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PaddleSeg v2.1.0
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@nepeplwu nepeplwu released this 19 May 13:44
· 25 commits to release/2.1 since this release
v2.1.0
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Learn about vigilant mode.

新特性

  • 语义分割方向新增医疗分割模型UNet3+、轻量级模型SFNet、ShuffleNetV2等模型。
  • 全新增加 全景分割 场景，支持训练、评估、预测以及可视化等能力，新增Anchor-Free的SOTA模型Panoptic-DeepLab。
  • 完善部署能力，新增 移动端部署 能力和 web端部署 能力，并支持添加后处理算子(argmax/softmax)。
  • 高精度的人像分割模型humanseg升级为动态图版，并显著优化边缘锯齿问题。
  • 升级学习率配置模块，新增10种学习率策略，涵盖了业界主流学习率调度方式。
  • 新增Weighted Cross Entropy Loss、L1 Loss、MSE Loss，适用于不同场景下的模型优化。

Bug修复

  • #1016 修复NonLocal2D模块在非gaussian模式下shape不一致的问题。
  • #1007 修复RandomRotation和RandomScaleAspect在未传入Label时无法正确调用的问题。
  • #1006 修复EMANet无法进行单卡训练的问题。
  • #995 修复了PaddleSeg在PaddlePaddle 2.1版本中存在的兼容性问题。
  • #980 修复DecoupledSegNet在PaddlePaddle 2.1版本中训练失败的问题。
  • #975 修复滑窗预测图像小于窗口大小时无法正确预测的问题。
  • #971 修复ResizeByLong进行数据增强，在预测时没有正确恢复尺寸的问题。

New Features

  • New semantic segmentation models such as the medical segmentation model UNet3+, the lightweight model SFNet, and ShuffleNetV2 have been added.
  • Newly added panoramic segmentation scenes, supporting training, evaluation, prediction and visualization capabilities, and new Anchor-Free SOTA model Panoptic-DeepLab.
  • Improve deployment capabilities, add mobile deployment and web deployment capabilities, and support the addition of post-processing operators (argmax/softmax).
  • The high-precision portrait segmentation model humanseg is upgraded to dynamic graph version, and the edge aliasing problem is significantly optimized.
  • Upgrade the learning rate configuration module and add 10 new learning rate strategies, covering the mainstream learning rate scheduling methods in the industry.
  • Added Weighted Cross Entropy Loss, L1 Loss, and MSE Loss, which are suitable for model optimization in different scenarios.

Bug Fix

  • #1016 Fix the problem that the shape of NonLocal2D module is inconsistent in non-gaussian mode.
  • #1007 Fixed an issue where RandomRotation and RandomScaleAspect could not be called correctly when Label was not passed in.
  • #1006 Fix the problem that EMANet cannot be trained in single card.
  • #995 Fixed the compatibility issue of PaddleSeg in PaddlePaddle 2.1 version.
  • #980 Fixed the problem that DecoupledSegNet failed to train in PaddlePaddle 2.1.
  • #975 Fix the problem that the sliding window prediction image cannot be correctly predicted when the image is smaller than the window size.
  • #971 Fix the problem that ResizeByLong does not restore the size correctly in predict phase.
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