Object Detection annotation Convert to Yolo Darknet Format
Support DataSet :
- COCO
- VOC
- UDACITY Object Detection
- KITTI 2D Object Detection
pip3 install -r requirements.txt
each dataset requried some parameters
see example.py
- Dataset Category
- Image path
- annotation path
- output path
- image type
- manipast file path
- class list file path(*.names)
aeroplane
bicycle
bird
boat
bottle
bus
car
cat
chair
cow
diningtable
dog
horse
motorbike
person
pottedplant
sheep
sofa
train
tvmonitor
python3 example.py --datasets [COCO/VOC/KITTI/UDACITY] --image_path <image_path> --label <label path or annotation file> --convert_output_path <output path> --image_type [".jpg" / ".png"] --manipast_path <output manipast file path> --clas_list_file <*.names file path>
- Support VOC Pascal Format
- Support Udacity Format
- Support COCO Format
- Support KITTI Format
- Write README
- Code Refactoring