check image similarity python

in this tutorial, we will explore how to check the similarity between images using python. image similarity is a crucial task in various applications such as content-based image retrieval, duplicate image detection, and more. we will use the popular opencv library along with other supporting libraries to achieve this task.
before we get started, make sure you have the following installed:
you can install these libraries using pip:
first, we need to load the images that we want to compare. for simplicity, we will load two images from the disk.
to simplify the comparison process, we will convert the images to grayscale. grayscale images contain only intensity values and are easier to compare.
there are several methods to compute image similarity. in this tutorial, we will use structural similarity index (ssi) which measures the similarity between two images. we will use the compare_ssim function from the skimage library.
you can visualize the difference between the two images by plotting the difference image.
in this tutorial, we learned how to check the similarity between two images using python. we loaded the images, converted them to grayscale, computed the structural similarity index, and visualized the results. you can further explore other image similarity metrics and techniques to suit your specific needs.
chatgpt
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[mh]

image hashing has been the best choice for image similarity from my experience