a =b# @sddlZddlZddlmZddlmZddlmZddl m Z m Z m Z ddl mZddlmZd gZedd ddd d d d d d ZdS) N)uniform_filter)utils)gaussian)_supported_float_typecheck_shape_equalitywarn)crop) dtype_rangestructural_similarityF)win_sizegradient data_range channel_axis multichannelgaussian_weightsfullc2Kst||t|j} |durlt|||d||d} | | |j|} tj| | d} |rhtj|j| d}|r|tj|j| d}||j}t j t j |d}t | D]}t||||||fi| }|r|r|\| |<|||<|||<q|r|\| |<|||<q|r$|\| |<|||<q|| |<q| } |rL|rL| ||fS|rZ| |fS|rh| |fS| S| dd}| dd}| d d }|d krtd |d krtd |d krtd| dd}|rd}|dur|r t||d}d|d}nd}tt|j|d kr2td|ddksHtd|dur|j|jkrltdddt|jj\}}||}|j}|rt}||dd}n t}d|i}|j| dd}|j| dd}||}|r||d}nd}||fi|} ||fi|}!|||fi|}"|||fi|}#|||fi|}$||"| | }%||#|!|!}&||$| |!}'|}(||(d})||(d}*d| |!|)d|'|*| d|!d|)|%|&|*f\}+},}-}.|-|.}/|+|,|/}|dd}0t||0jtjd} |r||+|/fi||}1|1|| |.fi||7}1|1|| |,|+|!|.|-||/fi|7}1|1d|j9}1|r| |1|fS| |1fSn|r| |fS| SdS) a Compute the mean structural similarity index between two images. Parameters ---------- im1, im2 : ndarray Images. Any dimensionality with same shape. win_size : int or None, optional The side-length of the sliding window used in comparison. Must be an odd value. If `gaussian_weights` is True, this is ignored and the window size will depend on `sigma`. gradient : bool, optional If True, also return the gradient with respect to im2. data_range : float, optional The data range of the input image (distance between minimum and maximum possible values). By default, this is estimated from the image data-type. 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. multichannel : bool, optional If True, treat the last dimension of the array as channels. Similarity calculations are done independently for each channel then averaged. This argument is deprecated: specify `channel_axis` instead. gaussian_weights : bool, optional If True, each patch has its mean and variance spatially weighted by a normalized Gaussian kernel of width sigma=1.5. full : bool, optional If True, also return the full structural similarity image. Other Parameters ---------------- use_sample_covariance : bool If True, normalize covariances by N-1 rather than, N where N is the number of pixels within the sliding window. K1 : float Algorithm parameter, K1 (small constant, see [1]_). K2 : float Algorithm parameter, K2 (small constant, see [1]_). sigma : float Standard deviation for the Gaussian when `gaussian_weights` is True. Returns ------- mssim : float The mean structural similarity index over the image. grad : ndarray The gradient of the structural similarity between im1 and im2 [2]_. This is only returned if `gradient` is set to True. S : ndarray The full SSIM image. This is only returned if `full` is set to True. Notes ----- To match the implementation of Wang et. al. [1]_, set `gaussian_weights` to True, `sigma` to 1.5, and `use_sample_covariance` to False. .. versionchanged:: 0.16 This function was renamed from ``skimage.measure.compare_ssim`` to ``skimage.metrics.structural_similarity``. References ---------- .. [1] Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004). Image quality assessment: From error visibility to structural similarity. IEEE Transactions on Image Processing, 13, 600-612. https://ece.uwaterloo.ca/~z70wang/publications/ssim.pdf, :DOI:`10.1109/TIP.2003.819861` .. [2] Avanaki, A. N. (2009). Exact global histogram specification optimized for structural similarity. Optical Review, 16, 613-621. :arxiv:`0901.0065` :DOI:`10.1007/s10043-009-0119-z` N)r r rrrr)dtype)ZaxisK1g{Gz?K2gQ?sigmag?rzK1 must be positivezK2 must be positivezsigma must be positiveuse_sample_covarianceTg @g?raDwin_size exceeds image extent. Either ensure that your images are at least 7x7; or pass win_size explicitly in the function call, with an odd value less than or equal to the smaller side of your images. If your images are multichannel (with color channels), set channel_axis to the axis number corresponding to the channels.zWindow size must be odd.zEInputs have mismatched dtype. Setting data_range based on im1.dtype.) stacklevelZreflect)rtruncatemodesizeF)copyg?)rrrdictupdateshapenpemptyndim functoolspartialrZ slice_at_axisranger Zmeanpop ValueErrorintanyZasarrayrr typerrZastyper Zfloat64r)2Zim1Zim2r r rrrrrkwargsZ float_typeargsZnchZmssimGSZ_atZchZ ch_resultrrrrrrZdminZdmaxr$Z filter_funcZ filter_argsZNPZcov_normZuxZuyZuxxZuyyZuxyZvxZvyZvxyRZC1ZC2ZA1ZA2ZB1ZB2DZpadZgradr4Elib/python3.9/site-packages/skimage/metrics/_structural_similarity.pyr sV                             &  )r%Znumpyr"Z scipy.ndimagerZ_sharedrZ_shared.filtersrZ _shared.utilsrrrZutil.arraycropr Z util.dtyper __all__Zdeprecate_multichannel_kwargr r4r4r4r5s