2020-08-11 19:23:35 +08:00
## Changelog
2021-09-01 22:43:38 +08:00
### V0.17 (09/01/2021)
**Highlights**
- Support SegFormer
- Support DPT
- Support Dark Zurich and Nighttime Driving datasets
- Support progressive evaluation
**New Features**
- Support SegFormer ([#599 ](https://github.com/open-mmlab/mmsegmentation/pull/599 ))
- Support DPT ([#605 ](https://github.com/open-mmlab/mmsegmentation/pull/605 ))
- Support Dark Zurich and Nighttime Driving datasets ([#815 ](https://github.com/open-mmlab/mmsegmentation/pull/815 ))
- Support progressive evaluation ([#709 ](https://github.com/open-mmlab/mmsegmentation/pull/709 ))
**Improvements**
- Add multiscale_output interface and unittests for HRNet ([#830 ](https://github.com/open-mmlab/mmsegmentation/pull/830 ))
- Support inherit cityscapes dataset ([#750 ](https://github.com/open-mmlab/mmsegmentation/pull/750 ))
- Fix some typos in README.md ([#824 ](https://github.com/open-mmlab/mmsegmentation/pull/824 ))
- Delete convert function and add instruction to ViT/Swin README.md ([#791 ](https://github.com/open-mmlab/mmsegmentation/pull/791 ))
- Add vit/swin/mit convert weight scripts ([#783 ](https://github.com/open-mmlab/mmsegmentation/pull/783 ))
- Add copyright files ([#796 ](https://github.com/open-mmlab/mmsegmentation/pull/796 ))
**Bug Fixes**
- Fix invalid checkpoint link in inference_demo.ipynb ([#814 ](https://github.com/open-mmlab/mmsegmentation/pull/814 ))
- Ensure that items in dataset have the same order across multi machine ([#780 ](https://github.com/open-mmlab/mmsegmentation/pull/780 ))
- Fix the log error ([#766 ](https://github.com/open-mmlab/mmsegmentation/pull/766 ))
2021-08-04 17:17:39 +08:00
### V0.16 (08/04/2021)
**Highlights**
- Support PyTorch 1.9
- Support SegFormer backbone MiT
- Support md2yml pre-commit hook
- Support frozen stage for HRNet
**New Features**
- Support SegFormer backbone MiT ([#594 ](https://github.com/open-mmlab/mmsegmentation/pull/594 ))
- Support md2yml pre-commit hook ([#732 ](https://github.com/open-mmlab/mmsegmentation/pull/732 ))
- Support mim ([#717 ](https://github.com/open-mmlab/mmsegmentation/pull/717 ))
- Add mmseg2torchserve tool ([#552 ](https://github.com/open-mmlab/mmsegmentation/pull/552 ))
**Improvements**
- Support hrnet frozen stage ([#743 ](https://github.com/open-mmlab/mmsegmentation/pull/743 ))
- Add template of reimplementation questions ([#741 ](https://github.com/open-mmlab/mmsegmentation/pull/741 ))
- Output pdf and epub formats for readthedocs ([#742 ](https://github.com/open-mmlab/mmsegmentation/pull/742 ))
- Refine the docstring of ResNet ([#723 ](https://github.com/open-mmlab/mmsegmentation/pull/723 ))
- Replace interpolate with resize ([#731 ](https://github.com/open-mmlab/mmsegmentation/pull/731 ))
- Update resource limit ([#700 ](https://github.com/open-mmlab/mmsegmentation/pull/700 ))
- Update config.md ([#678 ](https://github.com/open-mmlab/mmsegmentation/pull/678 ))
**Bug Fixes**
- Fix ATTENTION registry ([#729 ](https://github.com/open-mmlab/mmsegmentation/pull/729 ))
- Fix analyze log script ([#716 ](https://github.com/open-mmlab/mmsegmentation/pull/716 ))
- Fix doc api display ([#725 ](https://github.com/open-mmlab/mmsegmentation/pull/725 ))
- Fix patch_embed and pos_embed mismatch error ([#685 ](https://github.com/open-mmlab/mmsegmentation/pull/685 ))
- Fix efficient test for multi-node ([#707 ](https://github.com/open-mmlab/mmsegmentation/pull/707 ))
- Fix init_cfg in resnet backbone ([#697 ](https://github.com/open-mmlab/mmsegmentation/pull/697 ))
