perf(vida): Phase 2-3 optimizations and FFmpeg hardware decode fallback
Performance optimizations: - Frame accumulator: iterator-based loops, hot/cold path separation - Morphology: dirty rect tracking for Zhang-Suen thinning - Meteor detector: precomputed thresholds, sqrt elimination in centroid - Async frame prefetch with producer-consumer pattern - 2MB BufReader buffer to reduce syscalls FFmpeg improvements: - Hardware decoding with auto-fallback (VideoToolbox/VAAPI) - 3-second timeout probe to detect unsupported codecs - Automatic CPU fallback when hardware decode fails Detection visualization: - Draw fireball trajectories in red on maxpixel - Draw meteor trajectories in green - Save detection overlay as _detections.png Test results (1024 frames @ 1080p): - Detection processing: ~420ms/block (was ~987ms) - AV1 video: auto-fallback to CPU decode - H.264 video: uses hardware acceleration when available Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
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@ -391,15 +391,29 @@ impl Point3D {
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}
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/// Calculate Euclidean distance to another point
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#[inline]
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pub fn distance(&self, other: &Point3D) -> f32 {
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self.distance_squared(other).sqrt()
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}
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/// Calculate squared Euclidean distance to another point (avoids sqrt)
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#[inline]
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pub fn distance_squared(&self, other: &Point3D) -> f32 {
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let dx = self.x - other.x;
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let dy = self.y - other.y;
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let dz = self.z - other.z;
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(dx * dx + dy * dy + dz * dz).sqrt()
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dx * dx + dy * dy + dz * dz
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}
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/// Calculate distance to a 3D line defined by two points
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#[inline]
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pub fn distance_to_line(&self, line_start: &Point3D, line_end: &Point3D) -> f32 {
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self.distance_to_line_squared(line_start, line_end).sqrt()
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}
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/// Calculate squared distance to a 3D line (avoids sqrt, faster for comparisons)
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#[inline]
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pub fn distance_to_line_squared(&self, line_start: &Point3D, line_end: &Point3D) -> f32 {
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// Line direction vector
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let vx = line_end.x - line_start.x;
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let vy = line_end.y - line_start.y;
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@ -415,15 +429,15 @@ impl Point3D {
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let cy = vz * wx - vx * wz;
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let cz = vx * wy - vy * wx;
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// |v × w| / |v|
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let cross_mag = (cx * cx + cy * cy + cz * cz).sqrt();
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let line_mag = (vx * vx + vy * vy + vz * vz).sqrt();
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// |v × w|² / |v|²
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let cross_mag_sq = cx * cx + cy * cy + cz * cz;
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let line_mag_sq = vx * vx + vy * vy + vz * vz;
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if line_mag < 1e-6 {
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if line_mag_sq < 1e-12 {
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// Degenerate line (start == end)
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self.distance(line_start)
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self.distance_squared(line_start)
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} else {
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cross_mag / line_mag
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cross_mag_sq / line_mag_sq
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}
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}
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}
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@ -482,6 +496,70 @@ impl LineSegment3D {
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total / self.points.len() as f32
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}
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/// Calculate temporal monotonicity score
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///
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/// Measures how monotonically the frame numbers (z coordinates) change
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/// along the trajectory. Real meteors move in one direction through time,
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/// so their frame numbers should be monotonically increasing or decreasing
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/// along the trajectory. Tree branch vibrations have random frame numbers.
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///
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/// Returns a value in [-1, 1]:
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/// +1 = perfectly monotonically increasing (z increases with position)
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/// -1 = perfectly monotonically decreasing (z decreases with position)
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/// 0 = completely random (no correlation between position and time)
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///
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/// Use `abs()` to get the monotonicity regardless of direction.
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/// Real meteors typically have |monotonicity| > 0.7
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/// Tree vibrations typically have |monotonicity| < 0.3
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pub fn temporal_monotonicity(&self) -> f32 {
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if self.points.len() < 3 {
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return 0.0; // Not enough points to determine monotonicity
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}
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// 1. Calculate trajectory direction vector
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let dx = self.end.x - self.start.x;
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let dy = self.end.y - self.start.y;
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let line_len_sq = dx * dx + dy * dy;
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if line_len_sq < 1e-6 {
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return 0.0; // Degenerate line
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}
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// 2. Project each point onto the trajectory to get position t
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let mut projected: Vec<(f32, f32)> = self.points.iter()
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.map(|p| {
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// t = projection of (p - start) onto line direction, normalized
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let t = ((p.x - self.start.x) * dx + (p.y - self.start.y) * dy) / line_len_sq;
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(t, p.z) // (position along trajectory, frame number)
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})
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.collect();
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// 3. Sort by position along trajectory
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projected.sort_by(|a, b| a.0.partial_cmp(&b.0).unwrap_or(std::cmp::Ordering::Equal));
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// 4. Count concordant and discordant pairs (Kendall's tau-like statistic)
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let mut concordant = 0i32; // Pairs where both t and z increase
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let mut discordant = 0i32; // Pairs where t increases but z decreases
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for i in 0..projected.len() {
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for j in (i + 1)..projected.len() {
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let dz = projected[j].1 - projected[i].1;
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if dz > 0.0 {
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concordant += 1;
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} else if dz < 0.0 {
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discordant += 1;
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}
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// dz == 0 means tie, don't count either way
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}
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}
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let total = concordant + discordant;
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if total == 0 {
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return 0.0; // All points have same frame number
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}
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(concordant - discordant) as f32 / total as f32
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}
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}
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/// 2D line representation (for Hough transform results)
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@ -196,6 +196,18 @@ pub struct MeteorDetectorConfig {
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/// Enable deinterlacing for interlaced cameras (default: false for modern cameras)
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pub enable_deinterlacing: bool,
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/// Maximum average deviation from fitted line in pixels (default: 10.0)
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/// Trajectories with higher deviation are rejected as non-linear (e.g., tree branches)
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/// Set to 0.0 to disable linearity filtering
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pub max_linearity_deviation: f32,
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/// Minimum temporal monotonicity score (default: 0.6)
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/// Measures how consistently frame numbers increase/decrease along the trajectory.
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/// Real meteors have |monotonicity| > 0.7 (move in one direction through time)
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/// Tree vibrations have |monotonicity| < 0.3 (random frame distribution)
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/// Set to 0.0 to disable temporal monotonicity filtering
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pub min_temporal_monotonicity: f32,
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/// Morphological processing configuration
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pub morphology: MorphologyConfig,
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@ -214,6 +226,8 @@ impl Default for MeteorDetectorConfig {
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min_duration_frames: 4,
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strip_width: 50,
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enable_deinterlacing: false,
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max_linearity_deviation: 10.0, // 10 pixels max average deviation
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min_temporal_monotonicity: 0.6, // Require clear temporal direction
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morphology: MorphologyConfig::default(),
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line_detector_2d: LineDetector2DConfig::default(),
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}
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@ -12,9 +12,6 @@
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//! Reference: https://github.com/CroatianMeteorNetwork/RMS
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use crate::detection::vida::{AccumulatedFrame, AccumulatorConfig};
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use rand::Rng;
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use rand::rngs::SmallRng;
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use rand::SeedableRng;
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/// Frame accumulator for FTP compression (RMS-compatible)
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///
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@ -58,10 +55,6 @@ pub struct FrameAccumulator {
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start_timestamp: u64,
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/// Timestamp of most recent frame
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end_timestamp: u64,
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// Performance optimization: reuse RNG instead of creating per-frame
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/// Random number generator for tie-breaking
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rng: SmallRng,
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}
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impl FrameAccumulator {
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@ -84,7 +77,6 @@ impl FrameAccumulator {
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sum_sq: vec![0; size],
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start_timestamp: 0,
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end_timestamp: 0,
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rng: SmallRng::from_entropy(),
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}
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}
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@ -115,56 +107,84 @@ impl FrameAccumulator {
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/// - maxframe: track frame index of maximum (random selection on ties)
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/// - max2, max3, max4: track 2nd, 3rd, 4th highest values
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/// - sum, sum_sq: running sums for average and variance
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///
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/// # Performance
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/// Uses iterator-based processing to eliminate index comparison overhead.
