+++ /dev/null
-#include "CsvReader.h"
-#include "Utils.h"
-
-/** The default constructor of the CSV reader Class */
-CsvReader::CsvReader(const std::string &path, const char &separator){
- _file.open(path.c_str(), ifstream::in);
- _separator = separator;
-}
-
-/* Read a plane text file with .ply format */
-void CsvReader::readPLY(std::vector<cv::Point3f> &list_vertex, std::vector<std::vector<int> > &list_triangles)
-{
- std::string line, tmp_str, n;
- int num_vertex, num_triangles;
- int count = 0;
- bool end_header = false;
- bool end_vertex = false;
-
- // Read the whole *.ply file
- while (getline(_file, line)) {
- stringstream liness(line);
-
- // read header
- if(!end_header)
- {
- getline(liness, tmp_str, _separator);
- if( tmp_str == "element" )
- {
- getline(liness, tmp_str, _separator);
- getline(liness, n);
- if(tmp_str == "vertex") num_vertex = StringToInt(n);
- if(tmp_str == "face") num_triangles = StringToInt(n);
- }
- if(tmp_str == "end_header") end_header = true;
- }
-
- // read file content
- else if(end_header)
- {
- // read vertex and add into 'list_vertex'
- if(!end_vertex && count < num_vertex)
- {
- string x, y, z;
- getline(liness, x, _separator);
- getline(liness, y, _separator);
- getline(liness, z);
-
- cv::Point3f tmp_p;
- tmp_p.x = StringToInt(x);
- tmp_p.y = StringToInt(y);
- tmp_p.z = StringToInt(z);
- list_vertex.push_back(tmp_p);
-
- count++;
- if(count == num_vertex)
- {
- count = 0;
- end_vertex = !end_vertex;
- }
- }
- // read faces and add into 'list_triangles'
- else if(end_vertex && count < num_triangles)
- {
- std::string num_pts_per_face, id0, id1, id2;
- getline(liness, num_pts_per_face, _separator);
- getline(liness, id0, _separator);
- getline(liness, id1, _separator);
- getline(liness, id2);
-
- std::vector<int> tmp_triangle(3);
- tmp_triangle[0] = StringToInt(id0);
- tmp_triangle[1] = StringToInt(id1);
- tmp_triangle[2] = StringToInt(id2);
- list_triangles.push_back(tmp_triangle);
-
- count++;
- }
- }
- }
-}
+++ /dev/null
-#ifndef CSVREADER_H
-#define CSVREADER_H
-
-#include <iostream>
-#include <fstream>
-
-#include <opencv2/core/core.hpp>
-
-using namespace std;
-using namespace cv;
-
-class CsvReader {
-public:
- /**
- * The default constructor of the CSV reader Class.
- * The default separator is ' ' (empty space)
- *
- * @param path - The path of the file to read
- * @param separator - The separator character between words per line
- * @return
- */
- CsvReader(const std::string &path, const char &separator = ' ');
-
- /**
- * Read a plane text file with .ply format
- *
- * @param list_vertex - The container of the vertices list of the mesh
- * @param list_triangle - The container of the triangles list of the mesh
- * @return
- */
- void readPLY(std::vector<cv::Point3f> &list_vertex, std::vector<std::vector<int> > &list_triangles);
-
-private:
- /** The current stream file for the reader */
- ifstream _file;
- /** The separator character between words for each line */
- char _separator;
-};
-
-#endif
+++ /dev/null
-#include "CsvWriter.h"
-#include "Utils.h"
-
-CsvWriter::CsvWriter(const std::string &path, const std::string &separator){
- _file.open(path.c_str(), std::ofstream::out);
- _isFirstTerm = true;
- _separator = separator;
-}
-
-CsvWriter::~CsvWriter() {
- _file.flush();
- _file.close();
-}
-
-void CsvWriter::writeXYZ(const std::vector<cv::Point3f> &list_points3d)
-{
- std::string x, y, z;
- for(unsigned int i = 0; i < list_points3d.size(); ++i)
- {
- x = FloatToString(list_points3d[i].x);
- y = FloatToString(list_points3d[i].y);
- z = FloatToString(list_points3d[i].z);
-
- _file << x << _separator << y << _separator << z << std::endl;
- }
-
-}
-
-void CsvWriter::writeUVXYZ(const std::vector<cv::Point3f> &list_points3d, const std::vector<cv::Point2f> &list_points2d, const cv::Mat &descriptors)
-{
- std::string u, v, x, y, z, descriptor_str;
- for(int i = 0; i < list_points3d.size(); ++i)
- {
- u = FloatToString(list_points2d[i].x);
- v = FloatToString(list_points2d[i].y);
- x = FloatToString(list_points3d[i].x);
- y = FloatToString(list_points3d[i].y);
- z = FloatToString(list_points3d[i].z);
-
- _file << u << _separator << v << _separator << x << _separator << y << _separator << z;
-
- for(int j = 0; j < 32; ++j)
- {
- std::cout << descriptors.at<float>(i,j) << std::endl;
- descriptor_str = FloatToString(descriptors.at<float>(i,j));
- _file << _separator << descriptor_str;
- }
- _file << std::endl;
- }
-}
+++ /dev/null
-#ifndef CSVWRITER_H
-#define CSVWRITER_H
-
-#include <fstream>
-#include <iostream>
-
-#include <opencv2/core/core.hpp>
-
-class CsvWriter {
-public:
- CsvWriter(const std::string &path, const std::string &separator = " ");
- ~CsvWriter();
- void writeXYZ(const std::vector<cv::Point3f> &list_points3d);
- void writeUVXYZ(const std::vector<cv::Point3f> &list_points3d, const std::vector<cv::Point2f> &list_points2d, const cv::Mat &descriptors);
-
-private:
- std::ofstream _file;
- std::string _separator;
- bool _isFirstTerm;
-};
-
-#endif
+++ /dev/null
-/*
- * Mesh.cpp
- *
- * Created on: Apr 9, 2014
- * Author: edgar
- */
-
-#include "Mesh.h"
-#include "CsvReader.h"
-
-
-// --------------------------------------------------- //
-// TRIANGLE CLASS //
-// --------------------------------------------------- //
-
-/** The custom constructor of the Triangle Class */
-Triangle::Triangle(int id, cv::Point3f V0, cv::Point3f V1, cv::Point3f V2)
-{
- id_ = id; v0_ = V0; v1_ = V1; v2_ = V2;
-}
-
-/** The default destructor of the Class */
-Triangle::~Triangle()
-{
- // TODO Auto-generated destructor stub
-}
-
-
-// --------------------------------------------------- //
-// RAY CLASS //
-// --------------------------------------------------- //
-
-/** The custom constructor of the Ray Class */
-Ray::Ray(cv::Point3f P0, cv::Point3f P1) {
- p0_ = P0; p1_ = P1;
-}
-
-/** The default destructor of the Class */
-Ray::~Ray()
-{
- // TODO Auto-generated destructor stub
-}
-
-
-// --------------------------------------------------- //
-// OBJECT MESH CLASS //
-// --------------------------------------------------- //
-
-/** The default constructor of the ObjectMesh Class */
-Mesh::Mesh() : list_vertex_(0) , list_triangles_(0)
-{
- id_ = 0;
- num_vertexs_ = 0;
- num_triangles_ = 0;
-}
-
-/** The default destructor of the ObjectMesh Class */
-Mesh::~Mesh()
-{
- // TODO Auto-generated destructor stub
-}
-
-
-/** Load a CSV with *.ply format **/
-void Mesh::load(const std::string path)
-{
-
- // Create the reader
- CsvReader csvReader(path);
-
- // Clear previous data
- list_vertex_.clear();
- list_triangles_.clear();
-
- // Read from .ply file
- csvReader.readPLY(list_vertex_, list_triangles_);
-
- // Update mesh attributes
- num_vertexs_ = list_vertex_.size();
- num_triangles_ = list_triangles_.size();
-
-}
+++ /dev/null
-/*
- * Mesh.h
- *
- * Created on: Apr 9, 2014
- * Author: edgar
- */
-
-#ifndef MESH_H_
-#define MESH_H_
-
-#include <iostream>
-#include <opencv2/core/core.hpp>
-
-
-// --------------------------------------------------- //
-// TRIANGLE CLASS //
-// --------------------------------------------------- //
-
-class Triangle {
-public:
-
- explicit Triangle(int id, cv::Point3f V0, cv::Point3f V1, cv::Point3f V2);
- virtual ~Triangle();
-
- cv::Point3f getV0() const { return v0_; }
- cv::Point3f getV1() const { return v1_; }
- cv::Point3f getV2() const { return v2_; }
-
-private:
- /** The identifier number of the triangle */
- int id_;
- /** The three vertices that defines the triangle */
- cv::Point3f v0_, v1_, v2_;
-};
-
-
-// --------------------------------------------------- //
-// RAY CLASS //
-// --------------------------------------------------- //
-
-class Ray {
-public:
-
- explicit Ray(cv::Point3f P0, cv::Point3f P1);
- virtual ~Ray();
-
- cv::Point3f getP0() { return p0_; }
