Highlights
- Support PyTorch 1.9
- Support SegFormer backbone MiT
- Support md2yml pre-commit hook
- Support frozen stage for HRNet
New Features
- Support SegFormer backbone MiT (#594)
- Support md2yml pre-commit hook (#732)
- Support mim (#717)
- Add mmseg2torchserve tool (#552)
Improvements
- Support hrnet frozen stage (#743)
- Add template of reimplementation questions (#741)
- Output pdf and epub formats for readthedocs (#742)
- Refine the docstring of ResNet (#723)
- Replace interpolate with resize (#731)
- Update resource limit (#700)
- Update config.md (#678)
Bug Fixes
- Fix ATTENTION registry (#729)
- Fix analyze log script (#716)
- Fix doc api display (#725)
- Fix patch_embed and pos_embed mismatch error (#685)
- Fix efficient test for multi-node (#707)
- Fix init_cfg in resnet backbone (#697)
- Fix efficient test bug (#702)
- Fix url error in config docs (#680)
- Fix mmcv installation (#676)
- Fix torch version (#670)
Contributors
@sshuair @xiexinch @Junjun2016 @mmeendez8 @xvjiarui @sennnnn @puhsu @BIGWangYuDong @keke1u @daavoo
Highlights
- Support ViT, SETR, and Swin-Transformer
- Add Chinese documentation
- Unified parameter initialization
Bug Fixes
- Fix typo and links (#608)
- Fix Dockerfile (#607)
- Fix ViT init (#609)
- Fix mmcv version compatible table (#658)
- Fix model links of DMNEt (#660)
New Features
- Support loading DeiT weights (#538)
- Support SETR (#531, #635)
- Add config and models for ViT backbone with UperHead (#520, #635)
- Support Swin-Transformer (#511)
- Add higher accuracy FastSCNN (#606)
- Add Chinese documentation (#666)
Improvements
- Unified parameter initialization (#567)
- Separate CUDA and CPU in github action CI (#602)
- Support persistent dataloader worker (#646)
- Update meta file fields (#661, #664)
Highlights
- Support ONNX to TensorRT
- Support MIM
Bug Fixes
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)
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_classesin 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)
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)
Highlights
- Support memory efficient test, add more UNet models.
Bug Fixes
New Features
Improvements
- Move train_cfg/test_cfg inside model (#341)
Highlights
- Support MobileNetV3, DMNet, APCNet. Add models of ResNet18V1b, ResNet18V1c, ResNet50V1b.
Bug Fixes
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)
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)
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)
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)
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)
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)