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Release 1.3.1

Dev

docs: update badges and project URLs- Update PyPI version badge to us…

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

fix(table): add model path for slanet-plus to resolve RapidTableError

fix(table): add model path for slanet-plus to resolve RapidTableError

- 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

update 1.3.1

- Add support for Python3.11, 3.12, and 3.13
- Replace requirements.txt based installation with editable install

- 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

- Add "3.13" option for Python version
- Remove "3.9" option for Python version
- Update dependency version options:
  - Remove "0.8.x", "0.9.x", "0.10.x"
  - Add "1.1.x", "1.2.x", "1.3.x"

- 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

fix(model): improve VRAM detection and handling

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

fix: image dataset add lang field

docs: update torchvision version in CUDA installation guide

docs: update torchvision version in CUDA installation guide

- Update torchvision version from0.21.1 to0.21.0 in Windows CUDA acceleration guides
- Update both English and Chinese versions of the documentation

build: remove accelerate dependency

- Remove accelerate package from requirements.txt
- This change ensures only necessary external dependencies are introduced

build(deps): add accelerate package and update requirements https://github.com/opendatalab/MinerU/issues/2112

- Add accelerate package to support model training acceleration
- Update requirements.txt to include new dependency

master -> dev

Release 1.3.0

docs(readme): update release notes for version 1.3.0

docs(readme): update release notes for version 1.3.0 

- Remove duplicate entries for paddleocr2torch and thread safety
- Add new entry for real-time progress bar implementation
- Update mfr model to unimernet(2503)
- Extend torch version compatibility
- Enhance cuda support for various GPU models
- Improve parsing speed on MPS devices

- Update release notes in both English and Chinese README files
- Highlight major optimizations and improvements in version 1.3.0
- Clarify compatibility changes for torch, CUDA, and Python versions
- Emphasize performance improvements and parsing speed enhancements
- Mention specific bug fixes and parsing effect optimizations

Release 1.3.0

fix: support non-pdf file in batch mode

fix: convert image with pymupdf

fix: support non-pdf file in batch mode