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import argparse
from lib.common.config import get_cfg_defaults
from lib.dataset.PIFuDataset import PIFuDataset
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('-v',
'--show',
action='store_true',
help='vis sampler 3D')
parser.add_argument('-s',
'--speed',
action='store_true',
help='vis sampler 3D')
parser.add_argument('-l',
'--list',
action='store_true',
help='vis sampler 3D')
parser.add_argument('-c',
'--config',
default='./configs/train/icon-filter.yaml',
help='vis sampler 3D')
args_c = parser.parse_args()
args = get_cfg_defaults()
args.merge_from_file(args_c.config)
dataset = PIFuDataset(args, split='train', vis=args_c.show)
print(f"Number of subjects :{len(dataset.subject_list)}")
data_dict = dataset[0]
if args_c.list:
for k in data_dict.keys():
if not hasattr(data_dict[k], "shape"):
print(f"{k}: {data_dict[k]}")
else:
print(f"{k}: {data_dict[k].shape}")
if args_c.show:
# for item in dataset:
item = dataset[0]
dataset.visualize_sampling3D(item, mode='occ')
if args_c.speed:
# original: 2 it/s
# smpl online compute: 2 it/s
# normal online compute: 1.5 it/s
from tqdm import tqdm
for item in tqdm(dataset):
# pass
for k in item.keys():
if 'voxel' in k:
if not hasattr(item[k], "shape"):
print(f"{k}: {item[k]}")
else:
print(f"{k}: {item[k].shape}")
print("--------------------")
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