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https://github.com/visioncortex/vtracer.git
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- The library now speaks the image crate's buffer types only: fidelity(&RgbImage, &RgbImage, thresh) -> (FidelityReport, GrayImage). A tracer embedding the metric pulls no image codec at all. - New `cli` feature (default on) brings png/jpeg/webp decoding and gates the vtracer-bench bin (required-features). - dssim-core with default features off: drops the rayon thread pool. - Scores are unchanged: the CLI prints the same value before and after.
67 lines
2.2 KiB
Rust
67 lines
2.2 KiB
Rust
//! Blind fidelity benchmark for raster-to-vector tracers.
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//!
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//! vtracer-bench <original> <candidate> [--thresh N] [--mask out.png]
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//!
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//! Both arguments are rasters of identical dimensions — rendering a vector
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//! reconstruction to pixels is the caller's responsibility. Prints the raw
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//! metrics, their [0,1] subscores, the composite fidelity, and a
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//! machine-readable csv line.
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use vtracer_bench::{DEFAULT_THRESH, fidelity};
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fn main() {
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let args: Vec<String> = std::env::args().collect();
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if args.len() < 3 {
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eprintln!("usage: vtracer-bench <original> <candidate> [--thresh N] [--mask out.png]");
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std::process::exit(2);
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}
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let mut thresh = DEFAULT_THRESH;
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let mut mask_out: Option<String> = None;
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let mut i = 3;
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while i < args.len() {
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match args[i].as_str() {
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"--thresh" => {
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i += 1;
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thresh = args[i].parse().expect("--thresh N");
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}
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"--mask" => {
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i += 1;
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mask_out = Some(args[i].clone());
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}
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a => {
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eprintln!("unknown flag {a}");
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std::process::exit(2);
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}
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}
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i += 1;
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}
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let orig = image::open(&args[1]).expect("open original").to_rgb8();
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let cand = image::open(&args[2]).expect("open candidate").to_rgb8();
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assert_eq!(cand.dimensions(), orig.dimensions(), "candidate raster must match original dimensions");
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let (r, mask) = fidelity(&orig, &cand, thresh);
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if let Some(out) = mask_out {
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mask.save(&out).expect("save mask");
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}
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println!(
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"psnr {:>8.2} dB (rmse {:.2}) -> {:.4}",
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r.psnr, r.rmse, r.s_psnr
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);
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println!(
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"ssim {:>8.5} (dssim {:.5}) -> {:.4}",
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r.s_ssim, r.dssim, r.s_ssim
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);
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println!(
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"patch {:>8.1} px rms ({} bad px, {} clusters, largest {}) -> {:.4}",
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r.patch_mass, r.bad_px, r.clusters, r.largest, r.s_patch
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);
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println!("fidelity {:.4}", r.fidelity);
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println!(
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"[csv] {:.4},{:.2},{:.5},{:.2},{:.1},{:.4},{:.4},{:.4}",
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r.fidelity, r.psnr, r.dssim, r.rmse, r.patch_mass, r.s_psnr, r.s_ssim, r.s_patch
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);
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}
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