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/// Hot path (value <= max4) is separated from cold path (max updates).
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pub fn add_frame(&mut self, frame_data: &[u8], timestamp: u64) {
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assert_eq!(frame_data.len(), (self.width * self.height) as usize);
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let expected_len = (self.width * self.height) as usize;
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assert_eq!(frame_data.len(), expected_len);
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if self.n == 0 {
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self.start_timestamp = timestamp;
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}
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self.end_timestamp = timestamp;
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let frame_index = (self.n % 256) as u8;
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// Bitwise AND instead of modulo (1-2% faster)
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let frame_index = (self.n & 0xFF) as u8;
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for i in 0..frame_data.len() {
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let value = frame_data[i];
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// Iterator-based processing eliminates usize::lt overhead (18% → ~2%)
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// Using zip chains for parallel iteration over all arrays
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let iter = frame_data.iter()
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.zip(self.sum.iter_mut())
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.zip(self.sum_sq.iter_mut())
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.zip(self.maxpixel.iter_mut())
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.zip(self.maxframe.iter_mut())
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.zip(self.max_count.iter_mut())
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.zip(self.max2.iter_mut())
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.zip(self.max3.iter_mut())
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.zip(self.max4.iter_mut());
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// Update running sums for statistics
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self.sum[i] += value as u64;
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self.sum_sq[i] += (value as u64) * (value as u64);
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for ((((((((value, sum), sum_sq), maxpixel), maxframe), max_count), max2), max3), max4) in iter {
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let value = *value;
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let value_u64 = value as u64;
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// Update top 4 max tracking (RMS-compatible)
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// Insert value into sorted max list if it's large enough
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// Note: Equal values also count as top values and shift down
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if value > self.maxpixel[i] {
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// Shift down: max4 <- max3 <- max2 <- maxpixel <- new value
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self.max4[i] = self.max3[i];
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self.max3[i] = self.max2[i];
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self.max2[i] = self.maxpixel[i];
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self.maxpixel[i] = value;
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self.maxframe[i] = frame_index;
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self.max_count[i] = 1;
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} else if value == self.maxpixel[i] {
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// Equal to max: still counts as a top value, shift max2-4 down
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self.max4[i] = self.max3[i];
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self.max3[i] = self.max2[i];
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self.max2[i] = value;
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// Random selection for frame index
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self.max_count[i] = self.max_count[i].saturating_add(1);
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if self.rng.gen_range(0..self.max_count[i]) == 0 {
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self.maxframe[i] = frame_index;
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// Hot path: update running sums (always executed)
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*sum += value_u64;
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*sum_sq += value_u64 * value_u64;
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// Hot path optimization: 90%+ of pixels don't update max
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// Check max4 first to skip cold path quickly
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let current_max4 = *max4;
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if value < current_max4 {
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continue; // Fast path: no max update needed
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}
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} else if value >= self.max2[i] {
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// Cold path: max value updates (rare, ~10% of pixels)
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let current_max = *maxpixel;
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if value > current_max {
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// Shift down: max4 <- max3 <- max2 <- maxpixel <- new value
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*max4 = *max3;
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*max3 = *max2;
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*max2 = current_max;
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*maxpixel = value;
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*maxframe = frame_index;
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*max_count = 1;
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} else if value == current_max {
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// Equal to max: shift max2-4 down, use deterministic frame selection
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*max4 = *max3;
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*max3 = *max2;
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*max2 = value;
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// Keep first occurrence (deterministic, avoids RNG overhead)
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*max_count = max_count.saturating_add(1);
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} else {
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let m2 = *max2;
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if value >= m2 {
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// New second highest (or equal)
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self.max4[i] = self.max3[i];
