navigate.model.analysis.boundary_detect.binary_detect

navigate.model.analysis.boundary_detect.binary_detect(img_data: Union[_SupportsArray[dtype], _NestedSequence[_SupportsArray[dtype]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]], boundary: list, width: int = 1, 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)

Perform a binary search for tissue on an image. Return locations of pixels containing tissue.

Parameters:

• img_data (npt.ArrayLike) – Image

• boundary (dict) – List of xy pixel positions indicating presence of tissue as values.

• 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:

boundary – List of boundaries of tissue by row of downsampled image.

Return type:

list