TrustMark — Rust implementation
This crate implements a subset of the functionality of the TrustMark Python implementation, including encoding and decoding of watermarks for all variants in binary mode. The Rust implementation provides the same levels of error correction as the Python implementation.
Text mode watermarks and watermark removal are not implemented.
Open an issue if there's something in the Python version that want added to this crate!
Quick start
Download models
In order to encode or decode watermarks, you'll need to fetch the model files. The models are distributed as ONNX files.
From the workspace root (the rust/ directory), run:
cargo xtask fetch-models
This command downloads models to the models/ directory. You can move them from there as needed.
Run the CLI
As a first step, you can run the trustmark-cli which is defined in this repository.
From the workspace root, run:
cargo run --release -p trustmark-cli -- -m ./models encode -i ../images/ghost.png -o ../images/encoded.png
cargo run --release -p trustmark-cli -- -m ./models decode -i ../images/encoded.png
The argument to the -m option is the path to the models downloaded; if you moved them, pass the relative file path as the option value.
Use the library
Add trustmark to your project's cargo manifest with:
cargo add trustmark
A basic example of using trustmark is:
use trustmark::{Trustmark, Version, Variant};
let tm = Trustmark::new("./models", Variant::Q, Version::Bch5).unwrap();
let input = image::open("../images/ghost.png").unwrap();
let output = tm.encode("0010101".to_owned(), input, 0.95);
Running the benchmarks
Rust benchmarks
To run the Rust benchmarks, run the following from the workspace root:
cargo bench
Python benchmarks
To run the Python benchmarks, run the following from the workspace root:
benches/load.sh && benches/encode.sh
- DECaDE Centre for the Decentralized Digital Economy, University of Surrey, UK.↩
- Adobe Research, San Jose, CA.↩