{"id":21599286,"url":"https://github.com/t04glovern/icface","last_synced_at":"2025-06-30T09:34:33.265Z","repository":{"id":102175443,"uuid":"181201303","full_name":"t04glovern/icface","owner":"t04glovern","description":"Repository cleanup of https://github.com/Blade6570/icface while I play around with 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ICface\n\nRepository cleanup of [Blade6570/icface](https://github.com/Blade6570/icface) while I play around with it.\n\n## Setup\n\nThe general requirements are as follows:\n\n- Python 3.7\n- Pytorch 0.4.1.post2\n- Visdom and dominate\n- Natsort\n\n### Pretrained Model\n\nThe following command uses `aws s3` to pull the pretrained model to `src/checkpoints/gpubatch_resnet/`\n\n```bash\n./data_get.sh get\n```\n\n### Conda\n\nI've ported all this into a nice little conda environment for you to use\n\n```bash\nconda env create -f environment.yml\nconda env create -f environment-dlib.yml\ncd src\n```\n\n## Generate Image\n\n```bash\n# Activate dlib conda\nconda activate icface-dlib\n\n# Generate ./crop/1.png\npython image_crop.py \\\n  --image ./crop/test/trump.jpeg \\\n  --id 1\n```\n\n## Generate Video\n\n```bash\n# Activate icface conda\nconda activate icface\n\n# Generate a sample video\npython test.py \\\n  --dataroot ./ \\\n  --model pix2pix \\\n  --which_model_netG resnet_6blocks \\\n  --which_direction AtoB \\\n  --dataset_mode aligned \\\n  --norm batch \\\n  --display_id 0 \\\n  --batchSize 1 \\\n  --loadSize 128 \\\n  --fineSize 128 \\\n  --no_flip \\\n  --name gpubatch_resnet \\\n  --how_many 1 \\\n  --ndf 256 \\\n  --ngf 128 \\\n  --which_ref ./crop/\u003cvideo-id\u003e.png \\\n  --gpu_ids 0 \\\n  --csv_path ./crop/videos/\u003cinput-video\u003e.csv \\\n  --results_dir results_video\n\n# Splice the audio\nffmpeg -i ./crop/out.mp4 -i ./crop/videos/\u003cinput-video\u003e.mp4 -c copy -map 0:0 -map 1:1 -shortest ./crop/out_audio.mp4\n```\n\n## Generating Action Points\n\n```bash\n# Outside Container\ndocker run -it --rm algebr/openface:latest\n\n# Outside Container (new terminal window)\ndocker cp src/crop/videos/\u003cvideo-id\u003e.mp4 \u003cdocker-container\u003e:/home/openface-build\n\n# Within container (/home/openface-build)\n./build/bin/FeatureExtraction -f \u003cvideo-id\u003e.mp4\n\n# Outside Container\ndocker cp \u003cdocker-container\u003e:/home/openface-build/processed/\u003cvideo-id\u003e.csv src/crop/videos\n```\n\n## Attribution\n\n- [https://github.com/Blade6570/icface](https://github.com/Blade6570/icface)\n\n```bash\n@article{tripathy+kannala+rahtu,\n  title={ICface: Interpretable and Controllable Face Reenactment Using GANs},\n  author={Tripathy, Soumya and Kannala, Juho and Rahtu, Esa},\n  journal={arXiv preprint arXiv:1904.01909},\n  year={2019}\n}\n```\n\n- [https://github.com/TadasBaltrusaitis/OpenFace](https://github.com/TadasBaltrusaitis/OpenFace)\n  - [Command line arguments](https://github.com/TadasBaltrusaitis/OpenFace/wiki/Command-line-arguments)\n  - [Docker setup](https://github.com/TadasBaltrusaitis/OpenFace/wiki#quickstart-usage-of-openface-with-docker-thanks-edgar-aroutiounian)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ft04glovern%2Ficface","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ft04glovern%2Ficface","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ft04glovern%2Ficface/lists"}