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nerdislbandClaude Opus 5.5
cb61588e7d
Another maker's lens with the same specification ("Otherco 18-55mm f/3.5-5.6")
scores as high as the profile aliased "18-55mm f/3.5-5.6"; when it came first,
find_lens kept it and the exact-name check then refused it, so the alias was
never used. LensDb::find_lens_named ranks only the profiles named exactly so,
with the same maker and mount preferences (review on #2217).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
494 lines
22 KiB
Rust
494 lines
22 KiB
Rust
//! Lens correction profiles: distortion, transverse chromatic aberration (TCA) and vignetting.
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//!
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//! - [`model`]: the radial models (distortion poly3 / poly5 / PTLens, TCA linear / poly3, vignetting `pa`), and the
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//! least-squares conversion to the DNG opcode polynomials (`WarpRectilinear`, `FixVignetteRadial`) the pipeline
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//! already applies in its single geometry resample.
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//! - [`LensDb`]: profiles read from lensfun-format XML files in a directory the user supplies. The lensfun database
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//! is CC-BY-SA; it is never bundled with the code or the binary, only read at run time from where the user put it.
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//! - [`LensDb::find_camera`] / [`LensDb::find_lens`]: identification from EXIF make / model / lens model strings,
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//! with mount and crop-factor handling.
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//! - [`Profile::correction`]: the profile at a shot's focal length (and aperture / distance for vignetting),
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//! interpolated between calibrated points, expressed as [`lightcraft_develop::EmbeddedLens`] for a given image.
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//!
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//! Sources: the lensfun database format and model formulas as described in lensfun's published documentation
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//! (database file format and lens calibration pages; no lensfun code was read), Panorama Tools' distortion model
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//! (a, b, c) as documented by the PanoTools wiki, Adobe DNG specification 1.6 (opcodes `WarpRectilinear`,
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//! `FixVignetteRadial`). Interpolation and fitting: own design.
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#![forbid(unsafe_code)]
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#![deny(clippy::unwrap_used, clippy::expect_used, clippy::panic, clippy::unimplemented, clippy::todo, clippy::unreachable)]
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pub mod model;
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mod xml;
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use std::path::Path;
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use lightcraft_develop::{EmbeddedLens, EmbeddedVignette, EmbeddedWarp};
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use lightcraft_geom::Point;
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pub use model::{Distortion, Tca, Vignetting};
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/// Largest database file read (lensfun's biggest file is well under 1 MB).
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const MAX_FILE_BYTES: u64 = 16 << 20;
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/// Most files read from one directory.
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const MAX_FILES: usize = 2000;
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/// Largest radial error (half-diagonal units) accepted when converting a distortion to the DNG polynomial.
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pub const MAX_WARP_ERROR: f64 = 0.001;
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/// Largest relative error accepted when converting vignetting to the DNG polynomial.
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pub const MAX_VIGNETTE_ERROR: f64 = 0.01;
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#[derive(Debug, Clone, PartialEq)]
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pub enum Error {
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Io(String),
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Xml(String),
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TooLarge,
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}
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impl std::fmt::Display for Error {
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fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
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match self {
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Error::Io(e) => write!(f, "lens database: {e}"),
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Error::Xml(e) => write!(f, "lens database: invalid XML: {e}"),
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Error::TooLarge => write!(f, "lens database: file too large or too deeply nested"),
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}
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}
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}
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impl std::error::Error for Error {}
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/// A camera body: what is needed to pick lenses (mount) and scale profiles (crop factor).
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#[derive(Clone, Debug, PartialEq)]
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pub struct Camera {
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pub maker: String,
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pub model: String,
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pub mount: String,
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pub crop_factor: f64,
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}
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/// One calibrated vignetting point.
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#[derive(Clone, Copy, Debug, PartialEq)]
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pub struct VignettingPoint {
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pub focal: f64,
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pub aperture: f64,
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/// Focus distance, metres (lensfun uses 1000 for infinity).
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pub distance: f64,
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pub model: Vignetting,
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}
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/// A lens profile: names, mounts, the calibration frame and the calibrated points.
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#[derive(Clone, Debug, PartialEq)]
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pub struct Profile {
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pub maker: String,
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/// Every name the lens goes by (EXIF variants, translations).
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pub models: Vec<String>,
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pub mounts: Vec<String>,
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/// Crop factor of the camera the calibration was made on.
