Image Hasher

A library for getting perceptual hash values of images.

Thanks to Dr. Neal Krawetz for the outlines of the Mean (aHash), Gradient (dHash), and DCT (pHash) perceptual hash algorithms:
http://www.hackerfactor.com/blog/?/archives/432-Looks-Like-It.html (Accessed August 2014)

Also provides an implementation of the Blockhash.io algorithm.

This crate can operate directly on buffers from the PistonDevelopers/image crate.

This is fork of img_hash library, but with updated dependencies and some new features.

I am not familiar too much with this library, so if you have a need/willingness to develop it, I can add you as a co-maintainer.

Usage

Documentation

Add image_hasher to your Cargo.toml:

image_hasher = "3.0.0"

Example program:

use image_hasher::{HasherConfig, HashAlg};

fn main() {
    let image1 = image::open("image1.png").unwrap();
    let image2 = image::open("image2.png").unwrap();

    let hasher = HasherConfig::new().to_hasher();

    let hash1 = hasher.hash_image(&image1);
    let hash2 = hasher.hash_image(&image2);

    println!("Image1 hash: {}", hash1.to_base64());
    println!("Image2 hash: {}", hash2.to_base64());

    println!("Hamming Distance: {}", hash1.dist(&hash2));
}

Minimal version

Minimal version of Rust required to build this crate is 1.70.0.
To be able to use it with such rust compiler, you may need to pin some external dependencies to lower versions - look at CI to see which version is compatible with this crate.

Benchmarking

In order to build and test on Rust stable, the benchmarks have to be placed behind a feature gate. If you have Rust nightly installed and want to run benchmarks, use the following command:

cargo +nightly bench

Faster Image Resize

Latest version of library, allows to use fast_image_resize library under fast_image_unstable feature, that should be a lot of faster than image crate in resizing images.
Currently, it is marked as unstable feature, so it may be removed in later versions or change behavior.
Also it gives slightly different results than image crate.

License

Licensed under either of

• Apache License, Version 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
• MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT)

at your option.

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.