chess-corners

Ergonomic ChESS (Chess-board Extraction by Subtraction and Summation) detector on top of chess-corners-core.

This crate:

• Re-exports the main types from chess-corners-core (ChessParams, CornerDescriptor, ResponseMap).
• Provides a unified ChessConfig for single-scale and multiscale detection.
• Adds optional image::GrayImage integration and a small CLI binary for batch runs.

Examples

By default the image feature is enabled so you can work directly with GrayImage:

use chess_corners::{ChessConfig, ChessParams, find_chess_corners_image};
use image::io::Reader as ImageReader;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let img = ImageReader::open("board.png")?
        .decode()?
        .to_luma8();

    let mut cfg = ChessConfig::single_scale();
    cfg.params = ChessParams::default();

    let corners = find_chess_corners_image(&img, &cfg);
    println!("found {} corners", corners.len());
    Ok(())
}

You can also try the bundled examples on sample images in testimages/:

• Single-scale: cargo run -p chess-corners --example single_scale_image -- testimages/mid.png
• Multiscale: cargo run -p chess-corners --example multiscale_image -- testimages/large.png

Both examples require the image feature, which is enabled by default. If you build with --no-default-features, re-enable it when running examples: --features image.

Feature flags:

• image (default) – enable find_chess_corners_image for image::GrayImage.
• rayon – parallelize response computation and multiscale refinement.
• simd – enable portable-SIMD acceleration in the core response kernel (nightly only).
• par_pyramid – opt into SIMD/rayon in the pyramid builder.
• tracing – emit structured spans from multiscale detection and the CLI when enabled.

The full guide-style documentation and API docs are published at:

• Book: https://vitalyvorobyev.github.io/chess-corners-rs
• Rust docs: https://vitalyvorobyev.github.io/chess-corners-rs/api/