# DeepSIM **Repository Path**: zyabo/DeepSIM ## Basic Information - **Project Name**: DeepSIM - **Description**: No description available - **Primary Language**: Unknown - **License**: Not specified - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2020-12-28 - **Last Updated**: 2020-12-28 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # DeepSIM ### [Project](http://www.vision.huji.ac.il/deepsim) | [Paper](https://arxiv.org/abs/2007.01289)
Official PyTorch implementation of the paper: "Deep Single Image Manipulation". ## Results

### SuperPrimitive2Image

### Image2VideoFrames

## Getting Started ### Training - Train a model at 640 x 640 resolution (`bash ./scripts/train.sh`): ```bash #!./scripts/train.sh python3.7 train.py --dataroot ./datasets/face --name DeepSIM --niter 8000 --niter_decay 8000 --label_nc 0 --no_instance --tps_aug 1 --apply_binary_threshold 1 ``` - To view training results, please checkout intermediate results in `./checkpoints/DeepSIM/web/index.html`. ### Training with your own dataset - For binary training images (i.e. edge maps) use `--apply_binary_threshold 1`, to ensure that the edges input is indeed binary (during both training and inference), for segmentation maps use `--apply_binary_threshold 0`, you may also use `--edge_threshold` to control the threshold. - For TPS augmentations use `--tps_aug 1`, this will train the image with a new random TPS warp every epoch. - See `options/train_options.py` and `options/base_options.py` for all the training flags; see `options/test_options.py` and `options/base_options.py` for all the test flags. See pix2pixHD for further details. ### Testing - Test the model (`bash ./scripts/test.sh`): ```bash #!./scripts/test.sh python3.7 test.py --dataroot ./datasets/face --name DeepSIM --label_nc 0 --no_instance --apply_binary_threshold 1 --tps_aug 0 ``` The test results will be saved to a html file here: `./results/DeepSIM/test_latest/index.html`. More examples can be found in the `scripts` directory. ## Citation If you find this useful for your research, please use the following. ``` @misc{vinker2020deep, title={Deep Single Image Manipulation}, author={Yael Vinker and Eliahu Horwitz and Nir Zabari and Yedid Hoshen}, year={2020}, eprint={2007.01289}, archivePrefix={arXiv}, } ``` ## Acknowledgments This code borrows heavily from [pix2pixHD](https://github.com/NVIDIA/pix2pixHD).