GitLab

- Update batch processing logic for improved efficiency
- Refactor image analysis and inference methods
- Optimize dataset handling and image retrieval
- Improve error handling and logging in batch processes

- Comment out the line that updates det_count in batch_analyze.py
- Add a new OCR model configuration for Chinese (ch_lite) in models_config.yml- Update the Chinese OCR model configuration to use a different recognition model

- Change `bits` to `self._data_bits` for language detection
- This fixes the TypeError when opening PDF files

- 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

- Update predict_rec.py to check for NaN values in recognition results
- Replace NaN scores with 0.0 to ensure stability and consistency

- Add functions to calculate IoU, check if tables are inside each other, and merge tables
- Implement table merging for high IoU tables
- Add filtering to remove nested tables that don't overlap but cover a large area
- Update table_res_list and layout_res to reflect these changes

- Update OCR score formatting in batch_analyze.py and pdf_parse_union_core_v2.py
- Change score rounding method to preserve three decimal places
- Enhance accuracy representation without significantly altering the score value

- 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

- Refactor VRAM detection logic for better readability and efficiency
- Add fallback mechanism for unknown VRAM sizes
- Improve device checking in get_vram function

- 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

- Comment out OCR timing measurement code to improve readability and performance
- Remove unnecessary logging of OCR processing time

- Remove unused imports and comments
- Increase MIN_BATCH_INFERENCE_SIZE from 100 to 200
- Comment out VRAM cleaning and logging in batch_analyze.py
- Simplify code in doc_analyze_by_custom_model.py- Add tqdm progress bar in pdf_parse_union_core_v2.py
- Enable tqdm in OCR processing

- 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

- Replace ch_PP-OCRv4_det_infer.pth with ch_PP-OCRv3_det_infer.pth in models_config.yml
- Add new ch_PP-OCRv3_det_infer model configuration in arch_config.yaml

- Remove unnecessary GPU checks and cuda() calls
- Consolidate tensor device placement using .to(self.device)
- Add warning suppression for cleaner output
- Refactor conditional logic for better readability

- Remove unnecessary imports and code in batch_demo.py
- Update demo.py to use relative paths and improve code structure
- Adjust output directory structure in both scripts
- Remove redundant code and simplify functions

- Update PyMuPDF to version <1.25.0
- Update pydantic to version <2.11
- Update transformers to version < 5.0.0
- Remove always_apply parameter from alb.ToGray in image processing

- Update the default configuration path in pytorchocr_utility.py
- Add required dependencies for paddleocr2pytorch in setup.py:
  - shapely
  - pyclipper
  - omegaconf

- Remove unused UniMERNet and LayoutLMv3 model configurations
- Update OCR model path and dictionary path for PaddleOCR
- Modify README to update system requirements and installation instructions
- Update setup.py to include new package data

- Remove unused imports for concurrent.futures, multiprocessing, and paddle
- Delete commented-out code
- Update numpy dependency to remove upper version limit
- Remove InferenceResult import that was commented out

- Add newline at the beginning of arabic_dict.txt
- Change mode of multiple dictionary files

- 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

- Comment out OCR model initialization and execution for low-contrast spans
- Add batch OCR processing for collected image spans
- Adjust contrast threshold for OCR processing
- Remove unnecessary OCR processing for high-contrast spans
- Implement more efficient OCR workflow by processing multiple spans at once

- Enhance the logging of execution times by adding more detailed function identification
- Implement class name and module name inclusion for better traceability

- Remove unused OCR dictionaries for Arabic, Belarusian, Bulgarian and Armenian languages
- Update model configurations in arch_config.yaml:
- Comment out 'out_channels' for various language models
  - Rename Arabic, Korean, Japanese, Tamil and Devanagari model configurations to use 'v3' instead of 'v4'
- Delete ar_dict.txt, be_dict.txt and bg_dict.txt files
- Update arabic_dict.txt to remove blank line at the start

- Remove unused imports and code
- Simplify model architecture by removing unnecessary components
- Update initialization and forward pass logic
- Rename variables for consistency

- Added warnings module to import list
- Implemented a warning catcher to ignore FutureWarning from the transformers module
- This change prevents unnecessary warning messages during model inference

- Replace direct OCR model access with AtomModelSingleton for better model management
- Round OCR scores to 2 decimal places for consistency
- Improve error handling and logging in batch analysis
- Simplify OCR result processing in pdf_parse_union_core_v2.py

- Add support for multiple languages in OCR processing
- Create separate lists for each language to improve processing efficiency
- Update OCR model initialization to use PytorchPaddleOCR instead of ModifiedPaddleOCR
- Modify get_ocr_result_list function to include language information- Improve logging for OCR detection and recognition

- Split OCR process into detection and recognition stages
- Update batch analysis and document analysis pipelines
- Modify OCR result formatting and handling
- Remove unused imports and optimize code structure

- Add base model structure for OCR in pytorch
- Implement data augmentation and transformation modules
- Create utilities for dictionary handling and state dict conversion
- Include post-processing modules for OCR
- Add weight initialization and loading functions