- 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
- 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
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.
Refactor the `extras_require` section in `setup.py` to simplify and clarify
the available options. Consolidate CPU and GPU requirements into single
"lite" and "full" options to streamline installation for users.
Update the setup.py file to explicitly include the package data for the
magic_pdf.resources directory. This ensures that all files within thisdirectory are packaged and available for use with the magic_pdf package.
Introduce a new feature that allows users to choose between a "lite" and a "full"
model mode for PDF document analysis. The "lite" mode uses a faster, less
accurate model, while the "full" mode employs a higher-precision model at the
cost of speed. This selection can be made through the CLI or API, providing
flexibility for different use cases.
