data/visdrone.yaml

# train and val data as 1) directory: path/images/, 2) file: path/images.txt, or 3) list: [path1/images/, path2/images/]
train: ./VisDrone/split/train.txt  # 4K images
val: ./VisDrone/split/val.txt  # 700 imageS
test: ./VisDrone/split/test-dev.txt  # 20288 of 40670 images, submit to https:/competitions.codalab.org/competitions/20794

# number of classes
nc: 10

# class names
# names: ['person']
names: ['pedestrian', 'people', 'bicycle', 'car', 'van', 'truck', 'tricycle', 'awning-tricycle', 'bus', 'motor']

# Print classes
# with open('data/coco.yaml') as f:
#   d = yaml.load(f, Loader=yaml.FullLoader)  # dict
#   for i, x in enumerate(d['names']):
#     print(i, x)