How to create a slider of HSV color palette using OpenCV Python?

To create a slider for the HSV (Hue, Saturation and Value) color palette in OpenCV we use two different functions. These functions are cv2.reateTrackbar() and cv2.getTrackbarPos().

• Use the cv2.reateTrackbar() function to create the slider, while the cv2.getTrackbarPos() function is used to access the selected slider position value.

• Using these two functions, we create a slider containing H, S, V colors and a color window to display the selected color. By changing the position of the slider, we can select a specific color value.

• H ranges from 0 to 179, while S and # The range of ##V is between 0 and 255.

Syntax

cv2.createTrackbar(trackbar_name, window_name, default_value, max_value, callback_func)
cv2.getTrackbarPos(trackbar_name, window_name)

Parameters:

• ##trackbar_name

  − This is the name of the slider bar. This name is used to access the slider's position value.

• window_name

  − It is the name of the window attached to the slider.

• default_value

  − Set the default value of the slider.

• max_value

  − Maximum value of the slider.

• callback_func

  − Function executed when the value of the slider changes.

Steps

To create a slider that is an

HSV color palette

, you can follow these steps: The first step is to import the required libraries. The required Python libraries are

OpenCV

and NumPy. Please make sure you have them installed.

import cv2
import numpy as np

Next define a

callback function

. It takes the slider position as a default parameter. We define this function to do nothing.

def nothing(x):
   pass

Define the black image and create a window named

HSV Color Palette

. Track bars and colors will appear in this window.

img = np.zeros((300,650,3), np.uint8)
window_name = 'Trackbar Color Palette'
cv2.namedWindow(window_name, cv2.WINDOW_AUTOSIZE)

Create a color changing slider, passing all five parameters

cv2.createTrackbar('H',window_name,0,179,nothing)
cv2.createTrackbar('S',window_name,0,255,nothing)
cv2.createTrackbar('V',window_name,0,255,nothing)

Get the current slider position for all three

HSV

colors.

h = cv2.getTrackbarPos('H',window_name)
s = cv2.getTrackbarPos('S',window_name)
v = cv2.getTrackbarPos('V',window_name)

Update the color image window with the above colors. And convert the image color to

BGR

.

img[:] = [h,s,v]
img = cv2.cvtColor(img, cv2.COLOR_HSV2BGR)

Now displays the color of the selected track bar value in the color image window.

while(True):
   cv2.imshow(window_name,img)
   k = cv2.waitKey(1) & 0xFF
   if k == ord('q'):
      break

Example 1

In this Python program, we create a window as a color palette. We created three sliders to control the R, G, and B colors. Slide the slider and you will get the corresponding color display in the color window.

# import required libraries
import cv2
import numpy as np

def nothing(x):
   pass
   
# Create a black image, a window
img = np.zeros((300,650,3), np.uint8)
img = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
window_name = 'HSV Color Palette'
cv2.namedWindow(window_name, cv2.WINDOW_AUTOSIZE)

# create trackbars for color change
cv2.createTrackbar('H',window_name,0,179,nothing)
cv2.createTrackbar('S',window_name,0,255,nothing)
cv2.createTrackbar('V',window_name,0,255,nothing)
while(True):
   cv2.imshow(window_name,img)
key = cv2.waitKey(1) & 0xFF
   if key == ord('q'):
      break
      
   # get current positions of four trackbars
   h = cv2.getTrackbarPos('H',window_name)
   s = cv2.getTrackbarPos('S',window_name)
   v = cv2.getTrackbarPos('V',window_name)
   img[:] = [h,s,v]
   img = cv2.cvtColor(img, cv2.COLOR_HSV2BGR)
cv2.destroyAllWindows()

Output

When you run the above program, it will display the following output window. To close the output window, press the ‘

q

’ button.

By default, the values ​​of the three sliders are

0

, and the color of the window is black. Slide the slider and you will see the corresponding color in the color window. The Chinese translation of Example 2

is:

Example 2

In this program, we create a window as a

HSV

Color palette, which contains a switch button. We created four sliders, three for the HSV color and one for the switch button. When the

switch

button is turned on , only the colors in the color image are displayed. Slide the slider and you will get the corresponding color display in the color window.

import cv2
import numpy as np

def nothing(x):
   pass
   
# Create a black image, a window
img = np.zeros((300,650,3), np.uint8)
img = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
window_name = 'HSV Color Palette'
cv2.namedWindow(window_name, cv2.WINDOW_AUTOSIZE)

# create trackbars for color change
cv2.createTrackbar('H',window_name,0,179,nothing)
cv2.createTrackbar('S',window_name,0,255,nothing)
cv2.createTrackbar('V',window_name,0,255,nothing)

# create switch for ON/OFF functionality
# switch = '0 : OFF \n1 : ON'
cv2.createTrackbar('switch', window_name,0,1,nothing)
while(True):
   cv2.imshow(window_name,img)
   key = cv2.waitKey(1) & 0xFF
   if key == ord('q'):
      break
      
   # get current positions of four trackbars
   h = cv2.getTrackbarPos('H',window_name)
   s = cv2.getTrackbarPos('S',window_name)
   v = cv2.getTrackbarPos('V',window_name)
   sw = cv2.getTrackbarPos('switch',window_name)
   if sw == 0:
      img[:] = 0
   else:
      img[:] = [h,s,v]
      img = cv2.cvtColor(img, cv2.COLOR_HSV2BGR)
cv2.destroyAllWindows()

Output

When you run the above program, it will display the following output window. To close the output window, press the ‘

q

’ button.

By default, the value of all sliders is

0

. The color of the window is black. When you turn the switch on (selected as 1) and slide the HSV color slider to the desired value, the color of the window will correspond to the set value. For bright colors, select the maximum value for the S and V sliders, and slide the H slider. When the switch is off, sliding the slider will not change anything

If you slide the slider when the switch is off (set to 0), then the color of the window will not change. It will remain as is (i.e. black).

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