mmyolo/docs/en/notes/changelog.md

Changelog

v0.2.0（1/12/2022)

Highlights

1. Support YOLOv7 P5 and P6 model
2. Support YOLOv6 ML model
3. Support Grad-Based CAM and Grad-Free CAM
4. Support large image inference based on sahi
5. Add easydeploy project under the projects folder
6. Add custom dataset guide

New Features

1. browse_dataset.py script supports visualization of original image, data augmentation and intermediate results (#304)
2. Add flag to output labelme label file in image_demo.py (#288, #314)
3. Add labelme2coco script (#308, #313)
4. Add split COCO dataset script (#311)
5. Add two examples of backbone replacement in how-to.md and update plugin.md (#291)
6. Add contributing.md and code_style.md (#322)
7. Add docs about how to use mim to run scripts across libraries (#321)
8. Support YOLOv5 deployment at RV1126 device (#262)

Bug Fixes

1. Fix MixUp padding error (#319)
2. Fix scale factor order error of LetterResize and YOLOv5KeepRatioResize (#305)
3. Fix training errors of YOLOX Nano model (#285)
4. Fix RTMDet deploy error (#287)
5. Fix int8 deploy config (#315)
6. Fix make_stage_plugins doc in basebackbone (#296)
7. Enable switch to deploy when create pytorch model in deployment (#324)
8. Fix some errors in RTMDet model graph (#317)

Improvements

1. Add option of json output in test.py (#316)
2. Add area condition in extract_subcoco.py script (#286)
3. Deployment doc translation (#289)
4. Add YOLOv6 description overview doc (#252)
5. Improve config.md (#297, #303) 6Add mosaic9 graph in docstring (#307)
6. Improve browse_coco_json.py script args (#309)
7. Refactor some functions in dataset_analysis.py to be more general (#294)

Contributors

A total of 14 developers contributed to this release.

Thank @fcakyon, @matrixgame2018, @MambaWong, @imAzhou, @triple-Mu, @RangeKing, @PeterH0323, @xin-li-67, @kitecats, @hanrui1sensetime, @AllentDan, @Zheng-LinXiao, @hhaAndroid, @wanghonglie

v0.1.3（10/11/2022)

New Features

1. Support CBAM plug-in and provide plug-in documentation (#246)
2. Add YOLOv5 P6 model structure diagram and related descriptions (#273)

Bug Fixes

1. Fix training failure when saving best weights based on mmengine 0.3.1
2. Fix add_dump_metric error based on mmdet 3.0.0rc3 (#253)
3. Fix backbone does not support init_cfg issue (#272)
4. Change typing import method based on mmdet 3.0.0rc3 (#261)

Improvements

1. featmap_vis_demo support for folder and url input (#248)
2. Deploy docker file refinement (#242)

Contributors

A total of 10 developers contributed to this release.

Thank @kitecats, @triple-Mu, @RangeKing, @PeterH0323, @Zheng-LinXiao, @tkhe, @weikai520, @zytx121, @wanghonglie, @hhaAndroid

v0.1.2（3/11/2022)

Highlights

1. Support YOLOv5/YOLOv6/YOLOX/RTMDet deployments for ONNXRuntime and TensorRT
2. Support YOLOv6 s/t/n model training
3. YOLOv5 supports P6 model training which can input 1280-scale images
4. YOLOv5 supports VOC dataset training
5. Support PPYOLOE and YOLOv7 model inference and official weight conversion
6. Add YOLOv5 replacement backbone tutorial in How-to documentation

New Features

1. Add optimize_anchors script (#175)
2. Add extract_subcoco script (#186)
3. Add yolo2coco conversion script (#161)
4. Add dataset_analysis script (#172)
5. Remove Albu version restrictions (#187)

Bug Fixes

1. Fix the problem that cfg.resume does not work when set (#221)
2. Fix the problem of not showing bbox in feature map visualization script (#204)
3. uUpdate the metafile of RTMDet (#188)
4. Fix a visualization error in test_pipeline (#166)
5. Update badges (#140)

Improvements

1. Optimize Readthedoc display page (#209)
2. Add docstring for module structure diagram for base model (#196)
3. Support for not including any instance logic in LoadAnnotations (#161)
4. Update image_demo script to support folder and url paths (#128)
5. Update pre-commit hook (#129)

Documentation

1. Translate yolov5_description.md, yolov5_tutorial.md and visualization.md into English (#138, #198, #206)
2. Add deployment-related Chinese documentation (#220)
3. Update config.md, faq.md and pull_request_template.md (#190, #191, #200)
4. Update the article page (#133)

Contributors

A total of 14 developers contributed to this release.

Thank @imAzhou, @triple-Mu, @RangeKing, @PeterH0323, @xin-li-67, @Nioolek, @kitecats, @Bin-ze, @JiayuXu0, @cydiachen, @zhiqwang, @Zheng-LinXiao, @hhaAndroid, @wanghonglie

v0.1.1（29/9/2022)

Based on MMDetection's RTMDet high precision and low latency object detection algorithm, we have also released RTMDet and provided a Chinese document on the principle and implementation of RTMDet.

Highlights

1. Support RTMDet
2. Support for backbone customization plugins and update How-to documentation (#75)

Bug Fixes

1. Fix some documentation errors (#66, #72, #76, #83, #86)
2. Fix checkpoints link error (#63)
3. Fix the bug that the output of LetterResize does not meet the expectation when using imscale (#105)

Improvements

1. Reducing the size of docker images (#67)
2. Simplifying Compose Logic in BaseMixImageTransform (#71)
3. Supports dump results in test.py (#84)

Contributors

A total of 13 developers contributed to this release.

Thank @wanghonglie, @hhaAndroid, @yang-0201, @PeterH0323, @RangeKing, @satuoqaq, @Zheng-LinXiao, @xin-li-67, @suibe-qingtian, @MambaWong, @MichaelCai0912, @rimoire, @Nioolek

v0.1.0（21/9/2022)

We have released MMYOLO open source library, which is based on MMEngine, MMCV 2.x and MMDetection 3.x libraries. At present, the object detection has been realized, and it will be expanded to multi-task in the future.

Highlights

1. Support YOLOv5/YOLOX training, support YOLOv6 inference. Deployment will be supported soon.
2. Refactored YOLOX from MMDetection to accelerate training and inference.
3. Detailed introduction and advanced tutorials are provided, see the English tutorial.