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pub crop_factor: f64,
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/// Long / short side of the calibration frame.
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pub aspect_ratio: f64,
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/// False for fisheye and other non-rectilinear projections: distortion is then not applied.
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pub rectilinear: bool,
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/// Sorted by focal length.
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pub distortion: Vec<(f64, Distortion)>,
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pub tca: Vec<(f64, Tca)>,
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pub vignetting: Vec<VignettingPoint>,
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}
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/// The shot a correction is wanted for.
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#[derive(Clone, Copy, Debug, PartialEq)]
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pub struct Shot {
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/// Focal length, mm.
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pub focal: f64,
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pub aperture: Option<f64>,
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/// Focus distance, metres.
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pub distance: Option<f64>,
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/// Crop factor of the recorded frame: the camera's (from [`LensDb::find_camera`]), or larger when the camera
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/// recorded a crop of its sensor; the profile's own when unknown.
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pub crop_factor: Option<f64>,
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/// Image size in pixels (the frame the correction is expressed for; the optical centre is its centre).
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pub width: f64,
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pub height: f64,
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}
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/// A set of lens and camera profiles.
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#[derive(Clone, Debug, Default, PartialEq)]
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pub struct LensDb {
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pub cameras: Vec<Camera>,
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pub lenses: Vec<Profile>,
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}
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impl LensDb {
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/// Read every `*.xml` file in `dir` (lensfun database format). Unreadable or invalid files are skipped and
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/// reported in the second value; only a directory that can't be listed is an error.
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pub fn load_dir(dir: &Path) -> Result<(LensDb, Vec<(String, Error)>), Error> {
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let mut entries: Vec<_> = std::fs::read_dir(dir)
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.map_err(|e| Error::Io(format!("{}: {e}", dir.display())))?
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.flatten()
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.map(|e| e.path())
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.filter(|p| p.extension().is_some_and(|x| x.eq_ignore_ascii_case("xml")))
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.collect();
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entries.sort();
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entries.truncate(MAX_FILES);
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let mut db = LensDb::default();
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let mut errors = Vec::new();
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for path in entries {
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let name = path.display().to_string();
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match read_capped(&path).and_then(|s| LensDb::parse(&s)) {
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Ok(part) => db.extend(part),
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Err(e) => errors.push((name, e)),
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}
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}
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Ok((db, errors))
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}
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/// Parse one lensfun-format XML document.
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pub fn parse(xml: &str) -> Result<LensDb, Error> {
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let root = xml::parse(xml)?;
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let Some(top) = root.kid("lensdatabase") else { return Err(Error::Xml("no <lensdatabase> element".into())) };
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let cameras = top.kids("camera").filter_map(camera).collect();
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let lenses = top.kids("lens").flat_map(lens).collect();
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Ok(LensDb { cameras, lenses })
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}
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pub fn extend(&mut self, other: LensDb) {
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self.cameras.extend(other.cameras);
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self.lenses.extend(other.lenses);
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}
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pub fn is_empty(&self) -> bool {
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self.cameras.is_empty() && self.lenses.is_empty()
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}
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/// The camera with this EXIF make and model.
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pub fn find_camera(&self, make: &str, model: &str) -> Option<&Camera> {
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let (mk, md) = (tokens(make), tokens(model));
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if md.is_empty() {
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return None;
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}
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self.cameras.iter().find(|c| tokens(&c.model) == md && maker_matches(&tokens(&c.maker), &mk))
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}
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/// The best profile for an EXIF lens model (and lens make, when the file has one), preferring lenses for the
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/// camera's mount. `None` when no name is a convincing match.
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pub fn find_lens(&self, lens_make: Option<&str>, lens_model: &str, camera: Option<&Camera>) -> Option<&Profile> {
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self.best_lens(lens_make, lens_model, camera, |_| true)
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}
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/// [`find_lens`](Self::find_lens) among the profiles one of whose names is exactly `name`
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/// ([`Profile::names_exactly`]), for names that carry no maker, such as [`spec_name`]s: another maker's lens with
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/// the same specification scores as high, and must neither win nor, by coming first, hide the profile named so.
