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)
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)
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)
Highlights
- Support FP16 and more generalized OHEM
Bug Fixes
- Fixed Pascal VOC conversion script (#19)
- Fixed OHEM weight assign bug (#54)
- Fixed palette type when palette is not given (#27)
New Features
- Support FP16 (#21)
- Generalized OHEM (#54)
Improvements
- Add load-from flag (#33)
- Fixed training tricks doc about different learning rates of model (#26)