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navigate.model.analysis.boundary_detect.has_tissue

navigate.model.analysis.boundary_detect.has_tissue(image_data: Union[_SupportsArray[dtype], _NestedSequence[_SupportsArray[dtype]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]], x: int, y: int, width: int, offset: Optional[Union[_SupportsArray[dtype], _NestedSequence[_SupportsArray[dtype]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]] = None, variance: Optional[Union[_SupportsArray[dtype], _NestedSequence[_SupportsArray[dtype]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]] = None) → bool

Determine if an image contains tissue.

Parameters:
  • image_data (npt.ArrayLike) – Image

  • x (int) – Starting x-position of subimage. Must be smaller than image_data.shape[0].

  • y (int) – Starting y-position of subimage. Must be smaller than image_data.shape[1].

  • width (int) – Width of subimage. Must be smaller than min(image_data.shape[:1])

  • offset (npt.ArrayLike) – Camera pixel offset map. Same size as image_data.

  • variance (npt.ArrayLike) – Camera pixel variance map. Same size as image_data.

Returns:

Is tissue present?

Return type:

bool

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