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pub fn find_lens_named(&self, lens_make: Option<&str>, name: &str, camera: Option<&Camera>) -> Option<&Profile> {
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self.best_lens(lens_make, name, camera, |l| l.names_exactly(name))
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}
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fn best_lens(&self, lens_make: Option<&str>, lens_model: &str, camera: Option<&Camera>, eligible: impl Fn(&Profile) -> bool) -> Option<&Profile> {
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let exif = tokens(lens_model);
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if exif.is_empty() {
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return None;
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}
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let make = lens_make.map(tokens).unwrap_or_default();
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let mut best: Option<(f64, &Profile)> = None;
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for lens in self.lenses.iter().filter(|l| eligible(l)) {
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let maker = tokens(&lens.maker);
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if !make.is_empty() && !maker.is_empty() && !maker_matches(&maker, &make) {
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continue;
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}
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let mut score = lens.models.iter().map(|m| name_score(&tokens(m), &exif, &maker)).fold(0.0, f64::max);
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if let Some(cam) = camera
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&& !lens.mounts.is_empty()
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&& !lens.mounts.iter().any(|m| m.eq_ignore_ascii_case(&cam.mount))
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{
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score *= 0.8;
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}
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if score >= 0.6 && best.is_none_or(|(s, _)| score > s) {
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best = Some((score, lens));
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}
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}
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best.map(|(_, l)| l)
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}
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}
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fn read_capped(path: &Path) -> Result<String, Error> {
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let len = std::fs::metadata(path).map_err(|e| Error::Io(e.to_string()))?.len();
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if len > MAX_FILE_BYTES {
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return Err(Error::TooLarge);
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}
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let bytes = std::fs::read(path).map_err(|e| Error::Io(e.to_string()))?;
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Ok(String::from_utf8_lossy(&bytes).into_owned())
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}
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/// Lower-case word tokens; letters and digits are split ("24-105mm" → 24, 105, mm), decimals kept ("2.8").
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fn tokens(s: &str) -> Vec<String> {
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let mut out: Vec<String> = Vec::new();
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let mut cur = String::new();
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let mut prev_digit: Option<bool> = None;
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for c in s.chars().flat_map(char::to_lowercase) {
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let digit = c.is_ascii_digit() || (c == '.' && prev_digit == Some(true));
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if c.is_alphanumeric() || digit {
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if prev_digit.is_some_and(|p| p != digit) && !cur.is_empty() {
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out.push(std::mem::take(&mut cur));
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}
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cur.push(c);
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prev_digit = Some(digit);
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} else {
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if !cur.is_empty() {
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out.push(std::mem::take(&mut cur));
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}
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prev_digit = None;
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}
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}
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if !cur.is_empty() {
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out.push(cur);
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}
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for t in &mut out {
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// "4.0" and "4" are the same aperture
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if t.contains('.') && t.starts_with(|c: char| c.is_ascii_digit()) {
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let trimmed = t.trim_end_matches('0').trim_end_matches('.');
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*t = trimmed.to_string();
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}
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}
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out.retain(|t| !t.is_empty());
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out
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}
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fn is_number(t: &str) -> bool {
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t.starts_with(|c: char| c.is_ascii_digit())
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}
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/// Makers match when one's first word appears in the other ("NIKON CORPORATION" / "Nikon").
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fn maker_matches(a: &[String], b: &[String]) -> bool {
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match (a.first(), b.first()) {
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(Some(x), Some(y)) => b.contains(x) || a.contains(y),
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_ => true,
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}
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}
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/// How well a database name matches the EXIF name, 0..1. Every number in the database name (focal lengths,
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/// apertures) must appear in the EXIF name; the maker's words are ignored on both sides (EXIF often omits them).
