Refactor track for strict Clippy checks

crates/track/src/camtrack/bundle.rs

@@ -12,7 +12,7 @@ use rayon::prelude::*;
 
 use super::Distortion;
 use super::geometry::Pose;
-use super::linalg::*;
+use super::linalg::{M3, V3, add, cholesky_solve, dot, inv3, mm, mtv, mv, rodrigues, scale, skew, sub};
 
 /// A camera in the adjustment.
 #[derive(Clone, Copy, Debug, PartialEq)]
@@ -174,6 +174,29 @@ fn cam_jac(l: &Layout, ci: usize, c: &BaCam, xc: V3, a: &[[f64; 3]; 2], p: [f64;
     }
 }
 
+/// Smooth per-camera log focal lengths in the normal equations.
+fn add_focal_prior(cams: &[BaCam], o: &BaOpts, l: &Layout, s_mat: &mut [f64], bc: &mut [f64]) {
+    let n = l.n;
+    // Focal prior.
+    if let FocalMode::PerCamera(k) = o.focal {
+        for i in 0..cams.len().saturating_sub(1) {
+            let r = k * (cams[i].f.ln() - cams[i + 1].f.ln());
+            let (a, b) = (l.fidx[i], l.fidx[i + 1]);
+            let ia = (a != usize::MAX).then_some(a);
+            let ib = (b != usize::MAX).then_some(b);
+            for (idx, g) in [(ia, k), (ib, -k)] {
+                let Some(x) = idx else { continue };
+                bc[x] -= g * r;
+                for (idy, h) in [(ia, k), (ib, -k)] {
+                    if let Some(y) = idy {
+                        s_mat[x * n + y] += g * h;
+                    }
+                }
+            }
+        }
+    }
+}
+
 /// Run Levenberg–Marquardt. `cams` and `pts` are updated in place.
 pub fn adjust(cams: &mut [BaCam], pts: &mut [V3], obs: &[BaObs], o: &BaOpts) -> BaReport {
     let l = layout(cams.len(), o);
@@ -298,24 +321,7 @@ pub fn adjust(cams: &mut [BaCam], pts: &mut [V3], obs: &[BaObs], o: &BaOpts) ->
             let sys = (0..npts).map(|j| build_point(j, &mut s, &mut b)).collect();
             (s, b, sys)
         };
-        // Focal prior.
-        if let FocalMode::PerCamera(k) = o.focal {
-            for i in 0..cams.len().saturating_sub(1) {
-                let r = k * (cams[i].f.ln() - cams[i + 1].f.ln());
-                let (a, b) = (l.fidx[i], l.fidx[i + 1]);
-                let ia = (a != usize::MAX).then_some(a);
-                let ib = (b != usize::MAX).then_some(b);
-                for (idx, g) in [(ia, k), (ib, -k)] {
-                    let Some(x) = idx else { continue };
-                    bc[x] -= g * r;
-                    for (idy, h) in [(ia, k), (ib, -k)] {
-                        if let Some(y) = idy {
-                            s_mat[x * n + y] += g * h;
-                        }
-                    }
-                }
-            }
-        }
+        add_focal_prior(cams, o, &l, &mut s_mat, &mut bc);
         let base_s = s_mat.clone();
         let base_bc = bc.clone();
         let mean_diag = ((0..n).map(|i| base_s[i * n + i]).sum::<f64>() / n.max(1) as f64).max(1e-12);

crates/track/src/camtrack/geometry.rs

@@ -5,7 +5,10 @@
 //! All image points here are **normalised** (calibrated) coordinates `x = (u − c) / f`.
 //! A camera is `(R, C)` with `X_cam = R (X − C)`.
 
