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Showing 32 changed files with 193 additions and 212 deletions
CMakeLists.txt
......@@ -6,13 +6,9 @@ set(CMAKE_CXX_STANDARD 11)
find_package(OpenCV REQUIRED)
set(MNN_DIR /home/situ/MNN/MNN1.0/MNN)
include_directories(${MNN_DIR}/include)
include_directories(/home/situ/qfs/sdk_project/mnn_projects/face_recognize_mnn/include)
LINK_DIRECTORIES(${MNN_DIR}/build)
set(FACECOMPARISON_DIR /home/situ/qfs/sdk_project/mnn_projects/face_recognize_mnn/lib)
# add_library(facecomparison SHARED facerecognize.cpp retinaface.cpp facelandmarks.cpp facecomparison.cpp)
include_directories(/home/situ/qfs/face_recognize_mnn/include)
link_directories(${MNN_DIR}/build)
add_executable(main main.cpp facerecognize.cpp retinaface.cpp facelandmarks.cpp facecomparison.cpp)
# add_executable(main main.cpp)
# add_executable(main z.cpp)
target_link_libraries(main ${FACECOMPARISON_DIR}/libfacecomparison.so -lMNN ${OpenCV_LIBS})
# target_link_libraries(facecomparison -lMNN ${OpenCV_LIBS})
target_link_libraries(main -lMNN ${OpenCV_LIBS})
......
build/CMakeCache.txt
# This is the CMakeCache file.
# For build in directory: /home/situ/qfs/sdk_project/mnn_projects/face_recognize_mnn/build
# For build in directory: /home/situ/qfs/face_recognize_mnn/build
# It was generated by CMake: /usr/bin/cmake
# You can edit this file to change values found and used by cmake.
# If you do not want to change any of the values, simply exit the editor.
......@@ -329,10 +329,10 @@ CUDA_rt_LIBRARY:FILEPATH=/usr/lib/x86_64-linux-gnu/librt.so
OpenCV_DIR:PATH=/usr/local/lib/cmake/opencv4
//Value Computed by CMake
main_BINARY_DIR:STATIC=/home/situ/qfs/sdk_project/mnn_projects/face_recognize_mnn/build
main_BINARY_DIR:STATIC=/home/situ/qfs/face_recognize_mnn/build
//Value Computed by CMake
main_SOURCE_DIR:STATIC=/home/situ/qfs/sdk_project/mnn_projects/face_recognize_mnn
main_SOURCE_DIR:STATIC=/home/situ/qfs/face_recognize_mnn
########################
......@@ -342,7 +342,7 @@ main_SOURCE_DIR:STATIC=/home/situ/qfs/sdk_project/mnn_projects/face_recognize_mn
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CMAKE_AR-ADVANCED:INTERNAL=1
//This is the directory where this CMakeCache.txt was created
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CMAKE_CACHEFILE_DIR:INTERNAL=/home/situ/qfs/face_recognize_mnn/build
//Major version of cmake used to create the current loaded cache
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CMAKE_HAVE_PTHREAD_H:INTERNAL=1
//Source directory with the top level CMakeLists.txt file for this
// project
CMAKE_HOME_DIRECTORY:INTERNAL=/home/situ/qfs/sdk_project/mnn_projects/face_recognize_mnn
CMAKE_HOME_DIRECTORY:INTERNAL=/home/situ/qfs/face_recognize_mnn
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set(CMAKE_RELATIVE_PATH_TOP_BINARY "/home/situ/qfs/face_recognize_mnn/build")
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......