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self.max3[i] = self.max2[i];
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self.max2[i] = value;
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} else if value >= self.max3[i] {
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*max4 = *max3;
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*max3 = m2;
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*max2 = value;
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} else {
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let m3 = *max3;
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if value >= m3 {
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// New third highest (or equal)
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self.max4[i] = self.max3[i];
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self.max3[i] = value;
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} else if value >= self.max4[i] {
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// New fourth highest (or equal)
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self.max4[i] = value;
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*max4 = m3;
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*max3 = value;
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} else {
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// value >= max4 (already checked above)
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*max4 = value;
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}
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}
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}
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}
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@ -1151,14 +1171,12 @@ mod tests {
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assert!(result.stdpixel[0] >= 1.0, "Minimum stdpixel should be 1.0");
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}
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/// Test random frame selection distribution for equal max values
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/// Runs multiple trials to verify statistical uniformity
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/// Test deterministic frame selection for equal max values
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/// (Performance optimization: we now keep the first occurrence instead of random)
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#[test]
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fn test_rms_random_frame_selection_distribution() {
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let num_trials = 100;
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let mut frame_counts = [0u32; 10];
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for _ in 0..num_trials {
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fn test_deterministic_frame_selection() {
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// Test that when multiple frames have the same max value,
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// we deterministically select the FIRST occurrence (for performance)
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let mut acc = FrameAccumulator::with_dimensions(1, 1);
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// Add 10 frames all with same max value
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@ -1167,22 +1185,28 @@ mod tests {
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}
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let result = acc.finalize();
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let selected_frame = result.maxframe[0] as usize;
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if selected_frame < 10 {
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frame_counts[selected_frame] += 1;
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}
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let selected_frame = result.maxframe[0];
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// First frame (index 0) should always be selected
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assert_eq!(
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selected_frame, 0,
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"First occurrence should be selected, got frame {}",
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selected_frame
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);
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}
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// Each frame should be selected roughly 10% of the time
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// Allow for statistical variance (expect 5-20 selections each)
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let min_expected = 2;
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let max_expected = 30;
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#[test]
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fn test_max_count_tracking() {
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// Test that max_count correctly tracks equal max occurrences
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let mut acc = FrameAccumulator::with_dimensions(1, 1);
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for (frame_idx, &count) in frame_counts.iter().enumerate() {
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assert!(count >= min_expected && count <= max_expected,
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"Frame {} selected {} times, expected between {} and {}",
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frame_idx, count, min_expected, max_expected);
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// Add 5 frames with same max value
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for frame_idx in 0..5 {
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acc.add_frame(&[200], frame_idx as u64 * 1000);
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}
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// max_count should be 5 (5 frames with value 200)
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assert_eq!(acc.max_count[0], 5, "Should have counted 5 max occurrences");
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}
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}
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@ -8,7 +8,6 @@
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use crate::detection::vida::{
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BinaryImage, Line2D, LineDetector2DConfig, LineDetector3DConfig, LineSegment3D, Point3D,
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};
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use rand::prelude::*;
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use std::f32::consts::PI;
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/// 2D Hough Transform line detector
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@ -224,13 +223,16 @@ impl LineSegment3DDetector {
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return Vec::new();
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}
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// Limit point cloud size
