Get the average color of an image in Python

Images are a core part of our digital world, and analyzing their properties opens up a range of possibilities—from creative applications in design to technical solutions in AI and automation. One of the simplest yet powerful insights we can derive from an image is its average color. This value provides a single RGB representation that captures the dominant tone of the image, making it useful for a variety of use cases. In this blog post, we’ll guide you through the process of calculating the average color of an image step by step using Python, OpenCV, and NumPy.

Why Calculate the Average Color?

The average color of an image has many practical applications, such as:

• UI/UX Design: Generating themes or background colors based on user-uploaded images.
• Content Categorization: Grouping or filtering images by their dominant tones.
• Ambient Lighting: Syncing smart home lighting with the mood of displayed visuals.

This simple technique saves time, simplifies data, and creates unique user experiences.

Step-by-Step Guide

1. Install OpenCV Before we begin, ensure OpenCV is installed. OpenCV is a popular library for image processing. You can install it using the following command:

pip install opencv-python

2. Import the Necessary Libraries We’ll use OpenCV to load and process the image and NumPy for numerical operations.

import cv2
import numpy

3. Load the Image Read the image using OpenCV’s imread() function. Replace 'image.jpg' with the path to your image file.

import cv2
import numpy
myimg = cv2.imread('image.jpg')

import cv2
import numpy
myimg = cv2.imread('image.jpg')
avg_color_per_row = numpy.average(myimg, axis=0)
avg_color = numpy.average(avg_color_per_row, axis=0)

import cv2
import numpy
myimg = cv2.imread('image.jpg')
avg_color_per_row = numpy.average(myimg, axis=0)
avg_color = numpy.average(avg_color_per_row, axis=0)
print(avg_color)