GitLab

- Change dill dependency from >=0.3.9,<1 to >=0.3.8,<1
- Update dill version in both general and specific requirements

- Update matplotlib version range to >=3.10, <4
- Add version上限 for ultralytics: <9
- Remove redundant version ranges for full_old_linux

- Add project URLs in setup.py for better discoverability
- Make consistent changes across README.md and README_zh-CN.md

- Update Python version requirements to >=3.10
- Simplify torch installation command- Remove numpy version restriction
- Update CUDA compatibility information
- Adjust environment creation commands across multiple documentation files

- Remove rapid_table from install_requires in setup.py

- Update transformers to exclude version 4.51.0 due to compatibility issues- Rapid table version range expanded to >=1.0.5,<2.0.0
- Add separate 'full_old_linux' extras_require for better support of older Linux systems
- Update matplotlib version requirements for different platforms
- Remove platform-specific paddlepaddle versions,

- Add rapid_table==1.0.3 to old_linux specific dependencies
- This version is compatible with Linux systems from 2019 and earlier
- Newer versions of rapid_table depend on onnxruntime, which is not supported on older Linux systems

- Update matplotlib minimum version to 3.10 for Linux and MacOS
- Specify version ranges for PyYAML, ftfy, openai, shapely, pyclipper, and omegaconf
- Update dill to version <1 for compatibility

- 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 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

- Add 'ftfy' package to the list of dependencies in setup.py
- This change ensures that the ftfy package is installed along with other dependencies when setting up the project

- Update config version to1.2.0
- Refactor model initialization in model_init.py- Update dependencies in requirements.txt files
- Remove unused imports and models
- Add conditional imports for table models

- 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

- Update PaddlePaddle to 3.0.0rc1 for Linux and macOS

- Update rapidocr-paddle dependency to version >=1.4.5, <2.0.0- Update rapidocr_onnxruntime dependency to version >=1.4.4, <2.0.0

- 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

- Merge title blocks that are close to each other horizontally
- Adjust line insertion logic for title blocks- Increase image size and decrease confidence threshold for layout detection
- Update DocLayoutYOLO model weights
- Refactor drawing of bounding boxes for different block types

- Update rapid_table dependency to version 0.3.0 in setup.py

- 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 unimernet from 0.2.2 to 0.2.3 in requirements-docker.txt and setup.py
- Remove torchtext/eva-decord dependency

- Implement llm_aided_title function to optimize document titles using LLM
- Update pdf_parse_union_core_v2.py to include title optimization
- Modify ocr_mkcontent.py to use optimized title levels- Add openai SDK dependency in setup.py

- Specify torch==2.3.1 and torchvision==0.18.1 for Windows CUDA installation
- Add torch and torchvision version constraints in setup.py:
  - torch>=2.2.2,<=2.3.1
  - torchvision>=0.17.2,<=0.18.1
- Update installation instructions in both English and Chinese README files

- Add environment variables to disable albumentations and yolo updates
- Import torchtext and disable deprecation warnings
- Update unimernet to 0.2.2
- Specify ultralytics version as >=8.3.48
- Remove upper version limit for torch

- Update ultralytics to >=8.3.47

- Update `ultralytics` dependency to version >= 8.3.43
- This change ensures compatibility with yolov8 for formula detection

- Add albumentations package with version <=1.4.20 for old_linux
- This version is compatible with Linux systems from 2019 and earlier
- Version 1.4.21 and above introduced simsimd which is not supported on older Linux systems

- Integrate RapidOCR with RapidTable model for table recognition
- Improve memory management for devices with <= 8GB VRAM
- Update table recognition process to use RapidOCR for RapidTable
- Add rapidocr-paddle dependency in setup.py

- Add RapidTable model support for table recognition
- Update table model configuration and initialization
- Modify table recognition process to use RapidTable when specified
- Add RapidTable dependency to setup.py

- Update StructTableModel to use the latest struct-eqtable library
- Add support for HTML table extraction in PDF Extract Kit
- Improve error handling and model initialization
- Update dependencies in setup.py for struct-eqtable

- Add doclayout_yolo==0.0.2 to the list of dependencies in setup.py

update UniMERNet to 0.2.1

Update the paths to model weights and configuration files for the UniMERNet architecture
in both the demo.yaml and model_configs.yaml files. Adjust the mfr_model_init function toreflect the new weight and configuration paths. The changes include specifying more detailed
paths to the unimernet_base directory and changing the weight file extension to .pth.

The restriction on the matplotlib version has been updated to only apply on Windows
platforms, where precompiled packages are not available starting from version 3.9.1.
This change enables users on Linux and macOS to install newer versions of matplotlib,
addressing compatibility issues with recent bug fixes.