+ Ai^^RIHt^RIt^RIt^RIHtHt^RIHt^RI H t ] 'g^RI H t M^RIHt!RR ]4t R tRR ltRR ltRR R/RlltR#))combinations_with_replacementN)filtersfeature)img_as_float32)is_wasm)ThreadPoolExecutor)AbstractContextManagerc2a]tRt^toRtRtRtRtVtR#) PoolExecutorcR#N)self___s&*,]/var/www/html/photoedit/myenv/lib/python3.14/site-packages/skimage/feature/_basic_features.py__init__PoolExecutor.__init__ cR#r r)rexc_typeexc_valexc_tbs&&&&r__exit__PoolExecutor.__exit__rrc\W4#r )map)rfn iterabless&&&rrPoolExecutor.maps r% %rrN) __name__ __module__ __qualname____firstlineno__rrr__static_attributes____classdictcell__) __classdict__s@rr r s   & &rr c \\VP4^4UUu.uF8wr\P!\P!V4V,VR7NK: ppp\ P !V4pV#uuppi)axis)rrangendimnpgradientrhessian_matrix_eigvals)gaussian_filteredax0ax1H_elemseigvalss& r_texture_filterr7sp6eA<cRp\P!WRR7pV'd WV3, pV'dV\P!V43, pV'dV.\V4O5, pV#)F)sigmapreserve_ranger)rgaussiansobelr7)imgr9 intensityedgestextureresultsr2s&&&&& r)_singlescale_basic_features_singlechannelrB"sbG((%P'' GMM"34669_%6799 Nrc >aaaa\P!\S44oVfB\\P!V4\P!V4, ^,4p\P !\P!V4\P!V4V^RR7p\ VR7;_uu_4p \V PVVVV3RlV44p RRR4\PPX 4p V # +'giL1;i)aFeatures for a single channel nd image. Parameters ---------- img : 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. workers : int or None, optional The number of parallel threads to use. If set to ``None``, the full set of available cores are used. Returns ------- features : list List of features, each element of the list is an array of shape as img. NT)numbaseendpoint) max_workersc$<\SVSSSR7#))r>r?r@)rB)sr?r=r>r@s&r9_mutiscale_basic_features_singlechannel..isCiugr) r/ascontiguousarrayrintlog2logspacer listr itertoolschain from_iterable) r=r>r?r@ sigma_min sigma_max num_sigmaworkerssigmasex out_sigmasfeaturess ffff&&&& r'_mutiscale_basic_features_singlechannelr\0sX  ~c2 3C *RWWY-??!CD [[       F ' * *b FF    +,,Z8H O + *s #D  D channel_axiscaaaaaaaa\SSS.4'g \R4hVfSR\P3,oRpMVR8wd\P!SVR4oVVVVVVVV3Rl\ SP R,44p \\PPV 44p \P!V RR7p V #)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. 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..c 3\<"TF!p\SRV3,SSSSSSS R7xK# R#5i).)r>r?r@rTrUrVrWN)r\) .0dimr?imager>rVrUrTr@rWs & r ,multiscale_basic_features..sF *C 0 #s(O *s),r+) any ValueErrorr/newaxismoveaxisr-shaperPrQrRrSstack) rbr>r?r@rTrUrVrWr] all_resultsr[outs ffffffff$ rmultiscale_basic_featuresrnssr  5'* + + 8  c2::o&   E<4  R) KIOO11+>?H ((8" %C Jr)TTT)TTTg?NN)rQrnumpyr/skimagerrskimage.util.dtyper_shared._dependency_checksrconcurrent.futuresrr contextlibr r7rBr\rnrrrrvsO3$-0E1&-& @FSSr