New Features
Vision Foundation Model
* Release Segment Anything Model (SAM) based on PaddlePaddle. As a vision foundation model, SAM has the powerful zero-shot capability to segment any objects and images. SAM can also segment specified object with prompt input.
* Provide a gradio-based demo, which can be easily deployed to demonstrate the function of automatic full-image segmentation.
* Provide a script-based demo, which segments specific objects with a point, box, or mask as prompt input.
Semantic Segmentation
* Release PP-MobileSeg, a lightweight semantic segmentation model for mobile devices. Comparing PP-MobileSeg with the previous SOTA model on ADE20K dataset, the accuracy is increased by 1.5%, the speed is increased by 42.3%, and the number of parameters is reduced by 34.9%.
* Add 7 semantic segmentation models, i.e., MaskFormer, HRFormer, ViT-Adapter, CAE, SegNeXt, K-Net, and LPSNet.
* Enhance model training modules: Add Exponential Moving Average (EMA); refactor the optimizer as a customizable component; decouple Config from Builder, and strictly verify configuration information; move the user scripts into the `tools` directory.
* Enhance model deployment modules: Add FastDeploy, a high-performance and all-scenario model deployment solution; add examples and tutorials for C++ deployment on Windows.
Panoptic Segmentation
* Release PanopticSeg v0.5, a universal panoptic segmentation solution.
* Provide full-process development capabilities for panoptic segmentation scenes, and support functions such as dataset preparation, model training, model deployment, and visual analysis.
* Integrate Mask2Former and Panoptic-DeepLab models, and support Cityscapes and MS COCO datasets.
Quality Inspector
* Release QualityInspector v0.5, a full-process solution for industrial quality inspection.
* Support a unified and configurable pipeline that can flexibly use single-task and multi-task models, and integrate PaddleDetection and PaddleSeg models.
* Provide 3 unsupervised quality inspection methods.
* Support model evaluation and analysis functions, and one-click tuning by using the post-processing module.
* Support functions such as data labeling, data analysis, and format conversion in industrial quality inspection scenes, and provide practical examples.
Others
* Release EISeg v1.1, a semi-automatic tool for image annotation. Add manual labeling and automatic pre-labeling functions for detection objects, and support 3 dataset formats (COCO, VOC and YOLO).
* Add a video matting model RVM, and support video matting and background replacement functions. Add a .NET deployment tutorial for matting models. Add DIY applications for ID photos and wedding photos based on PP-Matting.
Bug Fixes
* Fix the precision error of multi-scale evaluation 2933 2978
* Fix the error of exporting the inference model for ESPNetV2 model 3003
* Fix the error of repeatedly downloading datasets under multi GPUs 3126
* Fix a bug in PortraitNet dataset 3024
新特性
视觉大模型
* 开源飞桨版本视觉大模型Segment Anything Model (SAM)。SAM具有强大的zero-shot能力，可以分割任意物体和图像，也可以使用提示输入分割特定目标。
* 提供基于Gradio的演示Demo，支持本地部署，可以快速体验SAM全图分割功能。
* 提供脚本演示Demo，支持点、框、掩码作为提示输入，快速得到SAM交互分割结果。
语义分割
* 发布超轻量级语义分割SOTA模型PP-MobileSeg，在ADE20K数据集上对比此前模型，精度提升1.5%、速度提升42.3%、参数量减少34.9%。
* 新增7个前沿语义分割模型：MaskFormer、HRFormer、ViT-Adapter、CAE、SegNeXt、K-Net和LPSNet。
* 增强训练功能：新增指数滑动平均EMA；支持自定义Optimizer组件，灵活配置训练超参；解耦Config和Builder，严格校验配置信息；训压推启动脚本统一到`tools`目录下。
* 增强部署功能：新增支持高性能、全场景的模型部署方案FastDeploy；新增Windows上CPP部署的示例和教程。
全景分割
* 发布通用的全景分割方案PanopticSeg v0.5版本。
* 提供全景分割场景的全流程开发能力，打通数据集准备、模型训练、模型推理、可视化分析等功能。
* 集成前沿模型Mask2Former和Panoptic-DeepLab，支持Cityscapes与MS COCO数据集。
工业质检
* 发布工业质检全流程解决方案QualityInspector v0.5版本。
* 支持统一可配置的算法方案，集成飞桨检测分割的能力和模型库，灵活使用单任务模型和多任务串联模型。
* 支持三种无监督异常检测算法。
* 支持工业级指标评测和分析功能，使用后处理模块可以一键调优。
* 支持工业质检场景的数据标注、数据分析、格式转换等功能，提供全流程实践范例。
其他
* 发布高性能智能标注工具EISeg v1.1版本，新增对检测目标的手工标注功能和自动预标注功能，支持COCO、VOC和YOLO的检测标注保存格式。
* 新增视频抠图模型RVM，支持视频预测和背景替换；新增人像抠图.NET部署教程；新增基于PP-Matting的证件照/结婚照DIY应用。
Bug修复
* 修复多尺度验证的精度错误 2933 2978
* 修复ESPNetV2模型导出预测模型的错误 3003
* 修复多卡重复下载数据集的错误 3126
* 修复PortraitNet数据集的错误 3024