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@@ -49,14 +49,14 @@ Easier to use: Just grab MinerU Desktop. No coding, no login, just a simple inte
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# Changelog
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- 2025/04/03 Release of version 1.3.0, with many changes in this version:
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- Installation and compatibility optimization
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- - By using paddleocr2torch, completely replaced the paddle framework and paddleocr used in the project, resolving conflicts between paddle and torch (OCR speed under single-process is slightly slower compared to the paddle framework).
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+ - By using paddleocr2torch, completely replaced the paddle framework and paddleocr used in the project, resolving conflicts between paddle and torch.
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- Removed the use of layoutlmv3 in layout, solving compatibility issues caused by `detectron2`.
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- Extended torch version compatibility to 2.2~2.6.
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- - CUDA compatibility extended to 11.8~12.6 (CUDA version determined by torch), addressing compatibility issues for some users with 50-series and H-series GPUs.
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+ - CUDA compatibility extended to 11.8~12.6 (CUDA version determined by torch), addressing compatibility issues for some users with 50-series and H-series Nvidia GPUs.
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- Python compatible versions extended to 3.10~3.12, resolving the issue of automatic downgrade to 0.6.1 during installation in non-3.10 environments.
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- Performance optimization (compared to version 1.0.1, formula parsing speed improved by over 1400%, and overall parsing speed improved by over 500%)
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- - Supported batch processing for multiple PDF files, enhancing the parsing speed of batch files.
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- - Optimized the loading and usage of the mfr model, reducing memory usage and improving parsing speed.
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+ - Improved parsing speed for batch processing of multiple small PDF files ([script example](demo/batch_demo.py)).
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+ - Optimized the loading and usage of the mfr model, reducing memory usage and improving parsing speed. (requires re-executing the [model download process](docs/how_to_download_models_en.md) to obtain incremental updates of model files)
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- Optimized memory usage, allowing the project to run with as little as 6GB.
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- Improved running speed on mps devices.
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- Parsing effect optimization
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