Yolov5 for Oriented Object Detection

The code for the implementation of “yolov5 + circular Smooth Label”.

Updates

• [2022/1/7] : Faster and stronger, some bugs fixed. details

Installation

Please refer to for installation and dataset preparation.

Getting Started

This repo is based on . Please see for the Oriented Detection basic usage.

Results and Models

The results on DOTAv1.5_subsize1024_gap200_rate1.0 test-dev set are shown in the table below(password:yolo).

| Model
^{(link) |size
(pixels) | TTA
(multi-scale/
rotate testing) | mAPOBB
0.5 | Speed
CPU b1
(ms)|Speed
2080Ti b1
(ms) |params
(M) |FLOPs
@1024 (B) | ---- | --- | --- | --- | --- | --- | --- | --- | --- | |[yolov5m][https://pan.baidu.com/s/17e5cqExBTPxyGmndbL9gwQ] |1024 | × |73.19 |- |- |21.6 |50.5 | |[yolov5m6][] |1024 | × |- |- |- |- | - | - | |[yolov5m7][] |1024 | × |- |- |- |- | - | - |}

Note:

• All the pre-trained checkpoint about yolov5 can be downloaded in this link.

Acknowledgements

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

• ultralytics/yolov5.
• Thinklab-SJTU/CSL_RetinaNet_Tensorflow.
• jbwang1997/OBBDetection
• CAPTAIN-WHU/DOTA_devkit

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，欢迎反馈给我，可以用以下联系方式跟我交流

• 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"