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