_qnli.md b/mshub_res/assets/mindspore/1.5/tinybert_enwiki128_qnli.md new file mode 100644 index 0000000..231b569 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/tinybert_enwiki128_qnli.md @@ -0,0 +1,79 @@ +# tinybert + +--- + +model-name: tinybert + +backbone-name: tinybert + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: enwiki128_qnli + +evaluation: acc88.86 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d33ae2a4548502bc392ed286d7dfb17102efc5ca8a9203b70b40df6a381d52ed + +license: Apache2.0 + +summary: tinybert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of tinybert from the MindSpore model zoo on Gitee at official/nlp/tinybert. + +tinybert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/tinybert](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/tinybert/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/tinybert_enwiki128_qnli" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, Qun Liu. TinyBERT: Distilling BERT for Natural Language Understanding. arXiv preprint arXiv:1909.10351. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/tinybert_enwiki128_sst2.md b/mshub_res/assets/mindspore/1.5/tinybert_enwiki128_sst2.md new file mode 100644 index 0000000..d00d5b9 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/tinybert_enwiki128_sst2.md @@ -0,0 +1,79 @@ +# tinybert + +--- + +model-name: tinybert + +backbone-name: tinybert + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: enwiki128_sst2 + +evaluation: acc90.28 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5d9df51b52990a6d20e500923163076dff8fb3821d791c50e1255588cb8b219d + +license: Apache2.0 + +summary: tinybert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of tinybert from the MindSpore model zoo on Gitee at official/nlp/tinybert. + +tinybert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/tinybert](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/tinybert/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/tinybert_enwiki128_sst2" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, Qun Liu. TinyBERT: Distilling BERT for Natural Language Understanding. arXiv preprint arXiv:1909.10351. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/tinydarknet_imagenet2012.md b/mshub_res/assets/mindspore/1.5/tinydarknet_imagenet2012.md new file mode 100644 index 0000000..0f87cb7 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/tinydarknet_imagenet2012.md @@ -0,0 +1,75 @@ +# tinydarknet + +--- + +model-name: tinydarknet + +backbone-name: tinydarknet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc59.0 | top5acc81.84 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 00a1544972eaeecec147e15dfa49c1796368c054776d59a73a7e905c285b6256 + +license: Apache2.0 + +summary: tinydarknet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of tinydarknet from the MindSpore model zoo on Gitee at official/cv/tinydarknet. + +tinydarknet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/tinydarknet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/tinydarknet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/tinydarknet_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/transformer_wmt.md b/mshub_res/assets/mindspore/1.5/transformer_wmt.md new file mode 100644 index 0000000..5e70f02 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/transformer_wmt.md @@ -0,0 +1,79 @@ +# transformer + +--- + +model-name: transformer + +backbone-name: transformer + +module-type: nlp + +fine-tunable: True + +model-version: 1.5 + +train-dataset: wmt + +evaluation: acc27.21 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: b322b9e912295d6f6dae34381488c8fa8676fd4759aae178f77b05acebb3dc0f + +license: Apache2.0 + +summary: transformer is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of transformer from the MindSpore model zoo on Gitee at official/nlp/transformer. + +transformer is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/transformer](https://gitee.com/mindspore/models/blob/r1.5/official/nlp/transformer/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/transformer_wmt" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Ashish Vaswani, Noam Shazeer, Niki Parmar, JakobUszkoreit, Llion Jones, Aidan N Gomez, Ł ukaszKaiser, and Illia Polosukhin. 2017. Attention is all you need. In NIPS 2017, pages 5998–6008. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/unet3d_luna16.md b/mshub_res/assets/mindspore/1.5/unet3d_luna16.md new file mode 100644 index 0000000..272c94c --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/unet3d_luna16.md @@ -0,0 +1,79 @@ +# unet3d + +--- + +model-name: unet3d + +backbone-name: unet3d + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: luna16 + +evaluation: acc96.54 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 557eb7c3914428458f037bdf6d9320015021ebb3ccdb9740fe01823eed41027a + +license: Apache2.0 + +summary: unet3d is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of unet3d from the MindSpore model zoo on Gitee at official/cv/unet3d. + +unet3d is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/unet3d](https://gitee.com/mindspore/models/blob/r1.5/official/cv/unet3d/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/unet3d_luna16" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Unet3D: Learning Dense VolumetricSegmentation from Sparse Annotation. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/unet_medical_isbi.md b/mshub_res/assets/mindspore/1.5/unet_medical_isbi.md new file mode 100644 index 0000000..6f140dc --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/unet_medical_isbi.md @@ -0,0 +1,80 @@ +# unet + +--- + +model-name: unet + +backbone-name: unet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: isbi + +evaluation: acc91.39 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 10a70d0264ff08f20b2887fb25f8676bd5eb0be61a9e48986ae63ca86667873a + +license: Apache2.0 + +summary: unet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of unet from the MindSpore model zoo on Gitee at official/cv/unet. + +unet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/unet](https://gitee.com/mindspore/models/blob/r1.5/official/cv/unet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/unet_medical_isbi" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Olaf Ronneberger, Philipp Fischer, Thomas Brox. "U-Net: Convolutional Networks for Biomedical Image Segmentation." conditionally accepted at MICCAI 2015. 2015. +2. Z. Zhou, M. M. R. Siddiquee, N. Tajbakhsh and J. Liang, "UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation," in IEEE Transactions on Medical Imaging, vol. 39, no. 6, pp. 1856-1867, June 2020, doi: 10.1109/TMI.2019.2959609. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/vgg16_bn_imagenet2012.md b/mshub_res/assets/mindspore/1.5/vgg16_bn_imagenet2012.md new file mode 100644 index 0000000..c23d9bc --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/vgg16_bn_imagenet2012.md @@ -0,0 +1,79 @@ +# vgg16 + +--- + +model-name: vgg16 + +backbone-name: vgg16 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc74.33 | top5acc92.1 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: e12b2eb08c1c32001a6f5873fa80b6430919949c5a8d4515469ea351eb416afa + +license: Apache2.0 + +summary: vgg16 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of vgg16 from the MindSpore model zoo on Gitee at official/cv/vgg16. + +vgg16 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/vgg16](https://gitee.com/mindspore/models/blob/r1.5/official/cv/vgg16/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/vgg16_bn_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Simonyan K, zisserman A. Very Deep Convolutional Networks for Large-Scale Image Recognition[J]. arXiv preprint arXiv:1409.1556, 2014. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/vgg16_cifar10.md b/mshub_res/assets/mindspore/1.5/vgg16_cifar10.md new file mode 100644 index 0000000..b34cc83 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/vgg16_cifar10.md @@ -0,0 +1,79 @@ +# vgg16 + +--- + +model-name: vgg16 + +backbone-name: vgg16 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cifar10 + +evaluation: acc93.44 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 0ad3742ac1e20bd06c50fe5bfce0d23e4df3e5baf976e360412093a23546f969 + +license: Apache2.0 + +summary: vgg16 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of vgg16 from the MindSpore model zoo on Gitee at official/cv/vgg16. + +vgg16 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/vgg16](https://gitee.com/mindspore/models/blob/r1.5/official/cv/vgg16/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/vgg16_cifar10" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Simonyan K, zisserman A. Very Deep Convolutional Networks for Large-Scale Image Recognition[J]. arXiv preprint arXiv:1409.1556, 2014. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/vgg16_imagenet2012.md b/mshub_res/assets/mindspore/1.5/vgg16_imagenet2012.md new file mode 100644 index 0000000..994bff2 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/vgg16_imagenet2012.md @@ -0,0 +1,79 @@ +# vgg16 + +--- + +model-name: vgg16 + +backbone-name: vgg16 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc73.49 | top5acc91.56 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: a400e47c89ce77ade7e45b7eb7c84dc04378152ed92a549e8b5f6e046ef36829 + +license: Apache2.0 + +summary: vgg16 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of vgg16 from the MindSpore model zoo on Gitee at official/cv/vgg16. + +vgg16 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/vgg16](https://gitee.com/mindspore/models/blob/r1.5/official/cv/vgg16/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/vgg16_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Simonyan K, zisserman A. Very Deep Convolutional Networks for Large-Scale Image Recognition[J]. arXiv preprint arXiv:1409.1556, 2014. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/vgg19_imagenet2012.md b/mshub_res/assets/mindspore/1.5/vgg19_imagenet2012.md new file mode 100644 index 0000000..2d54e0d --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/vgg19_imagenet2012.md @@ -0,0 +1,79 @@ +# vgg19 + +--- + +model-name: vgg19 + +backbone-name: vgg19 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc74 | top5acc91.97 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: ea034624d868d0b8b52eb6c0b46c5e8288f8773efe7d80c88ef430890a1cb12d + +license: Apache2.0 + +summary: vgg19 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of vgg19 from the MindSpore model zoo on Gitee at research/cv/vgg19. + +vgg19 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/vgg19](https://gitee.com/mindspore/models/blob/r1.5/research/cv/vgg19/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/vgg19_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Simonyan K, zisserman A. Very Deep Convolutional Networks for Large-Scale Image Recognition[J]. arXiv preprint arXiv:1409.1556, 2014. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/vit_imagenet2012.md b/mshub_res/assets/mindspore/1.5/vit_imagenet2012.md new file mode 100644 index 0000000..752f0f2 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/vit_imagenet2012.md @@ -0,0 +1,79 @@ +# vit + +--- + +model-name: vit + +backbone-name: vit + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: acc74.17 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c24895695e24c1cbb2deb12e4aeb43080cc4e420247cbbe571a70994a6366264 + +license: Apache2.0 + +summary: vit is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of vit from the MindSpore model zoo on Gitee at official/cv/vit. + +vit is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/vit](https://gitee.com/mindspore/models/blob/r1.5/official/cv/vit/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/vit_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, Neil Houlsby. 2021. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/vitbase_cifar10.md b/mshub_res/assets/mindspore/1.5/vitbase_cifar10.md new file mode 100644 index 0000000..39e06f2 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/vitbase_cifar10.md @@ -0,0 +1,62 @@ +# vit_base + +--- + +model-name: vit_base + +backbone-name: vit_base + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cifar10 + +evaluation: acc98.71 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 86646358bde1d63ce8a073ea0543f3cea94e95e1752ea621cb3c66a4b101a678 + +license: Apache2.0 + +summary: vit_base is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of vit_base from the MindSpore model zoo on Gitee at research/cv/vit_base. + +vit_base is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/vit_base](https://gitee.com/mindspore/models/blob/r1.5/research/cv/vit_base/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Dosovitskiy, A. , Beyer, L. , Kolesnikov, A. , Weissenborn, D. , & Houlsby, N.. (2020). An image is worth 16x16 words: transformers for image recognition at scale. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/warpctc_captcha.md b/mshub_res/assets/mindspore/1.5/warpctc_captcha.md new file mode 100644 index 0000000..06c6995 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/warpctc_captcha.md @@ -0,0 +1,75 @@ +# warpctc + +--- + +model-name: warpctc + +backbone-name: warpctc + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: captcha + +evaluation: acc99.17 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: f9bf44cb3d8889136139796d0f18100dd1dc65a720df33829ccd4009c9fdf3d9 + +license: Apache2.0 + +summary: warpctc is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of warpctc from the MindSpore model zoo on Gitee at official/cv/warpctc. + +warpctc is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/warpctc](https://gitee.com/mindspore/models/blob/r1.5/official/cv/warpctc/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/warpctc_captcha" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/wgan_batchnorm_G_lsunbedrooms.md b/mshub_res/assets/mindspore/1.5/wgan_batchnorm_G_lsunbedrooms.md new file mode 100644 index 0000000..72e5ba4 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/wgan_batchnorm_G_lsunbedrooms.md @@ -0,0 +1,62 @@ +# wgan + +--- + +model-name: wgan + +backbone-name: wgan + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: lsunbedrooms + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: f1a6d7adb5e168d3913b6bac61dbe77c487f5d5293bca3b951a73144d3a5e4f0 + +license: Apache2.0 + +summary: wgan is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of wgan from the MindSpore model zoo on Gitee at research/cv/wgan. + +wgan is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/wgan](https://gitee.com/mindspore/models/blob/r1.5/research/cv/wgan/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Martin Arjovsky, Soumith Chintala, Léon Bottou. "Wasserstein GAN"*In International Conference on Machine Learning(ICML 2017). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/wgan_nobatchnorm_G_lsunbedrooms.md b/mshub_res/assets/mindspore/1.5/wgan_nobatchnorm_G_lsunbedrooms.md new file mode 100644 index 0000000..e964762 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/wgan_nobatchnorm_G_lsunbedrooms.md @@ -0,0 +1,62 @@ +# wgan + +--- + +model-name: wgan + +backbone-name: wgan + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: lsunbedrooms + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: ca9fa2777634bb1f96aa61cf48cbfa45677d8b690ad362ae2708677a21f7a167 + +license: Apache2.0 + +summary: wgan is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of wgan from the MindSpore model zoo on Gitee at research/cv/wgan. + +wgan is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/wgan](https://gitee.com/mindspore/models/blob/r1.5/research/cv/wgan/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Martin Arjovsky, Soumith Chintala, Léon Bottou. "Wasserstein GAN"*In International Conference on Machine Learning(ICML 2017). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/wideanddeep_criteo.md b/mshub_res/assets/mindspore/1.5/wideanddeep_criteo.md new file mode 100644 index 0000000..f1693d0 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/wideanddeep_criteo.md @@ -0,0 +1,79 @@ +# wide_and_deep + +--- + +model-name: wide_and_deep + +backbone-name: wide_and_deep + +module-type: recommend + +fine-tunable: True + +model-version: 1.5 + +train-dataset: criteo + +evaluation: acc80.8 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d0522cdd4a01b8072d9500b5d4b28d2659dc5fb46d446664bad39413b2b8bff1 + +license: Apache2.0 + +summary: wide_and_deep is used for recommend + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of wide_and_deep from the MindSpore model zoo on Gitee at official/recommend/wide_and_deep. + +wide_and_deep is a recommend network. More details please refer to the MindSpore model zoo on Gitee at [official/recommend/wide_and_deep](https://gitee.com/mindspore/models/blob/r1.5/official/recommend/wide_and_deep/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/wideanddeep_criteo" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wide & Deep Learning for Recommender System + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/wideanddeep_dynamicshape_criteo.md b/mshub_res/assets/mindspore/1.5/wideanddeep_dynamicshape_criteo.md new file mode 100644 index 0000000..3906c26 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/wideanddeep_dynamicshape_criteo.md @@ -0,0 +1,79 @@ +# wide_and_deep + +--- + +model-name: wide_and_deep + +backbone-name: wide_and_deep + +module-type: recommend + +fine-tunable: True + +model-version: 1.5 + +train-dataset: criteo + +evaluation: acc78.88 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 98e97d16ca19a9871d4c5aa81acc4e38d033d7b54403d66d2f84d6b68cc07591 + +license: Apache2.0 + +summary: wide_and_deep is used for recommend + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of wide_and_deep from the MindSpore model zoo on Gitee at official/recommend/wide_and_deep. + +wide_and_deep is a recommend network. More details please refer to the MindSpore model zoo on Gitee at [official/recommend/wide_and_deep](https://gitee.com/mindspore/models/blob/r1.5/official/recommend/wide_and_deep/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/wideanddeep_dynamicshape_criteo" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wide & Deep Learning for Recommender System + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/wideanddeep_hostdevice_criteo.md b/mshub_res/assets/mindspore/1.5/wideanddeep_hostdevice_criteo.md new file mode 100644 index 0000000..cb4d4d9 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/wideanddeep_hostdevice_criteo.md @@ -0,0 +1,79 @@ +# wide_and_deep + +--- + +model-name: wide_and_deep + +backbone-name: wide_and_deep + +module-type: recommend + +fine-tunable: True + +model-version: 1.5 + +train-dataset: criteo + +evaluation: acc79.34 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 3155f6edc2168cd84c887a5a43eab90a358dcd48a649eef677dbc5377dc2cf11 + +license: Apache2.0 + +summary: wide_and_deep is used for recommend + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of wide_and_deep from the MindSpore model zoo on Gitee at official/recommend/wide_and_deep. + +wide_and_deep is a recommend network. More details please refer to the MindSpore model zoo on Gitee at [official/recommend/wide_and_deep](https://gitee.com/mindspore/models/blob/r1.5/official/recommend/wide_and_deep/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/wideanddeep_hostdevice_criteo" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wide & Deep Learning for Recommender System + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/wideanddeep_ps_criteo.md b/mshub_res/assets/mindspore/1.5/wideanddeep_ps_criteo.md new file mode 100644 index 0000000..f16481a --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/wideanddeep_ps_criteo.md @@ -0,0 +1,79 @@ +# wide_and_deep + +--- + +model-name: wide_and_deep + +backbone-name: wide_and_deep + +module-type: recommend + +fine-tunable: True + +model-version: 1.5 + +train-dataset: criteo + +evaluation: acc80.76 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 01a521846a22c35ff3bef3f53ef5cb4efdc8c4717e4ca5b2efd3c2d4c04663f6 + +license: Apache2.0 + +summary: wide_and_deep is used for recommend + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of wide_and_deep from the MindSpore model zoo on Gitee at official/recommend/wide_and_deep. + +wide_and_deep is a recommend network. More details please refer to the MindSpore model zoo on Gitee at [official/recommend/wide_and_deep](https://gitee.com/mindspore/models/blob/r1.5/official/recommend/wide_and_deep/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/wideanddeep_ps_criteo" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wide & Deep Learning for Recommender System + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/wideanddeepmultitable_outbrain.md b/mshub_res/assets/mindspore/1.5/wideanddeepmultitable_outbrain.md new file mode 100644 index 0000000..1a0c59b --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/wideanddeepmultitable_outbrain.md @@ -0,0 +1,79 @@ +# wide_and_deep_multitable + +--- + +model-name: wide_and_deep_multitable + +backbone-name: wide_and_deep_multitable + +module-type: recommend + +fine-tunable: True + +model-version: 1.5 + +train-dataset: outbrain + +evaluation: acc80.97 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: dfbee3851427816f19ced062e7318c0080bafd5e68db4772c718047dceea0b10 + +license: Apache2.0 + +summary: wide_and_deep_multitable is used for recommend + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of wide_and_deep_multitable from the MindSpore model zoo on Gitee at official/recommend/wide_and_deep_multitable. + +wide_and_deep_multitable is a recommend network. More details please refer to the MindSpore model zoo on Gitee at [official/recommend/wide_and_deep_multitable](https://gitee.com/mindspore/models/blob/r1.5/official/recommend/wide_and_deep_multitable/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/wideanddeepmultitable_outbrain" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wide & Deep Learning for Recommender System + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/wideresnet_cifar10.md b/mshub_res/assets/mindspore/1.5/wideresnet_cifar10.md new file mode 100644 index 0000000..b26cf9e --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/wideresnet_cifar10.md @@ -0,0 +1,62 @@ +# wideresnet + +--- + +model-name: wideresnet + +backbone-name: wideresnet + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: cifar10 + +evaluation: acc96.33 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 441c0aaa59b9e164be0666d5a318fc438532e7fd13730cfa0b6cb677a8217442 + +license: Apache2.0 + +summary: wideresnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of wideresnet from the MindSpore model zoo on Gitee at research/cv/wideresnet. + +wideresnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/wideresnet](https://gitee.com/mindspore/models/blob/r1.5/research/cv/wideresnet/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Sergey Zagoruyko."Wide Residual Netwoks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/xception_imagenet2012.md b/mshub_res/assets/mindspore/1.5/xception_imagenet2012.md new file mode 100644 index 0000000..78cb892 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/xception_imagenet2012.md @@ -0,0 +1,79 @@ +# xception + +--- + +model-name: xception + +backbone-name: xception + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: imagenet2012 + +evaluation: top1acc79.94 | top5acc94.97 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 0359d9ffe399d2c359bf7cf488b56f559e665dc5968b61a00809c8a0a53fb26c + +license: Apache2.0 + +summary: xception is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of xception from the MindSpore model zoo on Gitee at official/cv/xception. + +xception is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/xception](https://gitee.com/mindspore/models/blob/r1.5/official/cv/xception/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/xception_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Franois Chollet. Xception: Deep Learning with Depthwise Separable Convolutions. 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) IEEE, 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/yolov3darknet53_coco2014.md b/mshub_res/assets/mindspore/1.5/yolov3darknet53_coco2014.md new file mode 100644 index 0000000..bc482eb --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/yolov3darknet53_coco2014.md @@ -0,0 +1,79 @@ +# yolov3_darknet53 + +--- + +model-name: yolov3_darknet53 + +backbone-name: yolov3_darknet53 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2014 + +evaluation: acc31.3 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: b85b72bff16a6cad1a71c768e48e500589f24715897d8b35ac743ae11faa07b3 + +license: Apache2.0 + +summary: yolov3_darknet53 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of yolov3_darknet53 from the MindSpore model zoo on Gitee at official/cv/yolov3_darknet53. + +yolov3_darknet53 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/yolov3_darknet53](https://gitee.com/mindspore/models/blob/r1.5/official/cv/yolov3_darknet53/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/yolov3darknet53_coco2014" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +YOLOv3: An Incremental Improvement.Joseph Redmon, Ali Farhadi, University of Washington + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/yolov3darknet53quant_coco2014.md b/mshub_res/assets/mindspore/1.5/yolov3darknet53quant_coco2014.md new file mode 100644 index 0000000..2334fc0 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/yolov3darknet53quant_coco2014.md @@ -0,0 +1,79 @@ +# yolov3_darknet53_quant + +--- + +model-name: yolov3_darknet53_quant + +backbone-name: yolov3_darknet53_quant + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2014 + +evaluation: mAP31 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d41609bc771288a2424a7b6bd6fa688abc345fbdc152ead669eda8ed3d783c9c + +license: Apache2.0 + +summary: yolov3_darknet53_quant is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of yolov3_darknet53_quant from the MindSpore model zoo on Gitee at official/cv/yolov3_darknet53_quant. + +yolov3_darknet53_quant is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/yolov3_darknet53_quant](https://gitee.com/mindspore/models/blob/r1.5/official/cv/yolov3_darknet53_quant/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/yolov3darknet53quant_coco2014" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +YOLOv3: An Incremental Improvement.Joseph Redmon, Ali Farhadi, University of Washington + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/yolov3resnet18_coco2017.md b/mshub_res/assets/mindspore/1.5/yolov3resnet18_coco2017.md new file mode 100644 index 0000000..259bb17 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/yolov3resnet18_coco2017.md @@ -0,0 +1,79 @@ +# yolov3_resnet18 + +--- + +model-name: yolov3_resnet18 + +backbone-name: yolov3_resnet18 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: class0precision91.76 | class0recall66.27 | class1precision89.09 | class1recall76.93 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 42c46a3b9518282da79233d0b550c8d5d4c32e79c1ebe8facd155fe8f2e7e75b + +license: Apache2.0 + +summary: yolov3_resnet18 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of yolov3_resnet18 from the MindSpore model zoo on Gitee at official/cv/yolov3_resnet18. + +yolov3_resnet18 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/yolov3_resnet18](https://gitee.com/mindspore/models/blob/r1.5/official/cv/yolov3_resnet18/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/yolov3resnet18_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Joseph Redmon, Ali Farhadi. arXiv preprint arXiv:1804.02767, 2018. 2, 4, 7, 11. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/yolov3tiny_coco2017.md b/mshub_res/assets/mindspore/1.5/yolov3tiny_coco2017.md new file mode 100644 index 0000000..f059f7b --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/yolov3tiny_coco2017.md @@ -0,0 +1,79 @@ +# yolov3_tiny + +--- + +model-name: yolov3_tiny + +backbone-name: yolov3_tiny + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: mAP17.7 | mAP50acc36 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c4a5b747c28373bd2100abd732fca582c13ddf74d5dab5b5fd92fd9ce303c4a7 + +license: Apache2.0 + +summary: yolov3_tiny is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of yolov3_tiny from the MindSpore model zoo on Gitee at research/cv/yolov3_tiny. + +yolov3_tiny is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/yolov3_tiny](https://gitee.com/mindspore/models/blob/r1.5/research/cv/yolov3_tiny/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/yolov3tiny_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Joseph Redmon, Ali Farhadi. arXiv preprint arXiv:1804.02767, 2018.2, 4, 7, 11. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/yolov4_coco2017.md b/mshub_res/assets/mindspore/1.5/yolov4_coco2017.md new file mode 100644 index 0000000..c29e77b --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/yolov4_coco2017.md @@ -0,0 +1,79 @@ +# yolov4 + +--- + +model-name: yolov4 + +backbone-name: yolov4 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: acc44 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: e318152734c9bb89c2907f4d26bf0dff63241d7dffc52b2dc48c93353f13fde8 + +license: Apache2.0 + +summary: yolov4 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of yolov4 from the MindSpore model zoo on Gitee at official/cv/yolov4. + +yolov4 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/yolov4](https://gitee.com/mindspore/models/blob/r1.5/official/cv/yolov4/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/yolov4_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Bochkovskiy A, Wang C Y, Liao H Y M. YOLOv4: Optimal Speed and Accuracy of Object Detection[J]. arXiv preprint arXiv:2004.10934, 2020. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/yolov4shape416_coco2017.md b/mshub_res/assets/mindspore/1.5/yolov4shape416_coco2017.md new file mode 100644 index 0000000..2f9f146 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/yolov4shape416_coco2017.md @@ -0,0 +1,79 @@ +# yolov4 + +--- + +model-name: yolov4 + +backbone-name: yolov4 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: acc39.3 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 86e0cbb81173d2634066a010ea2615482a45f1372da8d3397d5bb8c1e25a27f9 + +license: Apache2.0 + +summary: yolov4 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of yolov4 from the MindSpore model zoo on Gitee at official/cv/yolov4. + +yolov4 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/yolov4](https://gitee.com/mindspore/models/blob/r1.5/official/cv/yolov4/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/yolov4shape416_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Bochkovskiy A, Wang C Y, Liao H Y M. YOLOv4: Optimal Speed and Accuracy of Object Detection[J]. arXiv preprint arXiv:2004.10934, 2020. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.5/yolov5shape640_coco2017.md b/mshub_res/assets/mindspore/1.5/yolov5shape640_coco2017.md new file mode 100644 index 0000000..92b0eb4 --- /dev/null +++ b/mshub_res/assets/mindspore/1.5/yolov5shape640_coco2017.md @@ -0,0 +1,75 @@ +# yolov5 + +--- + +model-name: yolov5 + +backbone-name: yolov5 + +module-type: cv + +fine-tunable: True + +model-version: 1.5 + +train-dataset: coco2017 + +evaluation: acc36.6 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.5 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 9e17460882efdf587ee451fcc401d4359f0d1f31eb40825a59c339e65e1ca89b + +license: Apache2.0 + +summary: yolov5 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of yolov5 from the MindSpore model zoo on Gitee at official/cv/yolov5. + +yolov5 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/yolov5](https://gitee.com/mindspore/models/blob/r1.5/official/cv/yolov5/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.5/yolov5shape640_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/3dcnn_brast2017.md b/mshub_res/assets/mindspore/1.6/3dcnn_brast2017.md new file mode 100644 index 0000000..b7f9c43 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/3dcnn_brast2017.md @@ -0,0 +1,62 @@ +# 3dcnn + +--- + +model-name: 3dcnn + +backbone-name: 3dcnn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: brast2017 + +evaluation: whole81.97 | core77.78 | enhance75.38 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: a12f237f4ded800922f3fe6849fe4fab77e1964599bd75e8d2c9402c941076bc + +license: Apache2.0 + +summary: 3dcnn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of 3dcnn from the MindSpore model zoo on Gitee at research/cv/3dcnn. + +3dcnn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/3dcnn](https://gitee.com/mindspore/models/blob/r1.6/research/cv/3dcnn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Chen, Lele, et al. "MRI tumor segmentation with densely connected 3D CNN." Medical Imaging 2018: Image Processing. Vol. 10574. International Society for Optics and Photonics, 2018. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/3ddensenet_iseg2017.md b/mshub_res/assets/mindspore/1.6/3ddensenet_iseg2017.md new file mode 100644 index 0000000..2a5a8bb --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/3ddensenet_iseg2017.md @@ -0,0 +1,58 @@ +# 3D_DenseNet + +--- + +model-name: 3D_DenseNet + +backbone-name: 3D_DenseNet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: iseg2017 + +evaluation: acc92 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 81196ef44f3db51e3d22b69d01373c162639fa31362dd71388906fc307ccc3fe + +license: Apache2.0 + +summary: 3D_DenseNet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of 3D_DenseNet from the MindSpore model zoo on Gitee at research/cv/3D_DenseNet. + +3D_DenseNet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/3D_DenseNet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/3D_DenseNet/README.md). + +All parameters in the module are trainable. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/adnet_vot2013vot2014.md b/mshub_res/assets/mindspore/1.6/adnet_vot2013vot2014.md new file mode 100644 index 0000000..611265e --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/adnet_vot2013vot2014.md @@ -0,0 +1,62 @@ +# ADNet + +--- + +model-name: ADNet + +backbone-name: ADNet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: vot2013vot2014 + +evaluation: acc70 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: a0c20d71945406fe3687d30a5f4d4011dd8eb7f846ca3d00ec2e0ea60324311e + +license: Apache2.0 + +summary: ADNet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ADNet from the MindSpore model zoo on Gitee at official/cv/ADNet. + +ADNet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/ADNet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/ADNet/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Sangdoo Yun（Seoul National University, South Korea）. "Action-Decision Networks for Visual Tracking with Deep Reinforcement Learning'. Presented at CVPR 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/advancedeast_icpr2018.md b/mshub_res/assets/mindspore/1.6/advancedeast_icpr2018.md new file mode 100644 index 0000000..9186ed7 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/advancedeast_icpr2018.md @@ -0,0 +1,62 @@ +# advanced_east + +--- + +model-name: advanced_east + +backbone-name: advanced_east + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: icpr2018 + +evaluation: F1acc61.52 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 29da691de69194138d3ab0f74ae62299cff4e3d7432e6e511f70706c238edc9e + +license: Apache2.0 + +summary: advanced_east is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of advanced_east from the MindSpore model zoo on Gitee at research/cv/advanced_east. + +advanced_east is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/advanced_east](https://gitee.com/mindspore/models/blob/r1.6/research/cv/advanced_east/README.md). + +All parameters in the module are trainable. + +## Citation + +EAST:An Efficient and Accurate Scene Text Detector. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/aecrnet_reside.md b/mshub_res/assets/mindspore/1.6/aecrnet_reside.md new file mode 100644 index 0000000..e85b664 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/aecrnet_reside.md @@ -0,0 +1,62 @@ +# aecrnet + +--- + +model-name: aecrnet + +backbone-name: aecrnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: reside + +evaluation: SSIM46 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: cdfb291c14241b830ec97f00b8f45442948342b245fb0e943e40d57720763b8f + +license: Apache2.0 + +summary: aecrnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of aecrnet from the MindSpore model zoo on Gitee at research/cv/aecrnet. + +aecrnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/aecrnet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/aecrnet/README.md). + +All parameters in the module are trainable. + +## Citation + +Contrastive Learning for Compact Single Image Dehazing, CVPR2021 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/albert_mnli.md b/mshub_res/assets/mindspore/1.6/albert_mnli.md new file mode 100644 index 0000000..2503d7a --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/albert_mnli.md @@ -0,0 +1,63 @@ +# albert + +--- + +model-name: albert + +backbone-name: albert + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: mnli + +evaluation: acc82.25 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: ec4f2c5302b299d7751a60615a1d0f4316527146a6909c5d86b9afa5720bcc7a + +license: Apache2.0 + +summary: albert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of albert from the MindSpore model zoo on Gitee at research/nlp/albert. + +albert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [research/nlp/albert](https://gitee.com/mindspore/models/blob/r1.6/research/nlp/albert/README.md). + +All parameters in the module are trainable. + +## Citation + +1. Lan, Z., Chen, M., Goodman, S., Gimpel, K., Sharma, P., & Soricut, R. (2020). ALBERT: A Lite BERT for Self-supervised Learning of Language Representations. ArXiv, abs/1909.11942. +2. Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv preprint arXiv:1810.04805. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/albert_squadv1.1.md b/mshub_res/assets/mindspore/1.6/albert_squadv1.1.md new file mode 100644 index 0000000..6352734 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/albert_squadv1.1.md @@ -0,0 +1,63 @@ +# albert + +--- + +model-name: albert + +backbone-name: albert + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: squadv1.1 + +evaluation: exactmatch80.88 | F1score88.71 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c60cc45a88fbf85bac9bc4bc3edced7d31281511bd6f70c6e13fb3ccc8e2ec09 + +license: Apache2.0 + +summary: albert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of albert from the MindSpore model zoo on Gitee at research/nlp/albert. + +albert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [research/nlp/albert](https://gitee.com/mindspore/models/blob/r1.6/research/nlp/albert/README.md). + +All parameters in the module are trainable. + +## Citation + +1. Lan, Z., Chen, M., Goodman, S., Gimpel, K., Sharma, P., & Soricut, R. (2020). ALBERT: A Lite BERT for Self-supervised Learning of Language Representations. ArXiv, abs/1909.11942. +2. Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv preprint arXiv:1810.04805. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/albert_sst2.md b/mshub_res/assets/mindspore/1.6/albert_sst2.md new file mode 100644 index 0000000..e7206a7 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/albert_sst2.md @@ -0,0 +1,63 @@ +# albert + +--- + +model-name: albert + +backbone-name: albert + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: sst2 + +evaluation: acc89.11 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 84769afa38111286e320c55c220a0cdf3c68a4f45239576e610ac9fd195ad190 + +license: Apache2.0 + +summary: albert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of albert from the MindSpore model zoo on Gitee at research/nlp/albert. + +albert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [research/nlp/albert](https://gitee.com/mindspore/models/blob/r1.6/research/nlp/albert/README.md). + +All parameters in the module are trainable. + +## Citation + +1. Lan, Z., Chen, M., Goodman, S., Gimpel, K., Sharma, P., & Soricut, R. (2020). ALBERT: A Lite BERT for Self-supervised Learning of Language Representations. ArXiv, abs/1909.11942. +2. Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv preprint arXiv:1810.04805. