| ## Changelog | |
| ### V0.11 (02/02/2021) | |
| **Highlights** | |
| - Support memory efficient test, add more UNet models. | |
| **Bug Fixes** | |
| - Fixed TTA resize scale ([#334](https://github.com/open-mmlab/mmsegmentation/pull/334)) | |
| - Fixed CI for pip 20.3 ([#307](https://github.com/open-mmlab/mmsegmentation/pull/307)) | |
| - Fixed ADE20k test ([#359](https://github.com/open-mmlab/mmsegmentation/pull/359)) | |
| **New Features** | |
| - Support memory efficient test ([#330](https://github.com/open-mmlab/mmsegmentation/pull/330)) | |
| - Add more UNet benchmarks ([#324](https://github.com/open-mmlab/mmsegmentation/pull/324)) | |
| - Support Lovasz Loss ([#351](https://github.com/open-mmlab/mmsegmentation/pull/351)) | |
| **Improvements** | |
| - Move train_cfg/test_cfg inside model ([#341](https://github.com/open-mmlab/mmsegmentation/pull/341)) | |
| ### V0.10 (01/01/2021) | |
| **Highlights** | |
| - Support MobileNetV3, DMNet, APCNet. Add models of ResNet18V1b, ResNet18V1c, ResNet50V1b. | |
| **Bug Fixes** | |
| - Fixed CPU TTA ([#276](https://github.com/open-mmlab/mmsegmentation/pull/276)) | |
| - Fixed CI for pip 20.3 ([#307](https://github.com/open-mmlab/mmsegmentation/pull/307)) | |
| **New Features** | |
| - Add ResNet18V1b, ResNet18V1c, ResNet50V1b, ResNet101V1b models ([#316](https://github.com/open-mmlab/mmsegmentation/pull/316)) | |
| - Support MobileNetV3 ([#268](https://github.com/open-mmlab/mmsegmentation/pull/268)) | |
| - Add 4 retinal vessel segmentation benchmark ([#315](https://github.com/open-mmlab/mmsegmentation/pull/315)) | |
| - Support DMNet ([#313](https://github.com/open-mmlab/mmsegmentation/pull/313)) | |
| - Support APCNet ([#299](https://github.com/open-mmlab/mmsegmentation/pull/299)) | |
| **Improvements** | |
| - Refactor Documentation page ([#311](https://github.com/open-mmlab/mmsegmentation/pull/311)) | |
| - Support resize data augmentation according to original image size ([#291](https://github.com/open-mmlab/mmsegmentation/pull/291)) | |
| ### V0.9 (30/11/2020) | |
| **Highlights** | |
| - Support 4 medical dataset, UNet and CGNet. | |
| **New Features** | |
| - Support RandomRotate transform ([#215](https://github.com/open-mmlab/mmsegmentation/pull/215), [#260](https://github.com/open-mmlab/mmsegmentation/pull/260)) | |
| - Support RGB2Gray transform ([#227](https://github.com/open-mmlab/mmsegmentation/pull/227)) | |
| - Support Rerange transform ([#228](https://github.com/open-mmlab/mmsegmentation/pull/228)) | |
| - Support ignore_index for BCE loss ([#210](https://github.com/open-mmlab/mmsegmentation/pull/210)) | |
| - Add modelzoo statistics ([#263](https://github.com/open-mmlab/mmsegmentation/pull/263)) | |
| - Support Dice evaluation metric ([#225](https://github.com/open-mmlab/mmsegmentation/pull/225)) | |
| - Support Adjust Gamma transform ([#232](https://github.com/open-mmlab/mmsegmentation/pull/232)) | |
| - Support CLAHE transform ([#229](https://github.com/open-mmlab/mmsegmentation/pull/229)) | |
| **Bug Fixes** | |
| - Fixed detail API link ([#267](https://github.com/open-mmlab/mmsegmentation/pull/267)) | |
| ### V0.8 (03/11/2020) | |
| **Highlights** | |
| - Support 4 medical dataset, UNet and CGNet. | |
| **New Features** | |
