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Update python samples
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0a7a54f312
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@ -30,6 +30,7 @@ def main():
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circles = cv.HoughCircles(img, cv.HOUGH_GRADIENT, 1, 10, np.array([]), 100, 30, 1, 30)
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if circles is not None: # Check if circles have been found and only then iterate over these and add them to the image
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circles = np.uint16(np.around(circles))
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_a, b, _c = circles.shape
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for i in range(b):
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cv.circle(cimg, (circles[0][i][0], circles[0][i][1]), circles[0][i][2], (0, 0, 255), 3, cv.LINE_AA)
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@ -38,10 +38,10 @@ def Hist_and_Backproj(val):
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## [Read the image]
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parser = argparse.ArgumentParser(description='Code for Back Projection tutorial.')
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parser.add_argument('--input', help='Path to input image.')
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parser.add_argument('--input', help='Path to input image.', default='home.jpg')
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args = parser.parse_args()
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src = cv.imread(args.input)
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src = cv.imread(cv.samples.findFile(args.input))
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if src is None:
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print('Could not open or find the image:', args.input)
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exit(0)
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@ -54,10 +54,10 @@ def Hist_and_Backproj(mask):
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# Read the image
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parser = argparse.ArgumentParser(description='Code for Back Projection tutorial.')
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parser.add_argument('--input', help='Path to input image.')
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parser.add_argument('--input', help='Path to input image.', default='home.jpg')
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args = parser.parse_args()
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src = cv.imread(args.input)
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src = cv.imread(cv.samples.findFile(args.input))
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if src is None:
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print('Could not open or find the image:', args.input)
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exit(0)
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@ -53,14 +53,14 @@ cv.normalize(r_hist, r_hist, alpha=0, beta=hist_h, norm_type=cv.NORM_MINMAX)
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## [Draw for each channel]
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for i in range(1, histSize):
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cv.line(histImage, ( bin_w*(i-1), hist_h - int(round(b_hist[i-1])) ),
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( bin_w*(i), hist_h - int(round(b_hist[i])) ),
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cv.line(histImage, ( bin_w*(i-1), hist_h - int(b_hist[i-1]) ),
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( bin_w*(i), hist_h - int(b_hist[i]) ),
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( 255, 0, 0), thickness=2)
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cv.line(histImage, ( bin_w*(i-1), hist_h - int(round(g_hist[i-1])) ),
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( bin_w*(i), hist_h - int(round(g_hist[i])) ),
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cv.line(histImage, ( bin_w*(i-1), hist_h - int(g_hist[i-1]) ),
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( bin_w*(i), hist_h - int(g_hist[i]) ),
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( 0, 255, 0), thickness=2)
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cv.line(histImage, ( bin_w*(i-1), hist_h - int(round(r_hist[i-1])) ),
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( bin_w*(i), hist_h - int(round(r_hist[i])) ),
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cv.line(histImage, ( bin_w*(i-1), hist_h - int(r_hist[i-1]) ),
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( bin_w*(i), hist_h - int(r_hist[i]) ),
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( 0, 0, 255), thickness=2)
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## [Draw for each channel]
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@ -30,7 +30,7 @@ def goodFeaturesToTrack_Demo(val):
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print('** Number of corners detected:', corners.shape[0])
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radius = 4
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for i in range(corners.shape[0]):
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cv.circle(copy, (corners[i,0,0], corners[i,0,1]), radius, (rng.randint(0,256), rng.randint(0,256), rng.randint(0,256)), cv.FILLED)
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cv.circle(copy, (int(corners[i,0,0]), int(corners[i,0,1])), radius, (rng.randint(0,256), rng.randint(0,256), rng.randint(0,256)), cv.FILLED)
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# Show what you got
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cv.namedWindow(source_window)
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@ -30,7 +30,7 @@ def goodFeaturesToTrack_Demo(val):
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print('** Number of corners detected:', corners.shape[0])
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radius = 4
