a6dddlmZddlZddlZddlmZmZddlmZddl m Z dZ ddZ dd Z ddd d ZdS))combinations_with_replacementN)filtersfeature)img_as_float32)ThreadPoolExecutorcfdttjdD}tj|}|S)Ncrg|]3\}}tjtj||4S)axis)npgradient).0ax0ax1gaussian_filtereds ?lib/python3.11/site-packages/skimage/feature/_basic_features.py z#_texture_filter.. sL C BK 12237cBBB)rrangendimrhessian_matrix_eigvals)rH_elemseigvalss` r_texture_filterr sY5ez9_mutiscale_basic_features_singlechannel..Ys"Ciugr) r ascontiguousarrayrintlog2logspacerlistmap itertoolschain from_iterable) r!r#r$r% sigma_min sigma_max num_sigma num_workerssigmasex out_sigmasfeaturess ```` r'_mutiscale_basic_features_singlechannelrD sTX ~c22 3 3C **RWY-?-??!CDD [       F  4 4 4  FF                    ,,Z88H Os.*C$$C(+C() channel_axisctgstd|dtjfd}n|dkrtj|dfdt jdD} ttj | } tj | d} | S)aLocal features for a single- or multi-channel nd image. Intensity, gradient intensity and local structure are computed at different scales thanks to Gaussian blurring. Parameters ---------- image : ndarray Input image, which can be grayscale or multichannel. intensity : bool, default True If True, pixel intensities averaged over the different scales are added to the feature set. edges : bool, default True If True, intensities of local gradients averaged over the different scales are added to the feature set. texture : bool, default True If True, eigenvalues of the Hessian matrix after Gaussian blurring at different scales are added to the feature set. sigma_min : float, optional Smallest value of the Gaussian kernel used to average local neighborhoods before extracting features. sigma_max : float, optional Largest value of the Gaussian kernel used to average local neighborhoods before extracting features. num_sigma : int, optional Number of values of the Gaussian kernel between sigma_min and sigma_max. If None, sigma_min multiplied by powers of 2 are used. num_workers : int or None, optional The number of parallel threads to use. If set to ``None``, the full set of available cores are used. channel_axis : int or None, optional If None, the image is assumed to be a grayscale (single channel) image. Otherwise, this parameter indicates which axis of the array corresponds to channels. .. versionadded:: 0.19 ``channel_axis`` was added in 0.19. Returns ------- features : np.ndarray Array of shape ``image.shape + (n_features,)``. When `channel_axis` is not None, all channels are concatenated along the features dimension. (i.e. ``n_features == n_features_singlechannel * n_channels``) z[At least one of `intensity`, `edges` or `textures`must be True for features to be computed.N.c 3VK|]#}td|f V$dS).)r#r$r%r<r=r>r?N)rD) rdimr$imager#r>r?r=r<r%s r z,multiscale_basic_features..sh    0 #s(O#       rr ) any ValueErrorr newaxismoveaxisrshaper7r9r:r;stack) rJr#r$r%r<r=r>r?rE all_resultsrCouts ```````` rmultiscale_basic_featuresrTcs r  5'* + +  8   c2:o&    E<44           R))   KIO11+>>??H (8" % % %C Jr)TTT)TTTr(r)NN)r9rnumpyr skimagerrskimage.util.dtyperconcurrent.futuresrrr'rDrTrrrrYs333333$$$$$$$$------11111159       @@@@J  SSSSSSSSr