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| 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() | |