- cv::Point3f getP1() { return p1_; }
-
-private:
- /** The two points that defines the ray */
- cv::Point3f p0_, p1_;
-};
-
-
-// --------------------------------------------------- //
-// OBJECT MESH CLASS //
-// --------------------------------------------------- //
-
-class Mesh
-{
-public:
-
- Mesh();
- virtual ~Mesh();
-
- std::vector<std::vector<int> > getTrianglesList() const { return list_triangles_; }
- cv::Point3f getVertex(int pos) const { return list_vertex_[pos]; }
- int getNumVertices() const { return num_vertexs_; }
-
- void load(const std::string path_file);
-
-private:
- /** The identification number of the mesh */
- int id_;
- /** The current number of vertices in the mesh */
- int num_vertexs_;
- /** The current number of triangles in the mesh */
- int num_triangles_;
- /* The list of triangles of the mesh */
- std::vector<cv::Point3f> list_vertex_;
- /* The list of triangles of the mesh */
- std::vector<std::vector<int> > list_triangles_;
-};
-
-#endif /* OBJECTMESH_H_ */
+++ /dev/null
-/*
- * Model.cpp
- *
- * Created on: Apr 9, 2014
- * Author: edgar
- */
-
-#include "Model.h"
-#include "CsvWriter.h"
-
-Model::Model() : list_points2d_in_(0), list_points2d_out_(0), list_points3d_in_(0)
-{
- n_correspondences_ = 0;
-}
-
-Model::~Model()
-{
- // TODO Auto-generated destructor stub
-}
-
-void Model::add_correspondence(const cv::Point2f &point2d, const cv::Point3f &point3d)
-{
- list_points2d_in_.push_back(point2d);
- list_points3d_in_.push_back(point3d);
- n_correspondences_++;
-}
-
-void Model::add_outlier(const cv::Point2f &point2d)
-{
- list_points2d_out_.push_back(point2d);
-}
-
-void Model::add_descriptor(const cv::Mat &descriptor)
-{
- descriptors_.push_back(descriptor);
-}
-
-void Model::add_keypoint(const cv::KeyPoint &kp)
-{
- list_keypoints_.push_back(kp);
-}
-
-
-/** Save a CSV file and fill the object mesh */
-void Model::save(const std::string path)
-{
- cv::Mat points3dmatrix = cv::Mat(list_points3d_in_);
- cv::Mat points2dmatrix = cv::Mat(list_points2d_in_);
- //cv::Mat keyPointmatrix = cv::Mat(list_keypoints_);
-
- cv::FileStorage storage(path, cv::FileStorage::WRITE);
- storage << "points_3d" << points3dmatrix;
- storage << "points_2d" << points2dmatrix;
- storage << "keypoints" << list_keypoints_;
- storage << "descriptors" << descriptors_;
-
- storage.release();
-}
-
-/** Load a YAML file using OpenCv functions **/
-void Model::load(const std::string path)
-{
- cv::Mat points3d_mat;
-
- cv::FileStorage storage(path, cv::FileStorage::READ);
- storage["points_3d"] >> points3d_mat;
- storage["descriptors"] >> descriptors_;
-
- points3d_mat.copyTo(list_points3d_in_);
-
- storage.release();
-
-}
+++ /dev/null
-/*
- * Model.h
- *
- * Created on: Apr 9, 2014
- * Author: edgar
- */
-
-#ifndef MODEL_H_
-#define MODEL_H_
-
-#include <iostream>
-#include <opencv2/core/core.hpp>
-#include <opencv2/features2d/features2d.hpp>
-
-class Model
-{
-public:
- Model();
- virtual ~Model();
-
- std::vector<cv::Point2f> get_points2d_in() const { return list_points2d_in_; }
- std::vector<cv::Point2f> get_points2d_out() const { return list_points2d_out_; }
- std::vector<cv::Point3f> get_points3d() const { return list_points3d_in_; }
- std::vector<cv::KeyPoint> get_keypoints() const { return list_keypoints_; }
- cv::Mat get_descriptors() const { return descriptors_; }
- int get_numDescriptors() const { return descriptors_.rows; }
-
-
- void add_correspondence(const cv::Point2f &point2d, const cv::Point3f &point3d);
- void add_outlier(const cv::Point2f &point2d);
- void add_descriptor(const cv::Mat &descriptor);
- void add_keypoint(const cv::KeyPoint &kp);
-
-
- void save(const std::string path);
- void load(const std::string path);
-
-
-private:
- /** The current number of correspondecnes */
- int n_correspondences_;
- /** The list of 2D points on the model surface */
- std::vector<cv::KeyPoint> list_keypoints_;
- /** The list of 2D points on the model surface */
- std::vector<cv::Point2f> list_points2d_in_;
- /** The list of 2D points outside the model surface */
- std::vector<cv::Point2f> list_points2d_out_;
- /** The list of 3D points on the model surface */
- std::vector<cv::Point3f> list_points3d_in_;
- /** The list of 2D points descriptors */
- cv::Mat descriptors_;
-};
-
-#endif /* OBJECTMODEL_H_ */
+++ /dev/null
-/*
- * ModelRegistration.cpp
- *
- * Created on: Apr 18, 2014
- * Author: edgar
- */
-
-#include "ModelRegistration.h"
-
-ModelRegistration::ModelRegistration()
-{
- n_registrations_ = 0;
- max_registrations_ = 0;
-}
-
-ModelRegistration::~ModelRegistration()
-{
- // TODO Auto-generated destructor stub
-}
-
-void ModelRegistration::registerPoint(const cv::Point2f &point2d, const cv::Point3f &point3d)
- {
- // add correspondence at the end of the vector
- list_points2d_.push_back(point2d);
- list_points3d_.push_back(point3d);
- n_registrations_++;
- }
-
-void ModelRegistration::reset()
-{
- n_registrations_ = 0;
- max_registrations_ = 0;
- list_points2d_.clear();
- list_points3d_.clear();
-}
+++ /dev/null
-/*
- * ModelRegistration.h
- *
- * Created on: Apr 18, 2014
- * Author: edgar
- */
-
-#ifndef MODELREGISTRATION_H_
-#define MODELREGISTRATION_H_
-
-#include <iostream>
-#include <opencv2/core/core.hpp>
-
-class ModelRegistration
-{
-public:
-
- ModelRegistration();
- virtual ~ModelRegistration();
-
- void setNumMax(int n) { max_registrations_ = n; }
-
- std::vector<cv::Point2f> get_points2d() const { return list_points2d_; }
- std::vector<cv::Point3f> get_points3d() const { return list_points3d_; }
- int getNumMax() const { return max_registrations_; }
- int getNumRegist() const { return n_registrations_; }
-
- bool is_registrable() const { return (n_registrations_ < max_registrations_); }
- void registerPoint(const cv::Point2f &point2d, const cv::Point3f &point3d);
- void reset();
-
-private:
-/** The current number of registered points */
-int n_registrations_;
-/** The total number of points to register */
-int max_registrations_;
-/** The list of 2D points to register the model */
-std::vector<cv::Point2f> list_points2d_;
-/** The list of 3D points to register the model */
-std::vector<cv::Point3f> list_points3d_;
-};
-
-#endif /* MODELREGISTRATION_H_ */
+++ /dev/null
-/*
- * PnPProblem.cpp
- *
- * Created on: Mar 28, 2014
- * Author: Edgar Riba
- */
-
-#include <iostream>
-#include <sstream>
-
-#include "PnPProblem.h"
-#include "Mesh.h"
-
-#include <opencv2/calib3d/calib3d.hpp>
-
-
-/* Functions for Möller–Trumbore intersection algorithm
- * */
-cv::Point3f CROSS(cv::Point3f v1, cv::Point3f v2)
-{
- cv::Point3f tmp_p;
- tmp_p.x = v1.y*v2.z - v1.z*v2.y;
- tmp_p.y = v1.z*v2.x - v1.x*v2.z;
- tmp_p.z = v1.x*v2.y - v1.y*v2.x;
- return tmp_p;
-}
-
-double DOT(cv::Point3f v1, cv::Point3f v2)
-{
- return v1.x*v2.x + v1.y*v2.y + v1.z*v2.z;
-}
-
-cv::Point3f SUB(cv::Point3f v1, cv::Point3f v2)
-{
- cv::Point3f tmp_p;
- tmp_p.x = v1.x - v2.x;
- tmp_p.y = v1.y - v2.y;
- tmp_p.z = v1.z - v2.z;
- return tmp_p;
-}
-
-/* End functions for Möller–Trumbore intersection algorithm
- * */
-
-// Function to get the nearest 3D point to the Ray origin
-cv::Point3f get_nearest_3D_point(std::vector<cv::Point3f> &points_list, cv::Point3f origin)
-{
- cv::Point3f p1 = points_list[0];
- cv::Point3f p2 = points_list[1];
-
- double d1 = std::sqrt( std::pow(p1.x-origin.x, 2) + std::pow(p1.y-origin.y, 2) + std::pow(p1.z-origin.z, 2) );
- double d2 = std::sqrt( std::pow(p2.x-origin.x, 2) + std::pow(p2.y-origin.y, 2) + std::pow(p2.z-origin.z, 2) );
-
- if(d1 < d2)
- {
- return p1;
- }
- else
- {
- return p2;
- }
-}
-
-// Custom constructor given the intrinsic camera parameters
-
-PnPProblem::PnPProblem(const double params[])
-{
- _A_matrix = cv::Mat::zeros(3, 3, CV_64FC1); // intrinsic camera parameters
- _A_matrix.at<double>(0, 0) = params[0]; // [ fx 0 cx ]
