o ^i@spddlZddlmZddlmZmZGdddZGdddZd dd d d d dZ ddZ ddZ ddZ dS)N) img_as_float)_supported_float_typecheck_nDc@eZdZddZddZdS)FeatureDetectorcCtg|_dSN)nparray keypoints_selfrO/var/www/html/RAG/RAG_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)rimagerrrdetects 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 horizontal)keypoints_color matches_color only_matches alignmentcs:t|}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|ddf|jd}ddl m }dur?tjjddfddt|D}n'|rPfddt|D}ntdr`t|kr`}nd}t|t|D]0\}}|\}}|j||df||df|df||df||df|dfd||dqjdS)aPlot matched features between two images. .. versionadded:: 0.23 Parameters ---------- image0 : (N, M [, 3]) array First image. image1 : (N, M [, 3]) array Second image. keypoints0 : (K1, 2) array First keypoint coordinates as ``(row, col)``. keypoints1 : (K2, 2) array Second keypoint coordinates as ``(row, col)``. matches : (Q, 2) array Indices of corresponding matches in first and second sets of descriptors, where `matches[:, 0]` (resp. `matches[:, 1]`) contains the indices in the first (resp. second) set of descriptors. ax : matplotlib.axes.Axes The Axes object where the images and their matched features are drawn. keypoints_color : matplotlib color, optional Color for keypoint locations. matches_color : matplotlib color or sequence thereof, optional Single color or sequence of colors for each line defined by `matches`, which connect keypoint matches. See [1]_ for an overview of supported color formats. By default, colors are picked randomly. only_matches : bool, optional Set to True to plot matches only and not the keypoint locations. alignment : {'horizontal', 'vertical'}, optional Whether to show the two images side by side (`'horizontal'`), or one above the other (`'vertical'`). References ---------- .. [1] https://matplotlib.org/stable/users/explain/colors/colors.html#specifying-colors Notes ----- To make a sequence of colors passed to `matches_color` work for any number of `matches`, you can wrap that sequence in :func:`itertools.cycle`. r)dtypeNr!)axisverticalzV`plot_matched_features` accepts either 'horizontal' or 'vertical' for alignment, but 'z~' was given. See https://scikit-image.org/docs/dev/api/skimage.feature.html#skimage.feature.plot_matched_features for details.none) facecolors edgecolorsgray)cmap) is_color_like)seedcsg|]}dqS))random.0_)rngrr sz)plot_matched_features..csg|]}qSrrr3)r#rrr7s__len__zb`matches_color` needs to be a single color or a sequence of length equal to the number of matches.-)color)rlistshaper zerosr'r concatenate ValueErrorscatterimshowr(matplotlib.colorsr/r2 default_rngrangehasattrlen enumerateplot)image0image1 keypoints0 keypoints1matchesaxr"r#r$r% new_shape0 new_shape1 new_image0 new_image1offsetrmesgnumber_of_matchesr/colors error_messageimatchidx0idx1r)r#r6rplot_matched_features,s6         .     r\cCs4t|}t|dt|}t|j}|j|ddS)NrFcopy)r squeezerrrr'astyper float_dtyperrr_prepare_grayscale_input_2Ds   rccCs:t|}t|tddt|}t|j}|j|ddS)NrFr])r r_rrDrrr'r`rarrr_prepare_grayscale_input_nDs  recCs||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_keypointssrk) numpyr utilr _shared.utilsrrrrr\rcrerkrrrrs