Open Source Computer Vision Library https://opencv.org/
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Merge pull request #20422 from fengyuentau:dnn_face Add DNN-based face detection and face recognition into modules/objdetect * Add DNN-based face detector impl and interface * Add a sample for DNN-based face detector * add recog * add notes * move samples from samples/cpp to samples/dnn * add documentation for dnn_face * add set/get methods for input size, nms & score threshold and topk * remove the DNN prefix from the face detector and face recognizer * remove default values in the constructor of impl * regenerate priors after setting input size * two filenames for readnet * Update face.hpp * Update face_recognize.cpp * Update face_match.cpp * Update face.hpp * Update face_recognize.cpp * Update face_match.cpp * Update face_recognize.cpp * Update dnn_face.markdown * Update dnn_face.markdown * Update face.hpp * Update dnn_face.markdown * add regression test for face detection * remove underscore prefix; fix warnings * add reference & acknowledgement for face detection * Update dnn_face.markdown * Update dnn_face.markdown * Update ts.hpp * Update test_face.cpp * Update face_match.cpp * fix a compile error for python interface; add python examples for face detection and recognition * Major changes for Vadim's comments: * Replace class name FaceDetector with FaceDetectorYN in related failes * Declare local mat before loop in modules/objdetect/src/face_detect.cpp * Make input image and save flag optional in samples/dnn/face_detect(.cpp, .py) * Add camera support in samples/dnn/face_detect(.cpp, .py) * correct file paths for regression test * fix convertion warnings; remove extra spaces * update face_recog * Update dnn_face.markdown * Fix warnings and errors for the default CI reports: * Remove trailing white spaces and extra new lines. * Fix convertion warnings for windows and iOS. * Add braces around initialization of subobjects. * Fix warnings and errors for the default CI systems: * Add prefix 'FR_' for each value name in enum DisType to solve the redefinition error for iOS compilation; Modify other code accordingly * Add bookmark '#tutorial_dnn_face' to solve warnings from doxygen * Correct documentations to solve warnings from doxygen * update FaceRecognizerSF * Fix the error for CI to find ONNX models correctly * add suffix f to float assignments * add backend & target options for initializing face recognizer * add checkeq for checking input size and preset size * update test and threshold * changes in response to alalek's comments: * fix typos in samples/dnn/face_match.py * import numpy before importing cv2 * add documentation to .setInputSize() * remove extra include in face_recognize.cpp * fix some bugs * Update dnn_face.markdown * update thresholds; remove useless code * add time suffix to YuNet filename in test * objdetect: update test code
3 years ago
// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
#include "opencv2/dnn.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>
#include "opencv2/objdetect.hpp"
using namespace cv;
using namespace std;
int main(int argc, char ** argv)
{
if (argc != 5)
{
std::cerr << "Usage " << argv[0] << ": "
<< "<det_onnx_path> "
<< "<reg_onnx_path> "
<< "<image1>"
<< "<image2>\n";
return -1;
}
String det_onnx_path = argv[1];
String reg_onnx_path = argv[2];
String image1_path = argv[3];
String image2_path = argv[4];
std::cout<<image1_path<<" "<<image2_path<<std::endl;
Mat image1 = imread(image1_path);
Mat image2 = imread(image2_path);
float score_thresh = 0.9f;
float nms_thresh = 0.3f;
double cosine_similar_thresh = 0.363;
double l2norm_similar_thresh = 1.128;
int top_k = 5000;
// Initialize FaceDetector
Ptr<FaceDetectorYN> faceDetector;
faceDetector = FaceDetectorYN::create(det_onnx_path, "", image1.size(), score_thresh, nms_thresh, top_k);
Mat faces_1;
faceDetector->detect(image1, faces_1);
if (faces_1.rows < 1)
{
std::cerr << "Cannot find a face in " << image1_path << "\n";
return -1;
}
faceDetector = FaceDetectorYN::create(det_onnx_path, "", image2.size(), score_thresh, nms_thresh, top_k);
Mat faces_2;
faceDetector->detect(image2, faces_2);
if (faces_2.rows < 1)
{
std::cerr << "Cannot find a face in " << image2_path << "\n";
return -1;
}
// Initialize FaceRecognizerSF
Ptr<FaceRecognizerSF> faceRecognizer = FaceRecognizerSF::create(reg_onnx_path, "");
Mat aligned_face1, aligned_face2;
faceRecognizer->alignCrop(image1, faces_1.row(0), aligned_face1);
faceRecognizer->alignCrop(image2, faces_2.row(0), aligned_face2);
Mat feature1, feature2;
faceRecognizer->feature(aligned_face1, feature1);
feature1 = feature1.clone();
faceRecognizer->feature(aligned_face2, feature2);
feature2 = feature2.clone();
double cos_score = faceRecognizer->match(feature1, feature2, FaceRecognizerSF::DisType::FR_COSINE);
double L2_score = faceRecognizer->match(feature1, feature2, FaceRecognizerSF::DisType::FR_NORM_L2);
if(cos_score >= cosine_similar_thresh)
{
std::cout << "They have the same identity;";
}
else
{
std::cout << "They have different identities;";
}
std::cout << " Cosine Similarity: " << cos_score << ", threshold: " << cosine_similar_thresh << ". (higher value means higher similarity, max 1.0)\n";
if(L2_score <= l2norm_similar_thresh)
{
std::cout << "They have the same identity;";
}
else
{
std::cout << "They have different identities.";
}
std::cout << " NormL2 Distance: " << L2_score << ", threshold: " << l2norm_similar_thresh << ". (lower value means higher similarity, min 0.0)\n";
return 0;
}