Calculating the number of blue pixels in a picture

Question

I am new to openCV and Python and a have a question concerning it. I am trying to find the amount of blue pixels of a picture so i can use them as a threshold in order to compare other pictures with it. I have tried looking through the documentation but i couldn't find anything helpful yet.

Can anyone give a hint or some help?

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BLUE_MAX = np.array([0, 0, 200], np.uint8)
BLUE_MIN = np.array([50, 50, 255], np.uint8)

dst = cv.inRange(img, BLUE_VALUE_MIN, BLUE_VALUE_MAX)
no_blue = cv.countNonZero(dst)

print('The number of blue pixels is: ' + str(no_blue))

-So based on your recommendation I built the following function but all I get when I run it is a blank picture.

Answer 1

For counting blue pixel in a RGB image you can simply do the following

1. Inrange the source image to filter out blue component to a binary image.
2. Count non zero pixel in the binary image using the function countNonZero.

You can refer below C++ code for how to do it

#include <stdio.h>
#include <opencv2/opencv.hpp>
using namespace cv;
using namespace std;

int main()
{
    Mat src,dst;
    src = imread("rgb1.jpg",1);
    inRange(src, Scalar(200,0,0), Scalar(255,50,50), dst); //In range with approximate blue range
    cout<<"No of blue pixels---->"<<countNonZero(dst)<<endl;
    imshow("src",src); 
    imshow("out",out);

    waitKey(0);

    return 0;
}

Edit:-

Here is the working python code

import cv2
import numpy as np

img = cv2.imread("bgr.png")
BLUE_MIN = np.array([0, 0, 200], np.uint8)
BLUE_MAX = np.array([50, 50, 255], np.uint8)

dst = cv2.inRange(img, BLUE_MIN, BLUE_MAX)
no_blue = cv2.countNonZero(dst)
print('The number of blue pixels is: ' + str(no_blue))
cv2.namedWindow("opencv")
cv2.imshow("opencv",img)
cv2.waitKey(0)

Hope this is what you looking for.....

Edit2:-

As @ kigurai commented below OpenCV consider image in BGR order and I gave wrong order for BLUE_MIN and BLUE_MAX array. So in the above code the lines

 BLUE_MIN = np.array([0, 0, 200], np.uint8)    
 BLUE_MAX = np.array([50, 50, 255], np.uint8)  

should changed to

 BLUE_MIN = np.array([200, 0, 0], np.uint8) // minimum value of blue pixel in BGR order
 BLUE_MAX = np.array([255, 50, 50], np.uint8)// maximum value of blue pixel in BGR order

Answer 2

If you are looking for blue pixels in a photographed image, I recommend converting to HSV colour space first and then look for the color range for blue. This way, you can ignore the brightness component.

See this question for colour ranges in HSV color space.