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/alexnet_cifar10.md b/mshub_res/assets/mindspore/1.6/alexnet_cifar10.md new file mode 100644 index 0000000..4e378b0 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/alexnet_cifar10.md @@ -0,0 +1,79 @@ +# alexnet + +--- + +model-name: alexnet + +backbone-name: alexnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cifar10 + +evaluation: acc89.38 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 84569e4934f9a49093d50ba43f851a761fb35a8dad72c991ae928e0646a261c7 + +license: Apache2.0 + +summary: alexnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of alexnet from the MindSpore model zoo on Gitee at official/cv/alexnet. + +alexnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/alexnet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/alexnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/alexnet_cifar10" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Krizhevsky A, Sutskever I, Hinton G E. ImageNet Classification with Deep ConvolutionalNeural Networks. *Advances In Neural Information Processing Systems*. 2012. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/alexnet_imagenet2012.md b/mshub_res/assets/mindspore/1.6/alexnet_imagenet2012.md new file mode 100644 index 0000000..2a760e5 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/alexnet_imagenet2012.md @@ -0,0 +1,79 @@ +# alexnet + +--- + +model-name: alexnet + +backbone-name: alexnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc57.45 | top5acc80 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 363ce17938585048f0725d57372bcef2d167b4e4346cb39f1128434686f2b69f + +license: Apache2.0 + +summary: alexnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of alexnet from the MindSpore model zoo on Gitee at official/cv/alexnet. + +alexnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/alexnet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/alexnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/alexnet_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Krizhevsky A, Sutskever I, Hinton G E. ImageNet Classification with Deep ConvolutionalNeural Networks. *Advances In Neural Information Processing Systems*. 2012. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/alphapose_coco2017.md b/mshub_res/assets/mindspore/1.6/alphapose_coco2017.md new file mode 100644 index 0000000..70e9f4e --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/alphapose_coco2017.md @@ -0,0 +1,62 @@ +# AlphaPose + +--- + +model-name: AlphaPose + +backbone-name: AlphaPose + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: acc71.86 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: f8873c73702fb26bb7b8ae1fc877630d8b941057595fab4ddf56ff4ffd1c151e + +license: Apache2.0 + +summary: AlphaPose is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of AlphaPose from the MindSpore model zoo on Gitee at research/cv/AlphaPose. + +AlphaPose is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/AlphaPose](https://gitee.com/mindspore/models/blob/r1.6/research/cv/AlphaPose/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Fang H S , Xie S , Tai Y W , et al. RMPE: Regional Multi-person Pose Estimation + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/arcface_ms1mv2.md b/mshub_res/assets/mindspore/1.6/arcface_ms1mv2.md new file mode 100644 index 0000000..e4e61d6 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/arcface_ms1mv2.md @@ -0,0 +1,62 @@ +# arcface + +--- + +model-name: arcface + +backbone-name: arcface + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: ms1mv2 + +evaluation: ijbb95.06 | ijbc96.39 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5897d6d1b98411e170625377871b1daf658f6ba477765ba3c9872a24097a629f + +license: Apache2.0 + +summary: arcface is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of arcface from the MindSpore model zoo on Gitee at research/cv/arcface. + +arcface is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/arcface](https://gitee.com/mindspore/models/blob/r1.6/research/cv/arcface/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Deng J , Guo J , Zafeiriou S . ArcFace: Additive Angular Margin Loss for Deep Face Recognition[J]. 2018. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/attgan_G_celeba.md b/mshub_res/assets/mindspore/1.6/attgan_G_celeba.md new file mode 100644 index 0000000..5326ffc --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/attgan_G_celeba.md @@ -0,0 +1,62 @@ +# AttGAN + +--- + +model-name: AttGAN + +backbone-name: AttGAN + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: celeba + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: cc3c9f53714cafa0279d3856f50d164dd8245b8a67fb0f60e72a36012fef2026 + +license: Apache2.0 + +summary: AttGAN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of AttGAN from the MindSpore model zoo on Gitee at research/cv/AttGAN. + +AttGAN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/AttGAN](https://gitee.com/mindspore/models/blob/r1.6/research/cv/AttGAN/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Zhenliang He, Wangmeng Zuo, Meina Kan, Shiguang Shan, Xilin Chen, et al. AttGAN: Facial Attribute Editing by Only Changing What You Want[C]// 2017 CVPR. IEEE + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/autoaugment_cifar10.md b/mshub_res/assets/mindspore/1.6/autoaugment_cifar10.md new file mode 100644 index 0000000..40b658c --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/autoaugment_cifar10.md @@ -0,0 +1,79 @@ +# autoaugment + +--- + +model-name: autoaugment + +backbone-name: autoaugment + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cifar10 + +evaluation: acc97.22 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 3dfbe4b3bfca01c359c016f09377eb157dfd3c569543e52f483b8b451b652d2d + +license: Apache2.0 + +summary: autoaugment is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of autoaugment from the MindSpore model zoo on Gitee at research/cv/autoaugment. + +autoaugment is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/autoaugment](https://gitee.com/mindspore/models/blob/r1.6/research/cv/autoaugment/README_CN.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/autoaugment_cifar10" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Cubuk, Ekin D., et al. "Autoaugment: Learning augmentation strategies from data." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/autodeeplab_cityscapes.md b/mshub_res/assets/mindspore/1.6/autodeeplab_cityscapes.md new file mode 100644 index 0000000..18f9b23 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/autodeeplab_cityscapes.md @@ -0,0 +1,62 @@ +# Auto-DeepLab + +--- + +model-name: Auto-DeepLab + +backbone-name: Auto-DeepLab + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cityscapes + +evaluation: 0.5macc75 | 1.0macc77 | 1.5macc78 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: acf76d476fc4e42dc078ff8ab2050bdff34cdb8280fb6e2778c48c628c00e39f + +license: Apache2.0 + +summary: Auto-DeepLab is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of Auto-DeepLab from the MindSpore model zoo on Gitee at research/cv/Auto-DeepLab. + +Auto-DeepLab is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/Auto-DeepLab](https://gitee.com/mindspore/models/blob/r1.6/research/cv/Auto-DeepLab/README.md). + +All parameters in the module are trainable. + +## Citation + +Chenxi Liu, Liang-Chieh Chen, Florian Schroff, Hartwig Adam, Wei Hua, Alan L. Yuille, Li Fei-Fei; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, pp. 82-92 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/avacifar_cifar10.md b/mshub_res/assets/mindspore/1.6/avacifar_cifar10.md new file mode 100644 index 0000000..1587b1c --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/avacifar_cifar10.md @@ -0,0 +1,58 @@ +# AVA_cifar + +--- + +model-name: AVA_cifar + +backbone-name: AVA_cifar + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cifar10 + +evaluation: top1acc90.87 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 955f6c567108af733ea82f8efb1eec0accd44cbc79a41b2d216ca83d09a646c6 + +license: Apache2.0 + +summary: AVA_cifar is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of AVA_cifar from the MindSpore model zoo on Gitee at research/cv/AVA_cifar. + +AVA_cifar is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/AVA_cifar](https://gitee.com/mindspore/models/blob/r1.6/research/cv/AVA_cifar/README.md). + +All parameters in the module are trainable. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/bertbase_cnnews128.md b/mshub_res/assets/mindspore/1.6/bertbase_cnnews128.md new file mode 100644 index 0000000..f8c37dc --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/bertbase_cnnews128.md @@ -0,0 +1,80 @@ +# bert + +--- + +model-name: bert + +backbone-name: bert + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cnnews128 + +evaluation: loss1.5 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5320e958731641eb26cad931a23ff7f462745877ddee89480daef239f0e2fa68 + +license: Apache2.0 + +summary: bert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of bert from the MindSpore model zoo on Gitee at official/nlp/bert. + +bert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/bert](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/bert/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/bertbase_cnnews128" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv preprint arXiv:1810.04805. +2. Junqiu Wei, Xiaozhe Ren, Xiaoguang Li, Wenyong Huang, Yi Liao, Yasheng Wang, Jiashu Lin, Xin Jiang, Xiao Chen, Qun Liu. NEZHA: Neural Contextualized Representation for Chinese Language Understanding. arXiv preprint arXiv:1909.00204. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/bertfinetuning_classifier_cola.md b/mshub_res/assets/mindspore/1.6/bertfinetuning_classifier_cola.md new file mode 100644 index 0000000..d0c70b9 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/bertfinetuning_classifier_cola.md @@ -0,0 +1,80 @@ +# bert + +--- + +model-name: bert + +backbone-name: bert + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cola + +evaluation: acc55.71 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 954952abff015a8686840dca6920282d75c20ee2b75eee341d4151e3c84e5d66 + +license: Apache2.0 + +summary: bert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of bert from the MindSpore model zoo on Gitee at official/nlp/bert. + +bert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/bert](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/bert/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/bertfinetuning_classifier_cola" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova.BERT：深度双向Transformer语言理解预训练). arXiv preprint arXiv:1810.04805. +2. Junqiu Wei, Xiaozhe Ren, Xiaoguang Li, Wenyong Huang, Yi Liao, Yasheng Wang, Jiashu Lin, Xin Jiang, Xiao Chen, Qun Liu.NEZHA：面向汉语理解的神经语境表示. arXiv preprint arXiv:1909.00204. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/bertfinetuning_nercrf_cluener.md b/mshub_res/assets/mindspore/1.6/bertfinetuning_nercrf_cluener.md new file mode 100644 index 0000000..b590360 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/bertfinetuning_nercrf_cluener.md @@ -0,0 +1,80 @@ +# bert + +--- + +model-name: bert + +backbone-name: bert + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cluener + +evaluation: acc92.48 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 2dbc96564c533fab13e185e03e7a50861d25824a72562b263a7f36df107f43b8 + +license: Apache2.0 + +summary: bert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of bert from the MindSpore model zoo on Gitee at official/nlp/bert. + +bert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/bert](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/bert/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/bertfinetuning_nercrf_cluener" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova.BERT：深度双向Transformer语言理解预训练). arXiv preprint arXiv:1810.04805. +2. Junqiu Wei, Xiaozhe Ren, Xiaoguang Li, Wenyong Huang, Yi Liao, Yasheng Wang, Jiashu Lin, Xin Jiang, Xiao Chen, Qun Liu.NEZHA：面向汉语理解的神经语境表示. arXiv preprint arXiv:1909.00204. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/bertfinetuning_nersoftmax_cluener.md b/mshub_res/assets/mindspore/1.6/bertfinetuning_nersoftmax_cluener.md new file mode 100644 index 0000000..b0fee18 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/bertfinetuning_nersoftmax_cluener.md @@ -0,0 +1,80 @@ +# bert + +--- + +model-name: bert + +backbone-name: bert + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cluener + +evaluation: acc93.75 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: e895a7e6d1d8d1aa3bb6c869136038416560714c30651801be6a93a4425aa4f3 + +license: Apache2.0 + +summary: bert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of bert from the MindSpore model zoo on Gitee at official/nlp/bert. + +bert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/bert](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/bert/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/bertfinetuning_nersoftmax_cluener" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova.BERT：深度双向Transformer语言理解预训练). arXiv preprint arXiv:1810.04805. +2. Junqiu Wei, Xiaozhe Ren, Xiaoguang Li, Wenyong Huang, Yi Liao, Yasheng Wang, Jiashu Lin, Xin Jiang, Xiao Chen, Qun Liu.NEZHA：面向汉语理解的神经语境表示. arXiv preprint arXiv:1909.00204. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/bertfinetuning_squad_squadv1.1.md b/mshub_res/assets/mindspore/1.6/bertfinetuning_squad_squadv1.1.md new file mode 100644 index 0000000..f62bc63 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/bertfinetuning_squad_squadv1.1.md @@ -0,0 +1,80 @@ +# bert + +--- + +model-name: bert + +backbone-name: bert + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: squadv1.1 + +evaluation: F1score88.45 | exactmatch81 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 9e4e1a8e0cd905f9d7caf5d04fec1b0e94fcd210682f21c8bfbb354f3660bc97 + +license: Apache2.0 + +summary: bert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of bert from the MindSpore model zoo on Gitee at official/nlp/bert. + +bert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/bert](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/bert/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/bertfinetuning_squad_squadv1.1" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova.BERT：深度双向Transformer语言理解预训练). arXiv preprint arXiv:1810.04805. +2. Junqiu Wei, Xiaozhe Ren, Xiaoguang Li, Wenyong Huang, Yi Liao, Yasheng Wang, Jiashu Lin, Xin Jiang, Xiao Chen, Qun Liu.NEZHA：面向汉语理解的神经语境表示. arXiv preprint arXiv:1909.00204. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/bertlarge_cnnews128.md b/mshub_res/assets/mindspore/1.6/bertlarge_cnnews128.md new file mode 100644 index 0000000..b67b363 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/bertlarge_cnnews128.md @@ -0,0 +1,75 @@ +# bert_thor + +--- + +model-name: bert_thor + +backbone-name: bert_thor + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cnnews128 + +evaluation: acc71.21 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 05ea53283419af7fb9358fccf99a8b5a47e2ed09a8592d9d4be62e1f1c0e77d5 + +license: Apache2.0 + +summary: bert_thor is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of bert_thor from the MindSpore model zoo on Gitee at official/nlp/bert_thor. + +bert_thor is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/bert_thor](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/bert_thor/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/bertlarge_cnnews128" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/bgcf_amazonbeauty.md b/mshub_res/assets/mindspore/1.6/bgcf_amazonbeauty.md new file mode 100644 index 0000000..1b33461 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/bgcf_amazonbeauty.md @@ -0,0 +1,79 @@ +# bgcf + +--- + +model-name: bgcf + +backbone-name: bgcf + +module-type: gnn + +fine-tunable: True + +model-version: 1.6 + +train-dataset: amazonbeauty + +evaluation: recall20acc15.32 | ndcg20acc9.16 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 1ba27594e030d343d1c71cb5bc7ae6323d39c8d187226c88e9931d96ad786ba1 + +license: Apache2.0 + +summary: bgcf is used for gnn + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of bgcf from the MindSpore model zoo on Gitee at official/gnn/bgcf. + +bgcf is a gnn network. More details please refer to the MindSpore model zoo on Gitee at [official/gnn/bgcf](https://gitee.com/mindspore/models/blob/r1.6/official/gnn/bgcf/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/bgcf_amazonbeauty" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Sun J, Guo W, Zhang D, et al. A Framework for Recommending Accurate and Diverse Items Using Bayesian Graph Convolutional Neural Networks[C]//Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2020: 2030-2039. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/c3d_hmdb51.md b/mshub_res/assets/mindspore/1.6/c3d_hmdb51.md new file mode 100644 index 0000000..46f9cc0 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/c3d_hmdb51.md @@ -0,0 +1,62 @@ +# c3d + +--- + +model-name: c3d + +backbone-name: c3d + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: hmdb51 + +evaluation: top1acc49.67 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 76ca14dbd7c499255af90cee53f9df858632989a6deef1be0a56f63d319b9789 + +license: Apache2.0 + +summary: c3d is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of c3d from the MindSpore model zoo on Gitee at official/cv/c3d. + +c3d is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/c3d](https://gitee.com/mindspore/models/blob/r1.6/official/cv/c3d/README.md). + +All parameters in the module are trainable. + +## Citation + +Learning Spatiotemporal Features with 3D Convolutional Networks + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/centerface_widerface.md b/mshub_res/assets/mindspore/1.6/centerface_widerface.md new file mode 100644 index 0000000..61784cc --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/centerface_widerface.md @@ -0,0 +1,79 @@ +# centerface + +--- + +model-name: centerface + +backbone-name: centerface + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: widerface + +evaluation: easy92.4 | medium91.7 | hard77.9 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 9e2809d1561c0450a0ef063cbacd7690f688931a8bce4fdc6579aa26237de908 + +license: Apache2.0 + +summary: centerface is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of centerface from the MindSpore model zoo on Gitee at official/cv/centerface. + +centerface is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/centerface](https://gitee.com/mindspore/models/blob/r1.6/official/cv/centerface/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/centerface_widerface" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +CenterFace: Joint Face Detection and Alignment Using Face as Point. Xu, Yuanyuan(Huaqiao University) and Yan, Wan(StarClouds) and Sun, Haixin(Xiamen University) and Yang, Genke(Shanghai Jiaotong University) and Luo, Jiliang(Huaqiao University) + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/centernet_coco2017.md b/mshub_res/assets/mindspore/1.6/centernet_coco2017.md new file mode 100644 index 0000000..20bbd1c --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/centernet_coco2017.md @@ -0,0 +1,79 @@ +# centernet + +--- + +model-name: centernet + +backbone-name: centernet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: mAP51.9 | AP50acc78.8 | AP75acc55.5 | medium44.5 | large63.9 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 9c6fbfe8d3e47807d63f3c59726201bff036ddcdbb011a73e6276a4364a4c041 + +license: Apache2.0 + +summary: centernet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of centernet from the MindSpore model zoo on Gitee at research/cv/centernet. + +centernet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/centernet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/centernet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/centernet_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Objects as Points. 2019. Xingyi Zhou(UT Austin) and Dequan Wang(UC Berkeley) and Philipp Krahenbuhl(UT Austin) + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/centernetdet_coco2017.md b/mshub_res/assets/mindspore/1.6/centernetdet_coco2017.md new file mode 100644 index 0000000..7162e5b --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/centernetdet_coco2017.md @@ -0,0 +1,62 @@ +# centernet_det + +--- + +model-name: centernet_det + +backbone-name: centernet_det + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: mAP41.5 | AP50acc59.8 | AP75acc59.8 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 39ccffb7eae3cbcf2821fe093e3f48c9acde272669a7d9f90a2f08964514f4fd + +license: Apache2.0 + +summary: centernet_det is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of centernet_det from the MindSpore model zoo on Gitee at research/cv/centernet_det. + +centernet_det is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/centernet_det](https://gitee.com/mindspore/models/blob/r1.6/research/cv/centernet_det/README.md). + +All parameters in the module are trainable. + +## Citation + +Objects as Points. 2019. Xingyi Zhou(UT Austin) and Dequan Wang(UC Berkeley) and Philipp Krahenbuhl(UT Austin) + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/centernetresnet101_coco2017.md b/mshub_res/assets/mindspore/1.6/centernetresnet101_coco2017.md new file mode 100644 index 0000000..eee2530 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/centernetresnet101_coco2017.md @@ -0,0 +1,79 @@ +# centernet_resnet101 + +--- + +model-name: centernet_resnet101 + +backbone-name: centernet_resnet101 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: mAP33.9 | AP50acc52 | AP75acc36 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c8fe163020a1498f69b00317f6d6bd21a05dc47ddef3d36942a01aa575d92122 + +license: Apache2.0 + +summary: centernet_resnet101 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of centernet_resnet101 from the MindSpore model zoo on Gitee at research/cv/centernet_resnet101. + +centernet_resnet101 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/centernet_resnet101](https://gitee.com/mindspore/models/blob/r1.6/research/cv/centernet_resnet101/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/centernetresnet101_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Objects as Points. 2019. Xingyi Zhou(UT Austin) and Dequan Wang(UC Berkeley) and Philipp Krahenbuhl(UT Austin) + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/centernetresnet50v1_coco2017.md b/mshub_res/assets/mindspore/1.6/centernetresnet50v1_coco2017.md new file mode 100644 index 0000000..1dbdb67 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/centernetresnet50v1_coco2017.md @@ -0,0 +1,62 @@ +# centernet_resnet50_v1 + +--- + +model-name: centernet_resnet50_v1 + +backbone-name: centernet_resnet50_v1 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: mAP30.8 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: a3bf9973d423847b59a2fc56d17e630650e95fb6862019c29b9a7bb92268c962 + +license: Apache2.0 + +summary: centernet_resnet50_v1 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of centernet_resnet50_v1 from the MindSpore model zoo on Gitee at research/cv/centernet_resnet50_v1. + +centernet_resnet50_v1 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/centernet_resnet50_v1](https://gitee.com/mindspore/models/blob/r1.6/research/cv/centernet_resnet50_v1/README.md). + +All parameters in the module are trainable. + +## Citation + +Objects as Points. 2019. Xingyi Zhou(UT Austin) and Dequan Wang(UC Berkeley) and Philipp Krahenbuhl(UT Austin) + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/cgan_G_mnist.md b/mshub_res/assets/mindspore/1.6/cgan_G_mnist.md new file mode 100644 index 0000000..0827e31 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/cgan_G_mnist.md @@ -0,0 +1,62 @@ +# CGAN + +--- + +model-name: CGAN + +backbone-name: CGAN + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: mnist + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 360a455b190fc1a56cfb487ed25278794e86ea615458cf3066ca06e3b8ad3d41 + +license: Apache2.0 + +summary: CGAN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of CGAN from the MindSpore model zoo on Gitee at research/cv/CGAN. + +CGAN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/CGAN](https://gitee.com/mindspore/models/blob/r1.6/research/cv/CGAN/README.md). + +All parameters in the module are trainable. + +## Citation + +Conditional Generative Adversarial Nets. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/cnnctc_mjstiiit.md b/mshub_res/assets/mindspore/1.6/cnnctc_mjstiiit.md new file mode 100644 index 0000000..71f59b6 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/cnnctc_mjstiiit.md @@ -0,0 +1,79 @@ +# cnnctc + +--- + +model-name: cnnctc + +backbone-name: cnnctc + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: mjstiiit + +evaluation: acc85.97 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 3468204da46492286ed466c9bab9572443b4e7d359396a5e38b42ceb3d0a6c6f + +license: Apache2.0 + +summary: cnnctc is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of cnnctc from the MindSpore model zoo on Gitee at official/cv/cnnctc. + +cnnctc is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/cnnctc](https://gitee.com/mindspore/models/blob/r1.6/official/cv/cnnctc/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/cnnctc_mjstiiit" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +J. Baek, G. Kim, J. Lee, S. Park, D. Han, S. Yun, S. J. Oh, and H. Lee, “What is wrong with scene text recognition model comparisons? dataset and model analysis,” ArXiv, vol. abs/1904.01906, 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/cnndirectionmodel_fsns.md b/mshub_res/assets/mindspore/1.6/cnndirectionmodel_fsns.md new file mode 100644 index 0000000..2d40677 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/cnndirectionmodel_fsns.md @@ -0,0 +1,75 @@ +# cnn_direction_model + +--- + +model-name: cnn_direction_model + +backbone-name: cnn_direction_model + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: fsns + +evaluation: acc91 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 7dffb4205b94d111f5a0d60065cbd78912013645926c8960813ce4b1fe13725c + +license: Apache2.0 + +summary: cnn_direction_model is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of cnn_direction_model from the MindSpore model zoo on Gitee at official/cv/cnn_direction_model. + +cnn_direction_model is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/cnn_direction_model](https://gitee.com/mindspore/models/blob/r1.6/official/cv/cnn_direction_model/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/cnndirectionmodel_fsns" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/crnn_synth.md b/mshub_res/assets/mindspore/1.6/crnn_synth.md new file mode 100644 index 0000000..7fc9dfa --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/crnn_synth.md @@ -0,0 +1,79 @@ +# crnn + +--- + +model-name: crnn + +backbone-name: crnn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: synth + +evaluation: svtacc80.83 | iiit5kacc79.73 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 640dd154c7d4bbf93de2103f5e58e3595e0085d6fcd07731669666dc9d0745fd + +license: Apache2.0 + +summary: crnn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of crnn from the MindSpore model zoo on Gitee at official/cv/crnn. + +crnn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/crnn](https://gitee.com/mindspore/models/blob/r1.6/official/cv/crnn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/crnn_synth" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Baoguang Shi, Xiang Bai, Cong Yao, "An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition", ArXiv, vol. abs/1507.05717, 2015. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/crnnseq2seqocr_fsns.md b/mshub_res/assets/mindspore/1.6/crnnseq2seqocr_fsns.md new file mode 100644 index 0000000..64c003b --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/crnnseq2seqocr_fsns.md @@ -0,0 +1,75 @@ +# crnn_seq2seq_ocr + +--- + +model-name: crnn_seq2seq_ocr + +backbone-name: crnn_seq2seq_ocr + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: fsns + +evaluation: annotationprecision74 | characterprecision96 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 2261862bb3757d491428eef42ec30a6898b6fc9b87ca43cf50522dfc55d8bd96 + +license: Apache2.0 + +summary: crnn_seq2seq_ocr is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of crnn_seq2seq_ocr from the MindSpore model zoo on Gitee at official/cv/crnn_seq2seq_ocr. + +crnn_seq2seq_ocr is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/crnn_seq2seq_ocr](https://gitee.com/mindspore/models/blob/r1.6/official/cv/crnn_seq2seq_ocr/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/crnnseq2seqocr_fsns" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/ctpn_icdar2013.md b/mshub_res/assets/mindspore/1.6/ctpn_icdar2013.md new file mode 100644 index 0000000..724306c --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/ctpn_icdar2013.md @@ -0,0 +1,62 @@ +# ctpn + +--- + +model-name: ctpn + +backbone-name: ctpn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: icdar2013 + +evaluation: precision90 | recall86 | Fmeasure88 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: a1cfaecc174c435683a889aef141e6edcb5b35535666f683c7f57d35c827565a + +license: Apache2.0 + +summary: ctpn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ctpn from the MindSpore model zoo on Gitee at official/cv/ctpn. + +ctpn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/ctpn](https://gitee.com/mindspore/models/blob/r1.6/official/cv/ctpn/README.md). + +All parameters in the module are trainable. + +## Citation + +Zhi Tian, Weilin Huang, Tong He, Pan He, Yu Qiao, "Detecting Text in Natural Image with Connectionist Text Proposal Network", ArXiv, vol. abs/1609.03605, 2016. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/cyclegan_GA_apple2orange.md b/mshub_res/assets/mindspore/1.6/cyclegan_GA_apple2orange.md new file mode 100644 index 0000000..9ecd1c1 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/cyclegan_GA_apple2orange.md @@ -0,0 +1,62 @@ +# CycleGAN + +--- + +model-name: CycleGAN + +backbone-name: CycleGAN + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: apple2orange + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 44bc99276b91d5113636c37a03e75d15daf6c836e6cc59be07507223f69f9a5d + +license: Apache2.0 + +summary: CycleGAN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of CycleGAN from the MindSpore model zoo on Gitee at research/cv/CycleGAN. + +CycleGAN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/CycleGAN](https://gitee.com/mindspore/models/blob/r1.6/research/cv/CycleGAN/README.md). + +All parameters in the module are trainable. + +## Citation + +Zhu J Y , Park T , Isola P , et al. Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks[J]. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/cyclegan_GA_horse2zebra.md b/mshub_res/assets/mindspore/1.6/cyclegan_GA_horse2zebra.md new file mode 100644 index 0000000..b91695e --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/cyclegan_GA_horse2zebra.md @@ -0,0 +1,62 @@ +# CycleGAN + +--- + +model-name: CycleGAN + +backbone-name: CycleGAN + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: horse2zebra + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 36b004b573f32132802b4dab55b80e9acb56cd7b9f49ffa48e13032c9315b296 + +license: Apache2.0 + +summary: CycleGAN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of CycleGAN from the MindSpore model zoo on Gitee at research/cv/CycleGAN. + +CycleGAN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/CycleGAN](https://gitee.com/mindspore/models/blob/r1.6/research/cv/CycleGAN/README.md). + +All parameters in the module are trainable. + +## Citation + +Zhu J Y , Park T , Isola P , et al. Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks[J]. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/cyclegan_GB_apple2orange.md b/mshub_res/assets/mindspore/1.6/cyclegan_GB_apple2orange.md new file mode 100644 index 0000000..c8a6801 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/cyclegan_GB_apple2orange.md @@ -0,0 +1,62 @@ +# CycleGAN + +--- + +model-name: CycleGAN + +backbone-name: CycleGAN + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: apple2orange + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: f10f714fd074dafdcdf0428d5d3c1e1e708cb7825a3105faf4b45ac905847b72 + +license: Apache2.0 + +summary: CycleGAN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of CycleGAN from the MindSpore model zoo on Gitee at research/cv/CycleGAN. + +CycleGAN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/CycleGAN](https://gitee.com/mindspore/models/blob/r1.6/research/cv/CycleGAN/README.md). + +All parameters in the module are trainable. + +## Citation + +Zhu J Y , Park T , Isola P , et al. Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks[J]. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/cyclegan_GB_horse2zebra.md b/mshub_res/assets/mindspore/1.6/cyclegan_GB_horse2zebra.md new file mode 100644 index 0000000..10f6a01 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/cyclegan_GB_horse2zebra.md @@ -0,0 +1,62 @@ +# CycleGAN + +--- + +model-name: CycleGAN + +backbone-name: CycleGAN + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: horse2zebra + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 7e674623287672c6c221f9a7914429f60c02cd510ba662de36df6ed49ac035a5 + +license: Apache2.0 + +summary: CycleGAN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of CycleGAN from the MindSpore model zoo on Gitee at research/cv/CycleGAN. + +CycleGAN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/CycleGAN](https://gitee.com/mindspore/models/blob/r1.6/research/cv/CycleGAN/README.md). + +All parameters in the module are trainable. + +## Citation + +Zhu J Y , Park T , Isola P , et al. Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks[J]. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/dbpn_div2k.md b/mshub_res/assets/mindspore/1.6/dbpn_div2k.md new file mode 100644 index 0000000..7c3cec8 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/dbpn_div2k.md @@ -0,0 +1,62 @@ +# DBPN + +--- + +model-name: DBPN + +backbone-name: DBPN + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: div2k + +evaluation: PSNR31.93 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 75d74c46e4efc3a4f2e81df53a3ab8817618d8193a6032a971fe02a5e307ef77 + +license: Apache2.0 + +summary: DBPN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of DBPN from the MindSpore model zoo on Gitee at research/cv/DBPN. + +DBPN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/DBPN](https://gitee.com/mindspore/models/blob/r1.6/research/cv/DBPN/README.md). + +All parameters in the module are trainable. + +## Citation + +Muhammad Haris, Greg Shakhnarovich, Norimichi Ukita + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/dbpngan_G_div2k.md b/mshub_res/assets/mindspore/1.6/dbpngan_G_div2k.md new file mode 100644 index 0000000..e4f9f76 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/dbpngan_G_div2k.md @@ -0,0 +1,62 @@ +# DBPN + +--- + +model-name: DBPN + +backbone-name: DBPN + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: div2k + +evaluation: PSNR29.23 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 00ad7584fde0e5a926596ed91bebd5c13aa04086c22ac6def15a9d14dcd7eec1 + +license: Apache2.0 + +summary: DBPN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of DBPN from the MindSpore model zoo on Gitee at research/cv/DBPN. + +DBPN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/DBPN](https://gitee.com/mindspore/models/blob/r1.6/research/cv/DBPN/README.md). + +All parameters in the module are trainable. + +## Citation + +Muhammad Haris, Greg Shakhnarovich, Norimichi Ukita + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/ddag_allresearch_sysumm01.md b/mshub_res/assets/mindspore/1.6/ddag_allresearch_sysumm01.md new file mode 100644 index 0000000..a8f0d54 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/ddag_allresearch_sysumm01.md @@ -0,0 +1,62 @@ +# DDAG + +--- + +model-name: DDAG + +backbone-name: DDAG + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: sysumm01 + +evaluation: rank1acc54 | mAP53 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: b96d446b3505789109dfb8e177173e8db9d673697e718af7ee7a3569ab9962eb + +license: Apache2.0 + +summary: DDAG is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of DDAG from the MindSpore model zoo on Gitee at research/cv/DDAG. + +DDAG is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/DDAG](https://gitee.com/mindspore/models/blob/r1.6/research/cv/DDAG/README.md). + +All parameters in the module are trainable. + +## Citation + +*Dynamic Dual-Attentive Aggregation Learning for Visible-Infrared Person Re-Identification* in ECCV 2020 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/ddag_indoorsearch_sysumm01.md b/mshub_res/assets/mindspore/1.6/ddag_indoorsearch_sysumm01.md new file mode 100644 index 0000000..d404aa9 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/ddag_indoorsearch_sysumm01.md @@ -0,0 +1,62 @@ +# DDAG + +--- + +model-name: DDAG + +backbone-name: DDAG + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: sysumm01 + +evaluation: rank1acc64 | mAP68 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: cf886e258622971503d06db8611b8ecddb1f7f0a5e1a7237a53068679200454f + +license: Apache2.0 + +summary: DDAG is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of DDAG from the MindSpore model zoo on Gitee at research/cv/DDAG. + +DDAG is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/DDAG](https://gitee.com/mindspore/models/blob/r1.6/research/cv/DDAG/README.md). + +All parameters in the module are trainable. + +## Citation + +*Dynamic Dual-Attentive Aggregation Learning for Visible-Infrared Person Re-Identification* in ECCV 2020 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/ddag_infraredtovisible_regdb.md b/mshub_res/assets/mindspore/1.6/ddag_infraredtovisible_regdb.md new file mode 100644 index 0000000..cdd6584 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/ddag_infraredtovisible_regdb.md @@ -0,0 +1,62 @@ +# DDAG + +--- + +model-name: DDAG + +backbone-name: DDAG + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: regdb + +evaluation: rank1acc68 | mAP61 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 7e35eb2e7b9431df5c776740dde0f7076c98d82c3b814287ffcb72db96f052fe + +license: Apache2.0 + +summary: DDAG is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of DDAG from the MindSpore model zoo on Gitee at research/cv/DDAG. + +DDAG is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/DDAG](https://gitee.com/mindspore/models/blob/r1.6/research/cv/DDAG/README.md). + +All parameters in the module are trainable. + +## Citation + +*Dynamic Dual-Attentive Aggregation Learning for Visible-Infrared Person Re-Identification* in ECCV 2020 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/ddag_visibletoinfrared_regdb.md b/mshub_res/assets/mindspore/1.6/ddag_visibletoinfrared_regdb.md new file mode 100644 index 0000000..d64a28b --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/ddag_visibletoinfrared_regdb.md @@ -0,0 +1,62 @@ +# DDAG + +--- + +model-name: DDAG + +backbone-name: DDAG + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: regdb + +evaluation: rank1acc69 | mAP63 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 113bc2e02f8d78fdb6f5456728abf6d8bde4a8aad1699bb1b53d79941641bd75 + +license: Apache2.0 + +summary: DDAG is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of DDAG from the MindSpore model zoo on Gitee at research/cv/DDAG. + +DDAG is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/DDAG](https://gitee.com/mindspore/models/blob/r1.6/research/cv/DDAG/README.md). + +All parameters in the module are trainable. + +## Citation + +*Dynamic Dual-Attentive Aggregation Learning for Visible-Infrared Person Re-Identification* in ECCV 2020 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/deepfm_criteo.md b/mshub_res/assets/mindspore/1.6/deepfm_criteo.md new file mode 100644 index 0000000..90b453a --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/deepfm_criteo.md @@ -0,0 +1,79 @@ +# deepfm + +--- + +model-name: deepfm + +backbone-name: deepfm + +module-type: recommend + +fine-tunable: True + +model-version: 1.6 + +train-dataset: criteo + +evaluation: acc80.5 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 57e11deb538dd32a8612ee655c14fe1438afe993ecd1a98c6ba6cf9e9c73e22d + +license: Apache2.0 + +summary: deepfm is used for recommend + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of deepfm from the MindSpore model zoo on Gitee at official/recommend/deepfm. + +deepfm is a recommend network. More details please refer to the MindSpore model zoo on Gitee at [official/recommend/deepfm](https://gitee.com/mindspore/models/blob/r1.6/official/recommend/deepfm/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/deepfm_criteo" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, Xiuqiang He. DeepFM: A Factorization-Machine based Neural Network for CTR Prediction + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/deeplabv3s16_voc2012.md b/mshub_res/assets/mindspore/1.6/deeplabv3s16_voc2012.md new file mode 100644 index 0000000..eb4d612 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/deeplabv3s16_voc2012.md @@ -0,0 +1,79 @@ +# deeplabv3 + +--- + +model-name: deeplabv3 + +backbone-name: deeplabv3 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: voc2012 + +evaluation: acc78.68 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 46e997f97de3d6d4e35405be59bbb621c12d3ce62a688939f9046179473bfd9e + +license: Apache2.0 + +summary: deeplabv3 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of deeplabv3 from the MindSpore model zoo on Gitee at official/cv/deeplabv3. + +deeplabv3 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/deeplabv3](https://gitee.com/mindspore/models/blob/r1.6/official/cv/deeplabv3/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/deeplabv3s16_voc2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Chen L C, Papandreou G, Schroff F, et al. Rethinking atrous convolution for semantic image segmentation[J]. arXiv preprint arXiv:1706.05587, 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/deeplabv3s8r2_voc2012.md b/mshub_res/assets/mindspore/1.6/deeplabv3s8r2_voc2012.md new file mode 100644 index 0000000..d9df61a --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/deeplabv3s8r2_voc2012.md @@ -0,0 +1,79 @@ +# deeplabv3 + +--- + +model-name: deeplabv3 + +backbone-name: deeplabv3 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: voc2012 + +evaluation: s8acc78.51 | ns8mul79.26 | ns8mulflip79.37 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: bb00c4455d1b1eaf91ed8c8f1e755b68cfdf8b2c0d5f8a32a611caaa5ae91b0d + +license: Apache2.0 + +summary: deeplabv3 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of deeplabv3 from the MindSpore model zoo on Gitee at official/cv/deeplabv3. + +deeplabv3 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/deeplabv3](https://gitee.com/mindspore/models/blob/r1.6/official/cv/deeplabv3/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/deeplabv3s8r2_voc2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Chen L C, Papandreou G, Schroff F, et al. Rethinking atrous convolution for semantic image segmentation[J]. arXiv preprint arXiv:1706.05587, 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/deeptext_icdar2013_scutforu_cocotextv2.md b/mshub_res/assets/mindspore/1.6/deeptext_icdar2013_scutforu_cocotextv2.md new file mode 100644 index 0000000..1459464 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/deeptext_icdar2013_scutforu_cocotextv2.md @@ -0,0 +1,79 @@ +# deeptext + +--- + +model-name: deeptext + +backbone-name: deeptext + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: icdar2013_scutforu_cocotextv2 + +evaluation: F1score85 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 0ac5e5cbfd40ddcd16e30b7baa1904ac7ec20c5e3f8f8850aa20fac9baf03f37 + +license: Apache2.0 + +summary: deeptext is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of deeptext from the MindSpore model zoo on Gitee at official/cv/deeptext. + +deeptext is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/deeptext](https://gitee.com/mindspore/models/blob/r1.6/official/cv/deeptext/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/deeptext_icdar2013_scutforu_cocotextv2" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Zhuoyao Zhong, Lianwen Jin, Shuangping Huang, South China University of Technology (SCUT), Published in ICASSP 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/delf_gldv2.md b/mshub_res/assets/mindspore/1.6/delf_gldv2.md new file mode 100644 index 0000000..98f2854 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/delf_gldv2.md @@ -0,0 +1,62 @@ +# delf + +--- + +model-name: delf + +backbone-name: delf + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: gldv2 + +evaluation: oxford5kmap91.85 | paris6k87.87 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5158fb46a95179157bcb7ba8110985b80c906a253d98a6a82667b113b64a1f77 + +license: Apache2.0 + +summary: delf is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of delf from the MindSpore model zoo on Gitee at research/cv/delf. + +delf is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/delf](https://gitee.com/mindspore/models/blob/r1.6/research/cv/delf/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Noh, H. , et al. "Large-Scale Image Retrieval with Attentive Deep Local Features." *2017 IEEE International Conference on Computer Vision (ICCV)* IEEE, 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/dem_att_cub.md b/mshub_res/assets/mindspore/1.6/dem_att_cub.md new file mode 100644 index 0000000..4347d6e --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/dem_att_cub.md @@ -0,0 +1,79 @@ +# dem + +--- + +model-name: dem + +backbone-name: dem + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cub + +evaluation: acc59.63 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: b355ea64eabc6f4ba8462c952a8973885dcbb06623879a921f11b3e9d14ff474 + +license: Apache2.0 + +summary: dem is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of dem from the MindSpore model zoo on Gitee at research/cv/dem. + +dem is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/dem](https://gitee.com/mindspore/models/blob/r1.6/research/cv/dem/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/dem_att_cub" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Li Zhang, Tao Xiang, Shaogang Gong."Learning a Deep Embedding Model for Zero-Shot Learning" *Proceedings of the CVPR*.2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/densenet121_imagenet2012.md b/mshub_res/assets/mindspore/1.6/densenet121_imagenet2012.md new file mode 100644 index 0000000..2d4da6b --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/densenet121_imagenet2012.md @@ -0,0 +1,79 @@ +# densenet + +--- + +model-name: densenet + +backbone-name: densenet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc75.54 | top5acc92.73 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 032146e64d981fcc6c08925adcb348e50a3b6b8f653226b5147ef76560d4367a + +license: Apache2.0 + +summary: densenet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of densenet from the MindSpore model zoo on Gitee at official/cv/densenet. + +densenet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/densenet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/densenet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/densenet121_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Densely Connected Convolutional Networks + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/depthnet_coarsenet_nyu.md b/mshub_res/assets/mindspore/1.6/depthnet_coarsenet_nyu.md new file mode 100644 index 0000000..b681b68 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/depthnet_coarsenet_nyu.md @@ -0,0 +1,62 @@ +# depthnet + +--- + +model-name: depthnet + +backbone-name: depthnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: nyu + +evaluation: delta1loss61.16 | delta2loss87.7 | delta3loss96.33 | absrelativeloss23.14 | sqrrelativeloss23.19 | rmselinearloss77.37 | rmselogloss27.35 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 7478e758cb681540fd9defad9393ef8df1525a0af8d747a58a517a7b87f16ca2 + +license: Apache2.0 + +summary: depthnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of depthnet from the MindSpore model zoo on Gitee at official/cv/depthnet. + +depthnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/depthnet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/depthnet/README.md). + +All parameters in the module are trainable. + +## Citation + +Depth Map Prediction from a Single Image using a Multi-Scale Deep Network. David Eigen, Christian Puhrsch, Rob Fergus. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/depthnet_finenet_nyu.md b/mshub_res/assets/mindspore/1.6/depthnet_finenet_nyu.md new file mode 100644 index 0000000..a497684 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/depthnet_finenet_nyu.md @@ -0,0 +1,62 @@ +# depthnet + +--- + +model-name: depthnet + +backbone-name: depthnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: nyu + +evaluation: delta1loss61.21 | delta2loss87.75 | delta3loss96.31 | absrelativeloss23.07 | sqrrelativeloss23.16 | rmselinearloss77.22 | rmselogloss27.36 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: b26f82f9bbff69ef9d0230814791f7ec8af371c1c8abc693154386c3347c78b4 + +license: Apache2.0 + +summary: depthnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of depthnet from the MindSpore model zoo on Gitee at official/cv/depthnet. + +depthnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/depthnet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/depthnet/README.md). + +All parameters in the module are trainable. + +## Citation + +Depth Map Prediction from a Single Image using a Multi-Scale Deep Network. David Eigen, Christian Puhrsch, Rob Fergus. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/dgcn_citeseer.md b/mshub_res/assets/mindspore/1.6/dgcn_citeseer.md new file mode 100644 index 0000000..47c427f --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/dgcn_citeseer.md @@ -0,0 +1,62 @@ +# dgcn + +--- + +model-name: dgcn + +backbone-name: dgcn + +module-type: gnn + +fine-tunable: True + +model-version: 1.6 + +train-dataset: citeseer + +evaluation: acc72.2 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 773432ed4ccfcf8945cfee10c5c7c72d209820efb523565459594445237aa953 + +license: Apache2.0 + +summary: dgcn is used for gnn + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of dgcn from the MindSpore model zoo on Gitee at research/gnn/dgcn. + +dgcn is a gnn network. More details please refer to the MindSpore model zoo on Gitee at [research/gnn/dgcn](https://gitee.com/mindspore/models/blob/r1.6/research/gnn/dgcn/readme_CN.md). + +All parameters in the module are trainable. + +## Citation + +Dual Graph Convolutional Networks for Graph-Based Semi-Supervised Classification[C]// the 2018 World Wide Web Conference. 2018. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/dgcn_cora.md b/mshub_res/assets/mindspore/1.6/dgcn_cora.md new file mode 100644 index 0000000..bcac478 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/dgcn_cora.md @@ -0,0 +1,62 @@ +# dgcn + +--- + +model-name: dgcn + +backbone-name: dgcn + +module-type: gnn + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cora + +evaluation: acc82.8 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: a1b1bfb3d76afdcb4a19751db7ecb246c9fb736bca08b1231bf681d10a2cf368 + +license: Apache2.0 + +summary: dgcn is used for gnn + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of dgcn from the MindSpore model zoo on Gitee at research/gnn/dgcn. + +dgcn is a gnn network. More details please refer to the MindSpore model zoo on Gitee at [research/gnn/dgcn](https://gitee.com/mindspore/models/blob/r1.6/research/gnn/dgcn/readme_CN.md). + +All parameters in the module are trainable. + +## Citation + +Dual Graph Convolutional Networks for Graph-Based Semi-Supervised Classification[C]// the 2018 World Wide Web Conference. 2018. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/dgcn_pubmed.md b/mshub_res/assets/mindspore/1.6/dgcn_pubmed.md new file mode 100644 index 0000000..3896c7d --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/dgcn_pubmed.md @@ -0,0 +1,62 @@ +# dgcn + +--- + +model-name: dgcn + +backbone-name: dgcn + +module-type: gnn + +fine-tunable: True + +model-version: 1.6 + +train-dataset: pubmed + +evaluation: acc80.3 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 76ea88b1ab45abbea81c99a6ae0eb5bb64da64f5bba04dbc5ae1a5c87e7de3fd + +license: Apache2.0 + +summary: dgcn is used for gnn + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of dgcn from the MindSpore model zoo on Gitee at research/gnn/dgcn. + +dgcn is a gnn network. More details please refer to the MindSpore model zoo on Gitee at [research/gnn/dgcn](https://gitee.com/mindspore/models/blob/r1.6/research/gnn/dgcn/readme_CN.md). + +All parameters in the module are trainable. + +## Citation + +Dual Graph Convolutional Networks for Graph-Based Semi-Supervised Classification[C]// the 2018 World Wide Web Conference. 2018. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/dgu_udc.md b/mshub_res/assets/mindspore/1.6/dgu_udc.md new file mode 100644 index 0000000..886c5c2 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/dgu_udc.md @@ -0,0 +1,58 @@ +# dgu + +--- + +model-name: dgu + +backbone-name: dgu + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: udc + +evaluation: R1acc82.14 | R2acc90.45 | R5acc97.75 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: ef323d57071720e70df35c28d0d8cffcfafdefdfe694ca4c39b21d013f2b8542 + +license: Apache2.0 + +summary: dgu is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of dgu from the MindSpore model zoo on Gitee at official/nlp/dgu. + +dgu is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/dgu](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/dgu/README_CN.md). + +All parameters in the module are trainable. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/dlrm_criteo.md b/mshub_res/assets/mindspore/1.6/dlrm_criteo.md new file mode 100644 index 0000000..831507a --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/dlrm_criteo.md @@ -0,0 +1,62 @@ +# dlrm + +--- + +model-name: dlrm + +backbone-name: dlrm + +module-type: recommend + +fine-tunable: True + +model-version: 1.6 + +train-dataset: criteo + +evaluation: acc78.96 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: b4e9982c2c18458c30eee7cd2f791fd28e62244de12c45cef813940e418a89f4 + +license: Apache2.0 + +summary: dlrm is used for recommend + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of dlrm from the MindSpore model zoo on Gitee at research/recommend/dlrm. + +dlrm is a recommend network. More details please refer to the MindSpore model zoo on Gitee at [research/recommend/dlrm](https://gitee.com/mindspore/models/blob/r1.6/research/recommend/dlrm/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Naumov M, Mudigere D, Shi H J M, et al. Deep learning recommendation model for personalization and recommendation systems[J]. arXiv preprint arXiv:1906.00091, 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/dncnn_bsd500.md b/mshub_res/assets/mindspore/1.6/dncnn_bsd500.md new file mode 100644 index 0000000..82ecf58 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/dncnn_bsd500.md @@ -0,0 +1,62 @@ +# DnCNN + +--- + +model-name: DnCNN + +backbone-name: DnCNN + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: bsd500 + +evaluation: bsd68acc29 | set12acc30 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: e02c3010a0e6f8b5750e5de1fb5c12fa98ab932133cb1dbb62dfdd77f69607cd + +license: Apache2.0 + +summary: DnCNN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of DnCNN from the MindSpore model zoo on Gitee at research/cv/DnCNN. + +DnCNN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/DnCNN](https://gitee.com/mindspore/models/blob/r1.6/research/cv/DnCNN/README.md). + +All parameters in the module are trainable. + +## Citation + +K. Zhang, W. Zuo, Y. Chen, D. Meng and L. Zhang, "Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising," in IEEE Transactions on Image Processing, vol. 26, no. 7, pp. 3142-3155, July 2017, doi: 10.1109/TIP.2017.2662206. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/dpn_imagenet2012.md b/mshub_res/assets/mindspore/1.6/dpn_imagenet2012.md new file mode 100644 index 0000000..145c2f4 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/dpn_imagenet2012.md @@ -0,0 +1,79 @@ +# dpn + +--- + +model-name: dpn + +backbone-name: dpn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc78.81 | top5acc94.34 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 3fa441570f3a6ca0b8cc03dc4205bd881dafad4d8780daf153beec501947b9b2 + +license: Apache2.0 + +summary: dpn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of dpn from the MindSpore model zoo on Gitee at official/cv/dpn. + +dpn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/dpn](https://gitee.com/mindspore/models/blob/r1.6/official/cv/dpn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/dpn_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Yunpeng Chen, Jianan Li, Huaxin Xiao, Xiaojie Jin, Shuicheng Yan, Jiashi Feng. "Dual Path Networks" (NIPS17). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/dscnn_speechcommandsdatasetversion1.md b/mshub_res/assets/mindspore/1.6/dscnn_speechcommandsdatasetversion1.md new file mode 100644 index 0000000..e5bf649 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/dscnn_speechcommandsdatasetversion1.md @@ -0,0 +1,62 @@ +# dscnn + +--- + +model-name: dscnn + +backbone-name: dscnn + +module-type: audio + +fine-tunable: True + +model-version: 1.6 + +train-dataset: speechcommandsdatasetversion1 + +evaluation: acc93.77 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5d18afdd3ffe3e9ec179392a66dc3d36cc1af63521e44bd60b70aed6a29c08a5 + +license: Apache2.0 + +summary: dscnn is used for audio + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of dscnn from the MindSpore model zoo on Gitee at research/audio/dscnn. + +dscnn is a audio network. More details please refer to the MindSpore model zoo on Gitee at [research/audio/dscnn](https://gitee.com/mindspore/models/blob/r1.6/research/audio/dscnn/README.md). + +All parameters in the module are trainable. + +## Citation + +Zhang, Yundong, Naveen Suda, Liangzhen Lai, and Vikas Chandra. "Hello edge: Keyword spotting on microcontrollers." arXiv preprint arXiv:1711.07128 (2017). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/east_icdar2015.md b/mshub_res/assets/mindspore/1.6/east_icdar2015.md new file mode 100644 index 0000000..7b904ca --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/east_icdar2015.md @@ -0,0 +1,62 @@ +# east + +--- + +model-name: east + +backbone-name: east + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: icdar2015 + +evaluation: acc81 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 4fa8a1a81a9d49db853cb483b2763e06219726158a8db96dcccbcd36d5d9ee52 + +license: Apache2.0 + +summary: east is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of east from the MindSpore model zoo on Gitee at official/cv/east. + +east is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/east](https://gitee.com/mindspore/models/blob/r1.6/official/cv/east/README.md). + +All parameters in the module are trainable. + +## Citation + +Xinyu Zhou, Cong Yao, He Wen, Yuzhi Wang, Shuchang Zhou, Weiran He, and Jiajun Liang Megvii Technology Inc., Beijing, China, Published in CVPR 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/edcn_criteo.md b/mshub_res/assets/mindspore/1.6/edcn_criteo.md new file mode 100644 index 0000000..f6d22d7 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/edcn_criteo.md @@ -0,0 +1,79 @@ +# EDCN + +--- + +model-name: EDCN + +backbone-name: EDCN + +module-type: recommend + +fine-tunable: True + +model-version: 1.6 + +train-dataset: criteo + +evaluation: acc81 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 33a5c3334d3781ac8718e4a3aa442d1c9a1a6813d49d1ff40d3a0e415225229b + +license: Apache2.0 + +summary: EDCN is used for recommend + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of EDCN from the MindSpore model zoo on Gitee at research/recommend/EDCN. + +EDCN is a recommend network. More details please refer to the MindSpore model zoo on Gitee at [research/recommend/EDCN](https://gitee.com/mindspore/models/blob/r1.6/research/recommend/EDCN/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/edcn_criteo" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Bo Chen*, Yichao Wang*, Zhirong Liu, Ruiming Tang, Wei Guo, Hongkun Zheng, Weiwei Yao, Muyu Zhang, Xiuqiang He. Enhancing Explicit and Implicit Feature Interactions via Information Sharing for Parallel Deep CTR Models + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/efficientnetb0_imagenet2012.md b/mshub_res/assets/mindspore/1.6/efficientnetb0_imagenet2012.md new file mode 100644 index 0000000..5d1dc9f --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/efficientnetb0_imagenet2012.md @@ -0,0 +1,62 @@ +# efficientnet-b0 + +--- + +model-name: efficientnet-b0 + +backbone-name: efficientnet-b0 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc76 | top5acc93 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 729e24f509546b149120624ed7577274ba9ed26ba06d1a88e11989ac1c9df344 + +license: Apache2.0 + +summary: efficientnet-b0 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of efficientnet-b0 from the MindSpore model zoo on Gitee at research/cv/efficientnet-b0. + +efficientnet-b0 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/efficientnet-b0](https://gitee.com/mindspore/models/blob/r1.6/research/cv/efficientnet-b0/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Mingxing Tan, Quoc V. Le. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/efficientnetb1_imagenet2012.md b/mshub_res/assets/mindspore/1.6/efficientnetb1_imagenet2012.md new file mode 100644 index 0000000..05f6610 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/efficientnetb1_imagenet2012.md @@ -0,0 +1,62 @@ +# efficientnet-b1 + +--- + +model-name: efficientnet-b1 + +backbone-name: efficientnet-b1 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc78.1 | top5acc94 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 49dec0aa32348a08ff7ef17b857c6d542809411469205dc1d478e130b8f8eb48 + +license: Apache2.0 + +summary: efficientnet-b1 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of efficientnet-b1 from the MindSpore model zoo on Gitee at research/cv/efficientnet-b1. + +efficientnet-b1 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/efficientnet-b1](https://gitee.com/mindspore/models/blob/r1.6/research/cv/efficientnet-b1/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Mingxing Tan, Quoc V. Le. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/efficientnetb2_imagenet2012.md b/mshub_res/assets/mindspore/1.6/efficientnetb2_imagenet2012.md new file mode 100644 index 0000000..9358b85 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/efficientnetb2_imagenet2012.md @@ -0,0 +1,62 @@ +# efficientnet-b2 + +--- + +model-name: efficientnet-b2 + +backbone-name: efficientnet-b2 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc79 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 55799d18a7c55199bc733257d548bbe9ed6341278f9c0af7dc88edc22ee9d386 + +license: Apache2.0 + +summary: efficientnet-b2 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of efficientnet-b2 from the MindSpore model zoo on Gitee at research/cv/efficientnet-b2. + +efficientnet-b2 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/efficientnet-b2](https://gitee.com/mindspore/models/blob/r1.6/research/cv/efficientnet-b2/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Mingxing Tan, Quoc V. Le. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/efficientnetb3_imagenet2012.md b/mshub_res/assets/mindspore/1.6/efficientnetb3_imagenet2012.md new file mode 100644 index 0000000..9a0d13d --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/efficientnetb3_imagenet2012.md @@ -0,0 +1,62 @@ +# efficientnet-b3 + +--- + +model-name: efficientnet-b3 + +backbone-name: efficientnet-b3 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc80 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 1409576e02e431ab6b71e1f96c3aa56ebb8b87a1f6d3fd96a1973c64b917c0b9 + +license: Apache2.0 + +summary: efficientnet-b3 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of efficientnet-b3 from the MindSpore model zoo on Gitee at research/cv/efficientnet-b3. + +efficientnet-b3 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/efficientnet-b3](https://gitee.com/mindspore/models/blob/r1.6/research/cv/efficientnet-b3/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Mingxing Tan, Quoc V. Le. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/emotect_baidu.md b/mshub_res/assets/mindspore/1.6/emotect_baidu.md new file mode 100644 index 0000000..8cee60c --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/emotect_baidu.md @@ -0,0 +1,58 @@ +# emotect + +--- + +model-name: emotect + +backbone-name: emotect + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: baidu + +evaluation: acc90.44 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5b0ddb04f17f27d706007353d15faf93b627dcaf0ce7fcfcf1b61d4f2ddc228b + +license: Apache2.0 + +summary: emotect is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of emotect from the MindSpore model zoo on Gitee at official/nlp/emotect. + +emotect is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/emotect](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/emotect/README_CN.md). + +All parameters in the module are trainable. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/erfnet_cityscapes.md b/mshub_res/assets/mindspore/1.6/erfnet_cityscapes.md new file mode 100644 index 0000000..9e930d1 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/erfnet_cityscapes.md @@ -0,0 +1,63 @@ +# erfnet + +--- + +model-name: erfnet + +backbone-name: erfnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cityscapes + +evaluation: acc70 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c356bab8810edfd54b6b9817eb37bdb6fb034e00da29f7a62ca9394aa58a05cc + +license: Apache2.0 + +summary: erfnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of erfnet from the MindSpore model zoo on Gitee at official/cv/erfnet. + +erfnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/erfnet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/erfnet/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +1. E. Romera, J. M. Alvarez, L. M. Bergasa and R. Arroyo."ERFNet: Efficient Residual Factorized ConvNet for Real-time Semantic Segmentation" +2. A. Paszke, A. Chaurasia, S. Kim, and E. Culurciello."ENet: A deep neural network architecture for real-time semantic segmentation." + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/faceattribute_fairface_rwmfd.md b/mshub_res/assets/mindspore/1.6/faceattribute_fairface_rwmfd.md new file mode 100644 index 0000000..afa72e4 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/faceattribute_fairface_rwmfd.md @@ -0,0 +1,62 @@ +# FaceAttribute + +--- + +model-name: FaceAttribute + +backbone-name: FaceAttribute + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: fairface_rwmfd + +evaluation: age49 | gender90 | mask99 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 6301d259829abf1fc2fcd1cf537b411ff6ab4aaf31fa9abf0d0160b7f08bde3c + +license: Apache2.0 + +summary: FaceAttribute is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of FaceAttribute from the MindSpore model zoo on Gitee at research/cv/FaceAttribute. + +FaceAttribute is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/FaceAttribute](https://gitee.com/mindspore/models/blob/r1.6/research/cv/FaceAttribute/README.md). + +All parameters in the module are trainable. + +## Citation + +Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. "Deep Residual Learning for Image Recognition" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/facedetection_widerface.md b/mshub_res/assets/mindspore/1.6/facedetection_widerface.md new file mode 100644 index 0000000..821a1c2 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/facedetection_widerface.md @@ -0,0 +1,79 @@ +# FaceDetection + +--- + +model-name: FaceDetection + +backbone-name: FaceDetection + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: widerface + +evaluation: mAP75 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: ce9c845efe2145a71dcadca8e5f7721f2edd27b0560f186f16c34d22001923d5 + +license: Apache2.0 + +summary: FaceDetection is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of FaceDetection from the MindSpore model zoo on Gitee at research/cv/FaceDetection. + +FaceDetection is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/FaceDetection](https://gitee.com/mindspore/models/blob/r1.6/research/cv/FaceDetection/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/facedetection_widerface" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +YOLOv3: An Incremental Improvement. Joseph Redmon, Ali Farhadi, University of Washington + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/facequalityassessment_300wlp.md b/mshub_res/assets/mindspore/1.6/facequalityassessment_300wlp.md new file mode 100644 index 0000000..2438539 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/facequalityassessment_300wlp.md @@ -0,0 +1,79 @@ +# FaceQualityAssessment + +--- + +model-name: FaceQualityAssessment + +backbone-name: FaceQualityAssessment + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: 300wlp + +evaluation: IPN19 | MAE18 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 07e44357d9a9a2b30677479e6bfce8a867d8333a16a20f22eca6e08d9f35a4c6 + +license: Apache2.0 + +summary: FaceQualityAssessment is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of FaceQualityAssessment from the MindSpore model zoo on Gitee at research/cv/FaceQualityAssessment. + +FaceQualityAssessment is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/FaceQualityAssessment](https://gitee.com/mindspore/models/blob/r1.6/research/cv/FaceQualityAssessment/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/facequalityassessment_300wlp" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. "Deep Residual Learning for Image Recognition" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/facerecognition_ms1mv2.md b/mshub_res/assets/mindspore/1.6/facerecognition_ms1mv2.md new file mode 100644 index 0000000..6e63532 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/facerecognition_ms1mv2.md @@ -0,0 +1,79 @@ +# FaceRecognition + +--- + +model-name: FaceRecognition + +backbone-name: FaceRecognition + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: ms1mv2 + +evaluation: acc90 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: fcbaed741e5f4e3360d058afcee3276455a958f06a84f3cfc96445d88f6f236a + +license: Apache2.0 + +summary: FaceRecognition is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of FaceRecognition from the MindSpore model zoo on Gitee at research/cv/FaceRecognition. + +FaceRecognition is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/FaceRecognition](https://gitee.com/mindspore/models/blob/r1.6/research/cv/FaceRecognition/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/facerecognition_ms1mv2" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. "Deep Residual Learning for Image Recognition" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/facerecognitionfortracking_lfw.md b/mshub_res/assets/mindspore/1.6/facerecognitionfortracking_lfw.md new file mode 100644 index 0000000..6214742 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/facerecognitionfortracking_lfw.md @@ -0,0 +1,79 @@ +# FaceRecognitionForTracking + +--- + +model-name: FaceRecognitionForTracking + +backbone-name: FaceRecognitionForTracking + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: lfw + +evaluation: FAR0.1recall62 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: e1ff7aab52774fea4d997b7afb83de5ec3a9aef5f49657111df8d3220c69cf05 + +license: Apache2.0 + +summary: FaceRecognitionForTracking is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of FaceRecognitionForTracking from the MindSpore model zoo on Gitee at research/cv/FaceRecognitionForTracking. + +FaceRecognitionForTracking is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/FaceRecognitionForTracking](https://gitee.com/mindspore/models/blob/r1.6/research/cv/FaceRecognitionForTracking/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/facerecognitionfortracking_lfw" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. "Deep Residual Learning for Image Recognition" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/fasterrcnndcn_coco2017.md b/mshub_res/assets/mindspore/1.6/fasterrcnndcn_coco2017.md new file mode 100644 index 0000000..c93f747 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/fasterrcnndcn_coco2017.md @@ -0,0 +1,62 @@ +# faster_rcnn_dcn + +--- + +model-name: faster_rcnn_dcn + +backbone-name: faster_rcnn_dcn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: acc40.2 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5f78ead585bb3772c49afcd525ac2f696819eea5864c33054ebd6cdf7eae3226 + +license: Apache2.0 + +summary: faster_rcnn_dcn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of faster_rcnn_dcn from the MindSpore model zoo on Gitee at research/cv/faster_rcnn_dcn. + +faster_rcnn_dcn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/faster_rcnn_dcn](https://gitee.com/mindspore/models/blob/r1.6/research/cv/faster_rcnn_dcn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Ren S , He K , Girshick R , et al. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 39(6). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/fasterrcnnresnetv1101_coco2017.md b/mshub_res/assets/mindspore/1.6/fasterrcnnresnetv1101_coco2017.md new file mode 100644 index 0000000..9a08446 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/fasterrcnnresnetv1101_coco2017.md @@ -0,0 +1,79 @@ +# faster_rcnn + +--- + +model-name: faster_rcnn + +backbone-name: faster_rcnn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: mAP40.2 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: bda0ddecfca47b953c2bc701ecc58846b0883d8218fa12f5ea484e6f8f7299d9 + +license: Apache2.0 + +summary: faster_rcnn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of faster_rcnn from the MindSpore model zoo on Gitee at official/cv/faster_rcnn. + +faster_rcnn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/faster_rcnn](https://gitee.com/mindspore/models/blob/r1.6/official/cv/faster_rcnn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/fasterrcnnresnetv1101_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Ren S , He K , Girshick R , et al. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 39(6). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/fasterrcnnresnetv1152_coco2017.md b/mshub_res/assets/mindspore/1.6/fasterrcnnresnetv1152_coco2017.md new file mode 100644 index 0000000..301fa75 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/fasterrcnnresnetv1152_coco2017.md @@ -0,0 +1,79 @@ +# faster_rcnn + +--- + +model-name: faster_rcnn + +backbone-name: faster_rcnn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: mAP41.1 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 8bdce4abb45407ae395369a8cb0c2c1e78694d136e5e7f6332a604ff7c2d8007 + +license: Apache2.0 + +summary: faster_rcnn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of faster_rcnn from the MindSpore model zoo on Gitee at official/cv/faster_rcnn. + +faster_rcnn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/faster_rcnn](https://gitee.com/mindspore/models/blob/r1.6/official/cv/faster_rcnn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/fasterrcnnresnetv1152_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Ren S , He K , Girshick R , et al. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 39(6). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/fasterrcnnresnetv150_coco2017.md b/mshub_res/assets/mindspore/1.6/fasterrcnnresnetv150_coco2017.md new file mode 100644 index 0000000..95f2a7b --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/fasterrcnnresnetv150_coco2017.md @@ -0,0 +1,79 @@ +# faster_rcnn + +--- + +model-name: faster_rcnn + +backbone-name: faster_rcnn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: mAP@.5IoU60.6 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: f8efcd9fe8900ee6b6cd9bab1c7b6f650c290e8d70a3557e619404fd828dfa9f + +license: Apache2.0 + +summary: faster_rcnn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of faster_rcnn from the MindSpore model zoo on Gitee at official/cv/faster_rcnn. + +faster_rcnn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/faster_rcnn](https://gitee.com/mindspore/models/blob/r1.6/official/cv/faster_rcnn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/fasterrcnnresnetv150_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Ren S , He K , Girshick R , et al. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 39(6). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/fastscnn_cityspaces.md b/mshub_res/assets/mindspore/1.6/fastscnn_cityspaces.md new file mode 100644 index 0000000..7df8ffa --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/fastscnn_cityspaces.md @@ -0,0 +1,62 @@ +# fastscnn + +--- + +model-name: fastscnn + +backbone-name: fastscnn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cityspaces + +evaluation: acc54 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 74f4e5fb01d4ae9384fa9cd5da5f92fbc804cade3c8d0df608f41998af0e1889 + +license: Apache2.0 + +summary: fastscnn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of fastscnn from the MindSpore model zoo on Gitee at official/cv/fastscnn. + +fastscnn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/fastscnn](https://gitee.com/mindspore/models/blob/r1.6/official/cv/fastscnn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Poudel R , Liwicki S , Cipolla R . Fast-SCNN: Fast Semantic Segmentation Network[J]. 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/fasttext_agnews.md b/mshub_res/assets/mindspore/1.6/fasttext_agnews.md new file mode 100644 index 0000000..7c91b2a --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/fasttext_agnews.md @@ -0,0 +1,79 @@ +# fasttext + +--- + +model-name: fasttext + +backbone-name: fasttext + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: agnews + +evaluation: acc92.58 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 067f30b7b6cd19bb8a79601f1da365a1189881a3050f82d610b4f107c4d75d97 + +license: Apache2.0 + +summary: fasttext is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of fasttext from the MindSpore model zoo on Gitee at official/nlp/fasttext. + +fasttext is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/fasttext](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/fasttext/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/fasttext_agnews" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +"Bag of Tricks for Efficient Text Classification", 2016, A. Joulin, E. Grave, P. Bojanowski, and T. Mikolov + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/fasttext_dbpedia.md b/mshub_res/assets/mindspore/1.6/fasttext_dbpedia.md new file mode 100644 index 0000000..6045b9e --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/fasttext_dbpedia.md @@ -0,0 +1,79 @@ +# fasttext + +--- + +model-name: fasttext + +backbone-name: fasttext + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: dbpedia + +evaluation: acc98.62 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 3798190b1dbb78c4e76baac2b1228bab6c0e5ba5dfdede664fab47abc02d0b1e + +license: Apache2.0 + +summary: fasttext is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of fasttext from the MindSpore model zoo on Gitee at official/nlp/fasttext. + +fasttext is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/fasttext](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/fasttext/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/fasttext_dbpedia" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +"Bag of Tricks for Efficient Text Classification", 2016, A. Joulin, E. Grave, P. Bojanowski, and T. Mikolov + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/fasttext_yelp.md b/mshub_res/assets/mindspore/1.6/fasttext_yelp.md new file mode 100644 index 0000000..d57e6ce --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/fasttext_yelp.md @@ -0,0 +1,79 @@ +# fasttext + +--- + +model-name: fasttext + +backbone-name: fasttext + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: yelp + +evaluation: acc95.86 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c6156d218c0e9ee484c273558e709c6f733528b0a14fdefdde1117db4dfe35c0 + +license: Apache2.0 + +summary: fasttext is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of fasttext from the MindSpore model zoo on Gitee at official/nlp/fasttext. + +fasttext is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/fasttext](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/fasttext/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/fasttext_yelp" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +"Bag of Tricks for Efficient Text Classification", 2016, A. Joulin, E. Grave, P. Bojanowski, and T. Mikolov + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/fatdeepffm_criteo.md b/mshub_res/assets/mindspore/1.6/fatdeepffm_criteo.md new file mode 100644 index 0000000..a082895 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/fatdeepffm_criteo.md @@ -0,0 +1,62 @@ +# Fat-DeepFFM + +--- + +model-name: Fat-DeepFFM + +backbone-name: Fat-DeepFFM + +module-type: recommend + +fine-tunable: True + +model-version: 1.6 + +train-dataset: criteo + +evaluation: acc80.91 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c347768ae3632983113fdf0583aa766db4300cd9abd9653699d135bfcd8dc938 + +license: Apache2.0 + +summary: Fat-DeepFFM is used for recommend + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of Fat-DeepFFM from the MindSpore model zoo on Gitee at research/recommend/Fat-DeepFFM. + +Fat-DeepFFM is a recommend network. More details please refer to the MindSpore model zoo on Gitee at [research/recommend/Fat-DeepFFM](https://gitee.com/mindspore/models/blob/r1.6/research/recommend/Fat-DeepFFM/README.md). + +All parameters in the module are trainable. + +## Citation + +Junlin Zhang , Tongwen Huang , Zhiqi Zhang FAT-DeepFFM: Field Attentive Deep Field-aware Factorization Machine + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/fcanet_augmentedpascal.md b/mshub_res/assets/mindspore/1.6/fcanet_augmentedpascal.md new file mode 100644 index 0000000..3a42ade --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/fcanet_augmentedpascal.md @@ -0,0 +1,62 @@ +# FCANet + +--- + +model-name: FCANet + +backbone-name: FCANet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: augmentedpascal + +evaluation: gracut2.38 | berkeley4.75 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: fcd13f4b29e0cf3a1f5fd8deb584b44b37810019bf45e4688b29d98ab156924e + +license: Apache2.0 + +summary: FCANet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of FCANet from the MindSpore model zoo on Gitee at research/cv/FCANet. + +FCANet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/FCANet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/FCANet/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Zheng Lin, Zhao Zhang, Lin-Zhuo Chen, Ming-Ming Cheng，Shao-Ping Lu，Interactive Image Segmentation with First Click Attention. (CVPR2020) + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/fcn4_musictagging.md b/mshub_res/assets/mindspore/1.6/fcn4_musictagging.md new file mode 100644 index 0000000..2482a5d --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/fcn4_musictagging.md @@ -0,0 +1,79 @@ +# fcn-4 + +--- + +model-name: fcn-4 + +backbone-name: fcn-4 + +module-type: audio + +fine-tunable: True + +model-version: 1.6 + +train-dataset: musictagging + +evaluation: acc90.89 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: bdb7116d2dc25ae80381a882b9d8a75f857e53a920561015e3a9245cf469d284 + +license: Apache2.0 + +summary: fcn-4 is used for audio + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of fcn-4 from the MindSpore model zoo on Gitee at research/audio/fcn-4. + +fcn-4 is a audio network. More details please refer to the MindSpore model zoo on Gitee at [research/audio/fcn-4](https://gitee.com/mindspore/models/blob/r1.6/research/audio/fcn-4/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/fcn4_musictagging" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +"Keunwoo Choi, George Fazekas, and Mark Sandler, “Automatic tagging using deep convolutional neural networks,” in International Society of Music Information Retrieval Conference. ISMIR, 2016." + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/fcn8s_voc2012.md b/mshub_res/assets/mindspore/1.6/fcn8s_voc2012.md new file mode 100644 index 0000000..2fdd96e --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/fcn8s_voc2012.md @@ -0,0 +1,79 @@ +# FCN8s + +--- + +model-name: FCN8s + +backbone-name: FCN8s + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: voc2012 + +evaluation: meanIoU64.57 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: e941446770369cad03e60a4154c3a6dc8e8ab20c19fa37ce2bd6f59fb9b97663 + +license: Apache2.0 + +summary: FCN8s is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of FCN8s from the MindSpore model zoo on Gitee at official/cv/FCN8s. + +FCN8s is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/FCN8s](https://gitee.com/mindspore/models/blob/r1.6/official/cv/FCN8s/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/fcn8s_voc2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Long, Jonathan, Evan Shelhamer, and Trevor Darrell. "Fully convolutional networks for semantic segmentation." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/fishnet99_imagenet2012.md b/mshub_res/assets/mindspore/1.6/fishnet99_imagenet2012.md new file mode 100644 index 0000000..8b5ee65 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/fishnet99_imagenet2012.md @@ -0,0 +1,62 @@ +# fishnet99 + +--- + +model-name: fishnet99 + +backbone-name: fishnet99 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc77.88 | top5acc93.88 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 95e536ca3b4b1f1fa9061b5f9cf75bdc15fb2a1fc8e1a820442516c980ebf7d3 + +license: Apache2.0 + +summary: fishnet99 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of fishnet99 from the MindSpore model zoo on Gitee at research/cv/fishnet99. + +fishnet99 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/fishnet99](https://gitee.com/mindspore/models/blob/r1.6/research/cv/fishnet99/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +FishNet: a versatile backbone for image, region, and pixel level prediction. In Proceedings of the 32nd International Conference on Neural Information Processing Systems (NIPS'18). Curran Associates Inc., Red Hook, NY, USA, 762–772. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/gan_G_mnist.md b/mshub_res/assets/mindspore/1.6/gan_G_mnist.md new file mode 100644 index 0000000..0300644 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/gan_G_mnist.md @@ -0,0 +1,62 @@ +# gan + +--- + +model-name: gan + +backbone-name: gan + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: mnist + +evaluation: likelihood220.47 | se2.33 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 78dd2421ad81e2088cbb43ee11a019eb3ac74c27e1e75fff597cb3f659840c6b + +license: Apache2.0 + +summary: gan is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of gan from the MindSpore model zoo on Gitee at research/cv/gan. + +gan is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/gan](https://gitee.com/mindspore/models/blob/r1.6/research/cv/gan/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Goodfellow I, Pouget-Abadie J, Mirza M, et al. Generative adversarial nets[J]. Advances in neural information processing systems, 2014, 27. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/gat_citeseer.md b/mshub_res/assets/mindspore/1.6/gat_citeseer.md new file mode 100644 index 0000000..7addab3 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/gat_citeseer.md @@ -0,0 +1,79 @@ +# gat + +--- + +model-name: gat + +backbone-name: gat + +module-type: gnn + +fine-tunable: True + +model-version: 1.6 + +train-dataset: citeseer + +evaluation: acc72.4 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 19500c505053c4c7491d303f729bbc8d757fb44993b9c1fdfa97d1551ff4f1e4 + +license: Apache2.0 + +summary: gat is used for gnn + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of gat from the MindSpore model zoo on Gitee at official/gnn/gat. + +gat is a gnn network. More details please refer to the MindSpore model zoo on Gitee at [official/gnn/gat](https://gitee.com/mindspore/models/blob/r1.6/official/gnn/gat/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/gat_citeseer" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Veličković, P., Cucurull, G., Casanova, A., Romero, A., Lio, P., & Bengio, Y. (2017).Graph attention networks. arXiv preprint arXiv:1710.10903. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/gat_cora.md b/mshub_res/assets/mindspore/1.6/gat_cora.md new file mode 100644 index 0000000..b49abca --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/gat_cora.md @@ -0,0 +1,79 @@ +# gat + +--- + +model-name: gat + +backbone-name: gat + +module-type: gnn + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cora + +evaluation: acc83.3 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 366b1211c0cbd2e101b7ae5ab1969dd0bc1f09d41a2b646c0c56f3e50b3627c3 + +license: Apache2.0 + +summary: gat is used for gnn + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of gat from the MindSpore model zoo on Gitee at official/gnn/gat. + +gat is a gnn network. More details please refer to the MindSpore model zoo on Gitee at [official/gnn/gat](https://gitee.com/mindspore/models/blob/r1.6/official/gnn/gat/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/gat_cora" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Veličković, P., Cucurull, G., Casanova, A., Romero, A., Lio, P., & Bengio, Y. (2017).Graph attention networks. arXiv preprint arXiv:1710.10903. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/gcn_citesser.md b/mshub_res/assets/mindspore/1.6/gcn_citesser.md new file mode 100644 index 0000000..1e28cd2 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/gcn_citesser.md @@ -0,0 +1,79 @@ +# gcn + +--- + +model-name: gcn + +backbone-name: gcn + +module-type: gnn + +fine-tunable: True + +model-version: 1.6 + +train-dataset: citesser + +evaluation: acc71.9 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 00cc8132de8f255591564040dbd655fc23e5826e0f6e350bd4e20ec85e910bf3 + +license: Apache2.0 + +summary: gcn is used for gnn + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of gcn from the MindSpore model zoo on Gitee at official/gnn/gcn. + +gcn is a gnn network. More details please refer to the MindSpore model zoo on Gitee at [official/gnn/gcn](https://gitee.com/mindspore/models/blob/r1.6/official/gnn/gcn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/gcn_citesser" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Thomas N. Kipf, Max Welling. 2016. Semi-Supervised Classification with Graph Convolutional Networks. In ICLR 2016. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/gcn_cora.md b/mshub_res/assets/mindspore/1.6/gcn_cora.md new file mode 100644 index 0000000..d99c640 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/gcn_cora.md @@ -0,0 +1,79 @@ +# gcn + +--- + +model-name: gcn + +backbone-name: gcn + +module-type: gnn + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cora + +evaluation: acc82.7 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5bf8a58e7129d0191c4e6c16d3eb346b6eb8885d5b7754b88fb8e959c9ae9876 + +license: Apache2.0 + +summary: gcn is used for gnn + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of gcn from the MindSpore model zoo on Gitee at official/gnn/gcn. + +gcn is a gnn network. More details please refer to the MindSpore model zoo on Gitee at [official/gnn/gcn](https://gitee.com/mindspore/models/blob/r1.6/official/gnn/gcn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/gcn_cora" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Thomas N. Kipf, Max Welling. 2016. Semi-Supervised Classification with Graph Convolutional Networks. In ICLR 2016. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/genetres50_minux_imagenet2012.md b/mshub_res/assets/mindspore/1.6/genetres50_minux_imagenet2012.md new file mode 100644 index 0000000..50d4121 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/genetres50_minux_imagenet2012.md @@ -0,0 +1,62 @@ +# GENet_Res50 + +--- + +model-name: GENet_Res50 + +backbone-name: GENet_Res50 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc77.75 | top5acc93.64 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 6b568bebdf808db1bdfd9d013bd45ecd132f5788275d4bd0a4b30884165015bd + +license: Apache2.0 + +summary: GENet_Res50 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of GENet_Res50 from the MindSpore model zoo on Gitee at research/cv/GENet_Res50. + +GENet_Res50 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/GENet_Res50](https://gitee.com/mindspore/models/blob/r1.6/research/cv/GENet_Res50/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/genetres50_plus_imagenet2012.md b/mshub_res/assets/mindspore/1.6/genetres50_plus_imagenet2012.md new file mode 100644 index 0000000..b7428f5 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/genetres50_plus_imagenet2012.md @@ -0,0 +1,62 @@ +# GENet_Res50 + +--- + +model-name: GENet_Res50 + +backbone-name: GENet_Res50 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc78.4 | top5acc94.14 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 407565a9b390e6daded58219afccc2352ecde06ce4dc4a4b89e3b9ae95030e53 + +license: Apache2.0 + +summary: GENet_Res50 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of GENet_Res50 from the MindSpore model zoo on Gitee at research/cv/GENet_Res50. + +GENet_Res50 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/GENet_Res50](https://gitee.com/mindspore/models/blob/r1.6/research/cv/GENet_Res50/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/genetres50_theta_imagenet2012.md b/mshub_res/assets/mindspore/1.6/genetres50_theta_imagenet2012.md new file mode 100644 index 0000000..0f55329 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/genetres50_theta_imagenet2012.md @@ -0,0 +1,62 @@ +# GENet_Res50 + +--- + +model-name: GENet_Res50 + +backbone-name: GENet_Res50 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc78.07 | top5acc93.93 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 44826193cafce1e97018e6b77712ecd077e2d5af4a03b2f3034b9772be80563d + +license: Apache2.0 + +summary: GENet_Res50 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of GENet_Res50 from the MindSpore model zoo on Gitee at research/cv/GENet_Res50. + +GENet_Res50 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/GENet_Res50](https://gitee.com/mindspore/models/blob/r1.6/research/cv/GENet_Res50/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/ghostnet_imagenet2012.md b/mshub_res/assets/mindspore/1.6/ghostnet_imagenet2012.md new file mode 100644 index 0000000..be426ff --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/ghostnet_imagenet2012.md @@ -0,0 +1,62 @@ +# ghostnet + +--- + +model-name: ghostnet + +backbone-name: ghostnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc73.81 | top5acc91.77 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 612f2fee612654057734283a50ff9eb9c967ee838c1b2f3b9b555e1689f53851 + +license: Apache2.0 + +summary: ghostnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ghostnet from the MindSpore model zoo on Gitee at research/cv/ghostnet. + +ghostnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ghostnet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/ghostnet/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Kai Han, Yunhe Wang, Qi Tian."GhostNet: More Features From Cheap Operations" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/gloreres200_imagenet2012.md b/mshub_res/assets/mindspore/1.6/gloreres200_imagenet2012.md new file mode 100644 index 0000000..a1bafdb --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/gloreres200_imagenet2012.md @@ -0,0 +1,62 @@ +# glore_res200 + +--- + +model-name: glore_res200 + +backbone-name: glore_res200 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc79.95 | top5acc94.89 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 106bba976cc6f7d5d59a74a63062d5600165090763fcfebc96af507b15c24dfb + +license: Apache2.0 + +summary: glore_res200 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of glore_res200 from the MindSpore model zoo on Gitee at research/cv/glore_res200. + +glore_res200 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/glore_res200](https://gitee.com/mindspore/models/blob/r1.6/research/cv/glore_res200/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Yunpeng Chenyz, Marcus Rohrbachy, Zhicheng Yany, Shuicheng Yanz, Jiashi Fengz, Yannis Kalantidisy + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/gloreres50_imagenet2012.md b/mshub_res/assets/mindspore/1.6/gloreres50_imagenet2012.md new file mode 100644 index 0000000..a931517 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/gloreres50_imagenet2012.md @@ -0,0 +1,62 @@ +# glore_res50 + +--- + +model-name: glore_res50 + +backbone-name: glore_res50 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc78.32 | top5acc94.02 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: b2ee8e5bdf5059b9229d539c485c8da1437b23c7b5554970808ca99610631efd + +license: Apache2.0 + +summary: glore_res50 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of glore_res50 from the MindSpore model zoo on Gitee at research/cv/glore_res50. + +glore_res50 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/glore_res50](https://gitee.com/mindspore/models/blob/r1.6/research/cv/glore_res50/README.md). + +All parameters in the module are trainable. + +## Citation + +Yupeng Chen, Marcus Rohrbach, Zhicheng Yan, Shuicheng Yan, Jiashi Feng, Yannis Kalantidis."Deep Residual Learning for Image Recognition" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/gnmtv2_wmtende.md b/mshub_res/assets/mindspore/1.6/gnmtv2_wmtende.md new file mode 100644 index 0000000..3a99ff2 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/gnmtv2_wmtende.md @@ -0,0 +1,79 @@ +# gnmt_v2 + +--- + +model-name: gnmt_v2 + +backbone-name: gnmt_v2 + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: wmtende + +evaluation: acc24 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 48546b769601e39e380c2ec3916930501195e200fe84f1ef04d91725b4380e1a + +license: Apache2.0 + +summary: gnmt_v2 is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of gnmt_v2 from the MindSpore model zoo on Gitee at official/nlp/gnmt_v2. + +gnmt_v2 is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/gnmt_v2](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/gnmt_v2/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/gnmtv2_wmtende" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/googlenet_cifar10.md b/mshub_res/assets/mindspore/1.6/googlenet_cifar10.md new file mode 100644 index 0000000..7717898 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/googlenet_cifar10.md @@ -0,0 +1,79 @@ +# googlenet + +--- + +model-name: googlenet + +backbone-name: googlenet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cifar10 + +evaluation: acc92.53 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: b2f7fe14782a3ab88ad3534ed5f419b4bbc3b477706258bd6ed8f90f529775e7 + +license: Apache2.0 + +summary: googlenet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of googlenet from the MindSpore model zoo on Gitee at official/cv/googlenet. + +googlenet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/googlenet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/googlenet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/googlenet_cifar10" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich. "Going deeper with convolutions." *Proceedings of the IEEE conference on computer vision and pattern recognition*. 2015. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/googlenet_imagenet2012.md b/mshub_res/assets/mindspore/1.6/googlenet_imagenet2012.md new file mode 100644 index 0000000..a3d5503 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/googlenet_imagenet2012.md @@ -0,0 +1,79 @@ +# googlenet + +--- + +model-name: googlenet + +backbone-name: googlenet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc72.97 | top5acc90.97 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c35b3baff0b4413988a95fa3691733a58d1695b66bf2ae47030c41e539885240 + +license: Apache2.0 + +summary: googlenet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of googlenet from the MindSpore model zoo on Gitee at official/cv/googlenet. + +googlenet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/googlenet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/googlenet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/googlenet_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich. "Going deeper with convolutions." *Proceedings of the IEEE conference on computer vision and pattern recognition*. 2015. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/gpt3_openweb.md b/mshub_res/assets/mindspore/1.6/gpt3_openweb.md new file mode 100644 index 0000000..2e97c1b --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/gpt3_openweb.md @@ -0,0 +1,79 @@ +# gpt + +--- + +model-name: gpt + +backbone-name: gpt + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: openweb + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: e4d4e4d4023b7475972250d8126a4e183eb60f3d87f11df1f1e09d414c58e448 + +license: Apache2.0 + +summary: gpt is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of gpt from the MindSpore model zoo on Gitee at official/nlp/gpt. + +gpt is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/gpt](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/gpt/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/gpt3_openweb" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Tom B.Brown, Benjamin Mann, Nick Ryder et al. Language Models are Few-Shot Learners. arXiv preprint arXiv:2005.14165 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/gru_muti30k.md b/mshub_res/assets/mindspore/1.6/gru_muti30k.md new file mode 100644 index 0000000..4b82fa9 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/gru_muti30k.md @@ -0,0 +1,81 @@ +# gru + +--- + +model-name: gru + +backbone-name: gru + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: muti30k + +evaluation: acc30 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 4d0e2582626ed286b9753b8e2b79dcd1c54dc87170f3ddae050796edb5ce8eeb + +license: Apache2.0 + +summary: gru is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of gru from the MindSpore model zoo on Gitee at official/nlp/gru. + +gru is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/gru](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/gru/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/gru_muti30k" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. "Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation", 2014, Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, Yoshua Bengio +2. "Sequence to Sequence Learning with Neural Networks", 2014, Ilya Sutskever, Oriol Vinyals, Quoc V. Le +3. "Neural Machine Translation by Jointly Learning to Align and Translate", 2014, Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/hardnet_imagenet2012.md b/mshub_res/assets/mindspore/1.6/hardnet_imagenet2012.md new file mode 100644 index 0000000..4b428c1 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/hardnet_imagenet2012.md @@ -0,0 +1,62 @@ +# hardnet + +--- + +model-name: hardnet + +backbone-name: hardnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc77.61 | top5acc93.61 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 9bda86bcba49a46f9f986431dba148f266437dd0196f0ebe50e3192cf4f01b0f + +license: Apache2.0 + +summary: hardnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of hardnet from the MindSpore model zoo on Gitee at research/cv/hardnet. + +hardnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/hardnet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/hardnet/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Chao P , Kao C Y , Ruan Y , et al. HarDNet: A Low Memory Traffic Network[C]// 2019 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2020. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/hrnet_cityscapes.md b/mshub_res/assets/mindspore/1.6/hrnet_cityscapes.md new file mode 100644 index 0000000..5088265 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/hrnet_cityscapes.md @@ -0,0 +1,62 @@ +# hrnet + +--- + +model-name: hrnet + +backbone-name: hrnet + +module-type: cvtmodel + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cityscapes + +evaluation: acc79 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: e36e05b484f8be0e4477261703853750205c38f7eb7cb1c034c990d360531e22 + +license: Apache2.0 + +summary: hrnet is used for cvtmodel + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of hrnet from the MindSpore model zoo on Gitee at research/cvtmodel/hrnet. + +hrnet is a cvtmodel network. More details please refer to the MindSpore model zoo on Gitee at [research/cvtmodel/hrnet](https://gitee.com/mindspore/models/blob/r1.6/research/cvtmodel/hrnet/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +http://rwightman.github.io/pytorch-image-models/models/ + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/hrnetw48cls_imagenet2012.md b/mshub_res/assets/mindspore/1.6/hrnetw48cls_imagenet2012.md new file mode 100644 index 0000000..5c3feb9 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/hrnetw48cls_imagenet2012.md @@ -0,0 +1,62 @@ +# HRNetW48_cls + +--- + +model-name: HRNetW48_cls + +backbone-name: HRNetW48_cls + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc79 | top5acc94 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 0ec1995df080ee801a33c6e9d659a4d3e2e677c642bf318ab96e3230b83fdca1 + +license: Apache2.0 + +summary: HRNetW48_cls is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of HRNetW48_cls from the MindSpore model zoo on Gitee at research/cv/HRNetW48_cls. + +HRNetW48_cls is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/HRNetW48_cls](https://gitee.com/mindspore/models/blob/r1.6/research/cv/HRNetW48_cls/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Deep High-Resolution Representation Learning for Visual Recognition. Jingdong Wang, Ke Sun, Tianheng Cheng, Borui Jiang, Chaorui Deng, Yang Zhao, Dong Liu, Yadong Mu, Mingkui Tan, Xinggang Wang, Wenyu Liu, Bin Xiao. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/hypertext_iflytek.md b/mshub_res/assets/mindspore/1.6/hypertext_iflytek.md new file mode 100644 index 0000000..e89535b --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/hypertext_iflytek.md @@ -0,0 +1,62 @@ +# hypertext + +--- + +model-name: hypertext + +backbone-name: hypertext + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: iflytek + +evaluation: acc58 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 720524602cfb91b3b2a759e420ccb54de686cb2508fa99b82c8af71314926be3 + +license: Apache2.0 + +summary: hypertext is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of hypertext from the MindSpore model zoo on Gitee at research/nlp/hypertext. + +hypertext is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [research/nlp/hypertext](https://gitee.com/mindspore/models/blob/r1.6/research/nlp/hypertext/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +[HyperText: Endowing FastText with Hyperbolic Geometry](https://arxiv.org/abs/2010.16143) + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/hypertext_tnews.md b/mshub_res/assets/mindspore/1.6/hypertext_tnews.md new file mode 100644 index 0000000..97d63ca --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/hypertext_tnews.md @@ -0,0 +1,62 @@ +# hypertext + +--- + +model-name: hypertext + +backbone-name: hypertext + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: tnews + +evaluation: acc91.3 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 704f893b690a8eb55f9ad4e4263eaed59890756e6f2a16674d0a5ffbbb3a674f + +license: Apache2.0 + +summary: hypertext is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of hypertext from the MindSpore model zoo on Gitee at research/nlp/hypertext. + +hypertext is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [research/nlp/hypertext](https://gitee.com/mindspore/models/blob/r1.6/research/nlp/hypertext/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +[HyperText: Endowing FastText with Hyperbolic Geometry](https://arxiv.org/abs/2010.16143) + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/ibnnet_imagenet2012.md b/mshub_res/assets/mindspore/1.6/ibnnet_imagenet2012.md new file mode 100644 index 0000000..27ec0dd --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/ibnnet_imagenet2012.md @@ -0,0 +1,62 @@ +# ibnnet + +--- + +model-name: ibnnet + +backbone-name: ibnnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc77.13 | top5acc93.59 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c9ab6f1198b1b930fb2df92715134de798e103c1dd66bca06f3ee826b1a9983e + +license: Apache2.0 + +summary: ibnnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ibnnet from the MindSpore model zoo on Gitee at research/cv/ibnnet. + +ibnnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ibnnet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/ibnnet/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Pan X , Ping L , Shi J , et al. Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net[C]// European Conference on Computer Vision. Springer, Cham, 2018. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/icnet_cityscapes.md b/mshub_res/assets/mindspore/1.6/icnet_cityscapes.md new file mode 100644 index 0000000..f78fc0a --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/icnet_cityscapes.md @@ -0,0 +1,62 @@ +# ICNet + +--- + +model-name: ICNet + +backbone-name: ICNet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cityscapes + +evaluation: avgmiou69.54 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 2a16822fefb0627b455c73a57321a9da24e2483b11487e173bcdc6c07841d867 + +license: Apache2.0 + +summary: ICNet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ICNet from the MindSpore model zoo on Gitee at research/cv/ICNet. + +ICNet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ICNet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/ICNet/README.md). + +All parameters in the module are trainable. + +## Citation + +ICNet for Real-Time Semantic Segmentation on High-Resolution Images + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/inceptionresnetv2_imagenet2012.md b/mshub_res/assets/mindspore/1.6/inceptionresnetv2_imagenet2012.md new file mode 100644 index 0000000..a538d0b --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/inceptionresnetv2_imagenet2012.md @@ -0,0 +1,62 @@ +# inception_resnet_v2 + +--- + +model-name: inception_resnet_v2 + +backbone-name: inception_resnet_v2 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc80.04 | top5acc94.54 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: cf282d78635945173a79accf2068b0c651aff1253eeae556f31428190b7e3dbd + +license: Apache2.0 + +summary: inception_resnet_v2 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of inception_resnet_v2 from the MindSpore model zoo on Gitee at research/cv/inception_resnet_v2. + +inception_resnet_v2 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/inception_resnet_v2](https://gitee.com/mindspore/models/blob/r1.6/research/cv/inception_resnet_v2/README.md). + +All parameters in the module are trainable. + +## Citation + +Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, Alex Alemi. Computer Vision and Pattern Recognition[J]. 2016. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/inceptionv3_imagenet2012.md b/mshub_res/assets/mindspore/1.6/inceptionv3_imagenet2012.md new file mode 100644 index 0000000..47db453 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/inceptionv3_imagenet2012.md @@ -0,0 +1,79 @@ +# inceptionv3 + +--- + +model-name: inceptionv3 + +backbone-name: inceptionv3 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc78.69 | top5acc94.3 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c3b6bd7fb0394255d8d96fde238face46e79b6a3a130c9a71135a1d8552536b4 + +license: Apache2.0 + +summary: inceptionv3 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of inceptionv3 from the MindSpore model zoo on Gitee at official/cv/inceptionv3. + +inceptionv3 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/inceptionv3](https://gitee.com/mindspore/models/blob/r1.6/official/cv/inceptionv3/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/inceptionv3_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Min Sun, Ali Farhadi, Steve Seitz. Ranking Domain-Specific Highlights by Analyzing Edited Videos[J]. 2014. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/inceptionv4_imagenet2012.md b/mshub_res/assets/mindspore/1.6/inceptionv4_imagenet2012.md new file mode 100644 index 0000000..68b4d2e --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/inceptionv4_imagenet2012.md @@ -0,0 +1,79 @@ +# inceptionv4 + +--- + +model-name: inceptionv4 + +backbone-name: inceptionv4 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc79.95 | top5acc94.83 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: da517828508f915ef06b3f33c45b8d52e0eaa019bbb86080de7f4beea30377f1 + +license: Apache2.0 + +summary: inceptionv4 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of inceptionv4 from the MindSpore model zoo on Gitee at official/cv/inceptionv4. + +inceptionv4 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/inceptionv4](https://gitee.com/mindspore/models/blob/r1.6/official/cv/inceptionv4/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/inceptionv4_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, Alex Alemi. Computer Vision and Pattern Recognition[J]. 2016. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/irn_div2k.md b/mshub_res/assets/mindspore/1.6/irn_div2k.md new file mode 100644 index 0000000..c9990dc --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/irn_div2k.md @@ -0,0 +1,62 @@ +# IRN + +--- + +model-name: IRN + +backbone-name: IRN + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: div2k + +evaluation: psnry34.77 | ssimy92.85 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 054d792d4b392cc87c045e43e29817770d52dff4b4efa0dbce6feadfb82159e0 + +license: Apache2.0 + +summary: IRN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of IRN from the MindSpore model zoo on Gitee at research/cv/IRN. + +IRN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/IRN](https://gitee.com/mindspore/models/blob/r1.6/research/cv/IRN/README.md). + +All parameters in the module are trainable. + +## Citation + +Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, and Tie-Yan Liu. 2020. Invertible Image Rescaling. In European Conference on Computer Vision (ECCV). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/learningtoseeinthedark_sony.md b/mshub_res/assets/mindspore/1.6/learningtoseeinthedark_sony.md new file mode 100644 index 0000000..b312ced --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/learningtoseeinthedark_sony.md @@ -0,0 +1,62 @@ +# LearningToSeeInTheDark + +--- + +model-name: LearningToSeeInTheDark + +backbone-name: LearningToSeeInTheDark + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: sony + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 039f394fe9dff0ed09600179f0135bffebf7699f64152993778bfeb72fcd5f20 + +license: Apache2.0 + +summary: LearningToSeeInTheDark is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of LearningToSeeInTheDark from the MindSpore model zoo on Gitee at research/cv/LearningToSeeInTheDark. + +LearningToSeeInTheDark is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/LearningToSeeInTheDark](https://gitee.com/mindspore/models/blob/r1.6/research/cv/LearningToSeeInTheDark/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Chen C, Chen Q, Xu J, et al. Learning to See in the Dark[C]// 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. IEEE, 2018. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/lenet_mnist.md b/mshub_res/assets/mindspore/1.6/lenet_mnist.md new file mode 100644 index 0000000..b0c121e --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/lenet_mnist.md @@ -0,0 +1,79 @@ +# lenet + +--- + +model-name: lenet + +backbone-name: lenet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: mnist + +evaluation: acc98.49 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: f0734abb1f74d3e4d96ed9baf3fd6f17596943d58cbb17509506fae4518fceef + +license: Apache2.0 + +summary: lenet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of lenet from the MindSpore model zoo on Gitee at official/cv/lenet. + +lenet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/lenet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/lenet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/lenet_mnist" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Y.Lecun, L.Bottou, Y.Bengio, P.Haffner. Gradient-Based Learning Applied to Document Recognition. *Proceedings of the IEEE*. 1998. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/lenetquant_mnist.md b/mshub_res/assets/mindspore/1.6/lenetquant_mnist.md new file mode 100644 index 0000000..9bf5d3d --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/lenetquant_mnist.md @@ -0,0 +1,79 @@ +# lenet_quant + +--- + +model-name: lenet_quant + +backbone-name: lenet_quant + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: mnist + +evaluation: acc98.79 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 92c14388fdf4ea90811de5031652b2e58570a5abf7c3653b0e958fb0e30f3546 + +license: Apache2.0 + +summary: lenet_quant is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of lenet_quant from the MindSpore model zoo on Gitee at official/cv/lenet_quant. + +lenet_quant is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/lenet_quant](https://gitee.com/mindspore/models/blob/r1.6/official/cv/lenet_quant/Readme.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/lenetquant_mnist" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Y.Lecun, L.Bottou, Y.Bengio, P.Haffner. Gradient-Based Learning Applied to Document Recognition. *Proceedings of the IEEE*. 1998. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/lpcnet_librispeech.md b/mshub_res/assets/mindspore/1.6/lpcnet_librispeech.md new file mode 100644 index 0000000..fb13f76 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/lpcnet_librispeech.md @@ -0,0 +1,62 @@ +# lpcnet + +--- + +model-name: lpcnet + +backbone-name: lpcnet + +module-type: audio + +fine-tunable: True + +model-version: 1.6 + +train-dataset: librispeech + +evaluation: MSE0.34 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 1b0912d8944ad2a817100caf798b415e628a1a7348bd554498fe7262cd8f6a29 + +license: Apache2.0 + +summary: lpcnet is used for audio + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of lpcnet from the MindSpore model zoo on Gitee at official/audio/lpcnet. + +lpcnet is a audio network. More details please refer to the MindSpore model zoo on Gitee at [official/audio/lpcnet](https://gitee.com/mindspore/models/blob/r1.6/official/audio/lpcnet/README.md). + +All parameters in the module are trainable. + +## Citation + +J.-M. Valin, J. Skoglund, A Real-Time Wideband Neural Vocoder at 1.6 kb/s Using LPCNet, Proc. INTERSPEECH, arxiv:1903.12087, 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/lstm_aclimdbv1.md b/mshub_res/assets/mindspore/1.6/lstm_aclimdbv1.md new file mode 100644 index 0000000..0a55e7e --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/lstm_aclimdbv1.md @@ -0,0 +1,62 @@ +# lstm + +--- + +model-name: lstm + +backbone-name: lstm + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: aclimdbv1 + +evaluation: acc86.18 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 7cc4125a91a2e792037cb17da99c2662c1b62ac9a4cc73f65fa6f43ba07e8ac6 + +license: Apache2.0 + +summary: lstm is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of lstm from the MindSpore model zoo on Gitee at official/nlp/lstm. + +lstm is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/lstm](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/lstm/README.md). + +All parameters in the module are trainable. + +## Citation + +Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, Christopher Potts. Learning Word Vectors for Sentiment Analysis. Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies. 2011 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/maskrcnn_coco2017.md b/mshub_res/assets/mindspore/1.6/maskrcnn_coco2017.md new file mode 100644 index 0000000..5c197f8 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/maskrcnn_coco2017.md @@ -0,0 +1,79 @@ +# maskrcnn + +--- + +model-name: maskrcnn + +backbone-name: maskrcnn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: acc32.9 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5fa5a1e12cf64538c26a984cd4e1cdd418a5629bfe15b265bb7b49536a6a8a99 + +license: Apache2.0 + +summary: maskrcnn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of maskrcnn from the MindSpore model zoo on Gitee at official/cv/maskrcnn. + +maskrcnn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/maskrcnn](https://gitee.com/mindspore/models/blob/r1.6/official/cv/maskrcnn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/maskrcnn_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Kaiming He, Georgia Gkioxari, Piotr Dollar and Ross Girshick. "MaskRCNN" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/mass_newscrawl_gigaword_cornell.md b/mshub_res/assets/mindspore/1.6/mass_newscrawl_gigaword_cornell.md new file mode 100644 index 0000000..74a7259 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/mass_newscrawl_gigaword_cornell.md @@ -0,0 +1,79 @@ +# mass + +--- + +model-name: mass + +backbone-name: mass + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: newscrawl_gigaword_cornell + +evaluation: RG1acc51.77 | RG2acc34.46 | RGL49.89 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 98414b2c2e27d7b8ee51754e5bf251fedb10f8700ed86ce25503df9b976b63ce + +license: Apache2.0 + +summary: mass is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of mass from the MindSpore model zoo on Gitee at official/nlp/mass. + +mass is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/mass](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/mass/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/mass_newscrawl_gigaword_cornell" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Song, Kaitao, Xu Tan, Tao Qin, Jianfeng Lu and Tie-Yan Liu.“MASS: Masked Sequence to Sequence Pre-training for Language Generation.”ICML (2019). