immich-automated-selfie-tim.../src/pipeline/steps/crop_and_resize.rs
2026-02-15 20:59:45 +01:00

311 lines
11 KiB
Rust

//! Face cropping and resizing step.
//!
//! Crops the face region from the full image using the bounding box data,
//! then resizes it to the configured output size.
use crate::config::Config;
use crate::pipeline::crop_face_with_intermediate;
use crate::pipeline::debug_utils::draw_simple_text;
use crate::pipeline::{
computed_keys, BoundingBox, ComputedValue, PipelineContext, ProcessingStep, StepOutcome,
};
use async_trait::async_trait;
use image::{DynamicImage, Rgb};
/// Crops the face region from the full image and resizes it.
///
/// This transformer step extracts the face region using the bounding box
/// from Immich (with padding) and immediately resizes it to the configured
/// output size.
pub struct CropAndResizeStep;
#[async_trait]
impl ProcessingStep for CropAndResizeStep {
fn id(&self) -> &'static str {
"crop_and_resize"
}
fn name(&self) -> &'static str {
"Crop & Resize"
}
async fn execute(&self, mut ctx: PipelineContext, config: &Config) -> StepOutcome {
let image = match ctx.require_image("cropping and resizing") {
Ok(img) => img,
Err(e) => return StepOutcome::Error { ctx, error: e },
};
let output_size = config.processing.output.size;
let eye_distance = config.processing.alignment.eye_distance;
// Crop returns CropResult with cropped images and face rectangle in crop coordinates
match crop_face_with_intermediate(image, &ctx.face_data, output_size, eye_distance) {
Ok(crop_result) => {
// Store padding info for debug visualization
ctx.set_computed(
computed_keys::PADDING_EDGES,
ComputedValue::PaddingEdges(crop_result.padding_edges),
);
// Check if too much of the crop falls outside the image
let crop_config = &config.processing.crop;
if crop_config.enabled {
let padding_pct = crop_result.padding_fraction * 100.0;
if padding_pct > crop_config.max_padding_percent {
// Set image so debug_visualize can use it
ctx.image = Some(crop_result.resized);
return StepOutcome::Skip {
ctx,
reason: "excessive_padding".to_string(),
detail: Some(format!(
"padding {:.1}% exceeds max {:.1}%",
padding_pct, crop_config.max_padding_percent
)),
};
}
}
// Use the pre-resized image from the crop function
let cropped_size = crop_result.cropped.width();
ctx.image = Some(crop_result.resized);
// Scale the face rectangle to match the resized image coordinates
let scale = output_size as f32 / cropped_size as f32;
// Store scale for downstream steps (e.g. blur normalization)
ctx.set_computed(
computed_keys::CROP_SCALE,
ComputedValue::Float(scale),
);
let scaled_face_rect = BoundingBox {
x1: crop_result.face_rect.x1 * scale,
y1: crop_result.face_rect.y1 * scale,
x2: crop_result.face_rect.x2 * scale,
y2: crop_result.face_rect.y2 * scale,
};
// Store the scaled face rectangle for later steps
ctx.set_computed(
computed_keys::FACE_RECT,
ComputedValue::FaceRect(scaled_face_rect),
);
StepOutcome::Continue(ctx)
}
Err(e) => StepOutcome::Skip {
ctx,
reason: "crop_failed".to_string(),
detail: Some(e.to_string()),
},
}
}
fn debug_visualize(&self, ctx: &PipelineContext, config: &Config) -> Option<DynamicImage> {
let edges = ctx
.get_computed(computed_keys::PADDING_EDGES)
.and_then(|v| v.as_padding_edges())?;
// Don't save debug images for passed photos with zero padding
if edges.total_fraction() == 0.0 {
return None;
}
let image = ctx.image.as_ref()?;
let rgb = image.to_rgb8();
let (width, height) = (rgb.width(), rgb.height());
let mut debug_img = rgb.clone();
// Tint padded regions with a semi-transparent red overlay
let tint = |pixel: &Rgb<u8>| -> Rgb<u8> {
Rgb([
(pixel[0] as u16 / 2 + 127).min(255) as u8,
pixel[1] / 2,
pixel[2] / 2,
])
};
let left_px = (edges.left * width as f32).round() as u32;
let right_px = (edges.right * width as f32).round() as u32;
let top_px = (edges.top * height as f32).round() as u32;
let bottom_px = (edges.bottom * height as f32).round() as u32;
// Tint left edge
for y in 0..height {
for x in 0..left_px.min(width) {
debug_img.put_pixel(x, y, tint(debug_img.get_pixel(x, y)));
}
}
// Tint right edge
for y in 0..height {
for x in width.saturating_sub(right_px)..width {
debug_img.put_pixel(x, y, tint(debug_img.get_pixel(x, y)));
}
}
// Tint top edge (only the non-corner part to avoid double-tinting)
for y in 0..top_px.min(height) {
for x in left_px.min(width)..width.saturating_sub(right_px) {
debug_img.put_pixel(x, y, tint(debug_img.get_pixel(x, y)));
