Releases: open-mmlab/mmsegmentation
Releases · open-mmlab/mmsegmentation
MMSegmentation v0.25.0 Release
What's Changed
Highlights
- Support PyTorch backend on MLU (1515)
Bug Fixes
- Fix the error of BCE loss when batch size is 1 (1629)
- Fix bug of
resize
function when align_corners is True (1592) - Fix Dockerfile to run demo script in docker container (1568)
- Correct inference_demo.ipynb path (1576)
- Fix the
build_segmentor
in colab demo (1551) - Fix md2yml script (1633, 1555)
- Fix main line link in MAE README.md (1556)
- Fix fastfcn
crop_size
in README.md by (1597) - Pip upgrade when testing windows platform (1610)
Improvements
Documentation
- Rewrite the installation guidance (1630)
- Format readme (1635)
- Replace markdownlint with mdformat to avoid ruby installation (1591)
- Add explanation and usage instructions for data configuration (1548)
- Configure Myst-parser to parse anchor tag (1589)
- Update QR code and link for QQ group (1598, 1574)
Contributors
- @atinfinity made their first contribution in #1568
- @DoubleChuang made their first contribution in #1576
- @alpha-baymax made their first contribution in #1515
- @274869388 made their first contribution in #1629
Full Changelog: v0.24.1...v0.25.0
MMSegmentation v0.24.1 Release
What's Changed
Full Changelog: v0.24.0...v0.24.1
MMSegmentation v0.24.0 Release
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, 1523)
- Support Resnet strikes back (1390)
- Support extra dataloader settings in configs (1435)
Bug Fixes
- Fix input previous results for the last cascade_decode_head (#1450)
- Fix validation loss logging (#1494)
- Fix the bug in binary_cross_entropy (1527)
- Support single channel prediction for Binary Cross Entropy Loss (#1454)
- Fix potential bugs in accuracy.py (1496)
- Avoid converting label ids twice by label map during evaluation (1417)
- Fix bug about label_map (1445)
- Fix image save path bug in Windows (1423)
- Fix MMSegmentation Colab demo (1501, 1452)
- Migrate azure blob for beit checkpoints (1503)
- Fix bug in
tools/analyse_logs.py
caused by wrong plot_iter in some cases (1428)
Improvements
- Merge BEiT and ConvNext's LR decay optimizer constructors (#1438)
- Register optimizer constructor with mmseg (#1456)
- Refactor transformer encode layer in ViT and BEiT backbone (#1481)
- Add
build_pos_embed
andbuild_layers
for BEiT (1517) - Add
with_cp
to mit and vit (1431) - Fix inconsistent dtype of
seg_label
in stdc decode (1463) - Delete random seed for training in
dist_train.sh
(1519) - Revise high
workers_per_gpus
in config file (#1506) - Add GPG keys and del mmcv version in Dockerfile (1534)
- Update checkpoint for model in deeplabv3plus (#1487)
- Add
DistSamplerSeedHook
to set epoch number to dataloader when runner isEpochBasedRunner
(1449) - Provide URLs of Swin Transformer pretrained models (1389)
- Updating Dockerfiles From Docker Directory and
get_started.md
to reach latest stable version of Python, PyTorch and MMCV (1446)
Documentation
- Add more clearly statement of CPU training/inference (1518)
New Contributors
- @jiangyitong made their first contribution in #1431
- @kahkeng made their first contribution in #1447
- @Nourollah made their first contribution in #1446
- @androbaza made their first contribution in #1452
- @Yzichen made their first contribution in #1445
- @whu-pzhang made their first contribution in #1423
- @panfeng-hover made their first contribution in #1417
- @Johnson-Wang made their first contribution in #1496
- @jere357 made their first contribution in #1460
- @mfernezir made their first contribution in #1494
- @donglixp made their first contribution in #1503
- @YuanLiuuuuuu made their first contribution in #1307
- @Dawn-bin made their first contribution in #1527
Full Changelog: v0.23.0...v0.24.0
MMSegmentation v0.23.0 Release
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)
- Support K-Net: Towards Unified Image Segmentation (#1289)
- Support dataset initialization with file client (#1402)
- Add class name function for STARE datasets (#1376)
- Support different seeds on different ranks when distributed training (#1362)
- Add
nlc2nchw2nlc
andnchw2nlc2nchw
to simplify tensor with different dimension operation (#1249)
Improvements
- Synchronize random seed for distributed sampler (#1411)
