MMSegmentation v0.10.0 Release

Highlights

• Support MobileNetV3, DMNet, APCNet. Add models of ResNet18V1b, ResNet18V1c, ResNet50V1b, ResNet101V1b.

Bug Fixes

• Fixed CPU TTA (#276)
• Fixed CI for pip 20.3 (#307)

New Features

• Add ResNet18V1b, ResNet18V1c, ResNet50V1b models (#316)
• Support MobileNetV3 (#268)
• Add 4 retinal vessel segmentation benchmark (#315)
• Support DMNet (#313)
• Support APCNet (#299)

Improvements

• Refactor Documentation page (#311)
• Support resize data augmentation according to original image size (#291)

MMSegmentation v0.9.0 Release

Highlights

• Add 5 transform augmentation, add model statistics.

New Features

• Support RandomRotate transform (#215, #260)
• Support RGB2Gray transform (#227)
• Support Rerange transform (#228)
• Support ignore_index for BCE loss (#210)
• Add modelzoo statistics (#263)
• Support Dice evaluation metric (#225)
• Support Adjust Gamma transform (#232)
• Support CLAHE transform (#229)

Bug Fixes

• Fixed detail API link (#267)

MMSegmentation v0.8.0 Release

Highlights

• Support 4 medical dataset, UNet and CGNet.

New Features

• Support customize runner (#118)
• Support UNet (#161)
• Support CHASE_DB1, DRIVE, STARE, HRD (#203)
• Support CGNet (#223)

MMSegmentation v0.7.0 Release

Highlights

• Support Pascal Context dataset and customizing class dataset.

Bug Fixes

• Fixed CPU inference (#153)

New Features

• Add DeepLab OS16 models (#154)
• Support Pascal Context dataset (#133)
• Support customizing dataset classes (#71)
• Support customizing dataset palette (#157)

Improvements

• Support 4D tensor output in ONNX (#150)
• Remove redundancies in ONNX export (#160)
• Migrate to MMCV DepthwiseSeparableConv (#158)
• Migrate to MMCV collect_env (#137)
• Use img_prefix and seg_prefix for loading (#153)

MMSegmentation v0.6.0 Release

Highlights

• Support new methods i.e. MobileNetV2, EMANet, DNL, PointRend, Semantic FPN, Fast-SCNN, ResNeSt.

Bug Fixes

• Fixed sliding inference ONNX export (#90)

New Features

• Support MobileNet v2 (#86)
• Support EMANet (#34)
• Support DNL (#37)
• Support PointRend (#109)
• Support Semantic FPN (#94)
• Support Fast-SCNN (#58)
• Support ResNeSt backbone (#47)
• Support ONNX export (experimental) (#12)

Improvements

• Support Upsample in ONNX (#100)
• Support Windows install (experimental) (#75)
• Add more OCRNet results (#20)
• Add PyTorch 1.6 CI (#64)
• Get version and githash automatically (#55)