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Image Similarity Toolkit in Python

Project description

SimiKit: Image Similarity Toolkit in Python

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Overview

SimiKit is a toolkit for commonly used image similarity algorithms. This project provides various tools to help developers quickly compare the effects of multiple image similarity algorithms, and assist developers in selecting an image similarity algorithm that best meets their needs.

Installation

pip instal simikit

Basic Usage

from simikit.features.hash import AHash

image_path = r'tests/image.png'
print(AHash().encode(image_path))

Supported Algorithms

  • HASH
    • Average hashing
    • Difference hashing
    • Perceptual hashing
    • Wavelet hashing
  • Transformer
    • VIT
    • DINOv2

Contribution

Thank you for your interest in simikit. Submissions in all aspects are welcome. Let's work together to make simikit better!

Future Plans

  • Add more image similarity algorithms

If there is any similarity algorithm that you want but is not currently available in the simikit, you are welcome to raise it in the Issues section!

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