Vanishing point detection for 2 & 3 parallel lines

Author: soumenca

VanishingPoint_detection/img1.jpg

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+
+import cv2
+import math
+import random
+import numpy as np
+import matplotlib.pyplot as plt
+from PIL import Image
+from scipy.ndimage import filters
+
+
+def slopIntercept(x, y):
+ slope = (y[1] - y[0])/(x[1] - x[0])
+ intercept = y[1] - slope*(x[1])
+ return [slope,intercept]
+
+def det(a, b):
+ return a[0] * b[1] - a[1] * b[0]
+
+def line_intersection(line1, line2):
+ xdiff = (line1[0][0] - line1[1][0], line2[0][0] - line2[1][0])
+ ydiff = (line1[0][1] - line1[1][1], line2[0][1] - line2[1][1])
+
+ div = det(xdiff, ydiff)
+ if div == 0:
+ return False
+
+ d = (det(*line1), det(*line2))
+ x = det(d, xdiff) / div
+ y = det(d, ydiff) / div
+ return x, y
+
+
+def vPoint(img):
+n1 = input('How many line want to select: ')
+n = 2*n1
+lines = []
+plt.imshow(img)
+p = plt.ginput(n)
+
+for i in range(0, n, 4):
+plt.plot([p[i][0], p[i+1][0]], [p[i][1], p[i+1][1]], marker = 'o')
+plt.plot([p[i+2][0], p[i+3][0]], [p[i+2][1], p[i+3][1]], marker = 'o')
+
+ for j in range(0, n, 6):
+ for i in range(j, j+6, 2):
+ x = [p[i][0], p[i+1][0]]
+ y = [p[i][1], p[i+1][1]]
+ lines.append(slopIntercept(x, y))
+
+ list_vp = []
+ for j in range(0, n1, 3):
+ for i in range(j, j+3, 3):
+ ang1 = math.degrees(math.atan((lines[0][0] - lines[1][0])/(1+ lines[1][0]*lines[0][0])))
+ ang2 = math.degrees(math.atan((lines[1][0] - lines[2][0])/(1+ lines[2][0]*lines[1][0])))
+ if ang1 > 90:
+ ang1 = 180 - ang1
+ if ang2 > 90:
+ ang2 = 180 - ang2
+ if ang1 < ang2:
+ x = (lines[i][1] - lines[i+1][1])/(lines[i+1][0] - lines[i][0])
+ y = lines[i+1][0]*x + lines[i+1][1]
+ vp = (x, y)
+ #vp = line_intersection((p[i], p[i+1]), (p[i+2], p[i+3]))
+ list_vp.append(vp)
+ else:
+ x = (lines[i+2][1] - lines[i+1][1])/(lines[i+1][0] - lines[i+2][0])
+ y = lines[i+1][0]*x + lines[i+1][1]
+ vp = (x, y)
+ #vp = line_intersection((p[i+2], p[i+3]), (p[i+4], p[i+5]))
+ list_vp.append(vp)
+ 
+
+plt.plot([list_vp[0][0], list_vp[1][0]], [list_vp[0][1], list_vp[1][1]], marker = 'o')
+print('The VPs coorinate are: ', list_vp)
+x1, y1 = list_vp[0]
+x2, y2 = list_vp[1]
+a, b = (y1 - y2), (x1 - x2)
+slope = a/b
+intercept = y1 - slope*(x1)
+print("The equataion is:", a,"x - ",b,"y + ",intercept*b," = 0")
+plt.show()
+
+def main():
+filename = 'img1.jpg'
+im = Image.open(filename, 'r')
+img = np.float32(im)
+
+vPoint(im)
+
+
+if __name__== "__main__":
+main()

VanishingPoint_detection/vanishing_point_threeLine.py

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+from scipy.ndimage import filters
+import cv2
+import numpy as np
+import matplotlib.pyplot as plt
+import random
+from PIL import Image
+
+def det(a, b):
+ return a[0] * b[1] - a[1] * b[0]
+
+def line_intersection(line1, line2):
+ xdiff = (line1[0][0] - line1[1][0], line2[0][0] - line2[1][0])
+ ydiff = (line1[0][1] - line1[1][1], line2[0][1] - line2[1][1])
+
+ div = det(xdiff, ydiff)
+ if div == 0:
+ return False
+
+ d = (det(*line1), det(*line2))
+ x = det(d, xdiff) / div
+ y = det(d, ydiff) / div
+ return x, y
+
+
+def vPoint(img):
+n1 = input('How many line want to select: ')
+n = 2*n1
+ list_vp = []
+plt.imshow(img)
+p = plt.ginput(n)
+ for i in range(0, n, 4):
+ plt.plot([p[i][0], p[i+1][0]], [p[i][1], p[i+1][1]], marker = 'o')
+plt.plot([p[i+2][0], p[i+3][0]], [p[i+2][1], p[i+3][1]], marker = 'o')
+ vp = line_intersection((p[i], p[i+1]), (p[i+2], p[i+3]))
+ print(vp)
+ list_vp.append(vp)
+ #plt.plot(vp[0], vp[1], 'ro', ls='')
+ plt.plot([list_vp[0][0], list_vp[1][0]], [list_vp[0][1], list_vp[1][1]], marker = 'o')
+ print('The VPs coorinate are: ', list_vp)
+ x1, y1 = list_vp[0]
+ x2, y2 = list_vp[1]
+ a, b = (y1 - y2), (x1 - x2)
+ slope = a/b
+ intercept = y1 - slope*(x1)
+ print("The equataion is:", a,"x - ",b,"y + ",intercept*b," = 0")
+ plt.show()
+
+def main():
+filename = 'img1.jpg'
+im = Image.open(filename, 'r')
+img = np.float32(im)
+
+R = vPoint(im)
+
+
+
+if __name__== "__main__":
+main()