In [1]:

    

%matplotlib inline
from matplotlib import pyplot as plt, cm
import numpy as np
import cv2


    

In [2]:

    

# load the image
image = cv2.imread("./data/gameboy.png")


    

In [5]:

    

# defining a list of boundaries in the RGB color space
# saying that all pixels in our image that have a 
# R >= 100, B >= 15, and G >= 17 along with R <= 200, B <= 56, and G <= 50 
# will be considered red
boundaries = [
    ([17, 15, 100], [50, 56, 200]),
    ([86, 31, 4], [220, 88, 50]),
    ([25, 146, 190], [62, 174, 250]),
    ([103, 86, 65], [145, 133, 128])
]

# loop over the boundaries
for (lower, upper) in boundaries:
    # create NumPy arrays from the boundaries
    lower = np.array(lower, dtype = "uint8")
    upper = np.array(upper, dtype = "uint8")
 
    # find the colors within the specified boundaries and apply
    # the mask
    mask = cv2.inRange(image, lower, upper)
    # cv2.bitwise_and : showing only pixels in the image that have a corresponding white (255) value in the mask.
    output = cv2.bitwise_and(image, image, mask = mask)
 
    # show the images
    plt.figure(figsize=(14,10))
    plt.subplot(131), plt.imshow(image, cmap = 'gray')
    plt.title('Original Image')
    plt.subplot(132), plt.imshow(mask, cmap = 'gray')
    plt.title('Mask Image')
    plt.subplot(133), plt.imshow(output, cmap = 'gray')
    plt.title('Bitwise Image')