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for i in range(corners.shape[0]):
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cv.circle(copy, (corners[i,0,0], corners[i,0,1]), radius, (rng.randint(0,256), rng.randint(0,256), rng.randint(0,256)), cv.FILLED)
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cv.circle(copy, (int(corners[i,0,0]), int(corners[i,0,1])), radius, (rng.randint(0,256), rng.randint(0,256), rng.randint(0,256)), cv.FILLED)
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# Show what you got
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cv.namedWindow(source_window)
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@ -53,7 +53,7 @@ thickness = 2
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sv = svm.getUncompressedSupportVectors()
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for i in range(sv.shape[0]):
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cv.circle(image, (sv[i,0], sv[i,1]), 6, (128, 128, 128), thickness)
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cv.circle(image, (int(sv[i,0]), int(sv[i,1])), 6, (128, 128, 128), thickness)
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## [show_vectors]
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cv.imwrite('result.png', image) # save the image
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@ -94,13 +94,13 @@ thick = -1
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for i in range(NTRAINING_SAMPLES):
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px = trainData[i,0]
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py = trainData[i,1]
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cv.circle(I, (px, py), 3, (0, 255, 0), thick)
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cv.circle(I, (int(px), int(py)), 3, (0, 255, 0), thick)
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# Class 2
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for i in range(NTRAINING_SAMPLES, 2*NTRAINING_SAMPLES):
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px = trainData[i,0]
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py = trainData[i,1]
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cv.circle(I, (px, py), 3, (255, 0, 0), thick)
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cv.circle(I, (int(px), int(py)), 3, (255, 0, 0), thick)
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## [show_data]
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#------------------------- 6. Show support vectors --------------------------------------------
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@ -109,7 +109,7 @@ thick = 2
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sv = svm.getUncompressedSupportVectors()
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for i in range(sv.shape[0]):
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cv.circle(I, (sv[i,0], sv[i,1]), 6, (128, 128, 128), thick)
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cv.circle(I, (int(sv[i,0]), int(sv[i,1])), 6, (128, 128, 128), thick)
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## [show_vectors]
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cv.imwrite('result.png', I) # save the Image
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@ -33,7 +33,7 @@ def hog(img):
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return hist
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## [hog]
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img = cv.imread('digits.png',0)
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img = cv.imread(cv.samples.findFile('digits.png'),0)
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if img is None:
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raise Exception("we need the digits.png image from samples/data here !")
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@ -40,6 +40,7 @@ while(1):
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p1, st, err = cv.calcOpticalFlowPyrLK(old_gray, frame_gray, p0, None, **lk_params)
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# Select good points
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if p1 is not None:
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good_new = p1[st==1]
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good_old = p0[st==1]
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@ -47,8 +48,8 @@ while(1):
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for i,(new,old) in enumerate(zip(good_new, good_old)):
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a,b = new.ravel()
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c,d = old.ravel()
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mask = cv.line(mask, (a,b),(c,d), color[i].tolist(), 2)
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frame = cv.circle(frame,(a,b),5,color[i].tolist(),-1)
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mask = cv.line(mask, (int(a),int(b)),(int(c),int(d)), color[i].tolist(), 2)
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frame = cv.circle(frame,(int(a),int(b)),5,color[i].tolist(),-1)
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img = cv.add(frame,mask)
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cv.imshow('frame',img)
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@ -86,8 +86,8 @@ def main():
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framenum = -1 # Frame counter
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captRefrnc = cv.VideoCapture(sourceReference)
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captUndTst = cv.VideoCapture(sourceCompareWith)
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captRefrnc = cv.VideoCapture(cv.samples.findFileOrKeep(sourceReference))
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captUndTst = cv.VideoCapture(cv.samples.findFileOrKeep(sourceCompareWith))
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if not captRefrnc.isOpened():
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print("Could not open the reference " + sourceReference)
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