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CXX_INCLUDES = -I/home/situ/MNN/MNN1.0/MNN/include -I/home/situ/qfs/face_recognize_mnn/include -isystem /usr/local/include/opencv4
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......
build/Makefile
......@@ -48,10 +48,10 @@ RM = /usr/bin/cmake -E remove -f
EQUALS = =
# The top-level source directory on which CMake was run.
CMAKE_SOURCE_DIR = /home/situ/qfs/sdk_project/mnn_projects/face_recognize_mnn
CMAKE_SOURCE_DIR = /home/situ/qfs/face_recognize_mnn
# The top-level build directory on which CMake was run.
CMAKE_BINARY_DIR = /home/situ/qfs/sdk_project/mnn_projects/face_recognize_mnn/build
CMAKE_BINARY_DIR = /home/situ/qfs/face_recognize_mnn/build
#=============================================================================
# Targets provided globally by CMake.
......@@ -80,9 +80,9 @@ edit_cache/fast: edit_cache
# The main all target
all: cmake_check_build_system
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# Install script for directory: /home/situ/qfs/sdk_project/mnn_projects/face_recognize_mnn
# Install script for directory: /home/situ/qfs/face_recognize_mnn
# Set the install prefix
if(NOT DEFINED CMAKE_INSTALL_PREFIX)
......@@ -45,5 +45,5 @@ endif()
string(REPLACE ";" "\n" CMAKE_INSTALL_MANIFEST_CONTENT
"${CMAKE_INSTALL_MANIFEST_FILES}")
file(WRITE "/home/situ/qfs/sdk_project/mnn_projects/face_recognize_mnn/build/${CMAKE_INSTALL_MANIFEST}"
file(WRITE "/home/situ/qfs/face_recognize_mnn/build/${CMAKE_INSTALL_MANIFEST}"
"${CMAKE_INSTALL_MANIFEST_CONTENT}")
......
build/main
No preview for this file type
facecomparison.cpp
#include "facecomparison.h"
bool FaceComparison::init_model(string face_det_model,string face_landm_model,string face_rec_model,InitModelError &model_error){
bool FaceComparison::inference(string image1_path,string image2_path){
face_det = RetinaFace();
face_det.confidence_threshold = confidence_threshold;
face_det.is_bbox_process = is_bbox_process;
face_det.num_thread=num_thread;
face_det.forward_type = forward_type;
bool init_det_code = face_det.init_model(face_det_model);
model_error.init_error.push_back(init_det_code);
face_landm =FaceLandmarks();
bool init_landm_code = face_landm.init_model(face_landm_model);
face_landm.num_thread=num_thread;
face_landm.forward_type=forward_type;
model_error.init_error.push_back(init_landm_code);
face_rec =FaceRecognize();
bool init_rec_code = face_rec.init_model(face_rec_model);
face_rec.num_thread=num_thread;
face_rec.forward_type=forward_type;
model_error.init_error.push_back(init_rec_code);
if(init_det_code&&init_landm_code&&init_rec_code){
return true;
}else{
return false;
}
}
int FaceComparison::inference(string image1_path,string image2_path,OutputInfo &output_info){
bool result=false;
cv::Mat image1=cv::imread(image1_path);
cv::Mat image2=cv::imread(image2_path);
if(image1.empty()||image2.empty()){
return false;
if(image1.empty()){
cout<<"Please check if the first picture path exists"<<endl;
output_info.error_code=9001;
return -1;
}
if(image2.empty()){
cout<<"Please check if the second picture path exists"<<endl;
output_info.error_code=9002;
return -1;
}
vector<Bbox> box1=face_det.inference(image1);
vector<Bbox> box2=face_det.inference(image2);
