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https://gitcode.com/gh_mirrors/es/esp32-opencv.git
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80 lines
2.2 KiB
Python
80 lines
2.2 KiB
Python
"""
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@file hough_lines.py
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@brief This program demonstrates line finding with the Hough transform
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"""
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import sys
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import math
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import cv2 as cv
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import numpy as np
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def main(argv):
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## [load]
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default_file = 'sudoku.png'
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filename = argv[0] if len(argv) > 0 else default_file
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# Loads an image
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src = cv.imread(cv.samples.findFile(filename), cv.IMREAD_GRAYSCALE)
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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!')
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print ('Usage: hough_lines.py [image_name -- default ' + default_file + '] \n')
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return -1
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## [load]
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## [edge_detection]
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# Edge detection
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dst = cv.Canny(src, 50, 200, None, 3)
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## [edge_detection]
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# Copy edges to the images that will display the results in BGR
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cdst = cv.cvtColor(dst, cv.COLOR_GRAY2BGR)
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cdstP = np.copy(cdst)
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## [hough_lines]
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# Standard Hough Line Transform
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lines = cv.HoughLines(dst, 1, np.pi / 180, 150, None, 0, 0)
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## [hough_lines]
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## [draw_lines]
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# Draw the lines
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if lines is not None:
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for i in range(0, len(lines)):
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rho = lines[i][0][0]
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theta = lines[i][0][1]
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a = math.cos(theta)
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b = math.sin(theta)
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x0 = a * rho
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y0 = b * rho
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pt1 = (int(x0 + 1000*(-b)), int(y0 + 1000*(a)))
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pt2 = (int(x0 - 1000*(-b)), int(y0 - 1000*(a)))
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cv.line(cdst, pt1, pt2, (0,0,255), 3, cv.LINE_AA)
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## [draw_lines]
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## [hough_lines_p]
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# Probabilistic Line Transform
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linesP = cv.HoughLinesP(dst, 1, np.pi / 180, 50, None, 50, 10)
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## [hough_lines_p]
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## [draw_lines_p]
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# Draw the lines
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if linesP is not None:
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for i in range(0, len(linesP)):
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l = linesP[i][0]
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cv.line(cdstP, (l[0], l[1]), (l[2], l[3]), (0,0,255), 3, cv.LINE_AA)
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## [draw_lines_p]
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## [imshow]
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# Show results
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cv.imshow("Source", src)
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cv.imshow("Detected Lines (in red) - Standard Hough Line Transform", cdst)
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cv.imshow("Detected Lines (in red) - Probabilistic Line Transform", cdstP)
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## [imshow]
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## [exit]
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# Wait and Exit
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cv.waitKey()
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return 0
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## [exit]
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if __name__ == "__main__":
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main(sys.argv[1:])
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