Add person dataset assembler, restructure repo

SmartCrop/facerecognizer.cpp

@@ -0,0 +1,136 @@
+#include "facerecognizer.h"
+#include <filesystem>
+
+#define INCBIN_PREFIX r
+#include "incbin.h"
+
+INCBIN(defaultRecognizer, WEIGHT_DIR "/face_recognition_sface_2021dec.onnx");
+INCBIN(defaultDetector, WEIGHT_DIR "/face_detection_yunet_2023mar.onnx");
+
+#include <opencv2/dnn/dnn.hpp>
+#include <opencv2/core.hpp>
+#include <opencv2/highgui.hpp>
+#include <fstream>
+
+#include "log.h"
+
+static const std::vector<unsigned char> onnx((unsigned char*)rdefaultDetectorData, ((unsigned char*)rdefaultDetectorData)+rdefaultDetectorSize);
+
+FaceRecognizer::FaceRecognizer(std::filesystem::path recognizerPath, const std::filesystem::path& detectorPath, const std::vector<cv::Mat>& referances)
+{
+	if(detectorPath.empty())
+	{
+		Log(Log::INFO)<<"Using builtin face detection model";
+
+		detector = cv::FaceDetectorYN::create("onnx", onnx, std::vector<unsigned char>(), {320, 320}, 0.6, 0.3, 5000, cv::dnn::Backend::DNN_BACKEND_OPENCV, cv::dnn::Target::DNN_TARGET_CPU);
+		if(!detector)
+			throw LoadException("Unable to load detector network from built in file");
+	}
+	else
+	{
+		detector = cv::FaceDetectorYN::create(detectorPath, "", {320, 320}, 0.6, 0.3, 5000, cv::dnn::Backend::DNN_BACKEND_OPENCV, cv::dnn::Target::DNN_TARGET_CPU);
+		if(!detector)
+			throw LoadException("Unable to load detector network from "+detectorPath.string());
+	}
+
+	bool defaultNetwork = recognizerPath.empty();
+
+	if(defaultNetwork)
+	{
+		Log(Log::INFO)<<"Using builtin face recognition model";
+		recognizerPath = cv::tempfile("onnx");
+		std::ofstream file(recognizerPath);
+		if(!file.is_open())
+			throw LoadException("Unable open temporary file at "+recognizerPath.string());
+		Log(Log::DEBUG)<<"Using "<<recognizerPath<<" as temporary file for onnx recongnition network";
+		file.write(reinterpret_cast<const char*>(rdefaultRecognizerData), rdefaultRecognizerSize);
+		file.close();
+	}
+
+	recognizer = cv::FaceRecognizerSF::create(recognizerPath.string(), "", cv::dnn::Backend::DNN_BACKEND_OPENCV, cv::dnn::Target::DNN_TARGET_CPU);
+
+	if(defaultNetwork)
+		std::filesystem::remove(recognizerPath);
+
+	if(!recognizer)
+		throw LoadException("Unable to load recognizer network from "+recognizerPath.string());
+
+	addReferances(referances);
+}
+
+cv::Mat FaceRecognizer::detectFaces(const cv::Mat& input)
+{
+	detector->setInputSize(input.size());
+	cv::Mat faces;
+	detector->detect(input, faces);
+	return faces;
+}
+
+bool FaceRecognizer::addReferances(const std::vector<cv::Mat>& referances)
+{
+	bool ret = false;
+	for(const cv::Mat& image : referances)
+	{
+		cv::Mat faces = detectFaces(image);
+		assert(faces.cols == 15);
+		if(faces.empty())
+		{
+			Log(Log::WARN)<<"A referance image provided dose not contian any face";
+			continue;
+		}
+		if(faces.rows > 1)
+			Log(Log::WARN)<<"A referance image provided contains more than one face, only the first detected face will be considered";
+		cv::Mat cropedImage;
+		recognizer->alignCrop(image, faces.row(0), cropedImage);
+		cv::Mat features;
+		recognizer->feature(cropedImage, features);
+		referanceFeatures.push_back(features.clone());
+		ret = true;
+	}
+
+	return ret;
+}
+
+void FaceRecognizer::setThreshold(double threasholdIn)
+{
+	threshold = threasholdIn;
+}
+
+double FaceRecognizer::getThreshold()
+{
+	return threshold;
+}
+
+void FaceRecognizer::clearReferances()
+{
+	referanceFeatures.clear();
+}
+
+std::pair<int, double> FaceRecognizer::isMatch(const cv::Mat& input, bool alone)
+{
+	cv::Mat faces = detectFaces(input);
+
+	if(alone && faces.rows > 1)
+		return {-2, 0};
+
+	std::pair<int, double> bestMatch = {-1, 0};
+
+	for(int i = 0; i < faces.rows; ++i)
+	{
+		cv::Mat face;
+		recognizer->alignCrop(input, faces.row(0), face);
+		cv::Mat features;
+		recognizer->feature(face, features);
+		features = features.clone();
+		for(size_t referanceIndex = 0; referanceIndex < referanceFeatures.size(); ++referanceIndex)
+		{
+			double score = recognizer->match(referanceFeatures[referanceIndex], features, cv::FaceRecognizerSF::FR_COSINE);
+			if(score > threshold && score > bestMatch.second)
+			{
+				bestMatch = {referanceIndex, score};
+			}
+		}
+	}
+
+	return bestMatch;
+}