66 lines
2 KiB
C++
66 lines
2 KiB
C++
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#ifndef GAZE_ESTIMATOR_HPP
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#define GAZE_ESTIMATOR_HPP
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#include <opencv2/opencv.hpp>
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#include "data.hpp"
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#include "face_detector.hpp"
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#include "normalizer.hpp"
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#include "gaze_predictor.hpp"
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namespace opengaze{
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class GazeEstimator {
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public:
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GazeEstimator();
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~GazeEstimator();
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/**
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* On the current implementation, we only has the "MPIIGaze" method which uses the input face/eye image
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* and output gaze direction directly. It is an appearance-based method. The "OpenFace" can also output
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* the gaze vector according to the pupil detection results. However, "OpenFace" implementation is not
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* included inside our OpenGaze toolkit yet.
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*/
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enum Method{MPIIGaze, OpenFace};
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/**
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* for the "MPIIGaze" method, the input image can be face or eye. The full-face patch model can output
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* more accurate gaze prediction than the eye image model, while the eye image base model is much faster.
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*/
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enum InputType{face, eye};
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/**
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* the main function to estimate the gaze.
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* It performs the face and facial landmarks detection, head pose estimation and then gaze prediction.
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* @param input_image input scene image
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* @param output data structure for output
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*/
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void estimateGaze(cv::Mat input_image, std::vector<opengaze::Sample> &output);
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void getImagePatch(cv::Mat input_image, std::vector<opengaze::Sample> &outputs);
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void setCameraParameters(cv::Mat camera_matrix, cv::Mat camera_dist);
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void setRootPath(std::string root_path);
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void setMethod(Method, std::vector<std::string> arguments);
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void initialFaceDetector(int number_users);
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Method method_type_;
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InputType input_type_; // the input type
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private:
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// class instances
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FaceDetector face_detector_;
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Normalizer normalizer_;
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GazePredictor gaze_predictor_;
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// camera intrinsic matrix
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cv::Mat camera_matrix_;
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// camera distortion matrix
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cv::Mat camera_dist_;
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// the root pat is used for load configuration file and models
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std::string root_path_;
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};
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}
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#endif //GAZE_ESTIMATOR_HPP
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