Measure max arc angle
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492b7d32c7
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038ca71b0c
51
3/hough.py
51
3/hough.py
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#! /usr/bin/env python
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# -*- coding: utf-8 -*-
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# vim:fenc=utf-8
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#
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# Copyright © 2018 pavle <pavle.portic@tilda.center>
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#
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# Distributed under terms of the MIT license.
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import cv2 as cv
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import numpy as np
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def main():
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filename = "set/A1.png"
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src = cv.imread(filename)
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# dst = cv.Canny(src, 50, 200, None, 3)
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edges = cv.Canny(src, 20, 250, apertureSize = 3)
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lines = cv.HoughLinesP(edges, 1, np.pi/180, 100, minLineLength=100, maxLineGap=10)
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dest = cv.cvtColor(edges, cv.COLOR_GRAY2BGR)
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for line in lines:
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x1,y1,x2,y2 = line[0]
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# cv.line(dest, (x1, y1), (x2, y2), (0, 0, 255), 2)
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cv.imshow('Detected', dest)
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cv.waitKey()
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# cdst = cv.cvtColor(dst, cv.COLOR_GRAY2BGR)
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# lines = cv.HoughLines(dst, 1, np.pi / 180, 150, None, 0, 0)
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# if lines is not None:
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# for i in [ 0 ]:
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# rho = lines[i][0][0]
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# theta = lines[i][0][1]
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# a = np.cos(theta)
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# b = np.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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# print type(lines)
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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.waitKey()
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return 0
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if __name__ == "__main__":
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main()
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28
3/proba.py
28
3/proba.py
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import cv2 as cv
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import numpy as np
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images = ['set/A1.png','set/A2.png','set/A3.png','set/A4.png','set/A5.png','set/A6.png','set/A7.png','set/A8.png','set/A9.png','set/A10.png']
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def main():
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i = images[4]
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img = cv.imread(i, 0)
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kernel = np.ones((5,5),np.uint8)
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closing = cv.morphologyEx(img, cv.MORPH_CLOSE, kernel)
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cv.imshow("Closing", closing)
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cv.imshow("Source", img)
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cv.waitKey()
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def rotateImage(image, angle):
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image_center = tuple(np.array(image.shape)/2)
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rot_mat = cv.getRotationMatrix2D(image_center,angle,1.0)
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result = cv.warpAffine(image, rot_mat, image.shape,flags=cv.INTER_LINEAR)
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return result
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if __name__ == "__main__":
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main()
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# -*- coding: utf-8 -*-
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# vim:fenc=utf-8
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#
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# Copyright © 2018 pavle <pavle.portic@tilda.center>
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#
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# Distributed under terms of the MIT license.
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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 os
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import numpy as np
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def main(argv):
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root = raw_input()
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# root = 'set/example_4'
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filename = [f for f in os.listdir(root) if os.path.isfile(os.path.join(root, f))]
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filename.sort()
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filename = os.path.join(root, filename[0])
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src = cv.imread(filename)
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img = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
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canny = cv.Canny(img, 50, 200, None, 3)
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lines = detect_lines(canny)
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for l in lines:
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cv.line(src, (l[0], l[1]), (l[2], l[3]), (0,0,255), 1, cv.LINE_AA)
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circle = detect_circle(img)
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print circle[0], circle[1], len(lines)/2, 0, 0, 0, 0
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# cv.imshow("Probabilistic Line Transform", src)
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# cv.imshow("Canny", canny)
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# cv.waitKey()
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return 0
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def detect_lines(img):
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linesP = cv.HoughLinesP(img, 1, np.pi / 180, 45, None, 30, 50)
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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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lines.append(linesP[i][0])
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return lines
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def detect_circle(img):
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rows = img.shape[0]
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circles = cv.HoughCircles(img, cv.HOUGH_GRADIENT, 1, rows/16, 100, 100, 30, 1, 50)
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if circles is not None:
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circles = np.uint16(np.around(circles))
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return circles[0][0][0], circles[0][0][1]
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return 0, 0
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if __name__ == "__main__":
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main(sys.argv[1:])
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@ -0,0 +1,128 @@
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# -*- coding: utf-8 -*-
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# vim:fenc=utf-8
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#
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# Copyright © 2018 pavle <pavle.portic@tilda.center>
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#
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# Distributed under terms of the MIT license.
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import cv2 as cv
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import numpy as np
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import os
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def main():
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# root = raw_input()
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root = 'set/example_4'
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filename = [f for f in os.listdir(root) if os.path.isfile(os.path.join(root, f))]
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filename.sort()
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filename = os.path.join(root, filename[0])
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src = cv.imread(filename)
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img = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
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canny = cv.Canny(img, 50, 200, None, 3)
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lines = detect_lines(canny)
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for l in lines:
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cv.line(src, (l[0], l[1]), (l[2], l[3]), (0,0,255), 1, cv.LINE_AA)
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circle = detect_circle(img)
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arc = measure_arc(img, circle[2], (circle[0], circle[1]))
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print circle[0], circle[1], len(lines)/2, 0, arc, 0, 0
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# cv.imshow("Probabilistic Line Transform", src)
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# cv.imshow("Canny", canny)
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# cv.waitKey()
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return 0
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def detect_lines(img):
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linesP = cv.HoughLinesP(img, 1, np.pi / 180, 45, None, 30, 50)
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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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lines.append(linesP[i][0])
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return lines
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def detect_circle(img):
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rows = img.shape[0]
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circles = cv.HoughCircles(img, cv.HOUGH_GRADIENT, 1, rows/16, 100, 100, 30, 1, 50)
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if circles is not None:
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circles = np.uint16(np.around(circles))
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return circles[0][0]
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return [0, 0, 0]
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def measure_arc(img, r, c):
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r += 2
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phi = 10
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while True:
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x, y = np.int0(pol2car(r, phi))
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x += c[0]
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y += c[1]
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if img[y, x] > 128:
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break
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phi += 2
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if phi == 360:
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return 360
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arcs = []
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while True:
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curr_phi = 0
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max_phi = 0
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p = phi + 1
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while True:
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x, y = np.int0(pol2car(r, p))
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x += c[0]
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y += c[1]
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if img[y, x] < 255:
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curr_phi += 1
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else:
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if curr_phi > max_phi:
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max_phi = curr_phi
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curr_phi = 0
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if p == phi:
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break
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# print curr_phi
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# copy = cv.cvtColor(img, cv.COLOR_GRAY2BGR)
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# cv.circle(copy, (x, y), 1, (0, 0, 255), 2)
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# cv.imshow("rotate", copy)
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# cv.waitKey()
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p += 1
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if p >= 360:
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p = 0
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if max_phi == 0:
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break
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arcs.append(max_phi)
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r += 5
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return max(arcs)
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def car2pol(x, y):
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return np.sqrt(x**2 + y**2), np.arctan2(y, x)
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def pol2car(r, p):
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p = np.radians(p)
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return r * np.cos(p), r * np.sin(p)
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if __name__ == "__main__":
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main()
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