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Merge branch 4.x
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@@ -0,0 +1,95 @@
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{
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"whitelist":
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{
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"": [
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"Canny",
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"GaussianBlur",
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"Laplacian",
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"HoughLines",
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"HoughLinesP",
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"HoughCircles",
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"Scharr",
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"Sobel",
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"adaptiveThreshold",
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"approxPolyDP",
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"arcLength",
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"bilateralFilter",
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"blur",
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"boundingRect",
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"boxFilter",
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"calcBackProject",
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"calcHist",
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"circle",
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"compareHist",
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"connectedComponents",
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"connectedComponentsWithStats",
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"contourArea",
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"convexHull",
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"convexityDefects",
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"cornerHarris",
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"cornerMinEigenVal",
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"createCLAHE",
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"createLineSegmentDetector",
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"cvtColor",
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"demosaicing",
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"dilate",
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"distanceTransform",
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"distanceTransformWithLabels",
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"drawContours",
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"ellipse",
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"ellipse2Poly",
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"equalizeHist",
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"erode",
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"filter2D",
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"findContours",
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"fitEllipse",
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"fitLine",
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"floodFill",
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"getAffineTransform",
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"getPerspectiveTransform",
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"getRotationMatrix2D",
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"getStructuringElement",
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"goodFeaturesToTrack",
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"grabCut",
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"integral",
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"integral2",
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"isContourConvex",
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"line",
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"matchShapes",
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"matchTemplate",
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"medianBlur",
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"minAreaRect",
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"minEnclosingCircle",
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"moments",
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"morphologyEx",
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"pointPolygonTest",
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"putText",
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"pyrDown",
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"pyrUp",
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"rectangle",
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"remap",
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"resize",
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"sepFilter2D",
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"threshold",
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"warpAffine",
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"warpPerspective",
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"warpPolar",
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"watershed",
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"fillPoly",
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"fillConvexPoly",
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"polylines"
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],
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"CLAHE": ["apply", "collectGarbage", "getClipLimit", "getTilesGridSize", "setClipLimit", "setTilesGridSize"],
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"segmentation_IntelligentScissorsMB": [
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"IntelligentScissorsMB",
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"setWeights",
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"setGradientMagnitudeMaxLimit",
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"setEdgeFeatureZeroCrossingParameters",
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"setEdgeFeatureCannyParameters",
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"applyImage",
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"applyImageFeatures",
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"buildMap",
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"getContour"
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]
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}
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}
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@@ -0,0 +1,30 @@
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#!/usr/bin/env python
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from __future__ import print_function
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import numpy as np
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import cv2 as cv
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from tests_common import NewOpenCVTests
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class Imgproc_Tests(NewOpenCVTests):
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def test_python_986(self):
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cntls = []
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img = np.zeros((100,100,3), dtype=np.uint8)
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color = (0,0,0)
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cnts = np.array(cntls, dtype=np.int32).reshape((1, -1, 2))
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try:
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cv.fillPoly(img, cnts, color)
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assert False
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except:
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assert True
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def test_filter2d(self):
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img = self.get_sample('samples/data/lena.jpg', 1)
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eps = 0.001
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# compare 2 ways of computing 3x3 blur using the same function
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kernel = np.array([[1, 1, 1], [1, 1, 1], [1, 1, 1]], dtype='float32')
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img_blur0 = cv.filter2D(img, cv.CV_32F, kernel*(1./9))
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img_blur1 = cv.filter2Dp(img, kernel, ddepth=cv.CV_32F, scale=1./9)
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self.assertLess(cv.norm(img_blur0 - img_blur1, cv.NORM_INF), eps)
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