def get_dataloader(args, scanrefer, all_scene_list, split, config, augment):
dataset = ScannetReferenceDataset(scanrefer=scanrefer,
scanrefer_all_scene=all_scene_list,
split=split,
num_points=args.num_points,
use_color=args.use_color,
use_height=(not args.no_height),
use_normal=args.use_normal,
use_multiview=args.use_multiview)
dataloader = DataLoader(dataset, batch_size=args.batch_size, shuffle=False)
return dataset, dataloader
def get_dataloader(args, scanrefer, all_scene_list, split, config):
dataset = ScannetReferenceDataset(scanrefer=scanrefer,
scanrefer_all_scene=all_scene_list,
split=split,
num_points=args.num_points,
use_color=args.use_color,
use_height=(not args.no_height),
use_normal=args.use_normal,
use_multiview=args.use_multiview)
print("evaluate on {} samples".format(len(dataset)))
dataloader = DataLoader(dataset, batch_size=args.batch_size, shuffle=True)
return dataset, dataloader
def get_dataloader(args, scanrefer, all_scene_list, split, config, augment):
dataset = ScannetReferenceDataset(scanrefer=scanrefer[split],
scanrefer_all_scene=all_scene_list,
split=split,
num_points=args.num_points,
use_height=(not args.no_height),
use_color=args.use_color,
use_normal=args.use_normal,
use_multiview=args.use_multiview)
# dataloader = DataLoader(dataset, batch_size=args.batch_size, shuffle=True)
dataloader = DataLoader(dataset,
batch_size=args.batch_size,
shuffle=True,
num_workers=4,
collate_fn=dataset.trainMerge)
return dataset, dataloader
def get_dataloader(args, scanrefer, all_scene_list, split):
dataset = ScannetReferenceDataset(
scanrefer=scanrefer,
scanrefer_all_scene=all_scene_list,
split=split,
args=CONF
)
dataloader = DataLoader(
dataset,
batch_size=args.batch_size,
shuffle=False,
num_workers=args.num_workers,
pin_memory=True,
collate_fn=dataset.collate_fn
)
return dataset, dataloader