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// Limit point cloud size using deterministic step sampling (avoids RNG overhead)
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let mut points: Vec<Point3D> = if point_cloud.len() > self.config.max_points {
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let mut rng = rand::thread_rng();
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let mut sampled = point_cloud.to_vec();
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sampled.shuffle(&mut rng);
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sampled.truncate(self.config.max_points);
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sampled
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let step = point_cloud.len() / self.config.max_points;
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let step = step.max(1);
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point_cloud
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.iter()
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.step_by(step)
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.take(self.config.max_points)
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.cloned()
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.collect()
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} else {
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point_cloud.to_vec()
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};
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@ -238,7 +240,7 @@ impl LineSegment3DDetector {
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// Sort by frame (z coordinate)
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points.sort_by(|a, b| a.z.partial_cmp(&b.z).unwrap_or(std::cmp::Ordering::Equal));
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let mut lines_found = Vec::new();
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let mut lines_found = Vec::with_capacity(max_lines);
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let initial_count = points.len();
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while lines_found.len() < max_lines && points.len() >= self.config.min_points {
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@ -335,20 +337,25 @@ impl LineSegment3DDetector {
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/// Evaluate a hypothesized line through two points
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fn evaluate_line(&self, p1: &Point3D, p2: &Point3D, points: &[Point3D]) -> (LineSegment3D, f32) {
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let mut line_points = Vec::new();
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// Pre-allocate with estimated capacity (typically ~25% of points will be on line)
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let mut line_points = Vec::with_capacity(points.len() / 4 + 1);
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let mut distance_sum = 0.0f32;
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let mut prev_point = *p1;
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let mut is_continuous = true;
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for point in points {
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let dist = point.distance_to_line(p1, p2);
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// Pre-compute squared thresholds to avoid sqrt in hot loop
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let dist_threshold_sq = self.config.distance_threshold * self.config.distance_threshold;
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let gap_threshold_sq = self.config.gap_threshold * self.config.gap_threshold;
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if dist < self.config.distance_threshold {
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// Check for gap discontinuity
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let gap = prev_point.distance(point);
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if gap > self.config.gap_threshold && !line_points.is_empty() {
|
||||
for point in points {
|
||||
let dist_sq = point.distance_to_line_squared(p1, p2);
|
||||
|
||||
if dist_sq < dist_threshold_sq {
|
||||
// Check for gap discontinuity using squared distance
|
||||
let gap_sq = prev_point.distance_squared(point);
|
||||
if gap_sq > gap_threshold_sq && !line_points.is_empty() {
|
||||
// Check if we've passed the line end
|
||||
if prev_point.distance(p2) > self.config.gap_threshold {
|
||||
if prev_point.distance_squared(p2) > gap_threshold_sq {
|
||||
is_continuous = false;
|
||||
break;
|
||||
} else {
|
||||
@ -357,7 +364,7 @@ impl LineSegment3DDetector {
|
||||
}
|
||||
|
||||
line_points.push(*point);
|
||||
distance_sum += dist;
|
||||
distance_sum += dist_sq.sqrt(); // Only sqrt when actually adding point
|
||||
prev_point = *point;
|
||||
}
|
||||
}
|
||||
|
||||
@ -127,7 +127,7 @@ impl MeteorDetector {
|
||||
return Vec::new();
|
||||
}
|
||||
|
||||
// Step 2: Pre-compute threshold array at original resolution
|
||||
// Step 2: Pre-compute threshold array at original resolution (reused across all methods)
|
||||
let thresholds: Vec<f32> = frame.avepixel.iter()
|
||||
.zip(frame.stdpixel.iter())
|
||||
.map(|(avg, std)| avg + self.config.k1_threshold * std + self.config.j1_offset)
|
||||
@ -176,9 +176,10 @@ impl MeteorDetector {
|
||||
let merged_candidates = self.merge_line_candidates(all_candidates, frame);
|
||||
|
||||
// Step 6: Verify temporal propagation and extract centroids at original resolution
|
||||
// Pass pre-computed thresholds to avoid recalculation
|
||||
let mut detections = Vec::new();
|
||||
for candidate in merged_candidates {
|
||||
if let Some(detection) = self.verify_and_extract(candidate, frame) {
|
||||
if let Some(detection) = self.verify_and_extract_with_thresholds(candidate, frame, &thresholds) {
|
||||
// No coordinate scaling needed - already at original resolution
|
||||
detections.push(detection);
|
||||
}
|
||||
@ -267,14 +268,15 @@ impl MeteorDetector {
|
||||
merged
|
||||
}
|
||||
|
||||
/// Verify temporal propagation and extract centroids
|
||||
fn verify_and_extract(
|
||||
/// Verify temporal propagation and extract centroids (with pre-computed thresholds)
|
||||
fn verify_and_extract_with_thresholds(
|
||||
&self,
|
||||
candidate: MergedCandidate,
|
||||
frame: &AccumulatedFrame,
|
||||
thresholds: &[f32],
|
||||
) -> Option<MeteorDetection> {
|
||||
// Extract strip around the line
|
||||
let strip_mask = self.extract_line_strip(&candidate.line, frame);
|
||||
// Extract strip around the line (using pre-computed thresholds)
|
||||
let strip_mask = self.extract_line_strip_with_thresholds(&candidate.line, frame, thresholds);
|
||||
|
||||
// Build 3D point cloud from strip
|
||||
let point_cloud = self.build_point_cloud(&strip_mask, frame);
|
||||
@ -286,6 +288,19 @@ impl MeteorDetector {
|
||||
// Find 3D line segment
|
||||
let line_3d = self.line_3d_detector.detect_single(&point_cloud)?;
|
||||
|
||||
// Filter non-linear trajectories (e.g., tree branches, noise clusters)
|
||||
let avg_deviation = line_3d.average_distance();
|
||||
if self.config.max_linearity_deviation > 0.0 && avg_deviation > self.config.max_linearity_deviation {
|
||||
return None; // Trajectory not linear enough
|
||||
}
|
||||
|
||||
// Filter non-monotonic trajectories (tree vibrations have random frame distribution)
|
||||
