GitLab

- Simplify aspect ratio calculation using direct coordinate subtraction
- Remove unnecessary list append operation
- Improve code readability and performance in table rotation detection

- Implement table orientation detection to identify if a table is in portrait mode
- Add rotation logic to turn portrait tables 90 degrees clockwise before OCR
- Update OCR processing to work with potentially rotated images
- Improve text box analysis to determine if a table is rotated

- Import os and pathlib modules to handle file paths
- Define the path to the slanet-plus model
- Update RapidTableInput initialization to include the model path

- 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

- Remove OCR utils, modified PaddleOCR, and StructEqTable model
- Delete related import statements and model definitions
- Update dependencies in setup.py to remove paddlepaddle and related OCR packages

- Comment out print statements in base_ocr_v20.py and pytorch_paddle.py
- Update table model initialization to use lang parameter instead of ocr_engine
- Remove unused RapidOCR initialization in rapid_table.py

- Import get_device function from magic_pdf.libs.config_reader- Update RapidTableModel initialization to include device parameter for Unitable model

- Update RapidTable dependency to version 1.0.3
- Add support for sub-models in RapidTable
- Update magic-pdf configuration to include table sub-model
- Modify table model initialization to support sub-models
- Update table prediction logic to handle new output format

- Remove conditional logic for OCR engine selection
- Always use RapidOCR as the OCR engine
- Simplify the __init__ method by removing unused code

- Add check for empty OCR result when using PaddleOCR model
- Assign None to ocr_result if no text is detected, preventing further errors

- Implement ONNXModelSingleton to manage ONNX models
- Modify ModifiedPaddleOCR to use ONNX models on ARM CPUs without CUDA
- Update RapidTableModel to use RapidOCR with ONNXRuntime on CPU
- Add rapidocr_onnxruntime dependency in setup.py

- Update clean_memory function to support both CUDA and NPU devices
- Implement get_device function to centralize device selection logic
- Modify model initialization and memory cleaning to use the selected device
- Update RapidTableModel to support both RapidOCR and PaddleOCR engines

- Add NPU support for memory cleaning and model initialization
- Optimize table model initialization and prediction process
- Update memory utils to support NPU
- Add language parameter for table model

- Change import paths from paddleocr.ppocr to ppocr for utility functions
- Update import paths for logging and utility modules in ppocr_273_mod.py- Modify import paths for tablemaster_paddle.py to use ppstructure instead of paddleocr.ppstructure

- Change import path for TableSystem from 'ppstructure.table.predict_table' to 'paddleocr.ppstructure.table.predict_table'
- Change import path for init_args from 'ppstructure.utility' to 'paddleocr.ppstructure.utility'

- Add a null check for OCR result in the predict method
- Return None values if OCR result is None to prevent further processing