https://github.com/hukaixuan19970627/dota_devkit_yolo
Trans DOTA OBB format(poly format) to YOLO format.
https://github.com/hukaixuan19970627/dota_devkit_yolo
aerial-imagery detection dota-devkit oriented rotation yolo-obb-labels yolov5
Last synced: 5 months ago
JSON representation
Trans DOTA OBB format(poly format) to YOLO format.
- Host: GitHub
- URL: https://github.com/hukaixuan19970627/dota_devkit_yolo
- Owner: hukaixuan19970627
- Created: 2021-03-13T08:21:33.000Z (about 4 years ago)
- Default Branch: master
- Last Pushed: 2021-05-29T05:57:31.000Z (almost 4 years ago)
- Last Synced: 2024-12-09T20:49:21.623Z (5 months ago)
- Topics: aerial-imagery, detection, dota-devkit, oriented, rotation, yolo-obb-labels, yolov5
- Language: Jupyter Notebook
- Homepage:
- Size: 38.6 MB
- Stars: 199
- Watchers: 1
- Forks: 39
- Open Issues: 9
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
## Brief Introduction
Based on [DOTA_devkit](https://github.com/CAPTAIN-WHU/DOTA_devkit).
Add some modules to trans DOTA annotation format to YOLO annotation format.
Add some files for every demo.
## Fuction
* `DOTA.py` Load image, and show the bounding oriented box.
* `ImgSplit.py` Split image and the label.
* `ResultMerge.py` Merge the detection result annotation txt.
* `dota_×_evaluation_task×.py` Evaluate the detection result annotation txt.
* `YOLO_Transformer.py` Trans DOTA format to YOLO(OBB or HBB) format.
* `Draw_DOTA_YOLO.py` Picture the YOLO_OBB labels(after augmented).
## Installation
Same as [DOTA_devkit](https://github.com/CAPTAIN-WHU/DOTA_devkit). Then:
```
$ pip install -r requirements.txt
```
## More detailed explanation
想要了解这几个函数实现的细节和原理可以看我的知乎文章;
[DOTA遥感数据集以及相关工具DOTA_devkit的整理(踩坑记录)](https://zhuanlan.zhihu.com/p/355862906);
[DOTA数据格式转YOLO数据格式工具(cv2.minAreaRect踩坑记录)](https://zhuanlan.zhihu.com/p/356416158);
## Usage Example
* `DOTA.py`
```javascript
$ python DOTA.py
```
* `ImgSplit.py`
```javascript
$ python ImgSplit_multi_process.py
```
* `ResultMerge.py`
```javascript
$ python ResultMerge.py
```
* `dota_v1.5_evaluation_task1.py`
change the path with yours.
```javascript
detpath = r'/.../evaluation_example/result_classname/Task1_{:s}.txt'
annopath = r'/.../evaluation_example/row_DOTA_labels/{:s}.txt'
imagesetfile = r'/.../evaluation_example/imgnamefile.txt'
```
```javascript
$ python dota_v1.5_evaluation_task1.py
```
* `YOLO_Transform.py`
```javascript
$ python YOLO_Transform.py
```
```javascript
DOTA format: poly classname diffcult
To
YOLO HBB format: classid x_c y_c width height —— def dota2Darknet()
longside format： classid x_c y_c longside shortside Θ Θ∈[0, 180) —— def dota2LongSideFormat()
```
* `Draw_DOTA_YOLO.py`
1.Run YOLO_Transformer.py to get the YOLO_OBB_labels first.
2.then augment YOLO_OBB_labels and visualize it:
```javascript
$ Draw_DOTA_YOLO.py
```
## 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](https://www.zhihu.com/people/lue-lue-lue-3-92-86)）
* 代码问题提issues,其他问题请知乎上联系
## 感激
感谢以下的项目,排名不分先后
* [DOTA_devkit](https://github.com/CAPTAIN-WHU/DOTA_devkit)
## 关于作者
```javascript
Name : "胡凯旋"
describe myself："咸鱼一枚"
```