-use super::linalg::*;
+use super::linalg::{
+    I3, M3, V3, add, col, cross, det3, dot, from_cols, madd, mm, mscale, mt, mtv, mv, nearest_rotation, normalize, null_vector, outer, scale, sub, svd3,
+    sym_eigen,
+};
 
 /// A deterministic xorshift generator for RANSAC samples.
 pub struct Rng(pub u64);
@@ -361,6 +364,7 @@ pub fn procrustes(a: &[V3], b: &[V3]) -> Option<M3> {
 
 #[cfg(test)]
 mod tests {
+    use super::super::linalg::{log_rot, norm, rodrigues};
     use super::*;
 
     fn scene() -> (Vec<V3>, Pose) {

crates/track/src/camtrack/solver.rs

@@ -7,7 +7,7 @@ use rayon::prelude::*;
 
 use super::bundle::{self, BaCam, BaObs, BaOpts, FocalMode};
 use super::geometry::{self, Pose};
-use super::linalg::*;
+use super::linalg::{V3, add, log_rot, mm, mt, mtv, mv, norm, normalize, rodrigues, scale, slerp, sub, sym_eigen};
 use super::{CameraSolve, CameraTracks, Distortion, ShotType, SolveMethod, SolveSettings, SolvedFrame, SolvedPoint};
 use crate::fit::{Model, ransac};
 

crates/track/src/face.rs

@@ -547,6 +547,32 @@ fn fit_from_face(face: &Face, topo: &Topology, offset: [f64; 2]) -> Option<FaceF
     Some(FaceFit { landmarks, detected, outline, center, height: b, roll })
 }
 
+/// Find the first skin pixel in successive rings around the predicted center.
+fn nearest_skin(skin: &[bool], size: (usize, usize), center: (usize, usize), radius: i64) -> Option<(usize, usize)> {
+    let (w, h) = size;
+    let (ci, cj) = center;
+    for r in 0..radius {
+        for dj in -r..=r {
+            for di in -r..=r {
+                if di.abs() != r && dj.abs() != r {
+                    continue;
+                }
+                let (i, j) = (ci as i64 + di, cj as i64 + dj);
+                if i >= 0 && j >= 0 && (i as usize) < w && (j as usize) < h && skin[j as usize * w + i as usize] {
+                    return Some((i as usize, j as usize));
+                }
+            }
+        }
+    }
+    None
+}
+
+struct FaceGeometry {
+    center: [f64; 2],
+    height: f64,
+    roll: f64,
+}
+
 /// A pixel window of a frame in layer coordinates.
 struct Window {
     x0: i64,
@@ -752,6 +778,59 @@ impl FaceTracker {
         Some(fit)
     }
 
