Spaces:
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Sleeping
| # Hugging Face Spaces Deployment Guide | |
| ## Prerequisites | |
| 1. A Hugging Face account | |
| 2. Git LFS installed locally: `git lfs install` | |
| 3. Model weights downloaded to the correct directories | |
| ## Deployment Steps | |
| ### 1. Prepare Model Weights | |
| You have two options: | |
| #### Option A: Upload weights via Git LFS (Recommended for public spaces) | |
| ```bash | |
| # Initialize Git LFS | |
| git lfs install | |
| # Track large files | |
| git lfs track "*.pt" | |
| git lfs track "*.pth" | |
| git lfs track "*.pkl" | |
| # Add weights | |
| git add .gitattributes | |
| git add detectors/*/checkpoint/pretrained/weights/best.pt | |
| git add detectors/P2G/src/utils/classes.pkl | |
| git commit -m "Add model weights" | |
| ``` | |
| #### Option B: Configure automatic download | |
| 1. Upload your model weights to Google Drive or another host | |
| 2. Update `download_weights.py` with the correct URLs | |
| 3. Weights will download automatically when the Space starts | |
| ### 2. Create Hugging Face Space | |
| 1. Go to https://huggingface.co/spaces | |
| 2. Click "Create new Space" | |
| 3. Choose: | |
| - **Name**: deepfake-detection-library (or your preferred name) | |
| - ** SDK**: Gradio | |
| - **License**: MIT | |
| - **Hardware**: CPU Basic (free) or upgrade to GPU if needed | |
| ### 3. Push to Hugging Face | |
| ```bash | |
| # Add HF remote (replace YOUR_USERNAME and SPACE_NAME) | |
| git remote add hf https://huggingface.co/spaces/YOUR_USERNAME/SPACE_NAME | |
| # Rename README for HF | |
| mv README.md README_github.md | |
| mv README_HF.md README.md | |
| # Push to Hugging Face | |
| git add . | |
| git commit -m "Initial commit for HF Spaces" | |
| git push hf main | |
| ``` | |
| ### 4. Configure Space | |
| In your Space settings on Hugging Face: | |
| - **Hardware**: Start with CPU Basic (free), upgrade to GPU if needed | |
| - **Secrets**: Add any API keys if needed (none required currently) | |
| - **Variables**: No special environment variables needed | |
| ### 5. Verify Deployment | |
| 1. Wait for the Space to build (may take 5-10 minutes) | |
| 2. Test each detector with sample images | |
| 3. Check logs for any errors | |
| ## File Size Considerations | |
| - **Git LFS** is required for files >10MB | |
| - Each model weight file (~100-500MB) will be stored via LFS | |
| - Free HF Spaces have storage limits; consider: | |
| - Upgrading to Pro for more storage | |
| - Using automatic download instead of uploading weights | |
| ## Troubleshooting | |
| ### Space fails to build | |
| - Check `requirements.txt` for incompatible versions | |
| - Review build logs in the Space interface | |
| - Ensure all dependencies are listed | |
| ### Weights not loading | |
| - Verify Git LFS tracked the files: `git lfs ls-files` | |
| - Check file sizes: LFS pointer files are ~130 bytes | |
| - Update `download_weights.py` if using automatic download | |
| ### Out of memory errors | |
| - Upgrade to GPU hardware (T4 small recommended) | |
| - Reduce batch size or model size if possible | |
| - Use CPU inference for deployment (already configured) | |
| ## Cost Optimization | |
| - **CPU Basic** (free): Works but slower | |
| - **CPU Upgrade** ($0.03/hour): Faster inference | |
| - **T4 Small GPU** ($0.60/hour): Needed for real-time performance | |
| ## Maintenance | |
| - Monitor Space usage in HF dashboard | |
| - Update models by pushing new weights via Git LFS | |
| - Check Gradio version compatibility: `pip list | grep gradio` | |
| ## Support | |
| For issues specific to this deployment, check: | |
| - [Gradio Documentation](https://gradio.app/docs/) | |
| - [HF Spaces Documentation](https://huggingface.co/docs/hub/spaces) | |
| - [GitHub Repository](https://github.com/truebees-ai/Image-Deepfake-Detectors-Public-Library) | |