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fn name_score(db: &[String], exif: &[String], maker: &[String]) -> f64 {
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let db: Vec<&String> = db.iter().filter(|t| !maker.contains(t)).collect();
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let exif: Vec<&String> = exif.iter().filter(|t| !maker.contains(t)).collect();
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if db.is_empty() || exif.is_empty() {
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return 0.0;
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}
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if db.iter().any(|t| is_number(t) && !exif.contains(t)) || exif.iter().any(|t| is_number(t) && !db.contains(t)) {
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return 0.0;
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}
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let common = db.iter().filter(|t| exif.contains(t)).count() as f64;
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common / db.len().max(exif.len()) as f64
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}
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fn camera(n: &xml::Node) -> Option<Camera> {
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Some(Camera {
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maker: n.kid_text("maker")?.to_string(),
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model: n.kid_text("model")?.to_string(),
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mount: n.kid_text("mount").unwrap_or_default().to_string(),
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crop_factor: crop_of(n.kid_text("cropfactor")).unwrap_or(1.0),
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})
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}
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fn crop_of(s: Option<&str>) -> Option<f64> {
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s.and_then(|v| v.trim().parse::<f64>().ok()).filter(|v| v.is_finite() && (0.05..=20.0).contains(v))
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}
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fn aspect_of(s: Option<&str>) -> Option<f64> {
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let s = s?.trim();
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let v = match s.split_once(':') {
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Some((a, b)) => a.trim().parse::<f64>().ok()? / b.trim().parse::<f64>().ok()?,
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None => s.parse::<f64>().ok()?,
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};
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let v = if v < 1.0 { 1.0 / v } else { v };
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(v.is_finite() && (1.0..=10.0).contains(&v)).then_some(v)
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}
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fn positive(v: Option<f64>) -> Option<f64> {
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v.filter(|v| *v > 0.0 && *v < 1e6)
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}
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/// One `<lens>` element → one profile per `<calibration>` (newer files give each its own crop factor and aspect).
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fn lens(n: &xml::Node) -> Vec<Profile> {
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let Some(maker) = n.kid_text("maker") else { return Vec::new() };
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let models: Vec<String> = n.kids("model").map(|m| m.text.trim().to_string()).filter(|m| !m.is_empty()).collect();
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if models.is_empty() {
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return Vec::new();
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}
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let crop = crop_of(n.kid_text("cropfactor")).unwrap_or(1.0);
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let aspect = aspect_of(n.kid_text("aspect-ratio")).unwrap_or(1.5);
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let rectilinear = n.kid_text("type").is_none_or(|t| t.eq_ignore_ascii_case("rectilinear"));
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let mounts = n.kids("mount").map(|m| m.text.trim().to_string()).filter(|m| !m.is_empty()).collect::<Vec<_>>();
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n.kids("calibration")
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.map(|cal| {
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let mut p = Profile {
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maker: maker.to_string(),
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models: models.clone(),
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mounts: mounts.clone(),
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crop_factor: crop_of(cal.attr("cropfactor")).unwrap_or(crop),
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aspect_ratio: aspect_of(cal.attr("aspect-ratio")).unwrap_or(aspect),
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rectilinear,
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distortion: Vec::new(),
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tca: Vec::new(),
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vignetting: Vec::new(),
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};
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for c in &cal.children {
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let Some(focal) = positive(c.num("focal")) else { continue };
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let k = |name: &str| c.num(name).unwrap_or(0.0);
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match (c.name.as_str(), c.attr("model")) {
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("distortion", Some("poly3")) => p.distortion.push((focal, Distortion::Poly3 { k1: k("k1") })),
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("distortion", Some("poly5")) => p.distortion.push((focal, Distortion::Poly5 { k1: k("k1"), k2: k("k2") })),
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("distortion", Some("ptlens")) => p.distortion.push((focal, Distortion::PtLens { a: k("a"), b: k("b"), c: k("c") })),
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("tca", Some("linear")) => {
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let one = |name: &str| c.num(name).unwrap_or(1.0);
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p.tca.push((focal, Tca::Linear { kr: one("kr"), kb: one("kb") }));
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}
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("tca", Some("poly3")) => {
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let one = |name: &str| c.num(name).unwrap_or(1.0);
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p.tca.push((focal, Tca::Poly3 { vr: one("vr"), vb: one("vb"), cr: k("cr"), cb: k("cb"), br: k("br"), bb: k("bb") }));
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}
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("vignetting", Some("pa")) => {
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let (Some(aperture), distance) = (positive(c.num("aperture")), positive(c.num("distance")).unwrap_or(1000.0)) else {
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continue;
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};
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let model = Vignetting { k1: k("k1"), k2: k("k2"), k3: k("k3") };
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p.vignetting.push(VignettingPoint { focal, aperture, distance, model });
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}
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_ => {}
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}
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}
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p.distortion.sort_by(|a, b| a.0.total_cmp(&b.0));
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p.tca.sort_by(|a, b| a.0.total_cmp(&b.0));
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p
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})
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.filter(|p| !p.distortion.is_empty() || !p.tca.is_empty() || !p.vignetting.is_empty())
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.collect()
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}
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/// Linear interpolation weights in a sorted key list: the bracketing indices and the weight of the upper one.
