# anygrasp_sdk

**Repository Path**: Yang_jinping/anygrasp_sdk

## Basic Information

- **Project Name**: anygrasp_sdk
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-02-28
- **Last Updated**: 2024-02-28

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

<img src="https://user-images.githubusercontent.com/12446953/208367719-4ef7922f-4001-41f7-aa9f-076e462d1325.png" width="60%">

# AnyGrasp SDK
AnyGrasp SDK for grasp detection & tracking.

[[arXiv](https://arxiv.org/abs/2212.08333)]
[[project](https://graspnet.net/anygrasp.html)]
[[dataset](https://graspnet.net/datasets.html)]
[[graspnetAPI](https://github.com/graspnet/graspnetAPI)]

## Update
* **October 8, 2023** Fix a bug in grasp detection inference code, which may cause partial grasp widths exceeding the constrained range.
* **July 20, 2023** Fix a bug in grasp detection inference code, which may cause no prediction when there are only one or two objects.

## Video
[![IMAGE ALT TEXT](https://graspnet.net/images/broken.gif)](https://www.youtube.com/watch?v=s0SUw1vgtr8 "AnyGrasp Demo: Cleaning fragments of a broken pot")
<br>
**AnyGrasp cleaning fragments of a broken pot**


[![IMAGE ALT TEXT](https://user-images.githubusercontent.com/12446953/222949407-01a040d1-0723-4026-ae5a-08631116dde4.gif)](https://www.youtube.com/watch?v=2KM3Lq5VaS4 "AnyGrasp Fish Catching Spotlight")
<br>
**AnyGrasp catching swimming robot fish**

## Requirements
- Python 3.6/3.7/3.8/3.9
- PyTorch 1.7.1 with CUDA 11.0
- [MinkowskiEngine](https://github.com/NVIDIA/MinkowskiEngine) v0.5.4


## Installation
1. Follow MinkowskiEngine [instructions](https://github.com/NVIDIA/MinkowskiEngine#anaconda) to install [Anaconda](https://www.anaconda.com/), cudatoolkit, Pytorch and MinkowskiEngine. **Note that you need ``export MAX_JOBS=2;`` before ``pip install`` if you are running on an laptop due to [this issue](https://github.com/NVIDIA/MinkowskiEngine/issues/228)**. If PyTorch reports a compatibility issue during program execution, you can re-install PyTorch via Pip instead of Anaconda.

2. Install other requirements from Pip.
```bash
    pip install -r requirements.txt
```

3. Install ``pointnet2`` module.
```bash
    cd pointnet2
    python setup.py install
```

## License Registration
   
Due to the IP issue, currently we can only release the SDK library file of AnyGrasp in a licensed manner. Please get the feature id of your machine and fill in the [form](https://forms.gle/XVV3Eip8njTYJEBo6) to apply for the license. See [license_registration/README.md](license_registration/README.md) for details. **If you are interested in code implementation, you can refer to our [baseline version of network](https://github.com/graspnet/graspnet-baseline), or a third-party implementation of our [GSNet](https://github.com/graspnet/graspness_unofficial).**


## Demo Code
Now you can run your code that uses AnyGrasp SDK. See [grasp_detection](grasp_detection) and [grasp_tracking](grasp_tracking) for details.


## Citation
Please cite these papers in your publications if it helps your research:

    @article{fang2023anygrasp,
      title={AnyGrasp: Robust and Efficient Grasp Perception in Spatial and Temporal Domains},
      author = {Fang, Hao-Shu and Wang, Chenxi and Fang, Hongjie and Gou, Minghao and Liu, Jirong and Yan, Hengxu and Liu, Wenhai and Xie, Yichen and Lu, Cewu},
      journal={IEEE Transactions on Robotics (T-RO)},
      year={2023}
    }
    
    @inproceedings{fang2020graspnet,
      title={Graspnet-1billion: A large-scale benchmark for general object grasping},
      author={Fang, Hao-Shu and Wang, Chenxi and Gou, Minghao and Lu, Cewu},
      booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
      pages={11444--11453},
      year={2020}
    }

    @inproceedings{wang2021graspness,
      title={Graspness discovery in clutters for fast and accurate grasp detection},
      author={Wang, Chenxi and Fang, Hao-Shu and Gou, Minghao and Fang, Hongjie and Gao, Jin and Lu, Cewu},
      booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
      pages={15964--15973},
      year={2021}
    }