o jz@sddlmZddlZddlZddlmZmZddlmZddl m Z e s+ddl m Z nddlmZGd d d eZ d d Z dddZ    dddZ    dddddZdS))combinations_with_replacementN)filtersfeature)img_as_float32)is_wasm)ThreadPoolExecutor)AbstractContextManagerc@s$eZdZddZddZddZdS) PoolExecutorcOdSN)self___r r `/var/www/html/Deteccion_Ine/venv/lib/python3.10/site-packages/skimage/feature/_basic_features.py__init__zPoolExecutor.__init__cCr r r )rexc_typeexc_valexc_tbr r r__exit__rzPoolExecutor.__exit__cCs t||Sr )map)rfn iterablesr r rrs zPoolExecutor.mapN)__name__ __module__ __qualname__rrrr r r rr s r cs,fddttjdD}t|}|S)Ncs(g|]\}}tjt||dqS)Zaxis)npZgradient).0Zax0Zax1gaussian_filteredr r sz#_texture_filter..r)rrangendimrZhessian_matrix_eigvals)r"ZH_elemsZeigvalsr r!r_texture_filters  r&TcCsPd}tj||dd}|r||f7}|r|t|f7}|r&|gt|R7}|S)Nr F)sigmaZpreserve_range)rZgaussianZsobelr&)imgr' intensityedgestextureresultsr"r r r)_singlescale_basic_features_singlechannel"s r-?c stt|durtt|t|d}tjt|t||ddd}t|d} t| fdd|} Wdn1sHwYt j | } | S) aZFeatures 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. 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. Returns ------- features : list List of features, each element of the list is an array of shape as img. NrT)numbaseZendpoint) max_workerscst|dS)N)r)r*r+)r-)sr*r(r)r+r ris z9_mutiscale_basic_features_singlechannel..) rZascontiguousarrayrintlog2Zlogspacer listr itertoolschain from_iterable) r(r)r*r+ sigma_min sigma_max num_sigma num_workersZsigmasexZ out_sigmasfeaturesr r5r'_mutiscale_basic_features_singlechannel0s(,  rC) channel_axisc stgs td|durdtjfd}n |dkr$t|dfddtjdD} ttj | } tj | dd} | 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 3s0|]}td|fdVqdS).)r)r*r+r=r>r?r@N)rC)r dimr*imager)r?r@r>r=r+r r s   z,multiscale_basic_features..r) any ValueErrorrZnewaxisZmoveaxisr$shaper9r:r;r<stack) rHr)r*r+r=r>r?r@rDZ all_resultsrBoutr rGrmultiscale_basic_featuresss9  rO)TTT)TTTr.r/NN)r:rnumpyrZskimagerrZskimage.util.dtyperZ_shared._dependency_checksrconcurrent.futuresrr contextlibr r&r-rCrOr r r rs>       E