feat: wire up image conversion pipeline and CLI

Add `convert.rs`: a SIMD nearest-color search and a rayon-parallel `nordify_pixels` function. Add `error.rs` with the `NordifyError` type. Rewrite `lib.rs` to expose `NordifyOptions`, `nordify_image`, and `nordify_file` as the public API. Rewrite `main.rs` to parse CLI arguments with `argh` and call into `lib.rs`. Add `argh` and `thiserror` as dependencies.
2026-08-28 13:41:18 +02:00
parent 4cbc25f2d6
commit 28dac1b7dc
5 changed files with 497 additions and 4 deletions
@@ -15,9 +15,11 @@ path = "src/main.rs"
 name = "nordify"

 [dependencies]
+argh = "0.1.19"
 image = "0.25.10"
 ndarray = { version = "0.17.2", features = ["rayon"] }
 rayon = "1.12.0"
+thiserror = "2.0.20"
 wide = "1.6.1"

 [profile.release]
@@ -0,0 +1,375 @@
+use crate::color::{Lab, LabPlanar, PlanarColor, Rgb, RgbPlanar};
+use crate::palette::{Expansion, Palette};
+use ndarray::parallel::prelude::*;
+use ndarray::{Array3, Axis};
+use wide::f64x4;
+
+/// Finds the index of the palette entry closest to `pixel` in Lab space.
+///
+/// This method compares squared distances, not distances. Squaring skips
+/// a `sqrt` call per comparison. It never changes which entry is
+/// closest, since `sqrt` is monotonic. The scan compares 4 palette
+/// entries at a time, then falls back to one at a time for the
+/// remainder. On a tie, the method returns the lower index.
+fn closest_index_lab_simd(pixel: Lab, palette: &LabPlanar) -> usize {
+    let (pl, pa, pb) = (
+        f64x4::splat(pixel.l),
+        f64x4::splat(pixel.a),
+        f64x4::splat(pixel.b),
+    );
+    let mut best_dist = f64::MAX;
+    let mut best_idx = 0;
+    let n = palette.len();
+    let chunks = n / 4;
+
+    for chunk_index in 0..chunks {
+        let i = chunk_index * 4;
+        let dl = f64x4::from(&palette.l()[i..i + 4]) - pl;
+        let da = f64x4::from(&palette.a()[i..i + 4]) - pa;
+        let db = f64x4::from(&palette.b()[i..i + 4]) - pb;
+        let dist_sq = (dl * dl + da * da + db * db).to_array();
+        for (lane, &d) in dist_sq.iter().enumerate() {
+            if d < best_dist {
+                best_dist = d;
+                best_idx = i + lane;
+            }
+        }
+    }
+    for i in (chunks * 4)..n {
+        let d = (palette.l()[i] - pixel.l).powi(2)
+            + (palette.a()[i] - pixel.a).powi(2)
+            + (palette.b()[i] - pixel.b).powi(2);
+        if d < best_dist {
+            best_dist = d;
+            best_idx = i;
+        }
+    }
+    best_idx
+}
+
+/// Finds the index of the palette entry closest to `pixel` in RGB space.
+///
+/// This method works the same way as `closest_index_lab_simd`, but
+/// compares raw `0..=255` RGB channels instead of Lab components.
+fn closest_index_rgb_simd(pixel: Rgb, palette: &RgbPlanar) -> usize {
+    let (pr, pg, pb) = (
+        f64x4::splat(f64::from(pixel.r)),
+        f64x4::splat(f64::from(pixel.g)),
+        f64x4::splat(f64::from(pixel.b)),
+    );
+    let mut best_dist = f64::MAX;
+    let mut best_idx = 0;
+    let n = palette.len();
+    let chunks = n / 4;
+
+    for chunk_index in 0..chunks {
+        let i = chunk_index * 4;
+        let dr = f64x4::from(&palette.r()[i..i + 4]) - pr;
+        let dg = f64x4::from(&palette.g()[i..i + 4]) - pg;
+        let db = f64x4::from(&palette.b()[i..i + 4]) - pb;
+        let dist_sq = (dr * dr + dg * dg + db * db).to_array();
+        for (lane, &d) in dist_sq.iter().enumerate() {
+            if d < best_dist {
+                best_dist = d;
+                best_idx = i + lane;
+            }
+        }
+    }
+    for i in (chunks * 4)..n {
+        let d = (palette.r()[i] - f64::from(pixel.r)).powi(2)
+            + (palette.g()[i] - f64::from(pixel.g)).powi(2)
+            + (palette.b()[i] - f64::from(pixel.b)).powi(2);
+        if d < best_dist {
+            best_dist = d;
+            best_idx = i;
+        }
+    }
+    best_idx
+}
+
+/// Finds the palette color closest to `pixel`.
