§ 1-Phiãó"—ddlZddlmZdd„ZdS)éN)Údistance_transform_edtéc󾇗t|dk|d¬¦«\}}tj|¦«}||kŠˆfd„|D¦«}|t|¦«}||‰<|S)as Expand labels in label image by ``distance`` pixels without overlapping. Given a label image, ``expand_labels`` grows label regions (connected components) outwards by up to ``distance`` units without overflowing into neighboring regions. More specifically, each background pixel that is within Euclidean distance of <= ``distance`` pixels of a connected component is assigned the label of that connected component. The `spacing` parameter can be used to specify the spacing rate of the distance transform used to calculate the Euclidean distance for anisotropic images. Where multiple connected components are within ``distance`` pixels of a background pixel, the label value of the closest connected component will be assigned (see Notes for the case of multiple labels at equal distance). Parameters ---------- label_image : ndarray of dtype int label image distance : float Euclidean distance in pixels by which to grow the labels. Default is one. spacing : float, or sequence of float, optional Spacing of elements along each dimension. If a sequence, must be of length equal to the input rank; if a single number, this is used for all axes. If not specified, a grid spacing of unity is implied. Returns ------- enlarged_labels : ndarray of dtype int Labeled array, where all connected regions have been enlarged Notes ----- Where labels are spaced more than ``distance`` pixels are apart, this is equivalent to a morphological dilation with a disc or hyperball of radius ``distance``. However, in contrast to a morphological dilation, ``expand_labels`` will not expand a label region into a neighboring region. This implementation of ``expand_labels`` is derived from CellProfiler [1]_, where it is known as module "IdentifySecondaryObjects (Distance-N)" [2]_. There is an important edge case when a pixel has the same distance to multiple regions, as it is not defined which region expands into that space. Here, the exact behavior depends on the upstream implementation of ``scipy.ndimage.distance_transform_edt``. See Also -------- :func:`skimage.measure.label`, :func:`skimage.segmentation.watershed`, :func:`skimage.morphology.dilation` References ---------- .. [1] https://cellprofiler.org .. [2] https://github.com/CellProfiler/CellProfiler/blob/082930ea95add7b72243a4fa3d39ae5145995e9c/cellprofiler/modules/identifysecondaryobjects.py#L559 Examples -------- >>> labels = np.array([0, 1, 0, 0, 0, 0, 2]) >>> expand_labels(labels, distance=1) array([1, 1, 1, 0, 0, 2, 2]) Labels will not overwrite each other: >>> expand_labels(labels, distance=3) array([1, 1, 1, 1, 2, 2, 2]) In case of ties, behavior is undefined, but currently resolves to the label closest to ``(0,) * ndim`` in lexicographical order. >>> labels_tied = np.array([0, 1, 0, 2, 0]) >>> expand_labels(labels_tied, 1) array([1, 1, 1, 2, 2]) >>> labels2d = np.array( ... [[0, 1, 0, 0], ... [2, 0, 0, 0], ... [0, 3, 0, 0]] ... ) >>> expand_labels(labels2d, 1) array([[2, 1, 1, 0], [2, 2, 0, 0], [2, 3, 3, 0]]) >>> expand_labels(labels2d, 1, spacing=[1, 0.5]) array([[1, 1, 1, 1], [2, 2, 2, 0], [3, 3, 3, 3]]) rT)ÚsamplingÚreturn_indicescó •—g|] }|‰‘Œ S©r )Ú.0Údimension_indicesÚ dilate_masks €úc/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/skimage/segmentation/_expand_labels.pyú z!expand_labels..cs,ø€ð#ð#ð#Ø+<И+Ô&ð#ð#ð#ó)rÚnpÚ zeros_likeÚtuple) Ú label_imageÚdistanceÚspacingÚ distancesÚnearest_label_coordsÚ labels_outÚmasked_nearest_label_coordsÚnearest_labelsr s @r Ú expand_labelsrs•ø€õl'=ØqÒ 7¸4ð'ñ'ô'Ñ#€IÐ#õ”˜{Ñ+Ô+€JؘxÒ'€Kð#ð#ð#ð#Ø@Tð#ñ#ô#Ðð!¥Ð'BÑ!CÔ!CÔD€NØ,€Jˆ{ÑØ Ðr)rr)ÚnumpyrÚ scipy.ndimagerrr rr úrsGðØÐÐÐØ0Ð0Ð0Ð0Ð0Ð0ðcðcðcðcðcðcr