用opencv识别颜色并输出坐标

1首先安装opencv

pip install opencv-python

参考https://blog.csdn.net/qq_42114833/article/details/128648458?spm=1001.2014.3001.5502

2然后我用的代码

import numpy as np
import cv2

font = cv2.FONT_HERSHEY_SIMPLEX

lower_red = np.array([0, 127, 128])  # 红色低阈值
upper_red = np.array([5, 255, 255])  # 红色高阈值
lower_blue = np.array([100, 100, 100])  # 蓝色低阈值
upper_blue = np.array([124, 255, 255])  # 蓝色高阈值

cap = cv2.VideoCapture(2)  # 打开USB摄像头
if (cap.isOpened()):  # 视频打开成功
    flag = 1
else:
    flag = 0
num = 0
if (flag):
    while (True):
        ret, frame = cap.read()  # 读取一帧
        if ret == False:  # 读取帧失败
            break

        hsv_img = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)# 根据颜色范围删选
        mask_red = cv2.inRange(hsv_img, lower_red, upper_red)
        mask_blue = cv2.inRange(hsv_img, lower_blue, upper_blue)

        mask_red = cv2.medianBlur(mask_red, 7)        # 中值滤波
        mask_blue = cv2.medianBlur(mask_blue, 7)

        mask = cv2.bitwise_or(mask_red, mask_blue,)  # 检测轮廓
        contours2, hierarchy2 = cv2.findContours(mask_red, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
        contours3, hierarchy3 = cv2.findContours(mask_blue, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

        for cnt2 in contours2:
            (x, y, w, h) = cv2.boundingRect(cnt2)  # 该函数返回矩阵四个点
            a = x + w / 2
            b = y + h / 2
            print("red:", a, b)
            cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 255), 2)  # 将检测到的颜色框起来
            cv2.putText(frame, 'red', (x, y - 5), font, 0.7, (0, 0, 255), 2)

        for cnt3 in contours3:
            (x3, y3, w3, h3) = cv2.boundingRect(cnt3)
            cv2.rectangle(frame, (x3, y3), (x3 + w3, y3 + h3), (255, 0, 0), 2)
            cv2.putText(frame, "Blue", (x3, y3 - 5), font, 0.7, (255, 0, 0), 2)

        num = num + 1
        cv2.imshow("dection", frame)
        #cv2.imwrite("imgs/%d.jpg" % num, frame)#照片写入，注释后不保存图片，但未注释的需要建imgs
        if cv2.waitKey(20) & 0xFF == 27:
            break
cv2.waitKey(0)
cv2.destroyAllWindows()

利用相机，并不保存照片