if(box1.empty()||box2.empty()){
return false;
if(box1.empty()){
cout<<"No faces are detected in the first picture"<<endl;
output_info.error_code=9003;
return -1;
}
if(box2.empty()){
cout<<"No faces are detected in the second picture"<<endl;
output_info.error_code=9004;
return -1;
}
int max_box1=0;
double max_area1=0,max_area2=0;
......@@ -47,18 +86,38 @@ bool FaceComparison::inference(string image1_path,string image2_path){
Mat align_resize_image2=face_rec.preprocess_face(face_area2,land2);
double samilar_score=face_rec.inference(align_resize_image1,align_resize_image2);
if(samilar_score>face_recongnize_thr){
result=true;
output_info.error_code=0;
output_info.result=true;
}else{
output_info.error_code=0;
output_info.result=false;
}
}
return result;
}
bool FaceComparison::inference(Mat image1,Mat image2){
bool result=false;
int FaceComparison::inference(Mat image1,Mat image2,OutputInfo &output_info){
if(image1.empty()){
cout<<"Please check if the first picture path exists"<<endl;
output_info.error_code=9001;
return -1;
}
if(image2.empty()){
cout<<"Please check if the second picture path exists"<<endl;
output_info.error_code=9002;
return -1;
}
vector<Bbox> box1=face_det.inference(image1);
vector<Bbox> box2=face_det.inference(image2);
if(box1.empty()||box2.empty()){
return false;
if(box1.empty()){
cout<<"No faces are detected in the first picture"<<endl;
output_info.error_code=9003;
return -1;
}
if(box2.empty()){
cout<<"No faces are detected in the second picture"<<endl;
output_info.error_code=9004;
return -1;
}
int max_box1=0;
double max_area1=0,max_area2=0;
......@@ -94,8 +153,12 @@ bool FaceComparison::inference(Mat image1,Mat image2){
Mat align_resize_image2=face_rec.preprocess_face(face_area2,land2);
double samilar_score=face_rec.inference(align_resize_image1,align_resize_image2);
if(samilar_score>face_recongnize_thr){
result=true;
output_info.error_code=0;
output_info.result=true;
}else{
output_info.error_code=0;
output_info.result=false;
}
}
return result;
return 0;
}
......
facelandmarks.cpp
#include "facelandmarks.h"
FaceLandmarks::FaceLandmarks(){
model_init=false;
}
// FaceLandmarks::~FaceLandmarks(){
// pfld_interpreter->releaseModel();
// pfld_interpreter->releaseSession(session);
......@@ -36,7 +34,7 @@ bool FaceLandmarks::init_model(string model_path){
pretreat = shared_ptr<MNN::CV::ImageProcess>(MNN::CV::ImageProcess::create(image_config));
// pretreat->setMatrix(transforms);
model_init = true;
return true;
}
vector<vector<float>> FaceLandmarks::inference(string image_path){
......
facerecognize.cpp
#include "facerecognize.h"
FaceRecognize::FaceRecognize(){}
#include "facerecognize.h" FaceRecognize::FaceRecognize(){} // FaceRecognize::~FaceRecognize(){ // net->releaseModel(); // net->releaseSession(session1); // net->releaseSession(session2); // } bool FaceRecognize::init_model(string model_path){ net=shared_ptr<MNN::Interpreter>(MNN::Interpreter::createFromFile(model_path.c_str())); ScheduleConfig config; config.numThread=num_thread; config.type=forward_type; session1 = net->createSession(config); session2 = net->createSession(config); input_tensor1 = net->getSessionInput(session1,NULL); input_tensor2 = net->getSessionInput(session2,NULL); net->resizeTensor(input_tensor1,{1,3,input_size[1],input_size[0]}); net->resizeSession(session1); net->resizeTensor(input_tensor2,{1,3,input_size[1],input_size[0]}); net->resizeSession(session2); //数据预处理 MNN::CV::ImageProcess::Config image_config; image_config.sourceFormat = MNN::CV::BGR; image_config.destFormat = MNN::CV::BGR; ::memcpy(image_config.mean,mean,sizeof(mean)); ::memcpy(image_config.normal,normal,sizeof(normal)); pretreat = shared_ptr<MNN::CV::ImageProcess>(MNN::CV::ImageProcess::create(image_config)); model_init = true; return model_init; } cv::Mat FaceRecognize::meanAxis0(const cv::Mat &src) { int num = src.rows; int dim = src.cols; cv::Mat output(1,dim,CV_32F); for(int i = 0 ; i < dim; i ++) { float sum = 0 ; for(int j = 0 ; j < num ; j++) { sum+=src.at<float>(j,i); } output.at<float>(0,i) = sum/num; } return output; } cv::Mat FaceRecognize::elementwiseMinus(const cv::Mat &A,const cv::Mat &B) { cv::Mat output(A.rows,A.cols,A.type()); assert(B.cols == A.cols); if(B.cols == A.cols) { for(int i = 0 ; i < A.rows; i ++) { for(int j = 0 ; j < B.cols; j++) { output.at<float>(i,j) = A.at<float>(i,j) - B.at<float>(0,j); } } } return output; } cv::Mat FaceRecognize::varAxis0(const cv::Mat &src) { cv:Mat temp_ = elementwiseMinus(src,meanAxis0(src)); cv::multiply(temp_ ,temp_ ,temp_ ); return meanAxis0(temp_); } int FaceRecognize::MatrixRank(cv::Mat M) { Mat w, u, vt; SVD::compute(M, w, u, vt); Mat1b nonZeroSingularValues = w > 0.0001; int rank = countNonZero(nonZeroSingularValues); return rank; } cv::Mat FaceRecognize::similarTransform(cv::Mat src,cv::Mat dst) { int num = src.rows; int dim = src.cols; cv::Mat src_mean = meanAxis0(src); cv::Mat dst_mean = meanAxis0(dst); cv::Mat src_demean = elementwiseMinus(src, src_mean); cv::Mat dst_demean = elementwiseMinus(dst, dst_mean); cv::Mat A = (dst_demean.t() * src_demean) / static_cast<float>(num); cv::Mat d(dim, 1, CV_32F); d.setTo(1.0f); if (cv::determinant(A) < 0) { d.at<float>(dim - 1, 0) = -1; } Mat T = cv::Mat::eye(dim + 1, dim + 1, CV_32F); cv::Mat U, S, V; SVD::compute(A, S,U, V); // the SVD function in opencv differ from scipy . int rank = MatrixRank(A); if (rank == 0) { assert(rank == 0); } else if (rank == dim - 1) { if (cv::determinant(U) * cv::determinant(V) > 0) { T.rowRange(0, dim).colRange(0, dim) = U * V; } else { int s = d.at<float>(dim - 1, 0) = -1; d.at<float>(dim - 1, 0) = -1; T.rowRange(0, dim).colRange(0, dim) = U * V; cv::Mat diag_ = cv::Mat::diag(d); cv::Mat twp = diag_*V; //np.dot(np.diag(d), V.T) Mat B = Mat::zeros(3, 3, CV_8UC1); Mat C = B.diag(0); T.rowRange(0, dim).colRange(0, dim) = U* twp; d.at<float>(dim - 1, 0) = s; } } else{ cv::Mat diag_ = cv::Mat::diag(d); cv::Mat twp = diag_*V.t(); //np.dot(np.diag(d), V.T) cv::Mat res = U* twp; // U T.rowRange(0, dim).colRange(0, dim) = -U.t()* twp; } cv::Mat var_ = varAxis0(src_demean); float val = cv::sum(var_).val[0]; cv::Mat res; cv::multiply(d,S,res); float scale = 1.0/val*cv::sum(res).val[0]; T.rowRange(0, dim).colRange(0, dim) = - T.rowRange(0, dim).colRange(0, dim).t(); cv::Mat temp1 = T.rowRange(0, dim).colRange(0, dim); // T[:dim, :dim] cv::Mat temp2 = src_mean.t(); //src_mean.T cv::Mat temp3 = temp1*temp2; // np.dot(T[:dim, :dim], src_mean.T) cv::Mat temp4 = scale*temp3; T.rowRange(0, dim).colRange(dim, dim+1)= -(temp4 - dst_mean.t()) ; T.rowRange(0, dim).colRange(0, dim) *= scale; return T; } Mat FaceRecognize::preprocess_face(Mat image,vector<vector<float>> land){ Mat out; cv::resize(image,out,Size(112,112)); float default1[5][2] = { {38.2946f, 51.6963f}, {73.5318f, 51.6963f}, {56.0252f, 71.7366f}, {41.5493f, 92.3655f}, {70.7299f, 92.3655f} }; float lands[5][2]={ {float(land[0][0]*112.0)/float(image.cols),float(land[0][1]*112.0)/float(image.rows)}, {float(land[1][0]*112.0)/float(image.cols),float(land[1][1]*112.0)/float(image.rows)}, {float(land[2][0]*112.0)/float(image.cols),float(land[2][1]*112.0)/float(image.rows)}, {float(land[3][0]*112.0)/float(image.cols),float(land[3][1]*112.0)/float(image.rows)}, {float(land[4][0]*112.0)/float(image.cols),float(land[4][1]*112.0)/float(image.rows)} }; cv::Mat src(5,2,CV_32FC1,default1); memcpy(src.data, default1, 2 * 5 * sizeof(float)); cv::Mat dst(5,2,CV_32FC1,lands); memcpy(dst.data, lands, 2 * 5 * sizeof(float)); cv::Mat M = similarTransform(dst, src); float M_[2][3]={ {M.at<float>(0,0),M.at<float>(0,1),M.at<float>(0,2)}, {M.at<float>(1,0),M.at<float>(1,1),M.at<float>(1,2)}, }; cv::Mat M__(2,3,CV_32FC1,M_); cv::Mat align_image; cv::warpAffine(out,align_image,M__,Size(112, 112)); return align_image; } double FaceRecognize::getMold(const vector<double>& vec) { int n = vec.size(); double sum = 0.0; for (int i = 0; i < n; ++i) sum += vec[i] * vec[i]; return sqrt(sum); } double FaceRecognize::cos_distance(const vector<double>& base, const vector<double>& target) { int n = base.size(); assert(n == target.size()); double tmp = 0.0; for (int i = 0; i < n; ++i) tmp += base[i] * target[i]; double simility = tmp / (getMold(base)*getMold(target)); return simility; } double FaceRecognize::inference(Mat image1,Mat image2){ cv::resize(image1,image1,Size2d(input_size[0],input_size[1])); cv::resize(image2,image2,Size2d(input_size[0],input_size[1])); pretreat->convert(image1.data,input_size[0],input_size[1],0,input_tensor1); pretreat->convert(image2.data,input_size[0],input_size[1],0,input_tensor2); //推理 net->runSession(session1); auto output1= net->getSessionOutput(session1, NULL); //推理 net->runSession(session2); auto output2= net->getSessionOutput(session2, NULL); MNN::Tensor feat_tensor1(output1, output1->getDimensionType()); MNN::Tensor feat_tensor2(output2, output2->getDimensionType()); output1->copyToHostTensor(&feat_tensor1); output2->copyToHostTensor(&feat_tensor2); auto feature1 = feat_tensor1.host<float>(); auto feature2 = feat_tensor2.host<float>(); vector<double> v1,v2; for(int i=0;i<int(feat_tensor1.size()/4);i++){ v1.push_back((double)feature1[i]); v2.push_back((double)feature2[i]); } double cos_score=cos_distance(v1,v2); return cos_score; } double FaceRecognize::inference(string image_path1,string image_path2){ Mat image1 = cv::imread(image_path1); Mat image2 = cv::imread(image_path2); cv::resize(image1,image1,Size2d(input_size[0],input_size[1])); cv::resize(image2,image2,Size2d(input_size[0],input_size[1])); pretreat->convert(image1.data,input_size[0],input_size[1],0,input_tensor1); pretreat->convert(image2.data,input_size[0],input_size[1],0,input_tensor2); //推理 net->runSession(session1); auto