52 lines
1.8 KiB
C++
52 lines
1.8 KiB
C++
#pragma once
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#include "config.hpp"
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#include "inference/face_detector.hpp"
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#include <algorithm>
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#include <memory>
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#include <string>
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// ── FaceDetectorFunc ──────────────────────────────────────────────────────────
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// KPN node: runs SCRFD-500MF to detect ALL faces in a frame.
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//
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// The inference backend (ONNX Runtime or raw TensorRT) is selected at compile
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// time; this node talks only to IFaceDetector via make_face_detector(cfg).
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struct FaceDetectorFunc {
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static constexpr std::string_view label() { return "face_detector"; }
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explicit FaceDetectorFunc(const Config& cfg)
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: detector_(make_face_detector(cfg))
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, max_faces_(cfg.max_faces)
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, min_face_px_(cfg.min_face_px)
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{}
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SceneFrame operator()(Frame f) {
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if (f.eof) return {std::move(f), {}};
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auto faces = detector_->detect(f.image);
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// Drop faces below minimum pixel size (too small for reliable ArcFace alignment)
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faces.erase(
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std::remove_if(faces.begin(), faces.end(), [&](const DetectedFace& d) {
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return d.bbox.width < min_face_px_ || d.bbox.height < min_face_px_;
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}),
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faces.end());
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// Sort largest-first so max_faces_ keeps the most informative detections
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std::sort(faces.begin(), faces.end(),
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[](const DetectedFace& a, const DetectedFace& b) {
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return a.bbox.area() > b.bbox.area();
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});
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if (static_cast<int>(faces.size()) > max_faces_)
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faces.resize(max_faces_);
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return {std::move(f), std::move(faces)};
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}
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private:
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std::unique_ptr<IFaceDetector> detector_;
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int max_faces_{10};
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float min_face_px_{40.f};
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};
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