Merge pull request #2090 from opendatalab/dev

docs(readme): update release notes for version 1.3.0

README.md

@@ -47,20 +47,23 @@ Easier to use: Just grab MinerU Desktop. No coding, no login, just a simple inte
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 # Changelog
-- 2025/04/03 Release of version 1.3.0, with many changes in this version:
+- 2025/04/03 Release of 1.3.0, in this version we made many optimizations and improvements:
   - Installation and compatibility optimization
-    - By using paddleocr2torch, completely replaced the paddle framework and paddleocr used in the project, resolving conflicts between paddle and torch.
-    - Removed the use of layoutlmv3 in layout, solving compatibility issues caused by `detectron2`.
-    - Extended torch version compatibility to 2.2~2.6.
-    - 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.
-    - 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.
-  - Performance optimization (compared to version 1.0.1, formula parsing speed improved by over 1400%, and overall parsing speed improved by over 500%)
-    - Improved parsing speed for batch processing of multiple small PDF files ([script example](demo/batch_demo.py)).
-    - 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)
-    - Optimized memory usage, allowing the project to run with as little as 6GB.
-    - Improved running speed on mps devices.
+    - By removing the use of `layoutlmv3` in layout, resolved compatibility issues caused by `detectron2`.
+    - Torch version compatibility extended to 2.2~2.6 (excluding 2.5).
+    - CUDA compatibility supports 11.8/12.4/12.6 (CUDA version determined by torch), resolving compatibility issues for some users with 50-series and H-series GPUs.
+    - Python compatible versions expanded to 3.10~3.12, solving the problem of automatic downgrade to 0.6.1 during installation in non-3.10 environments.
+    - Offline deployment process optimized; no internet connection required after successful deployment to download any model files.
+  - Performance optimization
+    - By supporting batch processing of multiple PDF files ([script example](demo/batch_demo.py)), improved parsing speed for small files in batches (compared to version 1.0.1, formula parsing speed increased by over 1400%, overall parsing speed increased by over 500%).
+    - Optimized loading and usage of the mfr model, reducing GPU memory usage and improving parsing speed (requires re-execution of the [model download process](docs/how_to_download_models_en.md) to obtain incremental updates of model files).
+    - Optimized GPU memory usage, requiring only a minimum of 6GB to run this project.
+    - Improved running speed on MPS devices.
   - Parsing effect optimization
-    - Updated the mfr model to unimernet(2503), solving the issue of missing line breaks in multi-line formulas.
+    - Updated the mfr model to `unimernet(2503)`, solving the issue of lost line breaks in multi-line formulas.
+  - Usability Optimization
+    - By using `paddleocr2torch`, completely replaced the use of the `paddle` framework and `paddleocr` in the project, resolving conflicts between `paddle` and `torch`, as well as thread safety issues caused by the `paddle` framework.
+    - Added a real-time progress bar during the parsing process to accurately track progress, making the wait less painful.
 - 2025/03/03 1.2.1 released, fixed several bugs:
   - Fixed the impact on punctuation marks during full-width to half-width conversion of letters and numbers
   - Fixed caption matching inaccuracies in certain scenarios

README_zh-CN.md

@@ -46,21 +46,23 @@
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 # 更新记录
-- 2025/04/03 1.3.0 发布，在这个版本我们做出了许多改变：
+- 2025/04/03 1.3.0 发布，在这个版本我们做出了许多优化和改进：
   - 安装与兼容性优化
-    - 通过使用paddleocr2torch，完全替代了paddle框架以及paddleocr在项目中的使用，解决了paddle和torch的冲突问题
-    - 通过移除layout中layoutlmv3的使用，解决了由`detectron2`导致的兼容问题
-    - torch版本兼容扩展到2.2~2.6
-    - cuda兼容扩展到11.8~12.6（cuda版本由torch决定），解决部分用户50系显卡与H系显卡的兼容问题
+    - 通过移除layout中`layoutlmv3`的使用，解决了由`detectron2`导致的兼容问题
+    - torch版本兼容扩展到2.2~2.6(2.5除外)
+    - cuda兼容支持11.8/12.4/12.6（cuda版本由torch决定），解决部分用户50系显卡与H系显卡的兼容问题
     - python兼容版本扩展到3.10~3.12，解决了在非3.10环境下安装时自动降级到0.6.1的问题
     - 优化离线部署流程，部署成功后不需要联网下载任何模型文件
-  - 性能优化（与1.0.1版本相比，公式解析速度最高提升超过1400%，整体解析速度提升超过500%）
-    - 通过支持多个pdf文件的batch处理（[脚本样例](demo/batch_demo.py)），提升了批量小文件的解析速度
+  - 性能优化
+    - 通过支持多个pdf文件的batch处理（[脚本样例](demo/batch_demo.py)），提升了批量小文件的解析速度 (与1.0.1版本相比，公式解析速度最高提升超过1400%，整体解析速度最高提升超过500%)
     - 通过优化mfr模型的加载和使用，降低了显存占用并提升了解析速度(需重新执行[模型下载流程](docs/how_to_download_models_zh_cn.md)以获得模型文件的增量更新)
     - 优化显存占用，最低仅需6GB即可运行本项目
     - 优化了在mps设备上的运行速度
   - 解析效果优化
-    - mfr模型更新到unimernet(2503)，解决多行公式中换行丢失的问题
+    - mfr模型更新到`unimernet(2503)`，解决多行公式中换行丢失的问题
+  - 易用性优化
+    - 通过使用`paddleocr2torch`，完全替代`paddle`框架以及`paddleocr`在项目中的使用，解决了`paddle`和`torch`的冲突问题，和由于`paddle`框架导致的线程不安全问题
+    - 解析过程增加实时进度条显示，精准把握解析进度，让等待不再痛苦
 - 2025/03/03 1.2.1 发布，修复了一些问题：
   - 修复在字母与数字的全角转半角操作时对标点符号的影响
   - 修复在某些情况下caption的匹配不准确问题