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