- _A_matrix.at<double>(1, 1) = params[1]; // [ 0 fy cy ]
- _A_matrix.at<double>(0, 2) = params[2]; // [ 0 0 1 ]
- _A_matrix.at<double>(1, 2) = params[3];
- _A_matrix.at<double>(2, 2) = 1;
- _R_matrix = cv::Mat::zeros(3, 3, CV_64FC1); // rotation matrix
- _t_matrix = cv::Mat::zeros(3, 1, CV_64FC1); // translation matrix
- _P_matrix = cv::Mat::zeros(3, 4, CV_64FC1); // rotation-translation matrix
-
-}
-
-PnPProblem::~PnPProblem()
-{
- // TODO Auto-generated destructor stub
-}
-
-void PnPProblem::set_P_matrix( const cv::Mat &R_matrix, const cv::Mat &t_matrix)
-{
- // Rotation-Translation Matrix Definition
- _P_matrix.at<double>(0,0) = R_matrix.at<double>(0,0);
- _P_matrix.at<double>(0,1) = R_matrix.at<double>(0,1);
- _P_matrix.at<double>(0,2) = R_matrix.at<double>(0,2);
- _P_matrix.at<double>(1,0) = R_matrix.at<double>(1,0);
- _P_matrix.at<double>(1,1) = R_matrix.at<double>(1,1);
- _P_matrix.at<double>(1,2) = R_matrix.at<double>(1,2);
- _P_matrix.at<double>(2,0) = R_matrix.at<double>(2,0);
- _P_matrix.at<double>(2,1) = R_matrix.at<double>(2,1);
- _P_matrix.at<double>(0,3) = t_matrix.at<double>(0);
- _P_matrix.at<double>(1,3) = t_matrix.at<double>(1);
- _P_matrix.at<double>(2,3) = t_matrix.at<double>(2);
-}
-
-
-// Estimate the pose given a list of 2D/3D correspondences and the method to use
-bool PnPProblem::estimatePose( const std::vector<cv::Point3f> &list_points3d,
- const std::vector<cv::Point2f> &list_points2d,
- int flags)
-{
- cv::Mat distCoeffs = cv::Mat::zeros(4, 1, CV_64FC1);
- cv::Mat rvec = cv::Mat::zeros(3, 1, CV_64FC1);
- cv::Mat tvec = cv::Mat::zeros(3, 1, CV_64FC1);
-
- bool useExtrinsicGuess = false;
-
- // Pose estimation
- bool correspondence = cv::solvePnP( list_points3d, list_points2d, _A_matrix, distCoeffs, rvec, tvec,
- useExtrinsicGuess, flags);
-
- // Transforms Rotation Vector to Matrix
- Rodrigues(rvec,_R_matrix);
- _t_matrix = tvec;
-
- // Set projection matrix
- this->set_P_matrix(_R_matrix, _t_matrix);
-
- return correspondence;
-}
-
-// Estimate the pose given a list of 2D/3D correspondences with RANSAC and the method to use
-
-void PnPProblem::estimatePoseRANSAC( const std::vector<cv::Point3f> &list_points3d, // list with model 3D coordinates
- const std::vector<cv::Point2f> &list_points2d, // list with scene 2D coordinates
- int flags, cv::Mat &inliers, int iterationsCount, // PnP method; inliers container
- float reprojectionError, float confidence ) // Ransac parameters
-{
- cv::Mat distCoeffs = cv::Mat::zeros(4, 1, CV_64FC1); // vector of distortion coefficients
- cv::Mat rvec = cv::Mat::zeros(3, 1, CV_64FC1); // output rotation vector
- cv::Mat tvec = cv::Mat::zeros(3, 1, CV_64FC1); // output translation vector
-
- bool useExtrinsicGuess = false; // if true the function uses the provided rvec and tvec values as
- // initial approximations of the rotation and translation vectors
-
- cv::solvePnPRansac( list_points3d, list_points2d, _A_matrix, distCoeffs, rvec, tvec,
- useExtrinsicGuess, iterationsCount, reprojectionError, confidence,
- inliers, flags );
-
- Rodrigues(rvec,_R_matrix); // converts Rotation Vector to Matrix
- _t_matrix = tvec; // set translation matrix
-
- this->set_P_matrix(_R_matrix, _t_matrix); // set rotation-translation matrix
-
-}
-
-// Given the mesh, backproject the 3D points to 2D to verify the pose estimation
-std::vector<cv::Point2f> PnPProblem::verify_points(Mesh *mesh)
-{
- std::vector<cv::Point2f> verified_points_2d;
- for( int i = 0; i < mesh->getNumVertices(); i++)
- {
- cv::Point3f point3d = mesh->getVertex(i);
- cv::Point2f point2d = this->backproject3DPoint(point3d);
- verified_points_2d.push_back(point2d);
- }
-
- return verified_points_2d;
-}
-
-
-// Backproject a 3D point to 2D using the estimated pose parameters
-
-cv::Point2f PnPProblem::backproject3DPoint(const cv::Point3f &point3d)
-{
- // 3D point vector [x y z 1]'
- cv::Mat point3d_vec = cv::Mat(4, 1, CV_64FC1);
- point3d_vec.at<double>(0) = point3d.x;
- point3d_vec.at<double>(1) = point3d.y;
- point3d_vec.at<double>(2) = point3d.z;
- point3d_vec.at<double>(3) = 1;
-
- // 2D point vector [u v 1]'
- cv::Mat point2d_vec = cv::Mat(4, 1, CV_64FC1);
- point2d_vec = _A_matrix * _P_matrix * point3d_vec;
-
- // Normalization of [u v]'
- cv::Point2f point2d;
- point2d.x = point2d_vec.at<double>(0) / point2d_vec.at<double>(2);
- point2d.y = point2d_vec.at<double>(1) / point2d_vec.at<double>(2);
-
- return point2d;
-}
-
-// Back project a 2D point to 3D and returns if it's on the object surface
-bool PnPProblem::backproject2DPoint(const Mesh *mesh, const cv::Point2f &point2d, cv::Point3f &point3d)
-{
- // Triangles list of the object mesh
- std::vector<std::vector<int> > triangles_list = mesh->getTrianglesList();
-
- double lambda = 8;
- double u = point2d.x;
- double v = point2d.y;
-
- // Point in vector form
- cv::Mat point2d_vec = cv::Mat::ones(3, 1, CV_64F); // 3x1
- point2d_vec.at<double>(0) = u * lambda;
- point2d_vec.at<double>(1) = v * lambda;
- point2d_vec.at<double>(2) = lambda;
-
- // Point in camera coordinates
- cv::Mat X_c = _A_matrix.inv() * point2d_vec ; // 3x1
-
- // Point in world coordinates
- cv::Mat X_w = _R_matrix.inv() * ( X_c - _t_matrix ); // 3x1
-
- // Center of projection
- cv::Mat C_op = cv::Mat(_R_matrix.inv()).mul(-1) * _t_matrix; // 3x1
-
- // Ray direction vector
- cv::Mat ray = X_w - C_op; // 3x1
- ray = ray / cv::norm(ray); // 3x1
-
- // Set up Ray
- Ray R((cv::Point3f)C_op, (cv::Point3f)ray);
-
- // A vector to store the intersections found
- std::vector<cv::Point3f> intersections_list;
-
- // Loop for all the triangles and check the intersection
- for (unsigned int i = 0; i < triangles_list.size(); i++)
- {
- cv::Point3f V0 = mesh->getVertex(triangles_list[i][0]);
- cv::Point3f V1 = mesh->getVertex(triangles_list[i][1]);
- cv::Point3f V2 = mesh->getVertex(triangles_list[i][2]);
-
- Triangle T(i, V0, V1, V2);
-
- double out;
- if(this->intersect_MollerTrumbore(R, T, &out))
- {
- cv::Point3f tmp_pt = R.getP0() + out*R.getP1(); // P = O + t*D
- intersections_list.push_back(tmp_pt);
- }
- }
-
- // If there are intersection, find the nearest one
- if (!intersections_list.empty())
- {
- point3d = get_nearest_3D_point(intersections_list, R.getP0());
- return true;
- }
- else
- {
- return false;
- }
-}
-
-// Möller–Trumbore intersection algorithm
-bool PnPProblem::intersect_MollerTrumbore(Ray &Ray, Triangle &Triangle, double *out)
-{
- const double EPSILON = 0.000001;
-
- cv::Point3f e1, e2;
- cv::Point3f P, Q, T;
- double det, inv_det, u, v;
- double t;
-
- cv::Point3f V1 = Triangle.getV0(); // Triangle vertices
- cv::Point3f V2 = Triangle.getV1();
- cv::Point3f V3 = Triangle.getV2();
-
- cv::Point3f O = Ray.getP0(); // Ray origin
- cv::Point3f D = Ray.getP1(); // Ray direction
-
- //Find vectors for two edges sharing V1
- e1 = SUB(V2, V1);
- e2 = SUB(V3, V1);
-
- // Begin calculation determinant - also used to calculate U parameter
- P = CROSS(D, e2);
-
- // If determinant is near zero, ray lie in plane of triangle
- det = DOT(e1, P);
-
- //NOT CULLING
- if(det > -EPSILON && det < EPSILON) return false;
- inv_det = 1.f / det;
-
- //calculate distance from V1 to ray origin
- T = SUB(O, V1);
-
- //Calculate u parameter and test bound
- u = DOT(T, P) * inv_det;
-
- //The intersection lies outside of the triangle
- if(u < 0.f || u > 1.f) return false;
-
- //Prepare to test v parameter
- Q = CROSS(T, e1);
-
- //Calculate V parameter and test bound
- v = DOT(D, Q) * inv_det;
-
- //The intersection lies outside of the triangle
- if(v < 0.f || u + v > 1.f) return false;
-
- t = DOT(e2, Q) * inv_det;
-
- if(t > EPSILON) { //ray intersection
- *out = t;
- return true;
- }
-
- // No hit, no win
- return false;
-}
+++ /dev/null
-/*
- * PnPProblem.h
- *
- * Created on: Mar 28, 2014
- * Author: Edgar Riba
- */
-
-#ifndef PNPPROBLEM_H_
