U ƒ±ËhÞã@sfddlZddlmZddlmZmZGdd„dƒZGdd„dƒZdd d „Z dd„Z dd„Z dd„Z dS)éNé)Ú img_as_float)Ú_supported_float_typeÚcheck_nDc@seZdZdd„Zdd„ZdS)ÚFeatureDetectorcCst g¡|_dS©N)ÚnpÚarrayZ keypoints_©Úself©r ú8/tmp/pip-unpacked-wheel-gtraehzf/skimage/feature/util.pyÚ__init__ szFeatureDetector.__init__cCs tƒ‚dS)z}Detect keypoints in image. Parameters ---------- image : 2D array Input image. N©ÚNotImplementedError)r Úimager r r Údetect s zFeatureDetector.detectN)Ú__name__Ú __module__Ú __qualname__rrr r r r rsrc@seZdZdd„Zdd„ZdS)ÚDescriptorExtractorcCst g¡|_dSr)rr Z descriptors_r r r r rszDescriptorExtractor.__init__cCs tƒ‚dS)zïExtract feature descriptors in image for given keypoints. Parameters ---------- image : 2D array Input image. keypoints : (N, 2) array Keypoint locations as ``(row, col)``. Nr)r rÚ keypointsr r r Úextracts zDescriptorExtractor.extractN)rrrrrr r r r rsrÚkFÚ horizontalc Csàt|ƒ}t|ƒ}t|jƒ} t|jƒ} |jd|jdkrH|jd| d<n"|jd|jdkrj|jd| d<|jd|jdkrŽ|jd| d<n"|jd|jdkr°|jd| d<| |jkrîtj| |jd} || d|jd…d|jd…f<| }| |jkr.tj| |jd} || d|jd…d|jd…f<| }t |j¡}| dkr`tj||gdd}d|d<n:| dkr†tj||gdd}d|d<nd| ›d }t|ƒ‚|s|j |dd…df|dd…dfd |d |j |dd…df|d|dd…df|dd |d |j |d d |  d|jd|d|jd|ddf¡tj   ¡}t|jdƒD]‚}||df}||df}|dkrŠ|  d¡}n|}|j||df||df|df||df||df|dfd|dqXdS)a¼Plot 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'``. ré)ÚdtypeNr)ÚaxisZverticalzKplot_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.Únone)Z facecolorsZ edgecolorsZgray)Zcmapéú-)Úcolor)rÚlistÚshaperÚzerosrr Z concatenateÚ ValueErrorZscatterZimshowrÚrandomZ default_rngÚrangeZplot)ZaxZimage1Zimage2Z keypoints1Z keypoints2ÚmatchesZkeypoints_colorZ matches_colorZ only_matchesÚ alignmentZ new_shape1Z new_shape2Z new_image1Z new_image2ÚoffsetrZmesgÚrngÚiZidx1Zidx2r!r r r Ú plot_matches+sh!             ÿ0ÿ.     "þr-cCs4t |¡}t|dƒt|ƒ}t|jƒ}|j|ddS)NrF©Úcopy)rÚsqueezerrrrÚastype©rZ float_dtyper r r Ú_prepare_grayscale_input_2Ds    r3cCs:t |¡}t|tddƒƒt|ƒ}t|jƒ}|j|ddS)NréFr.)rr0rr'rrrr1r2r r r Ú_prepare_grayscale_input_nD•s   r5cCs||d}|d}|d|dd…dfk|dd…df||dk@|d|dd…dfk@|dd…df||dk@}|S)aòMask 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``). rrNr )Z image_shaperZdistanceZrowsÚcolsÚmaskr r r Ú_mask_border_keypointssÿþýr8)rNFr) ZnumpyrÚutilrZ _shared.utilsrrrrr-r3r5r8r r r r Ús þ b