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fn bracket(keys: &[f64], x: f64) -> Option<(usize, usize, f64)> {
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let last = keys.len().checked_sub(1)?;
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let hi = keys.iter().position(|&k| k >= x).unwrap_or(last);
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let lo = hi.saturating_sub(1);
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let (a, b) = (keys.get(lo).copied()?, keys.get(hi).copied()?);
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if x <= a || b <= a {
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return Some((lo, lo, 0.0));
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}
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if x >= b {
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return Some((hi, hi, 0.0));
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}
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Some((lo, hi, (x - a) / (b - a)))
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}
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/// A value interpolated in focal length between calibrated points, by evaluating both neighbours.
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fn by_focal<T: Copy>(points: &[(f64, T)], focal: f64, eval: impl Fn(&T) -> f64) -> Option<f64> {
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let keys: Vec<f64> = points.iter().map(|p| p.0).collect();
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let (lo, hi, t) = bracket(&keys, focal)?;
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let (a, b) = (eval(&points.get(lo)?.1), eval(&points.get(hi)?.1));
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Some(a + (b - a) * t)
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}
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/// A lens name built from a lens specification (min / max focal length, f-number at each), for files that name
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/// no lens model, only its specification (Nikon DSLRs' maker note): "24-70mm f/2.8", "18-55mm f/3.5-5.6",
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/// "85mm f/1.8". Such a name says nothing about the maker, so [`Profile::names_exactly`] must confirm a match.
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pub fn spec_name(spec: [f64; 4]) -> String {
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fn num(v: f64) -> String {
|
|
let t = format!("{v:.1}");
|
|
t.trim_end_matches('0').trim_end_matches('.').to_string()
|
|
}
|
|
fn range(a: f64, b: f64) -> String {
|
|
if (a - b).abs() < 0.05 { num(a) } else { format!("{}-{}", num(a), num(b)) }
|
|
}
|
|
format!("{}mm f/{}", range(spec[0], spec[1]), range(spec[2], spec[3]))
|
|
}
|
|
|
|
impl Profile {
|
|
/// Whether one of the profile's names is exactly `name` (same words and numbers, ignoring case and
|
|
/// punctuation): the check for names that carry no maker, such as [`spec_name`]s, where the best partial match
|
|
/// could be another maker's lens with the same focal range. The maker's words count too, so "Samyang 85mm f/1.4"
|
|
/// is not "85mm f/1.4"; only a name given for the purpose (a user's alias) matches.
|
|
pub fn names_exactly(&self, name: &str) -> bool {
|
|
let want = tokens(name);
|
|
!want.is_empty() && self.models.iter().any(|m| tokens(m) == want)
|
|
}
|
|
|
|
/// Distortion ratio `r_d / r_u` at lensfun radius `r` for `focal` (1 when the profile has none).
|
|
pub fn distortion_ratio(&self, focal: f64, r: f64) -> f64 {
|
|
if !self.rectilinear {
|
|
return 1.0;
|
|
}
|
|
by_focal(&self.distortion, focal, |d| d.ratio(r)).unwrap_or(1.0)
|
|
}
|
|
|
|
/// TCA ratio for channel `ch` at lensfun radius `r` for `focal`.
|
|
pub fn tca_ratio(&self, focal: f64, ch: usize, r: f64) -> f64 {
|
|
by_focal(&self.tca, focal, |t| t.ratio(ch, r)).unwrap_or(1.0)
|
|
}
|
|
|
|
/// Vignetting attenuation at radius `r` (half-diagonal units): linear in focal length, in stops of aperture and
|
|
/// in 1 / distance between the calibrated points.