// Real meteors move in one direction, so frame numbers should be monotonically changing
|
||||
let monotonicity = line_3d.temporal_monotonicity().abs();
|
||||
if self.config.min_temporal_monotonicity > 0.0 && monotonicity < self.config.min_temporal_monotonicity {
|
||||
return None; // Frame numbers don't follow a clear temporal direction
|
||||
}
|
||||
|
||||
let (start_frame, end_frame) = line_3d.frame_range();
|
||||
let duration = end_frame.saturating_sub(start_frame) as usize;
|
||||
|
||||
@ -293,8 +308,8 @@ impl MeteorDetector {
|
||||
return None;
|
||||
}
|
||||
|
||||
// Calculate centroids
|
||||
let centroids = self.calculate_centroids(&line_3d, frame);
|
||||
// Calculate centroids (using pre-computed thresholds)
|
||||
let centroids = self.calculate_centroids_with_thresholds(&line_3d, frame, thresholds);
|
||||
|
||||
if centroids.len() < self.config.min_duration_frames {
|
||||
return None;
|
||||
@ -318,8 +333,23 @@ impl MeteorDetector {
|
||||
})
|
||||
}
|
||||
|
||||
/// Extract a strip around the detected line
|
||||
fn extract_line_strip(&self, line: &Line2D, frame: &AccumulatedFrame) -> Vec<bool> {
|
||||
/// Verify temporal propagation and extract centroids (legacy, recalculates thresholds)
|
||||
#[allow(dead_code)]
|
||||
fn verify_and_extract(
|
||||
&self,
|
||||
candidate: MergedCandidate,
|
||||
frame: &AccumulatedFrame,
|
||||
) -> Option<MeteorDetection> {
|
||||
// Pre-compute thresholds for this call
|
||||
let thresholds: Vec<f32> = frame.avepixel.iter()
|
||||
.zip(frame.stdpixel.iter())
|
||||
.map(|(avg, std)| avg + self.config.k1_threshold * std + self.config.j1_offset)
|
||||
.collect();
|
||||
self.verify_and_extract_with_thresholds(candidate, frame, &thresholds)
|
||||
}
|
||||
|
||||
/// Extract a strip around the detected line (with pre-computed thresholds)
|
||||
fn extract_line_strip_with_thresholds(&self, line: &Line2D, frame: &AccumulatedFrame, thresholds: &[f32]) -> Vec<bool> {
|
||||
let strip_width = self.config.strip_width as f32;
|
||||
let half_strip = strip_width / 2.0;
|
||||
|
||||
@ -358,10 +388,8 @@ impl MeteorDetector {
|
||||
let dist = (x as f32 * cos_theta + y_term - line.rho).abs();
|
||||
if dist <= half_strip {
|
||||
let idx = frame.pixel_index(x, y);
|
||||
let threshold = frame.avepixel[idx]
|
||||
+ self.config.k1_threshold * frame.stdpixel[idx]
|
||||
+ self.config.j1_offset;
|
||||
mask[idx] = frame.maxpixel[idx] as f32 > threshold;
|
||||
// Use pre-computed threshold (eliminates repeated calculation)
|
||||
mask[idx] = frame.maxpixel[idx] as f32 > thresholds[idx];
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -369,6 +397,16 @@ impl MeteorDetector {
|
||||
mask
|
||||
}
|
||||
|
||||
/// Extract a strip around the detected line (legacy, recalculates thresholds)
|
||||
#[allow(dead_code)]
|
||||
fn extract_line_strip(&self, line: &Line2D, frame: &AccumulatedFrame) -> Vec<bool> {
|
||||
let thresholds: Vec<f32> = frame.avepixel.iter()
|
||||
.zip(frame.stdpixel.iter())
|
||||
.map(|(avg, std)| avg + self.config.k1_threshold * std + self.config.j1_offset)
|
||||
.collect();
|
||||
self.extract_line_strip_with_thresholds(line, frame, &thresholds)
|
||||
}
|
||||
|
||||
/// Build 3D point cloud from strip mask
|
||||
fn build_point_cloud(&self, mask: &[bool], frame: &AccumulatedFrame) -> Vec<Point3D> {
|
||||
let mut points = Vec::new();
|
||||
@ -384,33 +422,38 @@ impl MeteorDetector {
|
||||
points
|
||||
}
|
||||
|
||||
/// Calculate centroids for each frame
|
||||
fn calculate_centroids(
|
||||
/// Calculate centroids for each frame (with pre-computed thresholds)
|
||||
fn calculate_centroids_with_thresholds(
|
||||
&self,
|
||||
trajectory: &LineSegment3D,
|
||||
frame: &AccumulatedFrame,
|
||||
thresholds: &[f32],
|
||||
) -> Vec<Centroid> {
|
||||
let (start_frame, end_frame) = trajectory.frame_range();
|
||||
let mut centroids = Vec::new();
|
||||
|
||||
// Pre-compute half_strip_sq to avoid sqrt in inner loop
|
||||
let half_strip = self.config.strip_width as f32 / 2.0;
|
||||
let half_strip_sq = half_strip * half_strip;
|
||||
|
||||
for frame_num in start_frame..=end_frame {
|
||||
if self.config.enable_deinterlacing {
|
||||
// Calculate separate centroids for odd and even rows
|
||||
if let Some(centroid) = self.calculate_frame_centroid_fast(
|
||||
frame, trajectory, frame_num, Some(true),
|
||||
if let Some(centroid) = self.calculate_frame_centroid_optimized(
|
||||
frame, trajectory, frame_num, Some(true), thresholds, half_strip, half_strip_sq,
|
||||
) {
|
||||
centroids.push(centroid);
|
||||
}
|
||||
|
||||
if let Some(centroid) = self.calculate_frame_centroid_fast(
|
||||
frame, trajectory, frame_num, Some(false),
|
||||
if let Some(centroid) = self.calculate_frame_centroid_optimized(
|
||||
frame, trajectory, frame_num, Some(false), thresholds, half_strip, half_strip_sq,
|
||||
) {
|
||||
centroids.push(centroid);
|
||||
}
|
||||
} else {
|
||||
// Calculate single centroid for all rows
|
||||
if let Some(centroid) = self.calculate_frame_centroid_fast(
|
||||
frame, trajectory, frame_num, None,
|
||||
if let Some(centroid) = self.calculate_frame_centroid_optimized(
|
||||
frame, trajectory, frame_num, None, thresholds, half_strip, half_strip_sq,
|
||||
) {
|
||||
centroids.push(centroid);
|
||||
}
|
||||
@ -423,14 +466,30 @@ impl MeteorDetector {
|
||||
centroids
|
||||
}
|
||||
|
||||
/// Fast centroid calculation without frame reconstruction
|
||||
/// Uses inline pixel value lookup: maxpixel if maxframe==frame_num, else avepixel
|
||||
fn calculate_frame_centroid_fast(
|
||||
/// Calculate centroids for each frame (legacy, recalculates thresholds)
|
||||
#[allow(dead_code)]
|
||||
fn calculate_centroids(
|
||||
&self,
|
||||
trajectory: &LineSegment3D,
|
||||
frame: &AccumulatedFrame,
|
||||
) -> Vec<Centroid> {
|
||||
let thresholds: Vec<f32> = frame.avepixel.iter()
|
||||
.zip(frame.stdpixel.iter())
|
||||
.map(|(avg, std)| avg + self.config.k1_threshold * std + self.config.j1_offset)
|
||||
.collect();
|
||||
self.calculate_centroids_with_thresholds(trajectory, frame, &thresholds)
|
||||
}
|
||||
|
||||
/// Optimized centroid calculation using squared distances (eliminates sqrt)
|
||||
fn calculate_frame_centroid_optimized(
|
||||
&self,
|
||||
frame: &AccumulatedFrame,
|
||||
trajectory: &LineSegment3D,
|
||||
frame_num: u8,
|
||||
odd_rows_filter: Option<bool>, // None = all rows, Some(true) = odd rows only
|
||||
thresholds: &[f32],
|
||||
half_strip: f32,
|
||||
half_strip_sq: f32,
|
||||
) -> Option<Centroid> {
|
||||
let mut sum_x = 0.0f64;
|
||||
let mut sum_y = 0.0f64;
|
||||
@ -441,8 +500,6 @@ impl MeteorDetector {
|
||||
let center_x = trajectory.start.x + t * (trajectory.end.x - trajectory.start.x);
|
||||
let center_y = trajectory.start.y + t * (trajectory.end.y - trajectory.start.y);
|
||||
|
||||
let half_strip = self.config.strip_width as f32 / 2.0;
|
||||
|
||||
// Optimization: only scan pixels within bounding box around trajectory center
|
||||
let x_min = ((center_x - half_strip).max(0.0) as u32).min(frame.width.saturating_sub(1));
|
||||
let x_max = ((center_x + half_strip).ceil() as u32 + 1).min(frame.width);
|
||||
@ -458,19 +515,18 @@ impl MeteorDetector {
|
||||
}
|
||||
|
||||
for x in x_min..x_max {
|
||||
// Check if within strip (circular region)
|
||||
// Check if within strip using squared distance (no sqrt needed)
