Detecting Red and Blue Squares (beanbags) using Python and CV2

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    I am new to CV2 and I am looking for some high level guidance for an application. I am working on a program that can detect red and blue beanbags that are in the frame of the camera. I played around with the example code offered by openCV to detect blue colors and modified it slightly to detect red as well.

    import cv2
    import numpy as np
    import matplotlib.pyplot as plt
    import matplotlib.image as mpimg
    
    cap = cv2.VideoCapture(0)
    
    while(1):
    
        # Take each frame
        _, frame = cap.read()
    
        # Convert BGR to HSV
        hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
    
        # define range of blue color in HSV
        lower_blue = np.array([110,50,50])
        upper_blue = np.array([130,255,255])
        lower_red = np.array([-20, 100, 100])
        upper_red = np.array([13, 255, 255])
    
        # Threshold the HSV image to get only blue colors
        mask = cv2.inRange(hsv, lower_red, upper_red)
    
        # Bitwise-AND mask and original image
        res = cv2.bitwise_and(frame,frame, mask= mask)
    
        cv2.imshow('frame',frame)
        cv2.imshow('mask',mask)
        cv2.imshow('res',res)
        k = cv2.waitKey(5) & 0xFF
        if k == 27:
            break
    
    cv2.destroyAllWindows()
    

    This is (slightly modified) copied and pasted code from the OpenCV site. I am looking for the correct way to analyze the res numpy array of the dimensions <460, 640, 3> in order to detect that

    1. I have red/blue objects(s) on my screen
    2. Do something with this information such as print(1 red and 2 blue squares detected)
    asked 23 secs ago

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  • نویسنده : استخدام کار بازدید : 67 تاريخ : جمعه 29 ارديبهشت 1396 ساعت: 22:00
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