Datasets:
Tasks:
Other
Languages:
English
Size Categories:
100K<n<1M
Annotations Creators:
expert-generated
DOI:
License:
File size: 1,439 Bytes
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import json
from urllib.request import urlopen
import huggingface_hub
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--local_dir", default="/home/linghao/Datasets/lightstage_dataset_download")
parser.add_argument("--light", required=True, choices=['lighting_patterns', 'OLAT'])
parser.add_argument("--obj_id", default=1, type=int)
parser.add_argument("--with_raw", default=False, action='store_true')
args = parser.parse_args()
def main():
data_json = json.loads(urlopen("https://oppo-us-research.github.io/OpenIllumination/data.json").read())
data_olat = json.loads(urlopen("https://oppo-us-research.github.io/OpenIllumination/data_olat.json").read())
repo_id = "OpenIllumination/OpenIllumination"
data = data_json if args.light == 'lighting_patterns' else data_olat
obj = data['obj_list'][args.obj_id - 1]
allow_patterns = [f"*{args.light}/{obj['data_name']}/Lights/*/raw_undistorted/*",
f"*{args.light}/{obj['data_name']}/output/*"
]
if args.light != "lighting_patterns" and args.with_raw:
allow_patterns.append(f"OLAT/{obj['data_name']}/RAW/*")
huggingface_hub.snapshot_download(repo_id,
repo_type="dataset",
allow_patterns=allow_patterns,
local_dir=args.local_dir)
if __name__ == '__main__':
main()
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