+    /// Connected dark features inside the fitted face, in normalized face coordinates.
+    fn feature_blobs(&self, frame: &Frame, win: &Window, skin: &[bool], luma: &[f32], outline: &[[f64; 2]], geometry: FaceGeometry) -> Vec<Blob> {
+        let FaceGeometry { center, height: b, roll } = geometry;
+        let (w, h) = (win.w, win.h);
+        // Non-skin components inside the face outline (shrunk a little: anti-aliased edges).
+        let inner: Vec<[f64; 2]> = outline.iter().map(|p| [center[0] + 0.9 * (p[0] - center[0]), center[1] + 0.9 * (p[1] - center[1])]).collect();
+        let mut feat = vec![false; w * h];
+        for j in 0..h {
+            for i in 0..w {
+                if !skin[j * w + i] && crate::mask::inside_polygon(&inner, win.layer(frame, i, j)) {
+                    feat[j * w + i] = true;
+                }
+            }
+        }
+        let min_area = (0.0006 * b * b).max(2.0) as usize;
+        let mut seen = vec![false; w * h];
+        let mut blobs: Vec<Blob> = vec![];
+        let skin_luma = self.skin.med[0] as f64;
+        for j0 in 0..h {
+            for i0 in 0..w {
+                if !feat[j0 * w + i0] || seen[j0 * w + i0] {
+                    continue;
+                }
+                let mut st = vec![(i0, j0)];
+                seen[j0 * w + i0] = true;
+                let mut pts = vec![];
+                while let Some((i, j)) = st.pop() {
+                    let q = to_face(center, b, roll, win.layer(frame, i, j));
+                    pts.push((q, skin_luma - luma[j * w + i] as f64));
+                    for dj in -1i64..=1 {
+                        for di in -1i64..=1 {
+                            let (a, c) = (i as i64 + di, j as i64 + dj);
+                            if a < 0 || c < 0 || a as usize >= w || c as usize >= h {
+                                continue;
+                            }
+                            let (a, c) = (a as usize, c as usize);
+                            if feat[c * w + a] && !seen[c * w + a] {
+                                seen[c * w + a] = true;
+                                st.push((a, c));
+                            }
+                        }
+                    }
+                }
+                if pts.len() >= min_area {
+                    let n = pts.len() as f64;
+                    let centroid = [pts.iter().map(|p| p.0[0]).sum::<f64>() / n, pts.iter().map(|p| p.0[1]).sum::<f64>() / n];
+                    blobs.push(Blob { pts, centroid });
+                }
+            }
+        }
+        blobs
+    }
+
     fn fit(&self, frame: &Frame) -> Option<FaceFit> {
         let pv = &self.prev;
         let b0 = pv.height;
@@ -769,22 +848,7 @@ impl FaceTracker {
         }
         // Seed: the skin pixel nearest the predicted centre.
         let (ci, cj) = win.cell(frame, pv.center)?;
-        let mut seed = None;
-        'search: for r in 0..(0.6 * b0).ceil() as i64 {
-            for dj in -r..=r {
-                for di in -r..=r {
-                    if di.abs() != r && dj.abs() != r {
-                        continue;
-                    }
-                    let (i, j) = (ci as i64 + di, cj as i64 + dj);
-                    if i >= 0 && j >= 0 && (i as usize) < w && (j as usize) < h && skin[j as usize * w + i as usize] {
-                        seed = Some((i as usize, j as usize));
-                        break 'search;
-                    }
-                }
-            }
-        }
-        let (si, sj) = seed?;
+        let (si, sj) = nearest_skin(&skin, (w, h), (ci, cj), (0.6 * b0).ceil() as i64)?;
         // Flood fill (4-connected).
         let mut comp = vec![false; w * h];
         let mut stack = vec![(si, sj)];
@@ -855,52 +919,7 @@ impl FaceTracker {
             roll += 180.0;
         }
         let b = major;
-        // Non-skin components inside the face outline (shrunk a little: anti-aliased edges).
-        let inner: Vec<[f64; 2]> = outline.iter().map(|p| [center[0] + 0.9 * (p[0] - center[0]), center[1] + 0.9 * (p[1] - center[1])]).collect();
-        let mut feat = vec![false; w * h];
-        for j in 0..h {
-            for i in 0..w {
-                if !skin[j * w + i] && crate::mask::inside_polygon(&inner, win.layer(frame, i, j)) {
-                    feat[j * w + i] = true;
-                }
-            }
-        }
-        let min_area = (0.0006 * b * b).max(2.0) as usize;
-        let mut seen = vec![false; w * h];
-        let mut blobs: Vec<Blob> = vec![];
-        let skin_luma = self.skin.med[0] as f64;
-        for j0 in 0..h {
-            for i0 in 0..w {
-                if !feat[j0 * w + i0] || seen[j0 * w + i0] {
-                    continue;
-                }
-                let mut st = vec![(i0, j0)];
-                seen[j0 * w + i0] = true;
-                let mut pts = vec![];
-                while let Some((i, j)) = st.pop() {
-                    let q = to_face(center, b, roll, win.layer(frame, i, j));
-                    pts.push((q, skin_luma - luma[j * w + i] as f64));
-                    for dj in -1i64..=1 {
-                        for di in -1i64..=1 {
-                            let (a, c) = (i as i64 + di, j as i64 + dj);
-                            if a < 0 || c < 0 || a as usize >= w || c as usize >= h {
-                                continue;
-                            }
-                            let (a, c) = (a as usize, c as usize);
-                            if feat[c * w + a] && !seen[c * w + a] {
-                                seen[c * w + a] = true;
-                                st.push((a, c));
-                            }
-                        }
-                    }
-                }
-                if pts.len() >= min_area {
-                    let n = pts.len() as f64;
-                    let centroid = [pts.iter().map(|p| p.0[0]).sum::<f64>() / n, pts.iter().map(|p| p.0[1]).sum::<f64>() / n];
-                    blobs.push(Blob { pts, centroid });
-                }
-            }
-        }
+        let blobs = self.feature_blobs(frame, &win, &skin, &luma, &outline, FaceGeometry { center, height: b, roll });
         // Match components to features near their expected positions.
         let ex = &self.expect;
         let mean_of = |ids: &[usize]| {

crates/track/src/roto.rs

@@ -407,7 +407,9 @@ fn beta(img: &[[f32; 3]], free: &[bool], w: usize, h: usize) -> f64 {
 