+///
+/// This method returns `None` if `palette` has no colors. Otherwise, it
+/// returns `Some` of the closest color. When `use_lab` is `true`, the
+/// method compares colors in Lab space, which better matches human color
+/// perception. Otherwise, it compares raw RGB channels.
+pub fn find_closest_color<T: Expansion>(
+    pixel: Rgb,
+    palette: &Palette<T>,
+    use_lab: bool,
+) -> Option<Rgb> {
+    if palette.is_empty() {
+        return None;
+    }
+    let idx = if use_lab {
+        closest_index_lab_simd(Lab::from(pixel), palette.lab_planar())
+    } else {
+        closest_index_rgb_simd(pixel, palette.rgb_planar())
+    };
+    Some(palette.colors()[idx])
+}
+
+/// Scratch buffers for one image row, reused across rows on the same
+/// rayon worker instead of allocated fresh every row.
+struct RowScratch {
+    row_rgb: RgbPlanar,
+    row_lab: LabPlanar,
+}
+
+impl RowScratch {
+    fn with_capacity(width: usize) -> Self {
+        Self {
+            row_rgb: RgbPlanar::with_capacity(width),
+            row_lab: LabPlanar::with_capacity(width),
+        }
+    }
+}
+
+/// Converts every pixel in `pixels` to its closest color in `palette`.
+///
+/// This method processes image rows in parallel. Within each row, it
+/// compares each pixel against `palette` 4 entries at a time. Set
+/// `use_lab` to `true` for perceptually accurate matching, or `false`
+/// for plain RGB distance.
+pub fn nordify_pixels<T: Expansion + Sync>(
+    pixels: &Array3<u8>,
+    palette: &Palette<T>,
+    use_lab: bool,
+) -> Array3<u8> {
+    let (height, width, _channels) = pixels.dim();
+    let mut output = Array3::<u8>::zeros((height, width, 3));
+
+    pixels
+        .axis_iter(Axis(0))
+        .into_par_iter()
+        .zip(output.axis_iter_mut(Axis(0)).into_par_iter())
+        .for_each_init(
+            || RowScratch::with_capacity(width),
+            |scratch, (in_row, mut out_row)| {
+                scratch.row_rgb.clear();
+                for x in 0..width {
+                    scratch.row_rgb.push(Rgb {
+                        r: in_row[[x, 0]],
+                        g: in_row[[x, 1]],
+                        b: in_row[[x, 2]],
+                    });
+                }
+
+                if use_lab {
+                    scratch.row_lab.convert_from(&scratch.row_rgb);
+                    for x in 0..width {
+                        let pixel = Lab {
+                            l: scratch.row_lab.l()[x],
+                            a: scratch.row_lab.a()[x],
+                            b: scratch.row_lab.b()[x],
+                        };
+                        let idx = closest_index_lab_simd(pixel, palette.lab_planar());
+                        let color = palette.colors()[idx];
+                        out_row[[x, 0]] = color.r;
+                        out_row[[x, 1]] = color.g;
+                        out_row[[x, 2]] = color.b;
+                    }
+                } else {
+                    for x in 0..width {
+                        let pixel = Rgb {
+                            r: in_row[[x, 0]],
+                            g: in_row[[x, 1]],
+                            b: in_row[[x, 2]],
+                        };
+                        let idx = closest_index_rgb_simd(pixel, palette.rgb_planar());
+                        let color = palette.colors()[idx];
+                        out_row[[x, 0]] = color.r;
+                        out_row[[x, 1]] = color.g;
+                        out_row[[x, 2]] = color.b;
+                    }
+                }
+            },
+        );
+
+    output
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::palette::CanExpand;
+
+    fn black_and_white_palette() -> Palette<CanExpand> {
+        Palette::new(vec![
+            Rgb { r: 0, g: 0, b: 0 },
+            Rgb {
+                r: 255,
+                g: 255,
+                b: 255,
+            },
+        ])
+    }
+
+    #[test]
+    fn test_find_closest_color_lab() {
+        let palette = black_and_white_palette();
+        let pixel = Rgb {
+            r: 10,
+            g: 10,
+            b: 10,
+        };
+        let closest = find_closest_color(pixel, &palette, true);
