原始图：
结果
代码
# -*- coding: utf-8 -*-
import cv2
import numpy as np
opencv=cv2.imread("opencv.jpg")
hsv = cv2.cvtColor(opencv, cv2.COLOR_BGR2HSV)
cv2.imshow('opencv',opencv)
#=============指定蓝色值的范围=============
minBlue = np.array([110,50,50])
maxBlue = np.array([130,255,255])
#确定蓝色区域 -获取掩密码
# cv2.inRange(image,lower,upper)
# image:原图像
# lower:图像中低于这个lower_red的值，值变为0
# upper:图像中高于这个upper_red的值，值变为0
# 而在lower_red～upper_red之间的值变成255
mask = cv2.inRange(hsv, minBlue, maxBlue)
#通过掩码控制的按位与，锁定蓝色区域
blue = cv2.bitwise_and(opencv,opencv, mask= mask)
cv2.imshow('blue',blue)
#=============指定绿色值的范围=============
minGreen = np.array([50,50,50])
maxGreen = np.array([70,255,255])
#确定绿色区域
mask = cv2.inRange(hsv, minGreen, maxGreen)
#通过掩码控制的按位与，锁定绿色区域
green = cv2.bitwise_and(opencv,opencv, mask= mask)
cv2.imshow('green',green)
#=============指定红色值的范围=============
minRed = np.array([0,50,50])
maxRed = np.array([30,255,255])
#确定红色区域
mask = cv2.inRange(hsv, minRed, maxRed)
#通过掩码控制的按位与，锁定红色区域
red= cv2.bitwise_and(opencv,opencv, mask= mask)
cv2.imshow('red',red)
cv2.waitKey()
cv2.destroyAllWindows()