import cv2 import numpy as np file=r"C:/Users/58219/Desktop/1.jpg" # step1:读取照⽚
img = cv2.imread(file) # step1.2:缩放图⽚() img = cv2.resize(img, None, fx=1.5,
fy=1.5) rows, cols, channels = img.shape # 展⽰图⽚ cv2.imshow("original...", img)
# step2.1 图⽚转换为灰度图并显⽰ hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) # :图⽚的⼆值化处理 #

np.array([0,125,125]) upper_red = np.array([255,255,255]) mask =
cv2.inRange(hsv, lower_red, upper_red)
#step2.3:腐蚀膨胀若是腐蚀膨胀后仍有⽩⾊噪点，可以增加iterations的值 erode = cv2.erode(mask, None,
iterations=5) # cv2.imshow('erode', erode) dilate = cv2.dilate(erode, None,
iterations=7) # step3遍历每个像素点，进⾏颜⾊的替换 ''' #若是想要将红底变成蓝底img[i,j]=(255,0,0)，
#若是想将蓝底变为红底则img[i,j]=(0,0,255), #若是想变⽩底img[i,j]=(255,255,255) ''' for i in
range(rows): for j in range(cols): if dilate[i,j] ==255: # 像素点255表⽰⽩⾊,180为灰度
img[i,j]=(255,255,255) # 此处替换颜⾊，为BGR通道，不是RGB通道 #step4 显⽰图像
new_file=r"C:/Users/58219/Desktop/11.jpg" cv2.imwrite(new_file, img) res =
cv2.imread(new_file) cv2.imshow('result...', res) # 窗⼝等待的命令，0表⽰⽆限等待
cv2.waitKey(0)

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