o :ήc@sddlmZddlZddlZddlmZmZddlmZddl m Z ddl m Z ddZ dd d Z  dddZe jdd   dddddZdS))combinations_with_replacementN)filtersfeature)img_as_float32)utils)ThreadPoolExecutorcs,fddttjdD}t|}|S)Ncs(g|]\}}tjt||dqS)axis)npgradient).0ax0ax1gaussian_filteredF/tmp/pip-target-vg8gfxp4/lib/python/skimage/feature/_basic_features.py sz#_texture_filter..)rrangendimrhessian_matrix_eigvals)rH_elemseigvalsrrr_texture_filter s  rTcCsPd}tj||dd}|r||f7}|r|t|f7}|r&|gt|R7}|S)NrF)preserve_range)rgaussiansobelr)imgsigma intensityedgestextureresultsrrrr)_singlescale_basic_features_singlechannels r$?c stt|durtt|t|d}tjt|t||ddd}t|d} t| fdd|} Wdn1sHwYt j | } | S) a\Features for a single channel nd image. Parameters ---------- img : ndarray Input image, which can be grayscale or multichannel. intensity : bool, default True If True, pixel intensities averaged over the different scales are added to the feature set. edges : bool, default True If True, intensities of local gradients averaged over the different scales are added to the feature set. texture : bool, default True If True, eigenvalues of the Hessian matrix after Gaussian blurring at different scales are added to the feature set. sigma_min : float, optional Smallest value of the Gaussian kernel used to average local neighbourhoods before extracting features. sigma_max : float, optional Largest value of the Gaussian kernel used to average local neighbourhoods before extracting features. num_sigma : int, optional Number of values of the Gaussian kernel between sigma_min and sigma_max. If None, sigma_min multiplied by powers of 2 are used. num_workers : int or None, optional The number of parallel threads to use. If set to ``None``, the full set of available cores are used. Returns ------- features : list List of features, each element of the list is an array of shape as img. NrT)numbaseendpoint) max_workerscst|dS)N)r r!r")r$)sr!rr r"rrZs z9_mutiscale_basic_features_singlechannel..) r ascontiguousarrayrintlog2logspacerlistmap itertoolschain from_iterable) rr r!r" sigma_min sigma_max num_sigma num_workerssigmasex out_sigmasfeaturesrr-r'_mutiscale_basic_features_singlechannel!s(,  r@r')multichannel_positionF) channel_axisc  stgs td| durdtjfd} n | dkr$t| dfddtjdD} ttj | } tj | dd} | S)a\Local 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. multichannel : bool, default False True if the last dimension corresponds to color channels. This argument is deprecated: specify `channel_axis` instead. 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 neighbourhoods before extracting features. sigma_max : float, optional Largest value of the Gaussian kernel used to average local neighbourhoods 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"r8r9r:r;N)r@)r dimr!imager r:r;r9r8r"rr s   z,multiscale_basic_features..r) any ValueErrorr newaxismoveaxisrshaper3r5r6r7stack) rF multichannelr r!r"r8r9r:r;rB all_resultsr?outrrErmultiscale_basic_featuresds>  rQ)TTT)TTTr%r&NN)FTTTr%r&NN)r5rnumpyr skimagerrskimage.util.dtyperskimage._sharedrconcurrent.futuresrrr$r@deprecate_multichannel_kwargrQrrrrs<      C