数据集格式转换¶
VOC转COCO¶
import cvtools
mode = 'train'
root = 'D:/data/VOCdevkit/VOC2007'
# The cls parameter is a file containing categories,
# one category string is one line
voc_to_coco = cvtools.VOC2COCO(root, mode=mode,
cls='voc/cls.txt')
voc_to_coco.convert()
voc_to_coco.save_json(to_file='voc/{}.json'.format(mode))
VOC转DarkNet¶
import cvtools
voc_to_darknet = cvtools.VOC2DarkNet(
current_path + '/data/VOC',
mode='trainval',
use_xml_name=True,
read_test=True
)
voc_to_darknet.convert(save_root=current_path + '/out/darknet')
DOTA转COCO¶
import cvtools
# convert dota dataset to coco dataset format
# label folder
label_root = '/media/data/DOTA/train/labelTxt/'
# imgage folder
image_root = '/media/data/DOTA/train/images/'
dota_to_coco = cvtools.DOTA2COCO(label_root, image_root)
dota_to_coco.convert()
save = 'dota/train_dota_x1y1wh_polygen.json'
dota_to_coco.save_json(save)