Mmsegmentation

What's Changed
- Fix `LayerDecayOptimizerConstructor` for MAE training ([1539](https://github.com/open-mmlab/mmsegmentation/pull/1539), [#1540](https://github.com/open-mmlab/mmsegmentation/pull/1540))


**Full Changelog**: https://github.com/open-mmlab/mmsegmentation/compare/v0.24.0...v0.24.1

What's Changed

**Highlights**

- Support MAE: Masked Autoencoders Are Scalable Vision Learners
- Support Resnet strikes back

**New Features**

- Support MAE: Masked Autoencoders Are Scalable Vision Learners ([1307](https://github.com/open-mmlab/mmsegmentation/pull/1307), [1523](https://github.com/open-mmlab/mmsegmentation/pull/1523))
- Support Resnet strikes back ([1390](https://github.com/open-mmlab/mmsegmentation/pull/1390))
- Support extra dataloader settings in configs ([1435](https://github.com/open-mmlab/mmsegmentation/pull/1435))

**Bug Fixes**

- Fix input previous results for the last cascade_decode_head ([1450](https://github.com/open-mmlab/mmsegmentation/pull/1450))
- Fix validation loss logging ([1494](https://github.com/open-mmlab/mmsegmentation/pull/1494))
- Fix the bug in binary_cross_entropy ([1527](https://github.com/open-mmlab/mmsegmentation/pull/1527))
- Support single channel prediction for Binary Cross Entropy Loss ([1454](https://github.com/open-mmlab/mmsegmentation/pull/1454))
- Fix potential bugs in accuracy.py ([1496](https://github.com/open-mmlab/mmsegmentation/pull/1496))
- Avoid converting label ids twice by label map during evaluation ([1417](https://github.com/open-mmlab/mmsegmentation/pull/1417))
- Fix bug about label_map ([1445](https://github.com/open-mmlab/mmsegmentation/pull/1445))
- Fix image save path bug in Windows ([1423](https://github.com/open-mmlab/mmsegmentation/pull/1423))
- Fix MMSegmentation Colab demo ([1501](https://github.com/open-mmlab/mmsegmentation/pull/1501), [1452](https://github.com/open-mmlab/mmsegmentation/pull/1452))
- Migrate azure blob for beit checkpoints ([1503](https://github.com/open-mmlab/mmsegmentation/pull/1503))
- Fix bug in `tools/analyse_logs.py` caused by wrong plot_iter in some cases ([1428](https://github.com/open-mmlab/mmsegmentation/pull/1428))

**Improvements**

- Merge BEiT and ConvNext's LR decay optimizer constructors ([1438](https://github.com/open-mmlab/mmsegmentation/pull/1438))
- Register optimizer constructor with mmseg ([1456](https://github.com/open-mmlab/mmsegmentation/pull/1456))
- Refactor transformer encode layer in ViT and BEiT backbone ([1481](https://github.com/open-mmlab/mmsegmentation/pull/1481))
- Add `build_pos_embed` and `build_layers` for BEiT ([1517](https://github.com/open-mmlab/mmsegmentation/pull/1517))
- Add `with_cp` to mit and vit ([1431](https://github.com/open-mmlab/mmsegmentation/pull/1431))
- Fix inconsistent dtype of `seg_label` in stdc decode ([1463](https://github.com/open-mmlab/mmsegmentation/pull/1463))
- Delete random seed for training in `dist_train.sh` ([1519](https://github.com/open-mmlab/mmsegmentation/pull/1519))
- Revise high `workers_per_gpus` in config file ([1506](https://github.com/open-mmlab/mmsegmentation/pull/1506))
- Add GPG keys and del mmcv version in Dockerfile ([1534](https://github.com/open-mmlab/mmsegmentation/pull/1534))
- Update checkpoint for model in deeplabv3plus ([1487](https://github.com/open-mmlab/mmsegmentation/pull/1487))
- Add `DistSamplerSeedHook` to set epoch number to dataloader when runner is `EpochBasedRunner` ([1449](https://github.com/open-mmlab/mmsegmentation/pull/1449))
- Provide URLs of Swin Transformer pretrained models ([1389](https://github.com/open-mmlab/mmsegmentation/pull/1389))
- Updating Dockerfiles From Docker Directory and `get_started.md` to reach latest stable version of Python, PyTorch and MMCV ([1446](https://github.com/open-mmlab/mmsegmentation/pull/1446))

