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.
With the rust-image feature, this crate can operate directly on buffers from the PistonDevelopers/image crate.
Add img_hash to your Cargo.toml:
[dependencies.img_hash]
version = "2.0"
# For interop with `image`:
features = ["rust-image"]
Example program:
```rust extern crate image; extern crate img_hash;
use std::path::Path; use img_hash::{ImageHash, HashType};
fn main() { let image1 = image::open(&Path::new("image1.png")).unwrap(); let image2 = image::open(&Path::new("image2.png")).unwrap();
// These two lines produce hashes with 64 bits (8 ** 2),
// using the Gradient hash, a good middle ground between
// the performance of Mean and the accuracy of DCT.
let hash1 = ImageHash::hash(&image1, 8, HashType::Gradient);
let hash2 = ImageHash::hash(&image2, 8, HashType::Gradient);
println!("Image1 hash: {}", hash1.to_base64());
println!("Image2 hash: {}", hash2.to_base64());
println!("% Difference: {}", hash1.dist_ratio(&hash2));
} ```
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 bench --features bench
Licensed under either of
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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.