Tutorial Sobel Derivatives
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"""
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@file sobel_demo.py
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@brief Sample code using Sobel and/or Scharr OpenCV functions to make a simple Edge Detector
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"""
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import sys
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import cv2
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def main(argv):
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## [variables]
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# First we declare the variables we are going to use
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window_name = ('Sobel Demo - Simple Edge Detector')
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scale = 1
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delta = 0
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ddepth = cv2.CV_16S
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## [variables]
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## [load]
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# As usual we load our source image (src)
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# Check number of arguments
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if len(argv) < 1:
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print ('Not enough parameters')
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print ('Usage:\nmorph_lines_detection.py < path_to_image >')
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return -1
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# Load the image
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src = cv2.imread(argv[0], cv2.IMREAD_COLOR)
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# Check if image is loaded fine
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if src is None:
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print ('Error opening image: ' + argv[0])
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return -1
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## [load]
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## [reduce_noise]
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# Remove noise by blurring with a Gaussian filter ( kernel size = 3 )
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src = cv2.GaussianBlur(src, (3, 3), 0)
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## [reduce_noise]
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## [convert_to_gray]
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# Convert the image to grayscale
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gray = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
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## [convert_to_gray]
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## [sobel]
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# Gradient-X
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# grad_x = cv2.Scharr(gray,ddepth,1,0)
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grad_x = cv2.Sobel(gray, ddepth, 1, 0, ksize=3, scale=scale, delta=delta, borderType=cv2.BORDER_DEFAULT)
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# Gradient-Y
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# grad_y = cv2.Scharr(gray,ddepth,0,1)
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grad_y = cv2.Sobel(gray, ddepth, 0, 1, ksize=3, scale=scale, delta=delta, borderType=cv2.BORDER_DEFAULT)
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## [sobel]
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## [convert]
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# converting back to uint8
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abs_grad_x = cv2.convertScaleAbs(grad_x)
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abs_grad_y = cv2.convertScaleAbs(grad_y)
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## [convert]
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## [blend]
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## Total Gradient (approximate)
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grad = cv2.addWeighted(abs_grad_x, 0.5, abs_grad_y, 0.5, 0)
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## [blend]
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## [display]
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cv2.imshow(window_name, grad)
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cv2.waitKey(0)
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## [display]
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return 0
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if __name__ == "__main__":
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main(sys.argv[1:])
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