- Fix efficient test bug ([#702 ](https://github.com/open-mmlab/mmsegmentation/pull/702 ))
- Fix url error in config docs ([#680 ](https://github.com/open-mmlab/mmsegmentation/pull/680 ))
- Fix mmcv installation ([#676 ](https://github.com/open-mmlab/mmsegmentation/pull/676 ))
- Fix torch version ([#670 ](https://github.com/open-mmlab/mmsegmentation/pull/670 ))
**Contributors**
@sshuair @xiexinch @Junjun2016 @mmeendez8 @xvjiarui @sennnnn @puhsu @BIGWangYuDong @keke1u @daavoo
2021-07-04 01:09:17 -07:00
### V0.15 (07/04/2021)
**Highlights**
- Support ViT, SETR, and Swin-Transformer
- Add Chinese documentation
- Unified parameter initialization
**Bug Fixes**
- Fix typo and links ([#608 ](https://github.com/open-mmlab/mmsegmentation/pull/608 ))
- Fix Dockerfile ([#607 ](https://github.com/open-mmlab/mmsegmentation/pull/607 ))
- Fix ViT init ([#609 ](https://github.com/open-mmlab/mmsegmentation/pull/609 ))
- Fix mmcv version compatible table ([#658 ](https://github.com/open-mmlab/mmsegmentation/pull/658 ))
- Fix model links of DMNEt ([#660 ](https://github.com/open-mmlab/mmsegmentation/pull/660 ))
**New Features**
- Support loading DeiT weights ([#538 ](https://github.com/open-mmlab/mmsegmentation/pull/538 ))
- Support SETR ([#531 ](https://github.com/open-mmlab/mmsegmentation/pull/531 ), [#635 ](https://github.com/open-mmlab/mmsegmentation/pull/635 ))
- Add config and models for ViT backbone with UperHead ([#520 ](https://github.com/open-mmlab/mmsegmentation/pull/531 ), [#635 ](https://github.com/open-mmlab/mmsegmentation/pull/520 ))
- Support Swin-Transformer ([#511 ](https://github.com/open-mmlab/mmsegmentation/pull/511 ))
- Add higher accuracy FastSCNN ([#606 ](https://github.com/open-mmlab/mmsegmentation/pull/606 ))
- Add Chinese documentation ([#666 ](https://github.com/open-mmlab/mmsegmentation/pull/666 ))
**Improvements**
- Unified parameter initialization ([#567 ](https://github.com/open-mmlab/mmsegmentation/pull/567 ))
- Separate CUDA and CPU in github action CI ([#602 ](https://github.com/open-mmlab/mmsegmentation/pull/602 ))
- Support persistent dataloader worker ([#646 ](https://github.com/open-mmlab/mmsegmentation/pull/646 ))
- Update meta file fields ([#661 ](https://github.com/open-mmlab/mmsegmentation/pull/661 ), [#664 ](https://github.com/open-mmlab/mmsegmentation/pull/664 ))
2021-06-02 18:43:08 -07:00
### V0.14 (06/02/2021)
**Highlights**
- Support ONNX to TensorRT
- Support MIM
**Bug Fixes**
- Fix ONNX to TensorRT verify ([#547 ](https://github.com/open-mmlab/mmsegmentation/pull/547 ))
- Fix save best for EvalHook ([#575 ](https://github.com/open-mmlab/mmsegmentation/pull/575 ))
**New Features**
- Support loading DeiT weights ([#538 ](https://github.com/open-mmlab/mmsegmentation/pull/538 ))
- Support ONNX to TensorRT ([#542 ](https://github.com/open-mmlab/mmsegmentation/pull/542 ))
- Support output results for ADE20k ([#544 ](https://github.com/open-mmlab/mmsegmentation/pull/544 ))
- Support MIM ([#549 ](https://github.com/open-mmlab/mmsegmentation/pull/549 ))
**Improvements**
- Add option for ViT output shape ([#530 ](https://github.com/open-mmlab/mmsegmentation/pull/530 ))
- Infer batch size using len(result) ([#532 ](https://github.com/open-mmlab/mmsegmentation/pull/532 ))
- Add compatible table between MMSeg and MMCV ([#558 ](https://github.com/open-mmlab/mmsegmentation/pull/558 ))
2021-05-05 16:56:19 -07:00
### V0.13 (05/05/2021)
**Highlights**
- Support Pascal Context Class-59 dataset.