 /// One min-cut over the `free` pixels; others keep `labels`. `prior`: P(foreground) per pixel
 /// and how much it weighs against the colour models.
-fn cut(img: &[[f32; 3]], w: usize, h: usize, labels: &mut [u8], free: &[bool], hard: &[u8], fg: &Gmm, bg: &Gmm, prior: Option<(&[f32], f64)>) {
+fn cut(img: &[[f32; 3]], size: (usize, usize), labels: &mut [u8], free: &[bool], hard: &[u8], models: (&Gmm, &Gmm), prior: Option<(&[f32], f64)>) {
+    let (w, h) = size;
+    let (fg, bg) = models;
     let mut idx = vec![u32::MAX; w * h];
     let mut nodes = vec![];
     for i in 0..w * h {
@@ -622,6 +624,36 @@ pub struct Prior {
     pub weight: f64,
 }
 
+/// Fit foreground/background colour models from strokes and the propagated matte.
+fn initial_models(rgb: &[[f32; 3]], hard: &[u8], fgs: &[bool], strokes: &[&Stroke], prior: Option<&Prior>, opts: &SegOpts, size: (usize, usize)) -> (Gmm, Gmm) {
+    let (w, h) = size;
+    // Initial colour models: the strokes (and the propagated matte).
+    match prior {
+        Some(p) => {
+            let fgc = samples(rgb, |i| (hard[i] == HARD_FG) || (hard[i] == 0 && p.soft[i] >= 0.5));
+            let bgc = samples(rgb, |i| (hard[i] == HARD_BG) || (hard[i] == 0 && p.soft[i] < 0.5));
+            let f = Gmm::fit(&fgc, COMPONENTS, MAX_SAMPLES);
+            let b = Gmm::fit(&bgc, COMPONENTS, MAX_SAMPLES);
+            (if f.is_empty() { p.fg.clone() } else { f }, if b.is_empty() { p.bg.clone() } else { b })
+        }
+        None => {
+            let fgc = samples(rgb, |i| hard[i] == HARD_FG);
+            let mut bgc = samples(rgb, |i| hard[i] == HARD_BG);
+            if bgc.is_empty() {
+                // No background strokes: what is far from the foreground strokes.
+                let d = matting::distance(fgs, w, h);
+                let r = strokes.iter().filter(|s| s.kind == StrokeKind::Fg).map(|s| s.radius).fold(1.0, f64::max) * opts.scale;
+                let far = (4.0 * r).max(0.25 * w.max(h) as f64) as f32;
+                bgc = samples(rgb, |i| d[i] > far);
+                if bgc.is_empty() {
+                    bgc = samples(rgb, |i| hard[i] != HARD_FG);
+                }
+            }
+            (Gmm::fit(&fgc, COMPONENTS, MAX_SAMPLES), Gmm::fit(&bgc, COMPONENTS, MAX_SAMPLES))
+        }
+    }
+}
+
 /// Segment a frame from its strokes (and a propagated prior): GrabCut iterations on a reduced
 /// copy, then a full-resolution cut in a band around the boundary.
 pub fn segment(img: &Image, strokes: &[&Stroke], prior: Option<&Prior>, opts: &SegOpts, refine_radius: f64) -> FrameSeg {
@@ -649,31 +681,7 @@ pub fn segment(img: &Image, strokes: &[&Stroke], prior: Option<&Prior>, opts: &S
     let soft_prior: Option<Vec<f32>> =
         prior.map(|p| if p.weight > PRIOR { p.soft.clone() } else { matting::gauss(&p.soft, w, h, (opts.search_radius * opts.scale / 4.0).max(1.0)) });
     let pw = prior.map_or(PRIOR, |p| p.weight);
-    // Initial colour models: the strokes (and the propagated matte).
-    let (fg0, bg0) = match prior {
-        Some(p) => {
-            let fgc = samples(&rgb, |i| (hard[i] == HARD_FG) || (hard[i] == 0 && p.soft[i] >= 0.5));
-            let bgc = samples(&rgb, |i| (hard[i] == HARD_BG) || (hard[i] == 0 && p.soft[i] < 0.5));
-            let f = Gmm::fit(&fgc, COMPONENTS, MAX_SAMPLES);
-            let b = Gmm::fit(&bgc, COMPONENTS, MAX_SAMPLES);