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/melgan_ljspeech.md b/mshub_res/assets/mindspore/1.6/melgan_ljspeech.md new file mode 100644 index 0000000..89f18ab --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/melgan_ljspeech.md @@ -0,0 +1,62 @@ +# melgan + +--- + +model-name: melgan + +backbone-name: melgan + +module-type: audio + +fine-tunable: True + +model-version: 1.6 + +train-dataset: ljspeech + +evaluation: no + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: dd4642f0752adfebf5d3875a636487ec857859ed62e194b5f14a4f1209b41024 + +license: Apache2.0 + +summary: melgan is used for audio + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of melgan from the MindSpore model zoo on Gitee at official/audio/melgan. + +melgan is a audio network. More details please refer to the MindSpore model zoo on Gitee at [official/audio/melgan](https://gitee.com/mindspore/models/blob/r1.6/official/audio/melgan/README.md). + +All parameters in the module are trainable. + +## Citation + +Kundan Kumar, Rithesh Kumar, Thibault de Boissiere, Lucas Gestin, Wei Zhen Teoh, Jose Sotelo, Alexandre de Brebisson, Yoshua Bengio, Aaron Courville. "MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis.". + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/metabaseline_miniimagenet.md b/mshub_res/assets/mindspore/1.6/metabaseline_miniimagenet.md new file mode 100644 index 0000000..6ddd0e2 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/metabaseline_miniimagenet.md @@ -0,0 +1,62 @@ +# meta-baseline + +--- + +model-name: meta-baseline + +backbone-name: meta-baseline + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: miniimagenet + +evaluation: top1acc62 | top5acc78 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 4d210e142e104ce3bd65ebb170dc04cc93f5edb0fc0ba6f3c8eb75b3b1d730fa + +license: Apache2.0 + +summary: meta-baseline is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of meta-baseline from the MindSpore model zoo on Gitee at research/cv/meta-baseline. + +meta-baseline is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/meta-baseline](https://gitee.com/mindspore/models/blob/r1.6/research/cv/meta-baseline/README.md). + +All parameters in the module are trainable. + +## Citation + +Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/mmoe_censusincome.md b/mshub_res/assets/mindspore/1.6/mmoe_censusincome.md new file mode 100644 index 0000000..cfacaa8 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/mmoe_censusincome.md @@ -0,0 +1,62 @@ +# mmoe + +--- + +model-name: mmoe + +backbone-name: mmoe + +module-type: recommend + +fine-tunable: True + +model-version: 1.6 + +train-dataset: censusincome + +evaluation: incomeauc99.85 | maritalauc100 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 882ff75c70f07637e809b3c68461cb3a665cb8e7b3f2ad60623e8ab2a0460127 + +license: Apache2.0 + +summary: mmoe is used for recommend + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of mmoe from the MindSpore model zoo on Gitee at research/recommend/mmoe. + +mmoe is a recommend network. More details please refer to the MindSpore model zoo on Gitee at [research/recommend/mmoe](https://gitee.com/mindspore/models/blob/r1.6/research/recommend/mmoe/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +modeling-task-relationships-in-multi-task-learning-with-multi-gate-mixture- + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/mnasnet_imagenet2012.md b/mshub_res/assets/mindspore/1.6/mnasnet_imagenet2012.md new file mode 100644 index 0000000..3deab0e --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/mnasnet_imagenet2012.md @@ -0,0 +1,79 @@ +# mnasnet + +--- + +model-name: mnasnet + +backbone-name: mnasnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc73.98 | top5acc91.68 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d72b9a520a7687c0017289dc80cb480f84c01d8542fee1fa367ab914467f69c2 + +license: Apache2.0 + +summary: mnasnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of mnasnet from the MindSpore model zoo on Gitee at research/cv/mnasnet. + +mnasnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/mnasnet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/mnasnet/README_CN.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/mnasnet_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, Mark Sandler, Andrew Howard, Quoc V. Le. MnasNet: Platform-Aware Neural Architecture Search for Mobile 2018. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/mobilenetv1_cifar10.md b/mshub_res/assets/mindspore/1.6/mobilenetv1_cifar10.md new file mode 100644 index 0000000..010a7ae --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/mobilenetv1_cifar10.md @@ -0,0 +1,79 @@ +# mobilenetv1 + +--- + +model-name: mobilenetv1 + +backbone-name: mobilenetv1 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cifar10 + +evaluation: top1acc93.17 | top5acc99.81 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 88aa89d6183c7268981ca7b0f4f7e17b851a1e0c4870a852f81252ae3a4b5057 + +license: Apache2.0 + +summary: mobilenetv1 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of mobilenetv1 from the MindSpore model zoo on Gitee at official/cv/mobilenetv1. + +mobilenetv1 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/mobilenetv1](https://gitee.com/mindspore/models/blob/r1.6/official/cv/mobilenetv1/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/mobilenetv1_cifar10" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Howard A G , Zhu M , Chen B , et al. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications[J]. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/mobilenetv1_imagenet2012.md b/mshub_res/assets/mindspore/1.6/mobilenetv1_imagenet2012.md new file mode 100644 index 0000000..14e5005 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/mobilenetv1_imagenet2012.md @@ -0,0 +1,79 @@ +# mobilenetv1 + +--- + +model-name: mobilenetv1 + +backbone-name: mobilenetv1 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc71.96 | top5acc90.44 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: b0c379792495cce4c253e7e042f3ce80eddd353de61082bf35c1ac14012f5cde + +license: Apache2.0 + +summary: mobilenetv1 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of mobilenetv1 from the MindSpore model zoo on Gitee at official/cv/mobilenetv1. + +mobilenetv1 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/mobilenetv1](https://gitee.com/mindspore/models/blob/r1.6/official/cv/mobilenetv1/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/mobilenetv1_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Howard A G , Zhu M , Chen B , et al. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications[J]. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/mobilenetv2quant_imagenet2012.md b/mshub_res/assets/mindspore/1.6/mobilenetv2quant_imagenet2012.md new file mode 100644 index 0000000..17c75d9 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/mobilenetv2quant_imagenet2012.md @@ -0,0 +1,79 @@ +# mobilenetv2_quant + +--- + +model-name: mobilenetv2_quant + +backbone-name: mobilenetv2_quant + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc71 | top5acc90 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 159439c2a76851460f42d66087f12558c8a0a7ec781c2ec4978e8684ae29887f + +license: Apache2.0 + +summary: mobilenetv2_quant is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of mobilenetv2_quant from the MindSpore model zoo on Gitee at official/cv/mobilenetv2_quant. + +mobilenetv2_quant is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/mobilenetv2_quant](https://gitee.com/mindspore/models/blob/r1.6/official/cv/mobilenetv2_quant/Readme.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/mobilenetv2quant_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Howard, Andrew, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang et al. "Searching for MobileNetV2." In Proceedings of the IEEE International Conference on Computer Vision, pp. 1314-1324. 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/mobilenetv3large_imagenet2012.md b/mshub_res/assets/mindspore/1.6/mobilenetv3large_imagenet2012.md new file mode 100644 index 0000000..a3bfdd5 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/mobilenetv3large_imagenet2012.md @@ -0,0 +1,62 @@ +# mobilenetv3_large + +--- + +model-name: mobilenetv3_large + +backbone-name: mobilenetv3_large + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc74.55 | top5acc91.76 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 7f979e6256886df0070f9f4286ec0b32f21119b1430a127afddefeb10dd7bc31 + +license: Apache2.0 + +summary: mobilenetv3_large is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of mobilenetv3_large from the MindSpore model zoo on Gitee at research/cv/mobilenetv3_large. + +mobilenetv3_large is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/mobilenetv3_large](https://gitee.com/mindspore/models/blob/r1.6/research/cv/mobilenetv3_large/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Howard, Andrew, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang et al."Searching for mobilenetv3."In Proceedings of the IEEE International Conference on Computer Vision, pp. 1314-1324.2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/mobilenetv3smallx10_imagenet2012.md b/mshub_res/assets/mindspore/1.6/mobilenetv3smallx10_imagenet2012.md new file mode 100644 index 0000000..ce7c078 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/mobilenetv3smallx10_imagenet2012.md @@ -0,0 +1,62 @@ +# mobilenetV3_small_x1_0 + +--- + +model-name: mobilenetV3_small_x1_0 + +backbone-name: mobilenetV3_small_x1_0 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc67 | top5acc87 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 76d176503f5a18bf60b5ee0ad23f150b36306b616c5798aef4df4ff917538a5f + +license: Apache2.0 + +summary: mobilenetV3_small_x1_0 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of mobilenetV3_small_x1_0 from the MindSpore model zoo on Gitee at research/cv/mobilenetV3_small_x1_0. + +mobilenetV3_small_x1_0 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/mobilenetV3_small_x1_0](https://gitee.com/mindspore/models/blob/r1.6/research/cv/mobilenetV3_small_x1_0/README.md). + +All parameters in the module are trainable. + +## Citation + +Howard, Andrew, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang et al."Searching for mobilenetv3."In Proceedings of the IEEE International Conference on Computer Vision, pp. 1314-1324.2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/mvd_allresearch_sysumm01.md b/mshub_res/assets/mindspore/1.6/mvd_allresearch_sysumm01.md new file mode 100644 index 0000000..c13cbde --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/mvd_allresearch_sysumm01.md @@ -0,0 +1,62 @@ +# MVD + +--- + +model-name: MVD + +backbone-name: MVD + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: sysumm01 + +evaluation: rank1acc56 | mAP55 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 1e6563e40ab1d7338784ed79cf1884a4b3daf52e6f927dad00c1156748636833 + +license: Apache2.0 + +summary: MVD is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of MVD from the MindSpore model zoo on Gitee at research/cv/MVD. + +MVD is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/MVD](https://gitee.com/mindspore/models/blob/r1.6/research/cv/MVD/README.md). + +All parameters in the module are trainable. + +## Citation + +Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-identification in CVPR 2021 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/mvd_indoorsearch_sysumm01.md b/mshub_res/assets/mindspore/1.6/mvd_indoorsearch_sysumm01.md new file mode 100644 index 0000000..bff9163 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/mvd_indoorsearch_sysumm01.md @@ -0,0 +1,62 @@ +# MVD + +--- + +model-name: MVD + +backbone-name: MVD + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: sysumm01 + +evaluation: rank1acc69 | mAP73 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 1728eca554944480a38072759da6873c8eba036a54142830703e42e0fabdaa3b + +license: Apache2.0 + +summary: MVD is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of MVD from the MindSpore model zoo on Gitee at research/cv/MVD. + +MVD is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/MVD](https://gitee.com/mindspore/models/blob/r1.6/research/cv/MVD/README.md). + +All parameters in the module are trainable. + +## Citation + +Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-identification in CVPR 2021 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/mvd_infraredtovisible_regdb.md b/mshub_res/assets/mindspore/1.6/mvd_infraredtovisible_regdb.md new file mode 100644 index 0000000..330ebaa --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/mvd_infraredtovisible_regdb.md @@ -0,0 +1,62 @@ +# MVD + +--- + +model-name: MVD + +backbone-name: MVD + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: regdb + +evaluation: rank1acc71 | mAP66 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: ef5f2f59d4ff57357d3dcc9e1b1e115f3501c55492c0337b97f9a4d6cab87c33 + +license: Apache2.0 + +summary: MVD is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of MVD from the MindSpore model zoo on Gitee at research/cv/MVD. + +MVD is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/MVD](https://gitee.com/mindspore/models/blob/r1.6/research/cv/MVD/README.md). + +All parameters in the module are trainable. + +## Citation + +Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-identification in CVPR 2021 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/mvd_visibletoinfrared_regdb.md b/mshub_res/assets/mindspore/1.6/mvd_visibletoinfrared_regdb.md new file mode 100644 index 0000000..69210e4 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/mvd_visibletoinfrared_regdb.md @@ -0,0 +1,62 @@ +# MVD + +--- + +model-name: MVD + +backbone-name: MVD + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: regdb + +evaluation: rank1acc71 | mAP67 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 6540c831b95f05f516ba7a5f13ee4bc2e92a603a1ec0b37e7ba9b37771cd7423 + +license: Apache2.0 + +summary: MVD is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of MVD from the MindSpore model zoo on Gitee at research/cv/MVD. + +MVD is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/MVD](https://gitee.com/mindspore/models/blob/r1.6/research/cv/MVD/README.md). + +All parameters in the module are trainable. + +## Citation + +Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-identification in CVPR 2021 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/naml_mindlarge.md b/mshub_res/assets/mindspore/1.6/naml_mindlarge.md new file mode 100644 index 0000000..6672f93 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/naml_mindlarge.md @@ -0,0 +1,79 @@ +# naml + +--- + +model-name: naml + +backbone-name: naml + +module-type: recommend + +fine-tunable: True + +model-version: 1.6 + +train-dataset: mindlarge + +evaluation: acc67 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 9d553eae6ce96f019148b69ed4ce3ebb665503d7f1eda7c4907e23242479cdce + +license: Apache2.0 + +summary: naml is used for recommend + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of naml from the MindSpore model zoo on Gitee at official/recommend/naml. + +naml is a recommend network. More details please refer to the MindSpore model zoo on Gitee at [official/recommend/naml](https://gitee.com/mindspore/models/blob/r1.6/official/recommend/naml/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/naml_mindlarge" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Chuhan Wu, Fangzhao Wu, Mingxiao An, Jianqiang Huang, Yongfeng Huang and Xing Xie: Neural News Recommendation with Attentive Multi-View Learning, IJCAI 2019 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/nasnet_imagenet2012.md b/mshub_res/assets/mindspore/1.6/nasnet_imagenet2012.md new file mode 100644 index 0000000..01ac54a --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/nasnet_imagenet2012.md @@ -0,0 +1,62 @@ +# nasnet + +--- + +model-name: nasnet + +backbone-name: nasnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc74.05 | top5acc91.59 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 9f84e8d6305d05ce9bc72d62d424364b4888b217e6eb25acc0557595c9cc70c6 + +license: Apache2.0 + +summary: nasnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of nasnet from the MindSpore model zoo on Gitee at official/cv/nasnet. + +nasnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/nasnet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/nasnet/README.md). + +All parameters in the module are trainable. + +## Citation + +Barret Zoph, Vijay Vasudevan, Jonathon Shlens, Quoc V. Le. Learning Transferable Architectures for Scalable Image Recognition. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/ncf_movielens.md b/mshub_res/assets/mindspore/1.6/ncf_movielens.md new file mode 100644 index 0000000..097701a --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/ncf_movielens.md @@ -0,0 +1,79 @@ +# ncf + +--- + +model-name: ncf + +backbone-name: ncf + +module-type: recommend + +fine-tunable: True + +model-version: 1.6 + +train-dataset: movielens + +evaluation: hr70.25 | ndcg42.23 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: ff7bd040b8e269a8a81b1dcc2f96e157bc4c279c7ecc84fe9c9a9f166690e99d + +license: Apache2.0 + +summary: ncf is used for recommend + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ncf from the MindSpore model zoo on Gitee at official/recommend/ncf. + +ncf is a recommend network. More details please refer to the MindSpore model zoo on Gitee at [official/recommend/ncf](https://gitee.com/mindspore/models/blob/r1.6/official/recommend/ncf/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/ncf_movielens" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +He X, Liao L, Zhang H, et al. Neural collaborative filtering[C]//Proceedings of the 26th international conference on world wide web. 2017: 173-182. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/neighbor2neighbor_kodak.md b/mshub_res/assets/mindspore/1.6/neighbor2neighbor_kodak.md new file mode 100644 index 0000000..bf6c678 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/neighbor2neighbor_kodak.md @@ -0,0 +1,62 @@ +# Neighbor2Neighbor + +--- + +model-name: Neighbor2Neighbor + +backbone-name: Neighbor2Neighbor + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: kodak + +evaluation: PSNR32 | SSIM88.31 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 6cfd9d193826c3a0c4d95fd5633171d438e28d1b4607c388434142ab161ee1cb + +license: Apache2.0 + +summary: Neighbor2Neighbor is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of Neighbor2Neighbor from the MindSpore model zoo on Gitee at research/cv/Neighbor2Neighbor. + +Neighbor2Neighbor is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/Neighbor2Neighbor](https://gitee.com/mindspore/models/blob/r1.6/research/cv/Neighbor2Neighbor/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Huang T , Li S , Jia X , et al. Neighbor2Neighbor: Self-Supervised Denoising from Single Noisy Images[J]. 2021. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/nima_ava.md b/mshub_res/assets/mindspore/1.6/nima_ava.md new file mode 100644 index 0000000..33305b1 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/nima_ava.md @@ -0,0 +1,63 @@ +# nima + +--- + +model-name: nima + +backbone-name: nima + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: ava + +evaluation: srcc65.71 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 8bffc3b6182d3ae4e4c3e0375f939f857ae8a651a81ab06f136d467a4f0fc5eb + +license: Apache2.0 + +summary: nima is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of nima from the MindSpore model zoo on Gitee at official/cv/nima. + +nima is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/nima](https://gitee.com/mindspore/models/blob/r1.6/official/cv/nima/README.md). + +All parameters in the module are trainable. + +## Citation + +1. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun."Deep Residual Learning for Image Recognition" +2. H. Talebi and P. Milanfar, "NIMA: Neural Image Assessment" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/ntsnet_cub2002011.md b/mshub_res/assets/mindspore/1.6/ntsnet_cub2002011.md new file mode 100644 index 0000000..a0af80c --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/ntsnet_cub2002011.md @@ -0,0 +1,79 @@ +# ntsnet + +--- + +model-name: ntsnet + +backbone-name: ntsnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cub2002011 + +evaluation: acc87 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 4b29c87a6402cab44efcc499e46dcec2eddf2f35c84002434c4f66be8b0968cc + +license: Apache2.0 + +summary: ntsnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ntsnet from the MindSpore model zoo on Gitee at research/cv/ntsnet. + +ntsnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ntsnet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/ntsnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/ntsnet_cub2002011" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Z. Yang, T. Luo, D. Wang, Z. Hu, J. Gao, and L. Wang, Learning to navigate for fine-grained classification, in Proceedings of the European Conference on Computer Vision (ECCV), 2018. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/octsqueeze_kitti.md b/mshub_res/assets/mindspore/1.6/octsqueeze_kitti.md new file mode 100644 index 0000000..31fff03 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/octsqueeze_kitti.md @@ -0,0 +1,62 @@ +# octsqueeze + +--- + +model-name: octsqueeze + +backbone-name: octsqueeze + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: kitti + +evaluation: no + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 1c6aac507575e41940aa4da2c4ee23fd19864b0081310ecd804df371c475aace + +license: Apache2.0 + +summary: octsqueeze is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of octsqueeze from the MindSpore model zoo on Gitee at official/cv/octsqueeze. + +octsqueeze is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/octsqueeze](https://gitee.com/mindspore/models/blob/r1.6/official/cv/octsqueeze/README.md). + +All parameters in the module are trainable. + +## Citation + +Huang L, Wang S, Wong K, Liu J, Urtasun R. Octsqueeze: Octree-structured entropy model for lidar compression. InProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2020 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/openpose_coco2017.md b/mshub_res/assets/mindspore/1.6/openpose_coco2017.md new file mode 100644 index 0000000..647eb31 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/openpose_coco2017.md @@ -0,0 +1,79 @@ +# openpose + +--- + +model-name: openpose + +backbone-name: openpose + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: mAP40.29 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 60d785f9834508e9144286cb14c5e0ce28303d7dee58f5dcc7610be9db30c81f + +license: Apache2.0 + +summary: openpose is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of openpose from the MindSpore model zoo on Gitee at official/cv/openpose. + +openpose is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/openpose](https://gitee.com/mindspore/models/blob/r1.6/official/cv/openpose/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/openpose_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Zhe Cao,Tomas Simon,Shih-En Wei,Yaser Sheikh,"Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields",The IEEE Conference on Computer Vision and Pattern Recongnition(CVPR),2017 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/osnet_dukemtmc.md b/mshub_res/assets/mindspore/1.6/osnet_dukemtmc.md new file mode 100644 index 0000000..2753482 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/osnet_dukemtmc.md @@ -0,0 +1,62 @@ +# osnet + +--- + +model-name: osnet + +backbone-name: osnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: dukemtmc + +evaluation: mAP67 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 8bb1f05441d45cb6d4de816fdc6132f6096a35e1792156bf6b36b9f8d1f5abaa + +license: Apache2.0 + +summary: osnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of osnet from the MindSpore model zoo on Gitee at research/cv/osnet. + +osnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/osnet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/osnet/README.md). + +All parameters in the module are trainable. + +## Citation + +Kaiyang Zhou, Yongxin Yang, Andrea Cavallaro, Tao Xiang, University of Surrey, Queen Mary University of London Samsung AI Center, Cambridge, Published in IEEE 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/osnet_market1501.md b/mshub_res/assets/mindspore/1.6/osnet_market1501.md new file mode 100644 index 0000000..b1927ac --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/osnet_market1501.md @@ -0,0 +1,62 @@ +# osnet + +--- + +model-name: osnet + +backbone-name: osnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: market1501 + +evaluation: mAP80 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 6501a276300a2e2b063e51269fa50d82dc9c0adcf704495eb499041ab64e267c + +license: Apache2.0 + +summary: osnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of osnet from the MindSpore model zoo on Gitee at research/cv/osnet. + +osnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/osnet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/osnet/README.md). + +All parameters in the module are trainable. + +## Citation + +Kaiyang Zhou, Yongxin Yang, Andrea Cavallaro, Tao Xiang, University of Surrey, Queen Mary University of London Samsung AI Center, Cambridge, Published in IEEE 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/osnet_msmt17.md b/mshub_res/assets/mindspore/1.6/osnet_msmt17.md new file mode 100644 index 0000000..0dda8bd --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/osnet_msmt17.md @@ -0,0 +1,62 @@ +# osnet + +--- + +model-name: osnet + +backbone-name: osnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: msmt17 + +evaluation: mAP40 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: ec3524966167784d1194504758a5a3865500c2c35a439398ad06b09166028564 + +license: Apache2.0 + +summary: osnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of osnet from the MindSpore model zoo on Gitee at research/cv/osnet. + +osnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/osnet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/osnet/README.md). + +All parameters in the module are trainable. + +## Citation + +Kaiyang Zhou, Yongxin Yang, Andrea Cavallaro, Tao Xiang, University of Surrey, Queen Mary University of London Samsung AI Center, Cambridge, Published in IEEE 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/pgan_G_celeba.md b/mshub_res/assets/mindspore/1.6/pgan_G_celeba.md new file mode 100644 index 0000000..291ced5 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/pgan_G_celeba.md @@ -0,0 +1,62 @@ +# PGAN + +--- + +model-name: PGAN + +backbone-name: PGAN + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: celeba + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 2abeb89fdc788de05ea01d151f54b7b0fdd8c75dd079ff42b0fc9bb4f175e60e + +license: Apache2.0 + +summary: PGAN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of PGAN from the MindSpore model zoo on Gitee at research/cv/PGAN. + +PGAN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/PGAN](https://gitee.com/mindspore/models/blob/r1.6/research/cv/PGAN/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Progressive Growing of GANs for Improved Quality, Stability, and Variation//2018 ICLR + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/pix2pix_G_facades.md b/mshub_res/assets/mindspore/1.6/pix2pix_G_facades.md new file mode 100644 index 0000000..4bc9ecd --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/pix2pix_G_facades.md @@ -0,0 +1,62 @@ +# Pix2Pix + +--- + +model-name: Pix2Pix + +backbone-name: Pix2Pix + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: facades + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 185b0679425ec6ac60b1d393023ec7b3f0c760feaa49e7d2a23c157a96a25b8d + +license: Apache2.0 + +summary: Pix2Pix is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of Pix2Pix from the MindSpore model zoo on Gitee at research/cv/Pix2Pix. + +Pix2Pix is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/Pix2Pix](https://gitee.com/mindspore/models/blob/r1.6/research/cv/Pix2Pix/README.md). + +All parameters in the module are trainable. + +## Citation + +Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A. Efros. "Image-to-Image Translation with Conditional Adversarial Networks", in CVPR 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/pix2pix_G_maps.md b/mshub_res/assets/mindspore/1.6/pix2pix_G_maps.md new file mode 100644 index 0000000..2a76fa0 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/pix2pix_G_maps.md @@ -0,0 +1,62 @@ +# Pix2Pix + +--- + +model-name: Pix2Pix + +backbone-name: Pix2Pix + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: maps + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 39aa394d029b5c8b727c8c478fb14ffd48f11564a8b395e9b123ea28e2a8f324 + +license: Apache2.0 + +summary: Pix2Pix is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of Pix2Pix from the MindSpore model zoo on Gitee at research/cv/Pix2Pix. + +Pix2Pix is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/Pix2Pix](https://gitee.com/mindspore/models/blob/r1.6/research/cv/Pix2Pix/README.md). + +All parameters in the module are trainable. + +## Citation + +Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A. Efros. "Image-to-Image Translation with Conditional Adversarial Networks", in CVPR 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/pnasnet_imagenet2012.md b/mshub_res/assets/mindspore/1.6/pnasnet_imagenet2012.md new file mode 100644 index 0000000..a7481b3 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/pnasnet_imagenet2012.md @@ -0,0 +1,62 @@ +# pnasnet + +--- + +model-name: pnasnet + +backbone-name: pnasnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc74.51 | top5acc91.97 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 3181cd398f1333c34796f37f0e8084aaa2989ea2b2222344fea28e68029b4aa7 + +license: Apache2.0 + +summary: pnasnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of pnasnet from the MindSpore model zoo on Gitee at research/cv/pnasnet. + +pnasnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/pnasnet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/pnasnet/README.md). + +All parameters in the module are trainable. + +## Citation + +Chenxi Liu, etc. Progressive Neural Architecture Search. 2018. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/pointnet2_modelnet40.md b/mshub_res/assets/mindspore/1.6/pointnet2_modelnet40.md new file mode 100644 index 0000000..75a851e --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/pointnet2_modelnet40.md @@ -0,0 +1,62 @@ +# pointnet2 + +--- + +model-name: pointnet2 + +backbone-name: pointnet2 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: modelnet40 + +evaluation: acc91.83 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d0dfc830f9b5635e7ee0d433b29626ec765374b3f408bbe533282822e5ab8dbb + +license: Apache2.0 + +summary: pointnet2 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of pointnet2 from the MindSpore model zoo on Gitee at research/cv/pointnet2. + +pointnet2 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/pointnet2](https://gitee.com/mindspore/models/blob/r1.6/research/cv/pointnet2/README.md). + +All parameters in the module are trainable. + +## Citation + +Qi, Charles R., et al. "Pointnet++: Deep hierarchical feature learning on point sets in a metric space." arXiv preprint arXiv:1706.02413 (2017). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/posenet_kingscollege.md b/mshub_res/assets/mindspore/1.6/posenet_kingscollege.md new file mode 100644 index 0000000..7187089 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/posenet_kingscollege.md @@ -0,0 +1,62 @@ +# posenet + +--- + +model-name: posenet + +backbone-name: posenet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: kingscollege + +evaluation: 2.2m | 3.44d + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d882ceb3f8dc68db7064732e3a0da7b6c37766e054cf7ad60c049aef987331cc + +license: Apache2.0 + +summary: posenet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of posenet from the MindSpore model zoo on Gitee at official/cv/posenet. + +posenet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/posenet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/posenet/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Kendall A, Grimes M, Cipolla R. "PoseNet: A convolutional network for real-time 6-dof camera relocalization."*In IEEE International Conference on Computer Vision (pp. 2938–2946), 2015. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/posenet_stmaryschurch.md b/mshub_res/assets/mindspore/1.6/posenet_stmaryschurch.md new file mode 100644 index 0000000..7fa5f9a --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/posenet_stmaryschurch.md @@ -0,0 +1,62 @@ +# posenet + +--- + +model-name: posenet + +backbone-name: posenet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: stmaryschurch + +evaluation: 2.0m | 5.93d + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: ae1db1bd49928839b6c295fbe50115ca43860c02c46b0542103e66a944c44e33 + +license: Apache2.0 + +summary: posenet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of posenet from the MindSpore model zoo on Gitee at official/cv/posenet. + +posenet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/posenet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/posenet/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Kendall A, Grimes M, Cipolla R. "PoseNet: A convolutional network for real-time 6-dof camera relocalization."*In IEEE International Conference on Computer Vision (pp. 2938–2946), 2015. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/protonet_omniglot.md b/mshub_res/assets/mindspore/1.6/protonet_omniglot.md new file mode 100644 index 0000000..4476140 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/protonet_omniglot.md @@ -0,0 +1,62 @@ +# ProtoNet + +--- + +model-name: ProtoNet + +backbone-name: ProtoNet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: omniglot + +evaluation: acc99.63 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: f2494972445dbe2c26d5d66dbe94cca5d047a6870aa28f5c42900c5e4562376a + +license: Apache2.0 + +summary: ProtoNet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ProtoNet from the MindSpore model zoo on Gitee at research/cv/ProtoNet. + +ProtoNet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ProtoNet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/ProtoNet/README.md). + +All parameters in the module are trainable. + +## Citation + +Prototypical Networks for Few-shot Learning + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/proxylessnas_imagenet2012.md b/mshub_res/assets/mindspore/1.6/proxylessnas_imagenet2012.md new file mode 100644 index 0000000..f3efdfb --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/proxylessnas_imagenet2012.md @@ -0,0 +1,62 @@ +# proxylessnas + +--- + +model-name: proxylessnas + +backbone-name: proxylessnas + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc74.66 | top5acc92.08 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: ee73221e47911a3c80c4d24e861205a6591c8b37ba0aa5b78e34444d4ab058b9 + +license: Apache2.0 + +summary: proxylessnas is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of proxylessnas from the MindSpore model zoo on Gitee at research/cv/proxylessnas. + +proxylessnas is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/proxylessnas](https://gitee.com/mindspore/models/blob/r1.6/research/cv/proxylessnas/README.md). + +All parameters in the module are trainable. + +## Citation + +Han Cai, Ligeng Zhu, Song Han. ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware. 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/psenet_icdar2015.md b/mshub_res/assets/mindspore/1.6/psenet_icdar2015.md new file mode 100644 index 0000000..689ded4 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/psenet_icdar2015.md @@ -0,0 +1,79 @@ +# psenet + +--- + +model-name: psenet + +backbone-name: psenet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: icdar2015 + +evaluation: acc81 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 06b2b0a90ecb0be4202db2c28a4672ecdab78d8995829da53bafd61ac18b77cf + +license: Apache2.0 + +summary: psenet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of psenet from the MindSpore model zoo on Gitee at official/cv/psenet. + +psenet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/psenet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/psenet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/psenet_icdar2015" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wenhai Wang, Enze Xie, Xiang Li, Wenbo Hou, Tong Lu, Gang Yu, Shuai Shao; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, pp. 9336-9345 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/pwcnet_flyingchairs.md b/mshub_res/assets/mindspore/1.6/pwcnet_flyingchairs.md new file mode 100644 index 0000000..41aab78 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/pwcnet_flyingchairs.md @@ -0,0 +1,62 @@ +# pwcnet + +--- + +model-name: pwcnet + +backbone-name: pwcnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: flyingchairs + +evaluation: PEP6.9 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: eadbc65347c2a1e5af11226368a97dd1926e40ecb6ff105ffbe1ab960af78a7e + +license: Apache2.0 + +summary: pwcnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of pwcnet from the MindSpore model zoo on Gitee at official/cv/pwcnet. + +pwcnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/pwcnet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/pwcnet/README.md). + +All parameters in the module are trainable. + +## Citation + +Deqing Sun, Xiaodong Yang, Ming-Yu Liu, and Jan Kautz. "PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/r2plus1d_ucf101.md b/mshub_res/assets/mindspore/1.6/r2plus1d_ucf101.md new file mode 100644 index 0000000..959cc3c --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/r2plus1d_ucf101.md @@ -0,0 +1,62 @@ +# r2plus1d + +--- + +model-name: r2plus1d + +backbone-name: r2plus1d + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: ucf101 + +evaluation: acc96 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 04bc87e418054af98902bb2c6d2470107e1ab952208230951670a597782ffac8 + +license: Apache2.0 + +summary: r2plus1d is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of r2plus1d from the MindSpore model zoo on Gitee at research/cv/r2plus1d. + +r2plus1d is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/r2plus1d](https://gitee.com/mindspore/models/blob/r1.6/research/cv/r2plus1d/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Du T , Wang H , Torresani L , et al. A Closer Look at Spatiotemporal Convolutions for Action Recognition[C]// IEEE/CVF Conference on Computer Vision and Pattern Recognition. 0. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/ras_dutstrain.md b/mshub_res/assets/mindspore/1.6/ras_dutstrain.md new file mode 100644 index 0000000..5c5afa5 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/ras_dutstrain.md @@ -0,0 +1,62 @@ +# ras + +--- + +model-name: ras + +backbone-name: ras + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: dutstrain + +evaluation: ECSSD91 | DUTStest81 | DUTOMRON75 | HKUIS90 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 01874ed4b95de1e7e08c304bbb8e1ef7158b6b9919f0217c8efdfe9b6c9eca5f + +license: Apache2.0 + +summary: ras is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ras from the MindSpore model zoo on Gitee at research/cv/ras. + +ras is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ras](https://gitee.com/mindspore/models/blob/r1.6/research/cv/ras/README.md). + +All parameters in the module are trainable. + +## Citation + +Reverse Attention-Based Residual Network for Salient Object Detection + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/refinedet_coco2017.md b/mshub_res/assets/mindspore/1.6/refinedet_coco2017.md new file mode 100644 index 0000000..5f233a3 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/refinedet_coco2017.md @@ -0,0 +1,62 @@ +# RefineDet + +--- + +model-name: RefineDet + +backbone-name: RefineDet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: acc28.69 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5df4c0602071678957f0039520cde9ebb995f7c2bbadddc817694a02582c4531 + +license: Apache2.0 + +summary: RefineDet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of RefineDet from the MindSpore model zoo on Gitee at research/cv/RefineDet. + +RefineDet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/RefineDet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/RefineDet/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +S. Zhang, L. Wen, X. Bian, Z. Lei and S. Z. Li, "Single-shot refinement neural network for object detection", Proc. IEEE/CVF Conf. Comput. Vis. Pattern Recognit., pp. 4203-4212, Jun. 2018. