github open-mmlab/mmdetection v2.23.0
MMDetection V2.23.0 Release

latest releases: v3.3.0, v3.2.0, v3.1.0...
2 years ago

Highlights

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

Full Changelog: v2.22.0...v2.23.0

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