immich-automated-selfie-tim.../src/pipeline/steps/head_pose.rs

298 lines
10 KiB
Rust

//! Head pose estimation step.
//!
//! Uses the DMHead ONNX model to estimate head pose (yaw, pitch, roll) and
//! filter out non-front-facing faces.
use crate::config::Config;
use crate::models::DMHeadModel;
use crate::pipeline::{computed_keys, draw_simple_text, ComputedValue, PipelineContext, ProcessingStep, StepOutcome};
use async_trait::async_trait;
use image::{DynamicImage, GenericImageView, Rgb, RgbImage};
/// Estimates head pose and filters non-frontal faces.
///
/// This step:
/// 1. Runs DMHead inference on the cropped face image
/// 2. Stores the HeadPose result in ctx.computed["head_pose"]
/// 3. Skips if any angle exceeds configured thresholds
pub struct HeadPoseStep;
#[async_trait]
impl ProcessingStep for HeadPoseStep {
fn id(&self) -> &'static str {
"head_pose"
}
fn name(&self) -> &'static str {
"Head Pose"
}
async fn execute(&self, mut ctx: PipelineContext, config: &Config) -> StepOutcome {
// Skip if head pose filtering is disabled
if !config.processing.head_pose.enabled {
return StepOutcome::Continue(ctx);
}
let image = match ctx.require_image("head pose estimation") {
Ok(img) => img,
Err(e) => return StepOutcome::Error { ctx, error: e },
};
// Load the DMHead model
let model = match DMHeadModel::global() {
Ok(m) => m,
Err(e) => {
// If model isn't available, skip this step with a warning
tracing::warn!("DMHead model not available, skipping head pose check: {}", e);
return StepOutcome::Continue(ctx);
}
};
// Extract a tighter face crop if we have the face rectangle
// DMHead works better with tight face crops centered on the face
let face_image: DynamicImage = if let Some(face_rect) = ctx
.get_computed(computed_keys::FACE_RECT)
.and_then(|v| v.as_face_rect())
{
// Use the face rectangle to extract a tighter crop
let (img_w, img_h) = image.dimensions();
let x = (face_rect.x1 as u32).min(img_w.saturating_sub(1));
let y = (face_rect.y1 as u32).min(img_h.saturating_sub(1));
let w = ((face_rect.x2 - face_rect.x1) as u32).min(img_w - x);
let h = ((face_rect.y2 - face_rect.y1) as u32).min(img_h - y);
if w > 10 && h > 10 {
// Add a small margin around the face for better model performance
let margin = (w.max(h) / 4).min(20);
let x = x.saturating_sub(margin);
let y = y.saturating_sub(margin);
let w = (w + margin * 2).min(img_w - x);
let h = (h + margin * 2).min(img_h - y);
image.crop_imm(x, y, w, h)
} else {
// Face rect too small, use full image
image.clone()
}
} else {
// No face rect available, use full image
image.clone()
};
// Run inference on the face crop
let pose = match model.estimate(&face_image) {
Ok(p) => p,
Err(e) => {
return StepOutcome::Error {
ctx,
error: format!("Head pose estimation failed: {}", e),
};
}
};
// Store pose in computed values
ctx.set_computed(computed_keys::HEAD_POSE, ComputedValue::HeadPose(pose));
// Check against thresholds
let head_pose_config = &config.processing.head_pose;
tracing::debug!(
"Head pose detected: yaw={:.1}°, pitch={:.1}°, roll={:.1}°",
pose.yaw,
pose.pitch,
pose.roll
);
if pose.yaw.abs() > head_pose_config.max_yaw {
return StepOutcome::Skip {
ctx,
reason: "head_turned".to_string(),
detail: Some(format!(
"Yaw {:.1}° exceeds threshold {:.1}°",
pose.yaw, head_pose_config.max_yaw
)),
};
}
if pose.pitch.abs() > head_pose_config.max_pitch {
return StepOutcome::Skip {
ctx,
reason: "head_turned".to_string(),
detail: Some(format!(
"Pitch {:.1}° exceeds threshold {:.1}°",
pose.pitch, head_pose_config.max_pitch
)),
};
}
if pose.roll.abs() > head_pose_config.max_roll {
return StepOutcome::Skip {
ctx,
reason: "head_turned".to_string(),
detail: Some(format!(
"Roll {:.1}° exceeds threshold {:.1}°",
pose.roll, head_pose_config.max_roll
)),
};
}
StepOutcome::Continue(ctx)
}