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/refinenet_voc2012.md b/mshub_res/assets/mindspore/1.6/refinenet_voc2012.md new file mode 100644 index 0000000..4fef81b --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/refinenet_voc2012.md @@ -0,0 +1,62 @@ +# RefineNet + +--- + +model-name: RefineNet + +backbone-name: RefineNet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: voc2012 + +evaluation: acc80 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 9dc1819104c292fa88ad4868737fcd8c7fb7d4f7e368dc10610e71941a1571fa + +license: Apache2.0 + +summary: RefineNet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of RefineNet from the MindSpore model zoo on Gitee at research/cv/RefineNet. + +RefineNet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/RefineNet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/RefineNet/README.md). + +All parameters in the module are trainable. + +## Citation + +guosheng.lin，anton.milan，et.al.RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation.arXiv:1611.06612v3 [cs.CV] 25 Nov 2016 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/res2net101_imagenet2012.md b/mshub_res/assets/mindspore/1.6/res2net101_imagenet2012.md new file mode 100644 index 0000000..e0d92df --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/res2net101_imagenet2012.md @@ -0,0 +1,79 @@ +# res2net + +--- + +model-name: res2net + +backbone-name: res2net + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc79 | top5acc94 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c4b5aa190d5163b44fb9aef5093adb3fd0bd6af49fbff0853a43faef8487b337 + +license: Apache2.0 + +summary: res2net is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of res2net from the MindSpore model zoo on Gitee at research/cv/res2net. + +res2net is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/res2net](https://gitee.com/mindspore/models/blob/r1.6/research/cv/res2net/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/res2net101_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Gao, Shang-Hua and Cheng, Ming-Ming and Zhao, Kai and Zhang, Xin-Yu and Yang, Ming-Hsuan and Torr, Philip. "Res2Net: A New Multi-scale Backbone Architecture"，TPAMI21 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/res2net152_imagenet2012.md b/mshub_res/assets/mindspore/1.6/res2net152_imagenet2012.md new file mode 100644 index 0000000..c1d2233 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/res2net152_imagenet2012.md @@ -0,0 +1,79 @@ +# res2net + +--- + +model-name: res2net + +backbone-name: res2net + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc79 | top5acc94 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: fb9ed083bb807e0d85c408e034904c9b8e169f6dc45daa84c42f7ee57723fc4e + +license: Apache2.0 + +summary: res2net is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of res2net from the MindSpore model zoo on Gitee at research/cv/res2net. + +res2net is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/res2net](https://gitee.com/mindspore/models/blob/r1.6/research/cv/res2net/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/res2net152_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Gao, Shang-Hua and Cheng, Ming-Ming and Zhao, Kai and Zhang, Xin-Yu and Yang, Ming-Hsuan and Torr, Philip. "Res2Net: A New Multi-scale Backbone Architecture"，TPAMI21 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/res2net50_imagenet2012.md b/mshub_res/assets/mindspore/1.6/res2net50_imagenet2012.md new file mode 100644 index 0000000..7fe689c --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/res2net50_imagenet2012.md @@ -0,0 +1,79 @@ +# res2net + +--- + +model-name: res2net + +backbone-name: res2net + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc78 | top5acc94 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 38aef446135e0e4afd02b64f4dd2ff208830c735c4332402a7c4ce741bb7fb0d + +license: Apache2.0 + +summary: res2net is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of res2net from the MindSpore model zoo on Gitee at research/cv/res2net. + +res2net is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/res2net](https://gitee.com/mindspore/models/blob/r1.6/research/cv/res2net/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/res2net50_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Gao, Shang-Hua and Cheng, Ming-Ming and Zhao, Kai and Zhang, Xin-Yu and Yang, Ming-Hsuan and Torr, Philip. "Res2Net: A New Multi-scale Backbone Architecture"，TPAMI21 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/res2netdeeplabv3_s8r2_voc2012.md b/mshub_res/assets/mindspore/1.6/res2netdeeplabv3_s8r2_voc2012.md new file mode 100644 index 0000000..867621c --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/res2netdeeplabv3_s8r2_voc2012.md @@ -0,0 +1,79 @@ +# res2net_deeplabv3 + +--- + +model-name: res2net_deeplabv3 + +backbone-name: res2net_deeplabv3 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: voc2012 + +evaluation: mIoU80 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: edea43f8f63ae5f6dc493ecd818e43b7ba455ab30bbdb9cddff5b15fc67b7438 + +license: Apache2.0 + +summary: res2net_deeplabv3 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of res2net_deeplabv3 from the MindSpore model zoo on Gitee at research/cv/res2net_deeplabv3. + +res2net_deeplabv3 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/res2net_deeplabv3](https://gitee.com/mindspore/models/blob/r1.6/research/cv/res2net_deeplabv3/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/res2netdeeplabv3_s8r2_voc2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Chen L C, Papandreou G, Schroff F, et al. Rethinking atrous convolution for semantic image segmentation[J]. arXiv preprint arXiv:1706.05587, 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/res2netdeeplabv3_s8r2multiscale_voc2012.md b/mshub_res/assets/mindspore/1.6/res2netdeeplabv3_s8r2multiscale_voc2012.md new file mode 100644 index 0000000..7fe898b --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/res2netdeeplabv3_s8r2multiscale_voc2012.md @@ -0,0 +1,79 @@ +# res2net_deeplabv3 + +--- + +model-name: res2net_deeplabv3 + +backbone-name: res2net_deeplabv3 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: voc2012 + +evaluation: mIoU80.34 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: edea43f8f63ae5f6dc493ecd818e43b7ba455ab30bbdb9cddff5b15fc67b7438 + +license: Apache2.0 + +summary: res2net_deeplabv3 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of res2net_deeplabv3 from the MindSpore model zoo on Gitee at research/cv/res2net_deeplabv3. + +res2net_deeplabv3 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/res2net_deeplabv3](https://gitee.com/mindspore/models/blob/r1.6/research/cv/res2net_deeplabv3/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/res2netdeeplabv3_s8r2multiscale_voc2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Chen L C, Papandreou G, Schroff F, et al. Rethinking atrous convolution for semantic image segmentation[J]. arXiv preprint arXiv:1706.05587, 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/res2netdeeplabv3_s8r2multiscalefilp_voc2012.md b/mshub_res/assets/mindspore/1.6/res2netdeeplabv3_s8r2multiscalefilp_voc2012.md new file mode 100644 index 0000000..f971e84 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/res2netdeeplabv3_s8r2multiscalefilp_voc2012.md @@ -0,0 +1,79 @@ +# res2net_deeplabv3 + +--- + +model-name: res2net_deeplabv3 + +backbone-name: res2net_deeplabv3 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: voc2012 + +evaluation: mIoU81 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: edea43f8f63ae5f6dc493ecd818e43b7ba455ab30bbdb9cddff5b15fc67b7438 + +license: Apache2.0 + +summary: res2net_deeplabv3 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of res2net_deeplabv3 from the MindSpore model zoo on Gitee at research/cv/res2net_deeplabv3. + +res2net_deeplabv3 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/res2net_deeplabv3](https://gitee.com/mindspore/models/blob/r1.6/research/cv/res2net_deeplabv3/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/res2netdeeplabv3_s8r2multiscalefilp_voc2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Chen L C, Papandreou G, Schroff F, et al. Rethinking atrous convolution for semantic image segmentation[J]. arXiv preprint arXiv:1706.05587, 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/res2netfasterrcnn_coco2017.md b/mshub_res/assets/mindspore/1.6/res2netfasterrcnn_coco2017.md new file mode 100644 index 0000000..96d0688 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/res2netfasterrcnn_coco2017.md @@ -0,0 +1,79 @@ +# res2net_faster_rcnn + +--- + +model-name: res2net_faster_rcnn + +backbone-name: res2net_faster_rcnn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: mAP40 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5ab8487dcba4cafd0389f008415735be3d49155592eacd153b1c25e17d46df62 + +license: Apache2.0 + +summary: res2net_faster_rcnn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of res2net_faster_rcnn from the MindSpore model zoo on Gitee at research/cv/res2net_faster_rcnn. + +res2net_faster_rcnn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/res2net_faster_rcnn](https://gitee.com/mindspore/models/blob/r1.6/research/cv/res2net_faster_rcnn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/res2netfasterrcnn_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Ren S , He K , Girshick R , et al. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 39(6). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/res2netyolov3_coco2017.md b/mshub_res/assets/mindspore/1.6/res2netyolov3_coco2017.md new file mode 100644 index 0000000..e4d3264 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/res2netyolov3_coco2017.md @@ -0,0 +1,79 @@ +# res2net_yolov3 + +--- + +model-name: res2net_yolov3 + +backbone-name: res2net_yolov3 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: mAP32 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 8d29fa83f0f50260d77fbe93f0f1149cd7d46d8574e20df290078b5a50ea1a7d + +license: Apache2.0 + +summary: res2net_yolov3 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of res2net_yolov3 from the MindSpore model zoo on Gitee at research/cv/res2net_yolov3. + +res2net_yolov3 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/res2net_yolov3](https://gitee.com/mindspore/models/blob/r1.6/research/cv/res2net_yolov3/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/res2netyolov3_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +YOLOv3: An Incremental Improvement. Joseph Redmon, Ali Farhadi, University of Washington + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/resnest50_imagenet2012.md b/mshub_res/assets/mindspore/1.6/resnest50_imagenet2012.md new file mode 100644 index 0000000..eab7e4d --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/resnest50_imagenet2012.md @@ -0,0 +1,62 @@ +# ResNeSt50 + +--- + +model-name: ResNeSt50 + +backbone-name: ResNeSt50 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc79.52 | top5acc94.45 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 2aaf98def70641e88a0d05214eafaa493fcb4f167aed12d3c103bea4808c881a + +license: Apache2.0 + +summary: ResNeSt50 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ResNeSt50 from the MindSpore model zoo on Gitee at research/cv/ResNeSt50. + +ResNeSt50 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ResNeSt50](https://gitee.com/mindspore/models/blob/r1.6/research/cv/ResNeSt50/README.md). + +All parameters in the module are trainable. + +## Citation + +Hang Zhang, Chongruo Wu, Alexander Smola et al. ResNeSt: Split-Attention Networks. 2020. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/resnet101_imagenet2012.md b/mshub_res/assets/mindspore/1.6/resnet101_imagenet2012.md new file mode 100644 index 0000000..e66a408 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/resnet101_imagenet2012.md @@ -0,0 +1,81 @@ +# resnet + +--- + +model-name: resnet + +backbone-name: resnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc78.55 | top5acc94.34 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d0ad1bb5fbd692b8fbfb7b6304560197bd4003e5c88f77ab1cee4141f302b936 + +license: Apache2.0 + +summary: resnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnet from the MindSpore model zoo on Gitee at official/cv/resnet. + +resnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/resnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/resnet101_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun."Deep Residual Learning for Image Recognition" +2. Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu."Squeeze-and-Excitation Networks" +3. Tong He, Zhi Zhang, Hang Zhang, Zhongyue Zhang, Junyuan Xie, Mu Li."Bag of Tricks for Image Classification with Convolutional Neural Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/resnet152_imagenet2012.md b/mshub_res/assets/mindspore/1.6/resnet152_imagenet2012.md new file mode 100644 index 0000000..253c345 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/resnet152_imagenet2012.md @@ -0,0 +1,81 @@ +# resnet + +--- + +model-name: resnet + +backbone-name: resnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc78.72 | top5acc94.32 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 76d176503f5a18bf60b5ee0ad23f150b36306b616c5798aef4df4ff917538a5f + +license: Apache2.0 + +summary: resnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnet from the MindSpore model zoo on Gitee at official/cv/resnet. + +resnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/resnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/resnet152_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun."Deep Residual Learning for Image Recognition" +2. Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu."Squeeze-and-Excitation Networks" +3. Tong He, Zhi Zhang, Hang Zhang, Zhongyue Zhang, Junyuan Xie, Mu Li."Bag of Tricks for Image Classification with Convolutional Neural Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/resnet18_cifar10.md b/mshub_res/assets/mindspore/1.6/resnet18_cifar10.md new file mode 100644 index 0000000..df0fbd9 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/resnet18_cifar10.md @@ -0,0 +1,81 @@ +# resnet + +--- + +model-name: resnet + +backbone-name: resnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cifar10 + +evaluation: acc94.02 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: e668e52ba28d5a90d8eb4166457f506c49b08d6fbc331823766a7ea3ea92fdcc + +license: Apache2.0 + +summary: resnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnet from the MindSpore model zoo on Gitee at official/cv/resnet. + +resnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/resnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/resnet18_cifar10" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun."Deep Residual Learning for Image Recognition" +2. Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu."Squeeze-and-Excitation Networks" +3. Tong He, Zhi Zhang, Hang Zhang, Zhongyue Zhang, Junyuan Xie, Mu Li."Bag of Tricks for Image Classification with Convolutional Neural Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/resnet18_imagenet2012.md b/mshub_res/assets/mindspore/1.6/resnet18_imagenet2012.md new file mode 100644 index 0000000..e8c0228 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/resnet18_imagenet2012.md @@ -0,0 +1,81 @@ +# resnet + +--- + +model-name: resnet + +backbone-name: resnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc70.47 | top5acc89.61 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 22a181090f89f52442a43fc0a59b0d6029257c129f2722d11a25c9023ba95942 + +license: Apache2.0 + +summary: resnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnet from the MindSpore model zoo on Gitee at official/cv/resnet. + +resnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/resnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/resnet18_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun."Deep Residual Learning for Image Recognition" +2. Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu."Squeeze-and-Excitation Networks" +3. Tong He, Zhi Zhang, Hang Zhang, Zhongyue Zhang, Junyuan Xie, Mu Li."Bag of Tricks for Image Classification with Convolutional Neural Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/resnet34_imagenet2012.md b/mshub_res/assets/mindspore/1.6/resnet34_imagenet2012.md new file mode 100644 index 0000000..3005513 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/resnet34_imagenet2012.md @@ -0,0 +1,81 @@ +# resnet + +--- + +model-name: resnet + +backbone-name: resnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc73.83 | top5acc91.61 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: b8303354c68c55560d1f1bb04dce4dfd62dd1f02a417c05bfa6b0a920396522c + +license: Apache2.0 + +summary: resnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnet from the MindSpore model zoo on Gitee at official/cv/resnet. + +resnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/resnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/resnet34_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun."Deep Residual Learning for Image Recognition" +2. Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu."Squeeze-and-Excitation Networks" +3. Tong He, Zhi Zhang, Hang Zhang, Zhongyue Zhang, Junyuan Xie, Mu Li."Bag of Tricks for Image Classification with Convolutional Neural Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/resnet50_imagenet2012.md b/mshub_res/assets/mindspore/1.6/resnet50_imagenet2012.md new file mode 100644 index 0000000..95382b5 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/resnet50_imagenet2012.md @@ -0,0 +1,81 @@ +# resnet + +--- + +model-name: resnet + +backbone-name: resnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc76.97 | top5acc93.44 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 41c1479844f6f848d4caf902cf940ebe4727df559495ed45885892fc55a2738f + +license: Apache2.0 + +summary: resnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnet from the MindSpore model zoo on Gitee at official/cv/resnet. + +resnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/resnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/resnet50_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun."Deep Residual Learning for Image Recognition" +2. Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu."Squeeze-and-Excitation Networks" +3. Tong He, Zhi Zhang, Hang Zhang, Zhongyue Zhang, Junyuan Xie, Mu Li."Bag of Tricks for Image Classification with Convolutional Neural Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/resnet50_quadruplet_sop.md b/mshub_res/assets/mindspore/1.6/resnet50_quadruplet_sop.md new file mode 100644 index 0000000..b3e20be --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/resnet50_quadruplet_sop.md @@ -0,0 +1,63 @@ +# metric_learn + +--- + +model-name: metric_learn + +backbone-name: metric_learn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: sop + +evaluation: acc74 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 9897589daa93d4fbb80959f59b4c5319ff12ed495e7bfcd4cf3c895e6d1c3c21 + +license: Apache2.0 + +summary: metric_learn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of metric_learn from the MindSpore model zoo on Gitee at research/cv/metric_learn. + +metric_learn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/metric_learn](https://gitee.com/mindspore/models/blob/r1.6/research/cv/metric_learn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +1. CVPR2015 F Schroff, Kalenichenko D,Philbin J."FaceNet: A Unified Embedding for Face Recognition and Clustering" +2. CVPR2017 Chen W, Chen X, Zhang J."Beyond triplet loss: A deep quadruplet network for person re-identification" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/resnet50_triplet_sop.md b/mshub_res/assets/mindspore/1.6/resnet50_triplet_sop.md new file mode 100644 index 0000000..296041f --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/resnet50_triplet_sop.md @@ -0,0 +1,63 @@ +# metric_learn + +--- + +model-name: metric_learn + +backbone-name: metric_learn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: sop + +evaluation: acc73 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 7f5122938bfc0e9f372eda4901259009f6b71520fb1d75feb42f10efefc7550f + +license: Apache2.0 + +summary: metric_learn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of metric_learn from the MindSpore model zoo on Gitee at research/cv/metric_learn. + +metric_learn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/metric_learn](https://gitee.com/mindspore/models/blob/r1.6/research/cv/metric_learn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +1. CVPR2015 F Schroff, Kalenichenko D,Philbin J."FaceNet: A Unified Embedding for Face Recognition and Clustering" +2. CVPR2017 Chen W, Chen X, Zhang J."Beyond triplet loss: A deep quadruplet network for person re-identification" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/resnet50quant_imagenet2012.md b/mshub_res/assets/mindspore/1.6/resnet50quant_imagenet2012.md new file mode 100644 index 0000000..c5cddb5 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/resnet50quant_imagenet2012.md @@ -0,0 +1,79 @@ +# resnet50_quant + +--- + +model-name: resnet50_quant + +backbone-name: resnet50_quant + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc76 | top5acc92 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 621460f6d626d2c4643d8afd45bc62588580ed0faabc31a678ec00b8aacf9b5b + +license: Apache2.0 + +summary: resnet50_quant is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnet50_quant from the MindSpore model zoo on Gitee at official/cv/resnet50_quant. + +resnet50_quant is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnet50_quant](https://gitee.com/mindspore/models/blob/r1.6/official/cv/resnet50_quant/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/resnet50quant_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun."Deep Residual Learning for Image Recognition." He, Kaiming , et al. "Deep Residual Learning for Image Recognition." IEEE Conference on Computer Vision & Pattern Recognition IEEE Computer Society, 2016. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/resnet50thor_imagenet2012.md b/mshub_res/assets/mindspore/1.6/resnet50thor_imagenet2012.md new file mode 100644 index 0000000..355136a --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/resnet50thor_imagenet2012.md @@ -0,0 +1,75 @@ +# resnet_thor + +--- + +model-name: resnet_thor + +backbone-name: resnet_thor + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc76.08 | top5acc92.81 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: ad9b3b0bef58cbc204493b84dd0da3972acdceb4d273233a99f890adbc905ffc + +license: Apache2.0 + +summary: resnet_thor is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnet_thor from the MindSpore model zoo on Gitee at official/cv/resnet_thor. + +resnet_thor is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnet_thor](https://gitee.com/mindspore/models/blob/r1.6/official/cv/resnet_thor/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/resnet50thor_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/resnetv2101_cifar10.md b/mshub_res/assets/mindspore/1.6/resnetv2101_cifar10.md new file mode 100644 index 0000000..377e00e --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/resnetv2101_cifar10.md @@ -0,0 +1,62 @@ +# resnetv2 + +--- + +model-name: resnetv2 + +backbone-name: resnetv2 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cifar10 + +evaluation: acc95.15 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 183f9e5feaef51c792c45f55ccafb2dd0467ae8809aee7537827d674c26633f5 + +license: Apache2.0 + +summary: resnetv2 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnetv2 from the MindSpore model zoo on Gitee at research/cv/resnetv2. + +resnetv2 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/resnetv2](https://gitee.com/mindspore/models/blob/r1.6/research/cv/resnetv2/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. "Identity Mappings in Deep Residual Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/resnetv2152_cifar10.md b/mshub_res/assets/mindspore/1.6/resnetv2152_cifar10.md new file mode 100644 index 0000000..2ec9e7c --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/resnetv2152_cifar10.md @@ -0,0 +1,62 @@ +# resnetv2 + +--- + +model-name: resnetv2 + +backbone-name: resnetv2 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cifar10 + +evaluation: acc95.61 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 63c4f1fc267ede99ce4006bfba643d1732f0a8f55400ec8d6f9f3af72f559647 + +license: Apache2.0 + +summary: resnetv2 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnetv2 from the MindSpore model zoo on Gitee at research/cv/resnetv2. + +resnetv2 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/resnetv2](https://gitee.com/mindspore/models/blob/r1.6/research/cv/resnetv2/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. "Identity Mappings in Deep Residual Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/resnetv250_cifar10.md b/mshub_res/assets/mindspore/1.6/resnetv250_cifar10.md new file mode 100644 index 0000000..ad59bca --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/resnetv250_cifar10.md @@ -0,0 +1,62 @@ +# resnetv2 + +--- + +model-name: resnetv2 + +backbone-name: resnetv2 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cifar10 + +evaluation: acc95.2 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d88993343168c69ee523052b7cd605fd0c7cb426dff6f033d7e2be068d05a9a3 + +license: Apache2.0 + +summary: resnetv2 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnetv2 from the MindSpore model zoo on Gitee at research/cv/resnetv2. + +resnetv2 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/resnetv2](https://gitee.com/mindspore/models/blob/r1.6/research/cv/resnetv2/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. "Identity Mappings in Deep Residual Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/resnetv250frn_imagenet2012.md b/mshub_res/assets/mindspore/1.6/resnetv250frn_imagenet2012.md new file mode 100644 index 0000000..bfc441a --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/resnetv250frn_imagenet2012.md @@ -0,0 +1,62 @@ +# resnetv2_50_frn + +--- + +model-name: resnetv2_50_frn + +backbone-name: resnetv2_50_frn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc77.22 | top5acc93.27 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 745667f00db73227b73815bc3e35afba8d384eed5606c004fe3c15f5907f296d + +license: Apache2.0 + +summary: resnetv2_50_frn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnetv2_50_frn from the MindSpore model zoo on Gitee at research/cv/resnetv2_50_frn. + +resnetv2_50_frn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/resnetv2_50_frn](https://gitee.com/mindspore/models/blob/r1.6/research/cv/resnetv2_50_frn/README.md). + +All parameters in the module are trainable. + +## Citation + +Saurabh Singh, Shankar Krishnan. Filter Response Normalization Layer: Eliminating Batch Dependence in the Training of Deep Neural Networks. 2020. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/resnext101_imagenet2012.md b/mshub_res/assets/mindspore/1.6/resnext101_imagenet2012.md new file mode 100644 index 0000000..9b4793c --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/resnext101_imagenet2012.md @@ -0,0 +1,79 @@ +# resnext + +--- + +model-name: resnext + +backbone-name: resnext + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc79.39 | top5acc94.62 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 83a09de8e7399c48d76fad179577da52bab3d0e667ec3d4501e5cdf1cbfc26d7 + +license: Apache2.0 + +summary: resnext is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnext from the MindSpore model zoo on Gitee at official/cv/resnext. + +resnext is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnext](https://gitee.com/mindspore/models/blob/r1.6/official/cv/resnext/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/resnext101_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Xie S, Girshick R, Dollár, Piotr, et al. Aggregated Residual Transformations for Deep Neural Networks. 2016. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/resnext15264x4d_imagenet2012.md b/mshub_res/assets/mindspore/1.6/resnext15264x4d_imagenet2012.md new file mode 100644 index 0000000..d85d343 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/resnext15264x4d_imagenet2012.md @@ -0,0 +1,62 @@ +# resnext152_64x4d + +--- + +model-name: resnext152_64x4d + +backbone-name: resnext152_64x4d + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc79.94 | top5acc94.66 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 8045c5d89d7d2fbc0019bd4f519aba5e57e4d0d2a8fb55906718374b9a0792f0 + +license: Apache2.0 + +summary: resnext152_64x4d is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnext152_64x4d from the MindSpore model zoo on Gitee at research/cv/resnext152_64x4d. + +resnext152_64x4d is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/resnext152_64x4d](https://gitee.com/mindspore/models/blob/r1.6/research/cv/resnext152_64x4d/README.md). + +All parameters in the module are trainable. + +## Citation + +Xie S, Girshick R, Dollár, Piotr, et al. Aggregated Residual Transformations for Deep Neural Networks. 2016. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/resnext50_imagenet2012.md b/mshub_res/assets/mindspore/1.6/resnext50_imagenet2012.md new file mode 100644 index 0000000..8743223 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/resnext50_imagenet2012.md @@ -0,0 +1,79 @@ +# resnext + +--- + +model-name: resnext + +backbone-name: resnext + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc78.51 | top5acc94.18 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 22857131a4cc5186af07582907888c7cf0d8361aeb78545ca20bace4e8f3961e + +license: Apache2.0 + +summary: resnext is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnext from the MindSpore model zoo on Gitee at official/cv/resnext. + +resnext is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnext](https://gitee.com/mindspore/models/blob/r1.6/official/cv/resnext/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/resnext50_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Xie S, Girshick R, Dollár, Piotr, et al. Aggregated Residual Transformations for Deep Neural Networks. 2016. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/retinaface_resnet50_widerface.md b/mshub_res/assets/mindspore/1.6/retinaface_resnet50_widerface.md new file mode 100644 index 0000000..ec001f7 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/retinaface_resnet50_widerface.md @@ -0,0 +1,62 @@ +# retinaface_resnet50 + +--- + +model-name: retinaface_resnet50 + +backbone-name: retinaface_resnet50 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: widerface + +evaluation: easy94.97 | medium93.89 | hard82.27 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d7a67c8289bec78788b5ab625f006b8d74992c77c25310ec5a9dd0e16722e2aa + +license: Apache2.0 + +summary: retinaface_resnet50 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of retinaface_resnet50 from the MindSpore model zoo on Gitee at official/cv/retinaface_resnet50. + +retinaface_resnet50 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/retinaface_resnet50](https://gitee.com/mindspore/models/blob/r1.6/official/cv/retinaface_resnet50/README.md). + +All parameters in the module are trainable. + +## Citation + +Jiankang Deng, Jia Guo, Yuxiang Zhou, Jinke Yu, Irene Kotsia, Stefanos Zafeiriou. "RetinaFace: Single-stage Dense Face Localisation in the Wild". 2019. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/retinanet_coco2017.md b/mshub_res/assets/mindspore/1.6/retinanet_coco2017.md new file mode 100644 index 0000000..b966815 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/retinanet_coco2017.md @@ -0,0 +1,79 @@ +# retinanet + +--- + +model-name: retinanet + +backbone-name: retinanet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: acc35 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 2fda03174122089d884f7fde4115d51145a25d44cca6f9c02f0653a83d17cab6 + +license: Apache2.0 + +summary: retinanet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of retinanet from the MindSpore model zoo on Gitee at official/cv/retinanet. + +retinanet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/retinanet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/retinanet/README_CN.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/retinanet_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Lin T Y , Goyal P , Girshick R , et al. Focal Loss for Dense Object Detection[C]// 2017 IEEE International Conference on Computer Vision (ICCV). IEEE, 2017:2999-3007. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/retinanetresnet101_coco2017.md b/mshub_res/assets/mindspore/1.6/retinanetresnet101_coco2017.md new file mode 100644 index 0000000..f6fde37 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/retinanetresnet101_coco2017.md @@ -0,0 +1,62 @@ +# retinanet_resnet101 + +--- + +model-name: retinanet_resnet101 + +backbone-name: retinanet_resnet101 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: acc36.39 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c58400d46600ce74f4cb1f28f513ead9defb7ad4fe100a7dada92d5a77d313c7 + +license: Apache2.0 + +summary: retinanet_resnet101 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of retinanet_resnet101 from the MindSpore model zoo on Gitee at research/cv/retinanet_resnet101. + +retinanet_resnet101 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/retinanet_resnet101](https://gitee.com/mindspore/models/blob/r1.6/research/cv/retinanet_resnet101/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Lin T Y , Goyal P , Girshick R , et al. Focal Loss for Dense Object Detection[C]// 2017 IEEE International Conference on Computer Vision (ICCV). IEEE, 2017:2999-3007. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/rotate_wn18rr.md b/mshub_res/assets/mindspore/1.6/rotate_wn18rr.md new file mode 100644 index 0000000..53757be --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/rotate_wn18rr.md @@ -0,0 +1,62 @@ +# rotate + +--- + +model-name: rotate + +backbone-name: rotate + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: wn18rr + +evaluation: MRR47 | MR3340 | HITS@1acc42 | HITS@3acc49 | HITS@10acc57 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d78bb8cb987c632060262a5de793fbb6c27dbc17241bd343e2d0a15fa3b76609 + +license: Apache2.0 + +summary: rotate is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of rotate from the MindSpore model zoo on Gitee at research/nlp/rotate. + +rotate is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [research/nlp/rotate](https://gitee.com/mindspore/models/blob/r1.6/research/nlp/rotate/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Zhiqing Sun, Zhi-Hong Deng, Jian-Yun Nie, Jian Tang: RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/semantichumanmatting_MattingHumanDatasets.md b/mshub_res/assets/mindspore/1.6/semantichumanmatting_MattingHumanDatasets.md new file mode 100644 index 0000000..47eab3f --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/semantichumanmatting_MattingHumanDatasets.md @@ -0,0 +1,62 @@ +# semantic_human_matting + +--- + +model-name: semantic_human_matting + +backbone-name: semantic_human_matting + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: MattingHumanDatasets + +evaluation: avesad5.47 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 1a11ded55674d2757cf16e6d4001c724ff16824a6a22d973485d352b3df2e8c6 + +license: Apache2.0 + +summary: semantic_human_matting is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of semantic_human_matting from the MindSpore model zoo on Gitee at official/cv/semantic_human_matting. + +semantic_human_matting is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/semantic_human_matting](https://gitee.com/mindspore/models/blob/r1.6/official/cv/semantic_human_matting/README.md). + +All parameters in the module are trainable. + +## Citation + +[Semantic Human Matting](https://arxiv.org/pdf/1809.01354.pdf): Quan Chen, Tiezheng Ge, Yanyu Xu, Zhiqiang Zhang, Xinxin Yang, Kun Gai. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/senet_imagenet2012.md b/mshub_res/assets/mindspore/1.6/senet_imagenet2012.md new file mode 100644 index 0000000..4dca577 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/senet_imagenet2012.md @@ -0,0 +1,62 @@ +# SE-Net + +--- + +model-name: SE-Net + +backbone-name: SE-Net + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc77.75 | top5acc93.84 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 3abfaa11d0d9ef240641050df3a8c26a3e0f31e9484d10404a37246d7dc5f31c + +license: Apache2.0 + +summary: SE-Net is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of SE-Net from the MindSpore model zoo on Gitee at research/cv/SE-Net. + +SE-Net is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/SE-Net](https://gitee.com/mindspore/models/blob/r1.6/research/cv/SE-Net/README.md). + +All parameters in the module are trainable. + +## Citation + +Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu. "Squeeze-and-Excitation Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/seres2net50_imagenet2012.md b/mshub_res/assets/mindspore/1.6/seres2net50_imagenet2012.md new file mode 100644 index 0000000..74ecfcc --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/seres2net50_imagenet2012.md @@ -0,0 +1,79 @@ +# res2net + +--- + +model-name: res2net + +backbone-name: res2net + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc77 | top5acc93 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 7d402e03e15d72cfbd35b024d81ebe6429ab34498b89f7cfb51bb5dc3376338d + +license: Apache2.0 + +summary: res2net is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of res2net from the MindSpore model zoo on Gitee at research/cv/res2net. + +res2net is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/res2net](https://gitee.com/mindspore/models/blob/r1.6/research/cv/res2net/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/seres2net50_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Gao, Shang-Hua and Cheng, Ming-Ming and Zhao, Kai and Zhang, Xin-Yu and Yang, Ming-Hsuan and Torr, Philip. "Res2Net: A New Multi-scale Backbone Architecture"，TPAMI21 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/seresnet50_imagenet2012.md b/mshub_res/assets/mindspore/1.6/seresnet50_imagenet2012.md new file mode 100644 index 0000000..9d8bdbf --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/seresnet50_imagenet2012.md @@ -0,0 +1,81 @@ +# resnet + +--- + +model-name: resnet + +backbone-name: resnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc76.75 | top5acc93.43 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: fae985bd431915d4f743375fced2bad4ad5f40aadd31b3c840151e11528d8d60 + +license: Apache2.0 + +summary: resnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnet from the MindSpore model zoo on Gitee at official/cv/resnet. + +resnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/resnet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/resnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/seresnet50_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun."Deep Residual Learning for Image Recognition" +2. Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu."Squeeze-and-Excitation Networks" +3. Tong He, Zhi Zhang, Hang Zhang, Zhongyue Zhang, Junyuan Xie, Mu Li."Bag of Tricks for Image Classification with Convolutional Neural Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/seresnext50_imagenet2012.md b/mshub_res/assets/mindspore/1.6/seresnext50_imagenet2012.md new file mode 100644 index 0000000..45111ae --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/seresnext50_imagenet2012.md @@ -0,0 +1,62 @@ +# SE_ResNeXt50 + +--- + +model-name: SE_ResNeXt50 + +backbone-name: SE_ResNeXt50 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc79 | top5acc94 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: ba9443c3aa8ca6aa55fe4cbd23afb3aedd94573c1cea8d613ffad810baed55a6 + +license: Apache2.0 + +summary: SE_ResNeXt50 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of SE_ResNeXt50 from the MindSpore model zoo on Gitee at research/cv/SE_ResNeXt50. + +SE_ResNeXt50 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/SE_ResNeXt50](https://gitee.com/mindspore/models/blob/r1.6/research/cv/SE_ResNeXt50/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu."Squeeze-and-Excitation Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/shufflenetv1_imagenet2012.md b/mshub_res/assets/mindspore/1.6/shufflenetv1_imagenet2012.md new file mode 100644 index 0000000..421db70 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/shufflenetv1_imagenet2012.md @@ -0,0 +1,79 @@ +# shufflenetv1 + +--- + +model-name: shufflenetv1 + +backbone-name: shufflenetv1 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc73.83 | top5acc91.54 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 9e484f77bf133ba65ecc6ac28c04d76e45fc822fdf4fb1636fd83dd30de0e462 + +license: Apache2.0 + +summary: shufflenetv1 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of shufflenetv1 from the MindSpore model zoo on Gitee at official/cv/shufflenetv1. + +shufflenetv1 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/shufflenetv1](https://gitee.com/mindspore/models/blob/r1.6/official/cv/shufflenetv1/README_CN.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/shufflenetv1_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Xiangyu Zhang, Xinyu Zhou, Mengxiao Lin, Jian Sun. "ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices." *Proceedings of the IEEE conference on computer vision and pattern recognition*. 2018. