MMYOLO releases v0.5.0
v0.5.0 (2/3/2023)
Highlights
- Support RTMDet-R rotated object detection
- Support for using mask annotation to improve YOLOv8 object detection performance
- Support MMRazor searchable NAS sub-network as the backbone of YOLO series algorithm
- Support calling MMRazor to distill the knowledge of RTMDet
- MMYOLO document structure optimization, comprehensive content upgrade
- Improve YOLOX mAP and training speed based on RTMDet training hyperparameters
- Support calculation of model parameters and FLOPs, provide GPU latency data on T4 devices, and update Model Zoo
- Support test-time augmentation (TTA)
- Support RTMDet, YOLOv8 and YOLOv7 assigner visualization
New Features
- Support inference for RTMDet instance segmentation tasks (#583)
- Beautify the configuration file in MMYOLO and add more comments (#501, #506, #516, #529, #531, #539)
- Refactor and optimize documentation (#568, #573, #579, #584, #587, #589, #596, #599, #600)
- Support fast version of YOLOX (#518)
- Support DeepStream in EasyDeploy and add documentation (#485, #545, #571)
- Add confusion matrix drawing script (#572)
- Add single channel application case (#460)
- Support auto registration (#597)
- Support Box CAM of YOLOv7, YOLOv8 and PPYOLOE (#601)
- Add automated generation of MM series repo registration information and tools scripts (#559)
- Added YOLOv7 model structure diagram (#504)
- Add how to specify specific GPU training and inference files (#503)
- Add check if
metainfo
is all lowercase when training or testing (#535) - Add links to Twitter, Discord, Medium, YouTube, etc. (#555)
Bug Fixes
- Fix isort version issue (#492, #497)
- Fix type error of assigner visualization (#509)
- Fix YOLOv8 documentation link error (#517)
- Fix RTMDet Decoder error in EasyDeploy (#519)
- Fix some document linking errors (#537)
- Fix RTMDet-Tiny weight path error (#580)
Improvements
- Update
contributing.md
- Optimize
DetDataPreprocessor
branch to support multitasking (#511) - Optimize
gt_instances_preprocess
so it can be used for other YOLO algorithms (#532) - Add
yolov7-e6e
weight conversion script (#570) - Reference YOLOv8 inference code modification PPYOLOE
Contributors
A total of 23 developers contributed to this release.
Thank @triple-Mu, @isLinXu, @Audrey528, @TianWen580, @yechenzhi, @RangeKing, @lyviva, @Nioolek, @PeterH0323, @tianleiSHI, @aptsunny, @satuoqaq, @vansin, @xin-li-67, @VoyagerXvoyagerx,
@landhill, @kitecats, @tang576225574, @HIT-cwh, @AI-Tianlong, @RangiLyu, @hhaAndroid, @liuyanyi