+        assert_eq!(closest, Some(Rgb { r: 0, g: 0, b: 0 }));
+    }
+
+    #[test]
+    fn test_find_closest_color_rgb() {
+        let palette = black_and_white_palette();
+        let pixel = Rgb {
+            r: 240,
+            g: 240,
+            b: 240,
+        };
+        let closest = find_closest_color(pixel, &palette, false);
+        assert_eq!(
+            closest,
+            Some(Rgb {
+                r: 255,
+                g: 255,
+                b: 255
+            })
+        );
+    }
+
+    #[test]
+    fn test_find_closest_color_empty_palette() {
+        let palette: Palette<CanExpand> = Palette::new(vec![]);
+        let pixel = Rgb { r: 1, g: 2, b: 3 };
+        assert_eq!(find_closest_color(pixel, &palette, true), None);
+    }
+
+    fn linear_scan_lab(pixel: Lab, palette: &LabPlanar) -> usize {
+        (0..palette.len())
+            .min_by(|&a, &b| {
+                let dist = |i: usize| {
+                    (palette.l()[i] - pixel.l).powi(2)
+                        + (palette.a()[i] - pixel.a).powi(2)
+                        + (palette.b()[i] - pixel.b).powi(2)
+                };
+                dist(a).partial_cmp(&dist(b)).unwrap()
+            })
+            .unwrap()
+    }
+
+    fn linear_scan_rgb(pixel: Rgb, palette: &RgbPlanar) -> usize {
+        (0..palette.len())
+            .min_by(|&a, &b| {
+                let dist = |i: usize| {
+                    (palette.r()[i] - f64::from(pixel.r)).powi(2)
+                        + (palette.g()[i] - f64::from(pixel.g)).powi(2)
+                        + (palette.b()[i] - f64::from(pixel.b)).powi(2)
+                };
+                dist(a).partial_cmp(&dist(b)).unwrap()
+            })
+            .unwrap()
+    }
+
+    fn sample_colors() -> Vec<Rgb> {
+        vec![
+            Rgb { r: 0, g: 0, b: 0 },
+            Rgb {
+                r: 255,
+                g: 255,
+                b: 255,
+            },
+            Rgb {
+                r: 46,
+                g: 52,
+                b: 64,
+            },
+            Rgb {
+                r: 216,
+                g: 222,
+                b: 233,
+            },
+            Rgb {
+                r: 136,
+                g: 192,
+                b: 208,
+            },
+            Rgb {
+                r: 191,
+                g: 97,
+                b: 106,
+            },
+            Rgb {
+                r: 163,
+                g: 190,
+                b: 140,
+            },
+        ]
+    }
+
+    #[test]
+    fn closest_index_lab_simd_matches_linear_scan() {
+        let colors = sample_colors();
+        let palette = Palette::<CanExpand>::new(colors);
+        let test_pixels = [
+            Rgb { r: 10, g: 10, b: 10 },
+            Rgb {
+                r: 200,
+                g: 200,
+                b: 200,
+            },
+            Rgb {
+                r: 140,
+                g: 190,
+                b: 210,
+            },
+        ];
+        for pixel in test_pixels {
+            let lab_pixel = Lab::from(pixel);
+            assert_eq!(
+                closest_index_lab_simd(lab_pixel, palette.lab_planar()),
+                linear_scan_lab(lab_pixel, palette.lab_planar())
+            );
+        }
+    }
+
+    #[test]
+    fn closest_index_rgb_simd_matches_linear_scan() {
+        let colors = sample_colors();
+        let palette = Palette::<CanExpand>::new(colors);
+        let test_pixels = [
+            Rgb { r: 10, g: 10, b: 10 },
+            Rgb {
+                r: 200,
+                g: 200,
+                b: 200,
+            },
+            Rgb {
+                r: 140,
+                g: 190,
+                b: 210,
+            },
+        ];
+        for pixel in test_pixels {
+            assert_eq!(
+                closest_index_rgb_simd(pixel, palette.rgb_planar()),
+                linear_scan_rgb(pixel, palette.rgb_planar())
+            );
+        }
+    }
+
+    #[test]
+    fn closest_index_lab_simd_tie_break_matches_first_wins() {
+        // Indices 0 and 1 sit at the same distance (1.0) from the pixel,
+        // within the same 4-wide SIMD chunk. The lower index must win.