- Support Visual Transformer Backbone.
- Support mFscore metric.
**Bug Fixes**
- Fixed Colaboratory tutorial ([#451 ](https://github.com/open-mmlab/mmsegmentation/pull/451 ))
- Fixed mIoU calculation range ([#471 ](https://github.com/open-mmlab/mmsegmentation/pull/471 ))
- Fixed sem_fpn, unet README.md ([#492 ](https://github.com/open-mmlab/mmsegmentation/pull/492 ))
- Fixed `num_classes` in FCN for Pascal Context 60-class dataset ([#488 ](https://github.com/open-mmlab/mmsegmentation/pull/488 ))
- Fixed FP16 inference ([#497 ](https://github.com/open-mmlab/mmsegmentation/pull/497 ))
**New Features**
- Support dynamic export and visualize to pytorch2onnx ([#463 ](https://github.com/open-mmlab/mmsegmentation/pull/463 ))
- Support export to torchscript ([#469 ](https://github.com/open-mmlab/mmsegmentation/pull/469 ), [#499 ](https://github.com/open-mmlab/mmsegmentation/pull/499 ))
- Support Pascal Context Class-59 dataset ([#459 ](https://github.com/open-mmlab/mmsegmentation/pull/459 ))
- Support Visual Transformer backbone ([#465 ](https://github.com/open-mmlab/mmsegmentation/pull/465 ))
- Support UpSample Neck ([#512 ](https://github.com/open-mmlab/mmsegmentation/pull/512 ))
- Support mFscore metric ([#509 ](https://github.com/open-mmlab/mmsegmentation/pull/509 ))
**Improvements**
- Add more CI for PyTorch ([#460 ](https://github.com/open-mmlab/mmsegmentation/pull/460 ))
- Add print model graph args for tools/print_config.py ([#451 ](https://github.com/open-mmlab/mmsegmentation/pull/451 ))
- Add cfg links in modelzoo README.md ([#468 ](https://github.com/open-mmlab/mmsegmentation/pull/469 ))
- Add BaseSegmentor import to segmentors/__init__.py ([#495 ](https://github.com/open-mmlab/mmsegmentation/pull/495 ))
- Add MMOCR, MMGeneration links ([#501 ](https://github.com/open-mmlab/mmsegmentation/pull/501 ), [#506 ](https://github.com/open-mmlab/mmsegmentation/pull/506 ))
- Add Chinese QR code ([#506 ](https://github.com/open-mmlab/mmsegmentation/pull/506 ))
- Use MMCV MODEL_REGISTRY ([#515 ](https://github.com/open-mmlab/mmsegmentation/pull/515 ))
- Add ONNX testing tools ([#498 ](https://github.com/open-mmlab/mmsegmentation/pull/498 ))
- Replace data_dict calling 'img' key to support MMDet3D ([#514 ](https://github.com/open-mmlab/mmsegmentation/pull/514 ))
- Support reading class_weight from file in loss function ([#513 ](https://github.com/open-mmlab/mmsegmentation/pull/513 ))
- Make tags as comment ([#505 ](https://github.com/open-mmlab/mmsegmentation/pull/505 ))
- Use MMCV EvalHook ([#438 ](https://github.com/open-mmlab/mmsegmentation/pull/438 ))
2021-04-03 21:02:56 -07:00
### V0.12 (04/03/2021)
**Highlights**
- Support FCN-Dilate 6 model.
