Tissue

Tissue is still in its early stages of development, so it may have bugs or APIs that are constantly changing.

Tissue is a Rust framework that enables effortless and efficient conversion of machine learning models into interactive, user-friendly demos. With Tissue, a few lines of code are all it takes to bring your machine learning algorithms to life with engaging visual applications.

Features

• Speedy Setup: Get started with Tissue in minutes and integrate seamlessly with your existing Rust machine learning projects.
• Interactive GUI: Create a graphical user interface that makes your models accessible to non-technical users.
• Rust-Powered: Take advantage of Rust's performance and safety features to deploy machine learning models efficiently.

Quick Start

To begin using Tissue, add it to your project's Cargo.toml file:

[dependencies]
tissue = "0.1.0"

Create an interactive demo with Tissue:

use tissue::{run, Input};

fn main() {
    run(
        |x: Vec<f32>| x.iter().sum(),
        &[Input::Number(234.289), Input::Number(235.6)],
    )
    .expect("Could not run");
}

Licenses

This library is licensed under either of:

• MIT license LICENSE-MIT or http://opensource.org/licenses/MIT
• Apache License 2.0 LICENSE-APACHE or https://opensource.org/licenses/Apache-2.0

at your option.

Acknowledgements

Tissue owes much to the foundational work of Chris McComb's tease; its initial codebase was critical to Tissue's early development, despite tease no longer being actively maintained.

Inspired by the user-friendly interfaces of Gradio and Streamlit, Tissue aspires to streamline the sharing and demonstration of machine learning models within the Rust ecosystem, emulating the simplicity these tools offer.

Embrace the power of Rust and bring the magic of your machine learning models to life with Tissue!