-            (if f.is_empty() { p.fg.clone() } else { f }, if b.is_empty() { p.bg.clone() } else { b })
-        }
-        None => {
-            let fgc = samples(&rgb, |i| hard[i] == HARD_FG);
-            let mut bgc = samples(&rgb, |i| hard[i] == HARD_BG);
-            if bgc.is_empty() {
-                // No background strokes: what is far from the foreground strokes.
-                let d = matting::distance(&fgs, w, h);
-                let r = strokes.iter().filter(|s| s.kind == StrokeKind::Fg).map(|s| s.radius).fold(1.0, f64::max) * opts.scale;
-                let far = (4.0 * r).max(0.25 * w.max(h) as f64) as f32;
-                bgc = samples(&rgb, |i| d[i] > far);
-                if bgc.is_empty() {
-                    bgc = samples(&rgb, |i| hard[i] != HARD_FG);
-                }
-            }
-            (Gmm::fit(&fgc, COMPONENTS, MAX_SAMPLES), Gmm::fit(&bgc, COMPONENTS, MAX_SAMPLES))
-        }
-    };
+    let (fg0, bg0) = initial_models(&rgb, &hard, &fgs, strokes, prior, opts, (w, h));
     let iters = if opts.best { 4 } else { 3 };
     let work = if opts.best { 960 } else { 480 };
     let f = w.max(h).div_ceil(work).max(1);
@@ -721,7 +729,7 @@ pub fn segment(img: &Image, strokes: &[&Stroke], prior: Option<&Prior>, opts: &S
         };
         let free = vec![true; cw * ch];
         for it in 0..iters {
-            cut(&crgb, cw, ch, &mut cl, &free, &chard, &fgm, &bgm, cprior.as_deref().map(|c| (c, pw)));
+            cut(&crgb, (cw, ch), &mut cl, &free, &chard, (&fgm, &bgm), cprior.as_deref().map(|c| (c, pw)));
             if it + 1 < iters {
                 let (a, b) = fit_models(&crgb, &cl);
                 if !a.is_empty() && !b.is_empty() {
@@ -743,11 +751,11 @@ pub fn segment(img: &Image, strokes: &[&Stroke], prior: Option<&Prior>, opts: &S
         let sd = matting::signed_distance(&labels, w, h);
         let band = f as f32 + 1.5;
         let free: Vec<bool> = sd.iter().map(|d| d.abs() <= band).collect();
-        cut(&rgb, w, h, &mut labels, &free, &hard, &fgm, &bgm, soft_prior.as_deref().map(|c| (c, pw)));
+        cut(&rgb, (w, h), &mut labels, &free, &hard, (&fgm, &bgm), soft_prior.as_deref().map(|c| (c, pw)));
     } else {
         let free = vec![true; w * h];
         for it in 0..iters {
-            cut(&rgb, w, h, &mut labels, &free, &hard, &fgm, &bgm, soft_prior.as_deref().map(|c| (c, pw)));
+            cut(&rgb, (w, h), &mut labels, &free, &hard, (&fgm, &bgm), soft_prior.as_deref().map(|c| (c, pw)));
             if it + 1 < iters {
                 let (a, b) = fit_models(&rgb, &labels);
                 if !a.is_empty() && !b.is_empty() {
@@ -843,7 +851,7 @@ pub fn propagate(prev_img: &Image, prev: &FrameSeg, next_img: &Image, strokes: &
     let hard = vec![0u8; w * h];
     let soft = matting::gauss(&prior.soft, w, h, (r as f64 / 4.0).max(1.0));
     let (fg, bg) = if prev.fg.is_empty() || prev.bg.is_empty() { fit_models(&rgb, &labels) } else { (prev.fg.clone(), prev.bg.clone()) };
-    cut(&rgb, w, h, &mut labels, &free, &hard, &fg, &bg, Some((&soft, PRIOR)));
+    cut(&rgb, (w, h), &mut labels, &free, &hard, (&fg, &bg), Some((&soft, PRIOR)));
     let seeds = core_of(&prior.soft, w, h, r as f64);
     clean(&mut labels, &seeds, &vec![false; w * h], w, h);
     finish(next_img, &rgb, labels, strokes, Some(&prior.refine), opts, refine_radius)

