This project provides an OCR (Optical Character Recognition) solution for detecting and recognizing Book titles from Images of Arabic Books. It utilizes YOLOv5 for text detection and EasyOCR for text recognition. The application is containerized using Docker and exposes API endpoints via Flask.
- YOLOv5: Transfer Learning for 40 epochs for text detection on the Books dataset from arabic-documents-ocr-dataset-kaggle.
- EasyOCR: For text recognition only.
- Flask: Python micro web framework for API endpoints.
- Docker: Containerization technology for easy deployment.
Title Object Detection achieves 66 mAp.
To run the Book Title OCR application, Docker must be installed on your system.
git clone https://github.com/your-repo/book-ocr-docker.git
cd book-ocr-docker
docker build -t book-ocr-docker .
Run the Docker Container
docker run -p 5000:5000 book-ocr-docker
The application will be accessible at http://127.0.0.1:5000/.
The following API endpoints are available:
URL: http://127.0.0.1:5000/predict Method: [POST] Description: Upload an image containing Arabic Book for OCR processing.
form-data Key: image in format {.png, .jpg, .jpeg} Value: Select your image file to upload.
Returns Title string in arabic.
- YOLOv5: ultralytics/yolov5
- EasyOCR: JaidedAI/EasyOCR
- Dataset: humansintheloop/arabic-documents-ocr-dataset-kaggle