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| # Preparation | ||
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| ### Installation | ||
| **We highly recommand that you use Anaconda for Installation** | ||
| ``` | ||
| conda create -n simswap python=3.6 | ||
| conda activate simswap | ||
| conda install pytorch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0 cudatoolkit=10.2 -c pytorch | ||
| (option): pip install --ignore-installed imageio | ||
| pip install insightface==0.2.1 onnxruntime moviepy | ||
| ``` | ||
| - We use the face detection and alignment methods from **[insightface](https://github.com/deepinsight/insightface)** for image preprocessing. Please download the relative files and unzip them to ./insightface_func/models from [this link](https://onedrive.live.com/?authkey=%21ADJ0aAOSsc90neY&cid=4A83B6B633B029CC&id=4A83B6B633B029CC%215837&parId=4A83B6B633B029CC%215834&action=locate). | ||
| - The pytorch and cuda versions above are most recommanded. They may vary. | ||
| - Using insightface with different versions is not recommanded. Please use this specific version. | ||
| - These settings are tested valid on both Windows and Ununtu. | ||
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| ### Pretrained model | ||
| There are two archive files in the drive: **checkpoints.zip** and **arcface_checkpoint.tar** | ||
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| - **Copy the arcface_checkpoint.tar into ./arcface_model** | ||
| - **Unzip checkpoints.zip, place it in the root dir ./** | ||
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| [[Google Drive]](https://drive.google.com/drive/folders/1jV6_0FIMPC53FZ2HzZNJZGMe55bbu17R?usp=sharing) | ||
| [[Baidu Drive]](https://pan.baidu.com/s/1wFV11RVZMHqd-ky4YpLdcA) Password: ```jd2v``` | ||
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| ### Note | ||
| We expect users to have GPU with at least 8G memory. For those who do not, we will provide Colab Notebook implementation in the future. |
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| # Usage | ||
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| ### Simple face swapping for already face-aligned images | ||
| ``` | ||
| python test_one_image.py --isTrain false --name people --Arc_path arcface_model/arcface_checkpoint.tar --pic_a_path crop_224/6.jpg --pic_b_path crop_224/ds.jpg --output_path output/ | ||
| ``` | ||
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| ### Face swapping for video | ||
| - Swap only one face within the video(the one with highest confidence by face detection). | ||
| ``` | ||
| python test_video_swapsingle.py --isTrain false --name people --Arc_path arcface_model/arcface_checkpoint.tar --pic_a_path ./demo_file/Iron_man.jpg --video_path ./demo_file/mutil_people_1080p.mp4 --output_path ./output/mutil_test_swapsingle.mp4 --temp_path ./temp_results | ||
| ``` | ||
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| - Swap all faces within the video. | ||
| ``` | ||
| python test_video_swapmutil.py --isTrain false --name people --Arc_path arcface_model/arcface_checkpoint.tar --pic_a_path ./demo_file/Iron_man.jpg --video_path ./demo_file/mutil_people_1080p.mp4 --output_path ./output/mutil_test_swapmutil.mp4 --temp_path ./temp_results | ||
| ``` | ||
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| ### Face swapping for Arbitrary images | ||
| - Swap only one face within one image(the one with highest confidence by face detection). The result would be saved to ./output/result_whole_swapsingle.jpg | ||
| ``` | ||
| python test_wholeimage_swapsingle.py --isTrain false --name people --Arc_path arcface_model/arcface_checkpoint.tar --pic_a_path ./demo_file/Iron_man.jpg --pic_b_path ./demo_file/mutil_people.jpg --output_path ./output/ | ||
| ``` | ||
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| - Swap all faces within one image. The result would be saved to ./output/result_whole_swapmutil.jpg | ||
| ``` | ||
| python test_wholeimage_swapmutil.py --isTrain false --name people --Arc_path arcface_model/arcface_checkpoint.tar --pic_a_path ./demo_file/Iron_man.jpg --pic_b_path ./demo_file/mutil_people.jpg --output_path ./output/ | ||
| ``` | ||
| Difference between single face swapping and all face swapping are shown below. | ||
| <img src="../img/multi_face_comparison.png"/> | ||
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| ### Parameters | ||
| | Parameters | Function | | ||
| | :---- | :---- | | ||
| | --name | The SimSwap training logs name | | ||
| | --pic_a_path | Path of image with the target face | | ||
| | --pic_b_path | Path of image with the source face to swap | | ||
| | --video_path | Path of video with the source face to swap | | ||
| | --temp_path | Path to store intermediate files | | ||
| | --output_path | Path of directory to store the face swapping result | | ||
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| ### Note | ||
| We expect users to have GPU with at least 8G memory. For those who do not, we will provide Colab Notebook implementation in the future. |
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