-#define PNPPROBLEM_H_
-
-#include <iostream>
-
-#include <opencv2/core/core.hpp>
-#include <opencv2/highgui/highgui.hpp>
-
-#include "Mesh.h"
-#include "ModelRegistration.h"
-
-class PnPProblem
-{
-
-public:
- explicit PnPProblem(const double param[]); // custom constructor
- virtual ~PnPProblem();
-
- bool backproject2DPoint(const Mesh *mesh, const cv::Point2f &point2d, cv::Point3f &point3d);
- bool intersect_MollerTrumbore(Ray &R, Triangle &T, double *out);
- std::vector<cv::Point2f> verify_points(Mesh *mesh);
- cv::Point2f backproject3DPoint(const cv::Point3f &point3d);
- bool estimatePose(const std::vector<cv::Point3f> &list_points3d, const std::vector<cv::Point2f> &list_points2d, int flags);
- void estimatePoseRANSAC( const std::vector<cv::Point3f> &list_points3d, const std::vector<cv::Point2f> &list_points2d,
- int flags, cv::Mat &inliers,
- int iterationsCount, float reprojectionError, float confidence );
-
- cv::Mat get_A_matrix() const { return _A_matrix; }
- cv::Mat get_R_matrix() const { return _R_matrix; }
- cv::Mat get_t_matrix() const { return _t_matrix; }
- cv::Mat get_P_matrix() const { return _P_matrix; }
-
- void set_P_matrix( const cv::Mat &R_matrix, const cv::Mat &t_matrix);
-
-private:
- /** The calibration matrix */
- cv::Mat _A_matrix;
- /** The computed rotation matrix */
- cv::Mat _R_matrix;
- /** The computed translation matrix */
- cv::Mat _t_matrix;
- /** The computed projection matrix */
- cv::Mat _P_matrix;
-};
-
-#endif /* PNPPROBLEM_H_ */
+++ /dev/null
-/*
- * RobustMatcher.cpp
- *
- * Created on: Jun 4, 2014
- * Author: eriba
- */
-
-#include "RobustMatcher.h"
-#include <time.h>
-
-#include <opencv2/features2d/features2d.hpp>
-
-RobustMatcher::~RobustMatcher()
-{
- // TODO Auto-generated destructor stub
-}
-
-void RobustMatcher::computeKeyPoints( const cv::Mat& image, std::vector<cv::KeyPoint>& keypoints)
-{
- detector_->detect(image, keypoints);
-}
-
-void RobustMatcher::computeDescriptors( const cv::Mat& image, std::vector<cv::KeyPoint>& keypoints, cv::Mat& descriptors)
-{
- extractor_->compute(image, keypoints, descriptors);
-}
-
-int RobustMatcher::ratioTest(std::vector<std::vector<cv::DMatch> > &matches)
-{
- int removed = 0;
- // for all matches
- for ( std::vector<std::vector<cv::DMatch> >::iterator
- matchIterator= matches.begin(); matchIterator!= matches.end(); ++matchIterator)
- {
- // if 2 NN has been identified
- if (matchIterator->size() > 1)
- {
- // check distance ratio
- if ((*matchIterator)[0].distance / (*matchIterator)[1].distance > ratio_)
- {
- matchIterator->clear(); // remove match
- removed++;
- }
- }
- else
- { // does not have 2 neighbours
- matchIterator->clear(); // remove match
- removed++;
- }
- }
- return removed;
-}
-
-void RobustMatcher::symmetryTest( const std::vector<std::vector<cv::DMatch> >& matches1,
- const std::vector<std::vector<cv::DMatch> >& matches2,
- std::vector<cv::DMatch>& symMatches )
-{
-
- // for all matches image 1 -> image 2
- for (std::vector<std::vector<cv::DMatch> >::const_iterator
- matchIterator1 = matches1.begin(); matchIterator1 != matches1.end(); ++matchIterator1)
- {
-
- // ignore deleted matches
- if (matchIterator1->empty() || matchIterator1->size() < 2)
- continue;
-
- // for all matches image 2 -> image 1
- for (std::vector<std::vector<cv::DMatch> >::const_iterator
- matchIterator2 = matches2.begin(); matchIterator2 != matches2.end(); ++matchIterator2)
- {
- // ignore deleted matches
- if (matchIterator2->empty() || matchIterator2->size() < 2)
- continue;
-
- // Match symmetry test
- if ((*matchIterator1)[0].queryIdx ==
- (*matchIterator2)[0].trainIdx &&
- (*matchIterator2)[0].queryIdx ==
- (*matchIterator1)[0].trainIdx)
- {
- // add symmetrical match
- symMatches.push_back(
- cv::DMatch((*matchIterator1)[0].queryIdx,
- (*matchIterator1)[0].trainIdx,
- (*matchIterator1)[0].distance));
- break; // next match in image 1 -> image 2
- }
- }
- }
-
-}
-
-void RobustMatcher::robustMatch( const cv::Mat& frame, std::vector<cv::DMatch>& good_matches,
- std::vector<cv::KeyPoint>& keypoints_frame, const cv::Mat& descriptors_model )
-{
-
- // 1a. Detection of the ORB features
- this->computeKeyPoints(frame, keypoints_frame);
-
- // 1b. Extraction of the ORB descriptors
- cv::Mat descriptors_frame;
- this->computeDescriptors(frame, keypoints_frame, descriptors_frame);
-
- // 2. Match the two image descriptors
- std::vector<std::vector<cv::DMatch> > matches12, matches21;
-
- // 2a. From image 1 to image 2
- matcher_->knnMatch(descriptors_frame, descriptors_model, matches12, 2); // return 2 nearest neighbours
-
- // 2b. From image 2 to image 1
- matcher_->knnMatch(descriptors_model, descriptors_frame, matches21, 2); // return 2 nearest neighbours
-
- // 3. Remove matches for which NN ratio is > than threshold
- // clean image 1 -> image 2 matches
- int removed1 = ratioTest(matches12);
- // clean image 2 -> image 1 matches
- int removed2 = ratioTest(matches21);
-
- // 4. Remove non-symmetrical matches
- symmetryTest(matches12, matches21, good_matches);
-
-}
-
-void RobustMatcher::fastRobustMatch( const cv::Mat& frame, std::vector<cv::DMatch>& good_matches,
- std::vector<cv::KeyPoint>& keypoints_frame,
- const cv::Mat& descriptors_model )
-{
- good_matches.clear();
-
- // 1a. Detection of the ORB features
- this->computeKeyPoints(frame, keypoints_frame);
-
- // 1b. Extraction of the ORB descriptors
- cv::Mat descriptors_frame;
- this->computeDescriptors(frame, keypoints_frame, descriptors_frame);
-
- // 2. Match the two image descriptors
- std::vector<std::vector<cv::DMatch> > matches;
- matcher_->knnMatch(descriptors_frame, descriptors_model, matches, 2);
-
- // 3. Remove matches for which NN ratio is > than threshold
- int removed = ratioTest(matches);
-
- // 4. Fill good matches container
- for ( std::vector<std::vector<cv::DMatch> >::iterator
- matchIterator= matches.begin(); matchIterator!= matches.end(); ++matchIterator)
- {
- if (!matchIterator->empty()) good_matches.push_back((*matchIterator)[0]);
- }
-
-}
+++ /dev/null
-/*
- * RobustMatcher.h
- *
- * Created on: Jun 4, 2014
- * Author: eriba
- */
-
-#ifndef ROBUSTMATCHER_H_
-#define ROBUSTMATCHER_H_
-
-#include <iostream>
-#include <boost/shared_ptr.hpp>
-
-#include <opencv2/core/core.hpp>
-#include <opencv2/highgui/highgui.hpp>
-#include <opencv2/features2d/features2d.hpp>
-#include <opencv2/nonfree/nonfree.hpp>
-
-class RobustMatcher {
-public:
- RobustMatcher() : ratio_(0.8f)
- {
- // ORB is the default feature
- detector_ = new cv::OrbFeatureDetector();
- extractor_ = new cv::OrbDescriptorExtractor();
-
- // BruteFroce matcher with Norm Hamming is the default matcher
- matcher_ = new cv::BFMatcher(cv::NORM_HAMMING, false);
-
- }
- virtual ~RobustMatcher();
-
- // Set the feature detector
- void setFeatureDetector(cv::FeatureDetector * detect) { detector_ = detect; }
-
- // Set the descriptor extractor
- void setDescriptorExtractor(cv::DescriptorExtractor * desc) { extractor_ = desc; }
-
- // Set the matcher
- void setDescriptorMatcher(cv::DescriptorMatcher * match) { matcher_ = match; }
-
- // Compute the keypoints of an image
- void computeKeyPoints( const cv::Mat& image, std::vector<cv::KeyPoint>& keypoints);
-
- // Compute the descriptors of an image given its keypoints
- void computeDescriptors( const cv::Mat& image, std::vector<cv::KeyPoint>& keypoints, cv::Mat& descriptors);
-
- // Set ratio parameter for the ratio test
- void setRatio( float rat) { ratio_ = rat; }
-
- // Clear matches for which NN ratio is > than threshold
- // return the number of removed points
- // (corresponding entries being cleared,
- // i.e. size will be 0)
- int ratioTest(std::vector<std::vector<cv::DMatch> > &matches);
-
- // Insert symmetrical matches in symMatches vector
- void symmetryTest( const std::vector<std::vector<cv::DMatch> >& matches1,