**Documentation**

- Add more clearly statement of CPU training/inference ([1518](https://github.com/open-mmlab/mmsegmentation/pull/1518))

New Contributors
* jiangyitong made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1431
* kahkeng made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1447
* Nourollah made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1446
* androbaza made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1452
* Yzichen made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1445
* whu-pzhang made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1423
* panfeng-hover made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1417
* Johnson-Wang made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1496
* jere357 made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1460
* mfernezir made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1494
* donglixp made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1503
* YuanLiuuuuuu made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1307
* Dawn-bin made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1527

**Full Changelog**: https://github.com/open-mmlab/mmsegmentation/compare/v0.23.0...v0.24.0

What's Changed

**Highlights**

- Support BEiT: BERT Pre-Training of Image Transformers
- Support K-Net: Towards Unified Image Segmentation
- Add `avg_non_ignore` of CELoss to support average loss over non-ignored elements
- Support dataset initialization with file client

**New Features**

- Support BEiT: BERT Pre-Training of Image Transformers ([1404](https://github.com/open-mmlab/mmsegmentation/pull/1404))
- Support K-Net: Towards Unified Image Segmentation ([1289](https://github.com/open-mmlab/mmsegmentation/pull/1289))
- Support dataset initialization with file client ([1402](https://github.com/open-mmlab/mmsegmentation/pull/1402))
- Add class name function for STARE datasets ([1376](https://github.com/open-mmlab/mmsegmentation/pull/1376))
- Support different seeds on different ranks when distributed training ([1362](https://github.com/open-mmlab/mmsegmentation/pull/1362))
- Add `nlc2nchw2nlc` and `nchw2nlc2nchw` to simplify tensor with different dimension operation ([1249](https://github.com/open-mmlab/mmsegmentation/pull/1249))

**Improvements**

- Synchronize random seed for distributed sampler ([1411](https://github.com/open-mmlab/mmsegmentation/pull/1411))
- Add script and documentation for multi-machine distributed training ([1383](https://github.com/open-mmlab/mmsegmentation/pull/1383))

**Bug Fixes**

- Add `avg_non_ignore` of CELoss to support average loss over non-ignored elements ([1409](https://github.com/open-mmlab/mmsegmentation/pull/1409))
- Fix some wrong URLs of models or logs in `./configs` ([1336](https://github.com/open-mmlab/mmsegmentation/pull/1433))
- Add title and color theme arguments to plot function in `tools/confusion_matrix.py` ([1401](https://github.com/open-mmlab/mmsegmentation/pull/1401))
- Fix outdated link in Colab demo ([1392](https://github.com/open-mmlab/mmsegmentation/pull/1392))
- Fix typos ([1424](https://github.com/open-mmlab/mmsegmentation/pull/1424), [#1405](https://github.com/open-mmlab/mmsegmentation/pull/1405), [#1371](https://github.com/open-mmlab/mmsegmentation/pull/1371), [#1366](https://github.com/open-mmlab/mmsegmentation/pull/1366), [#1363](https://github.com/open-mmlab/mmsegmentation/pull/1363))

**Documentation**

- Add FAQ document ([1420](https://github.com/open-mmlab/mmsegmentation/pull/1420))
- Fix the config name style description in official docs([1414](https://github.com/open-mmlab/mmsegmentation/pull/1414))

New Contributors

* kinglintianxia made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1371
* CCODING04 made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1376
* mob5566 made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1401
* xiongnemo made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1392
* Xiangxu-0103 made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1405

