9ivSSKrSSKJr SSKJrJr "SS5r"SS5rS SS S S .S jr Sr Sr Sr g)N) img_as_float)_supported_float_typecheck_nDc \rSrSrSrSrSrg)FeatureDetector c:[R"/5UlgN)nparray keypoints_selfs T/var/www/html/land-doc-ocr/venv/lib/python3.13/site-packages/skimage/feature/util.py__init__FeatureDetector.__init__ s((2,c[5e)zUDetect keypoints in image. Parameters ---------- image : 2D array Input image. NotImplementedError)rimages rdetectFeatureDetector.detects "##r)rN)__name__ __module__ __qualname____firstlineno__rr__static_attributes__rrrr s ' $rrc \rSrSrSrSrSrg)DescriptorExtractorc:[R"/5Ulgr )r r descriptors_rs rrDescriptorExtractor.__init__sHHRLrc[5e)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 rextractDescriptorExtractor.extracts "##r)r%N)rrrrrr)rr rrr"r"s ) $rr"kF horizontal)keypoints_color matches_color only_matches alignmentc[U5n[U5n[UR5n [UR5n URSURS:aURSU S'O2URSURS:aURSU S'URSURS:aURSU S'O2URSURS:aURSU S'XR:waD[R"XR S9n X SURS2SURS24'U nXR:waD[R"XR S9n XSURS2SURS24'U n[R "UR5nU S:Xa[R"X/SS9nSUS'O3U S:Xa[R"X/SS9nSUS'OSU S 3n[U5eU(dLURUSS2S4USS2S4S US 9 URUSS2S4US-USS2S4US-S US 9 URUS S 9 URSURSUS-URSUS-S45 URSnSSK J n UcH[RRSS9n[!U5Vs/sHnURS5PM nnOYU"U5(a[!U5Vs/sHnUPM nnO0[#US5(a[%U5U:XaUnO Sn[U5e['U5HDunnUunnUR)UUS4UUS4US-4UUS4UUS4US-4SUUS9 MF gs snfs snf)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 zerosr3r concatenate ValueErrorscatterimshowr4matplotlib.colorsr;random default_rngrangehasattrlen enumerateplot)image0image1 keypoints0 keypoints1matchesaxr-r.r/r0 new_shape0 new_shape1 new_image0 new_image1offsetrmesgnumber_of_matchesr;rng_colors error_messageimatchidx0idx1s rplot_matched_featuresre,sl& !F & !Ffll#Jfll#J ||Aa( Q 1 a6<<? * Q 1  ||Aa( Q 1 a6<<? * Q 1 \\!XXj = ;A$V\\!_$&7 Q&778\\!XXj = ;A$V\\!_$&7 Q&778 XXfll #FL /a8q j /a8q (k*    q!t  q!t &  q!t vay ( q!t vay (&  IIe&I!GGQ Q&)+V\\!_vay-H! LM a(/ii###+)./@)AB)AA#**Q-)AB } % %)./@)AB)AA-)AB  * *s=/AEV/V F ''g&5 d  a *T1W"5q "A B a *T1W"5q "A B )  'CBs O> Oc[R"U5n[US5 [U5n[ UR 5nUR USS9$)NrFcopy)r squeezerrrr3astyper float_dtypes r_prepare_grayscale_input_2DrmsE JJu E UA  E' 4K << %< 00rc[R"U5n[U[SS55 [ U5n[ UR 5nURUSS9$)NrFrg)r rirrKrrr3rjrks r_prepare_grayscale_input_nDrpsK JJu E UE!QK  E' 4K << %< 00rcUSnUSnUS- USS2S4:USS2S4X2- S-:-US- USS2S4:-USS2S4XB- S-:-nU$)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``). rr2Nr ) image_shaper(distancerowscolsmasks r_mask_border_keypointsrws( q>D q>D Q,)AqD/ ) QT?do1 2 4 qLIadO + - QT?do1 2 4  Kr) numpyr utilr _shared.utilsrrrr"rermrprwr rrr{sH $ $ $$4K \11r