feat: Add landmark and recognition models to uniface-cpp

uniface-cpp/examples/recognize.cpp

@@ -0,0 +1,81 @@
+#include <iomanip>
+#include <iostream>
+
+#include <opencv2/highgui.hpp>
+#include <opencv2/imgproc.hpp>
+#include <uniface/uniface.hpp>
+
+int main(int argc, char** argv) {
+    if (argc < 5) {
+        std::cout << "Usage: " << argv[0]
+                  << " <detector_model> <recognizer_model> <image1> <image2>" << std::endl;
+        std::cout << "\nCompares faces from two images and outputs similarity score." << std::endl;
+        return 1;
+    }
+
+    const std::string detector_path = argv[1];
+    const std::string recognizer_path = argv[2];
+    const std::string image1_path = argv[3];
+    const std::string image2_path = argv[4];
+
+    try {
+        // Load models
+        uniface::RetinaFace detector(detector_path);
+        uniface::ArcFace recognizer(recognizer_path);
+
+        // Load images
+        cv::Mat image1 = cv::imread(image1_path);
+        cv::Mat image2 = cv::imread(image2_path);
+
+        if (image1.empty()) {
+            std::cerr << "Failed to load image: " << image1_path << std::endl;
+            return 1;
+        }
+        if (image2.empty()) {
+            std::cerr << "Failed to load image: " << image2_path << std::endl;
+            return 1;
+        }
+
+        // Detect faces
+        auto faces1 = detector.detect(image1);
+        auto faces2 = detector.detect(image2);
+
+        if (faces1.empty()) {
+            std::cerr << "No face detected in image1" << std::endl;
+            return 1;
+        }
+        if (faces2.empty()) {
+            std::cerr << "No face detected in image2" << std::endl;
+            return 1;
+        }
+
+        std::cout << "Detected " << faces1.size() << " face(s) in image1" << std::endl;
+        std::cout << "Detected " << faces2.size() << " face(s) in image2" << std::endl;
+
+        // Get embeddings for first face in each image
+        auto embedding1 = recognizer.getNormalizedEmbedding(image1, faces1[0].landmarks);
+        auto embedding2 = recognizer.getNormalizedEmbedding(image2, faces2[0].landmarks);
+
+        // Compute similarity
+        float similarity = uniface::cosineSimilarity(embedding1, embedding2);
+
+        std::cout << std::fixed << std::setprecision(4);
+        std::cout << "\nCosine Similarity: " << similarity << std::endl;
+
+        // Interpretation
+        if (similarity > 0.4f) {
+            std::cout << "Result: Same person (similarity > 0.4)" << std::endl;
+        } else {
+            std::cout << "Result: Different persons (similarity <= 0.4)" << std::endl;
+        }
+
+    } catch (const cv::Exception& e) {
+        std::cerr << "OpenCV Error: " << e.what() << std::endl;
+        return 1;
+    } catch (const std::exception& e) {
+        std::cerr << "Error: " << e.what() << std::endl;
+        return 1;
+    }
+
+    return 0;
+}