o h@sjddlZddlmZddlmZmZGdddZGdddZ dd d Z ddZ ddZ ddZ dS)N) img_as_float)_supported_float_typecheck_nDc@eZdZddZddZdS)FeatureDetectorcCtg|_dSN)nparray keypoints_selfrO/var/www/html/scripts/venv/lib/python3.10/site-packages/skimage/feature/util.py__init__ zFeatureDetector.__init__cCt)z}Detect keypoints in image. Parameters ---------- image : 2D array Input image. NotImplementedError)rimagerrrdetect s zFeatureDetector.detectN)__name__ __module__ __qualname__rrrrrrr rc@r)DescriptorExtractorcCrr )r r descriptors_r rrrrrzDescriptorExtractor.__init__cCr)zExtract feature descriptors in image for given keypoints. Parameters ---------- image : 2D array Input image. keypoints : (N, 2) array Keypoint locations as ``(row, col)``. r)rr keypointsrrrextracts zDescriptorExtractor.extractN)rrrrrrrrrrrrkF horizontalc Cst|}t|}t|j} t|j} |jd|jdkr$|jd| d<n|jd|jdkr5|jd| d<|jd|jdkrG|jd| d<n|jd|jdkrX|jd| d<| |jkrwtj| |jd} || d|jdd|jdf<| }| |jkrtj| |jd} || d|jdd|jdf<| }t|j}| dkrtj||gdd}d|d<n| dkrtj||gdd}d|d<n d| d }t||s|j |dddf|dddfd |d |j |dddf|d|dddf|dd |d |j |d d | d|jd|d|jd|ddftj }t|jdD]A}||df}||df}|durA| d}n|}|j||df||df|df||df||df|dfd|dq(dS)aPlot matched features. Parameters ---------- ax : matplotlib.axes.Axes Matches and image are drawn in this ax. image1 : (N, M [, 3]) array First grayscale or color image. image2 : (N, M [, 3]) array Second grayscale or color image. keypoints1 : (K1, 2) array First keypoint coordinates as ``(row, col)``. keypoints2 : (K2, 2) array Second keypoint coordinates as ``(row, col)``. matches : (Q, 2) array Indices of corresponding matches in first and second set of descriptors, where ``matches[:, 0]`` denote the indices in the first and ``matches[:, 1]`` the indices in the second set of descriptors. keypoints_color : matplotlib color, optional Color for keypoint locations. matches_color : matplotlib color, optional Color for lines which connect keypoint matches. By default the color is chosen randomly. only_matches : bool, optional Whether to only plot matches and not plot the keypoint locations. alignment : {'horizontal', 'vertical'}, optional Whether to show images side by side, ``'horizontal'``, or one above the other, ``'vertical'``. r)dtypeNr!)axisverticalzKplot_matches accepts either 'horizontal' or 'vertical' for alignment, but 'zu' was given. See https://scikit-image.org/docs/dev/api/skimage.feature.html#skimage.feature.plot_matches for details.none) facecolors edgecolorsgray)cmap-)color)rlistshaper zerosr#r concatenate ValueErrorscatterimshowr$random default_rngrangeplot)aximage1image2 keypoints1 keypoints2matcheskeypoints_color matches_color only_matches alignment new_shape1 new_shape2 new_image1 new_image2offsetrmesgrngiidx1idx2r-rrr plot_matches+sh!          0.     " rMcCs4t|}t|dt|}t|j}|j|ddS)NrFcopy)r squeezerrrr#astyper float_dtyperrr_prepare_grayscale_input_2Ds   rTcCs:t|}t|tddt|}t|j}|j|ddS)NrFrN)r rPrr7rrr#rQrRrrr_prepare_grayscale_input_nDs  rVcCs||d}|d}|d|dddfk|dddf||dk@|d|dddfk@|dddf||dk@}|S)aMask coordinates that are within certain distance from the image border. Parameters ---------- image_shape : (2, ) array_like Shape of the image as ``(rows, cols)``. keypoints : (N, 2) array Keypoint coordinates as ``(rows, cols)``. distance : int Image border distance. Returns ------- mask : (N, ) bool array Mask indicating if pixels are within the image (``True``) or in the border region of the image (``False``). rr"Nr) image_shaperdistancerowscolsmaskrrr_mask_border_keypointssr\)r NFr!) numpyr utilr _shared.utilsrrrrrMrTrVr\rrrrs  b