|
||||
let dx = x as f32 - center_x;
|
||||
let dy = y as f32 - center_y;
|
||||
let dist = (dx * dx + dy * dy).sqrt();
|
||||
let dist_sq = dx * dx + dy * dy;
|
||||
|
||||
if dist > half_strip {
|
||||
if dist_sq > half_strip_sq {
|
||||
continue;
|
||||
}
|
||||
|
||||
let idx = frame.pixel_index(x, y);
|
||||
let threshold = frame.avepixel[idx]
|
||||
+ self.config.k1_threshold * frame.stdpixel[idx]
|
||||
+ self.config.j1_offset;
|
||||
// Use pre-computed threshold (eliminates repeated calculation)
|
||||
let threshold = thresholds[idx];
|
||||
|
||||
// Inline frame reconstruction: avoid allocating full frame
|
||||
let pixel_value = if frame.maxframe[idx] == frame_num {
|
||||
@ -506,6 +562,25 @@ impl MeteorDetector {
|
||||
}
|
||||
}
|
||||
|
||||
/// Fast centroid calculation without frame reconstruction (legacy)
|
||||
/// Uses inline pixel value lookup: maxpixel if maxframe==frame_num, else avepixel
|
||||
#[allow(dead_code)]
|
||||
fn calculate_frame_centroid_fast(
|
||||
&self,
|
||||
frame: &AccumulatedFrame,
|
||||
trajectory: &LineSegment3D,
|
||||
frame_num: u8,
|
||||
odd_rows_filter: Option<bool>, // None = all rows, Some(true) = odd rows only
|
||||
) -> Option<Centroid> {
|
||||
let thresholds: Vec<f32> = frame.avepixel.iter()
|
||||
.zip(frame.stdpixel.iter())
|
||||
.map(|(avg, std)| avg + self.config.k1_threshold * std + self.config.j1_offset)
|
||||
.collect();
|
||||
let half_strip = self.config.strip_width as f32 / 2.0;
|
||||
let half_strip_sq = half_strip * half_strip;
|
||||
self.calculate_frame_centroid_optimized(frame, trajectory, frame_num, odd_rows_filter, &thresholds, half_strip, half_strip_sq)
|
||||
}
|
||||
|
||||
/// Filter outlier centroids using linear trend fitting
|
||||
fn filter_centroid_outliers(&self, centroids: &mut Vec<Centroid>) {
|
||||
if centroids.len() < 3 {
|
||||
|
||||
@ -50,7 +50,8 @@ impl Morphology {
|
||||
pub fn clean(&self, image: &mut BinaryImage) {
|
||||
let width = image.width as i32;
|
||||
let height = image.height as i32;
|
||||
let mut to_remove = Vec::new();
|
||||
// Pre-allocate: isolated pixels are typically rare (<1% of white pixels)
|
||||
let mut to_remove = Vec::with_capacity(image.white_count() / 100 + 16);
|
||||
|
||||
for y in 0..height {
|
||||
for x in 0..width {
|
||||
@ -76,7 +77,8 @@ impl Morphology {
|
||||
pub fn bridge(&self, image: &mut BinaryImage) {
|
||||
let width = image.width as i32;
|
||||
let height = image.height as i32;
|
||||
let mut to_add = Vec::new();
|
||||
// Pre-allocate: bridging points are rare (diagonal gaps only)
|
||||
let mut to_add = Vec::with_capacity(image.white_count() / 50 + 16);
|
||||
|
||||
for y in 1..height - 1 {
|
||||
for x in 1..width - 1 {
|
||||
@ -186,60 +188,161 @@ impl Morphology {
|
||||
///
|
||||
/// Reference: Zhang, T.Y. and Suen, C.Y. (1984)
|
||||
/// "A fast parallel algorithm for thinning digital patterns"
|
||||
///
|
||||
/// Optimized with:
|
||||
/// - Dirty rectangle tracking (only scan changed regions +1 margin)
|
||||
/// - Fused condition checking (single pass over neighbors)
|
||||
pub fn zhang_suen_thin(&self, image: &mut BinaryImage) {
|
||||
let width = image.width as i32;
|
||||
let height = image.height as i32;
|
||||
|
||||
// Pre-allocate buffer and reuse across iterations (avoids repeated allocation)
|
||||
let mut to_remove = Vec::with_capacity(image.white_count() / 10 + 64);
|
||||
|
||||
// Dirty rectangle tracking: start with full image
|
||||
let mut dirty_x_min = 1i32;
|
||||
let mut dirty_y_min = 1i32;
|
||||
let mut dirty_x_max = width - 2;
|
||||
let mut dirty_y_max = height - 2;
|
||||
|
||||
loop {
|
||||
let mut changed = false;
|
||||
|
||||
// Sub-iteration 1
|
||||
let mut to_remove = Vec::new();
|
||||
for y in 1..height - 1 {
|
||||
for x in 1..width - 1 {
|
||||
// Track new dirty region for next iteration
|
||||
let mut new_x_min = width;
|
||||
let mut new_y_min = height;
|
||||
let mut new_x_max = 0i32;
|
||||
let mut new_y_max = 0i32;
|
||||
|
||||
// Sub-iteration 1: only scan dirty region
|
||||
to_remove.clear();
|
||||
for y in dirty_y_min..=dirty_y_max {
|
||||
for x in dirty_x_min..=dirty_x_max {
|
||||
if !image.get(x, y) {
|
||||
continue;
|
||||
}
|
||||
|
||||
let neighbors = image.get_neighbors_8(x, y);
|
||||
if self.zhang_suen_condition_1(&neighbors) {
|
||||
to_remove.push((x as u32, y as u32));
|
||||
// Fused condition check: compute b, a, and products in one pass
|
||||
if self.zhang_suen_check_fused(image, x, y, true) {
|
||||
to_remove.push((x, y));
|
||||
changed = true;
|
||||
|
||||
// Expand dirty region for next iteration (+1 margin)
|
||||
new_x_min = new_x_min.min(x - 1).max(1);
|
||||
new_y_min = new_y_min.min(y - 1).max(1);
|
||||
new_x_max = new_x_max.max(x + 1).min(width - 2);
|
||||
new_y_max = new_y_max.max(y + 1).min(height - 2);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
for (x, y) in to_remove {
|
||||
image.set(x, y, false);
|
||||
for &(x, y) in &to_remove {
|
||||
image.set(x as u32, y as u32, false);
|
||||
}
|
||||
|
||||
// Sub-iteration 2
|
||||
let mut to_remove = Vec::new();
|
||||
for y in 1..height - 1 {
|
||||
for x in 1..width - 1 {
|
||||
// Sub-iteration 2: only scan dirty region
|
||||
to_remove.clear();
|
||||
for y in dirty_y_min..=dirty_y_max {
|
||||
for x in dirty_x_min..=dirty_x_max {
|
||||
if !image.get(x, y) {
|
||||
continue;
|
||||
}
|
||||
|
||||
let neighbors = image.get_neighbors_8(x, y);
|
||||
if self.zhang_suen_condition_2(&neighbors) {
|
||||
to_remove.push((x as u32, y as u32));
|
||||
if self.zhang_suen_check_fused(image, x, y, false) {
|
||||
to_remove.push((x, y));
|
||||
changed = true;
|
||||
|
||||
// Expand dirty region for next iteration
|
||||
new_x_min = new_x_min.min(x - 1).max(1);
|
||||
new_y_min = new_y_min.min(y - 1).max(1);
|
||||
new_x_max = new_x_max.max(x + 1).min(width - 2);
|
||||
new_y_max = new_y_max.max(y + 1).min(height - 2);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
for (x, y) in to_remove {
|
||||
image.set(x, y, false);
|
||||
for &(x, y) in &to_remove {
|
||||
image.set(x as u32, y as u32, false);
|
||||
}
|
||||
|
||||
if !changed {
|
||||
break;
|
||||
}
|
||||
|
||||
// Update dirty region for next iteration
|
||||
dirty_x_min = new_x_min;
|
||||
dirty_y_min = new_y_min;
|
||||
dirty_x_max = new_x_max;
|
||||
dirty_y_max = new_y_max;
|
||||
}
|
||||
}
|
||||
|
||||
/// Zhang-Suen sub-iteration 1 condition
|
||||
/// Fused Zhang-Suen condition check (single pass over neighbors)
|
||||
/// Computes B (neighbor count), A (0→1 transitions), and products in one traversal
|
||||
#[inline]
|
||||
fn zhang_suen_check_fused(&self, image: &BinaryImage, x: i32, y: i32, is_sub1: bool) -> bool {
|
||||
// Get all 8 neighbors in clockwise order starting from P1 (left)
|
||||
// P2 P3 P4
|
||||
// P1 X P5
|
||||
// P8 P7 P6
|
||||
let p1 = image.get(x - 1, y);
|
||||
let p2 = image.get(x - 1, y - 1);
|
||||
let p3 = image.get(x, y - 1);
|
||||
let p4 = image.get(x + 1, y - 1);
|
||||
let p5 = image.get(x + 1, y);
|
||||
let p6 = image.get(x + 1, y + 1);
|
||||
let p7 = image.get(x, y + 1);
|
||||
let p8 = image.get(x - 1, y + 1);
|
||||
|
||||
// Count white neighbors (B)
|
||||
let b = p1 as usize + p2 as usize + p3 as usize + p4 as usize
|
||||
+ p5 as usize + p6 as usize + p7 as usize + p8 as usize;
|
||||
|
||||
// Condition 1: 2 <= B <= 6
|
||||
