OpenCV is a library of programming functions mainly aimed at real-time computer vision.
In this article, Let’s create a window which will contain RGB color palette with track bars. By moving the trackbars the value of RGB Colors will change b/w 0 to 255. So using the same, we can find the color with its RGB values.
Libraries needed: OpenCV Numpy
Approach:
Create a black window with three color channels with resolution 512 x 512. Then create three ‘B’ ‘G’ ‘R’ trackbars using predefined functions of OpenCV library. Set the values of channels from 0 to 255. Merging the black window with these color trackbars.
# Python program to create RGB color # palette with trackbars # importing libraries import cv2 import numpy as np # empty function called when # any trackbar moves def emptyFunction(): pass def main(): # blackwindow having 3 color chanels image = np.zeros((512, 512, 3), np.uint8) windowName ="Open CV Color Palette" # window name cv2.namedWindow(windowName) # there trackbars which have the name # of trackbars min and max value cv2.createTrackbar('Blue', windowName, 0, 255, emptyFunction) cv2.createTrackbar('Green', windowName, 0, 255, emptyFunction) cv2.createTrackbar('Red', windowName, 0, 255, emptyFunction) # Used to open the window # till press the ESC key while(True): cv2.imshow(windowName, image) if cv2.waitKey(1) == 27: break # values of blue, green, red blue = cv2.getTrackbarPos('Blue', windowName) green = cv2.getTrackbarPos('Green', windowName) red = cv2.getTrackbarPos('Red', windowName) # merge all three color chanels and # make the image composites image from rgb image[:] = [blue, green, red] print(blue, green, red) cv2.destroyAllWindows() # Calling main() if __name__=="__main__": main() |
Output:
Note: Above programs will not run on online IDE.
