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 and build_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 is EpochBasedRunner (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 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