| - Support customize runner ([#118](https://github.com/open-mmlab/mmsegmentation/pull/118)) | |
| - Support UNet ([#161](https://github.com/open-mmlab/mmsegmentation/pull/162)) | |
| - Support CHASE_DB1, DRIVE, STARE, HRD ([#203](https://github.com/open-mmlab/mmsegmentation/pull/203)) | |
| - Support CGNet ([#223](https://github.com/open-mmlab/mmsegmentation/pull/223)) | |
| ### V0.7 (07/10/2020) | |
| **Highlights** | |
| - Support Pascal Context dataset and customizing class dataset. | |
| **Bug Fixes** | |
| - Fixed CPU inference ([#153](https://github.com/open-mmlab/mmsegmentation/pull/153)) | |
| **New Features** | |
| - Add DeepLab OS16 models ([#154](https://github.com/open-mmlab/mmsegmentation/pull/154)) | |
| - Support Pascal Context dataset ([#133](https://github.com/open-mmlab/mmsegmentation/pull/133)) | |
| - Support customizing dataset classes ([#71](https://github.com/open-mmlab/mmsegmentation/pull/71)) | |
| - Support customizing dataset palette ([#157](https://github.com/open-mmlab/mmsegmentation/pull/157)) | |
| **Improvements** | |
| - Support 4D tensor output in ONNX ([#150](https://github.com/open-mmlab/mmsegmentation/pull/150)) | |
| - Remove redundancies in ONNX export ([#160](https://github.com/open-mmlab/mmsegmentation/pull/160)) | |
| - Migrate to MMCV DepthwiseSeparableConv ([#158](https://github.com/open-mmlab/mmsegmentation/pull/158)) | |
| - Migrate to MMCV collect_env ([#137](https://github.com/open-mmlab/mmsegmentation/pull/137)) | |
| - Use img_prefix and seg_prefix for loading ([#153](https://github.com/open-mmlab/mmsegmentation/pull/153)) | |
| ### V0.6 (10/09/2020) | |
| **Highlights** | |
| - Support new methods i.e. MobileNetV2, EMANet, DNL, PointRend, Semantic FPN, Fast-SCNN, ResNeSt. | |
| **Bug Fixes** | |
| - Fixed sliding inference ONNX export ([#90](https://github.com/open-mmlab/mmsegmentation/pull/90)) | |
| **New Features** | |
| - Support MobileNet v2 ([#86](https://github.com/open-mmlab/mmsegmentation/pull/86)) | |
| - Support EMANet ([#34](https://github.com/open-mmlab/mmsegmentation/pull/34)) | |
| - Support DNL ([#37](https://github.com/open-mmlab/mmsegmentation/pull/37)) | |
| - Support PointRend ([#109](https://github.com/open-mmlab/mmsegmentation/pull/109)) | |
| - Support Semantic FPN ([#94](https://github.com/open-mmlab/mmsegmentation/pull/94)) | |
| - Support Fast-SCNN ([#58](https://github.com/open-mmlab/mmsegmentation/pull/58)) | |
| - Support ResNeSt backbone ([#47](https://github.com/open-mmlab/mmsegmentation/pull/47)) | |
| - Support ONNX export (experimental) ([#12](https://github.com/open-mmlab/mmsegmentation/pull/12)) | |
| **Improvements** | |
| - Support Upsample in ONNX ([#100](https://github.com/open-mmlab/mmsegmentation/pull/100)) | |
| - Support Windows install (experimental) ([#75](https://github.com/open-mmlab/mmsegmentation/pull/75)) | |
| - Add more OCRNet results ([#20](https://github.com/open-mmlab/mmsegmentation/pull/20)) | |
| - Add PyTorch 1.6 CI ([#64](https://github.com/open-mmlab/mmsegmentation/pull/64)) | |
| - Get version and githash automatically ([#55](https://github.com/open-mmlab/mmsegmentation/pull/55)) | |
| ### v0.5.1 (11/08/2020) | |
| **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) | |