import argparse import os import os.path as osp import tempfile import zipfile import mmcv HRF_LEN = 15 TRAINING_LEN = 5 def parse_args(): parser = argparse.ArgumentParser( description='Convert HRF dataset to mmsegmentation format') parser.add_argument('healthy_path', help='the path of healthy.zip') parser.add_argument( 'healthy_manualsegm_path', help='the path of healthy_manualsegm.zip') parser.add_argument('glaucoma_path', help='the path of glaucoma.zip') parser.add_argument( 'glaucoma_manualsegm_path', help='the path of glaucoma_manualsegm.zip') parser.add_argument( 'diabetic_retinopathy_path', help='the path of diabetic_retinopathy.zip') parser.add_argument( 'diabetic_retinopathy_manualsegm_path', help='the path of diabetic_retinopathy_manualsegm.zip') 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() images_path = [ args.healthy_path, args.glaucoma_path, args.diabetic_retinopathy_path ] annotations_path = [ args.healthy_manualsegm_path, args.glaucoma_manualsegm_path, args.diabetic_retinopathy_manualsegm_path ] if args.out_dir is None: out_dir = osp.join('data', 'HRF') 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')) print('Generating images...') for now_path in images_path: with tempfile.TemporaryDirectory(dir=args.tmp_dir) as tmp_dir: zip_file = zipfile.ZipFile(now_path) zip_file.extractall(tmp_dir) assert len(os.listdir(tmp_dir)) == HRF_LEN, \ 'len(os.listdir(tmp_dir)) != {}'.format(HRF_LEN) for filename in sorted(os.listdir(tmp_dir))[:TRAINING_LEN]: img = mmcv.imread(osp.join(tmp_dir, filename)) mmcv.imwrite( img, osp.join(out_dir, 'images', 'training', osp.splitext(filename)[0] + '.png')) for filename in sorted(os.listdir(tmp_dir))[TRAINING_LEN:]: img = mmcv.imread(osp.join(tmp_dir, filename)) mmcv.imwrite( img, osp.join(out_dir, 'images', 'validation', osp.splitext(filename)[0] + '.png')) print('Generating annotations...') for now_path in annotations_path: with tempfile.TemporaryDirectory(dir=args.tmp_dir) as tmp_dir: zip_file = zipfile.ZipFile(now_path) zip_file.extractall(tmp_dir) assert len(os.listdir(tmp_dir)) == HRF_LEN, \ 'len(os.listdir(tmp_dir)) != {}'.format(HRF_LEN) for filename in sorted(os.listdir(tmp_dir))[:TRAINING_LEN]: img = mmcv.imread(osp.join(tmp_dir, filename)) # 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', 'training', osp.splitext(filename)[0] + '.png')) for filename in sorted(os.listdir(tmp_dir))[TRAINING_LEN:]: img = mmcv.imread(osp.join(tmp_dir, filename)) mmcv.imwrite( img[:, :, 0] // 128, osp.join(out_dir, 'annotations', 'validation', osp.splitext(filename)[0] + '.png')) print('Done!') if __name__ == '__main__': main()