|hi ddlZddlmZddZy)N)distance_transform_edtct|dk(|d\}}tj|}||k}|Dcgc]}|| }}|t|} | ||<|Scc}w)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)samplingreturn_indices)rnp zeros_liketuple) label_imagedistancespacing distancesnearest_label_coords labels_out dilate_maskdimension_indicesmasked_nearest_label_coordsnearest_labelss b/var/www/html/test/engine/venv/lib/python3.12/site-packages/skimage/segmentation/_expand_labels.py expand_labelsrsl'=q74'#I#{+Jx'K AU#+<+&##!'B!CDN,J{  #s A)r)numpyr scipy.ndimagerrrrs0cr