- Add script and documentation for multi-machine distributed training (#1383)
Bug Fixes
- Add
avg_non_ignore
of CELoss to support average loss over non-ignored elements (#1409) - Fix some wrong URLs of models or logs in
./configs
(#1336) - Add title and color theme arguments to plot function in
tools/confusion_matrix.py
(#1401) - Fix outdated link in Colab demo (#1392)
- Fix typos (#1424, #1405, #1371, #1366, #1363)
Documentation
New Contributors
- @kinglintianxia made their first contribution in #1371
- @CCODING04 made their first contribution in #1376
- @mob5566 made their first contribution in #1401
- @xiongnemo made their first contribution in #1392
- @Xiangxu-0103 made their first contribution in #1405
MMSegmentation v0.22.1 Release
MMSegmentation v0.22.0 Release
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)
- Support iSAID aerial Dataset. (#1115
- Generating and plotting confusion matrix. (#1301)
Improvements
- Refactor 4 decoder heads (ASPP, FCN, PSP, UPer): Split forward function into
_forward_feature
andcls_seg
. (#1299) - Add
min_size
arg inResize
to keep the shape after resize bigger than slide window. (#1318) - Revise pre-commit-hooks. (#1315)
- Add win-ci. (#1296)
Bug Fixes
- Fix
mlp_ratio
type in Swin Transformer. (#1274) - Fix path errors in
./demo
. (#1269) - Fix bug in conversion of potsdam. (#1279)
- Make accuracy take into account
ignore_index
. (#1259) - Add Pytorch HardSwish assertion in unit test. (#1294)
- Fix wrong palette value in vaihingen. (#1292)
- Fix the bug that SETR cannot load pretrain. (#1293)
- Update correct
In Collection
in metafile of each configs. (#1239) - Upload completed STDC models. (#1332)
- Fix
DNLHead
exports onnx inference difference type Cast error. (#1161)
Contributors
- @JiaYanhao made their first contribution in #1269
- @andife made their first contribution in #1281
- @SBCV made their first contribution in #1279
- @HJoonKwon made their first contribution in #1259
- @Tsingularity made their first contribution in #1290
- @Waterman0524 made their first contribution in #1115
- @MeowZheng made their first contribution in #1315
- @linfangjian01 made their first contribution in #1318
MMSegmentation v0.21.1 Release
Bug Fixes
- Fix repeating log by
setup_multi_processes
. (#1267) - Fix typos in docs. (#1263)
- Upgrade isort in pre-commit hook. (#1270)
Improvements
- Use MMCV load_state_dict function in ViT/Swin. (#1272)
- Add exception for PointRend for support CPU-only. (#1271)
New Contributors
- @RangeKing made their first contribution in #1263
MMSegmentation v0.21.0 Release
Highlights
- Officially Support CPUs training and inference, please use the latest MMCV (1.4.4) to try it out.
- Support Segmenter: Transformer for Semantic Segmentation (ICCV'2021).
- Support ISPRS Potsdam and Vaihingen Dataset.
- Add Mosaic transform and
MultiImageMixDataset
class indataset_wrappers
.
New Features
- Support Segmenter: Transformer for Semantic Segmentation (ICCV'2021) (#955)
- Support ISPRS Potsdam and Vaihingen Dataset (#1097, #1171)
- Add segformer‘s benchmark on cityscapes (#1155)
- Add auto resume (#1172)
- Add Mosaic transform and
MultiImageMixDataset
class indataset_wrappers
(#1093, #1105) - Add log collector (#1175)
Improvements
- New-style CPU training and inference (#1251)
- Add UNet benchmark with multiple losses supervision (#1143)
Bug Fixes
- Fix the model statistics in doc for readthedoc (#1153)
- Set random seed for
palette
if not given (#1152) - Add
COCOStuffDataset
inclass_names.py
(#1222) - Fix bug in non-distributed multi-gpu training/testing (#1247)
- Delete unnecessary lines of STDCHead (#1231)
New Contributors
- @jbwang1997 made their first contribution in #1152
- @BeaverCC made their first contribution in #1206
- @Echo-minn made their first contribution in #1214
- @rstrudel made their first contribution in #955
MMSegmentation v0.20.2 Release
What's Changed
- [Fix] Revise
--option
to--options
in #1140.
Publish this version is to avoid BC-Breaking problem caused by v0.20.1.
Contributors:
@RockeyCoss
MMSegmentation v0.20.1 Release
Improvements
- Change options to cfg-options (#1129)
Bug Fixes
- Fix
<!-- [ABSTRACT] -->
in metafile. (#1127) - Fix correct
num_classes
of HRNet inLoveDA
dataset (#1136)
Contributors
@MengzhangLI
@RockeyCoss