GitLab

- Update table recognition logic to process each table individually
- Refactor layout detection to use tqdm for progress tracking
- Optimize OCR recognition by using a single tqdm wrapper
- Improve MFR prediction with a more accurate progress bar
- Simplify MFD prediction by removing unnecessary total calculation

- Add tqdm progress bar to batch prediction loops in multiple model modules
- Improve logging and error handling in batch analysis script
- Update table model initialization to use default sub-model if none specified
- Add tqdm dependency to requirements.txt

- Comment out LayoutLMv3, TableMaster, and StructEqTable models
- Update MFR model path to unimernet_hf_small_2503- Remove unused import in Unimernet.py

- 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 unnecessary __getitem__ method
- Simplify image cropping in detect_math_formula_region
- Improve code readability and efficiency

- 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

- Sort detected images by area before processing to enhance MFR accuracy
- Implement stable sorting to maintain original order of images with equal

refactor(magic_pdf): adjust VRAM allocation and MFR batch size- Update VRAM allocation logic to use 'VIRTUAL_VRAM_SIZE' environment variable
- Reduce MFR (Math Formula Recognition) batch size from 64 to 32