fn debug_visualize(&self, ctx: &PipelineContext, _config: &Config) -> Option<DynamicImage> {
// Get head pose from computed values
let pose = ctx
.get_computed(computed_keys::HEAD_POSE)
.and_then(|v| v.as_head_pose())?;
// Get the current image to draw on
let image = ctx.image.as_ref()?;
let rgb = image.to_rgb8();
let (width, height) = (rgb.width(), rgb.height());
// Create a copy for visualization
let mut debug_img = rgb.clone();
// Draw a center crosshair
let cx = width / 2;
let cy = height / 2;
let crosshair_size = 20u32;
// Horizontal line
for x in cx.saturating_sub(crosshair_size)..=(cx + crosshair_size).min(width - 1) {
debug_img.put_pixel(x, cy, Rgb([0, 255, 0]));
}
// Vertical line
for y in cy.saturating_sub(crosshair_size)..=(cy + crosshair_size).min(height - 1) {
debug_img.put_pixel(cx, y, Rgb([0, 255, 0]));
}
// Draw pose direction arrow from center
// Yaw rotates left/right, pitch rotates up/down
let arrow_len = 40.0_f32;
let yaw_rad = pose.yaw.to_radians();
let pitch_rad = pose.pitch.to_radians();
// Arrow endpoint based on yaw and pitch
let dx = (yaw_rad.sin() * arrow_len) as i32;
let dy = (-pitch_rad.sin() * arrow_len) as i32; // Negative because y increases downward
let ex = (cx as i32 + dx).clamp(0, width as i32 - 1) as u32;
let ey = (cy as i32 + dy).clamp(0, height as i32 - 1) as u32;
// Draw arrow line using Bresenham's algorithm
draw_line(&mut debug_img, cx as i32, cy as i32, ex as i32, ey as i32, Rgb([255, 0, 0]));
// Draw roll indicator as a tilted line through center
let roll_rad = pose.roll.to_radians();
let roll_len = 30.0_f32;
let rx1 = (cx as f32 - roll_rad.cos() * roll_len) as u32;
let ry1 = (cy as f32 - roll_rad.sin() * roll_len) as u32;
let rx2 = (cx as f32 + roll_rad.cos() * roll_len) as u32;
let ry2 = (cy as f32 + roll_rad.sin() * roll_len) as u32;
draw_line(&mut debug_img, rx1 as i32, ry1 as i32, rx2 as i32, ry2 as i32, Rgb([0, 255, 255]));
// Draw text background bar at bottom for pose values
let bar_height = 20u32;
for y in height.saturating_sub(bar_height)..height {
for x in 0..width {
debug_img.put_pixel(x, y, Rgb([0, 0, 0]));
}
}
// Draw simple text representation of values using block characters
// Format: Y:-20 P:+29 R:-21
let text = format!(
"Y:{:+.0} P:{:+.0} R:{:+.0}",
pose.yaw, pose.pitch, pose.roll
);
draw_simple_text(&mut debug_img, 5, height - bar_height + 4, &text, Rgb([255, 255, 255]));
Some(DynamicImage::ImageRgb8(debug_img))
}
}
/// Draw a line using Bresenham's algorithm.
fn draw_line(img: &mut RgbImage, x0: i32, y0: i32, x1: i32, y1: i32, color: Rgb<u8>) {
let (width, height) = (img.width() as i32, 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;
}
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::immich_api::FaceData;
use image::RgbImage;
fn make_test_ctx() -> PipelineContext {
let face_data = FaceData {
bounding_box_x1: 0.0,
bounding_box_y1: 0.0,
bounding_box_x2: 100.0,
bounding_box_y2: 100.0,
image_width: 100,
image_height: 100,
};
PipelineContext::new("test".to_string(), "2024-01-01".to_string(), face_data)
}
#[tokio::test]
async fn test_disabled_skips_check() {
let step = HeadPoseStep;
let ctx = make_test_ctx();
let mut config = Config::default();
config.processing.head_pose.enabled = false;
// Create a dummy image
let img = DynamicImage::ImageRgb8(RgbImage::new(100, 100));
let ctx = ctx.with_image(img);
match step.execute(ctx, &config).await {
StepOutcome::Continue(_) => {} // Expected
other => panic!("Expected Continue when disabled, got {:?}", other),
}
}
#[tokio::test]
async fn test_no_image_error() {
let step = HeadPoseStep;
let ctx = make_test_ctx();
let mut config = Config::default();
config.processing.head_pose.enabled = true;
match step.execute(ctx, &config).await {
StepOutcome::Error { error, .. } => {
assert!(error.contains("No image"));
}
other => panic!("Expected Error, got {:?}", other),
}
}
}