**Bug Fixes**

- Fix the ZeroDivisionError that all pixels in one image is ignored. ([1336](https://github.com/open-mmlab/mmsegmentation/pull/1336))

**Improvements**

- Provide URLs of STDC, Segmenter and Twins pretrained models ([1272](https://github.com/open-mmlab/mmsegmentation/pull/1357))

**Highlights**

- Support ConvNeXt: A ConvNet for the 2020s. Please use the latest MMClassification (0.21.0) to try it out.
- Support iSAID aerial Dataset.
- Officially Support inference on Windows OS.

**New Features**

- Support ConvNeXt: A ConvNet for the 2020s. ([1216](https://github.com/open-mmlab/mmsegmentation/pull/1216))
- Support iSAID aerial Dataset. ([1115](https://github.com/open-mmlab/mmsegmentation/pull/1115)
- Generating and plotting confusion matrix. ([1301](https://github.com/open-mmlab/mmsegmentation/pull/1301))

**Improvements**

- Refactor 4 decoder heads (ASPP, FCN, PSP, UPer): Split forward function into `_forward_feature` and `cls_seg`. ([1299](https://github.com/open-mmlab/mmsegmentation/pull/1299))
- Add `min_size` arg in `Resize` to keep the shape after resize bigger than slide window. ([1318](https://github.com/open-mmlab/mmsegmentation/pull/1318))
- Revise pre-commit-hooks. ([1315](https://github.com/open-mmlab/mmsegmentation/pull/1315))
- Add win-ci. ([1296](https://github.com/open-mmlab/mmsegmentation/pull/1296))

**Bug Fixes**

- Fix `mlp_ratio` type in Swin Transformer. ([1274](https://github.com/open-mmlab/mmsegmentation/pull/1274))
- Fix path errors in `./demo` . ([1269](https://github.com/open-mmlab/mmsegmentation/pull/1269))
- Fix bug in conversion of potsdam. ([1279](https://github.com/open-mmlab/mmsegmentation/pull/1279))
- Make accuracy take into account `ignore_index`. ([1259](https://github.com/open-mmlab/mmsegmentation/pull/1259))
- Add Pytorch HardSwish assertion in unit test. ([1294](https://github.com/open-mmlab/mmsegmentation/pull/1294))
- Fix wrong palette value in vaihingen. ([1292](https://github.com/open-mmlab/mmsegmentation/pull/1292))
- Fix the bug that SETR cannot load pretrain. ([1293](https://github.com/open-mmlab/mmsegmentation/pull/1293))
- Update correct `In Collection` in metafile of each configs. ([1239](https://github.com/open-mmlab/mmsegmentation/pull/1239))
- Upload completed STDC models. ([1332](https://github.com/open-mmlab/mmsegmentation/pull/1332))
- Fix `DNLHead` exports onnx inference difference type Cast error. ([1161](https://github.com/open-mmlab/mmsegmentation/pull/1332))


**Contributors**

- JiaYanhao made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1269
- andife made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1281
- SBCV made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1279
- HJoonKwon made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1259
- Tsingularity made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1290
- Waterman0524 made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1115
- MeowZheng made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1315
- linfangjian01 made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1318

**Bug Fixes**

- Fix repeating log by `setup_multi_processes`. ([1267](https://github.com/open-mmlab/mmsegmentation/pull/1267))
- Fix typos in docs. ([1263](https://github.com/open-mmlab/mmsegmentation/pull/1263))
- Upgrade isort in pre-commit hook. ([1270](https://github.com/open-mmlab/mmsegmentation/pull/1270))

**Improvements**

- Use MMCV load_state_dict function in ViT/Swin. ([1272](https://github.com/open-mmlab/mmsegmentation/pull/1272))
- Add exception for PointRend for support CPU-only. ([1271](https://github.com/open-mmlab/mmsegmentation/pull/1270))

**New Contributors**
* RangeKing made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1263