output1= net->getSessionOutput(session1, NULL); //推理 net->runSession(session2); auto output2= net->getSessionOutput(session2, NULL); MNN::Tensor feat_tensor1(output1, output1->getDimensionType()); MNN::Tensor feat_tensor2(output2, output2->getDimensionType()); output1->copyToHostTensor(&feat_tensor1); output2->copyToHostTensor(&feat_tensor2); auto feature1 = feat_tensor1.host<float>(); auto feature2 = feat_tensor2.host<float>(); vector<double> v1,v2; for(int i=0;i<int(feat_tensor1.size()/4);i++){ v1.push_back((double)feature1[i]); v2.push_back((double)feature2[i]); } double cos_score=cos_distance(v1,v2); return cos_score; }
#include "facerecognize.h"
// FaceRecognize::~FaceRecognize(){
// net->releaseModel();
......@@ -10,7 +12,9 @@ FaceRecognize::FaceRecognize(){}
bool FaceRecognize::init_model(string model_path){
net=shared_ptr<MNN::Interpreter>(MNN::Interpreter::createFromFile(model_path.c_str()));
if(nullptr==net){
return false;
}
ScheduleConfig config;
config.numThread=num_thread;
config.type=forward_type;
......@@ -32,8 +36,8 @@ bool FaceRecognize::init_model(string model_path){
::memcpy(image_config.mean,mean,sizeof(mean));
::memcpy(image_config.normal,normal,sizeof(normal));
pretreat = shared_ptr<MNN::CV::ImageProcess>(MNN::CV::ImageProcess::create(image_config));
model_init = true;
return model_init;
return true;
}
......
include/facecomparison.h
......@@ -6,11 +6,20 @@
#include "retinaface.h"
#include "facelandmarks.h"
struct OutputInfo{
int error_code;
bool result;
};
struct InitModelError{
vector<bool> init_error;
};
class FaceComparison{
public:
// 人脸检测阈值
float confidence_threshold = 0.2;
float confidence_threshold = 0.5;
// 是否进行人脸外廓
bool is_bbox_process = true;
......@@ -25,8 +34,8 @@ class FaceComparison{
//接口
bool inference(string image_path1,string image_path2);
bool inference(Mat image1,Mat image2);
int inference(string image_path1,string image_path2,OutputInfo &output_info);
int inference(Mat image1,Mat image2,OutputInfo &output_info);
private:
RetinaFace face_det;
......@@ -35,18 +44,6 @@ class FaceComparison{
public:
FaceComparison(){};
FaceComparison(string face_det_model,string face_landm_model,string face_rec_model){
face_det = RetinaFace(face_det_model);
face_det.confidence_threshold = confidence_threshold;
face_det.is_bbox_process = is_bbox_process;
face_det.num_thread=num_thread;
face_det.forward_type = forward_type;
face_landm =FaceLandmarks(face_landm_model);
face_landm.num_thread=num_thread;
face_landm.forward_type=forward_type;
face_rec =FaceRecognize(face_rec_model);
face_rec.num_thread=num_thread;
face_rec.forward_type=forward_type;
}
bool init_model(string face_det_model,string face_landm_model,string face_rec_model,InitModelError &model_error);
};
#endif
......
include/facelandmarks.h
......@@ -16,11 +16,8 @@ class FaceLandmarks{
MNNForwardType forward_type = MNN_FORWARD_CPU;
public:
FaceLandmarks();
FaceLandmarks(){};
// ~FaceLandmarks();
FaceLandmarks(string model_path){
init_model(model_path);
};
bool init_model(string model_path);
vector<vector<float>> inference(string image_path);
vector<vector<float>> inference(Mat image);
......@@ -34,3 +31,4 @@ class FaceLandmarks{
shared_ptr<MNN::CV::ImageProcess> pretreat;
};
#endif
......
