Image similarity measurement is a common task in various computer vision applications. Whether you want to compare two images for similarity or find similar images in a dataset, image similarity measurement can be a valuable tool. In this blog post, we will explore how to measure image similarity using the imageio library in Python.

Installing imageio

To get started, we need to install the imageio library. You can install it using pip by running the following command:

pip install imageio

Loading Images

First, let’s learn how to load images using imageio. We can use the imread function to read image files into a NumPy array. Here’s an example of how to load an image:

import imageio

# Load image
image = imageio.imread('path/to/image.jpg')

Replace 'path/to/image.jpg' with the actual path to your image file. Now we have the image loaded into a NumPy array, and we can proceed to measure its similarity with another image.

Calculating Image Similarity

The imageio library provides various methods for calculating image similarity, but in this blog post, we will focus on using the Structural Similarity Index (SSIM).

SSIM is a widely used algorithm for measuring image similarity. It compares the structural information between two images and gives a similarity score ranging from -1 to 1, where -1 represents completely dissimilar images, 0 represents same or similar images, and 1 represents identical images.

To calculate the SSIM score between two images using imageio, we can use the compare_ssim function. Here’s an example:

import imageio
from skimage.metrics import structural_similarity as ssim

# Load images
image1 = imageio.imread('path/to/image1.jpg')
image2 = imageio.imread('path/to/image2.jpg')

# Calculate SSIM score
score, diff = ssim(image1, image2, full=True)

Replace 'path/to/image1.jpg' and 'path/to/image2.jpg' with the actual paths to the images you want to compare. The compare_ssim function returns the SSIM score and a difference image highlighting the dissimilar areas between the two images.

Conclusion

In this blog post, we have learned how to measure image similarity using the imageio library in Python. We covered the basics of loading images and calculating image similarity using the SSIM algorithm. By understanding these concepts, you can now incorporate image similarity measurement into your computer vision projects.

Remember to experiment with different images and explore other image similarity algorithms available in imageio to find the best approach for your specific use-case.