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34d359fe03
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
104 lines
3.1 KiB
C++
104 lines
3.1 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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#include "opencv2/dnn.hpp"
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#include "opencv2/imgproc.hpp"
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#include "opencv2/highgui.hpp"
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#include <iostream>
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#include "opencv2/objdetect.hpp"
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using namespace cv;
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using namespace std;
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int main(int argc, char ** argv)
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{
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if (argc != 5)
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{
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std::cerr << "Usage " << argv[0] << ": "
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<< "<det_onnx_path> "
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<< "<reg_onnx_path> "
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<< "<image1>"
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<< "<image2>\n";
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return -1;
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}
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String det_onnx_path = argv[1];
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String reg_onnx_path = argv[2];
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String image1_path = argv[3];
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String image2_path = argv[4];
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std::cout<<image1_path<<" "<<image2_path<<std::endl;
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Mat image1 = imread(image1_path);
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Mat image2 = imread(image2_path);
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float score_thresh = 0.9f;
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float nms_thresh = 0.3f;
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double cosine_similar_thresh = 0.363;
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double l2norm_similar_thresh = 1.128;
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int top_k = 5000;
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// Initialize FaceDetector
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Ptr<FaceDetectorYN> faceDetector;
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faceDetector = FaceDetectorYN::create(det_onnx_path, "", image1.size(), score_thresh, nms_thresh, top_k);
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Mat faces_1;
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faceDetector->detect(image1, faces_1);
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if (faces_1.rows < 1)
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{
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std::cerr << "Cannot find a face in " << image1_path << "\n";
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return -1;
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}
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faceDetector = FaceDetectorYN::create(det_onnx_path, "", image2.size(), score_thresh, nms_thresh, top_k);
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Mat faces_2;
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faceDetector->detect(image2, faces_2);
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if (faces_2.rows < 1)
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{
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std::cerr << "Cannot find a face in " << image2_path << "\n";
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return -1;
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}
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// Initialize FaceRecognizerSF
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Ptr<FaceRecognizerSF> faceRecognizer = FaceRecognizerSF::create(reg_onnx_path, "");
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Mat aligned_face1, aligned_face2;
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faceRecognizer->alignCrop(image1, faces_1.row(0), aligned_face1);
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faceRecognizer->alignCrop(image2, faces_2.row(0), aligned_face2);
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Mat feature1, feature2;
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faceRecognizer->feature(aligned_face1, feature1);
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feature1 = feature1.clone();
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faceRecognizer->feature(aligned_face2, feature2);
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feature2 = feature2.clone();
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double cos_score = faceRecognizer->match(feature1, feature2, FaceRecognizerSF::DisType::FR_COSINE);
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double L2_score = faceRecognizer->match(feature1, feature2, FaceRecognizerSF::DisType::FR_NORM_L2);
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if(cos_score >= cosine_similar_thresh)
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{
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std::cout << "They have the same identity;";
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}
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else
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{
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std::cout << "They have different identities;";
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}
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std::cout << " Cosine Similarity: " << cos_score << ", threshold: " << cosine_similar_thresh << ". (higher value means higher similarity, max 1.0)\n";
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if(L2_score <= l2norm_similar_thresh)
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{
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std::cout << "They have the same identity;";
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}
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else
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{
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std::cout << "They have different identities.";
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}
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std::cout << " NormL2 Distance: " << L2_score << ", threshold: " << l2norm_similar_thresh << ". (lower value means higher similarity, min 0.0)\n";
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return 0;
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}
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