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| title: My OCR Demo | |
| emoji: 📸 | |
| colorFrom: blue | |
| colorTo: green | |
| sdk: gradio | |
| sdk_version: "4.20.0" # Check your requirements.txt for the exact Gradio version you are using | |
| app_file: app.py | |
| pinned: false | |
| # Add this line if your paddleocr_models directory is large and you want to ensure LFS is used for it. | |
| # It's good practice even if individual files inside are already LFS tracked. | |
| # You might need to adjust if your models are not LFS tracked at the folder level. | |
| # For now, since individual model files are LFS tracked, this might not be strictly necessary | |
| # but can be a good general practice for model directories. | |
| # hf_storage_lfs: | |
| # - "paddleocr_models/**" | |
| # My PaddleOCR Demo Application | |
| This is a web application that uses PaddleOCR to perform Optical Character Recognition (OCR) on uploaded images. | |
| It's built with Gradio and deployed on Hugging Face Spaces. | |
| The application uses bundled PaddleOCR models for English, managed with Git LFS to ensure fast startup and avoid re-downloads. | |
| ## How to Use | |
| 1. Upload an image using the interface. | |
| 2. The extracted text and the image with bounding boxes will be displayed. |