https://github.com/BossZard/rotation-yolov5

rotation detection based on yolov5
https://github.com/BossZard/rotation-yolov5

Last synced: about 2 months ago
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rotation detection based on yolov5

• Host: GitHub
• URL: https://github.com/BossZard/rotation-yolov5
• Owner: BossZard
• License: gpl-3.0
• Created: 2020-11-11T08:16:58.000Z (almost 4 years ago)
• Default Branch: master
• Last Pushed: 2023-11-21T05:53:01.000Z (10 months ago)
• Last Synced: 2024-06-16T17:06:52.648Z (3 months ago)
• Language: Jupyter Notebook
• Size: 7.78 MB
• Stars: 378
• Watchers: 6
• Forks: 97
• Open Issues: 25
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-yolo-object-detection - BossZard/rotation-yolov5 - yolov5?style=social"/> : rotation detection based on yolov5. (Applications)

README

        
the rotation detection

# Requirement

```bash

torch==1.6

shapely==1.7.1

opencv==4.2.0.34

```

# inference

you can download the weights [BaiduYun](https://pan.baidu.com/s/1l7AwoT78tQEQ-K_vOJobQQ)(password is 4ud5) or [GoogleDrive](https://drive.google.com/drive/folders/1McWvzy_UAUCOBFmzjzawVqC0KroSLmEy?usp=sharing) for ship detection by my dataset(not DOTA) to test the demo.

```bash

$ python detect.py

```

![image](result.png)

# train

## what format my model need

Not much different from yolo dataset,just add an __angle__ and we define the box attribute w is always __longer__ than h!

So wo define the box label is (cls, c_x, c_y, Longest side，short side, angle)

Attention!we define angle is a classify question,so we define 180 classes for angle.

For Example:

![image](rbox.png)

Range for angle is [-90，90), so wo should __add__ __90__ in angle while make your dataset label and then your label's Range should be [0,179)

![image](label_format.png)

## modify yaml

models/yolov5m.yaml: set nc to your dataset class num;

data/wheat0.yaml:set nc to your dataset class num, and set names to your dataset class name;

```bash

$ python train.py

```

# update

2021.1.4---correct some BUG for training

# details

If you have any question,welcome discuss with me by [This](https://zhuanlan.zhihu.com/p/270388743) or email to [email protected]