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Update python samples

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This commit is contained in:
Suleyman TURKMEN 2021-02-17 12:04:49 +03:00
parent 0a7a54f312
commit 9b399f3960
11 changed files with 25 additions and 23 deletions
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1
samples/python/houghcircles.py
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@ -30,6 +30,7 @@ def main():
circles = cv.HoughCircles(img, cv.HOUGH_GRADIENT, 1, 10, np.array([]), 100, 30, 1, 30) circles = cv.HoughCircles(img, cv.HOUGH_GRADIENT, 1, 10, np.array([]), 100, 30, 1, 30)
if circles is not None: # Check if circles have been found and only then iterate over these and add them to the image if circles is not None: # Check if circles have been found and only then iterate over these and add them to the image
circles = np.uint16(np.around(circles))
_a, b, _c = circles.shape _a, b, _c = circles.shape
for i in range(b): for i in range(b):
cv.circle(cimg, (circles[0][i][0], circles[0][i][1]), circles[0][i][2], (0, 0, 255), 3, cv.LINE_AA) cv.circle(cimg, (circles[0][i][0], circles[0][i][1]), circles[0][i][2], (0, 0, 255), 3, cv.LINE_AA)

4
samples/python/tutorial_code/Histograms_Matching/back_projection/calcBackProject_Demo1.py
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@ -38,10 +38,10 @@ def Hist_and_Backproj(val):
## [Read the image] ## [Read the image]
parser = argparse.ArgumentParser(description='Code for Back Projection tutorial.') parser = argparse.ArgumentParser(description='Code for Back Projection tutorial.')
parser.add_argument('--input', help='Path to input image.') parser.add_argument('--input', help='Path to input image.', default='home.jpg')
args = parser.parse_args() args = parser.parse_args()
src = cv.imread(args.input) src = cv.imread(cv.samples.findFile(args.input))
if src is None: if src is None:
print('Could not open or find the image:', args.input) print('Could not open or find the image:', args.input)
exit(0) exit(0)

4
samples/python/tutorial_code/Histograms_Matching/back_projection/calcBackProject_Demo2.py
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@ -54,10 +54,10 @@ def Hist_and_Backproj(mask):
# Read the image # Read the image
parser = argparse.ArgumentParser(description='Code for Back Projection tutorial.') parser = argparse.ArgumentParser(description='Code for Back Projection tutorial.')
parser.add_argument('--input', help='Path to input image.') parser.add_argument('--input', help='Path to input image.', default='home.jpg')
args = parser.parse_args() args = parser.parse_args()
src = cv.imread(args.input) src = cv.imread(cv.samples.findFile(args.input))
if src is None: if src is None:
print('Could not open or find the image:', args.input) print('Could not open or find the image:', args.input)
exit(0) exit(0)

12
samples/python/tutorial_code/Histograms_Matching/histogram_calculation/calcHist_Demo.py
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@ -53,14 +53,14 @@ cv.normalize(r_hist, r_hist, alpha=0, beta=hist_h, norm_type=cv.NORM_MINMAX)
## [Draw for each channel] ## [Draw for each channel]
for i in range(1, histSize): for i in range(1, histSize):
cv.line(histImage, ( bin_w*(i-1), hist_h - int(round(b_hist[i-1])) ), cv.line(histImage, ( bin_w*(i-1), hist_h - int(b_hist[i-1]) ),
( bin_w*(i), hist_h - int(round(b_hist[i])) ), ( bin_w*(i), hist_h - int(b_hist[i]) ),
( 255, 0, 0), thickness=2) ( 255, 0, 0), thickness=2)
cv.line(histImage, ( bin_w*(i-1), hist_h - int(round(g_hist[i-1])) ), cv.line(histImage, ( bin_w*(i-1), hist_h - int(g_hist[i-1]) ),
( bin_w*(i), hist_h - int(round(g_hist[i])) ), ( bin_w*(i), hist_h - int(g_hist[i]) ),
( 0, 255, 0), thickness=2) ( 0, 255, 0), thickness=2)
cv.line(histImage, ( bin_w*(i-1), hist_h - int(round(r_hist[i-1])) ), cv.line(histImage, ( bin_w*(i-1), hist_h - int(r_hist[i-1]) ),
( bin_w*(i), hist_h - int(round(r_hist[i])) ), ( bin_w*(i), hist_h - int(r_hist[i]) ),
( 0, 0, 255), thickness=2) ( 0, 0, 255), thickness=2)
## [Draw for each channel] ## [Draw for each channel]

2
samples/python/tutorial_code/TrackingMotion/corner_subpixels/cornerSubPix_Demo.py
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@ -30,7 +30,7 @@ def goodFeaturesToTrack_Demo(val):
print('** Number of corners detected:', corners.shape[0]) print('** Number of corners detected:', corners.shape[0])
radius = 4 radius = 4
for i in range(corners.shape[0]): for i in range(corners.shape[0]):
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) 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)
# Show what you got # Show what you got
cv.namedWindow(source_window) cv.namedWindow(source_window)