include/facerecognize.h
......@@ -35,7 +35,7 @@ class FaceRecognize{
float normal[3] = {1.0f/127.5f,1.0f/127.5f,1.0f/127.5f};
public:
FaceRecognize();
FaceRecognize(){};
// ~FaceRecognize();
FaceRecognize(string model_path){
init_model(model_path);
......
include/retinaface.h
......@@ -63,11 +63,8 @@ class RetinaFace{
public:
RetinaFace();
RetinaFace(){};
// ~RetinaFace();
RetinaFace(string model_path){
init_model(model_path);
}
bool init_model(string model_path);
// 推理
......
lib/libfacecomparison.so deleted 100755 → 0
No preview for this file type
main.cpp
#include "facecomparison.h"
int main(){
// FaceLandmarks face_landmarks1 = FaceLandmarks("/home/situ/qfs/sdk_project/mnn_projects/face_recognize_mnn/model/det_landmarks_106_v0.0.1.mnn");
// FaceLandmarks face_landmarks1 = FaceLandmarks();
// face_landmarks1.init_model("/home/situ/qfs/sdk_project/mnn_projects/face_recognize_mnn/model/det_landmarks_106_v0.0.1.mnn");
// vector<string> filenames;
// cv::glob("/home/situ/图片/img3", filenames, false);
// for(auto path:filenames){
......@@ -17,14 +18,16 @@ int main(){
Mat image1 = cv::imread("/data/face_recognize/pipeline_test/35326a760af111ec9f2300163e772630/310cardImageContent163047910320427.jpg");
Mat image2 = cv::imread("/data/face_recognize/pipeline_test/35326a760af111ec9f2300163e772630/310faceImageContent163047910353714.jpg");
string face_det_model = "/home/situ/qfs/sdk_project/mnn_projects/face_recognize_mnn/model/det_face_retina_mnn_1.0.0_v0.1.1.mnn";
string face_landm_model = "/home/situ/qfs/sdk_project/mnn_projects/face_recognize_mnn/model/det_landmarks_106_v0.0.1.mnn";
string face_rec_model = "/home/situ/qfs/sdk_project/mnn_projects/face_recognize_mnn/model/cls_face_mnn_1.0.0_v0.1.1.mnn";
FaceComparison face_rec = FaceComparison(face_det_model,face_landm_model,face_rec_model);
bool result = face_rec.inference(image1,image2);
cout<<result<<endl;
string face_det_model = "/home/situ/qfs/face_recognize_mnn/model/det_face_retina_mnn_1.0.0_v0.1.1.mnn";
string face_landm_model = "/home/situ/qfs/face_recognize_mnn/model/det_landmarks_106_v0.0.1.mnn";
string face_rec_model = "/home/situ/qfs/face_recognize_mnn/model/cls_face_mnn_1.0.0_v0.1.1.mnn";
InitModelError init_model_code;
OutputInfo output_info;
FaceComparison face_rec = FaceComparison();
bool init_model = face_rec.init_model(face_det_model,face_landm_model,face_rec_model,init_model_code);
int result = face_rec.inference(image1,image2,output_info);
cout<<output_info.error_code<<" "<<output_info.result<<endl;
// string model_path = "/home/situ/qfs/sdk_project/mnn_projects/face_recognize_mnn/model/det_face_retina_mnn_1.0.0_v0.1.1.mnn";
// RetinaFace face_det = RetinaFace(model_path.c_str());
......@@ -38,3 +41,4 @@ int main(){
// cv::waitKey(0);
// return 0;
}
......
retinaface.cpp
#include "retinaface.h"
RetinaFace::RetinaFace(){}
// RetinaFace::~RetinaFace(){
// net->releaseModel();
......@@ -28,7 +27,7 @@ bool RetinaFace::init_model(string model_path){
::memcpy(image_config.mean,mean,sizeof(mean));
pretreat = shared_ptr<MNN::CV::ImageProcess>(CV::ImageProcess::create(image_config));
model_init = true;
return true;
}
......
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