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Running
on
Zero
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# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
"""Get image shape on CrowdHuman dataset.
Here is an example to run this script.
Example:
python tools/misc/get_crowdhuman_id_hw.py ${CONFIG} \
--dataset ${DATASET_TYPE}
"""
import argparse
import json
import logging
import os.path as osp
from multiprocessing import Pool
import mmcv
from mmengine.config import Config
from mmengine.fileio import dump, get, get_text
from mmengine.logging import print_log
def parse_args():
parser = argparse.ArgumentParser(description='Collect image metas')
parser.add_argument('config', help='Config file path')
parser.add_argument(
'--dataset',
choices=['train', 'val'],
help='Collect image metas from which dataset')
parser.add_argument(
'--nproc',
default=10,
type=int,
help='Processes used for get image metas')
args = parser.parse_args()
return args
def get_image_metas(anno_str, img_prefix):
id_hw = {}
anno_dict = json.loads(anno_str)
img_path = osp.join(img_prefix, f"{anno_dict['ID']}.jpg")
img_id = anno_dict['ID']
img_bytes = get(img_path)
img = mmcv.imfrombytes(img_bytes, backend='cv2')
id_hw[img_id] = img.shape[:2]
return id_hw
def main():
args = parse_args()
# get ann_file and img_prefix from config files
cfg = Config.fromfile(args.config)
dataset = args.dataset
dataloader_cfg = cfg.get(f'{dataset}_dataloader')
ann_file = osp.join(dataloader_cfg.dataset.data_root,
dataloader_cfg.dataset.ann_file)
img_prefix = osp.join(dataloader_cfg.dataset.data_root,
dataloader_cfg.dataset.data_prefix['img'])
# load image metas
print_log(
f'loading CrowdHuman {dataset} annotation...', level=logging.INFO)
anno_strs = get_text(ann_file).strip().split('\n')
pool = Pool(args.nproc)
# get image metas with multiple processes
id_hw_temp = pool.starmap(
get_image_metas,
zip(anno_strs, [img_prefix for _ in range(len(anno_strs))]),
)
pool.close()
# save image metas
id_hw = {}
for sub_dict in id_hw_temp:
id_hw.update(sub_dict)
data_root = osp.dirname(ann_file)
save_path = osp.join(data_root, f'id_hw_{dataset}.json')
print_log(
f'\nsaving "id_hw_{dataset}.json" in "{data_root}"',
level=logging.INFO)
dump(id_hw, save_path, file_format='json')
if __name__ == '__main__':
main()
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