Merge pull request #1616 from myhloli/dev

docs(readme): update changelog for v1.1.0 release

README.md

@@ -48,10 +48,13 @@ Easier to use: Just grab MinerU Desktop. No coding, no login, just a simple inte
 
 # Changelog
 - 2025/01/22 1.1.0 released. In this version we have focused on improving parsing accuracy and efficiency:
-  - Upgraded to the latest doclayout_yolo(2501) model, enhancing layout recognition accuracy.
-  - Upgraded to the latest unimernet(2501) model, improving formula recognition accuracy.
-  - On devices that meet certain configuration requirements (16GB+ VRAM), by optimizing resource usage and restructuring the processing pipeline, overall parsing speed has been increased by more than 50%.
-  - Added a new heading classification feature (testing version, enabled by default) to the online demo, which supports hierarchical classification of headings, thereby enhancing document structuring.
+  - Model capability upgrade (requires re-executing the [model download process](docs/how_to_download_models_en.md) to obtain incremental updates of model files)
+    - The layout recognition model has been upgraded to the latest `doclayout_yolo(2501)` model, improving layout recognition accuracy.
+    - The formula parsing model has been upgraded to the latest `unimernet(2501)` model, improving formula recognition accuracy.
+  - Performance optimization
+    - On devices that meet certain configuration requirements (16GB+ VRAM), by optimizing resource usage and restructuring the processing pipeline, overall parsing speed has been increased by more than 50%.
+  - Parsing effect optimization
+    - Added a new heading classification feature (testing version, enabled by default) to the online demo, which supports hierarchical classification of headings, thereby enhancing document structuring.
 - 2025/01/10 1.0.1 released. This is our first official release, where we have introduced a completely new API interface and enhanced compatibility through extensive refactoring, as well as a brand new automatic language identification feature:
   - New API Interface
     - For the data-side API, we have introduced the Dataset class, designed to provide a robust and flexible data processing framework. This framework currently supports a variety of document formats, including images (.jpg and .png), PDFs, Word documents (.doc and .docx), and PowerPoint presentations (.ppt and .pptx). It ensures effective support for data processing tasks ranging from simple to complex.

README_zh-CN.md

@@ -47,10 +47,13 @@
 
 # 更新记录
 - 2025/01/22 1.1.0 发布，在这个版本我们重点提升了解析的精度与效率：
-  - 升级了最新版的doclayout_yolo(2501)模型，提升了layout识别精度
-  - 升级了最新版的unimernet(2501)模型，提升了公式识别精度
-  - 在配置满足一定条件（显存16GB+）的设备上，通过优化资源占用和重构处理流水线，整体解析速度提升50%以上
-  - 在线demo上新增标题分级功能（测试版本，默认开启），支持对标题进行分级，提升文档结构化程度
+  - 模型能力升级（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） 
+    - 布局识别模型升级到最新的`doclayout_yolo(2501)`模型，提升了layout识别精度
+    - 公式解析模型升级到最新的`unimernet(2501)`模型，提升了公式识别精度
+  - 性能优化
+    - 在配置满足一定条件（显存16GB+）的设备上，通过优化资源占用和重构处理流水线，整体解析速度提升50%以上
+  - 解析效果优化
+    - 在线demo（mineru.net/huggingface/modelscope）上新增标题分级功能（测试版本，默认开启），支持对标题进行分级，提升文档结构化程度
 - 2025/01/10 1.0.1 发布，这是我们的第一个正式版本，在这个版本中，我们通过大量重构带来了全新的API接口和更广泛的兼容性，以及全新的自动语言识别功能：
   - 全新API接口 
     - 对于数据侧API，我们引入了Dataset类，旨在提供一个强大而灵活的数据处理框架。该框架当前支持包括图像（.jpg及.png）、PDF、Word（.doc及.docx）、以及PowerPoint（.ppt及.pptx）在内的多种文档格式，确保了从简单到复杂的数据处理任务都能得到有效的支持。