add face feature extraction pipeline

face_pipeline/src/face_embedder.cpp

@@ -0,0 +1,59 @@
+#include "face_pipeline/face_embedder.h"
+
+#include <cmath>
+#include <stdexcept>
+
+#include <opencv2/objdetect/face.hpp>
+
+namespace face_pipeline {
+
+class SFaceEmbedder::Impl {
+public:
+    explicit Impl(const std::string& path)
+        : recognizer(cv::FaceRecognizerSF::create(path, "")) {
+        if (recognizer.empty()) throw std::runtime_error("failed to load SFace model: " + path);
+    }
+
+    cv::Ptr<cv::FaceRecognizerSF> recognizer;
+};
+
+SFaceEmbedder::SFaceEmbedder(const std::string& model_path)
+    : impl_(new Impl(model_path)) {
+    cv::Mat validation_input(112, 112, CV_8UC3, cv::Scalar(127, 127, 127));
+    extract(validation_input);
+}
+
+SFaceEmbedder::~SFaceEmbedder() = default;
+
+std::vector<float> SFaceEmbedder::extract(const cv::Mat& aligned_face) {
+    if (aligned_face.empty() || aligned_face.size() != cv::Size(112, 112) ||
+        aligned_face.type() != CV_8UC3) {
+        throw std::runtime_error("SFace input must be a 112x112 BGR image");
+    }
+
+    cv::Mat feature;
+    impl_->recognizer->feature(aligned_face, feature);
+    cv::Mat flattened = feature.reshape(1, 1);
+    if (flattened.type() != CV_32F || flattened.total() != 128) {
+        throw std::runtime_error("SFace output must contain 128 float values");
+    }
+
+    const float norm = static_cast<float>(cv::norm(flattened, cv::NORM_L2));
+    if (!std::isfinite(norm) || norm <= 1e-12f) {
+        throw std::runtime_error("SFace produced an invalid feature vector");
+    }
+    flattened /= norm;
+
+    const float* begin = flattened.ptr<float>();
+    std::vector<float> embedding(begin, begin + flattened.total());
+    for (float value : embedding) {
+        if (!std::isfinite(value)) throw std::runtime_error("SFace produced non-finite values");
+    }
+    return embedding;
+}
+
+std::string SFaceEmbedder::modelName() const {
+    return "opencv_sface_2021dec";
+}
+
+}  // namespace face_pipeline