Mmsegmentation

**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))

**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

**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 and UNet ([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))

**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))

**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))

**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))