GitLab

- 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

fix: convert image with pymupdf

fix: support non-pdf file in batch mode

feat(web_api): update configuration and remove unused code

- Comment out PaddlePaddle GPU installation in Dockerfile
- Add OCR model download URL in download_models.py
- Update config version in magic-pdf.json
- Remove outdated information and simplify README.md
- Remove volume creation for PaddleOCR models in Dockerfile

docs(user_guide): update installation guide and CUDA support

- Update CUDA version requirements to 12.4 and higher
- Add support for CUDA 12.6 and CANN environments- Update Python version requirements to 3.10-3.12
- Remove paddlepaddle-gpu installation and related instructions
- Update magic-pdf installation command to use Aliyun mirror
- Add storage requirements and update memory requirements
- Update GPU hardware support list to include all GPUs with Tensor Cores
- Add support for Apple Silicon

docs(readme): update changelog and compatibility information

- Update changelog for version 1.3.0 release
- Clarify CUDA and GPU compatibility improvements
- Add information about batch processing speed improvements
- Update model download process and memory usage optimizations
- Include link to batch processing demo script

feat(model): add tqdm progress bar to model prediction loops

- 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

- Remove outdated comments in table-config examples
- Add tqdm to requirements in all Docker environments

- 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

feat(model): update Chinese OCR detection model to PP-OCRv3

- 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

refactor(ocr): remove redundant code and improve code quality

- 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

refactor(demo): simplify batch_demo.py and update demo.py

- 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

feat: add batch example

update released note

- Add RapidOCR and PaddleOCR2Pytorch to the Acknowledgments list in README.md
- Add RapidOCR and PaddleOCR2Pytorch to the Acknowledgments list in README_zh-CN.md

- Installation and compatibility optimizations:
- Replace PaddleOCR with paddleocr2torch to resolve conflicts between Paddle and PyTorch
  - Remove layoutlmv3 usage to solve compatibility issues with detectron2
  - Extend PyTorch version compatibility to2.2~2.6  - Extend CUDA compatibility to 11.8~12.6
  - Extend Python version compatibility to 3.10~3.12

- Performance optimizations:
 - Support batch processing for multiple PDF files
  - Optimize mfr model loading and usage to reduce memory consumption and improve speed
  - Reduce minimum memory requirement to 6GB
  - Improve running speed on MPS devices

- Parsing effect optimization:
  - Update mfr model to unimernet(2503) to fix line break issues in multi-line formulas

update docs

- Update CUDA version requirements to12.4
- Recommend nvidia-driver-570-server for Ubuntu
- Remove Python version specification for conda environment
- Update magic-pdf version requirement to 1.3.0
- Simplify CUDA acceleration testing instructions
- Remove OCR acceleration with paddlepaddle-gpu
- Update torch and torchvision installation instructions for Windows

- Update Python version requirement to 3.10-3.12
- Expand CUDA environment options to 11.8/12.4/12.6
- Update GPU VRAM requirement to 6GB or more
-

feat: support 3.10~3.12 & remove paddle

- 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 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

- Remove paddleocr, paddlepaddle, rapidocr-paddle, and rapidocr-onnxruntime from requirements.txt files
- Simplify pip install commands in Dockerfiles
- Remove installation of paddlepaddle-gpu in china and global Dockerfiles
- Update requirements.txt files across all Docker configurations

- Commented out the code that copies the paddleocr model to user directory
- This change affects both download_models.py and download_models_hf.py scripts