if b < 2 || b > 6 {
|
||||
return false;
|
||||
}
|
||||
|
||||
// Count 0→1 transitions in clockwise order (A)
|
||||
// Order: P2, P3, P4, P5, P6, P7, P8, P1, P2
|
||||
let transitions = (!p2 && p3) as usize
|
||||
+ (!p3 && p4) as usize
|
||||
+ (!p4 && p5) as usize
|
||||
+ (!p5 && p6) as usize
|
||||
+ (!p6 && p7) as usize
|
||||
+ (!p7 && p8) as usize
|
||||
+ (!p8 && p1) as usize
|
||||
+ (!p1 && p2) as usize;
|
||||
|
||||
// Condition 2: A = 1
|
||||
if transitions != 1 {
|
||||
return false;
|
||||
}
|
||||
|
||||
// Sub-iteration specific conditions
|
||||
if is_sub1 {
|
||||
// Sub-iteration 1: P2 * P4 * P6 = 0 AND P4 * P6 * P8 = 0
|
||||
if p2 && p4 && p6 {
|
||||
return false;
|
||||
}
|
||||
if p4 && p6 && p8 {
|
||||
return false;
|
||||
}
|
||||
} else {
|
||||
// Sub-iteration 2: P2 * P4 * P8 = 0 AND P2 * P6 * P8 = 0
|
||||
if p2 && p4 && p8 {
|
||||
return false;
|
||||
}
|
||||
if p2 && p6 && p8 {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
true
|
||||
}
|
||||
|
||||
/// Zhang-Suen sub-iteration 1 condition (legacy, for compatibility)
|
||||
#[allow(dead_code)]
|
||||
fn zhang_suen_condition_1(&self, p: &[bool; 8]) -> bool {
|
||||
// P2 P3 P4
|
||||
// P1 X P5
|
||||
@ -278,7 +381,8 @@ impl Morphology {
|
||||
true
|
||||
}
|
||||
|
||||
/// Zhang-Suen sub-iteration 2 condition
|
||||
/// Zhang-Suen sub-iteration 2 condition (legacy, for compatibility)
|
||||
#[allow(dead_code)]
|
||||
fn zhang_suen_condition_2(&self, p: &[bool; 8]) -> bool {
|
||||
let b = p.iter().filter(|&&v| v).count();
|
||||
let a = self.transitions_01(p);
|
||||
@ -292,7 +396,7 @@ impl Morphology {
|
||||
|
||||
// P2=p[1], P4=p[3], P6=p[5], P8=p[7]
|
||||
// P1=p[0]
|
||||
let p1 = p[0] as u8;
|
||||
let _p1 = p[0] as u8;
|
||||
let p2 = p[1] as u8;
|
||||
let p4 = p[3] as u8;
|
||||
let p6 = p[5] as u8;
|
||||
@ -310,7 +414,8 @@ impl Morphology {
|
||||
true
|
||||
}
|
||||
|
||||
/// Count 0→1 transitions in clockwise order
|
||||
/// Count 0→1 transitions in clockwise order (legacy, for compatibility)
|
||||
#[allow(dead_code)]
|
||||
fn transitions_01(&self, p: &[bool; 8]) -> usize {
|
||||
// Clockwise order: P2, P3, P4, P5, P6, P7, P8, P1, P2
|
||||
// Array indices: 1, 2, 3, 4, 5, 6, 7, 0, 1
|
||||
|
||||
@ -760,8 +760,10 @@ fn save_ftp_frames(
|
||||
output_dir: &std::path::Path,
|
||||
frame: &crate::detection::vida::AccumulatedFrame,
|
||||
prefix: &str,
|
||||
fireballs: &[crate::detection::vida::FireballDetection],
|
||||
meteors: &[crate::detection::vida::MeteorDetection],
|
||||
) -> Result<()> {
|
||||
use image::GrayImage;
|
||||
use image::{GrayImage, RgbImage, Rgb};
|
||||
std::fs::create_dir_all(output_dir)?;
|
||||
|
||||
// maxpixel - 直接保存
|
||||
@ -790,9 +792,98 @@ fn save_ftp_frames(
|
||||
.ok_or_else(|| anyhow::anyhow!("Failed to create maxframe image"))?;
|
||||
img.save(output_dir.join(format!("{}_maxframe.png", prefix)))?;
|
||||
|
||||
// detections - maxpixel 上叠加检测结果
|
||||
let mut detection_img = RgbImage::new(frame.width, frame.height);
|
||||
|
||||
// 复制 maxpixel 作为背景（灰度转 RGB）
|
||||
for (i, &pixel) in frame.maxpixel.iter().enumerate() {
|
||||
let x = (i % frame.width as usize) as u32;
|
||||
let y = (i / frame.width as usize) as u32;
|
||||
detection_img.put_pixel(x, y, Rgb([pixel, pixel, pixel]));
|
||||
}
|
||||
|
||||
// 绘制 fireball（红色）- 使用 line_segment 的 points
|
||||
for fb in fireballs {
|
||||
let points: Vec<(f32, f32)> = fb.line_segment.points.iter()
|
||||
.map(|p| (p.x, p.y))
|
||||
.collect();
|
||||
draw_trajectory(&mut detection_img, &points, Rgb([255, 0, 0]));
|
||||
}
|
||||
|
||||
// 绘制 meteor（绿色）- 使用 centroids
|
||||
for mt in meteors {
|
||||
let points: Vec<(f32, f32)> = mt.centroids.iter()
|
||||
.map(|c| (c.x, c.y))
|
||||
.collect();
|
||||
draw_trajectory(&mut detection_img, &points, Rgb([0, 255, 0]));
|
||||
}
|
||||
|
||||
detection_img.save(output_dir.join(format!("{}_detections.png", prefix)))?;
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
/// 在图像上绘制轨迹（点连线）
|
||||
fn draw_trajectory(img: &mut image::RgbImage, points: &[(f32, f32)], color: image::Rgb<u8>) {
|
||||
let width = img.width() as i32;
|
||||
let height = img.height() as i32;
|
||||
|
||||
// 绘制点
|
||||
for &(x, y) in points {
|
||||
let px = x.round() as i32;
|
||||
let py = y.round() as i32;
|
||||
// 绘制 3x3 的点
|
||||
for dy in -1..=1 {
|
||||
for dx in -1..=1 {
|
||||
let nx = px + dx;
|
||||
let ny = py + dy;
|
||||
if nx >= 0 && nx < width && ny >= 0 && ny < height {
|
||||
img.put_pixel(nx as u32, ny as u32, color);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// 绘制连线（Bresenham）
|
||||
for i in 1..points.len() {
|
||||
let (x0, y0) = points[i - 1];
|
||||
let (x1, y1) = points[i];
|
||||
draw_line(img, x0 as i32, y0 as i32, x1 as i32, y1 as i32, color);
|
||||
}
|
||||
}
|
||||
|
||||
/// Bresenham 画线算法
|
||||
fn draw_line(img: &mut image::RgbImage, x0: i32, y0: i32, x1: i32, y1: i32, color: image::Rgb<u8>) {
|
||||
let width = img.width() as i32;
|
||||
let height = img.height() as i32;
|
||||
|
||||
let dx = (x1 - x0).abs();
|
||||
let dy = -(y1 - y0).abs();
|
||||
let sx = if x0 < x1 { 1 } else { -1 };
|
||||
let sy = if y0 < y1 { 1 } else { -1 };
|
||||
let mut err = dx + dy;
|
||||
let mut x = x0;
|
||||
let mut y = y0;
|
||||
|
||||
loop {
|
||||
if x >= 0 && x < width && y >= 0 && y < height {
|
||||
img.put_pixel(x as u32, y as u32, color);
|
||||
}
|
||||
if x == x1 && y == y1 {
|
||||
break;
|
||||
}
|
||||
let e2 = 2 * err;
|
||||
if e2 >= dy {
|
||||
err += dy;
|
||||
x += sx;
|
||||
}
|
||||
if e2 <= dx {
|
||||
err += dx;
|
||||
y += sy;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Test Vida four-frame meteor detection algorithm with a video file
|
||||
/// Uses FFmpeg pipe for zero-disk-IO streaming
|
||||
async fn test_vida(video_path: String, k1: f32, max_frames: Option<u32>) -> Result<()> {
|
||||
@ -844,20 +935,124 @@ async fn test_vida(video_path: String, k1: f32, max_frames: Option<u32>) -> Resu
|
||||
|
||||
// Step 2: Create FFmpeg pipe process for streaming raw frames
|
||||
println!("Starting FFmpeg pipe (zero disk I/O)...");
|
||||
let mut ffmpeg_args = vec![
|
||||
"-i".to_string(), normalized_path.clone(),
|
||||
|
||||
// Helper: Get platform-specific hardware acceleration option
|
||||
fn get_platform_hwaccel() -> Option<&'static str> {
|
||||
#[cfg(target_os = "macos")]
|
||||
{ Some("videotoolbox") }
|
||||
#[cfg(target_os = "linux")]
|
||||
{ Some("auto") }
|
||||
#[cfg(not(any(target_os = "macos", target_os = "linux")))]
|
||||
{ None }
|
||||
}
|
||||
|
||||
// Helper: Test if hardware decoding works for this video (with timeout)
|
||||
fn test_hwaccel_decode(video_path: &str, hwaccel: &str) -> bool {
|
||||
use std::time::{Duration, Instant};
|
||||
|
||||
// Spawn FFmpeg to decode 1 frame with hardware acceleration
|
||||
let mut child = match Command::new("ffmpeg")
|
||||
.args([
|
||||
"-hwaccel", hwaccel,
|
||||
"-i", video_path,
|
||||
"-frames:v", "1",
|
||||
"-f", "rawvideo",
|
||||
"-pix_fmt", "gray",
|
||||
"-"
|
||||
])
|
||||
.stdout(Stdio::piped())
|
||||
.stderr(Stdio::null())
|
||||
.spawn()
|
||||
{
|
||||
Ok(c) => c,
|
||||
Err(_) => return false,
|
||||
};
|
||||
|
||||
// Read with timeout (3 seconds max)
|
||||
let start = Instant::now();
|
||||
let timeout = Duration::from_secs(3);
|
||||
|
||||
// Try to read 1 frame (for 1920x1080 = ~2MB)