- const std::vector<std::vector<cv::DMatch> >& matches2,
- std::vector<cv::DMatch>& symMatches );
-
- // Match feature points using ratio and symmetry test
- void robustMatch( const cv::Mat& frame, std::vector<cv::DMatch>& good_matches,
- std::vector<cv::KeyPoint>& keypoints_frame,
- const cv::Mat& descriptors_model );
-
- // Match feature points using ratio test
- void fastRobustMatch( const cv::Mat& frame, std::vector<cv::DMatch>& good_matches,
- std::vector<cv::KeyPoint>& keypoints_frame,
- const cv::Mat& descriptors_model );
-
-private:
- // pointer to the feature point detector object
- cv::FeatureDetector * detector_;
- // pointer to the feature descriptor extractor object
- cv::DescriptorExtractor * extractor_;
- // pointer to the matcher object
- cv::DescriptorMatcher * matcher_;
- // max ratio between 1st and 2nd NN
- float ratio_;
-};
-
-#endif /* ROBUSTMATCHER_H_ */
+++ /dev/null
-/*
- * Utils.cpp
- *
- * Created on: Mar 28, 2014
- * Author: Edgar Riba
- */
-
-#include <iostream>
-
-#include "PnPProblem.h"
-#include "ModelRegistration.h"
-#include "Utils.h"
-
-#include <opencv2/imgproc/imgproc.hpp>
-#include <opencv2/calib3d/calib3d.hpp>
-#include <opencv2/nonfree/features2d.hpp>
-
-
-// For text
-int fontFace = cv::FONT_ITALIC;
-double fontScale = 0.75;
-double thickness_font = 2;
-
-// For circles
-int lineType = 8;
-int radius = 4;
-double thickness_circ = -1;
-
-// Draw a text with the question point
-void drawQuestion(cv::Mat image, cv::Point3f point, cv::Scalar color)
-{
- std::string x = IntToString((int)point.x);
- std::string y = IntToString((int)point.y);
- std::string z = IntToString((int)point.z);
-
- std::string text = " Where is point (" + x + "," + y + "," + z + ") ?";
- cv::putText(image, text, cv::Point(25,50), fontFace, fontScale, color, thickness_font, 8);
-}
-
-// Draw a text with the number of entered points
-void drawText(cv::Mat image, std::string text, cv::Scalar color)
-{
- cv::putText(image, text, cv::Point(25,50), fontFace, fontScale, color, thickness_font, 8);
-}
-
-// Draw a text with the number of entered points
-void drawText2(cv::Mat image, std::string text, cv::Scalar color)
-{
- cv::putText(image, text, cv::Point(25,75), fontFace, fontScale, color, thickness_font, 8);
-}
-
-// Draw a text with the frame ratio
-void drawFPS(cv::Mat image, double fps, cv::Scalar color)
-{
- std::string fps_str = IntToString((int)fps);
- std::string text = fps_str + " FPS";
- cv::putText(image, text, cv::Point(500,50), fontFace, fontScale, color, thickness_font, 8);
-}
-
-// Draw a text with the frame ratio
-void drawConfidence(cv::Mat image, double confidence, cv::Scalar color)
-{
- std::string conf_str = IntToString((int)confidence);
- std::string text = conf_str + " %";
- cv::putText(image, text, cv::Point(500,75), fontFace, fontScale, color, thickness_font, 8);
-}
-
-// Draw a text with the number of entered points
-void drawCounter(cv::Mat image, int n, int n_max, cv::Scalar color)
-{
- std::string n_str = IntToString(n);
- std::string n_max_str = IntToString(n_max);
- std::string text = n_str + " of " + n_max_str + " points";
- cv::putText(image, text, cv::Point(500,50), fontFace, fontScale, color, thickness_font, 8);
-}
-
-// Draw the points and the coordinates
-void drawPoints(cv::Mat image, std::vector<cv::Point2f> &list_points_2d, std::vector<cv::Point3f> &list_points_3d, cv::Scalar color)
-{
- for (unsigned int i = 0; i < list_points_2d.size(); ++i)
- {
- cv::Point2f point_2d = list_points_2d[i];
- cv::Point3f point_3d = list_points_3d[i];
-
- // Draw Selected points
- cv::circle(image, point_2d, radius, color, -1, lineType );
-
- std::string idx = IntToString(i+1);
- std::string x = IntToString((int)point_3d.x);
- std::string y = IntToString((int)point_3d.y);
- std::string z = IntToString((int)point_3d.z);
- std::string text = "P" + idx + " (" + x + "," + y + "," + z +")";
-
- point_2d.x = point_2d.x + 10;
- point_2d.y = point_2d.y - 10;
- cv::putText(image, text, point_2d, fontFace, fontScale*0.5, color, thickness_font, 8);
- }
-}
-
-// Draw only the points
-void draw2DPoints(cv::Mat image, std::vector<cv::Point2f> &list_points, cv::Scalar color)
-{
- for( size_t i = 0; i < list_points.size(); i++)
- {
- cv::Point2f point_2d = list_points[i];
-
- // Draw Selected points
- cv::circle(image, point_2d, radius, color, -1, lineType );
- }
-}
-
-void drawArrow(cv::Mat image, cv::Point2i p, cv::Point2i q, cv::Scalar color, int arrowMagnitude, int thickness, int line_type, int shift)
-{
- //Draw the principle line
- cv::line(image, p, q, color, thickness, line_type, shift);
- const double PI = 3.141592653;
- //compute the angle alpha
- double angle = atan2((double)p.y-q.y, (double)p.x-q.x);
- //compute the coordinates of the first segment
- p.x = (int) ( q.x + arrowMagnitude * cos(angle + PI/4));
- p.y = (int) ( q.y + arrowMagnitude * sin(angle + PI/4));
- //Draw the first segment
- cv::line(image, p, q, color, thickness, line_type, shift);
- //compute the coordinates of the second segment
- p.x = (int) ( q.x + arrowMagnitude * cos(angle - PI/4));
- p.y = (int) ( q.y + arrowMagnitude * sin(angle - PI/4));
- //Draw the second segment
- cv::line(image, p, q, color, thickness, line_type, shift);
-}
-
-void draw3DCoordinateAxes(cv::Mat image, const std::vector<cv::Point2f> &list_points2d)
-{
- cv::Scalar red(0, 0, 255);
- cv::Scalar green(0,255,0);
- cv::Scalar blue(255,0,0);
- cv::Scalar black(0,0,0);
-
- const double PI = 3.141592653;
- int length = 50;
-
- cv::Point2i origin = list_points2d[0];
- cv::Point2i pointX = list_points2d[1];
- cv::Point2i pointY = list_points2d[2];
- cv::Point2i pointZ = list_points2d[3];
-
- drawArrow(image, origin, pointX, red, 9, 2);
- drawArrow(image, origin, pointY, blue, 9, 2);
- drawArrow(image, origin, pointZ, green, 9, 2);
- cv::circle(image, origin, radius/2, black, -1, lineType );
-
-}
-
-// Draw the object mesh
-void drawObjectMesh(cv::Mat image, const Mesh *mesh, PnPProblem *pnpProblem, cv::Scalar color)
-{
- std::vector<std::vector<int> > list_triangles = mesh->getTrianglesList();
- for( size_t i = 0; i < list_triangles.size(); i++)
- {
- std::vector<int> tmp_triangle = list_triangles.at(i);
-
- cv::Point3f point_3d_0 = mesh->getVertex(tmp_triangle[0]);
- cv::Point3f point_3d_1 = mesh->getVertex(tmp_triangle[1]);
- cv::Point3f point_3d_2 = mesh->getVertex(tmp_triangle[2]);
-
- cv::Point2f point_2d_0 = pnpProblem->backproject3DPoint(point_3d_0);
- cv::Point2f point_2d_1 = pnpProblem->backproject3DPoint(point_3d_1);
- cv::Point2f point_2d_2 = pnpProblem->backproject3DPoint(point_3d_2);
-
- cv::line(image, point_2d_0, point_2d_1, color, 1);
- cv::line(image, point_2d_1, point_2d_2, color, 1);
- cv::line(image, point_2d_2, point_2d_0, color, 1);
- }
-}
-
-bool equal_point(const cv::Point2f &p1, const cv::Point2f &p2)
-{
- return ( (p1.x == p2.x) && (p1.y == p2.y) );
-}
-
-double get_translation_error(const cv::Mat &t_true, const cv::Mat &t)
-{
- return cv::norm( t_true - t );
-}
-
-double get_rotation_error(const cv::Mat &R_true, const cv::Mat &R)
-{
- cv::Mat error_vec, error_mat;
- error_mat = R_true * cv::Mat(R.inv()).mul(-1);
- cv::Rodrigues(error_mat, error_vec);
-
- return cv::norm(error_vec);
-}
-
-cv::Mat rot2euler(const cv::Mat & rotationMatrix)
-{
- cv::Mat euler(3,1,CV_64F);
-
- double m00 = rotationMatrix.at<double>(0,0);
- double m01 = rotationMatrix.at<double>(0,1);
- double m02 = rotationMatrix.at<double>(0,2);
- double m10 = rotationMatrix.at<double>(1,0);
- double m11 = rotationMatrix.at<double>(1,1);
- double m12 = rotationMatrix.at<double>(1,2);
- double m20 = rotationMatrix.at<double>(2,0);
- double m21 = rotationMatrix.at<double>(2,1);
- double m22 = rotationMatrix.at<double>(2,2);
-
- double x, y, z;
-
- // Assuming the angles are in radians.