crates/track/src/roto/matting.rs

@@ -200,7 +200,8 @@ pub fn guided_filter(img: &[[f32; 3]], p: &[f32], w: usize, h: usize, r: usize,
 /// (K. He, J. Sun and X. Tang, "Fast Matting Using Large Kernel Matting Laplacian Matrices",
 /// CVPR 2010): `(L·x)ᵢ = Σ_{k∋i} (xᵢ − a_kᵀIᵢ − b_k)` with `(a_k, b_k)` the ridge-regression
 /// fit of `x` to the colours in window k.
-pub fn closed_form(img: &[[f32; 3]], init: &[f32], known: &[bool], w: usize, h: usize, r: usize, eps: f32, iters: usize) -> Vec<f32> {
+pub fn closed_form(img: &[[f32; 3]], init: &[f32], known: &[bool], size: (usize, usize), r: usize, eps: f32, iters: usize) -> Vec<f32> {
+    let (w, h) = size;
     let n = w * h;
     if n == 0 || known.iter().all(|k| *k) {
         return init.to_vec();

crates/track/src/roto/refine.rs

@@ -123,7 +123,7 @@ pub fn matte_alpha(
             q[j] = if band[j] { q[j].clamp(0.0, 1.0) } else { cp[j] };
         }
         if p.higher_quality {
-            q = matting::closed_form(&cimg, &q, &outside, cw, ch, 1, 1e-5 * (1.0 + p.smooth.max(0.0)) as f32, 50);
+            q = matting::closed_form(&cimg, &q, &outside, (cw, ch), 1, 1e-5 * (1.0 + p.smooth.max(0.0)) as f32, 50);
         }
         // Refine Edge Matte adjustments.
         if p.smooth > 1.0 {
@@ -177,7 +177,8 @@ pub fn matte_alpha(
 /// Decontaminate edge colours of `rgb` in place for the matte `alpha` (see
 /// [`matting::decontaminate`]); returns the decontamination map. `band`: the Refine Edge band
 /// (pixels where decontamination always applies).
-pub fn decontaminate(rgb: &mut [[f32; 3]], alpha: &[f32], band: &[u8], w: usize, h: usize, p: &MatteParams, band_radius: f64, scale: f64) -> Vec<f32> {
+pub fn decontaminate(rgb: &mut [[f32; 3]], alpha: &[f32], band: &[u8], size: (usize, usize), p: &MatteParams, band_radius: f64, scale: f64) -> Vec<f32> {
+    let (w, h) = size;
     if !p.decontaminate {
         return vec![0.0; w * h];
     }

crates/track/src/roto/tests.rs

@@ -246,7 +246,7 @@ fn refine_edge_recovers_a_soft_edge_and_decontaminates() {
     assert!(frac as f64 > 0.6 * n as f64, "{frac}/{n} fractional");
     // Decontamination: edge pixels' colour is the foreground's, not a blue blend.
     let mut col = rgb.clone();
-    let map = decontaminate(&mut col, &a, &seg.refine, W as usize, H as usize, &p, 9.0, 1.0);
+    let map = decontaminate(&mut col, &a, &seg.refine, (W as usize, H as usize), &p, 9.0, 1.0);
     let (mut blue_before, mut blue_after, mut m) = (0.0f64, 0.0f64, 0usize);
     for i in 0..a.len() {
         if a[i] > 0.2 && a[i] < 0.8 {