pythoncode-tutorials/machine-learning/sift/sift.py at master · hulinhui-code/pythoncode-tutorials · GitHub

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importcv2

# reading the image
img=cv2.imread('table.jpg')
# convert to greyscale
gray=cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# create SIFT feature extractor
sift=cv2.xfeatures2d.SIFT_create()
# detect features from the image
keypoints, descriptors=sift.detectAndCompute(img, None)
# draw the detected key points
sift_image=cv2.drawKeypoints(gray, keypoints, img)
# show the image
cv2.imshow('image', sift_image)
# save the image
cv2.imwrite("table-sift.jpg", sift_image)
cv2.waitKey(0)
cv2.destroyAllWindows()
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importcv2

# reading the image
img=cv2.imread('table.jpg')
# convert to greyscale
gray=cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# create SIFT feature extractor
sift=cv2.xfeatures2d.SIFT_create()
# detect features from the image
keypoints, descriptors=sift.detectAndCompute(img, None)
# draw the detected key points
sift_image=cv2.drawKeypoints(gray, keypoints, img)
# show the image
cv2.imshow('image', sift_image)
# save the image
cv2.imwrite("table-sift.jpg", sift_image)
cv2.waitKey(0)
cv2.destroyAllWindows()
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importcv2

# reading the image
img=cv2.imread('table.jpg')
# convert to greyscale
gray=cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# create SIFT feature extractor
sift=cv2.xfeatures2d.SIFT_create()
# detect features from the image
keypoints, descriptors=sift.detectAndCompute(img, None)
# draw the detected key points
sift_image=cv2.drawKeypoints(gray, keypoints, img)
# show the image
cv2.imshow('image', sift_image)
# save the image
cv2.imwrite("table-sift.jpg", sift_image)
cv2.waitKey(0)
cv2.destroyAllWindows()
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importcv2

# reading the image
img=cv2.imread('table.jpg')
# convert to greyscale
gray=cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# create SIFT feature extractor
sift=cv2.xfeatures2d.SIFT_create()
# detect features from the image
keypoints, descriptors=sift.detectAndCompute(img, None)
# draw the detected key points
sift_image=cv2.drawKeypoints(gray, keypoints, img)
# show the image
cv2.imshow('image', sift_image)
# save the image
cv2.imwrite("table-sift.jpg", sift_image)
cv2.waitKey(0)
cv2.destroyAllWindows()
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importcv2

# reading the image
img=cv2.imread('table.jpg')
# convert to greyscale
gray=cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# create SIFT feature extractor
sift=cv2.xfeatures2d.SIFT_create()
# detect features from the image
keypoints, descriptors=sift.detectAndCompute(img, None)
# draw the detected key points
sift_image=cv2.drawKeypoints(gray, keypoints, img)
# show the image
cv2.imshow('image', sift_image)
# save the image
cv2.imwrite("table-sift.jpg", sift_image)
cv2.waitKey(0)
cv2.destroyAllWindows()
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importcv2

# reading the image
img=cv2.imread('table.jpg')
# convert to greyscale
gray=cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# create SIFT feature extractor
sift=cv2.xfeatures2d.SIFT_create()
# detect features from the image
keypoints, descriptors=sift.detectAndCompute(img, None)
# draw the detected key points
sift_image=cv2.drawKeypoints(gray, keypoints, img)
# show the image
cv2.imshow('image', sift_image)
# save the image
cv2.imwrite("table-sift.jpg", sift_image)
cv2.waitKey(0)
cv2.destroyAllWindows()
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importcv2

# reading the image
img=cv2.imread('table.jpg')
# convert to greyscale
gray=cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# create SIFT feature extractor
sift=cv2.xfeatures2d.SIFT_create()
# detect features from the image
keypoints, descriptors=sift.detectAndCompute(img, None)
# draw the detected key points
sift_image=cv2.drawKeypoints(gray, keypoints, img)
# show the image
cv2.imshow('image', sift_image)
# save the image
cv2.imwrite("table-sift.jpg", sift_image)
cv2.waitKey(0)
cv2.destroyAllWindows()