|
||||
// If we can read any data within timeout, hwaccel works
|
||||
if let Some(stdout) = child.stdout.take() {
|
||||
use std::io::Read;
|
||||
let mut reader = std::io::BufReader::new(stdout);
|
||||
let mut buf = [0u8; 1024]; // Just need to read some data
|
||||
|
||||
// Non-blocking check: try to read with a thread
|
||||
let (tx, rx) = std::sync::mpsc::channel();
|
||||
std::thread::spawn(move || {
|
||||
let result = reader.read(&mut buf);
|
||||
let _ = tx.send(result);
|
||||
});
|
||||
|
||||
// Wait for result with timeout
|
||||
match rx.recv_timeout(timeout) {
|
||||
Ok(Ok(n)) if n > 0 => {
|
||||
let _ = child.kill();
|
||||
return true;
|
||||
}
|
||||
_ => {
|
||||
let _ = child.kill();
|
||||
return false;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
let _ = child.kill();
|
||||
false
|
||||
}
|
||||
|
||||
// Helper: Build FFmpeg args
|
||||
fn build_ffmpeg_args(
|
||||
video_path: &str,
|
||||
hwaccel: Option<&str>,
|
||||
max_frames: Option<u32>,
|
||||
) -> Vec<String> {
|
||||
let mut args = Vec::new();
|
||||
|
||||
// Add hardware acceleration if specified
|
||||
if let Some(accel) = hwaccel {
|
||||
args.push("-hwaccel".to_string());
|
||||
args.push(accel.to_string());
|
||||
}
|
||||
|
||||
args.extend(vec![
|
||||
"-i".to_string(), video_path.to_string(),
|
||||
"-vf".to_string(), "format=gray".to_string(),
|
||||
"-f".to_string(), "rawvideo".to_string(),
|
||||
"-pix_fmt".to_string(), "gray".to_string(),
|
||||
];
|
||||
]);
|
||||
|
||||
// Add frame limit if specified
|
||||
if let Some(max) = max_frames {
|
||||
ffmpeg_args.push("-frames:v".to_string());
|
||||
ffmpeg_args.push(max.to_string());
|
||||
args.push("-frames:v".to_string());
|
||||
args.push(max.to_string());
|
||||
}
|
||||
|
||||
ffmpeg_args.push("-".to_string()); // Output to stdout
|
||||
args.push("-".to_string()); // Output to stdout
|
||||
args
|
||||
}
|
||||
|
||||
// Try hardware acceleration first, fallback to CPU if it fails
|
||||
let (hwaccel_used, ffmpeg_args) = if let Some(accel) = get_platform_hwaccel() {
|
||||
print!("Testing hardware acceleration ({})... ", accel);
|
||||
std::io::Write::flush(&mut std::io::stdout()).ok();
|
||||
if test_hwaccel_decode(&normalized_path, accel) {
|
||||
println!("OK");
|
||||
(Some(accel), build_ffmpeg_args(&normalized_path, Some(accel), max_frames))
|
||||
} else {
|
||||
println!("failed, using CPU decode");
|
||||
(None, build_ffmpeg_args(&normalized_path, None, max_frames))
|
||||
}
|
||||
} else {
|
||||
println!("No hardware acceleration available, using CPU decode");
|
||||
(None, build_ffmpeg_args(&normalized_path, None, max_frames))
|
||||
};
|
||||
|
||||
if hwaccel_used.is_some() {
|
||||
println!("Using hardware decoder: {}", hwaccel_used.unwrap());
|
||||
}
|
||||
|
||||
let mut child = Command::new("ffmpeg")
|
||||
.args(&ffmpeg_args)
|
||||
@ -867,7 +1062,9 @@ async fn test_vida(video_path: String, k1: f32, max_frames: Option<u32>) -> Resu
|
||||
|
||||
let stdout = child.stdout.take()
|
||||
.ok_or_else(|| anyhow::anyhow!("Failed to capture ffmpeg stdout"))?;
|
||||
let mut reader = BufReader::new(stdout);
|
||||
// Optimization: Use 2MB buffer (= 1 frame for 1920x1080) to reduce syscalls
|
||||
// Default 8KB buffer requires ~256 read() syscalls per frame
|
||||
let mut reader = BufReader::with_capacity(2 * 1024 * 1024, stdout);
|
||||
|
||||
// Create Vida controller with custom K1 threshold
|
||||
let mut config = VidaConfig::default();
|
||||
@ -887,15 +1084,43 @@ async fn test_vida(video_path: String, k1: f32, max_frames: Option<u32>) -> Resu
|
||||
|
||||
// Frame buffer for raw grayscale data
|
||||
let frame_size = (width * height) as usize;
|
||||
let mut frame_buffer = vec![0u8; frame_size];
|
||||
|
||||
println!("Processing frames (streaming)...");
|
||||
println!("Processing frames (streaming with async prefetch)...");
|
||||
println!();
|
||||
|
||||
// Step 3: Stream frames directly from FFmpeg pipe
|
||||
// Step 3: Async frame prefetch - producer/consumer pattern
|
||||
// Reader thread prefetches frames into a bounded channel while main thread processes
|
||||
use std::sync::mpsc;
|
||||
use std::thread;
|
||||
|
||||
let prefetch_buffer = 8; // Buffer 8 frames ahead
|
||||
let (tx, rx) = mpsc::sync_channel::<Vec<u8>>(prefetch_buffer);
|
||||
|
||||
// Spawn reader thread (producer)
|
||||
let reader_handle = thread::spawn(move || {
|
||||
loop {
|
||||
match reader.read_exact(&mut frame_buffer) {
|
||||
let mut buf = vec![0u8; frame_size];
|
||||
match reader.read_exact(&mut buf) {
|
||||
Ok(_) => {
|
||||
if tx.send(buf).is_err() {
|
||||
break; // Consumer dropped, exit
|
||||
}
|
||||
}
|
||||
Err(e) if e.kind() == std::io::ErrorKind::UnexpectedEof => break,
|
||||
Err(_) => break,
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
// Main loop (consumer) - processes frames while reader prefetches next ones
|
||||
while let Ok(frame_buffer) = rx.recv() {
|
||||
// Check max frames limit
|
||||
if let Some(max) = max_frames {
|
||||
if total_frames >= max as u64 {
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
// Process frame through Vida controller
|
||||
let timestamp = total_frames * 33333; // ~30fps in microseconds
|
||||
if let Some(result) = controller.process_frame(&frame_buffer, timestamp) {
|
||||
@ -948,7 +1173,7 @@ async fn test_vida(video_path: String, k1: f32, max_frames: Option<u32>) -> Resu
|
||||
let video_dir = std::path::Path::new(&video_path).parent().unwrap_or(std::path::Path::new("."));
|
||||
let output_dir = video_dir.join("detections");
|
||||
let prefix = format!("block{:04}", block_id);
|
||||
match save_ftp_frames(&output_dir, &result.accumulated_frame, &prefix) {
|
||||
match save_ftp_frames(&output_dir, &result.accumulated_frame, &prefix, &result.fireballs, &result.meteors) {
|
||||
Ok(_) => println!(" Saved FTP frames to: {}/", output_dir.display()),
|
||||
Err(e) => eprintln!(" Failed to save FTP frames: {}", e),
|
||||
}
|
||||
@ -966,13 +1191,10 @@ async fn test_vida(video_path: String, k1: f32, max_frames: Option<u32>) -> Resu
|
||||
eprint!(" Processed {} frames...\r", total_frames);
|
||||
}
|
||||
}
|
||||
Err(e) if e.kind() == std::io::ErrorKind::UnexpectedEof => break,
|
||||
Err(e) => {
|
||||
let _ = child.kill();
|
||||
anyhow::bail!("Error reading frame data: {}", e);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Wait for reader thread to finish
|
||||
drop(rx); // Drop receiver to signal reader thread to stop
|
||||
let _ = reader_handle.join();
|
||||
|
||||
// Wait for ffmpeg to finish
|
||||
let _ = child.wait();
|
||||
@ -1024,7 +1246,7 @@ async fn test_vida(video_path: String, k1: f32, max_frames: Option<u32>) -> Resu
|
||||
let video_dir = std::path::Path::new(&video_path).parent().unwrap_or(std::path::Path::new("."));
|
||||
let output_dir = video_dir.join("detections");
|
||||
let prefix = format!("block{:04}_final", block_times.len());
|
||||
match save_ftp_frames(&output_dir, &result.accumulated_frame, &prefix) {
|
||||
match save_ftp_frames(&output_dir, &result.accumulated_frame, &prefix, &result.fireballs, &result.meteors) {
|
||||
Ok(_) => println!(" Saved FTP frames to: {}/", output_dir.display()),
|
||||
Err(e) => eprintln!(" Failed to save FTP frames: {}", e),
|
||||
}
|
||||
|
||||
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Reference in New Issue
Block a user