- if (m10 > 0.998) { // singularity at north pole
- x = 0;
- y = CV_PI/2;
- z = atan2(m02,m22);
- }
- else if (m10 < -0.998) { // singularity at south pole
- x = 0;
- y = -CV_PI/2;
- z = atan2(m02,m22);
- }
- else
- {
- x = atan2(-m12,m11);
- y = asin(m10);
- z = atan2(-m20,m00);
- }
-
- euler.at<double>(0) = x;
- euler.at<double>(1) = y;
- euler.at<double>(2) = z;
-
- return euler;
-}
-
-cv::Mat euler2rot(const cv::Mat & euler)
-{
- cv::Mat rotationMatrix(3,3,CV_64F);
-
- double x = euler.at<double>(0);
- double y = euler.at<double>(1);
- double z = euler.at<double>(2);
-
- // Assuming the angles are in radians.
- double ch = cos(z);
- double sh = sin(z);
- double ca = cos(y);
- double sa = sin(y);
- double cb = cos(x);
- double sb = sin(x);
-
- double m00, m01, m02, m10, m11, m12, m20, m21, m22;
-
- m00 = ch * ca;
- m01 = sh*sb - ch*sa*cb;
- m02 = ch*sa*sb + sh*cb;
- m10 = sa;
- m11 = ca*cb;
- m12 = -ca*sb;
- m20 = -sh*ca;
- m21 = sh*sa*cb + ch*sb;
- m22 = -sh*sa*sb + ch*cb;
-
- rotationMatrix.at<double>(0,0) = m00;
- rotationMatrix.at<double>(0,1) = m01;
- rotationMatrix.at<double>(0,2) = m02;
- rotationMatrix.at<double>(1,0) = m10;
- rotationMatrix.at<double>(1,1) = m11;
- rotationMatrix.at<double>(1,2) = m12;
- rotationMatrix.at<double>(2,0) = m20;
- rotationMatrix.at<double>(2,1) = m21;
- rotationMatrix.at<double>(2,2) = m22;
-
- return rotationMatrix;
-}
-
-int StringToInt ( const std::string &Text )
-{
- std::istringstream ss(Text);
- int result;
- return ss >> result ? result : 0;
-}
-
-std::string FloatToString ( float Number )
-{
- std::ostringstream ss;
- ss << Number;
- return ss.str();
-}
-
-std::string IntToString ( int Number )
-{
- std::ostringstream ss;
- ss << Number;
- return ss.str();
-}
+++ /dev/null
-/*
- * Utils.h
- *
- * Created on: Mar 28, 2014
- * Author: Edgar Riba
- */
-
-#ifndef UTILS_H_
-#define UTILS_H_
-
-#include <iostream>
-#include <cv.h>
-
-#include "PnPProblem.h"
-
-// Draw a text with the question point
-void drawQuestion(cv::Mat image, cv::Point3f point, cv::Scalar color);
-
-// Draw a text in the left of the image
-void drawText(cv::Mat image, std::string text, cv::Scalar color);
-void drawText2(cv::Mat image, std::string text, cv::Scalar color);
-void drawFPS(cv::Mat image, double fps, cv::Scalar color);
-void drawConfidence(cv::Mat image, double confidence, cv::Scalar color);
-
-// Draw a text with the number of registered points
-void drawCounter(cv::Mat image, int n, int n_max, cv::Scalar color);
-
-// Draw the points and the coordinates
-void drawPoints(cv::Mat image, std::vector<cv::Point2f> &list_points_2d, std::vector<cv::Point3f> &list_points_3d, cv::Scalar color);
-
-// Draw only the points
-void draw2DPoints(cv::Mat image, std::vector<cv::Point2f> &list_points, cv::Scalar color);
-
-// Draw the object mesh
-void drawObjectMesh(cv::Mat image, const Mesh *mesh, PnPProblem *pnpProblem, cv::Scalar color);
-
-// Draw an arrow into the image
-void drawArrow(cv::Mat image, cv::Point2i p, cv::Point2i q, cv::Scalar color, int arrowMagnitude = 9, int thickness=1, int line_type=8, int shift=0);
-
-// Draw the 3D coordinate axes
-void draw3DCoordinateAxes(cv::Mat image, const std::vector<cv::Point2f> &list_points2d);
-
-// Compute the 2D points with the esticv::Mated pose
-std::vector<cv::Point2f> verification_points(PnPProblem *p);
-
-bool equal_point(const cv::Point2f &p1, const cv::Point2f &p2);
-
-double get_translation_error(const cv::Mat &t_true, const cv::Mat &t);
-double get_rotation_error(const cv::Mat &R_true, const cv::Mat &R);
-double get_variance(const std::vector<cv::Point3f> list_points3d);
-cv::Mat rot2quat(cv::Mat &rotationMatrix);
-cv::Mat quat2rot(cv::Mat &q);
-cv::Mat euler2rot(const cv::Mat & euler);
-cv::Mat rot2euler(const cv::Mat & rotationMatrix);
-cv::Mat quat2euler(const cv::Mat & q);
-int StringToInt ( const std::string &Text );
-std::string FloatToString ( float Number );
-std::string IntToString ( int Number );
-
-class Timer
-{
-public:
- Timer();
- void start() { tstart = (double)clock()/CLOCKS_PER_SEC; }
- void stop() { tstop = (double)clock()/CLOCKS_PER_SEC; }
- void reset() { tstart = 0; tstop = 0;}
-
- double getTimeMilli() const { return (tstop-tstart)*1000; }
- double getTimeSec() const { return tstop-tstart; }
-
-private:
- double tstart, tstop, ttime;
-};
-
-#endif /* UTILS_H_ */
+++ /dev/null
-#include <iostream>
-#include <time.h>
-
-#include "cv.h"
-#include "highgui.h"
-
-#include <opencv2/core/core.hpp>
-#include <opencv2/highgui/highgui.hpp>
-#include <opencv2/imgproc/imgproc.hpp>
-#include <opencv2/calib3d/calib3d.hpp>
-#include <opencv2/video/tracking.hpp>
-
-#include "Mesh.h"
-#include "Model.h"
-#include "PnPProblem.h"
-#include "RobustMatcher.h"
-#include "ModelRegistration.h"
-#include "Utils.h"
-
-// COOKIES BOX - ORB
-std::string yml_read_path = "../Data/cookies_ORB.yml"; // 3dpts + descriptors
-
-// COOKIES BOX MESH
-std::string ply_read_path = "../Data/box.ply"; // mesh
-
-void help()
-{
-std::cout
-<< "--------------------------------------------------------------------------" << std::endl
-<< "This program shows how to detect an object given its 3D textured model. You can choose to "
-<< "use a recorded video or the webcam." << std::endl
-<< "Usage:" << std::endl
-<< "./pnp_detection ~/path_to_video/box.mp4" << std::endl
-<< "./pnp_detection " << std::endl
-<< "--------------------------------------------------------------------------" << std::endl
-<< std::endl;
-}
-
-
-/*
- * Set up the intrinsic camera parameters: UVC WEBCAM
- */
-
-double f = 55; // focal length in mm
-double sx = 22.3, sy = 14.9; // sensor size
-double width = 640, height = 480; // image size
-
-double params_WEBCAM[] = { width*f/sx, // fx
- height*f/sy, // fy
- width/2, // cx
- height/2}; // cy
-
-
-/*
- * Set up some basic colors
- */
-cv::Scalar red(0, 0, 255);
-cv::Scalar green(0,255,0);
-cv::Scalar blue(255,0,0);
-cv::Scalar yellow(0,255,255);
-
-
-// Robust Matcher parameters
-
-int numKeyPoints = 2000; // number of detected keypoints
-float ratio = 0.70f; // ratio test
-bool fast_match = true; // fastRobustMatch() or robustMatch()
-
-
-// RANSAC parameters
-
-int iterationsCount = 500; // number of Ransac iterations.
