Spaces:
Sleeping
Sleeping
File size: 3,365 Bytes
a479aa5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 | # 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)
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