def get_preprocessor(cfg, dataset=None, device=None):
''' Returns preprocessor instance.
Args:
cfg (dict): config dictionary
dataset (dataset): dataset
device (device): pytorch device
'''
p_type = cfg['preprocessor']['type']
cfg_path = cfg['preprocessor']['config']
model_file = cfg['preprocessor']['model_file']
if p_type == 'psgn':
preprocessor = preprocess.PSGNPreprocessor(
cfg_path=cfg_path,
pointcloud_n=cfg['data']['pointcloud_n'],
dataset=dataset,
device=device,
model_file=model_file,
)
elif p_type is None:
preprocessor = None
else:
raise ValueError('Invalid Preprocessor %s' % p_type)
return preprocessor
def get_preprocessor(cfg, dataset=None):
""" Returns preprocessor instance.
Args:
cfg (dict): config dictionary
dataset (dataset): dataset
"""
p_type = cfg["preprocessor"]["type"]
cfg_path = cfg["preprocessor"]["config"]
model_file = cfg["preprocessor"]["model_file"]
if p_type == "psgn":
preprocessor = preprocess.PSGNPreprocessor(
cfg_path=cfg_path,
pointcloud_n=cfg["data"]["pointcloud_n"],
dataset=dataset,
model_file=model_file,
)
elif p_type is None:
preprocessor = None
else:
raise ValueError("Invalid Preprocessor %s" % p_type)
return preprocessor