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
# 红底变蓝底
# 将在两个阈值内的像素值设置为⽩⾊（255），
#⽽不在阈值区间内的像素值设置为⿊⾊（0）
#
lower_red= 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)
