Highlights

• Support Mask2Former: Masked-attention Mask Transformer for Universal Image Segmentation
• Support EfficientNet: EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
• Support setting data root through environment variable MMDET_DATASETS, users don't have to modify the corresponding path in config files anymore.
• Find a good recipe for fine-tuning high precision ResNet backbone pre-trained by Torchvision.

New Features

• Support Mask2Former(#6938)(#7466)(#7471)
• Support EfficientNet (#7514)
• Support setting data root through environment variable MMDET_DATASETS, users don't have to modify the corresponding path in config files anymore. (#7386)
• Support setting different seeds to different ranks (#7432)
• Update the dist_train.sh so that the script can be used to support launching multi-node training on machines without slurm (#7415)
• Find a good recipe for fine-tuning high precision ResNet backbone pre-trained by Torchvision (#7489)

Bug Fixes

• Fix bug in VOC unit test which removes the data directory (#7270)
• Adjust the order of get_classes and FileClient (#7276)
• Force the inputs of get_bboxes in yolox_head to float32 (#7324)
• Fix misplaced arguments in LoadPanopticAnnotations (#7388)
• Fix reduction=mean in CELoss. (#7449)
• Update unit test of CrossEntropyCost (#7537)
• Fix memory leaking in panpotic segmentation evaluation (#7538)
• Fix the bug of shape broadcast in YOLOv3 (#7551)

Improvements

• Add Chinese version of onnx2tensorrt.md (#7219)
• Update colab tutorials (#7310)
• Update information about Localization Distillation (#7350)
• Add Chinese version of finetune.md (#7178)
• Update YOLOX log for non square input (#7235)
• Add nproc in coco_panoptic.py for panoptic quality computing (#7315)
• Allow to set channel_order in LoadImageFromFile (#7258)
• Take point sample related functions out of mask_point_head (#7353)
• Add instance evaluation for coco_panoptic (#7313)
• Enhance the robustness of analyze_logs.py (#7407)
• Supplementary notes of sync_random_seed (#7440)
• Update docstring of cross entropy loss (#7472)
• Update pascal voc result (#7503)
• We create How-to documentation to record any questions about How to xxx. In this version, we added
  • How to use Mosaic augmentation (#7507)
  • How to use backbone in mmcls (#7438)
  • How to produce and submit the prediction results of panoptic segmentation models on COCO test-dev set (#7430))

Contributors

A total of 27 developers contributed to this release. Thanks @ZwwWayne, @haofanwang, @shinya7y, @chhluo, @yangrisheng, @triple-Mu, @jbwang1997, @HikariTJU, @imflash217, @274869388, @zytx121, @matrixgame2018, @jamiechoi1995, @BIGWangYuDong, @JingweiZhang12, @Xiangxu-0103, @hhaAndroid, @jshilong, @osbm, @ceroytres, @bunge-bedstraw-herb, @Youth-Got, @daavoo, @jiangyitong, @RangiLyu, @CCODING04, @yarkable

New Contributors

• @triple-Mu made their first contribution in https://github.com/open-mmlab/mmdetection/pull/7219
• @yangrisheng made their first contribution in https://github.com/open-mmlab/mmdetection/pull/7180
• @imflash217 made their first contribution in https://github.com/open-mmlab/mmdetection/pull/7398
• @osbm made their first contribution in https://github.com/open-mmlab/mmdetection/pull/7498
• @ceroytres made their first contribution in https://github.com/open-mmlab/mmdetection/pull/7510
• @bunge-bedstraw-herb made their first contribution in https://github.com/open-mmlab/mmdetection/pull/7507
• @Youth-Got made their first contribution in https://github.com/open-mmlab/mmdetection/pull/7521
• @CCODING04 made their first contribution in https://github.com/open-mmlab/mmdetection/pull/7386

Full Changelog: https://github.com/open-mmlab/mmdetection/compare/v2.22.0...v2.23.0