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| # Copyright (c) OpenMMLab. All rights reserved. | |
| import argparse | |
| import os | |
| import os.path as osp | |
| import tempfile | |
| import zipfile | |
| import mmcv | |
| import numpy as np | |
| from mmengine.utils import mkdir_or_exist | |
| def parse_args(): | |
| parser = argparse.ArgumentParser( | |
| description='Convert REFUGE dataset to mmsegmentation format') | |
| parser.add_argument('--raw_data_root', help='the root path of raw data') | |
| 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 extract_img(root: str, | |
| cur_dir: str, | |
| out_dir: str, | |
| mode: str = 'train', | |
| file_type: str = 'img') -> None: | |
| """_summary_ | |
| Args: | |
| Args: | |
| root (str): root where the extracted data is saved | |
| cur_dir (cur_dir): dir where the zip_file exists | |
| out_dir (str): root dir where the data is saved | |
| mode (str, optional): Defaults to 'train'. | |
| file_type (str, optional): Defaults to 'img',else to 'mask'. | |
| """ | |
| zip_file = zipfile.ZipFile(cur_dir) | |
| zip_file.extractall(root) | |
| for cur_dir, dirs, files in os.walk(root): | |
| # filter child dirs and directories with "Illustration" and "MACOSX" | |
| if len(dirs) == 0 and \ | |
| cur_dir.split('\\')[-1].find('Illustration') == -1 and \ | |
| cur_dir.find('MACOSX') == -1: | |
| file_names = [ | |
| file for file in files | |
| if file.endswith('.jpg') or file.endswith('.bmp') | |
| ] | |
| for filename in sorted(file_names): | |
| img = mmcv.imread(osp.join(cur_dir, filename)) | |
| if file_type == 'annotations': | |
| img = img[:, :, 0] | |
| img[np.where(img == 0)] = 1 | |
| img[np.where(img == 128)] = 2 | |
| img[np.where(img == 255)] = 0 | |
| mmcv.imwrite( | |
| img, | |
| osp.join(out_dir, file_type, mode, | |
| osp.splitext(filename)[0] + '.png')) | |
| def main(): | |
| args = parse_args() | |
| raw_data_root = args.raw_data_root | |
| if args.out_dir is None: | |
| out_dir = osp.join('./data', 'REFUGE') | |
| else: | |
| out_dir = args.out_dir | |
| print('Making directories...') | |
| mkdir_or_exist(out_dir) | |
| mkdir_or_exist(osp.join(out_dir, 'images')) | |
| mkdir_or_exist(osp.join(out_dir, 'images', 'training')) | |
| mkdir_or_exist(osp.join(out_dir, 'images', 'validation')) | |
| mkdir_or_exist(osp.join(out_dir, 'images', 'test')) | |
| mkdir_or_exist(osp.join(out_dir, 'annotations')) | |
| mkdir_or_exist(osp.join(out_dir, 'annotations', 'training')) | |
| mkdir_or_exist(osp.join(out_dir, 'annotations', 'validation')) | |
| mkdir_or_exist(osp.join(out_dir, 'annotations', 'test')) | |
| print('Generating images and annotations...') | |
| # process data from the child dir on the first rank | |
| cur_dir, dirs, files = list(os.walk(raw_data_root))[0] | |
| print('====================') | |
| files = list(filter(lambda x: x.endswith('.zip'), files)) | |
| with tempfile.TemporaryDirectory(dir=args.tmp_dir) as tmp_dir: | |
| for file in files: | |
| # search data folders for training,validation,test | |
| mode = list( | |
| filter(lambda x: file.lower().find(x) != -1, | |
| ['training', 'test', 'validation']))[0] | |
| file_root = osp.join(tmp_dir, file[:-4]) | |
| file_type = 'images' if file.find('Anno') == -1 and file.find( | |
| 'GT') == -1 else 'annotations' | |
| extract_img(file_root, osp.join(cur_dir, file), out_dir, mode, | |
| file_type) | |
| print('Done!') | |
| if __name__ == '__main__': | |
| main() | |