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/shufflenetv2_imagenet2012.md b/mshub_res/assets/mindspore/1.6/shufflenetv2_imagenet2012.md new file mode 100644 index 0000000..3fb3083 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/shufflenetv2_imagenet2012.md @@ -0,0 +1,79 @@ +# shufflenetv2 + +--- + +model-name: shufflenetv2 + +backbone-name: shufflenetv2 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc69.63 | top5acc88.72 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: e1100bc808f1cbb37664d776085b4d82b19b5c9853c44f143366d76f6414bcbb + +license: Apache2.0 + +summary: shufflenetv2 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of shufflenetv2 from the MindSpore model zoo on Gitee at official/cv/shufflenetv2. + +shufflenetv2 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/shufflenetv2](https://gitee.com/mindspore/models/blob/r1.6/official/cv/shufflenetv2/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/shufflenetv2_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Ma, N., Zhang, X., Zheng, H. T., & Sun, J. (2018). Shufflenet v2: Practical guidelines for efficient cnn architecture design. In Proceedings of the European conference on computer vision (ECCV) (pp. 116-131). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/siamfc_ilsvrc2015vid.md b/mshub_res/assets/mindspore/1.6/siamfc_ilsvrc2015vid.md new file mode 100644 index 0000000..887844d --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/siamfc_ilsvrc2015vid.md @@ -0,0 +1,62 @@ +# SiamFC + +--- + +model-name: SiamFC + +backbone-name: SiamFC + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: ilsvrc2015vid + +evaluation: acc58.6 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 082586450b38aa49f4794fde27bb1368d65a515f9e9549ef78a37d74ff7e36aa + +license: Apache2.0 + +summary: SiamFC is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of SiamFC from the MindSpore model zoo on Gitee at research/cv/SiamFC. + +SiamFC is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/SiamFC](https://gitee.com/mindspore/models/blob/r1.6/research/cv/SiamFC/README.md). + +All parameters in the module are trainable. + +## Citation + +Luca Bertinetto Jack Valmadre Jo˜ao F. Henriques Andrea Vedaldi Philip H. S. Torr Department of Engineering Science, University of Oxford + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/simclr_encoder_cifar10.md b/mshub_res/assets/mindspore/1.6/simclr_encoder_cifar10.md new file mode 100644 index 0000000..42fbc33 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/simclr_encoder_cifar10.md @@ -0,0 +1,62 @@ +# simclr + +--- + +model-name: simclr + +backbone-name: simclr + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cifar10 + +evaluation: acc84.96 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 1a1c57d30a456fe89cb7a873f41632cc65147b4e2a2e93a0c2a8f31ebadfc71e + +license: Apache2.0 + +summary: simclr is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of simclr from the MindSpore model zoo on Gitee at official/cv/simclr. + +simclr is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/simclr](https://gitee.com/mindspore/models/blob/r1.6/official/cv/simclr/README.md). + +All parameters in the module are trainable. + +## Citation + +Ting Chen and Simon Kornblith and Mohammad Norouzi and Geoffrey Hinton. A Simple Framework for Contrastive Learning of Visual Representations. *arXiv preprint arXiv:2002.05709*. 2020. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/simclr_linearclassifier_cifar10.md b/mshub_res/assets/mindspore/1.6/simclr_linearclassifier_cifar10.md new file mode 100644 index 0000000..c55f091 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/simclr_linearclassifier_cifar10.md @@ -0,0 +1,62 @@ +# simclr + +--- + +model-name: simclr + +backbone-name: simclr + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cifar10 + +evaluation: acc84.96 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 24e2b2afcb09694808fb2226e32c436eb63964dfe8e4504f0f23240c9a7f83cb + +license: Apache2.0 + +summary: simclr is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of simclr from the MindSpore model zoo on Gitee at official/cv/simclr. + +simclr is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/simclr](https://gitee.com/mindspore/models/blob/r1.6/official/cv/simclr/README.md). + +All parameters in the module are trainable. + +## Citation + +Ting Chen and Simon Kornblith and Mohammad Norouzi and Geoffrey Hinton. A Simple Framework for Contrastive Learning of Visual Representations. *arXiv preprint arXiv:2002.05709*. 2020. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/simplebaselines_coco2017.md b/mshub_res/assets/mindspore/1.6/simplebaselines_coco2017.md new file mode 100644 index 0000000..d602571 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/simplebaselines_coco2017.md @@ -0,0 +1,62 @@ +# simple_baselines + +--- + +model-name: simple_baselines + +backbone-name: simple_baselines + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: acc72.3 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 31ad53e844b3a5301b8663e9b228c4eecdb904494ab605a1e9886f3956fbd00c + +license: Apache2.0 + +summary: simple_baselines is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of simple_baselines from the MindSpore model zoo on Gitee at research/cv/simple_baselines. + +simple_baselines is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/simple_baselines](https://gitee.com/mindspore/models/blob/r1.6/research/cv/simple_baselines/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Bin Xiao, Haiping Wu, Yichen Wei."Simple baselines for human pose estimation and tracking" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/simplepose_coco2017.md b/mshub_res/assets/mindspore/1.6/simplepose_coco2017.md new file mode 100644 index 0000000..05bb491 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/simplepose_coco2017.md @@ -0,0 +1,79 @@ +# simple_pose + +--- + +model-name: simple_pose + +backbone-name: simple_pose + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: acc70 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 206c944b9a756c17475c97864469cfb3c5e56b8737ecf6dccaf544b9fc75f0df + +license: Apache2.0 + +summary: simple_pose is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of simple_pose from the MindSpore model zoo on Gitee at official/cv/simple_pose. + +simple_pose is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/simple_pose](https://gitee.com/mindspore/models/blob/r1.6/official/cv/simple_pose/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/simplepose_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +B. Xiao, H. Wu, and Y. Wei, “Simple baselines for human pose estimation and tracking,” in Proc. Eur. Conf. Comput. Vis., 2018, pp. 472–487. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/singlepathnas_imagenet2012.md b/mshub_res/assets/mindspore/1.6/singlepathnas_imagenet2012.md new file mode 100644 index 0000000..bbc0f35 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/singlepathnas_imagenet2012.md @@ -0,0 +1,62 @@ +# single_path_nas + +--- + +model-name: single_path_nas + +backbone-name: single_path_nas + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc74.22 | top5acc91.73 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 692cfdf824de2958ed92ffc178c9e55738ecd6c60a474e7d76ec99a4f0aa15ae + +license: Apache2.0 + +summary: single_path_nas is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of single_path_nas from the MindSpore model zoo on Gitee at research/cv/single_path_nas. + +single_path_nas is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/single_path_nas](https://gitee.com/mindspore/models/blob/r1.6/research/cv/single_path_nas/README.md). + +All parameters in the module are trainable. + +## Citation + +https://zhuanlan.zhihu.com/p/63605721 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/skipgram_text8.md b/mshub_res/assets/mindspore/1.6/skipgram_text8.md new file mode 100644 index 0000000..802e96a --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/skipgram_text8.md @@ -0,0 +1,80 @@ +# skipgram + +--- + +model-name: skipgram + +backbone-name: skipgram + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: text8 + +evaluation: acc35.78 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5ce385cfc638b6ab2f10309fb4980792513458db4dfa1cc5adb2b2c382b1457a + +license: Apache2.0 + +summary: skipgram is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of skipgram from the MindSpore model zoo on Gitee at research/nlp/skipgram. + +skipgram is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [research/nlp/skipgram](https://gitee.com/mindspore/models/blob/r1.6/research/nlp/skipgram/README_CN.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/skipgram_text8" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Mikolov T, Chen K, Corrado G, et al. Efficient estimation of word representations in vector space[J]. arXiv preprint arXiv:1301.3781, 2013. +2. Mikolov T, Sutskever I, Chen K, et al. Distributed representations of words and phrases and their compositionality[J]. arXiv preprint arXiv:1310.4546, 2013. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/sknet_cifar10.md b/mshub_res/assets/mindspore/1.6/sknet_cifar10.md new file mode 100644 index 0000000..181d5ac --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/sknet_cifar10.md @@ -0,0 +1,62 @@ +# sknet + +--- + +model-name: sknet + +backbone-name: sknet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cifar10 + +evaluation: acc94 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 278db3c641d1be970d4fce82478f5e5b56f62ce4cbc8f122743a4093ba84014a + +license: Apache2.0 + +summary: sknet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of sknet from the MindSpore model zoo on Gitee at research/cv/sknet. + +sknet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/sknet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/sknet/README.md). + +All parameters in the module are trainable. + +## Citation + +Xiang Li, Wenhai Wang, Xiaolin Hu, Jian Yang. "Selective Kernel Networks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/squeezenet11_imagenet2012.md b/mshub_res/assets/mindspore/1.6/squeezenet11_imagenet2012.md new file mode 100644 index 0000000..a20ae96 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/squeezenet11_imagenet2012.md @@ -0,0 +1,62 @@ +# squeezenet1_1 + +--- + +model-name: squeezenet1_1 + +backbone-name: squeezenet1_1 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc58.51 | top5acc80.82 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c50c0293a9efbe2a9338bf41df6e8c399c4ef40511e9d27a5ebef83deea61252 + +license: Apache2.0 + +summary: squeezenet1_1 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of squeezenet1_1 from the MindSpore model zoo on Gitee at research/cv/squeezenet1_1. + +squeezenet1_1 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/squeezenet1_1](https://gitee.com/mindspore/models/blob/r1.6/research/cv/squeezenet1_1/README.md). + +All parameters in the module are trainable. + +## Citation + +Forrest N. Iandola and Song Han and Matthew W. Moskewicz and Khalid Ashraf and William J. Dally and Kurt Keutzer. "SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/squeezenet_cifar10.md b/mshub_res/assets/mindspore/1.6/squeezenet_cifar10.md new file mode 100644 index 0000000..a069b53 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/squeezenet_cifar10.md @@ -0,0 +1,79 @@ +# squeezenet + +--- + +model-name: squeezenet + +backbone-name: squeezenet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cifar10 + +evaluation: top1acc83.6 | top5acc99.31 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 6c40f21ad01c31a3e528a31e19d5c9a6890db0f17fa1475183e1a04641d223f7 + +license: Apache2.0 + +summary: squeezenet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of squeezenet from the MindSpore model zoo on Gitee at official/cv/squeezenet. + +squeezenet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/squeezenet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/squeezenet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/squeezenet_cifar10" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Forrest N. Iandola and Song Han and Matthew W. Moskewicz and Khalid Ashraf and William J. Dally and Kurt Keutzer. "SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/squeezenetresidual_cifar10.md b/mshub_res/assets/mindspore/1.6/squeezenetresidual_cifar10.md new file mode 100644 index 0000000..c403038 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/squeezenetresidual_cifar10.md @@ -0,0 +1,79 @@ +# squeezenet + +--- + +model-name: squeezenet + +backbone-name: squeezenet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cifar10 + +evaluation: top1acc87.25 | top5acc99.57 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5451da81fe3644f6ed2cae202aed49d08780de576b81828db2bfd3f293096e93 + +license: Apache2.0 + +summary: squeezenet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of squeezenet from the MindSpore model zoo on Gitee at official/cv/squeezenet. + +squeezenet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/squeezenet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/squeezenet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/squeezenetresidual_cifar10" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Forrest N. Iandola and Song Han and Matthew W. Moskewicz and Khalid Ashraf and William J. Dally and Kurt Keutzer. "SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/squeezenetresidual_imagenet2012.md b/mshub_res/assets/mindspore/1.6/squeezenetresidual_imagenet2012.md new file mode 100644 index 0000000..9a0ba7c --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/squeezenetresidual_imagenet2012.md @@ -0,0 +1,79 @@ +# squeezenet + +--- + +model-name: squeezenet + +backbone-name: squeezenet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc60.81 | top5acc82.55 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 1de97504c15df754cd37738b6b5bb89bdbe87a722c90c5e250e277985b075e35 + +license: Apache2.0 + +summary: squeezenet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of squeezenet from the MindSpore model zoo on Gitee at official/cv/squeezenet. + +squeezenet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/squeezenet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/squeezenet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/squeezenetresidual_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Forrest N. Iandola and Song Han and Matthew W. Moskewicz and Khalid Ashraf and William J. Dally and Kurt Keutzer. "SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/srcnn_ilsvrc2013.md b/mshub_res/assets/mindspore/1.6/srcnn_ilsvrc2013.md new file mode 100644 index 0000000..ffef017 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/srcnn_ilsvrc2013.md @@ -0,0 +1,62 @@ +# srcnn + +--- + +model-name: srcnn + +backbone-name: srcnn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: ilsvrc2013 + +evaluation: set5acc36.65 | set14acc32.57 | bsd200acc33.77 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: a55d5c782c1d131cefca86ad0c823fcbe610496429a552a39e0276b47428f212 + +license: Apache2.0 + +summary: srcnn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of srcnn from the MindSpore model zoo on Gitee at official/cv/srcnn. + +srcnn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/srcnn](https://gitee.com/mindspore/models/blob/r1.6/official/cv/srcnn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang. Image Super-Resolution Using Deep Convolutional Networks. 2014. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/srgan_div2k.md b/mshub_res/assets/mindspore/1.6/srgan_div2k.md new file mode 100644 index 0000000..b148daa --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/srgan_div2k.md @@ -0,0 +1,62 @@ +# SRGAN + +--- + +model-name: SRGAN + +backbone-name: SRGAN + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: div2k + +evaluation: psnr27.22 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5ec7e2e43b4e9abdee38e5bdb8f3703571c884f4827629065bd504822641ecc9 + +license: Apache2.0 + +summary: SRGAN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of SRGAN from the MindSpore model zoo on Gitee at research/cv/SRGAN. + +SRGAN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/SRGAN](https://gitee.com/mindspore/models/blob/r1.6/research/cv/SRGAN/README.md). + +All parameters in the module are trainable. + +## Citation + +Christian Ledig, Lucas thesis, Ferenc Huszar, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, Wenzhe Shi Twitter. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/ssd300_coco2017.md b/mshub_res/assets/mindspore/1.6/ssd300_coco2017.md new file mode 100644 index 0000000..208244a --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/ssd300_coco2017.md @@ -0,0 +1,79 @@ +# ssd + +--- + +model-name: ssd + +backbone-name: ssd + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: acc23 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d0b0449bab807e03528c88498425921a7a43a8d97fdd92bed6cf25d5b3379b07 + +license: Apache2.0 + +summary: ssd is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ssd from the MindSpore model zoo on Gitee at official/cv/ssd. + +ssd is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/ssd](https://gitee.com/mindspore/models/blob/r1.6/official/cv/ssd/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/ssd300_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg.European Conference on Computer Vision (ECCV), 2016 (In press). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/ssdghostnet_coco2017.md b/mshub_res/assets/mindspore/1.6/ssdghostnet_coco2017.md new file mode 100644 index 0000000..c6a2820 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/ssdghostnet_coco2017.md @@ -0,0 +1,79 @@ +# ssd_ghostnet + +--- + +model-name: ssd_ghostnet + +backbone-name: ssd_ghostnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: acc24.26 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: a1893fc926f7d721952733e7c42557520e7933060b5eb35bb0fec31d0b19dd1a + +license: Apache2.0 + +summary: ssd_ghostnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ssd_ghostnet from the MindSpore model zoo on Gitee at research/cv/ssd_ghostnet. + +ssd_ghostnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ssd_ghostnet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/ssd_ghostnet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/ssdghostnet_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg.European Conference on Computer Vision (ECCV), 2016 (In press). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/ssdinceptionv2_coco2014mini.md b/mshub_res/assets/mindspore/1.6/ssdinceptionv2_coco2014mini.md new file mode 100644 index 0000000..024d9b4 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/ssdinceptionv2_coco2014mini.md @@ -0,0 +1,62 @@ +# ssd_inceptionv2 + +--- + +model-name: ssd_inceptionv2 + +backbone-name: ssd_inceptionv2 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2014mini + +evaluation: mAP24 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c081a75c11307ace671e36168a17aa14c0d862736b96c9853329add2af7c9dfc + +license: Apache2.0 + +summary: ssd_inceptionv2 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ssd_inceptionv2 from the MindSpore model zoo on Gitee at research/cv/ssd_inceptionv2. + +ssd_inceptionv2 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ssd_inceptionv2](https://gitee.com/mindspore/models/blob/r1.6/research/cv/ssd_inceptionv2/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg.European Conference on Computer Vision (ECCV), 2016 (In press). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/ssdmobilenetv1fpn_coco2017.md b/mshub_res/assets/mindspore/1.6/ssdmobilenetv1fpn_coco2017.md new file mode 100644 index 0000000..624dba5 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/ssdmobilenetv1fpn_coco2017.md @@ -0,0 +1,79 @@ +# ssd + +--- + +model-name: ssd + +backbone-name: ssd + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: acc35.11 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5ff919cd507500f18f184c9174d66336edd2afcf8e18d6d9fc85a6d5bd59d4a8 + +license: Apache2.0 + +summary: ssd is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ssd from the MindSpore model zoo on Gitee at official/cv/ssd. + +ssd is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/ssd](https://gitee.com/mindspore/models/blob/r1.6/official/cv/ssd/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/ssdmobilenetv1fpn_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg.European Conference on Computer Vision (ECCV), 2016 (In press). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/ssdmobilenetv2_coco2017.md b/mshub_res/assets/mindspore/1.6/ssdmobilenetv2_coco2017.md new file mode 100644 index 0000000..284da02 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/ssdmobilenetv2_coco2017.md @@ -0,0 +1,62 @@ +# ssd_mobilenetV2 + +--- + +model-name: ssd_mobilenetV2 + +backbone-name: ssd_mobilenetV2 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: acc24 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 6da31f6eeee4d350e9bb658efbd697342d28f6a3b13fd5cb3e6aca2dc64707bb + +license: Apache2.0 + +summary: ssd_mobilenetV2 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ssd_mobilenetV2 from the MindSpore model zoo on Gitee at research/cv/ssd_mobilenetV2. + +ssd_mobilenetV2 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ssd_mobilenetV2](https://gitee.com/mindspore/models/blob/r1.6/research/cv/ssd_mobilenetV2/README.md). + +All parameters in the module are trainable. + +## Citation + +Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg.European Conference on Computer Vision (ECCV), 2016 (In press). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/ssdmobilenetv2fpnlite_coco2017.md b/mshub_res/assets/mindspore/1.6/ssdmobilenetv2fpnlite_coco2017.md new file mode 100644 index 0000000..c52f3fb --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/ssdmobilenetv2fpnlite_coco2017.md @@ -0,0 +1,62 @@ +# ssd_mobilenetV2_FPNlite + +--- + +model-name: ssd_mobilenetV2_FPNlite + +backbone-name: ssd_mobilenetV2_FPNlite + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: acc25.53 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 3cd83784a509fb83ea85a86277f61e1b3a90e17f86b826153a3ffcd3bd0d8b11 + +license: Apache2.0 + +summary: ssd_mobilenetV2_FPNlite is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ssd_mobilenetV2_FPNlite from the MindSpore model zoo on Gitee at research/cv/ssd_mobilenetV2_FPNlite. + +ssd_mobilenetV2_FPNlite is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ssd_mobilenetV2_FPNlite](https://gitee.com/mindspore/models/blob/r1.6/research/cv/ssd_mobilenetV2_FPNlite/README.md). + +All parameters in the module are trainable. + +## Citation + +Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg.European Conference on Computer Vision (ECCV), 2016 (In press). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/ssdresnet34_coco2017.md b/mshub_res/assets/mindspore/1.6/ssdresnet34_coco2017.md new file mode 100644 index 0000000..4607483 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/ssdresnet34_coco2017.md @@ -0,0 +1,62 @@ +# ssd_resnet34 + +--- + +model-name: ssd_resnet34 + +backbone-name: ssd_resnet34 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: acc24.08 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 33db66225ad886f0b6efb910d3982c1b15ca35b8a82b4e696e64155468a93ad3 + +license: Apache2.0 + +summary: ssd_resnet34 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ssd_resnet34 from the MindSpore model zoo on Gitee at research/cv/ssd_resnet34. + +ssd_resnet34 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ssd_resnet34](https://gitee.com/mindspore/models/blob/r1.6/research/cv/ssd_resnet34/README.md). + +All parameters in the module are trainable. + +## Citation + +Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg.European Conference on Computer Vision (ECCV), 2016 (In press). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/ssdresnet50_coco2017.md b/mshub_res/assets/mindspore/1.6/ssdresnet50_coco2017.md new file mode 100644 index 0000000..87c5d7b --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/ssdresnet50_coco2017.md @@ -0,0 +1,79 @@ +# ssd_resnet50 + +--- + +model-name: ssd_resnet50 + +backbone-name: ssd_resnet50 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: acc32.2 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: fa1e8c98113823174646d933ffa5f0edae7f7da0f66ca6eca697d7b6008e9226 + +license: Apache2.0 + +summary: ssd_resnet50 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ssd_resnet50 from the MindSpore model zoo on Gitee at research/cv/ssd_resnet50. + +ssd_resnet50 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/ssd_resnet50](https://gitee.com/mindspore/models/blob/r1.6/research/cv/ssd_resnet50/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/ssdresnet50_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg.European Conference on Computer Vision (ECCV), 2016 (In press). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/ssdresnet50fpn_coco2017.md b/mshub_res/assets/mindspore/1.6/ssdresnet50fpn_coco2017.md new file mode 100644 index 0000000..f380bff --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/ssdresnet50fpn_coco2017.md @@ -0,0 +1,79 @@ +# ssd + +--- + +model-name: ssd + +backbone-name: ssd + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: acc37.56 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5bf0dc1251ceca4bccc7fa1c42b972188901bf668c4fdf08b0856f6fb3a2bcd1 + +license: Apache2.0 + +summary: ssd is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ssd from the MindSpore model zoo on Gitee at official/cv/ssd. + +ssd is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/ssd](https://gitee.com/mindspore/models/blob/r1.6/official/cv/ssd/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/ssdresnet50fpn_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg.European Conference on Computer Vision (ECCV), 2016 (In press). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/ssdvgg16_coco2017.md b/mshub_res/assets/mindspore/1.6/ssdvgg16_coco2017.md new file mode 100644 index 0000000..6dfe0b5 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/ssdvgg16_coco2017.md @@ -0,0 +1,79 @@ +# ssd + +--- + +model-name: ssd + +backbone-name: ssd + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: acc23.39 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 03ee602a3dcecd3999fc8b3bec633467e8a7ce72de02a214e654d2c51430a4fa + +license: Apache2.0 + +summary: ssd is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of ssd from the MindSpore model zoo on Gitee at official/cv/ssd. + +ssd is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/ssd](https://gitee.com/mindspore/models/blob/r1.6/official/cv/ssd/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/ssdvgg16_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg.European Conference on Computer Vision (ECCV), 2016 (In press). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/stackedhourglass_mpii.md b/mshub_res/assets/mindspore/1.6/stackedhourglass_mpii.md new file mode 100644 index 0000000..95d811d --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/stackedhourglass_mpii.md @@ -0,0 +1,62 @@ +# StackedHourglass + +--- + +model-name: StackedHourglass + +backbone-name: StackedHourglass + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: mpii + +evaluation: acc87.7 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 61919979915eb5083883e241aa92585b55a8c09f44f5f36c9e18022af6e9f6d6 + +license: Apache2.0 + +summary: StackedHourglass is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of StackedHourglass from the MindSpore model zoo on Gitee at research/cv/StackedHourglass. + +StackedHourglass is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/StackedHourglass](https://gitee.com/mindspore/models/blob/r1.6/research/cv/StackedHourglass/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Stacked Hourglass Networks for Human Pose Estimation + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/stargan_G_celeba.md b/mshub_res/assets/mindspore/1.6/stargan_G_celeba.md new file mode 100644 index 0000000..2c61d4d --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/stargan_G_celeba.md @@ -0,0 +1,62 @@ +# StarGAN + +--- + +model-name: StarGAN + +backbone-name: StarGAN + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: celeba + +evaluation: no + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d3784354455957b431cd751e093c9645d27f4a225279011d69f894811aff558e + +license: Apache2.0 + +summary: StarGAN is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of StarGAN from the MindSpore model zoo on Gitee at research/cv/StarGAN. + +StarGAN is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/StarGAN](https://gitee.com/mindspore/models/blob/r1.6/research/cv/StarGAN/README.md). + +All parameters in the module are trainable. + +## Citation + +StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/stgcn_cheb15_pemsd7m.md b/mshub_res/assets/mindspore/1.6/stgcn_cheb15_pemsd7m.md new file mode 100644 index 0000000..82864f0 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/stgcn_cheb15_pemsd7m.md @@ -0,0 +1,62 @@ +# stgcn + +--- + +model-name: stgcn + +backbone-name: stgcn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: pemsd7m + +evaluation: mae2.22 | mape5.27 | rmse4.05 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 72a56d2a94902b3e39bd4f7209d03fdbb7297c9fea7b4a962dc9e3bdfbc27ebb + +license: Apache2.0 + +summary: stgcn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of stgcn from the MindSpore model zoo on Gitee at research/cv/stgcn. + +stgcn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/stgcn](https://gitee.com/mindspore/models/blob/r1.6/research/cv/stgcn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Bing yu, Haoteng Yin, and Zhanxing Zhu. "Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting." Proceedings of the 27th International Joint Conference on Artificial Intelligence. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/stgcn_cheb30_pemsd7m.md b/mshub_res/assets/mindspore/1.6/stgcn_cheb30_pemsd7m.md new file mode 100644 index 0000000..89ed45e --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/stgcn_cheb30_pemsd7m.md @@ -0,0 +1,62 @@ +# stgcn + +--- + +model-name: stgcn + +backbone-name: stgcn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: pemsd7m + +evaluation: mae2.89 | mape7.35 | rmse5.43 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 8ff99b5672b05a8df426d9a2c465cbcb2cdfffaf6234408ab917c4c1e946563d + +license: Apache2.0 + +summary: stgcn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of stgcn from the MindSpore model zoo on Gitee at research/cv/stgcn. + +stgcn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/stgcn](https://gitee.com/mindspore/models/blob/r1.6/research/cv/stgcn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Bing yu, Haoteng Yin, and Zhanxing Zhu. "Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting." Proceedings of the 27th International Joint Conference on Artificial Intelligence. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/stgcn_cheb45_pemsd7m.md b/mshub_res/assets/mindspore/1.6/stgcn_cheb45_pemsd7m.md new file mode 100644 index 0000000..f131754 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/stgcn_cheb45_pemsd7m.md @@ -0,0 +1,62 @@ +# stgcn + +--- + +model-name: stgcn + +backbone-name: stgcn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: pemsd7m + +evaluation: mae3.22 | mape8.37 | rmse6.09 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 75da728efa227e2c6333d5a529d190c8dfb14eea475c7e4dc780d08acd0d2645 + +license: Apache2.0 + +summary: stgcn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of stgcn from the MindSpore model zoo on Gitee at research/cv/stgcn. + +stgcn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/stgcn](https://gitee.com/mindspore/models/blob/r1.6/research/cv/stgcn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Bing yu, Haoteng Yin, and Zhanxing Zhu. "Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting." Proceedings of the 27th International Joint Conference on Artificial Intelligence. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/stgcn_gcn15_pemsd7m.md b/mshub_res/assets/mindspore/1.6/stgcn_gcn15_pemsd7m.md new file mode 100644 index 0000000..4f90d3f --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/stgcn_gcn15_pemsd7m.md @@ -0,0 +1,62 @@ +# stgcn + +--- + +model-name: stgcn + +backbone-name: stgcn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: pemsd7m + +evaluation: mae2.22 | mape5.38 | rmse4.06 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 1db5f527a97596ee870cacd2029dd87d8a61b70ab32d10ed13ef5bf97e72103e + +license: Apache2.0 + +summary: stgcn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of stgcn from the MindSpore model zoo on Gitee at research/cv/stgcn. + +stgcn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/stgcn](https://gitee.com/mindspore/models/blob/r1.6/research/cv/stgcn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Bing yu, Haoteng Yin, and Zhanxing Zhu. "Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting." Proceedings of the 27th International Joint Conference on Artificial Intelligence. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/stgcn_gcn30_pemsd7m.md b/mshub_res/assets/mindspore/1.6/stgcn_gcn30_pemsd7m.md new file mode 100644 index 0000000..45d2d42 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/stgcn_gcn30_pemsd7m.md @@ -0,0 +1,62 @@ +# stgcn + +--- + +model-name: stgcn + +backbone-name: stgcn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: pemsd7m + +evaluation: mae2.88 | mape7.22 | rmse5.38 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 25f13d7b960f9c9838737efeada659b09ff8109b3a3b78b33da270a1c4f7c617 + +license: Apache2.0 + +summary: stgcn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of stgcn from the MindSpore model zoo on Gitee at research/cv/stgcn. + +stgcn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/stgcn](https://gitee.com/mindspore/models/blob/r1.6/research/cv/stgcn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Bing yu, Haoteng Yin, and Zhanxing Zhu. "Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting." Proceedings of the 27th International Joint Conference on Artificial Intelligence. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/stgcn_gcn45_pemsd7m.md b/mshub_res/assets/mindspore/1.6/stgcn_gcn45_pemsd7m.md new file mode 100644 index 0000000..5fc2736 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/stgcn_gcn45_pemsd7m.md @@ -0,0 +1,62 @@ +# stgcn + +--- + +model-name: stgcn + +backbone-name: stgcn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: pemsd7m + +evaluation: mae3.2 | mape8.32 | rmse6.08 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: f649e6cd1537acdc2759c33615b85373227b2b4153cec27fc708012bc9783ca7 + +license: Apache2.0 + +summary: stgcn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of stgcn from the MindSpore model zoo on Gitee at research/cv/stgcn. + +stgcn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/stgcn](https://gitee.com/mindspore/models/blob/r1.6/research/cv/stgcn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Bing yu, Haoteng Yin, and Zhanxing Zhu. "Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting." Proceedings of the 27th International Joint Conference on Artificial Intelligence. 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/swintransformer_imagenet2012.md b/mshub_res/assets/mindspore/1.6/swintransformer_imagenet2012.md new file mode 100644 index 0000000..31d7d1d --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/swintransformer_imagenet2012.md @@ -0,0 +1,58 @@ +# swin_transformer + +--- + +model-name: swin_transformer + +backbone-name: swin_transformer + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc80.96 | top5acc95.37 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: fe17613c1195629274edb22f92fc0704ddd02a20df8bd7e100afbb443d854e7e + +license: Apache2.0 + +summary: swin_transformer is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of swin_transformer from the MindSpore model zoo on Gitee at research/cv/swin_transformer. + +swin_transformer is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/swin_transformer](https://gitee.com/mindspore/models/blob/r1.6/research/cv/swin_transformer/README_CN.md). + +All parameters in the module are trainable. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/tacotron2_ljspeech1.1.md b/mshub_res/assets/mindspore/1.6/tacotron2_ljspeech1.1.md new file mode 100644 index 0000000..b3549f8 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/tacotron2_ljspeech1.1.md @@ -0,0 +1,62 @@ +# tacotron2 + +--- + +model-name: tacotron2 + +backbone-name: tacotron2 + +module-type: audio + +fine-tunable: True + +model-version: 1.6 + +train-dataset: ljspeech1.1 + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 12176c49d868e86841b96f9f6517f1e28287a203ec67137b76d59bfdc1e19a62 + +license: Apache2.0 + +summary: tacotron2 is used for audio + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of tacotron2 from the MindSpore model zoo on Gitee at research/audio/tacotron2. + +tacotron2 is a audio network. More details please refer to the MindSpore model zoo on Gitee at [research/audio/tacotron2](https://gitee.com/mindspore/models/blob/r1.6/research/audio/tacotron2/README.md). + +All parameters in the module are trainable. + +## Citation + +Jonathan, et al. Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/textcnn_moviereview.md b/mshub_res/assets/mindspore/1.6/textcnn_moviereview.md new file mode 100644 index 0000000..1210cb8 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/textcnn_moviereview.md @@ -0,0 +1,79 @@ +# textcnn + +--- + +model-name: textcnn + +backbone-name: textcnn + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: moviereview + +evaluation: acc77.44 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c3f83fae12202952e0b0f12abb9032208bb0c55d9c001e383d5e005cc256f052 + +license: Apache2.0 + +summary: textcnn is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of textcnn from the MindSpore model zoo on Gitee at official/nlp/textcnn. + +textcnn is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/textcnn](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/textcnn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/textcnn_moviereview" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Kim Y. Convolutional neural networks for sentence classification[J]. arXiv preprint arXiv:1408.5882, 2014. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/textcnn_sst2.md b/mshub_res/assets/mindspore/1.6/textcnn_sst2.md new file mode 100644 index 0000000..baf38d6 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/textcnn_sst2.md @@ -0,0 +1,79 @@ +# textcnn + +--- + +model-name: textcnn + +backbone-name: textcnn + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: sst2 + +evaluation: acc82.91 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 7130c9d6d615f72caf1e27340de952f907ebe31a98886a57c0c38779c2eee6b7 + +license: Apache2.0 + +summary: textcnn is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of textcnn from the MindSpore model zoo on Gitee at official/nlp/textcnn. + +textcnn is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/textcnn](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/textcnn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/textcnn_sst2" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Kim Y. Convolutional neural networks for sentence classification[J]. arXiv preprint arXiv:1408.5882, 2014. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/textcnn_subj.md b/mshub_res/assets/mindspore/1.6/textcnn_subj.md new file mode 100644 index 0000000..0fb86ad --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/textcnn_subj.md @@ -0,0 +1,79 @@ +# textcnn + +--- + +model-name: textcnn + +backbone-name: textcnn + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: subj + +evaluation: acc90.17 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 104ce6ddf0555a1c10b1dc21204e7071e3d68141b3380a573517245d0ef819fb + +license: Apache2.0 + +summary: textcnn is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of textcnn from the MindSpore model zoo on Gitee at official/nlp/textcnn. + +textcnn is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/textcnn](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/textcnn/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/textcnn_subj" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Kim Y. Convolutional neural networks for sentence classification[J]. arXiv preprint arXiv:1408.5882, 2014. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/textcrnn_gru_polarity_moviereview.md b/mshub_res/assets/mindspore/1.6/textcrnn_gru_polarity_moviereview.md new file mode 100644 index 0000000..76001fb --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/textcrnn_gru_polarity_moviereview.md @@ -0,0 +1,79 @@ +# textrcnn + +--- + +model-name: textrcnn + +backbone-name: textrcnn + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: polarity_moviereview + +evaluation: acc81.05 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 24768f71515678d7ce0c525896a990652f79148d8ebcfa6f21a3b31a4d12826b + +license: Apache2.0 + +summary: textrcnn is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of textrcnn from the MindSpore model zoo on Gitee at research/nlp/textrcnn. + +textrcnn is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [research/nlp/textrcnn](https://gitee.com/mindspore/models/blob/r1.6/research/nlp/textrcnn/readme.