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| # π Hugging Face Deployment Checklist | |
| ## β All Files Ready for Deployment | |
| ### π **Core Application Files:** | |
| - β `app.py` - Main Gradio application (YOLO-based detection) | |
| - β `requirements.txt` - All dependencies for Gradio | |
| - β `README.md` - Documentation | |
| - β `DEPLOYMENT_GUIDE.md` - Deployment instructions | |
| ### π€ **AI Models (All Present):** | |
| - β `models/yolo11s.pt` - Vehicle detection (11MB) | |
| - β `models/detect1.pt` - License plate detection (6MB) | |
| - β `models/read_char.pt` - Character reading (6MB) | |
| - β `models/best_province.pt` - Province detection (6MB) | |
| - β `models/best_segment.pt` - Segmentation (backup) (6MB) | |
| ### βοΈ **Configuration Files:** | |
| - β `config/data.yaml` - Character mappings (47 Thai chars + digits) | |
| - β `config/data_province.yaml` - Province mappings (77 Thai provinces) | |
| ### π **Model Verification:** | |
| - β **Character Recognition**: Maps "ΰΈΰΈ 1687" correctly | |
| - β **Province Recognition**: Maps class "58" β "ΰΈͺΰΈΰΈΰΈ₯ΰΈ²" | |
| - β **Detection Pipeline**: Matches original API exactly | |
| - β **Confidence Thresholds**: All set to 0.3 | |
| ## ποΈ **Deployment Instructions:** | |
| ### **Step 1: Create Hugging Face Space** | |
| 1. Go to [Hugging Face Spaces](https://huggingface.co/spaces) | |
| 2. Click "Create new Space" | |
| 3. Choose: | |
| - **SDK**: Gradio | |
| - **Python Version**: 3.11 | |
| - **Hardware**: CPU Basic (free tier) | |
| ### **Step 2: Upload Files** | |
| Upload ALL files from this `deploy_huggingface/` folder: | |
| ``` | |
| deploy_huggingface/ | |
| βββ app.py # Main app | |
| βββ requirements.txt # Dependencies | |
| βββ README.md # Documentation | |
| βββ models/ # All 5 model files | |
| βββ config/ # 2 YAML config files | |
| βββ *.md files # Documentation | |
| ``` | |
| ### **Step 3: Automatic Deployment** | |
| - Hugging Face will automatically: | |
| - Install dependencies from `requirements.txt` | |
| - Run `app.py` with Gradio | |
| - Provide public URL for testing | |
| ### **Step 4: Verify Deployment** | |
| Test with the license plate image: | |
| - β Should detect vehicles in protection zone | |
| - β Should find license plates in vehicles | |
| - β Should read "ΰΈΰΈ1687" (not "2ΰΈΰΉΰΈ«ΰΈ₯ΰΈ") | |
| - β Should show province "ΰΈͺΰΈΰΈΰΈ₯ΰΈ²" (not "Unknown") | |
| ## π **File Sizes (Total: ~45MB)** | |
| ``` | |
| app.py - 15KB | |
| requirements.txt - 1KB | |
| config/ - 5KB | |
| models/yolo11s.pt - 11MB | |
| models/detect1.pt - 6MB | |
| models/read_char.pt - 6MB | |
| models/best_province.pt - 6MB | |
| models/best_segment.pt - 6MB | |
| Documentation - 50KB | |
| ``` | |
| ## π― **Expected Performance:** | |
| - **Vehicle Detection**: β Working | |
| - **License Plate Detection**: β Working | |
| - **Character Reading**: β Fixed (correct Thai characters) | |
| - **Province Recognition**: β Fixed (77 provinces mapped) | |
| - **UI**: β Interactive Gradio interface | |
| - **Speed**: ~2-5 seconds per image (CPU) | |
| ## π¨ **Pre-Deployment Test:** | |
| Run locally first: | |
| ```bash | |
| cd deploy_huggingface | |
| python app.py | |
| ``` | |
| - Should start on http://localhost:7860 | |
| - Test with vehicle images | |
| - Verify license plate reading accuracy | |
| ## β **Ready for Production!** | |
| All files are present and tested. The app now matches the working API's detection accuracy exactly. | |
| **License plate "ΰΈΰΈ 1687 ΰΈͺΰΈΰΈΰΈ₯ΰΈ²" will be correctly detected! πβ¨** |