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Changelog

V0.14 (06/02/2021)

Highlights

  • Support ONNX to TensorRT
  • Support MIM

Bug Fixes

  • Fix ONNX to TensorRT verify (#547)
  • Fix save best for EvalHook (#575)

New Features

  • Support loading DeiT weights (#538)
  • Support ONNX to TensorRT (#542)
  • Support output results for ADE20k (#544)
  • Support MIM (#549)

Improvements

  • Add option for ViT output shape (#530)
  • Infer batch size using len(result) (#532)
  • Add compatible table between MMSeg and MMCV (#558)

V0.13 (05/05/2021)

Highlights

  • Support Pascal Context Class-59 dataset.
  • Support Visual Transformer Backbone.
  • Support mFscore metric.

Bug Fixes

  • Fixed Colaboratory tutorial (#451)
  • Fixed mIoU calculation range (#471)
  • Fixed sem_fpn, unet README.md (#492)
  • Fixed num_classes in FCN for Pascal Context 60-class dataset (#488)
  • Fixed FP16 inference (#497)

New Features

  • Support dynamic export and visualize to pytorch2onnx (#463)
  • Support export to torchscript (#469, #499)
  • Support Pascal Context Class-59 dataset (#459)
  • Support Visual Transformer backbone (#465)
  • Support UpSample Neck (#512)
  • Support mFscore metric (#509)

Improvements

  • Add more CI for PyTorch (#460)
  • Add print model graph args for tools/print_config.py (#451)
  • Add cfg links in modelzoo README.md (#468)
  • Add BaseSegmentor import to segmentors/init.py (#495)
  • Add MMOCR, MMGeneration links (#501, #506)
  • Add Chinese QR code (#506)
  • Use MMCV MODEL_REGISTRY (#515)
  • Add ONNX testing tools (#498)
  • Replace data_dict calling 'img' key to support MMDet3D (#514)
  • Support reading class_weight from file in loss function (#513)
  • Make tags as comment (#505)
  • Use MMCV EvalHook (#438)

V0.12 (04/03/2021)

Highlights

  • Support FCN-Dilate 6 model.
  • Support Dice Loss.

Bug Fixes

  • Fixed PhotoMetricDistortion Doc (#388)
  • Fixed install scripts (#399)
  • Fixed Dice Loss multi-class (#417)

New Features

  • Support Dice Loss (#396)
  • Add plot logs tool (#426)
  • Add opacity option to show_result (#425)
  • Speed up mIoU metric (#430)

Improvements

  • Refactor unittest file structure (#440)
  • Fix typos in the repo (#449)
  • Include class-level metrics in the log (#445)

V0.11 (02/02/2021)

Highlights

  • Support memory efficient test, add more UNet models.

Bug Fixes

  • Fixed TTA resize scale (#334)
  • Fixed CI for pip 20.3 (#307)
  • Fixed ADE20k test (#359)

New Features

  • Support memory efficient test (#330)
  • Add more UNet benchmarks (#324)
  • Support Lovasz Loss (#351)

Improvements

  • Move train_cfg/test_cfg inside model (#341)

V0.10 (01/01/2021)

Highlights

  • Support MobileNetV3, DMNet, APCNet. Add models of ResNet18V1b, ResNet18V1c, ResNet50V1b.

Bug Fixes

  • Fixed CPU TTA (#276)
  • Fixed CI for pip 20.3 (#307)

New Features

  • Add ResNet18V1b, ResNet18V1c, ResNet50V1b, ResNet101V1b models (#316)
  • Support MobileNetV3 (#268)
  • Add 4 retinal vessel segmentation benchmark (#315)
  • Support DMNet (#313)
  • Support APCNet (#299)

Improvements

  • Refactor Documentation page (#311)
  • Support resize data augmentation according to original image size (#291)

V0.9 (30/11/2020)

Highlights

  • Support 4 medical dataset, UNet and CGNet.

New Features

  • Support RandomRotate transform (#215, #260)
  • Support RGB2Gray transform (#227)
  • Support Rerange transform (#228)
  • Support ignore_index for BCE loss (#210)
  • Add modelzoo statistics (#263)
  • Support Dice evaluation metric (#225)
  • Support Adjust Gamma transform (#232)
  • Support CLAHE transform (#229)

Bug Fixes

  • Fixed detail API link (#267)

V0.8 (03/11/2020)

Highlights

  • Support 4 medical dataset, UNet and CGNet.

New Features

  • Support customize runner (#118)
  • Support UNet (#161)
  • Support CHASE_DB1, DRIVE, STARE, HRD (#203)
  • Support CGNet (#223)

V0.7 (07/10/2020)

Highlights

  • Support Pascal Context dataset and customizing class dataset.

Bug Fixes

  • Fixed CPU inference (#153)

New Features

  • Add DeepLab OS16 models (#154)
  • Support Pascal Context dataset (#133)
  • Support customizing dataset classes (#71)
  • Support customizing dataset palette (#157)

Improvements

  • Support 4D tensor output in ONNX (#150)
  • Remove redundancies in ONNX export (#160)
  • Migrate to MMCV DepthwiseSeparableConv (#158)
  • Migrate to MMCV collect_env (#137)
  • Use img_prefix and seg_prefix for loading (#153)

V0.6 (10/09/2020)

Highlights

  • Support new methods i.e. MobileNetV2, EMANet, DNL, PointRend, Semantic FPN, Fast-SCNN, ResNeSt.

Bug Fixes

  • Fixed sliding inference ONNX export (#90)

New Features

  • Support MobileNet v2 (#86)
  • Support EMANet (#34)
  • Support DNL (#37)
  • Support PointRend (#109)
  • Support Semantic FPN (#94)
  • Support Fast-SCNN (#58)
  • Support ResNeSt backbone (#47)
  • Support ONNX export (experimental) (#12)

Improvements

  • Support Upsample in ONNX (#100)
  • Support Windows install (experimental) (#75)
  • Add more OCRNet results (#20)
  • Add PyTorch 1.6 CI (#64)
  • Get version and githash automatically (#55)

v0.5.1 (11/08/2020)

Highlights

  • Support FP16 and more generalized OHEM

Bug Fixes

  • Fixed Pascal VOC conversion script (#19)
  • Fixed OHEM weight assign bug (#54)
  • Fixed palette type when palette is not given (#27)

New Features

  • Support FP16 (#21)
  • Generalized OHEM (#54)

Improvements

  • Add load-from flag (#33)
  • Fixed training tricks doc about different learning rates of model (#26)