91 lines
3.4 KiB
Markdown
91 lines
3.4 KiB
Markdown
## Changelog
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### V0.8 (03/11/2020)
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**Highlights**
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- Support 4 medical dataset, UNet and CGNet.
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**New Features**
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- Support customize runner ([#118](https://github.com/open-mmlab/mmsegmentation/pull/118))
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- Support UNet ([#161](https://github.com/open-mmlab/mmsegmentation/pull/162))
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- Support CHASE_DB1, DRIVE, STARE, HRD ([#203](https://github.com/open-mmlab/mmsegmentation/pull/203))
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- Support CGNet ([#223](https://github.com/open-mmlab/mmsegmentation/pull/223))
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### V0.7 (07/10/2020)
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**Highlights**
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- Support Pascal Context dataset and customizing class dataset.
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**Bug Fixes**
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- Fixed CPU inference ([#153](https://github.com/open-mmlab/mmsegmentation/pull/153))
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**New Features**
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- Add DeepLab OS16 models ([#154](https://github.com/open-mmlab/mmsegmentation/pull/154))
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- Support Pascal Context dataset ([#133](https://github.com/open-mmlab/mmsegmentation/pull/133))
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- Support customizing dataset classes ([#71](https://github.com/open-mmlab/mmsegmentation/pull/71))
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- Support customizing dataset palette ([#157](https://github.com/open-mmlab/mmsegmentation/pull/157))
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**Improvements**
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- Support 4D tensor output in ONNX ([#150](https://github.com/open-mmlab/mmsegmentation/pull/150))
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- Remove redundancies in ONNX export ([#160](https://github.com/open-mmlab/mmsegmentation/pull/160))
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- Migrate to MMCV DepthwiseSeparableConv ([#158](https://github.com/open-mmlab/mmsegmentation/pull/158))
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- Migrate to MMCV collect_env ([#137](https://github.com/open-mmlab/mmsegmentation/pull/137))
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- Use img_prefix and seg_prefix for loading ([#153](https://github.com/open-mmlab/mmsegmentation/pull/153))
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### V0.6 (10/09/2020)
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**Highlights**
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- Support new methods i.e. MobileNetV2, EMANet, DNL, PointRend, Semantic FPN, Fast-SCNN, ResNeSt.
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**Bug Fixes**
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- Fixed sliding inference ONNX export ([#90](https://github.com/open-mmlab/mmsegmentation/pull/90))
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**New Features**
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- Support MobileNet v2 ([#86](https://github.com/open-mmlab/mmsegmentation/pull/86))
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- Support EMANet ([#34](https://github.com/open-mmlab/mmsegmentation/pull/34))
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- Support DNL ([#37](https://github.com/open-mmlab/mmsegmentation/pull/37))
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- Support PointRend ([#109](https://github.com/open-mmlab/mmsegmentation/pull/109))
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- Support Semantic FPN ([#94](https://github.com/open-mmlab/mmsegmentation/pull/94))
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- Support Fast-SCNN ([#58](https://github.com/open-mmlab/mmsegmentation/pull/58))
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- Support ResNeSt backbone ([#47](https://github.com/open-mmlab/mmsegmentation/pull/47))
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- Support ONNX export (experimental) ([#12](https://github.com/open-mmlab/mmsegmentation/pull/12))
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**Improvements**
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- Support Upsample in ONNX ([#100](https://github.com/open-mmlab/mmsegmentation/pull/100))
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- Support Windows install (experimental) ([#75](https://github.com/open-mmlab/mmsegmentation/pull/75))
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- Add more OCRNet results ([#20](https://github.com/open-mmlab/mmsegmentation/pull/20))
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- Add PyTorch 1.6 CI ([#64](https://github.com/open-mmlab/mmsegmentation/pull/64))
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- Get version and githash automatically ([#55](https://github.com/open-mmlab/mmsegmentation/pull/55))
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### v0.5.1 (11/08/2020)
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**Highlights**
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- Support FP16 and more generalized OHEM
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**Bug Fixes**
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- Fixed Pascal VOC conversion script (#19)
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- Fixed OHEM weight assign bug (#54)
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- Fixed palette type when palette is not given (#27)
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**New Features**
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- Support FP16 (#21)
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- Generalized OHEM (#54)
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**Improvements**
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- Add load-from flag (#33)
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- Fixed training tricks doc about different learning rates of model (#26)
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