PureCV

A high-performance, pure Rust computer vision library focusing on the core and imgproc modules of OpenCV. PureCV is built from the ground up to be memory-safe, thread-safe, and highly portable without the overhead of C++ FFI.

🎯 Philosophy

Unlike existing wrappers, PureCV is a native rewrite. It aims to provide:

• Zero-FFI: No complex linking or C++ toolchain requirements.
• Memory Safety: Elimination of segmentation faults and buffer overflows via Rust's ownership model.
• Modern Parallelism: Native integration with Rayon for effortless multi-core processing.
• WASM & Native SIMD: Optimized for the web and high-performance native architectures using explicit SIMD (via pulp).

✨ Features

purecv-core

• Matrix Operations: Multi-dimensional Matrix<T> with support for common arithmetic (add, sub, mul, div) and bitwise logic.
• Factory Methods: Intuitive initialization with zeros, ones, eye, and diag.
• Structural: flip, rotate, transpose, repeat, reshape, hconcat, vconcat.
• Math & Stats: sqrt, exp, log, pow, sum, mean, minMaxLoc, norm.
• Channel Management: split, merge, mixChannels.

purecv-imgproc

• Color Conversions: High-performance cvt_color supporting RGB, BGR, Gray, and more.
• Filtering: (In Progress) Fast convolutions and image filters.

🚀 Getting Started

Installation

Add the following to your Cargo.toml:

[dependencies]
purecv = { git = "https://github.com/webarkit/purecv" }

Usage Example

use purecv::core::{Matrix, Size, Scalar};
use purecv::imgproc::{cvt_color, ColorConversionCodes};

fn main() -> Result<(), Box<dyn std::error::Error>> {
    // Create a 3-channel matrix initialized to ones
    let mat = Matrix::<f32>::ones(480, 640, 3);
    
    // Create an identity matrix
    let identity = Matrix::<f32>::eye(3, 3, 1);
    
    println!("Matrix size: {}x{}", mat.cols, mat.rows);
    Ok(())
}

Running Examples

Explore the capabilities of PureCV by running the provided examples:

# Basic matrix arithmetic
cargo run --example arithmetic

# Structural operations (flip, rotate, split/merge)
cargo run --example structural_ops

# Color conversion (RGB to Grayscale)
cargo run --example color_conversion

🧪 Testing & Benchmarking

Running Tests

PureCV uses a comprehensive suite of unit tests to ensure correctness and parity with OpenCV.

# Run all tests
cargo test

Running Benchmarks

Performance is a core focus. You can run benchmarks to see the impact of SIMD and multi-threading on your architecture:

# Run all benchmarks
cargo bench

🗺 Roadmap

• Phase 1: Core Foundation - Matrix types, arithmetic, geometric utilities, and basic structural transforms.
• [/] Phase 2: Performance - SIMD optimizations and benchmarking vs OpenCV C++.
• Phase 3: WebAssembly - Specialized wrappers and multi-threading for the web.
• Phase 4: Image Processing - Advanced filtering, convolutions, and feature detection.

📄 License

This project is licensed under the LGPL-3.0 License.