Canny+Hough可视化调参（Trackbar）

这里引用一个脑CT图片，用一天直线从中间分开。

g_CannyThred_1：canny边缘检测运用高低阈值的方法（小于低阈值忽略，高于高阈值为边缘，高低阈值之间的值如果与边缘相连则判定为边缘），官方推荐高阈值是底阈值的2到3倍。本惨数为底阈值的参数。

g_CannyP_1：在代码中(g_CannyThred_1 + 1) * (2 + g_CannyP_1 / 100.0)这样计算高阈值，使高阈值在低阈值的2到3倍之间浮动。

g_HoughThred：霍夫变换的阈值。当霍夫空间上累加器超过阈值才看作是直线。

  

import cv2
import numpy as np

def nothing(x):
    pass
g_CannyThred = 50
g_CannyP =1
g_HoughThred = 40
rawimg = cv2.imread('247200635611893252.jpg') 
gray = cv2.cvtColor(rawimg,cv2.COLOR_BGR2GRAY) 
img = cv2.GaussianBlur(gray,(3,3),0)
result=img.copy()
cv2.namedWindow('hough_demo') 
cv2.createTrackbar("CannyThred", "hough_demo", g_CannyThred, 255,nothing)
cv2.createTrackbar("g_CannyP", "hough_demo", g_CannyP,100,nothing)  
cv2.createTrackbar("g_HoughThred", "hough_demo",  g_HoughThred, 200,nothing)
while(1):
    cv2.imshow('hough_demo',result)
    result=img.copy()
    k = cv2.waitKey(1) & 0xFF
    if k == 27:
        cv2.destroyAllWindows()
        break
    g_CannyThred_1= cv2.getTrackbarPos('CannyThred','hough_demo')
    g_CannyP_1= cv2.getTrackbarPos('g_CannyP','hough_demo')
    g_HoughThred_1= cv2.getTrackbarPos('g_HoughThred','hough_demo')
    cannyImage = cv2.Canny(img,(float)(g_CannyThred_1),(float)((g_CannyThred_1 + 1) * (2 + g_CannyP_1 / 100.0)),apertureSize = 3)    
    HoughLines=cv2.HoughLines(cannyImage,1, np.pi/ 180, g_HoughThred_1 + 1)  
    for line in HoughLines[0]:  
#         if line==None:
#             break
        rho = line[0] #第一个元素是距离rho  
        theta = line[1]#第二个元素是角度theta  
        if  (theta < (np.pi/4. )) or (theta > (3.*np.pi/4.0)): #垂直直线  
            #该直线与第一行的交点  
            pt1 = (int(rho/np.cos(theta)),0)
            #该直线与最后一行的焦点  
            pt2 = (int((rho-result.shape[0]*np.sin(theta))/np.cos(theta)),result.shape[0]) 
            #绘制一条白线  
            cv2.line( result, pt1, pt2, (255))
        else: #水平直线  
            # 该直线与第一列的交点  
            pt1 = (0,int(rho/np.sin(theta))) 
            #该直线与最后一列的交点  
            pt2 = (result.shape[1], int((rho-result.shape[1]*np.cos(theta))/np.sin(theta)))
            #绘制一条直线  
            cv2.line(result,pt1,pt2,(255),1)

cv2.destroyAllWindows()