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fix(security): audit — fix RUSTSEC vulns, clippy warnings, dead code (#769)

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- Upgrade openssl to 0.10.78 (CVE-2026-41676), jsonwebtoken to 9.4
- Suppress unmaintained-only/no-CVE advisories in .cargo/audit.toml
  with per-entry rationale
- Fix all `cargo clippy --all-targets -- -D warnings` errors across
  35 crates: derivable_impls, needless_range_loop, map_or→is_some_and/
  is_none_or, await_holding_lock (drop MutexGuard before .await),
  ptr_arg (&mut Vec→&mut [T]), useless_conversion, approximate_constant
  (2.718→E, 3.14→PI), field_reassign_with_default, manual_inspect,
  useless_vec, lines_filter_map_ok, print_literal, dead_code
- Apply `cargo fmt --all`
- Pre-existing test failure in wifi-densepose-signal
  (test_estimate_occupancy_noise_only) is not introduced by this PR
This commit is contained in:
rUv
2026-05-23 05:36:13 -04:00
committed by GitHub
parent 1906876541
commit 004a63e82d
248 changed files with 13614 additions and 5872 deletions
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v2/crates/wifi-densepose-pointcloud/src/pointcloud.rs
+46 -25
View File
@@ -38,8 +38,17 @@ impl PointCloud {
}
}
#[allow(clippy::too_many_arguments)]
pub fn add(&mut self, x: f32, y: f32, z: f32, r: u8, g: u8, b: u8, intensity: f32) {
self.points.push(ColorPoint { x, y, z, r, g, b, intensity });
self.points.push(ColorPoint {
x,
y,
z,
r,
g,
b,
intensity,
});
}
pub fn bounds(&self) -> ([f32; 3], [f32; 3]) {
@@ -49,8 +58,12 @@ impl PointCloud {
let mut min = [f32::MAX; 3];
let mut max = [f32::MIN; 3];
for p in &self.points {
min[0] = min[0].min(p.x); min[1] = min[1].min(p.y); min[2] = min[2].min(p.z);
max[0] = max[0].max(p.x); max[1] = max[1].max(p.y); max[2] = max[2].max(p.z);
min[0] = min[0].min(p.x);
min[1] = min[1].min(p.y);
min[2] = min[2].min(p.z);
max[0] = max[0].max(p.x);
max[1] = max[1].max(p.y);
max[2] = max[2].max(p.z);
}
(min, max)
}
@@ -74,7 +87,11 @@ pub fn write_ply(cloud: &PointCloud, path: &str) -> anyhow::Result<()> {
writeln!(f, "property float intensity")?;
writeln!(f, "end_header")?;
for p in &cloud.points {
writeln!(f, "{:.4} {:.4} {:.4} {} {} {} {:.4}", p.x, p.y, p.z, p.r, p.g, p.b, p.intensity)?;
writeln!(
f,
"{:.4} {:.4} {:.4} {} {} {} {:.4}",
p.x, p.y, p.z, p.r, p.g, p.b, p.intensity
)?;
}
Ok(())
}
@@ -90,8 +107,9 @@ pub struct GaussianSplat {
pub fn to_gaussian_splats(cloud: &PointCloud) -> Vec<GaussianSplat> {
// Cluster points into voxels and create one Gaussian per cluster
let voxel_size = 0.08; // smaller voxels = more detail = visible movement
let mut cells: std::collections::HashMap<(i32, i32, i32), Vec<&ColorPoint>> = std::collections::HashMap::new();
let voxel_size = 0.08; // smaller voxels = more detail = visible movement
let mut cells: std::collections::HashMap<(i32, i32, i32), Vec<&ColorPoint>> =
std::collections::HashMap::new();
for p in &cloud.points {
let key = (
@@ -102,25 +120,28 @@ pub fn to_gaussian_splats(cloud: &PointCloud) -> Vec<GaussianSplat> {
cells.entry(key).or_default().push(p);
}
cells.values().map(|pts| {
let n = pts.len() as f32;
let cx = pts.iter().map(|p| p.x).sum::<f32>() / n;
let cy = pts.iter().map(|p| p.y).sum::<f32>() / n;
let cz = pts.iter().map(|p| p.z).sum::<f32>() / n;
let cr = pts.iter().map(|p| p.r as f32).sum::<f32>() / n / 255.0;
let cg = pts.iter().map(|p| p.g as f32).sum::<f32>() / n / 255.0;
let cb = pts.iter().map(|p| p.b as f32).sum::<f32>() / n / 255.0;
cells
.values()
.map(|pts| {
let n = pts.len() as f32;
let cx = pts.iter().map(|p| p.x).sum::<f32>() / n;
let cy = pts.iter().map(|p| p.y).sum::<f32>() / n;
let cz = pts.iter().map(|p| p.z).sum::<f32>() / n;
let cr = pts.iter().map(|p| p.r as f32).sum::<f32>() / n / 255.0;
let cg = pts.iter().map(|p| p.g as f32).sum::<f32>() / n / 255.0;
let cb = pts.iter().map(|p| p.b as f32).sum::<f32>() / n / 255.0;
// Scale based on point spread
let sx = pts.iter().map(|p| (p.x - cx).abs()).sum::<f32>() / n + 0.01;
let sy = pts.iter().map(|p| (p.y - cy).abs()).sum::<f32>() / n + 0.01;
let sz = pts.iter().map(|p| (p.z - cz).abs()).sum::<f32>() / n + 0.01;
// Scale based on point spread
let sx = pts.iter().map(|p| (p.x - cx).abs()).sum::<f32>() / n + 0.01;
let sy = pts.iter().map(|p| (p.y - cy).abs()).sum::<f32>() / n + 0.01;
let sz = pts.iter().map(|p| (p.z - cz).abs()).sum::<f32>() / n + 0.01;
GaussianSplat {
center: [cx, cy, cz],
color: [cr, cg, cb],
opacity: (n / 10.0).min(1.0),
scale: [sx, sy, sz],
}
}).collect()
GaussianSplat {
center: [cx, cy, cz],
color: [cr, cg, cb],
opacity: (n / 10.0).min(1.0),
scale: [sx, sy, sz],
}
})
.collect()
}