Drowning_Person_Detection/core/data/downloader/mscoco.py

70 lines
2.8 KiB
Python

"""Prepare MS COCO datasets"""
import os
import sys
import argparse
import zipfile
# TODO: optim code
cur_path = os.path.abspath(os.path.dirname(__file__))
root_path = os.path.split(os.path.split(os.path.split(cur_path)[0])[0])[0]
sys.path.append(root_path)
from core.utils import download, makedirs, try_import_pycocotools
_TARGET_DIR = os.path.expanduser('~/.torch/datasets/coco')
def parse_args():
parser = argparse.ArgumentParser(
description='Initialize MS COCO dataset.',
epilog='Example: python mscoco.py --download-dir ~/mscoco',
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('--download-dir', type=str, default='~/mscoco/', help='dataset directory on disk')
parser.add_argument('--no-download', action='store_true', help='disable automatic download if set')
parser.add_argument('--overwrite', action='store_true',
help='overwrite downloaded files if set, in case they are corrupted')
args = parser.parse_args()
return args
def download_coco(path, overwrite=False):
_DOWNLOAD_URLS = [
('http://images.cocodataset.org/zips/train2017.zip',
'10ad623668ab00c62c096f0ed636d6aff41faca5'),
('http://images.cocodataset.org/annotations/annotations_trainval2017.zip',
'8551ee4bb5860311e79dace7e79cb91e432e78b3'),
('http://images.cocodataset.org/zips/val2017.zip',
'4950dc9d00dbe1c933ee0170f5797584351d2a41'),
# ('http://images.cocodataset.org/annotations/stuff_annotations_trainval2017.zip',
# '46cdcf715b6b4f67e980b529534e79c2edffe084'),
# test2017.zip, for those who want to attend the competition.
# ('http://images.cocodataset.org/zips/test2017.zip',
# '4e443f8a2eca6b1dac8a6c57641b67dd40621a49'),
]
makedirs(path)
for url, checksum in _DOWNLOAD_URLS:
filename = download(url, path=path, overwrite=overwrite, sha1_hash=checksum)
# extract
with zipfile.ZipFile(filename) as zf:
zf.extractall(path=path)
if __name__ == '__main__':
args = parse_args()
path = os.path.expanduser(args.download_dir)
if not os.path.isdir(path) or not os.path.isdir(os.path.join(path, 'train2017')) \
or not os.path.isdir(os.path.join(path, 'val2017')) \
or not os.path.isdir(os.path.join(path, 'annotations')):
if args.no_download:
raise ValueError(('{} is not a valid directory, make sure it is present.'
' Or you should not disable "--no-download" to grab it'.format(path)))
else:
download_coco(path, overwrite=args.overwrite)
# make symlink
makedirs(os.path.expanduser('~/.torch/datasets'))
if os.path.isdir(_TARGET_DIR):
os.remove(_TARGET_DIR)
os.symlink(path, _TARGET_DIR)
try_import_pycocotools()