i^ddlmZddlZddlZddlmZmZddlmZddl m Z e sddl m Z nddlmZGd d eZ d Z dd Z dd Z ddddZy))combinations_with_replacementN)filtersfeature)img_as_float32)is_wasm)ThreadPoolExecutor)AbstractContextManagerceZdZdZdZdZy) PoolExecutorcyN)self___s /var/www/ITT-ServiceAPI-Services/ITT-Document-Scan/mrzscanner/mrzenv/lib/python3.12/site-packages/skimage/feature/_basic_features.py__init__zPoolExecutor.__init__ cyrr)rexc_typeexc_valexc_tbs r__exit__zPoolExecutor.__exit__rrct||Sr)map)rfn iterabless rrzPoolExecutor.mapsr9% %rN)__name__ __module__ __qualname__rrrrrrr r s   &rr c tt|jdDcgc]2\}}tjtj|||4}}}t j |}|Scc}}w)Nraxis)rrangendimnpgradientrhessian_matrix_eigvals)gaussian_filteredax0ax1H_elemseigvalss r_texture_filterr0so6ez9_mutiscale_basic_features_singlechannel..isCiugr) r(ascontiguousarrayrintlog2logspacer listr itertoolschain from_iterable) r6r7r8r9 sigma_min sigma_max num_sigmaworkerssigmasex out_sigmasfeaturess ```` r'_mutiscale_basic_features_singlechannelrU0sX  ~c2 3C *RWWY-??!CD [[       F ' * b FF    ,,Z8H O  s ("C33C<) channel_axisctgs td|dtjfd}n|dk7rtj|dfdt j dD} ttjj| } 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. 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 3NK|]}td|f yw).)r7r8r9rMrNrOrPN)rU) .0dimr8imager7rOrNrMr9rPs r z,multiscale_basic_features..sE   0 #s(O  s"%r$) any ValueErrorr(newaxismoveaxisr&shaperIrJrKrLstack) r\r7r8r9rMrNrOrPrV all_resultsrTouts ```````` rmultiscale_basic_featuresrfssr  5'* + 8  c2::o&   E<4  R) KIOO11+>?H ((8" %C Jr)TTT)TTTg?NN)rJrnumpyr(skimagerrskimage.util.dtyper_shared._dependency_checksrconcurrent.futuresr r contextlibr r0r;rUrfrrrrns3$-0E1&-&59     @J   SSr