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model_name = Models.REGSEG48 ... image_processor = ComposeProcessing( [ SegmentationResize((768, 1024)), StandardizeImage(max_value=255.0), NormalizeImage(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]), ImagePermute(permutation=(2, 0, 1)), ] ) best_model = models.get( model_name=model_name, num_classes=5, checkpoint_path=os.path.join( trainer.checkpoints_dir_path, "ckpt_best.pth") ).cuda().eval() best_model.set_dataset_processing_params( class_names=['background', 'enamel', 'dentin', 'pulp', 'bones'], image_processor=image_processor )
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Same as STDC
TypeError: cross_entropy_loss(): argument 'input' (position 1) must be Tensor, not tuple
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The text was updated successfully, but these errors were encountered: