1cc277630f2381f2ba0f01dcf833801a830f5c3b,skimage/metrics/_contingency_table.py,,contingency_table,#,7

Before Change

    im_test_r = im_test.ravel()
    im_true_r = im_true.ravel()
    ignored = np.zeros(im_true_r.shape, np.bool)
    for label in ignore_labels:
        ignored[im_true_r == label] = True
    data = np.ones(im_true_r.shape)
    data[ignored] = 0

After Change

        ignore_labels = []
    im_test_r = im_test.reshape(-1)
    im_true_r = im_true.reshape(-1)
    data = np.isin(im_true_r, ignore_labels, invert=True).astype(float)
    if normalize:
        data /= np.count_nonzero(data)
    cont = sparse.coo_matrix((data, (im_true_r, im_test_r))).tocsr()
    return cont

Instances