How to Display an OpenCV image in Python with Matplotlib?

How to Display an OpenCV Image in Python with Matplotlib

OpenCV is a popular library for image processing, but its default color format is BGR, which can cause images to look incorrect when displayed using Matplotlib, which expects RGB format. To display OpenCV images correctly in Matplotlib, you need to convert the image's color format.

Why Color Conversion is Necessary

OpenCV loads images in BGR (Blue, Green, Red) format by default, whereas Matplotlib expects RGB (Red, Green, Blue) format. If you try to display a BGR image directly using Matplotlib, the colors will appear distorted. Converting BGR to RGB fixes this issue and ensures proper color representation.

Step-by-Step Guide to Display an OpenCV Image with Matplotlib

import cv2
import matplotlib.pyplot as plt

# Load the image using OpenCV
image_bgr = cv2.imread('path_to_image.jpg')

# Convert BGR to RGB
image_rgb = cv2.cvtColor(image_bgr, cv2.COLOR_BGR2RGB)

# Display the image using Matplotlib
plt.imshow(image_rgb)
plt.axis('off')  # Hide axis ticks and labels
plt.show()

Make sure to replace 'path_to_image.jpg' with the actual path to your image file.

Displaying Grayscale Images

If your image is in grayscale, you can convert it accordingly and display it using Matplotlib's grayscale colormap:

# Convert BGR to Grayscale
image_gray = cv2.cvtColor(image_bgr, cv2.COLOR_BGR2GRAY)

# Display grayscale image
plt.imshow(image_gray, cmap='gray')
plt.axis('off')
plt.show()

Summary

To display OpenCV images correctly with Matplotlib, always convert the image color format from BGR to RGB. This simple step prevents color distortions and ensures your images are shown accurately. For grayscale images, using the 'gray' colormap in Matplotlib provides a clear and correct visualization.