https://github.com/prithivsakthiur/video-face-swapper

Model trained for educational purposes only; usage subject to terms and conditions. 📟
https://github.com/prithivsakthiur/video-face-swapper

deepfakes face model roop swap

Last synced: about 1 month ago
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Model trained for educational purposes only; usage subject to terms and conditions. 📟

• Host: GitHub
• URL: https://github.com/prithivsakthiur/video-face-swapper
• Owner: PRITHIVSAKTHIUR
• Created: 2024-05-17T15:41:24.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-05-17T18:36:52.000Z (about 1 year ago)
• Last Synced: 2025-03-31T03:11:53.534Z (3 months ago)
• Topics: deepfakes, face, model, roop, swap
• Language: Python
• Homepage: https://huggingface.co/spaces/prithivMLmods/Video-Face-Swapper
• Size: 10.5 MB
• Stars: 7
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
---

title: Video Face Swapper

emoji: 🙄😯

colorFrom: indigo

colorTo: green

sdk: gradio

sdk_version: 4.27.0

app_file: app.py

pinned: true

license: creativeml-openrail-m

---

🚀Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

🚀Huggingface Spaces : https://huggingface.co/spaces/prithivMLmods/Video-Face-Swapper

🚀Docs for Space : 

    # Make sure you have git-lfs installed (https://git-lfs.com)

    git lfs install

    

    git clone https://huggingface.co/spaces/prithivMLmods/Video-Face-Swapper

    

    # If you want to clone without large files - just their pointers

    

    GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/spaces/prithivMLmods/Video-Face-Swapper

## 🖼️🖼️Source Image and Target Video as inputs : 

![row01](assets/roop1.png)

## 🔃🔃Processing Input Sources : 

![row01](assets/roopee.png)

## 🏵️🏵️Starts Enhancing the Model Sources

![row01](assets/roop0.png)

## 📤The Final Outcome :

![row01](assets/roopy.gif)

## 📟PyPI Requirements.txt

        --extra-index-url https://download.pytorch.org/whl/cu118

        

        numpy==1.23.5

        opencv-python==4.7.0.72

        onnx==1.14.0

        insightface==0.7.3

        psutil==5.9.5

        tk==0.1.0

        customtkinter==5.1.3

        pillow==9.5.0

        torch==2.0.1+cu118; sys_platform != 'darwin'

        torch==2.0.1; sys_platform == 'darwin'

        torchvision==0.15.2+cu118; sys_platform != 'darwin'

        torchvision==0.15.2; sys_platform == 'darwin'

        onnxruntime==1.15.0; sys_platform == 'darwin' and platform_machine != 'arm64'

        onnxruntime-silicon==1.13.1; sys_platform == 'darwin' and platform_machine == 'arm64'

        onnxruntime-gpu==1.15.0; sys_platform != 'darwin'

        tensorflow==2.13.0rc1; sys_platform == 'darwin'

        tensorflow==2.12.0; sys_platform != 'darwin'

        opennsfw2==0.10.2

        protobuf==4.23.2

        tqdm==4.65.0

        gfpgan==1.3.8

        gradio==3.40.1

        tkinterdnd2==0.3.0; sys_platform != 'darwin' and platform_machine != 'arm64'

        tkinterdnd2-universal==1.7.3; sys_platform == 'darwin' and platform_machine == 'arm64'

        onnxruntime-coreml==1.13.1; python_version == '3.9' and sys_platform == 'darwin' and platform_machine != 'arm64'

## ⚠️⚠️⚠️ Guidelines :

    When using a video face swapper deepfake tool, it's crucial to adhere to both technical and ethical standards to avoid misuse. First, ensure your system meets the software requirements, and carefully follow installation instructions. Use high-quality video and face images, maintaining consistent lighting and angles for best results. Load your media into the tool, align and adjust settings, and preview the swap before rendering. Refine the output using editing tools to correct artifacts and enhance quality. Export the final video in the appropriate format.

    

    Ethically, always obtain explicit consent from individuals whose faces you use. Never create deceptive or misleading content, and avoid using the tool for malicious purposes like defamation or harassment. Comply with local laws and clearly label deepfake content to avoid confusion. Be respectful and sensitive, refraining from making offensive or harmful content. Use deepfake technology positively for education, entertainment, and art, and regularly review your projects to ensure they meet ethical standards. Stay informed about the latest advancements and engage with the community to learn and share best practices, ensuring your use of deepfake technology is responsible and respectful.

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