hukaixuan19970627/yolov5_obb：yolov 5 + cslLabel

hukaixuan19970627

项目介绍

hukaixuan19970627/yolov5_obb 是一个托管在 GitHub 上的开源项目，主要使用 Python 编写，采用 GNU General Public License v3.0 许可证，目前获得 2.0k 个 Star、427 次 Fork。

仓库全名: hukaixuan19970627/yolov5_obb

README 摘要

Yolov5 for Oriented Object Detection The code for the implementation of “Yolov5 + Circular Smooth Label”. Results and Models The results on DOTAsubsize1024gap200rate1.0 test-dev set are shown in the table below. (password: yolo) Model (download link) |Size (pixels) | TTA (multi-scale/ rotate testing) | OBB mAP test 0.5 DOTAv1.0 | OBB mAP test 0.5 DOTAv1.5 | OBB mAP test 0.5 DOTAv2.0 | Speed CPU b1 (ms)|Speed 2080Ti…

完整内容见 GitHub 原始 README 或本页。

常见问题

yolov5_obb 用什么语言开发？

主要使用 Python 编写，采用 GNU General Public License v3.0 许可证，目前有 2.0k 个 Star。

yolov5_obb 可以免费商用吗？

仓库标注的许可证为 GNU General Public License v3.0，商用前请先阅读仓库 LICENSE 文件确认授权范围。

如何获取 yolov5_obb 的源码？

可以直接克隆仓库：git clone https://github.com/hukaixuan19970627/yolov5_obb.git，默认分支为 master；安装与运行步骤见仓库 README。

yolov5_obb 最近还在维护吗？

仓库最近一次更新为 2023年10月14日，当前有 192 个未关闭 Issue；Star 数为 2.0k，可作为社区活跃度的参考。

关于

aerial-imagery detection dota oriented rotated-object rotation yolov5

GNU General Public License v3.0
2.0k Stars
427 Forks
14 Watching

简要分析

热度分

2820

价值分

1291

活跃状态

活跃

GitHub

语言占比

C++

Cuda

Cython

Dockerfile

Jupyter Notebook

Makefile

Python

SWIG

Shell

贡献者

hukaixuan19970627

Ethan-niu

sunbuhui

Yolov5 for Oriented Object Detection

The code for the implementation of “Yolov5 + Circular Smooth Label”.

Results and Models

The results on DOTA_subsize1024_gap200_rate1.0 test-dev set are shown in the table below. (password: yolo)

Model ^{(download link)}	Size ^(pixels)	TTA ^{(multi-scale/ rotate testing)}	OBB mAP^{test ^0.5 DOTAv1.0}	OBB mAP^{test ^0.5 DOTAv1.5}	OBB mAP^{test ^0.5 DOTAv2.0}	Speed ^{CPU b1 (ms)}	Speed ^{2080Ti b1 (ms)}	Speed ^{2080Ti b16 (ms)}	params ^(M)	FLOPs ^{@640 (B)}
yolov5m [baidu/google]	1024	×	77.3	73.2	58.0	328.2	16.9	11.3	21.6	50.5
yolov5s [baidu]	1024	×	76.8	-	-	-	15.6	-	7.5	17.5
yolov5n [baidu]	1024	×	73.3	-	-	-	15.2	-	2.0	5.0

Table Notes (click to expand / **点我看更多**)

All checkpoints are trained to 300 epochs with COCO pre-trained checkpoints, default settings and hyperparameters.
mAP^{test dota} values are for single-model single-scale on DOTA(1024,1024,200,1.0) dataset.
Reproduce Example:

python val.py --data 'data/dotav15_poly.yaml' --img 1024 --conf 0.01 --iou 0.4 --task 'test' --batch 16 --save-json --name 'dotav15_test_split'
python tools/TestJson2VocClassTxt.py --json_path 'runs/val/dotav15_test_split/best_obb_predictions.json' --save_path 'runs/val/dotav15_test_split/obb_predictions_Txt'
python DOTA_devkit/ResultMerge_multi_process.py --scrpath 'runs/val/dotav15_test_split/obb_predictions_Txt' --dstpath 'runs/val/dotav15_test_split/obb_predictions_Txt_Merged'
zip the poly format results files and submit it to https://captain-whu.github.io/DOTA/evaluation.html

Speed averaged over DOTAv1.5 val_split_subsize1024_gap200 images using a 2080Ti gpu. NMS + pre-process times is included.
Reproduce by python val.py --data 'data/dotav15_poly.yaml' --img 1024 --task speed --batch 1

Updates

[2022/1/7] : Faster and stronger, some bugs fixed, yolov5 base version updated.

Installation

Please refer to install.md for installation and dataset preparation.

Getting Started

This repo is based on yolov5.

And this repo has been rebuilt, Please see GetStart.md for the Oriented Detection latest basic usage.

Acknowledgements

I have used utility functions from other wonderful open-source projects. Espeicially thank the authors of:

More detailed explanation

想要了解相关实现的细节和原理可以看我的知乎文章:

自己改建YOLOv5旋转目标的踩坑记录.

有问题反馈

在使用中有任何问题，建议先按照install.md检查环境依赖项，再按照GetStart.md检查使用流程是否正确，善用搜索引擎和github中的issue搜索框，可以极大程度上节省你的时间。

若遇到的是新问题，可以用以下联系方式跟我交流，为了提高沟通效率，请尽可能地提供相关信息以便我复现该问题。

知乎（@略略略）
代码问题提issues,其他问题请知乎上联系

关于作者

  Name  : "胡凯旋"
  describe myself："咸鱼一枚"

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