U ?h@s.ddlmZddlZdgZdddddZdS)Ncontingency_tableF) ignore_labels normalizecCsb|dkr g}|d}|d}tj||ddt}|rH|t|}t|||ff}|S)a Return the contingency table for all regions in matched segmentations. Parameters ---------- im_true : ndarray of int Ground-truth label image, same shape as im_test. im_test : ndarray of int Test image. ignore_labels : sequence of int, optional Labels to ignore. Any part of the true image labeled with any of these values will not be counted in the score. normalize : bool Determines if the contingency table is normalized by pixel count. Returns ------- cont : scipy.sparse.csr_matrix A contingency table. `cont[i, j]` will equal the number of voxels labeled `i` in `im_true` and `j` in `im_test`. NT)invert) ZreshapenpisinZastypefloatZ count_nonzerosparseZ coo_matrixZtocsr)Zim_trueZim_testrrZ im_test_rZ im_true_rdatacontr T/var/www/html/venv/lib/python3.8/site-packages/skimage/metrics/_contingency_table.pyrs  )Z scipy.sparser numpyr__all__rr r r rs