mirror of
https://github.com/yakhyo/uniface.git
synced 2026-05-14 12:17:51 +00:00
114 lines
4.1 KiB
C++
114 lines
4.1 KiB
C++
#include <iomanip>
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#include <iostream>
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#include <opencv2/highgui.hpp>
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#include <opencv2/imgproc.hpp>
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#include <uniface/uniface.hpp>
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int main(int argc, char** argv) {
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if (argc < 3) {
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std::cout << "Usage: " << argv[0]
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<< " <detector_model> <image_path> [recognizer_model] [landmark_model]"
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<< std::endl;
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std::cout << "\nAnalyzes faces in an image using available models." << std::endl;
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std::cout << " - detector_model: Required. Path to face detector ONNX model." << std::endl;
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std::cout << " - recognizer_model: Optional. Path to face recognizer ONNX model."
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<< std::endl;
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std::cout << " - landmark_model: Optional. Path to 106-point landmark ONNX model."
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<< std::endl;
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return 1;
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}
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const std::string detector_path = argv[1];
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const std::string image_path = argv[2];
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const std::string recognizer_path = (argc > 3) ? argv[3] : "";
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const std::string landmark_path = (argc > 4) ? argv[4] : "";
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try {
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// Create analyzer and load components
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uniface::FaceAnalyzer analyzer;
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std::cout << "Loading detector: " << detector_path << std::endl;
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analyzer.loadDetector(detector_path);
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if (!recognizer_path.empty()) {
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std::cout << "Loading recognizer: " << recognizer_path << std::endl;
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analyzer.loadRecognizer(recognizer_path);
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}
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if (!landmark_path.empty()) {
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std::cout << "Loading landmarker: " << landmark_path << std::endl;
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analyzer.loadLandmarker(landmark_path);
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}
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// Load image
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cv::Mat image = cv::imread(image_path);
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if (image.empty()) {
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std::cerr << "Failed to load image: " << image_path << std::endl;
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return 1;
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}
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std::cout << "\nAnalyzing image..." << std::endl;
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// Analyze faces
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auto results = analyzer.analyze(image);
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std::cout << "Found " << results.size() << " face(s)\n" << std::endl;
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// Process each face
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for (size_t i = 0; i < results.size(); ++i) {
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const auto& result = results[i];
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std::cout << "Face " << (i + 1) << ":" << std::endl;
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std::cout << " BBox: [" << result.face.bbox.x << ", " << result.face.bbox.y << ", "
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<< result.face.bbox.width << ", " << result.face.bbox.height << "]"
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<< std::endl;
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std::cout << std::fixed << std::setprecision(3);
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std::cout << " Confidence: " << result.face.confidence << std::endl;
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// Draw bounding box
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cv::rectangle(image, result.face.bbox, cv::Scalar(0, 255, 0), 2);
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// Draw 5-point landmarks from detector
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for (const auto& pt : result.face.landmarks) {
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cv::circle(image, pt, 3, cv::Scalar(0, 0, 255), -1);
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}
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// If 106-point landmarks available
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if (result.landmarks) {
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std::cout << " Landmarks: 106 points detected" << std::endl;
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for (const auto& pt : result.landmarks->points) {
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cv::circle(image, pt, 1, cv::Scalar(0, 255, 255), -1);
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}
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}
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// If embedding available
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if (result.embedding) {
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// Show first few values of embedding
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std::cout << " Embedding: [";
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for (size_t j = 0; j < 5; ++j) {
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std::cout << (*result.embedding)[j];
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if (j < 4)
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std::cout << ", ";
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}
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std::cout << ", ... ] (512-dim)" << std::endl;
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}
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std::cout << std::endl;
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}
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// Save result
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cv::imwrite("analyzer_result.jpg", image);
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std::cout << "Saved result to analyzer_result.jpg" << std::endl;
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} catch (const cv::Exception& e) {
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std::cerr << "OpenCV Error: " << e.what() << std::endl;
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return 1;
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} catch (const std::exception& e) {
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std::cerr << "Error: " << e.what() << std::endl;
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return 1;
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}
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return 0;
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}
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