Release PaddleSeg v2.8.0 · PaddlePaddle/PaddleSeg

New Features

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.

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.

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.

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.

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.

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。

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。