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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()