a =br@s0ddlZddlZddlmZddZddZdS)N)cKDTreecCstt|}tt|}t|dkrBt|dkr>> points_a = (3, 0) >>> points_b = (6, 0) >>> shape = (7, 1) >>> image_a = np.zeros(shape, dtype=bool) >>> image_b = np.zeros(shape, dtype=bool) >>> image_a[points_a] = True >>> image_b[points_b] = True >>> hausdorff_distance(image_a, image_b) 3.0 r)k)np transposenonzeroleninfmaxrquery)image0image1a_pointsb_pointsr:lib/python3.9/site-packages/skimage/metrics/set_metrics.pyhausdorff_distances#  rc Cstt|}tt|}t|dks8t|dkrJtjddddSt||\}}t||\}}|}|} ||} || } | | kr|| ||| fS|||||fSdS)aReturns pair of points that are Hausdorff distance apart between nonzero elements of given images. The Hausdorff distance [1]_ is the maximum distance between any point on ``image0`` and its nearest point on ``image1``, and vice-versa. Parameters ---------- image0, image1 : ndarray Arrays where ``True`` represents a point that is included in a set of points. Both arrays must have the same shape. Returns ------- point_a, point_b : array A pair of points that have Hausdorff distance between them. References ---------- .. [1] http://en.wikipedia.org/wiki/Hausdorff_distance Examples -------- >>> points_a = (3, 0) >>> points_b = (6, 0) >>> shape = (7, 1) >>> image_a = np.zeros(shape, dtype=bool) >>> image_b = np.zeros(shape, dtype=bool) >>> image_a[points_a] = True >>> image_b[points_b] = True >>> hausdorff_pair(image_a, image_b) (array([3, 0]), array([6, 0])) rz#One or both of the images is empty.) stacklevel)rrN) rrrrwarningswarnrr Zargmax) r r rrZnearest_dists_from_bZnearest_a_point_indices_from_bZnearest_dists_from_aZnearest_b_point_indices_from_aZmax_index_from_aZmax_index_from_bZmax_dist_from_aZmax_dist_from_brrrhausdorff_pair9s,#  r)rZnumpyrZ scipy.spatialrrrrrrrs 2