2
samples/python/tutorial_code/TrackingMotion/good_features_to_track/goodFeaturesToTrack_Demo.py
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@ -30,7 +30,7 @@ def goodFeaturesToTrack_Demo(val):
print('** Number of corners detected:', corners.shape[0]) print('** Number of corners detected:', corners.shape[0])
radius = 4 radius = 4
for i in range(corners.shape[0]): for i in range(corners.shape[0]):
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) 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)
# Show what you got # Show what you got
cv.namedWindow(source_window) cv.namedWindow(source_window)

2
samples/python/tutorial_code/ml/introduction_to_svm/introduction_to_svm.py
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@ -53,7 +53,7 @@ thickness = 2
sv = svm.getUncompressedSupportVectors() sv = svm.getUncompressedSupportVectors()
for i in range(sv.shape[0]): for i in range(sv.shape[0]):
cv.circle(image, (sv[i,0], sv[i,1]), 6, (128, 128, 128), thickness) cv.circle(image, (int(sv[i,0]), int(sv[i,1])), 6, (128, 128, 128), thickness)
## [show_vectors] ## [show_vectors]
cv.imwrite('result.png', image) # save the image cv.imwrite('result.png', image) # save the image

6
samples/python/tutorial_code/ml/non_linear_svms/non_linear_svms.py
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@ -94,13 +94,13 @@ thick = -1
for i in range(NTRAINING_SAMPLES): for i in range(NTRAINING_SAMPLES):
px = trainData[i,0] px = trainData[i,0]
py = trainData[i,1] py = trainData[i,1]
cv.circle(I, (px, py), 3, (0, 255, 0), thick) cv.circle(I, (int(px), int(py)), 3, (0, 255, 0), thick)
# Class 2 # Class 2
for i in range(NTRAINING_SAMPLES, 2*NTRAINING_SAMPLES): for i in range(NTRAINING_SAMPLES, 2*NTRAINING_SAMPLES):
px = trainData[i,0] px = trainData[i,0]
py = trainData[i,1] py = trainData[i,1]
cv.circle(I, (px, py), 3, (255, 0, 0), thick) cv.circle(I, (int(px), int(py)), 3, (255, 0, 0), thick)
## [show_data] ## [show_data]
#------------------------- 6. Show support vectors -------------------------------------------- #------------------------- 6. Show support vectors --------------------------------------------
@ -109,7 +109,7 @@ thick = 2
sv = svm.getUncompressedSupportVectors() sv = svm.getUncompressedSupportVectors()
for i in range(sv.shape[0]): for i in range(sv.shape[0]):
cv.circle(I, (sv[i,0], sv[i,1]), 6, (128, 128, 128), thick) cv.circle(I, (int(sv[i,0]), int(sv[i,1])), 6, (128, 128, 128), thick)
## [show_vectors] ## [show_vectors]
cv.imwrite('result.png', I) # save the Image cv.imwrite('result.png', I) # save the Image

2
samples/python/tutorial_code/ml/py_svm_opencv/hogsvm.py
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@ -33,7 +33,7 @@ def hog(img):
return hist return hist
## [hog] ## [hog]
img = cv.imread('digits.png',0) img = cv.imread(cv.samples.findFile('digits.png'),0)
if img is None: if img is None:
raise Exception("we need the digits.png image from samples/data here !") raise Exception("we need the digits.png image from samples/data here !")

9
samples/python/tutorial_code/video/optical_flow/optical_flow.py
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@ -40,15 +40,16 @@ while(1):
p1, st, err = cv.calcOpticalFlowPyrLK(old_gray, frame_gray, p0, None, **lk_params) p1, st, err = cv.calcOpticalFlowPyrLK(old_gray, frame_gray, p0, None, **lk_params)
# Select good points # Select good points
good_new = p1[st==1] if p1 is not None:
good_old = p0[st==1] good_new = p1[st==1]
good_old = p0[st==1]
# draw the tracks # draw the tracks
for i,(new,old) in enumerate(zip(good_new, good_old)): for i,(new,old) in enumerate(zip(good_new, good_old)):
a,b = new.ravel() a,b = new.ravel()
c,d = old.ravel() c,d = old.ravel()
mask = cv.line(mask, (a,b),(c,d), color[i].tolist(), 2) mask = cv.line(mask, (int(a),int(b)),(int(c),int(d)), color[i].tolist(), 2)
frame = cv.circle(frame,(a,b),5,color[i].tolist(),-1) frame = cv.circle(frame,(int(a),int(b)),5,color[i].tolist(),-1)
img = cv.add(frame,mask) img = cv.add(frame,mask)
cv.imshow('frame',img) cv.imshow('frame',img)

4
samples/python/tutorial_code/videoio/video-input-psnr-ssim.py
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@ -86,8 +86,8 @@ def main():
framenum = -1 # Frame counter framenum = -1 # Frame counter
captRefrnc = cv.VideoCapture(sourceReference) captRefrnc = cv.VideoCapture(cv.samples.findFileOrKeep(sourceReference))
captUndTst = cv.VideoCapture(sourceCompareWith) captUndTst = cv.VideoCapture(cv.samples.findFileOrKeep(sourceCompareWith))
if not captRefrnc.isOpened(): if not captRefrnc.isOpened():
print("Could not open the reference " + sourceReference) print("Could not open the reference " + sourceReference)