|
|
pub fn vignetting_attenuation(&self, focal: f64, aperture: Option<f64>, distance: Option<f64>, r: f64) -> Option<f64> {
|
|
let mut focals: Vec<f64> = self.vignetting.iter().map(|v| v.focal).collect();
|
|
focals.sort_by(f64::total_cmp);
|
|
focals.dedup();
|
|
let (lo, hi, t) = bracket(&focals, focal)?;
|
|
let at = |f: f64| -> Option<f64> {
|
|
let pts: Vec<&VignettingPoint> = self.vignetting.iter().filter(|v| v.focal == f).collect();
|
|
// the calibrated distance nearest the shot's (in 1/d; infinity when unknown)
|
|
let inv = |d: f64| 1.0 / d.max(0.01);
|
|
let want = distance.map_or(0.0, inv);
|
|
let near = pts.iter().map(|v| v.distance).min_by(|a, b| (inv(*a) - want).abs().total_cmp(&(inv(*b) - want).abs()))?;
|
|
let mut at_d: Vec<&&VignettingPoint> = pts.iter().filter(|v| v.distance == near).collect();
|
|
at_d.sort_by(|a, b| a.aperture.total_cmp(&b.aperture));
|
|
let stops: Vec<f64> = at_d.iter().map(|v| v.aperture.log2()).collect();
|
|
// unknown aperture: the widest calibrated one (the strongest falloff)
|
|
let n = aperture.filter(|a| *a > 0.0).map_or(stops.first().copied()?, f64::log2);
|
|
let (i, j, u) = bracket(&stops, n)?;
|
|
let (a, b) = (at_d.get(i)?.model.attenuation(r), at_d.get(j)?.model.attenuation(r));
|
|
Some(a + (b - a) * u)
|
|
};
|
|
let (a, b) = (at(*focals.get(lo)?)?, at(*focals.get(hi)?)?);
|
|
Some(a + (b - a) * t)
|
|
}
|
|
|
|
/// The correction for `shot`, as the DNG opcode polynomials the pipeline applies, centred on the image.
|
|
/// Distortion and TCA are combined per plane (R, G, B); a model the polynomial can't follow closely
|
|
/// ([`MAX_WARP_ERROR`], [`MAX_VIGNETTE_ERROR`]) or that would fold the image is left out.
|
|
pub fn correction(&self, shot: &Shot) -> Option<EmbeddedLens> {
|
|
let (w, h) = (shot.width, shot.height);
|
|
if !(w >= 2.0 && h >= 2.0 && w.is_finite() && h.is_finite() && shot.focal.is_finite() && shot.focal > 0.0) {
|
|
return None;
|
|
}
|
|
let cam = shot.crop_factor.filter(|c| c.is_finite() && *c > 0.0).unwrap_or(self.crop_factor);
|
|
// DNG radius (1 = image half diagonal) → lensfun radii
|
|
let to_vig = self.crop_factor / cam;
|
|
let to_dist = to_vig * (1.0 + self.aspect_ratio * self.aspect_ratio).sqrt();
|
|
let center = Point::new(0.5, 0.5);
|
|
let radius = w.hypot(h) / 2.0 / w.max(h);
|
|
let f = shot.focal;
|
|
let mut lens = EmbeddedLens::default();
|
|
let has_dist = self.rectilinear && !self.distortion.is_empty();
|
|
if has_dist || !self.tca.is_empty() {
|
|
let plane = |ch: usize| -> Option<[f64; 6]> {
|
|
let ratio = |r: f64| {
|
|
let rl = r * to_dist;
|
|
let d = self.distortion_ratio(f, rl);
|
|
d * self.tca_ratio(f, ch, rl * d)
|
|
};
|
|
let (k, err) = model::fit_even4(ratio)?;
|
|
(err <= MAX_WARP_ERROR).then_some([k[0], k[1], k[2], k[3], 0.0, 0.0])
|
|
};
|
|
if let (Some(r), Some(g), Some(b)) = (plane(0), plane(1), plane(2)) {
|
|
lens.warp = Some(EmbeddedWarp { planes: [r, g, b], center, radius });
|
|
}
|
|
}
|
|
if !self.vignetting.is_empty() {
|
|
let att = |r: f64| self.vignetting_attenuation(f, shot.aperture, shot.distance, r * to_vig).unwrap_or(1.0);
|
|
if let Some((k, err)) = model::fit_gain5(|r| 1.0 / att(r).max(0.05))
|
|
&& err <= MAX_VIGNETTE_ERROR
|
|
{
|
|
lens.vignette = Some(EmbeddedVignette { k, center, radius });
|
|
}
|
|
}
|
|
(lens.warp.is_some() || lens.vignette.is_some()).then_some(lens)
|
|
}
|
|
}
|
|
|
|
#[cfg(test)]
|
|
mod tests;
|