U ?h@stddlmZddlZddlZddlmZmZddlmZddl m Z ddZ dd d Z dd dZ dddddZdS))combinations_with_replacementN)filtersfeature)img_as_float32)ThreadPoolExecutorcs,fddttjdD}t|}|S)Ncs(g|] \}}tjt||dqS)Zaxis)npZgradient).0Zax0Zax1gaussian_filteredQ/var/www/html/venv/lib/python3.8/site-packages/skimage/feature/_basic_features.py sz#_texture_filter..)rrangendimrZhessian_matrix_eigvals)r ZH_elemsZeigvalsr r r _texture_filter s   rTcCsLd}tj||dd}|r"||f7}|r6|t|f7}|rH|t|7}|S)Nr F)Zpreserve_range)rZgaussianZsobelr)imgsigma intensityedgestextureresultsr r r r )_singlescale_basic_features_singlechannels r?c stt|dkr2tt|t|d}tjt|t||ddd}t|d$} t| fdd|} W5QRXt 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)rrr)r)srrrrr r Ys z9_mutiscale_basic_features_singlechannel..) rZascontiguousarrayrintlog2Zlogspacerlistmap itertoolschain from_iterable) rrrr sigma_min sigma_max num_sigma num_workersZsigmasexZ out_sigmasfeaturesr r!r '_mutiscale_basic_features_singlechannel s&,  r0) channel_axisc stgstd|dkr2dtjfd}n|dkrHt|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 3s.|]&}td|fdVqdS).)rrrr*r+r,r-N)r0)r dimrimagerr,r-r+r*rr r s  z,multiscale_basic_features..r) any ValueErrorrZnewaxisZmoveaxisrshaper%r'r(r)stack) r5rrrr*r+r,r-r1Z all_resultsr/outr r4r multiscale_basic_featurescs9  r<)TTT)TTTrrNN)TTTrrNN)r'rnumpyrZskimagerrZskimage.util.dtyperconcurrent.futuresrrrr0r<r r r r s8     E