FastDeploy 0.6.0 Release Note

0.6.0 Release Note

模型

• 新增FSANet头部姿态识别模型 详情
• 新增PFLD人脸对齐模型 详情
• PP-Tracking模型增加轨迹可视化 详情
• 新增ERNIE文本分类模型 详情

服务化部署

• FastDeploy Runtime新增Clone接口支持，降低Paddle Inference/TensorRT/OpenVINO后端在多实例下内存/显存的使用

端侧部署

• 新增RKNPU2（3588）部署支持 详情

性能优化

• 优化YOLO系列、PaddleClas、PaddleDetection前后处理内存创建逻辑
• 融合视觉预处理操作，优化PaddleClas、PaddleDetection预处理性能
• 集成TensorRT BatchedNMSDynamic_TRT插件，提升TensorRT端到端部署性能

其它

• 修复若干文档问题
• 增加FastDeploy Runtime C++使用示例 详情

0.6.0 Release Note

Model

• Support FSANet head pose recognition model Details
• Support PFLD face alignment model Details
• PP-Tracking model adds track visualisation Details
• Support ERNIE text classification model Details

Service-based Deployment

• FastDeploy Runtime Adds Clone interface support for service-based deployment, reducing the memory、GPU memory usage of Paddle Inference、TensorRT、OpenVINO backend in multiple instances.

Edge Deployment

• Support RKNPU2（3588） Details.

Performance Optimisation

• Optimize preprocessing and postprocessing memory creation logic on YOLO series, PaddleClas, PaddleDetection.
• Integrate visual preprocessing operations, optimize the preprocessing performance of PaddleClas and PaddleDetection, and improve end-to-end performance.
• Integrating the TensorRT BatchedNMSDynamic_TRT plugin to improve the performance of TensorRT end-to-end deployments.

Others

• Fixing several documentation issues
• Adding FastDeploy Runtime C++ usage examples Details

New Contributors

• @rainyfly made their first contribution in #453
• @WinterGeng made their first contribution in #487

Full Changelog: release/0.4.0...release/0.6.0