python opencv识别红绿灯

 流程图如下

 全代码：

import cv2
import numpy as np

cap = cv2.VideoCapture('red.mp4')
while True:
    ret, frame = cap.read()
    if ret == False:
        break
    frame = cv2.resize(frame, (1720, 800))
    # 截取roi区域
    roiColor = frame[320:340, 510:600]
    # 转换hsv颜色空间
    hsv = cv2.cvtColor(roiColor, cv2.COLOR_BGR2HSV)

    # red
    lower_hsv_red = np.array([157, 177, 122])
    upper_hsv_red = np.array([179, 255, 255])
    mask_red = cv2.inRange(hsv, lowerb=lower_hsv_red, upperb=upper_hsv_red)
    # 中值滤波
    red_blur = cv2.medianBlur(mask_red, 7)
    # green
    lower_hsv_green = np.array([49, 79, 137])
    upper_hsv_green = np.array([90, 255, 255])
    mask_green = cv2.inRange(hsv, lowerb=lower_hsv_green, upperb=upper_hsv_green)
    # 中值滤波
    green_blur = cv2.medianBlur(mask_green, 7)

    # yellow
    lower_hsv_yellow = np.array([0, 19, 110])
    upper_hsv_yellow = np.array([240, 153, 255])
    mask_yellow = cv2.inRange(hsv, lowerb=lower_hsv_yellow, upperb=upper_hsv_yellow)
    # 中值滤波
    yellow_blur = cv2.medianBlur(mask_yellow, 7)

    # 因为图像是二值的图像，所以如果图像出现白点，也就是255，那么就取他的max最大值255
    red_color = np.max(red_blur)
    green_color = np.max(green_blur)
    yellow_color = np.max(yellow_blur)
    # 在red_color中判断二值图像如果数值等于255，那么就判定为red
    if red_color == 255:
        cv2.rectangle(frame, (500, 300), (630, 350), (0, 0, 255), 2)  # 按坐标画出矩形框
        cv2.putText(frame, "red", (420, 360), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 255), 2)  # 显示red文本信息
    # 在green_color中判断二值图像如果数值等于255，那么就判定为green
    elif green_color == 255:
        cv2.rectangle(frame, (500, 300), (630, 350), (0, 255, 0), 2)  # 按坐标画出矩形框
        cv2.putText(frame, "green", (420, 360), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 255, 0), 2)  # 显示green文本信息
    # 在yellow_color中判断二值图像如果数值等于255，那么就判定为yellow
    elif yellow_color == 255:
        cv2.rectangle(frame, (500, 300), (630, 350), (0, 255, 255), 2)  # 按坐标画出矩形框
        cv2.putText(frame, "yellow", (420, 360), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 255, 255), 2)  # 显示yellow文本信息

    cv2.imshow('frame', frame)
    red_blur = cv2.resize(red_blur, (300, 200))
    green_blur = cv2.resize(green_blur, (300, 200))
    yellow_blur = cv2.resize(yellow_blur, (300, 200))
    cv2.imshow('red_window', red_blur)
    cv2.imshow('green_window', green_blur)
    cv2.imshow('yellow_window', yellow_blur)

    c = cv2.waitKey(1)
    if c == 27:
        break