import argparse import os import os.path as osp import tempfile import zipfile import cv2 import mmcv def parse_args(): parser = argparse.ArgumentParser( description='Convert DRIVE dataset to mmsegmentation format') parser.add_argument( 'training_path', help='the training part of DRIVE dataset') parser.add_argument( 'testing_path', help='the testing part of DRIVE dataset') parser.add_argument('--tmp_dir', help='path of the temporary directory') parser.add_argument('-o', '--out_dir', help='output path') args = parser.parse_args() return args def main(): args = parse_args() training_path = args.training_path testing_path = args.testing_path if args.out_dir is None: out_dir = osp.join('data', 'DRIVE') else: out_dir = args.out_dir print('Making directories...') mmcv.mkdir_or_exist(out_dir) mmcv.mkdir_or_exist(osp.join(out_dir, 'images')) mmcv.mkdir_or_exist(osp.join(out_dir, 'images', 'training')) mmcv.mkdir_or_exist(osp.join(out_dir, 'images', 'validation')) mmcv.mkdir_or_exist(osp.join(out_dir, 'annotations')) mmcv.mkdir_or_exist(osp.join(out_dir, 'annotations', 'training')) mmcv.mkdir_or_exist(osp.join(out_dir, 'annotations', 'validation')) with tempfile.TemporaryDirectory(dir=args.tmp_dir) as tmp_dir: print('Extracting training.zip...') zip_file = zipfile.ZipFile(training_path) zip_file.extractall(tmp_dir) print('Generating training dataset...') now_dir = osp.join(tmp_dir, 'training', 'images') for img_name in os.listdir(now_dir): img = mmcv.imread(osp.join(now_dir, img_name)) mmcv.imwrite( img, osp.join( out_dir, 'images', 'training', osp.splitext(img_name)[0].replace('_training', '') + '.png')) now_dir = osp.join(tmp_dir, 'training', '1st_manual') for img_name in os.listdir(now_dir): cap = cv2.VideoCapture(osp.join(now_dir, img_name)) ret, img = cap.read() mmcv.imwrite( img[:, :, 0] // 128, osp.join(out_dir, 'annotations', 'training', osp.splitext(img_name)[0] + '.png')) print('Extracting test.zip...') zip_file = zipfile.ZipFile(testing_path) zip_file.extractall(tmp_dir) print('Generating validation dataset...') now_dir = osp.join(tmp_dir, 'test', 'images') for img_name in os.listdir(now_dir): img = mmcv.imread(osp.join(now_dir, img_name)) mmcv.imwrite( img, osp.join( out_dir, 'images', 'validation', osp.splitext(img_name)[0].replace('_test', '') + '.png')) now_dir = osp.join(tmp_dir, 'test', '1st_manual') if osp.exists(now_dir): for img_name in os.listdir(now_dir): cap = cv2.VideoCapture(osp.join(now_dir, img_name)) ret, img = cap.read() # The annotation img should be divided by 128, because some of # the annotation imgs are not standard. We should set a # threshold to convert the nonstandard annotation imgs. The # value divided by 128 is equivalent to '1 if value >= 128 # else 0' mmcv.imwrite( img[:, :, 0] // 128, osp.join(out_dir, 'annotations', 'validation', osp.splitext(img_name)[0] + '.png')) now_dir = osp.join(tmp_dir, 'test', '2nd_manual') if osp.exists(now_dir): for img_name in os.listdir(now_dir): cap = cv2.VideoCapture(osp.join(now_dir, img_name)) ret, img = cap.read() mmcv.imwrite( img[:, :, 0] // 128, osp.join(out_dir, 'annotations', 'validation', osp.splitext(img_name)[0] + '.png')) print('Removing the temporary files...') print('Done!') if __name__ == '__main__': main()