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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