32 lines
846 B
Python
32 lines
846 B
Python
import scipy.io as sio # type: ignore
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import torch
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@torch.no_grad()
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def make_mask(
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filename_mask: str,
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camera_sequence: list[torch.Tensor],
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device: torch.device,
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dtype: torch.dtype,
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) -> torch.Tensor:
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mask: torch.Tensor = torch.tensor(
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sio.loadmat(filename_mask)["maskInfo"]["maskIdx2D"][0][0],
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device=device,
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dtype=torch.bool,
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)
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mask = mask > 0.5
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limit: torch.Tensor = torch.tensor(
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2**16 - 1,
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device=device,
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dtype=dtype,
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)
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for id in range(0, len(camera_sequence)):
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if torch.any(camera_sequence[id].flatten() >= limit):
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mask = mask & ~(torch.any(camera_sequence[id] >= limit, dim=-1))
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if torch.any(camera_sequence[id].flatten() < 0):
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mask = mask & ~(torch.any(camera_sequence[id] < 0, dim=-1))
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return mask
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