[;jqtddlZddlmZddlmZmZGddZGddZd dd d d d Z dZ dZ dZ y)N) img_as_float)_supported_float_typecheck_nDceZdZdZdZy)FeatureDetectorc8tjg|_yN)nparray keypoints_selfs ]G:\00. PROJECTS\API\Inventory\templateJSON\kerjaOCR\Lib\site-packages\skimage/feature/util.py__init__zFeatureDetector.__init__ s((2,ct)z}Detect keypoints in image. Parameters ---------- image : 2D array Input image. NotImplementedError)rimages rdetectzFeatureDetector.detects "##rN)__name__ __module__ __qualname__rrrrrr s ' $rrceZdZdZdZy)DescriptorExtractorc8tjg|_yr )r r descriptors_rs rrzDescriptorExtractor.__init__sHHRLrct)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 keypointss rextractzDescriptorExtractor.extracts "##rN)rrrrr"rrrrrs ) $rrkF horizontal)keypoints_color matches_color only_matches alignmentct|}t|}t|j} t|j} |jd|jdkr|jd| d<n1|jd|jdkDr|jd| d<|jd|jdkr|jd| d<n1|jd|jdkDr|jd| d<| |jk7rHtj| |j } || d|jdd|jdf<| }| |jk7rHtj| |j } || d|jdd|jdf<| }tj |j}| dk(rtj||gd}d|d<n5| dk(rtj||gd}d|d<nd| d }t||sR|j|dddf|dddfd | |j|dddf|dz|dddf|dzd | |j|d |jd|jd|dz|jd|dzdf|jd}ddl m }|Htjjd}t!|Dcgc]}|jd}}nK||rt!|Dcgc]}|}}n*t#|drt%||k(r|}n d}t|t'|D]F\}}|\}}|j)||df||df|dzf||df||df|dzfd||Hycc}wcc}w)aPlot matched features between two images. .. versionadded:: 0.23 Parameters ---------- image0 : (N, M [, 3]) array First image. image1 : (N, M [, 3]) array Second image. keypoints0 : (K1, 2) array First keypoint coordinates as ``(row, col)``. keypoints1 : (K2, 2) array Second keypoint coordinates as ``(row, col)``. matches : (Q, 2) array Indices of corresponding matches in first and second sets of descriptors, where `matches[:, 0]` (resp. `matches[:, 1]`) contains the indices in the first (resp. second) set of descriptors. ax : matplotlib.axes.Axes The Axes object where the images and their matched features are drawn. keypoints_color : matplotlib color, optional Color for keypoint locations. matches_color : matplotlib color or sequence thereof, optional Single color or sequence of colors for each line defined by `matches`, which connect keypoint matches. See [1]_ for an overview of supported color formats. By default, colors are picked randomly. only_matches : bool, optional Set to True to plot matches only and not the keypoint locations. alignment : {'horizontal', 'vertical'}, optional Whether to show the two images side by side (`'horizontal'`), or one above the other (`'vertical'`). References ---------- .. [1] https://matplotlib.org/stable/users/explain/colors/colors.html#specifying-colors Notes ----- To make a sequence of colors passed to `matches_color` work for any number of `matches`, you can wrap that sequence in :func:`itertools.cycle`. r)dtypeNr$)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)seed__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.colorsr3random default_rngrangehasattrlen enumerateplot)image0image1 keypoints0 keypoints1matchesaxr%r&r'r( new_shape0 new_shape1 new_image0 new_image1offsetrmesgnumber_of_matchesr3rng_colors error_messageimatchidx0idx1s rplot_matched_featuresr],sl& !F & !Ffll#Jfll#J ||Aa( Q 1 a6<<? * Q 1  ||Aa( Q 1 a6<<? * Q 1 V\\!XXj = ;A $V\\!_$&7 Q&778V\\!XXj = ;A $V\\!_$&7 Q&778 XXfll #FL /a8q j /a8q (k*    q!t  q!t &  q!t vay ( q!t vay (&  IIe&I!GGQ Q&)+V\\!_vay-H! LM a(/ii###+)./@)AB)AA#**Q-)AB } %)./@)AB)AA-)AB  *s=/AEV/V F ''g&5 d  a *T1W"5q "A B a *T1W"5q "A B )  'CBs O Octj|}t|dt|}t |j }|j |dS)NrFcopy)r squeezerrrr+astyper float_dtypes r_prepare_grayscale_input_2DresE JJu E UA  E' 4K << %< 00rctj|}t|tddt |}t |j }|j|dS)NrFr_)r rarrCrrr+rbrcs r_prepare_grayscale_input_nDrhsK JJu E UE!QK  E' 4K << %< 00rc|d}|d}|dz |dddfk|dddf||z dzkz|dz |dddfkz|dddf||z dzkz}|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_shaper!distancerowscolsmasks r_mask_border_keypointsros( q>D q>D Q,)AqD/ ) QT?dXo1 2 4 qLIadO + - QT?dXo1 2 4  Kr) numpyr utilr _shared.utilsrrrrr]rerhrorrrrssH $ $ $$4K \11r