python-图像边缘算法-动态显示过程

import os
import matplotlib.pyplot as plt
import cv2
import numpy as np

def get_EuclideanDistance(x,y):
    myx = np.array(x)
    myy = np.array(y)
    return np.sqrt(np.sum((myx-myy)*(myx-myy)))

dir = os.listdir('./train')

if __name__ == '__main__':

    print('loading %s ...'%dir[1])
    print('working')
    image1 = cv2.imread('./train/'+dir[1])
    w = image1.shape[1]
    h = image1.shape[0]
    image2 = np.zeros((h,w,3), np.uint8)

    black = np.array([0,0,0])
    white = np.array([255,255,255])
    centercolor = np.array([125,125,125])
    #此处为关键，打开图片框
    plt.ion()
    i = 0
    for y in range(0,h-1):
        for x in range(0,w-1):

            down = image1[y+1,x,:]
            right = image1[y,x+1,:]

            here = image1[y,x,:]
            here2 = here
            right2 = right
            down2 = down
            if get_EuclideanDistance(here2,down2) > 16 and get_EuclideanDistance(here2,right2) > 16 :
                image2[y,x,:]=black
            elif get_EuclideanDistance(here2,down2) <=16 and get_EuclideanDistance(here2,right2)<=16:
                image2[y,x,:] = white
            else:
                image2[y,x,:] = centercolor

            i += 1
            #每2000此运算显示一次图片，频率太高影响运算速度
            if i %2000 == 0:
                plt.imshow(image2)
            #这里每次显示0.1秒
                plt.pause(0.1)
print("finish")
plt.show()