计算与直线共线的点

图像识别CV/pythoncv_learn/calc_parallel_lines.py

@@ -10,12 +10,20 @@ def calcY(p3y, A, B, L):
     b = (A * A) + (B * B)
     return int((a / math.sqrt(b)) + p3y)
 
+def calcCollinearX(line, p3y):
+    p1x, p1y, p2x, p2y = line
+    return int(((p3y - p2y) * p1x + (p1y - p3y) * p2x) / (p1y - p2y))
+
+def calcCollinearY(line, p3x):
+    p1x, p1y, p2x, p2y = line
+    return int(((p3x - p1x) * p2y + (p2x - p3x) * p1y) / (p2x - p1x))
+
 img = np.zeros((600, 600, 3), dtype = int)
 img = np.array(img,dtype='uint8')
 
-point1 = (100,230)
-point2 = (520,320)
-point3 = (500,200)
+point1 = (100,100)
+point2 = (500,500)
+point3 = (360,320)
 
 cv2.line(img, point1, point2, (0,0,255), 1)
 cv2.circle(img, point3, 3, (0,255,0), -1)
@@ -27,10 +35,23 @@ p3x, p3y = point3
 
 A = p1x - p2x
 B = p1y - p2y
+L = 100
 
-y = calcY(p3y, A, B, 400)
+y = calcY(p3y, A, B, L)
 x = calcX(p3x, p3y, A, B, y)
-cv2.line(img, point3, (x, y), (255, 0, 0), 1)
+point4 = (x, y)
+cv2.circle(img, point4, 3, (255,255,0), -1)
+cv2.line(img, point3, point4, (255, 0, 0), 1)
+
+n3_y = point3[1]
+n3_x = calcCollinearX((*point1, *point2), n3_y)
+n4_x = point4[0]
+n4_y = calcCollinearY((*point1, *point2), n4_x)
+cv2.circle(img, (n3_x, n3_y), 3, (0,255,0), -1)
+cv2.circle(img, (n4_x, n4_y), 3, (255,255,0), -1)
+
+
+
 cv2.imshow('img2', img)
 
 cv2.waitKey(0)