dtourolle
e43ae10439
A Border choice beside the projection — crop to the picture, or fill it — that redraws the preview filled so the invented pixels are seen before they are confirmed (FR-MRG-1), greyed with the reason when the model is not there. The job fills at half the composite's resolution in a display-ish space (white balance, matrix, gamma; invertible) and samples the result back into the linear DNG wherever no frame reached; the sidecar's merge line says border filled and with which knobs. Experimental because the fill is right in thin borders and wrong in deep corners, where the model's Places2 prior puts clouds in sky and water under grass; so its six knobs — working scale, edge erosion, coarse pass, band width, mirror depth, seam feather — are sliders under the choice, each committing a redraw, until the defaults are right.
102 lines
4.0 KiB
Rust
102 lines
4.0 KiB
Rust
//! The app's side of `dr-inference-engine` (docs/inference.md §8).
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//!
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//! What lives here is what only the app knows: where the runtime file might
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//! be, where the disposable cache goes, which model files this device has,
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//! and how the engine's status becomes a line on the settings page. What
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//! runs the models does not.
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use std::path::PathBuf;
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use dr_inference_engine::{Form, Role, Status};
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use dr_types::FaceDetector;
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/// Start the engine: choose the runtime, probe in the background, compile
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/// engines for whatever this device turns out to have.
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///
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/// `runtime_dirs` is where the platform put `libonnxruntime`: an empty list
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/// is the tract build. Called once, after the models are on disk — on
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/// Android that is the end of `install_bundled_models`, since the probe
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/// fingerprints the model files and a probe before they land would be a
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/// probe of nothing.
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pub fn init(runtime_dirs: Vec<PathBuf>) {
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let dir = crate::library::shared_face_models_dir();
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let mut models: Vec<(Role, PathBuf)> = FaceDetector::ALL
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.iter()
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.map(|d| (Role::Detector, dir.join(d.file_name())))
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.collect();
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models.push((Role::Embedder, dir.join("arcface_mbf_b1.onnx")));
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models.push((Role::Scene, dir.join("yolo26s-sem-ade20k.onnx")));
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models.push((Role::Landmarks, dir.join(crate::library::LANDMARK_MODEL)));
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models.push((Role::EyeClassifier, dir.join(crate::library::EYE_MODEL)));
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models.push((
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Role::EyeClassifier,
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dir.join(crate::library::SUNGLASSES_MODEL),
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));
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if let Some(p) = crate::library::inpaint_model() {
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models.push((Role::Inpainter, p));
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}
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models.retain(|(_, p)| p.is_file());
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dr_inference_engine::init(dr_inference_engine::Config {
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runtime_dirs,
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cache_dir: crate::library::inference_cache_dir(),
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models,
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embedded: {
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let [landscape, portrait] = dr_pano::xfeat::embedded_model_bytes();
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vec![
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(Role::Segmenter, dr_segment::embedded_model_bytes()),
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(Role::Keypoints, landscape),
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(Role::Keypoints, portrait),
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]
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},
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ceiling: None,
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threads: 0,
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decay: std::time::Duration::ZERO,
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});
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// A low-memory signal drops every session nobody is mid-run with; the
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// next use loads again. Same tier as the GPU caches: rebuilt from data
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// the process still holds, and on a mobile GPU or NPU the largest pool.
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crate::memory::evict_at(crate::memory::Tier::Gpu, dr_inference_engine::release_all);
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}
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/// Which form the current backend loads `detector` in, given the files on
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/// this device — the fact `faces.model_id` has to carry (§7).
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///
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/// Reads the shared directory only. An account-private model directory can
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/// override the file `library::face_models` loads, but not which form the
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/// backend wants, and the int8 sibling is something a packager ships, not
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/// something a user drops in.
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pub fn detector_form(detector: FaceDetector) -> Form {
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let canonical = crate::library::shared_face_models_dir().join(detector.file_name());
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dr_inference_engine::resolve_model(Role::Detector, &canonical).1
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}
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/// The `faces.model_id` this device indexes under with `detector`.
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pub fn model_id(detector: FaceDetector) -> &'static str {
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match detector_form(detector) {
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Form::F32 => detector.model_id(),
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Form::Int8 => detector.model_id_int8(),
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}
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}
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/// The two lines the About panel shows: what is running the models, and
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/// why or how far along.
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pub fn about_lines() -> (String, String) {
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let status: Status = dr_inference_engine::status();
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let line = status.line();
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let detail = if status.probing {
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"Checking what this device can run the models on…".to_string()
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} else if status.engines.1 > 0 && status.engines.0 < status.engines.1 {
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format!(
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"Preparing {} engines · {} of {}",
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status.rung.label(),
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status.engines.0,
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status.engines.1
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)
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} else {
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status.reason
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};
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(line, detail)
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}
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