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import cv2import imutilscap = cv2.VideoCapture(0)## Readimg = cv2.imread("D:/deng/ppp/3.png")def Detector_color():    while(True):        # Capture frame-by-frame        ret, frame = cap.read()        frame = imutils.resize(frame, width=600)        # Our operations on the frame come here        blurred = cv2.GaussianBlur(frame, (7, 7), 0)        hsv = cv2.cvtColor(blurred, cv2.COLOR_BGR2HSV)        #hsv = cv2.GaussianBlur(hsv, (7, 7), 0)        # perform edge detection, then perform a dilation + erosion to        # close gaps in between object edges        # edged = cv2.Canny(hsv, 50, 100)        #inRange()函数用于图像颜色分割        # edged = cv2.inRange(hsv, Redlower, Redupper)        edged = cv2.inRange(hsv, (0, 0, 0), (180, 255, 255))        edged = cv2.dilate(edged, None, iterations=2)        edged = cv2.erode(edged, None, iterations=2)        ## mask of green (36,0,0) ~ (70, 255,255)        mask1 = cv2.inRange(hsv, (36, 43, 46), (70, 255, 255))        ## mask o blue (100,43,46) ~ (124, 255, 255)        mask2 = cv2.inRange(hsv, (100, 43, 46), (155, 255, 255))        ##  red        mask3 = cv2.inRange(hsv, (156, 43, 46), (180, 255, 255))        mask = {
   "green": mask1, "blue": mask2, "red": mask3}        for key, value in mask.items():            target = cv2.bitwise_and(edged, edged, mask=value)            cnts = cv2.findContours(target, cv2.RETR_EXTERNAL,                                    cv2.CHAIN_APPROX_SIMPLE)[-2]            for c in cnts:                # if the contour is not sufficiently large, ignore it                if cv2.contourArea(c) < 100:                    continue                else:                    # y = i                    print(key)                    # return cDetector_color()

仅需要将摄像头对准有颜色的物体即可。运行结果：

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