Python OpenCV ColorMap

In this post, you will learn how to apply the OpenCV colormap. Python provides several colormaps for performing visualization.

OpenCV stands for Open Source Computer Vision Library. It is a free, open source library which is used for computer vision. It provides good support in Machine Learning, Face Recognition, Deep Learning, etc. The OpenCV module is being used for a very wide range of image processing and analysis tasks, like object identification, colour detection, optical character recognition, photo editing, and so on. It provides lots of functions for image processing.

Python OpenCV provides the applyColorMap() function to apply a color map on a given image. It has some predefined constants to apply the colormap. These are the following colormap lists-

• COLORMAP_AUTUMN = 0
• COLORMAP_BONE = 1
• COLORMAP_JET = 2
• COLORMAP_WINTER = 3
• COLORMAP_RAINBOW = 4
• COLORMAP_OCEAN = 5
• COLORMAP_SUMMER = 6
• COLORMAP_SPRING = 7
• COLORMAP_COOL = 8
• COLORMAP_HSV = 9
• COLORMAP_PINK = 10
• COLORMAP_HOT = 11
• COLORMAP_PARULA = 12

Syntax of cv2.applycolormap()

This function accepts three parameters.

applyColorMap(Mat src, Mat dst, int colormap)

The src is an object of the class Mat representing the source image. The dst is an object of the class Mat representing the destination image and the colormap is a variable of integer type representing the type of the color map to be applied.

The basic use of colormap is to show different meanings of a grayscale image with different colors. Like, we can represent hotter and cooler regions on a map, we can also represent autumn, winter and summer seasons and, so on.

In the given Python program, we are using 'COLORMAP_AUTUMN' and 'COLORMAP_BONE' colormap.

import cv2
import numpy as np
  
# image path 
path = r'nature.jpg'

# using imread()  
img = cv2.imread(path)

im1 = cv2.applyColorMap(img, cv2.COLORMAP_AUTUMN)
im2 = cv2.applyColorMap(img, cv2.COLORMAP_BONE)

cv2.imshow('image', np.hstack((im1, im2)))
cv2.waitKey(0);
cv2.destroyAllWindows();
cv2.waitKey(1)

In the given example, we are using 'COLORMAP_JET' and 'COLORMAP_WINTER' colormap.

import cv2
import numpy as np
  
# image path 
path = r'nature.jpg'

# using imread()  
img = cv2.imread(path)

im3 = cv2.applyColorMap(img, cv2.COLORMAP_JET)
im4 = cv2.applyColorMap(img, cv2.COLORMAP_WINTER)

cv2.imshow('image', np.hstack((im3, im4)))
cv2.waitKey(0);
cv2.destroyAllWindows();
cv2.waitKey(1)

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