README.md

metadata

title: Kraken OCR on Samaritan Manuscripts
emoji: 📜
colorFrom: blue
colorTo: indigo
sdk: gradio
sdk_version: 5.33.0
app_file: app.py
pinned: false

Kraken OCR on Samaritan Manuscripts - Gradio App

This is a Gradio web application for OCR on Samaritan Manuscripts.

Setup

1. Install requirements:

pip install -r requirements.txt

2. Place your models:
   • Put segmentation models (.mlmodel files) in app/models/seg/
   • Put recognition models (.mlmodel files) in app/models/rec/

Running the App

python app.py

Usage

1. Select segmentation and recognition models from the dropdown menus
2. Upload an image file (supported formats: PNG, JPG, JPEG, TIF, TIFF)
3. Click "Process Image" to run OCR
4. View the results and download the XML output

Features

• Dynamic model selection
• Image preview
• XML output display
• Download processed results
• Error handling and progress indicators

Hugging Face Space Configuration

To run this app on Hugging Face Spaces, you need to:

1. Create a new Space with Gradio SDK

2. Add the following files to your Space:

   • app.py
   • requirements.txt
   • models/ directory with your models
   • templates/ directory with your templates

3. Make sure your requirements.txt includes:

gradio>=4.0.0
kraken
Pillow
numpy
opencv-python
jinja2

4. The Space should be configured with:

   • Python 3.10 runtime
   • GPU if available
   • At least 8GB RAM

5. Your Space's app.py should be in the root directory, not in an app/ subdirectory

6. Update the model paths in app.py to use relative paths:

MODELS_DIR = Path("models")
SEG_MODELS_DIR = MODELS_DIR / "seg"
REC_MODELS_DIR = MODELS_DIR / "rec"

7. Make sure all model files are included in your Space's repository

Troubleshooting

If you encounter issues on Hugging Face Spaces:

1. Check the Space logs for errors
2. Verify all model files are present
3. Ensure all dependencies are in requirements.txt
4. Check file permissions and paths
5. Make sure the app is running on the correct port (7860)