GitLab

- Add support for Apple M1 chips (mps device)
- Refactor image processing for better performance and compatibility
- Update model loading and inference for various devices
- Adjust batch processing and memory management

- Remove unused @ImportPIL decorator from load_images_from_pdf function
- Update image shape handling in YOLOv11.py for better compatibility

These changes improve code readability and performance without altering the original functionality.

- Replace PIL with cv2 for image processing
- Fix issues with image cropping and resizing
- Add boundary checks and error handling
- Optimize code for better performance and readability

- Remove PIL usage across multiple files
- Convert image processing functions to use NumPy arrays
- Update crop_img function to work with NumPy arrays
- Modify image loading and resizing to use NumPy and OpenCV
- Clean up unused imports and comments related to PIL

- Increase batch size from 8 to 256 for language detection inference
- Add timing measurement for language detection process

- Remove YOLO v11 language detection model from model_configs.yaml
- Update language detection utils to use a fixed model path instead of dynamic configuration
- Remove unused model weight parameter for YOLO v11 language detection

- Remove LangDetectMode and related conditional logic
- Use a single model weight for language detection
- Add logging for language detection results
- Update model initialization and prediction methods

- Add language detection model initialization and integration
- Update model list to include language detection
- Refactor language detection utils for better model management

- Add separate models for Chinese/Japanese and English/French/German detection
- Implement mode-based detection to use appropriate models for different languages
- Update language detection process to use higher DPI for better accuracy
- Modify model initialization and prediction logic to support new language-specific models

- Add YOLOv11 language detection model for PDF documents
- Implement language detection in PymuDocDataset
- Update app.py to include 'auto' language option
- Create language detection utilities and constants