- Support Dice Loss.
**Bug Fixes**
- Fixed PhotoMetricDistortion Doc ([#388 ](https://github.com/open-mmlab/mmsegmentation/pull/388 ))
- Fixed install scripts ([#399 ](https://github.com/open-mmlab/mmsegmentation/pull/399 ))
- Fixed Dice Loss multi-class ([#417 ](https://github.com/open-mmlab/mmsegmentation/pull/417 ))
**New Features**
- Support Dice Loss ([#396 ](https://github.com/open-mmlab/mmsegmentation/pull/396 ))
- Add plot logs tool ([#426 ](https://github.com/open-mmlab/mmsegmentation/pull/426 ))
- Add opacity option to show_result ([#425 ](https://github.com/open-mmlab/mmsegmentation/pull/425 ))
- Speed up mIoU metric ([#430 ](https://github.com/open-mmlab/mmsegmentation/pull/430 ))
**Improvements**
- Refactor unittest file structure ([#440 ](https://github.com/open-mmlab/mmsegmentation/pull/440 ))
- Fix typos in the repo ([#449 ](https://github.com/open-mmlab/mmsegmentation/pull/449 ))
- Include class-level metrics in the log ([#445 ](https://github.com/open-mmlab/mmsegmentation/pull/445 ))
2021-02-02 15:09:20 -08:00
### 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 ))
2021-01-02 15:29:56 -08:00
### 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**
2021-01-04 23:52:40 -08:00
- Add ResNet18V1b, ResNet18V1c, ResNet50V1b, ResNet101V1b models ([#316 ](https://github.com/open-mmlab/mmsegmentation/pull/316 ))
2021-01-02 15:29:56 -08:00
- 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 ))
2020-12-01 21:10:55 -08:00
### 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 ))
2020-11-04 16:18:02 -08:00
### 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 ))
2020-10-10 19:19:52 +08:00
### 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 ))
2020-09-10 20:57:18 +08:00
### V0.6 (10/09/2020)
2020-10-07 19:50:16 +08:00
2020-09-10 20:57:18 +08:00
**Highlights**
2020-10-07 19:50:16 +08:00
- Support new methods i.e. MobileNetV2, EMANet, DNL, PointRend, Semantic FPN, Fast-SCNN, ResNeSt.
2020-09-10 20:57:18 +08:00
**Bug Fixes**
2020-10-07 19:50:16 +08:00
2020-09-10 20:57:18 +08:00
- Fixed sliding inference ONNX export ([#90 ](https://github.com/open-mmlab/mmsegmentation/pull/90 ))
**New Features**
2020-10-07 19:50:16 +08:00
2020-09-10 20:57:18 +08:00
- 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**
2020-10-07 19:50:16 +08:00
2020-09-10 20:57:18 +08:00
- 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 ))
2020-08-11 19:23:35 +08:00
### v0.5.1 (11/08/2020)
2020-10-07 19:50:16 +08:00
2020-08-11 19:23:35 +08:00
**Highlights**
2020-10-07 19:50:16 +08:00
2020-08-11 19:23:35 +08:00
- Support FP16 and more generalized OHEM
2020-10-07 19:50:16 +08:00
2020-08-11 19:23:35 +08:00
**Bug Fixes**
2020-10-07 19:50:16 +08:00
2020-08-11 19:23:35 +08:00
- Fixed Pascal VOC conversion script (#19 )
- Fixed OHEM weight assign bug (#54 )
- Fixed palette type when palette is not given (#27 )
2020-10-07 19:50:16 +08:00
2020-08-11 19:23:35 +08:00
**New Features**
2020-10-07 19:50:16 +08:00
2020-08-11 19:23:35 +08:00
- Support FP16 (#21 )
- Generalized OHEM (#54 )
2020-10-07 19:50:16 +08:00
2020-08-11 19:23:35 +08:00
**Improvements**
2020-10-07 19:50:16 +08:00
2020-08-11 19:23:35 +08:00
- Add load-from flag (#33 )
- Fixed training tricks doc about different learning rates of model (#26 )