-float reprojectionError = 2.0; // maximum allowed distance to consider it an inlier.
-float confidence = 0.95; // ransac successful confidence.
-
-
-// Kalman Filter parameters
-
-int minInliersKalman = 30; // Kalman threshold updating
-
-
-/**********************************************************************************************************/
-
-void initKalmanFilter( cv::KalmanFilter &KF, int nStates, int nMeasurements, int nInputs, double dt);
-
-
-/**********************************************************************************************************/
-
-
-void updateKalmanFilter( cv::KalmanFilter &KF, cv::Mat &measurements,
- cv::Mat &translation_estimated, cv::Mat &rotation_estimated );
-
-/**********************************************************************************************************/
-
-
-void fillMeasurements( cv::Mat &measurements,
- const cv::Mat &translation_measured, const cv::Mat &rotation_measured);
-
-
-/**********************************************************************************************************/
-
-
-int main(int argc, char *argv[])
-{
-
- help();
-
- PnPProblem pnp_detection(params_WEBCAM);
- PnPProblem pnp_detection_est(params_WEBCAM);
-
- Model model; // instantiate Model object
- model.load(yml_read_path); // load a 3D textured object model
-
- Mesh mesh; // instantiate Mesh object
- mesh.load(ply_read_path); // load an object mesh
-
-
- RobustMatcher rmatcher; // instantiate RobustMatcher
-
- cv::FeatureDetector * detector = new cv::OrbFeatureDetector(numKeyPoints); // instatiate ORB feature detector
- cv::DescriptorExtractor * extractor = new cv::OrbDescriptorExtractor(); // instatiate ORB descriptor extractor
-
- rmatcher.setFeatureDetector(detector); // set feature detector
- rmatcher.setDescriptorExtractor(extractor); // set descriptor extractor
-
-
- cv::Ptr<cv::flann::IndexParams> indexParams = cv::makePtr<cv::flann::LshIndexParams>(6, 12, 1); // instantiate LSH index parameters
- cv::Ptr<cv::flann::SearchParams> searchParams = cv::makePtr<cv::flann::SearchParams>(50); // instantiate flann search parameters
-
- cv::DescriptorMatcher * matcher = new cv::FlannBasedMatcher(indexParams, searchParams); // instantiate FlannBased matcher
- rmatcher.setDescriptorMatcher(matcher); // set matcher
-
-
- rmatcher.setRatio(ratio); // set ratio test parameter
-
-
- cv::KalmanFilter KF; // instantiate Kalman Filter
-
- int nStates = 18; // the number of states
- int nMeasurements = 6; // the number of measured states
- int nInputs = 0; // the number of action control
-
- double dt = 0.125; // time between measurements (1/FPS)
-
- initKalmanFilter(KF, nStates, nMeasurements, nInputs, dt); // init function
-
- cv::Mat measurements(nMeasurements, 1, CV_64F); measurements.setTo(cv::Scalar(0));
- bool good_measurement = false;
-
-
- // Get the MODEL INFO
-
- std::vector<cv::Point3f> list_points3d_model = model.get_points3d(); // list with model 3D coordinates
- cv::Mat descriptors_model = model.get_descriptors(); // list with descriptors of each 3D coordinate
-
-
- // Create & Open Window
- cv::namedWindow("REAL TIME DEMO", CV_WINDOW_KEEPRATIO);
-
-
- cv::VideoCapture cap; // instantiate VideoCapture
- (argc < 2) ? cap.open(1) : cap.open(argv[1]); // open the default camera device
- // or a recorder video
-
- if(!cap.isOpened()) // check if we succeeded
- {
- std::cout << "Could not open the camera device" << std::endl;
- return -1;
- }
-
-
- // start and end times
- time_t start, end;
-
- // fps calculated using number of frames / seconds
- double fps;
-
- // frame counter
- int counter = 0;
-
- // floating point seconds elapsed since start
- double sec;
-
- // start the clock
- time(&start);
-
- double tstart2, tstop2, ttime2; // algorithm metrics
- double tstart, tstop, ttime; // algorithm metrics
-
- cv::Mat frame, frame_vis;
-
- while(cap.read(frame) && cv::waitKey(30) != 27) // capture frame until ESC is pressed
- {
-
- frame_vis = frame.clone(); // refresh visualisation frame
-
-
- // -- Step 1: Robust matching between model descriptors and scene descriptors
-
- std::vector<cv::DMatch> good_matches; // to obtain the 3D points of the model
- std::vector<cv::KeyPoint> keypoints_scene; // to obtain the 2D points of the scene
-
-
- if(fast_match)
- {
- rmatcher.fastRobustMatch(frame, good_matches, keypoints_scene, descriptors_model);
- }
- else
- {
- rmatcher.robustMatch(frame, good_matches, keypoints_scene, descriptors_model);
- }
-
-
- // -- Step 2: Find out the 2D/3D correspondences
-
- std::vector<cv::Point3f> list_points3d_model_match; // container for the model 3D coordinates found in the scene
- std::vector<cv::Point2f> list_points2d_scene_match; // container for the model 2D coordinates found in the scene
-
- for(unsigned int match_index = 0; match_index < good_matches.size(); ++match_index)
- {
- cv::Point3f point3d_model = list_points3d_model[ good_matches[match_index].trainIdx ]; // 3D point from model
- cv::Point2f point2d_scene = keypoints_scene[ good_matches[match_index].queryIdx ].pt; // 2D point from the scene
- list_points3d_model_match.push_back(point3d_model); // add 3D point
- list_points2d_scene_match.push_back(point2d_scene); // add 2D point
- }
-
- // Draw outliers
- draw2DPoints(frame_vis, list_points2d_scene_match, red);
-
-
- cv::Mat inliers_idx;
- std::vector<cv::Point2f> list_points2d_inliers;
-
- if(good_matches.size() > 0) // None matches, then RANSAC crashes
- {
-
-
- // -- Step 3: Estimate the pose using RANSAC approach
- pnp_detection.estimatePoseRANSAC( list_points3d_model_match, list_points2d_scene_match,
- cv::ITERATIVE, inliers_idx,
- iterationsCount, reprojectionError, confidence );
-
- // -- Step 4: Catch the inliers keypoints to draw
- for(int inliers_index = 0; inliers_index < inliers_idx.rows; ++inliers_index)
- {
- int n = inliers_idx.at<int>(inliers_index); // i-inlier
- cv::Point2f point2d = list_points2d_scene_match[n]; // i-inlier point 2D
- list_points2d_inliers.push_back(point2d); // add i-inlier to list
- }
-
- // Draw inliers points 2D
- draw2DPoints(frame_vis, list_points2d_inliers, blue);
-
-
- // -- Step 5: Kalman Filter
-
- good_measurement = false;
-
- // GOOD MEASUREMENT
- if( inliers_idx.rows >= minInliersKalman )
- {
-
- // Get the measured translation
- cv::Mat translation_measured(3, 1, CV_64F);
- translation_measured = pnp_detection.get_t_matrix();
-
- // Get the measured rotation
- cv::Mat rotation_measured(3, 3, CV_64F);
- rotation_measured = pnp_detection.get_R_matrix();
-
- // fill the measurements vector
- fillMeasurements(measurements, translation_measured, rotation_measured);
-
- good_measurement = true;
-
- }
-
- // Instantiate estimated translation and rotation
- cv::Mat translation_estimated(3, 1, CV_64F);
- cv::Mat rotation_estimated(3, 3, CV_64F);
-
- // update the Kalman filter with good measurements
- updateKalmanFilter( KF, measurements,
- translation_estimated, rotation_estimated);
-
-
- // -- Step 6: Set estimated projection matrix
- pnp_detection_est.set_P_matrix(rotation_estimated, translation_estimated);
-
- }
-
- // -- Step X: Draw pose
-
- if(good_measurement)
- {
- drawObjectMesh(frame_vis, &mesh, &pnp_detection, green); // draw current pose
- }
- else
- {
- drawObjectMesh(frame_vis, &mesh, &pnp_detection_est, yellow); // draw estimated pose
- }
-
- double l = 5;
- std::vector<cv::Point2f> pose_points2d;
- pose_points2d.push_back(pnp_detection_est.backproject3DPoint(cv::Point3f(0,0,0))); // axis center
- pose_points2d.push_back(pnp_detection_est.backproject3DPoint(cv::Point3f(l,0,0))); // axis x
- pose_points2d.push_back(pnp_detection_est.backproject3DPoint(cv::Point3f(0,l,0))); // axis y
- pose_points2d.push_back(pnp_detection_est.backproject3DPoint(cv::Point3f(0,0,l))); // axis z
