15 Mar Apply Sepia Tone filter with OpenCV

Give your image a warm, vintage look by applying a sepia tone. We have used the NumPy library for this. Initially, we imported the numpy. After that set the array for the sepia filter and use the transform() function:

import numpy as np

Let us see the example:

# Read and display an image with OpenCV and apply sepia tone

import cv2
import numpy as np

# Load an image
image = cv2.imread(r'C:\Users\hp\Downloads\Astronaut.png')

# Create a sepia filter kernel
sepia_kernel = np.array([[0.272, 0.534, 0.131],
                         [0.349, 0.686, 0.168],
                         [0.393, 0.769, 0.189]])

# Apply the sepia filter
sepia_image = cv2.transform(image, sepia_kernel)

# Display the image
cv2.imshow("Sepia Tone", image)

# Wait for a key press and close the window
cv2.waitKey(0)
cv2.destroyAllWindows()

The following is the output:

Explanation:

This Python script applies a sepia tone effect to an image using the OpenCV and NumPy libraries:

• It starts by importing the necessary libraries.
• The script then loads the input image from the specified file path into the variable image using OpenCV’s cv2.imread() function.
• To create the sepia effect, it defines a 3×3 matrix called sepia_kernel, which contains specific weights for red, green, and blue color channels to mimic the warm tones of sepia.
• The sepia filter is applied to the image using the cv2.transform() function, which applies the matrix transformation to the image and produces the modified sepia_image.
• The processed image is then displayed in a window titled “Sepia Tone” using the cv2.imshow() function.
• The script waits indefinitely for the user to press a key with cv2.waitKey(0) before closing all OpenCV windows via cv2.destroyAllWindows().
• This workflow allows the user to view the sepia-toned image and close the display window when ready.

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