+        let palette = LabPlanar::new(
+            vec![50.0, 50.0, 50.0, 50.0],
+            vec![-1.0, 1.0, 10.0, 20.0],
+            vec![0.0, 0.0, 0.0, 0.0],
+        );
+        let pixel = Lab {
+            l: 50.0,
+            a: 0.0,
+            b: 0.0,
+        };
+        assert_eq!(closest_index_lab_simd(pixel, &palette), 0);
+    }
+}
@@ -0,0 +1,9 @@
+use thiserror::Error;
+
+#[derive(Debug, Error)]
+pub enum NordifyError {
+    #[error("failed to read or write image: {0}")]
+    Image(#[from] image::ImageError),
+}
+
+pub type Result<T> = std::result::Result<T, NordifyError>;
@@ -1,6 +1,71 @@
 mod color;
+mod convert;
+mod error;
 mod palette;

-pub fn add(a: u32, b: u32) -> u32 {
-    a + b
+pub use error::{NordifyError, Result};
+
+use ndarray::Array3;
+use palette::{CanExpand, Palette, NORD_PALETTE};
+
+/// Options controlling how an image converts to the Nord color palette.
+#[derive(Debug, Clone)]
+pub struct NordifyOptions {
+    /// Expand the palette with colors interpolated between close pairs.
+    pub expand: bool,
+    /// Interpolated colors to add between each close pair, when
+    /// `expand` is `true`.
+    pub expansion_factor: usize,
+    /// Compare colors in perceptual Lab space instead of raw RGB.
+    pub use_lab: bool,
+}
+
+impl Default for NordifyOptions {
+    fn default() -> Self {
+        Self {
+            expand: true,
+            expansion_factor: 3,
+            use_lab: true,
+        }
+    }
+}
+
+/// Converts `image` to the Nord color palette.
+///
+/// This method never fails. It replaces each pixel with its closest Nord
+/// palette color, per `options`.
+pub fn nordify_image(image: &image::RgbImage, options: &NordifyOptions) -> image::RgbImage {
+    let (width, height) = image.dimensions();
+    let raw = image.as_raw().clone();
+    let pixels = Array3::from_shape_vec((height as usize, width as usize, 3), raw)
+        .expect("RgbImage's raw buffer length always matches height * width * 3");
+
+    let base = Palette::<CanExpand>::new(NORD_PALETTE.to_vec());
+    let output: Array3<u8> = if options.expand {
+        let expanded = base.expand(options.expansion_factor);
+        convert::nordify_pixels(&pixels, &expanded, options.use_lab)
+    } else {
+        convert::nordify_pixels(&pixels, &base, options.use_lab)
+    };
+
+    let (raw_out, _offset) = output.into_raw_vec_and_offset();
+    image::RgbImage::from_raw(width, height, raw_out)
+        .expect("output buffer length always matches width * height * 3 by construction")
+}
+
+/// Reads the image at `input`, converts it to the Nord color palette,
+/// then writes the result to `output`.
+///
+/// # Errors
+///
+/// Returns an error if `input` cannot be read and decoded, or if
+/// `output` cannot be written.
+pub fn nordify_file(
+    input: impl AsRef<std::path::Path>,
+    output: impl AsRef<std::path::Path>,
+    options: &NordifyOptions,
+) -> Result<()> {
+    let img = image::open(input)?.to_rgb8();
+    nordify_image(&img, options).save(output)?;
+    Ok(())
 }
@@ -1,3 +1,45 @@
-fn main() {
-    println!("Hello, world!");
+use std::path::PathBuf;
+
+/// Convert an image to the Nord color palette without dithering artifacts.
+#[derive(argh::FromArgs)]
+struct Args {
+    /// input image path
+    #[argh(positional)]
+    input: PathBuf,
+
+    /// output image path
+    #[argh(option, short = 'o')]
+    output: PathBuf,
+
+    /// use only the original 16 Nord colors (disable palette expansion)
+    #[argh(switch)]
+    no_expand: bool,
+
+    /// number of interpolated colors between close palette entries (default: 3)
+    #[argh(option, default = "3")]
+    expansion_factor: usize,
+
+    /// use plain RGB distance instead of perceptual LAB distance
+    #[argh(switch)]
+    rgb_distance: bool,
+}
+
+fn main() -> std::process::ExitCode {
+    let args: Args = argh::from_env();
+    let options = nordify_rs::NordifyOptions {
+        expand: !args.no_expand,
+        expansion_factor: args.expansion_factor,
+        use_lab: !args.rgb_distance,
+    };
+
+    match nordify_rs::nordify_file(&args.input, &args.output, &options) {
+        Ok(()) => {
+            println!("Saved to {}", args.output.display());
+            std::process::ExitCode::SUCCESS
+        }
+        Err(err) => {
+            eprintln!("Error: {err}");
+            std::process::ExitCode::FAILURE
+        }
+    }
 }