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- # Copyright (c) OpenMMLab. All rights reserved.
- import argparse
- import os.path as osp
- from functools import partial
-
- import mmcv
- import numpy as np
- from detail import Detail
- from PIL import Image
-
- _mapping = np.sort(
- np.array([
- 0, 2, 259, 260, 415, 324, 9, 258, 144, 18, 19, 22, 23, 397, 25, 284,
- 158, 159, 416, 33, 162, 420, 454, 295, 296, 427, 44, 45, 46, 308, 59,
- 440, 445, 31, 232, 65, 354, 424, 68, 326, 72, 458, 34, 207, 80, 355,
- 85, 347, 220, 349, 360, 98, 187, 104, 105, 366, 189, 368, 113, 115
- ]))
- _key = np.array(range(len(_mapping))).astype('uint8')
-
-
- def generate_labels(img_id, detail, out_dir):
-
- def _class_to_index(mask, _mapping, _key):
- # assert the values
- values = np.unique(mask)
- for i in range(len(values)):
- assert (values[i] in _mapping)
- index = np.digitize(mask.ravel(), _mapping, right=True)
- return _key[index].reshape(mask.shape)
-
- mask = Image.fromarray(
- _class_to_index(detail.getMask(img_id), _mapping=_mapping, _key=_key))
- filename = img_id['file_name']
- mask.save(osp.join(out_dir, filename.replace('jpg', 'png')))
- return osp.splitext(osp.basename(filename))[0]
-
-
- def parse_args():
- parser = argparse.ArgumentParser(
- description='Convert PASCAL VOC annotations to mmsegmentation format')
- parser.add_argument('devkit_path', help='pascal voc devkit path')
- parser.add_argument('json_path', help='annoation json filepath')
- parser.add_argument('-o', '--out_dir', help='output path')
- args = parser.parse_args()
- return args
-
-
- def main():
- args = parse_args()
- devkit_path = args.devkit_path
- if args.out_dir is None:
- out_dir = osp.join(devkit_path, 'VOC2010', 'SegmentationClassContext')
- else:
- out_dir = args.out_dir
- json_path = args.json_path
- mmcv.mkdir_or_exist(out_dir)
- img_dir = osp.join(devkit_path, 'VOC2010', 'JPEGImages')
-
- train_detail = Detail(json_path, img_dir, 'train')
- train_ids = train_detail.getImgs()
-
- val_detail = Detail(json_path, img_dir, 'val')
- val_ids = val_detail.getImgs()
-
- mmcv.mkdir_or_exist(
- osp.join(devkit_path, 'VOC2010/ImageSets/SegmentationContext'))
-
- train_list = mmcv.track_progress(
- partial(generate_labels, detail=train_detail, out_dir=out_dir),
- train_ids)
- with open(
- osp.join(devkit_path, 'VOC2010/ImageSets/SegmentationContext',
- 'train.txt'), 'w') as f:
- f.writelines(line + '\n' for line in sorted(train_list))
-
- val_list = mmcv.track_progress(
- partial(generate_labels, detail=val_detail, out_dir=out_dir), val_ids)
- with open(
- osp.join(devkit_path, 'VOC2010/ImageSets/SegmentationContext',
- 'val.txt'), 'w') as f:
- f.writelines(line + '\n' for line in sorted(val_list))
-
- print('Done!')
-
-
- if __name__ == '__main__':
- main()
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