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@cuicheng01 cuicheng01 released this 20 Aug 06:33
· 2 commits to release/3.2 since this release
v3.2.0
ea48b94

2025.8.20 v3.2.0 released

  • Deployment Capability Upgrades:

    • Fully supports PaddlePaddle framework versions 3.1.0 and 3.1.1.
    • High-performance inference supports CUDA 12, with backend options including Paddle Inference and ONNX Runtime.
    • High-stability serving solution is fully open-sourced, enabling users to customize Docker images and SDKs as needed.
    • High-stability serving solution supports invocation via manually constructed HTTP requests, allowing client applications to be developed in any programming language.

  • Key Model Additions:

    • Added training, inference, and deployment support for PP-OCRv5 English, Thai, and Greek recognition models. The PP-OCRv5 English model delivers an 11% improvement over the main PP-OCRv5 model in English scenarios, with the Thai model achieving an accuracy of 82.68% and the Greek model 89.28%.

  • Benchmark Enhancements:

    • All pipelines support fine-grained benchmarking, enabling the measurement of end-to-end inference time as well as per-layer and per-module latency data to assist with performance analysis.
    • Added key metrics such as inference latency and memory usage for commonly used configurations on mainstream hardware to the documentation, providing deployment reference for users.

  • Bug Fixes:

    • Fixed an issue where invalid input image file formats could cause recursive calls.
    • Resolved ineffective parameter settings for chart recognition, seal recognition, and document pre-processing in the configuration files for the PP-DocTranslation and PP-StructureV3 pipelines.
    • Fixed an issue where PDF files were not properly closed after inference.

  • Other Updates:

    • Added support for Windows users with NVIDIA 50-series graphics cards; users can install the corresponding PaddlePaddle framework version as per the installation guide.
    • The PP-OCR model series now supports returning coordinates for individual characters.
    • The model_name parameter in PaddlePredictorOption has been moved to PaddleInfer, improving usability.
    • Refactored the official model download logic, with new support for multiple model hosting platforms such as AIStudio and ModelScope.

2025.8.20 v3.2.0 发布

  • 部署能力升级：

    • 全面支持飞桨框架 3.1.0 和 3.1.1 版本。
    • 高性能推理支持 CUDA 12，可使用 Paddle Inference、ONNX Runtime 后端推理。
    • 高稳定性服务化部署方案全面开源，支持用户根据需求对 Docker 镜像和 SDK 进行定制化修改。
    • 高稳定性服务化部署方案支持通过手动构造HTTP请求的方式调用，该方式允许客户端代码使用任意编程语言编写。

  • 重要模型新增：

    • 新增 PP-OCRv5 英文、泰文、希腊文识别模型的训练、推理、部署。其中 PP-OCRv5 英文模型较 PP-OCRv5 主模型在英文场景提升 11%，泰文识别模型精度 82.68%，希腊文识别模型精度 89.28%。

  • Benchmark升级：

    • 全部产线支持产线细粒度 benchmark，能够测量产线端到端推理时间以及逐层、逐模块的耗时数据，可用于辅助产线性能分析。
    • 在文档中补充各产线常用配置在主流硬件上的关键指标，包括推理耗时和内存占用等，为用户部署提供参考。

  • Bug修复：

    • 修复了当输入图片文件格式不合法时，导致递归调用的问题。
    • 修复了 PP-DocTranslation 和 PP-StructureV3 产线配置文件中图表识别、印章识别、文档预处理参数设置不生效的问题。
    • 修复 PDF 文件在推理结束后未正确关闭的问题。

  • 其他升级：

    • 支持 Windows 用户使用英伟达 50 系显卡，可根据安装文档安装对应版本的 paddle 框架。
    • PP-OCR 系列模型支持返回单文字坐标。
    • 将 PaddlePredictorOption 中的 model_name 参数移至 PaddleInfer 中，改善了用户易用性。
    • 重构了官方模型下载逻辑，新增了 AIStudio、ModelScope 等多模型托管平台。

Full Changelog: v3.1.4...v3.2.0

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