160 lines
No EOL
5.2 KiB
C++
160 lines
No EOL
5.2 KiB
C++
#include "gaze_predictor.hpp"
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#include <string>
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// caffe
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#define USE_OPENCV 1;
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#include <caffe/caffe.hpp>
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#include <caffe/util/io.hpp>
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#include <caffe/blob.hpp>
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#include <caffe/layers/pose_data_layer.hpp>
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#include <caffe/layers/memory_data_layer.hpp>
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using namespace cv;
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using namespace std;
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using namespace caffe;
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namespace opengaze {
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caffe::Net<float> *p_net_;
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GazePredictor::GazePredictor() {
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}
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GazePredictor::~GazePredictor() {
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delete p_net_;
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}
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void GazePredictor::initiaMPIIGaze(const std::vector<std::string> arguments={}) {
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p_net_ = nullptr;
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string param_path = arguments[0];
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string model_path = arguments[1];
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int gpu_id = stoi(arguments[3]);
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// Set GPU (or CPU)
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/*caffe::Caffe::set_mode(caffe::Caffe::CPU);
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cout << "Using CPU model" << endl;*/
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caffe::Caffe::set_mode(caffe::Caffe::GPU);
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cout << "Using GPU with id " << gpu_id << endl;
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Caffe::SetDevice(gpu_id);
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cout << "load caffe model parameters from " << param_path << endl;
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// create CNN
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p_net_ = new Net<float>(param_path, caffe::TEST);
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cout << "load caffe model from " << model_path << endl;
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// load pre-trained weights (binary proto)
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p_net_->CopyTrainedLayersFrom(model_path);
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// judge model type base on the paramater file name
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size_t i = param_path.rfind("/", param_path.length());
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string filename;
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if (i != string::npos)
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filename = param_path.substr(i+1, param_path.length() - i);
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if (!filename.compare(string("lenet_test.prototxt")))
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model_type_ = 1;
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else if (!filename.compare(string("googlenet.prototxt")))
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model_type_ = 2;
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else if (!filename.compare(string("alexnet_eye.prototxt")))
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model_type_ = 3;
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else if (!filename.compare(string("alexnet_face.prototxt")))
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model_type_ = 4; // the single face model
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else if (!filename.compare(string("alexnet_face_448.prototxt")))
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model_type_ = 4; // the single face model
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else{
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model_type_ = 0;
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cout<<"Cannot define the type of model!"<<endl;
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exit(EXIT_FAILURE);
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}
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}
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// gaze estimation with single face input image and with MPIIGaze method
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Point3f GazePredictor::predictGazeMPIIGaze(cv::Mat input_image) {
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vector<Mat> img_vec;
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img_vec.push_back(input_image);
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Vec2f gaze_norm_2d;
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Point3f gaze_norm_3d;
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std::vector<int> labelVector;
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labelVector.clear();
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labelVector.push_back(1);
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labelVector.push_back(1);
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float loss = 0.0;
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caffe::shared_ptr<caffe::MemoryDataLayer<float> > data_layer_;
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data_layer_ = boost::static_pointer_cast<MemoryDataLayer<float> >(p_net_->layer_by_name("data"));
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data_layer_->AddMatVector(img_vec, labelVector);
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// run network
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p_net_->ForwardPrefilled(&loss);
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if (model_type_==1)
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{
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// get output layer "ip2"
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float *temp = (float*)p_net_->blob_by_name("ip2")->cpu_data();
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// copy estimated gaze vector
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gaze_norm_2d.val[0] = temp[0];
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gaze_norm_2d.val[1] = temp[1];
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temp = nullptr;
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}
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else if (model_type_==2)// if it is googlenet
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{
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float *temp1 = (float*)p_net_->blob_by_name("loss1/classifier")->cpu_data();
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float *temp2 = (float*)p_net_->blob_by_name("loss2/classifier")->cpu_data();
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float *temp3 = (float*)p_net_->blob_by_name("loss3/classifier")->cpu_data();
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// average the output of three output values
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gaze_norm_2d.val[0] = (temp1[0]+temp2[0]+temp3[0]) / 3.0f;
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gaze_norm_2d.val[1] = (temp1[1]+temp2[1]+temp3[1]) / 3.0f;
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temp1 = nullptr;
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temp2 = nullptr;
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temp3 = nullptr;
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}
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else if (model_type_==3)// if it is alexnet
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{
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float *temp;
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temp = (float*)p_net_->blob_by_name("fc8")->cpu_data();// blob name can be fc8
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if (temp == NULL)
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temp = (float*)p_net_->blob_by_name("gaze_output")->cpu_data(); //blob name can be gaze_output
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if (temp == NULL) {
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cout << "ERROR: cannot find the blob name in the model. The final blob name muse be fc8 or gaze_output" << endl;
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exit(EXIT_FAILURE);
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}
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// copy estimated gaze vector
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gaze_norm_2d.val[0] = temp[0];
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gaze_norm_2d.val[1] = temp[1];
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temp = NULL;
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}
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else if (model_type_==4)// if it is alexnet
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{
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float *temp;
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temp = (float*)p_net_->blob_by_name("fc8")->cpu_data();// blob name can be fc8
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if (temp == NULL)
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temp = (float*)p_net_->blob_by_name("gaze_output")->cpu_data(); //blob name can be gaze_output
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if (temp == NULL) {
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cout << "ERROR: cannot find the blob name in the model. The final blob name muse be fc8 or gaze_output" << endl;
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exit(EXIT_FAILURE);
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}
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// copy estimated gaze vector
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gaze_norm_2d.val[0] = temp[0];
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gaze_norm_2d.val[1] = temp[1];
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//// get the feature out
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//temp = (float*)p_net_->blob_by_name("fc6_gaze")->cpu_data();
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//for (int num_f=0; num_f<4096; ++num_f)
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//{
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// feature[num_f] = temp[num_f];
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//}
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temp = NULL;
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}
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float theta = gaze_norm_2d.val[0];
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float phi = gaze_norm_2d.val[1];
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gaze_norm_3d.x = (-1.0f)*cos(theta)*sin(phi);
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gaze_norm_3d.y = (-1.0f)*sin(theta);
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gaze_norm_3d.z = (-1.0f)*cos(theta)*cos(phi);
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return gaze_norm_3d;
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}
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} |