41 lines
1 KiB
Python
41 lines
1 KiB
Python
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import torch
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from functions.ImageAlignment import ImageAlignment
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@torch.no_grad()
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def calculate_rotation(
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image_alignment: ImageAlignment,
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input: torch.Tensor,
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reference_image: torch.Tensor,
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batch_size: int,
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) -> torch.Tensor:
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angle = torch.zeros((input.shape[0]))
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data_loader = torch.utils.data.DataLoader(
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torch.utils.data.TensorDataset(input),
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batch_size=batch_size,
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shuffle=False,
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)
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start_position: int = 0
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for input_batch in data_loader:
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assert len(input_batch) == 1
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end_position = start_position + input_batch[0].shape[0]
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angle_temp = image_alignment.dry_run_angle(
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input=input_batch[0],
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new_reference_image=reference_image,
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)
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assert angle_temp is not None
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angle[start_position:end_position] = angle_temp
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start_position += input_batch[0].shape[0]
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angle = torch.where(angle >= 180, 360.0 - angle, angle)
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angle = torch.where(angle <= -180, 360.0 + angle, angle)
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return angle
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