neuralib.segmentation.stardist.run_2d.StarDistResult

final class neuralib.segmentation.stardist.run_2d.StarDistResult

Bases: object

Stardist results

Dimension parameters:

N = Number of segmented cell

E = Number of polygons edge

W = Image width

H = Image height

P = Number of image pixel with label

filename: str

Source image file name

labels: ndarray

Image with label. Array[float, [H, W]]

cords: ndarray

Coordinates. Array[float, [N, 2, E]]

prob: ndarray

Detected probability. Array[float, N]

points: ndarray

Coordinates to points by simple XY average. Array[float, [N, 2]]

classmethod load(file)

Parameters:

file (str | Path | bytes | BinaryIO | BufferedIOBase | BufferedReader)

Return type:

Self

savez(output_file)

Save filename, cord, prob, point, shape, index, index, value as a npz file.

shape: Array[int, 2] in H,W

index: index with labels. Array[int, [P, 2]]

value: label value in its index Array[int, P]

Parameters:

output_file (str | Path | bytes | BinaryIO | BufferedIOBase | BufferedReader) – output

Return type:

None

save_roi(output_file)

Save as imageJ .roi file

Parameters:

output_file (str | Path | bytes | BinaryIO | BufferedIOBase | BufferedReader)

Return type:

None

get_index_value()

Get labelled pixel index and its value.

Returns:

Array[int, [P, 2]] and Array[float, P]

Return type:

tuple[ndarray, ndarray]

with_probability(threshold)

Parameters:

threshold (float)

Return type:

Self

__init__(filename, labels, cords, prob)

Method generated by attrs for class StarDistResult.

Parameters:

• filename (str)

• labels (ndarray)

• cords (ndarray)

• prob (ndarray)

Return type:

None