}
}
// Tint bottom edge (only the non-corner part)
for y in height.saturating_sub(bottom_px)..height {
for x in left_px.min(width)..width.saturating_sub(right_px) {
debug_img.put_pixel(x, y, tint(debug_img.get_pixel(x, y)));
}
}
// Draw padding percentage bar at the bottom
let total_pct = edges.total_fraction() * 100.0;
let max_pct = config.processing.crop.max_padding_percent;
let bar_height = 20u32;
let bar_y = height.saturating_sub(bar_height);
let bar_width = (width as f32 * 0.8) as u32;
let bar_x = (width - bar_width) / 2;
// Background
for y in bar_y..height {
for x in 0..width {
debug_img.put_pixel(x, y, Rgb([40, 40, 40]));
}
}
// Bar outline
let outline_y = bar_y + 4;
let outline_height = bar_height - 8;
for x in bar_x..bar_x + bar_width {
debug_img.put_pixel(x, outline_y, Rgb([200, 200, 200]));
debug_img.put_pixel(x, outline_y + outline_height - 1, Rgb([200, 200, 200]));
}
for y in outline_y..outline_y + outline_height {
debug_img.put_pixel(bar_x, y, Rgb([200, 200, 200]));
debug_img.put_pixel(bar_x + bar_width - 1, y, Rgb([200, 200, 200]));
}
// Fill bar (scale: 0-50% maps to full bar)
let max_scale = 50.0_f32;
let normalized = (total_pct / max_scale).clamp(0.0, 1.0);
let fill_width = ((bar_width - 4) as f32 * normalized) as u32;
let fill_color = if total_pct > max_pct {
Rgb([255, 80, 80]) // Red - exceeds threshold
} else if total_pct > max_pct * 0.7 {
Rgb([255, 200, 80]) // Yellow - approaching threshold
} else {
Rgb([80, 255, 80]) // Green - well within threshold
};
for y in (outline_y + 2)..(outline_y + outline_height - 2) {
for x in (bar_x + 2)..(bar_x + 2 + fill_width) {
if x < width {
debug_img.put_pixel(x, y, fill_color);
}
}
}
// Draw threshold marker on the bar
let threshold_x =
bar_x + 2 + ((bar_width - 4) as f32 * (max_pct / max_scale).clamp(0.0, 1.0)) as u32;
if threshold_x < bar_x + bar_width {
for y in outline_y..(outline_y + outline_height) {
debug_img.put_pixel(threshold_x, y, Rgb([255, 255, 255]));
}
}
// Text label
let text = format!("{:.1}%", total_pct);
draw_simple_text(&mut debug_img, 5, bar_y + 6, &text, Rgb([255, 255, 255]));
Some(DynamicImage::ImageRgb8(debug_img))
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::immich_api::FaceData;
use image::{DynamicImage, Rgb, RgbImage};
fn make_ctx_with_image(image: DynamicImage) -> PipelineContext {
// Face in the center of a 100x100 image
let face_data = FaceData {
bounding_box_x1: 30.0,
bounding_box_y1: 30.0,
bounding_box_x2: 70.0,
bounding_box_y2: 70.0,
image_width: 100,
image_height: 100,
};
PipelineContext::new("test".to_string(), "2024-01-01".to_string(), face_data)
.with_image(image)
}
fn create_test_image(width: u32, height: u32) -> DynamicImage {
let img = RgbImage::from_fn(width, height, |x, y| {
// Create a pattern so we can verify cropping
Rgb([(x % 256) as u8, (y % 256) as u8, 128])
});
DynamicImage::ImageRgb8(img)
}
#[tokio::test]
async fn test_crop_and_resize_success() {
let step = CropAndResizeStep;
let img = create_test_image(100, 100);
let ctx = make_ctx_with_image(img);
let mut config = Config::default();
config.processing.output.size = 512;
match step.execute(ctx, &config).await {
StepOutcome::Continue(new_ctx) => {
assert!(new_ctx.image.is_some());
let resized = new_ctx.image.unwrap();
// Should be resized to the configured output size
assert_eq!(resized.width(), 512);
assert_eq!(resized.height(), 512);
}
_ => panic!("Expected Continue"),
}
}
#[tokio::test]
async fn test_crop_and_resize_no_image() {
let step = CropAndResizeStep;
let face_data = FaceData {
bounding_box_x1: 30.0,
bounding_box_y1: 30.0,
bounding_box_x2: 70.0,
bounding_box_y2: 70.0,
image_width: 100,
image_height: 100,
};
let ctx = PipelineContext::new("test".to_string(), "2024-01-01".to_string(), face_data);
let config = Config::default();
match step.execute(ctx, &config).await {
StepOutcome::Error { error, .. } => {
assert!(error.contains("No image"));
}
_ => panic!("Expected Error"),
}
}
#[tokio::test]
async fn test_crop_and_resize_different_sizes() {
let step = CropAndResizeStep;
let img = create_test_image(200, 200);
let ctx = make_ctx_with_image(img);
let mut config = Config::default();
config.processing.output.size = 256;
match step.execute(ctx, &config).await {
StepOutcome::Continue(new_ctx) => {
let resized = new_ctx.image.unwrap();
assert_eq!(resized.width(), 256);
assert_eq!(resized.height(), 256);
}
_ => panic!("Expected Continue"),
}
}
}