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/textcrnn_gru_polarity_moviereview" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Siwei Lai, Liheng Xu, Kang Liu, Jun Zhao: Recurrent Convolutional Neural Networks for Text Classification. AAAI 2015: 2267-2273 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/textcrnn_lstm_polarity_moviereview.md b/mshub_res/assets/mindspore/1.6/textcrnn_lstm_polarity_moviereview.md new file mode 100644 index 0000000..3c790e1 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/textcrnn_lstm_polarity_moviereview.md @@ -0,0 +1,79 @@ +# textrcnn + +--- + +model-name: textrcnn + +backbone-name: textrcnn + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: polarity_moviereview + +evaluation: acc80.76 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5f9d9fbf78b31fb4f51d3b5c9e92f1a97b0e4388b11b060ad4001307e1615e74 + +license: Apache2.0 + +summary: textrcnn is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of textrcnn from the MindSpore model zoo on Gitee at research/nlp/textrcnn. + +textrcnn is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [research/nlp/textrcnn](https://gitee.com/mindspore/models/blob/r1.6/research/nlp/textrcnn/readme.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/textcrnn_lstm_polarity_moviereview" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Siwei Lai, Liheng Xu, Kang Liu, Jun Zhao: Recurrent Convolutional Neural Networks for Text Classification. AAAI 2015: 2267-2273 + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/textfusenet_totaltext.md b/mshub_res/assets/mindspore/1.6/textfusenet_totaltext.md new file mode 100644 index 0000000..45b3f16 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/textfusenet_totaltext.md @@ -0,0 +1,62 @@ +# textfusenet + +--- + +model-name: textfusenet + +backbone-name: textfusenet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: totaltext + +evaluation: totaltext81 | ctw1500acc81 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 2971951ea94b225b12fa9ec9b044510b46eefa17f026866f16961fe017acc6c9 + +license: Apache2.0 + +summary: textfusenet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of textfusenet from the MindSpore model zoo on Gitee at research/cv/textfusenet. + +textfusenet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/textfusenet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/textfusenet/README.md). + +All parameters in the module are trainable. + +## Citation + +Jian Ye, Zhe Chen, Juhua Liu, Bo Du. "TextFuseNet: Scene Text Detection with Richer Fused Features" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/tgcn_losloop.md b/mshub_res/assets/mindspore/1.6/tgcn_losloop.md new file mode 100644 index 0000000..220c86e --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/tgcn_losloop.md @@ -0,0 +1,62 @@ +# tgcn + +--- + +model-name: tgcn + +backbone-name: tgcn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: losloop + +evaluation: acc91.21 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 0b3162244fffca2e0ca5658e59ac4d80aaecf216dd4b4cf16c962e82da9cd26c + +license: Apache2.0 + +summary: tgcn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of tgcn from the MindSpore model zoo on Gitee at research/cv/tgcn. + +tgcn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/tgcn](https://gitee.com/mindspore/models/blob/r1.6/research/cv/tgcn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +3848-3858.Zhao L, Song Y, Zhang C, et al. T-gcn: A temporal graph convolutional network for traffic prediction[J]. IEEE Transactions on Intelligent Transportation Systems, 2019, 21(9): 3848-3858. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/tgcn_sztaxi.md b/mshub_res/assets/mindspore/1.6/tgcn_sztaxi.md new file mode 100644 index 0000000..1cb0926 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/tgcn_sztaxi.md @@ -0,0 +1,62 @@ +# tgcn + +--- + +model-name: tgcn + +backbone-name: tgcn + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: sztaxi + +evaluation: acc71.56 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c79c54aff6d58c82d097fc3754788017cd03ca916a585a775b6c692a7c9a0d41 + +license: Apache2.0 + +summary: tgcn is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of tgcn from the MindSpore model zoo on Gitee at research/cv/tgcn. + +tgcn is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/tgcn](https://gitee.com/mindspore/models/blob/r1.6/research/cv/tgcn/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Zhao L, Song Y, Zhang C, et al. T-gcn: A temporal graph convolutional network for traffic prediction[J]. IEEE Transactions on Intelligent Transportation Systems, 2019, 21(9): 3848-3858. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/tinybert_enwiki128_mnli.md b/mshub_res/assets/mindspore/1.6/tinybert_enwiki128_mnli.md new file mode 100644 index 0000000..6d4b605 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/tinybert_enwiki128_mnli.md @@ -0,0 +1,79 @@ +# tinybert + +--- + +model-name: tinybert + +backbone-name: tinybert + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: enwiki128_mnli + +evaluation: acc81.31 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 71dc99d4f2c9a369760fe1620bd2a48e611bbc7bbe15bfd564e69f4d0fee6d82 + +license: Apache2.0 + +summary: tinybert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of tinybert from the MindSpore model zoo on Gitee at official/nlp/tinybert. + +tinybert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/tinybert](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/tinybert/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/tinybert_enwiki128_mnli" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, Qun Liu. TinyBERT: Distilling BERT for Natural Language Understanding. arXiv preprint arXiv:1909.10351. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/tinybert_enwiki128_qnli.md b/mshub_res/assets/mindspore/1.6/tinybert_enwiki128_qnli.md new file mode 100644 index 0000000..576c34d --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/tinybert_enwiki128_qnli.md @@ -0,0 +1,79 @@ +# tinybert + +--- + +model-name: tinybert + +backbone-name: tinybert + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: enwiki128_qnli + +evaluation: acc88.86 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d33ae2a4548502bc392ed286d7dfb17102efc5ca8a9203b70b40df6a381d52ed + +license: Apache2.0 + +summary: tinybert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of tinybert from the MindSpore model zoo on Gitee at official/nlp/tinybert. + +tinybert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/tinybert](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/tinybert/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/tinybert_enwiki128_qnli" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, Qun Liu. TinyBERT: Distilling BERT for Natural Language Understanding. arXiv preprint arXiv:1909.10351. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/tinybert_enwiki128_sst2.md b/mshub_res/assets/mindspore/1.6/tinybert_enwiki128_sst2.md new file mode 100644 index 0000000..1d80d18 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/tinybert_enwiki128_sst2.md @@ -0,0 +1,79 @@ +# tinybert + +--- + +model-name: tinybert + +backbone-name: tinybert + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: enwiki128_sst2 + +evaluation: acc90.28 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 5d9df51b52990a6d20e500923163076dff8fb3821d791c50e1255588cb8b219d + +license: Apache2.0 + +summary: tinybert is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of tinybert from the MindSpore model zoo on Gitee at official/nlp/tinybert. + +tinybert is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/tinybert](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/tinybert/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/tinybert_enwiki128_sst2" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, Qun Liu. TinyBERT: Distilling BERT for Natural Language Understanding. arXiv preprint arXiv:1909.10351. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/tinydarknet_imagenet2012.md b/mshub_res/assets/mindspore/1.6/tinydarknet_imagenet2012.md new file mode 100644 index 0000000..4e8ddcc --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/tinydarknet_imagenet2012.md @@ -0,0 +1,75 @@ +# tinydarknet + +--- + +model-name: tinydarknet + +backbone-name: tinydarknet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc59.0 | top5acc81.84 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 00a1544972eaeecec147e15dfa49c1796368c054776d59a73a7e905c285b6256 + +license: Apache2.0 + +summary: tinydarknet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of tinydarknet from the MindSpore model zoo on Gitee at official/cv/tinydarknet. + +tinydarknet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/tinydarknet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/tinydarknet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/tinydarknet_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/transformer_wmt.md b/mshub_res/assets/mindspore/1.6/transformer_wmt.md new file mode 100644 index 0000000..de7ecde --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/transformer_wmt.md @@ -0,0 +1,79 @@ +# transformer + +--- + +model-name: transformer + +backbone-name: transformer + +module-type: nlp + +fine-tunable: True + +model-version: 1.6 + +train-dataset: wmt + +evaluation: acc27.21 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: b322b9e912295d6f6dae34381488c8fa8676fd4759aae178f77b05acebb3dc0f + +license: Apache2.0 + +summary: transformer is used for nlp + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of transformer from the MindSpore model zoo on Gitee at official/nlp/transformer. + +transformer is a nlp network. More details please refer to the MindSpore model zoo on Gitee at [official/nlp/transformer](https://gitee.com/mindspore/models/blob/r1.6/official/nlp/transformer/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/transformer_wmt" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Ashish Vaswani, Noam Shazeer, Niki Parmar, JakobUszkoreit, Llion Jones, Aidan N Gomez, Ł ukaszKaiser, and Illia Polosukhin. 2017. Attention is all you need. In NIPS 2017, pages 5998–6008. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/unet3d_luna16.md b/mshub_res/assets/mindspore/1.6/unet3d_luna16.md new file mode 100644 index 0000000..d0c1af4 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/unet3d_luna16.md @@ -0,0 +1,79 @@ +# unet3d + +--- + +model-name: unet3d + +backbone-name: unet3d + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: luna16 + +evaluation: acc96.54 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 557eb7c3914428458f037bdf6d9320015021ebb3ccdb9740fe01823eed41027a + +license: Apache2.0 + +summary: unet3d is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of unet3d from the MindSpore model zoo on Gitee at official/cv/unet3d. + +unet3d is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/unet3d](https://gitee.com/mindspore/models/blob/r1.6/official/cv/unet3d/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/unet3d_luna16" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Unet3D: Learning Dense VolumetricSegmentation from Sparse Annotation. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/unet3plus_lits2017.md b/mshub_res/assets/mindspore/1.6/unet3plus_lits2017.md new file mode 100644 index 0000000..c745725 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/unet3plus_lits2017.md @@ -0,0 +1,62 @@ +# UNet3+ + +--- + +model-name: UNet3+ + +backbone-name: UNet3+ + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: lits2017 + +evaluation: acc96 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: bcad7cb89d81da57d53b49928f6d0af96bb5d26552170bc4900402b8171d02b0 + +license: Apache2.0 + +summary: UNet3+ is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of UNet3+ from the MindSpore model zoo on Gitee at research/cv/UNet3+. + +UNet3+ is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/UNet3+](https://gitee.com/mindspore/models/blob/r1.6/research/cv/UNet3+/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Huang H , Lin L , Tong R , et al. UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation[J]. arXiv, 2020. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/unet_medical_isbi.md b/mshub_res/assets/mindspore/1.6/unet_medical_isbi.md new file mode 100644 index 0000000..f41acb6 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/unet_medical_isbi.md @@ -0,0 +1,80 @@ +# unet + +--- + +model-name: unet + +backbone-name: unet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: isbi + +evaluation: acc91.39 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 10a70d0264ff08f20b2887fb25f8676bd5eb0be61a9e48986ae63ca86667873a + +license: Apache2.0 + +summary: unet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of unet from the MindSpore model zoo on Gitee at official/cv/unet. + +unet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/unet](https://gitee.com/mindspore/models/blob/r1.6/official/cv/unet/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/unet_medical_isbi" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +1. Olaf Ronneberger, Philipp Fischer, Thomas Brox. "U-Net: Convolutional Networks for Biomedical Image Segmentation." conditionally accepted at MICCAI 2015. 2015. +2. Z. Zhou, M. M. R. Siddiquee, N. Tajbakhsh and J. Liang, "UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation," in IEEE Transactions on Medical Imaging, vol. 39, no. 6, pp. 1856-1867, June 2020, doi: 10.1109/TMI.2019.2959609. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/vgg16_bn_imagenet2012.md b/mshub_res/assets/mindspore/1.6/vgg16_bn_imagenet2012.md new file mode 100644 index 0000000..8dd16e9 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/vgg16_bn_imagenet2012.md @@ -0,0 +1,79 @@ +# vgg16 + +--- + +model-name: vgg16 + +backbone-name: vgg16 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc74.33 | top5acc92.1 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: e12b2eb08c1c32001a6f5873fa80b6430919949c5a8d4515469ea351eb416afa + +license: Apache2.0 + +summary: vgg16 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of vgg16 from the MindSpore model zoo on Gitee at official/cv/vgg16. + +vgg16 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/vgg16](https://gitee.com/mindspore/models/blob/r1.6/official/cv/vgg16/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/vgg16_bn_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Simonyan K, zisserman A. Very Deep Convolutional Networks for Large-Scale Image Recognition[J]. arXiv preprint arXiv:1409.1556, 2014. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/vgg16_cifar10.md b/mshub_res/assets/mindspore/1.6/vgg16_cifar10.md new file mode 100644 index 0000000..5c57052 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/vgg16_cifar10.md @@ -0,0 +1,79 @@ +# vgg16 + +--- + +model-name: vgg16 + +backbone-name: vgg16 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cifar10 + +evaluation: acc93.44 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 0ad3742ac1e20bd06c50fe5bfce0d23e4df3e5baf976e360412093a23546f969 + +license: Apache2.0 + +summary: vgg16 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of vgg16 from the MindSpore model zoo on Gitee at official/cv/vgg16. + +vgg16 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/vgg16](https://gitee.com/mindspore/models/blob/r1.6/official/cv/vgg16/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/vgg16_cifar10" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Simonyan K, zisserman A. Very Deep Convolutional Networks for Large-Scale Image Recognition[J]. arXiv preprint arXiv:1409.1556, 2014. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/vgg16_imagenet2012.md b/mshub_res/assets/mindspore/1.6/vgg16_imagenet2012.md new file mode 100644 index 0000000..5f7bb18 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/vgg16_imagenet2012.md @@ -0,0 +1,79 @@ +# vgg16 + +--- + +model-name: vgg16 + +backbone-name: vgg16 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc73.49 | top5acc91.56 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: a400e47c89ce77ade7e45b7eb7c84dc04378152ed92a549e8b5f6e046ef36829 + +license: Apache2.0 + +summary: vgg16 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of vgg16 from the MindSpore model zoo on Gitee at official/cv/vgg16. + +vgg16 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/vgg16](https://gitee.com/mindspore/models/blob/r1.6/official/cv/vgg16/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/vgg16_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Simonyan K, zisserman A. Very Deep Convolutional Networks for Large-Scale Image Recognition[J]. arXiv preprint arXiv:1409.1556, 2014. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/vgg19_imagenet2012.md b/mshub_res/assets/mindspore/1.6/vgg19_imagenet2012.md new file mode 100644 index 0000000..2a94708 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/vgg19_imagenet2012.md @@ -0,0 +1,79 @@ +# vgg19 + +--- + +model-name: vgg19 + +backbone-name: vgg19 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc74 | top5acc91.97 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: ea034624d868d0b8b52eb6c0b46c5e8288f8773efe7d80c88ef430890a1cb12d + +license: Apache2.0 + +summary: vgg19 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of vgg19 from the MindSpore model zoo on Gitee at research/cv/vgg19. + +vgg19 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/vgg19](https://gitee.com/mindspore/models/blob/r1.6/research/cv/vgg19/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/vgg19_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Simonyan K, zisserman A. Very Deep Convolutional Networks for Large-Scale Image Recognition[J]. arXiv preprint arXiv:1409.1556, 2014. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/vit_imagenet2012.md b/mshub_res/assets/mindspore/1.6/vit_imagenet2012.md new file mode 100644 index 0000000..cd51c3a --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/vit_imagenet2012.md @@ -0,0 +1,79 @@ +# vit + +--- + +model-name: vit + +backbone-name: vit + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: acc74.17 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c24895695e24c1cbb2deb12e4aeb43080cc4e420247cbbe571a70994a6366264 + +license: Apache2.0 + +summary: vit is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of vit from the MindSpore model zoo on Gitee at official/cv/vit. + +vit is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/vit](https://gitee.com/mindspore/models/blob/r1.6/official/cv/vit/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/vit_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, Neil Houlsby. 2021. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/vitbase_cifar10.md b/mshub_res/assets/mindspore/1.6/vitbase_cifar10.md new file mode 100644 index 0000000..495d5b3 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/vitbase_cifar10.md @@ -0,0 +1,62 @@ +# vit_base + +--- + +model-name: vit_base + +backbone-name: vit_base + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cifar10 + +evaluation: acc98.71 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 86646358bde1d63ce8a073ea0543f3cea94e95e1752ea621cb3c66a4b101a678 + +license: Apache2.0 + +summary: vit_base is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of vit_base from the MindSpore model zoo on Gitee at research/cv/vit_base. + +vit_base is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/vit_base](https://gitee.com/mindspore/models/blob/r1.6/research/cv/vit_base/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Dosovitskiy, A. , Beyer, L. , Kolesnikov, A. , Weissenborn, D. , & Houlsby, N.. (2020). An image is worth 16x16 words: transformers for image recognition at scale. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/vnet_promise2012.md b/mshub_res/assets/mindspore/1.6/vnet_promise2012.md new file mode 100644 index 0000000..f6f34ec --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/vnet_promise2012.md @@ -0,0 +1,62 @@ +# vnet + +--- + +model-name: vnet + +backbone-name: vnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: promise2012 + +evaluation: dice85 | hausdorffdistance10 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 6afc96e827a5ced76fbe95f93f02dbfea6be024d3261eb4f335e1897b07c8ad9 + +license: Apache2.0 + +summary: vnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of vnet from the MindSpore model zoo on Gitee at research/cv/vnet. + +vnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/vnet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/vnet/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +F Milletari, Navab N, Ahmadi S A. V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation[C]// 2016 Fourth International Conference on 3D Vision (3DV). IEEE, 2016. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/warpctc_captcha.md b/mshub_res/assets/mindspore/1.6/warpctc_captcha.md new file mode 100644 index 0000000..f769064 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/warpctc_captcha.md @@ -0,0 +1,75 @@ +# warpctc + +--- + +model-name: warpctc + +backbone-name: warpctc + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: captcha + +evaluation: acc99.17 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: f9bf44cb3d8889136139796d0f18100dd1dc65a720df33829ccd4009c9fdf3d9 + +license: Apache2.0 + +summary: warpctc is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of warpctc from the MindSpore model zoo on Gitee at official/cv/warpctc. + +warpctc is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/warpctc](https://gitee.com/mindspore/models/blob/r1.6/official/cv/warpctc/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/warpctc_captcha" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/wgan_batchnorm_G_lsunbedrooms.md b/mshub_res/assets/mindspore/1.6/wgan_batchnorm_G_lsunbedrooms.md new file mode 100644 index 0000000..e02ee3b --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/wgan_batchnorm_G_lsunbedrooms.md @@ -0,0 +1,62 @@ +# wgan + +--- + +model-name: wgan + +backbone-name: wgan + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: lsunbedrooms + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: f1a6d7adb5e168d3913b6bac61dbe77c487f5d5293bca3b951a73144d3a5e4f0 + +license: Apache2.0 + +summary: wgan is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of wgan from the MindSpore model zoo on Gitee at research/cv/wgan. + +wgan is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/wgan](https://gitee.com/mindspore/models/blob/r1.6/research/cv/wgan/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Martin Arjovsky, Soumith Chintala, Léon Bottou. "Wasserstein GAN"*In International Conference on Machine Learning(ICML 2017). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/wgan_nobatchnorm_G_lsunbedrooms.md b/mshub_res/assets/mindspore/1.6/wgan_nobatchnorm_G_lsunbedrooms.md new file mode 100644 index 0000000..09fdd8e --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/wgan_nobatchnorm_G_lsunbedrooms.md @@ -0,0 +1,62 @@ +# wgan + +--- + +model-name: wgan + +backbone-name: wgan + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: lsunbedrooms + +evaluation: - + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: ca9fa2777634bb1f96aa61cf48cbfa45677d8b690ad362ae2708677a21f7a167 + +license: Apache2.0 + +summary: wgan is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of wgan from the MindSpore model zoo on Gitee at research/cv/wgan. + +wgan is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/wgan](https://gitee.com/mindspore/models/blob/r1.6/research/cv/wgan/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Martin Arjovsky, Soumith Chintala, Léon Bottou. "Wasserstein GAN"*In International Conference on Machine Learning(ICML 2017). + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/wideanddeep_criteo.md b/mshub_res/assets/mindspore/1.6/wideanddeep_criteo.md new file mode 100644 index 0000000..c23be41 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/wideanddeep_criteo.md @@ -0,0 +1,79 @@ +# wide_and_deep + +--- + +model-name: wide_and_deep + +backbone-name: wide_and_deep + +module-type: recommend + +fine-tunable: True + +model-version: 1.6 + +train-dataset: criteo + +evaluation: acc80.8 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d0522cdd4a01b8072d9500b5d4b28d2659dc5fb46d446664bad39413b2b8bff1 + +license: Apache2.0 + +summary: wide_and_deep is used for recommend + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of wide_and_deep from the MindSpore model zoo on Gitee at official/recommend/wide_and_deep. + +wide_and_deep is a recommend network. More details please refer to the MindSpore model zoo on Gitee at [official/recommend/wide_and_deep](https://gitee.com/mindspore/models/blob/r1.6/official/recommend/wide_and_deep/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/wideanddeep_criteo" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wide & Deep Learning for Recommender System + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/wideanddeep_dynamicshape_criteo.md b/mshub_res/assets/mindspore/1.6/wideanddeep_dynamicshape_criteo.md new file mode 100644 index 0000000..54bf281 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/wideanddeep_dynamicshape_criteo.md @@ -0,0 +1,79 @@ +# wide_and_deep + +--- + +model-name: wide_and_deep + +backbone-name: wide_and_deep + +module-type: recommend + +fine-tunable: True + +model-version: 1.6 + +train-dataset: criteo + +evaluation: acc78.88 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 98e97d16ca19a9871d4c5aa81acc4e38d033d7b54403d66d2f84d6b68cc07591 + +license: Apache2.0 + +summary: wide_and_deep is used for recommend + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of wide_and_deep from the MindSpore model zoo on Gitee at official/recommend/wide_and_deep. + +wide_and_deep is a recommend network. More details please refer to the MindSpore model zoo on Gitee at [official/recommend/wide_and_deep](https://gitee.com/mindspore/models/blob/r1.6/official/recommend/wide_and_deep/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/wideanddeep_dynamicshape_criteo" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wide & Deep Learning for Recommender System + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/wideanddeep_hostdevice_criteo.md b/mshub_res/assets/mindspore/1.6/wideanddeep_hostdevice_criteo.md new file mode 100644 index 0000000..43f4f89 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/wideanddeep_hostdevice_criteo.md @@ -0,0 +1,79 @@ +# wide_and_deep + +--- + +model-name: wide_and_deep + +backbone-name: wide_and_deep + +module-type: recommend + +fine-tunable: True + +model-version: 1.6 + +train-dataset: criteo + +evaluation: acc79.34 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 3155f6edc2168cd84c887a5a43eab90a358dcd48a649eef677dbc5377dc2cf11 + +license: Apache2.0 + +summary: wide_and_deep is used for recommend + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of wide_and_deep from the MindSpore model zoo on Gitee at official/recommend/wide_and_deep. + +wide_and_deep is a recommend network. More details please refer to the MindSpore model zoo on Gitee at [official/recommend/wide_and_deep](https://gitee.com/mindspore/models/blob/r1.6/official/recommend/wide_and_deep/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/wideanddeep_hostdevice_criteo" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wide & Deep Learning for Recommender System + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/wideanddeep_ps_criteo.md b/mshub_res/assets/mindspore/1.6/wideanddeep_ps_criteo.md new file mode 100644 index 0000000..9f58ca3 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/wideanddeep_ps_criteo.md @@ -0,0 +1,79 @@ +# wide_and_deep + +--- + +model-name: wide_and_deep + +backbone-name: wide_and_deep + +module-type: recommend + +fine-tunable: True + +model-version: 1.6 + +train-dataset: criteo + +evaluation: acc80.76 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 01a521846a22c35ff3bef3f53ef5cb4efdc8c4717e4ca5b2efd3c2d4c04663f6 + +license: Apache2.0 + +summary: wide_and_deep is used for recommend + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of wide_and_deep from the MindSpore model zoo on Gitee at official/recommend/wide_and_deep. + +wide_and_deep is a recommend network. More details please refer to the MindSpore model zoo on Gitee at [official/recommend/wide_and_deep](https://gitee.com/mindspore/models/blob/r1.6/official/recommend/wide_and_deep/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/wideanddeep_ps_criteo" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wide & Deep Learning for Recommender System + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/wideanddeepmultitable_outbrain.md b/mshub_res/assets/mindspore/1.6/wideanddeepmultitable_outbrain.md new file mode 100644 index 0000000..7ba848d --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/wideanddeepmultitable_outbrain.md @@ -0,0 +1,79 @@ +# wide_and_deep_multitable + +--- + +model-name: wide_and_deep_multitable + +backbone-name: wide_and_deep_multitable + +module-type: recommend + +fine-tunable: True + +model-version: 1.6 + +train-dataset: outbrain + +evaluation: acc80.97 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: dfbee3851427816f19ced062e7318c0080bafd5e68db4772c718047dceea0b10 + +license: Apache2.0 + +summary: wide_and_deep_multitable is used for recommend + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of wide_and_deep_multitable from the MindSpore model zoo on Gitee at official/recommend/wide_and_deep_multitable. + +wide_and_deep_multitable is a recommend network. More details please refer to the MindSpore model zoo on Gitee at [official/recommend/wide_and_deep_multitable](https://gitee.com/mindspore/models/blob/r1.6/official/recommend/wide_and_deep_multitable/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/wideanddeepmultitable_outbrain" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Wide & Deep Learning for Recommender System + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/wideresnet_cifar10.md b/mshub_res/assets/mindspore/1.6/wideresnet_cifar10.md new file mode 100644 index 0000000..0c43e2f --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/wideresnet_cifar10.md @@ -0,0 +1,62 @@ +# wideresnet + +--- + +model-name: wideresnet + +backbone-name: wideresnet + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: cifar10 + +evaluation: acc96.33 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 441c0aaa59b9e164be0666d5a318fc438532e7fd13730cfa0b6cb677a8217442 + +license: Apache2.0 + +summary: wideresnet is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of wideresnet from the MindSpore model zoo on Gitee at research/cv/wideresnet. + +wideresnet is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/wideresnet](https://gitee.com/mindspore/models/blob/r1.6/research/cv/wideresnet/README_CN.md). + +All parameters in the module are trainable. + +## Citation + +Sergey Zagoruyko."Wide Residual Netwoks" + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/xception_imagenet2012.md b/mshub_res/assets/mindspore/1.6/xception_imagenet2012.md new file mode 100644 index 0000000..3e37efa --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/xception_imagenet2012.md @@ -0,0 +1,79 @@ +# xception + +--- + +model-name: xception + +backbone-name: xception + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: imagenet2012 + +evaluation: top1acc79.94 | top5acc94.97 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 0359d9ffe399d2c359bf7cf488b56f559e665dc5968b61a00809c8a0a53fb26c + +license: Apache2.0 + +summary: xception is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of xception from the MindSpore model zoo on Gitee at official/cv/xception. + +xception is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/xception](https://gitee.com/mindspore/models/blob/r1.6/official/cv/xception/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/xception_imagenet2012" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Franois Chollet. Xception: Deep Learning with Depthwise Separable Convolutions. 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) IEEE, 2017. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/yolov3darknet53_coco2014.md b/mshub_res/assets/mindspore/1.6/yolov3darknet53_coco2014.md new file mode 100644 index 0000000..17f5cee --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/yolov3darknet53_coco2014.md @@ -0,0 +1,79 @@ +# yolov3_darknet53 + +--- + +model-name: yolov3_darknet53 + +backbone-name: yolov3_darknet53 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2014 + +evaluation: acc31.3 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: b85b72bff16a6cad1a71c768e48e500589f24715897d8b35ac743ae11faa07b3 + +license: Apache2.0 + +summary: yolov3_darknet53 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of yolov3_darknet53 from the MindSpore model zoo on Gitee at official/cv/yolov3_darknet53. + +yolov3_darknet53 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/yolov3_darknet53](https://gitee.com/mindspore/models/blob/r1.6/official/cv/yolov3_darknet53/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/yolov3darknet53_coco2014" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +YOLOv3: An Incremental Improvement.Joseph Redmon, Ali Farhadi, University of Washington + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/yolov3darknet53quant_coco2014.md b/mshub_res/assets/mindspore/1.6/yolov3darknet53quant_coco2014.md new file mode 100644 index 0000000..a63a700 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/yolov3darknet53quant_coco2014.md @@ -0,0 +1,79 @@ +# yolov3_darknet53_quant + +--- + +model-name: yolov3_darknet53_quant + +backbone-name: yolov3_darknet53_quant + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2014 + +evaluation: mAP31 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: d41609bc771288a2424a7b6bd6fa688abc345fbdc152ead669eda8ed3d783c9c + +license: Apache2.0 + +summary: yolov3_darknet53_quant is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of yolov3_darknet53_quant from the MindSpore model zoo on Gitee at official/cv/yolov3_darknet53_quant. + +yolov3_darknet53_quant is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/yolov3_darknet53_quant](https://gitee.com/mindspore/models/blob/r1.6/official/cv/yolov3_darknet53_quant/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/yolov3darknet53quant_coco2014" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +YOLOv3: An Incremental Improvement.Joseph Redmon, Ali Farhadi, University of Washington + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/yolov3resnet18_coco2017.md b/mshub_res/assets/mindspore/1.6/yolov3resnet18_coco2017.md new file mode 100644 index 0000000..9d863f4 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/yolov3resnet18_coco2017.md @@ -0,0 +1,79 @@ +# yolov3_resnet18 + +--- + +model-name: yolov3_resnet18 + +backbone-name: yolov3_resnet18 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: class0precision91.76 | class0recall66.27 | class1precision89.09 | class1recall76.93 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 42c46a3b9518282da79233d0b550c8d5d4c32e79c1ebe8facd155fe8f2e7e75b + +license: Apache2.0 + +summary: yolov3_resnet18 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of yolov3_resnet18 from the MindSpore model zoo on Gitee at official/cv/yolov3_resnet18. + +yolov3_resnet18 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/yolov3_resnet18](https://gitee.com/mindspore/models/blob/r1.6/official/cv/yolov3_resnet18/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/yolov3resnet18_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Joseph Redmon, Ali Farhadi. arXiv preprint arXiv:1804.02767, 2018. 2, 4, 7, 11. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/yolov3tiny_coco2017.md b/mshub_res/assets/mindspore/1.6/yolov3tiny_coco2017.md new file mode 100644 index 0000000..41bce75 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/yolov3tiny_coco2017.md @@ -0,0 +1,79 @@ +# yolov3_tiny + +--- + +model-name: yolov3_tiny + +backbone-name: yolov3_tiny + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: mAP17.7 | mAP50acc36 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: c4a5b747c28373bd2100abd732fca582c13ddf74d5dab5b5fd92fd9ce303c4a7 + +license: Apache2.0 + +summary: yolov3_tiny is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of yolov3_tiny from the MindSpore model zoo on Gitee at research/cv/yolov3_tiny. + +yolov3_tiny is a cv network. More details please refer to the MindSpore model zoo on Gitee at [research/cv/yolov3_tiny](https://gitee.com/mindspore/models/blob/r1.6/research/cv/yolov3_tiny/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/yolov3tiny_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Joseph Redmon, Ali Farhadi. arXiv preprint arXiv:1804.02767, 2018.2, 4, 7, 11. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/yolov4_coco2017.md b/mshub_res/assets/mindspore/1.6/yolov4_coco2017.md new file mode 100644 index 0000000..7d56447 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/yolov4_coco2017.md @@ -0,0 +1,79 @@ +# yolov4 + +--- + +model-name: yolov4 + +backbone-name: yolov4 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: acc44 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: e318152734c9bb89c2907f4d26bf0dff63241d7dffc52b2dc48c93353f13fde8 + +license: Apache2.0 + +summary: yolov4 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of yolov4 from the MindSpore model zoo on Gitee at official/cv/yolov4. + +yolov4 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/yolov4](https://gitee.com/mindspore/models/blob/r1.6/official/cv/yolov4/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/yolov4_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Bochkovskiy A, Wang C Y, Liao H Y M. YOLOv4: Optimal Speed and Accuracy of Object Detection[J]. arXiv preprint arXiv:2004.10934, 2020. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/yolov4shape416_coco2017.md b/mshub_res/assets/mindspore/1.6/yolov4shape416_coco2017.md new file mode 100644 index 0000000..72961e5 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/yolov4shape416_coco2017.md @@ -0,0 +1,79 @@ +# yolov4 + +--- + +model-name: yolov4 + +backbone-name: yolov4 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: acc39.3 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 86e0cbb81173d2634066a010ea2615482a45f1372da8d3397d5bb8c1e25a27f9 + +license: Apache2.0 + +summary: yolov4 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of yolov4 from the MindSpore model zoo on Gitee at official/cv/yolov4. + +yolov4 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/yolov4](https://gitee.com/mindspore/models/blob/r1.6/official/cv/yolov4/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/yolov4shape416_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Citation + +Bochkovskiy A, Wang C Y, Liao H Y M. YOLOv4: Optimal Speed and Accuracy of Object Detection[J]. arXiv preprint arXiv:2004.10934, 2020. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. diff --git a/mshub_res/assets/mindspore/1.6/yolov5shape640_coco2017.md b/mshub_res/assets/mindspore/1.6/yolov5shape640_coco2017.md new file mode 100644 index 0000000..ec2f1f2 --- /dev/null +++ b/mshub_res/assets/mindspore/1.6/yolov5shape640_coco2017.md @@ -0,0 +1,75 @@ +# yolov5 + +--- + +model-name: yolov5 + +backbone-name: yolov5 + +module-type: cv + +fine-tunable: True + +model-version: 1.6 + +train-dataset: coco2017 + +evaluation: acc36.6 + +author: MindSpore team + +update-time: 2022-03-30 + +repo-link: + +user-id: MindSpore + +used-for: inference + +mindspore-version: 1.6 + +asset: + +- + file-format: ckpt + asset-link: + asset-sha256: 9e17460882efdf587ee451fcc401d4359f0d1f31eb40825a59c339e65e1ca89b + +license: Apache2.0 + +summary: yolov5 is used for cv + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of yolov5 from the MindSpore model zoo on Gitee at official/cv/yolov5. + +yolov5 is a cv network. More details please refer to the MindSpore model zoo on Gitee at [official/cv/yolov5](https://gitee.com/mindspore/models/blob/r1.6/official/cv/yolov5/README.md). + +All parameters in the module are trainable. + +## Usage + +```python +import mindspore_hub as mshub +from mindspore import context + +context.set_context(mode=context.GRAPH_MODE, + device_target="Ascend", + device_id=0) + +model = "mindspore/1.6/yolov5shape640_coco2017" +network = mshub.load(model) +network.set_train(False) + +# ... +``` + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. -- Gitee