- draw3DCoordinateAxes(frame_vis, pose_points2d); // draw axes
-
- // FRAME RATE
-
- // see how much time has elapsed
- time(&end);
-
- // calculate current FPS
- ++counter;
- sec = difftime (end, start);
-
- fps = counter / sec;
-
- drawFPS(frame_vis, fps, yellow); // frame ratio
- double ratio = ((double)inliers_idx.rows/(double)good_matches.size())*100;
- drawConfidence(frame_vis, ratio, yellow);
-
-
- // -- Step X: Draw some debugging text
-
- // Draw some debug text
- int inliers_int = inliers_idx.rows;
- int outliers_int = good_matches.size() - inliers_int;
- std::string inliers_str = IntToString(inliers_int);
- std::string outliers_str = IntToString(outliers_int);
- std::string n = IntToString(good_matches.size());
- std::string text = "Found " + inliers_str + " of " + n + " matches";
- std::string text2 = "Inliers: " + inliers_str + " - Outliers: " + outliers_str;
-
- drawText(frame_vis, text, green);
- drawText2(frame_vis, text2, red);
-
- cv::imshow("REAL TIME DEMO", frame_vis);
-
- //cv::waitKey(0);
-
- }
-
- // Close and Destroy Window
- cv::destroyWindow("REAL TIME DEMO");
-
- std::cout << "GOODBYE ..." << std::endl;
-
-}
-
-/**********************************************************************************************************/
-void initKalmanFilter(cv::KalmanFilter &KF, int nStates, int nMeasurements, int nInputs, double dt)
-{
-
- KF.init(nStates, nMeasurements, nInputs, CV_64F); // init Kalman Filter
-
- cv::setIdentity(KF.processNoiseCov, cv::Scalar::all(1e-5)); // set process noise
- cv::setIdentity(KF.measurementNoiseCov, cv::Scalar::all(1e-2)); // set measurement noise
- cv::setIdentity(KF.errorCovPost, cv::Scalar::all(1)); // error covariance
-
-
- /** DYNAMIC MODEL **/
-
- // [1 0 0 dt 0 0 dt2 0 0 0 0 0 0 0 0 0 0 0]
- // [0 1 0 0 dt 0 0 dt2 0 0 0 0 0 0 0 0 0 0]
- // [0 0 1 0 0 dt 0 0 dt2 0 0 0 0 0 0 0 0 0]
- // [0 0 0 1 0 0 dt 0 0 0 0 0 0 0 0 0 0 0]
- // [0 0 0 0 1 0 0 dt 0 0 0 0 0 0 0 0 0 0]
- // [0 0 0 0 0 1 0 0 dt 0 0 0 0 0 0 0 0 0]
- // [0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0]
- // [0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]
- // [0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0]
- // [0 0 0 0 0 0 0 0 0 1 0 0 dt 0 0 dt2 0 0]
- // [0 0 0 0 0 0 0 0 0 0 1 0 0 dt 0 0 dt2 0]
- // [0 0 0 0 0 0 0 0 0 0 0 1 0 0 dt 0 0 dt2]
- // [0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 dt 0 0]
- // [0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 dt 0]
- // [0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 dt]
- // [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0]
- // [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0]
- // [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1]
-
- // position
- KF.transitionMatrix.at<double>(0,3) = dt;
- KF.transitionMatrix.at<double>(1,4) = dt;
- KF.transitionMatrix.at<double>(2,5) = dt;
- KF.transitionMatrix.at<double>(3,6) = dt;
- KF.transitionMatrix.at<double>(4,7) = dt;
- KF.transitionMatrix.at<double>(5,8) = dt;
- KF.transitionMatrix.at<double>(0,6) = 0.5*pow(dt,2);
- KF.transitionMatrix.at<double>(1,7) = 0.5*pow(dt,2);
- KF.transitionMatrix.at<double>(2,8) = 0.5*pow(dt,2);
-
- // orientation
- KF.transitionMatrix.at<double>(9,12) = dt;
- KF.transitionMatrix.at<double>(10,13) = dt;
- KF.transitionMatrix.at<double>(11,14) = dt;
- KF.transitionMatrix.at<double>(12,15) = dt;
- KF.transitionMatrix.at<double>(13,16) = dt;
- KF.transitionMatrix.at<double>(14,17) = dt;
- KF.transitionMatrix.at<double>(9,15) = 0.5*pow(dt,2);
- KF.transitionMatrix.at<double>(10,16) = 0.5*pow(dt,2);
- KF.transitionMatrix.at<double>(11,17) = 0.5*pow(dt,2);
-
-
- /** MEASUREMENT MODEL **/
-
- // [1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
- // [0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
- // [0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
- // [0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]
- // [0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0]
- // [0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]
-
- KF.measurementMatrix.at<double>(0,0) = 1; // x
- KF.measurementMatrix.at<double>(1,1) = 1; // y
- KF.measurementMatrix.at<double>(2,2) = 1; // z
- KF.measurementMatrix.at<double>(3,9) = 1; // roll
- KF.measurementMatrix.at<double>(4,10) = 1; // pitch
- KF.measurementMatrix.at<double>(5,11) = 1; // yaw
-
- //std::cout << "A " << std::endl << KF.transitionMatrix << std::endl;
- //std::cout << "C " << std::endl << KF.measurementMatrix << std::endl;
-
-}
-
-/**********************************************************************************************************/
-void updateKalmanFilter( cv::KalmanFilter &KF, cv::Mat &measurement,
- cv::Mat &translation_estimated, cv::Mat &rotation_estimated )
-{
-
- // First predict, to update the internal statePre variable
- cv::Mat prediction = KF.predict();
-
- // The "correct" phase that is going to use the predicted value and our measurement
- cv::Mat estimated = KF.correct(measurement);
-
- // Estimated translation
- translation_estimated.at<double>(0) = estimated.at<double>(0);
- translation_estimated.at<double>(1) = estimated.at<double>(1);
- translation_estimated.at<double>(2) = estimated.at<double>(2);
-
- // Estimated euler angles
- cv::Mat eulers_estimated(3, 1, CV_64F);
- eulers_estimated.at<double>(0) = estimated.at<double>(9);
- eulers_estimated.at<double>(1) = estimated.at<double>(10);
- eulers_estimated.at<double>(2) = estimated.at<double>(11);
-
- // Convert estimated quaternion to rotation matrix
- rotation_estimated = euler2rot(eulers_estimated);
-
-}
-
-/**********************************************************************************************************/
-void fillMeasurements( cv::Mat &measurements,
- const cv::Mat &translation_measured, const cv::Mat &rotation_measured)
-{
- // Convert rotation matrix to euler angles
- cv::Mat measured_eulers(3, 1, CV_64F);
- measured_eulers = rot2euler(rotation_measured);
-
- // Set measurement to predict
- measurements.at<double>(0) = translation_measured.at<double>(0); // x
- measurements.at<double>(1) = translation_measured.at<double>(1); // y
- measurements.at<double>(2) = translation_measured.at<double>(2); // z
- measurements.at<double>(3) = measured_eulers.at<double>(0); // roll
- measurements.at<double>(4) = measured_eulers.at<double>(1); // pitch
- measurements.at<double>(5) = measured_eulers.at<double>(2); // yaw
-}
+++ /dev/null
-#include <iostream>
-
-#include "Mesh.h"
-#include "Model.h"
-#include "PnPProblem.h"
-#include "RobustMatcher.h"
-#include "ModelRegistration.h"
-#include "Utils.h"
-
-#include <opencv2/core/core.hpp>
-#include <opencv2/imgproc/imgproc.hpp>
-#include <opencv2/calib3d/calib3d.hpp>
-#include <opencv2/features2d/features2d.hpp>
-#include <opencv2/nonfree/features2d.hpp>
-
- /*
- * Set up the images paths
- */
-
- // COOKIES BOX [718x480]
- std::string img_path = "../Data/resized_IMG_3875.JPG"; // f 55
-
- // COOKIES BOX MESH
- std::string ply_read_path = "../Data/box.ply";
-
- // YAML writting path
- std::string write_path = "../Data/cookies_ORB.yml";
-
- void help()
- {
- std::cout
- << "--------------------------------------------------------------------------" << std::endl
- << "This program shows how to create your 3D textured model. " << std::endl
- << "Usage:" << std::endl
- << "./pnp_registration " << std::endl
- << "--------------------------------------------------------------------------" << std::endl
- << std::endl;
- }
-
- // Boolean the know if the registration it's done
- bool end_registration = false;
-
- /*
- * Set up the intrinsic camera parameters: CANON
- */
- double f = 45; // focal length in mm
- double sx = 22.3, sy = 14.9;
- double width = 2592, height = 1944;
- double params_CANON[] = { width*f/sx, // fx
- height*f/sy, // fy
- width/2, // cx
- height/2}; // cy
-
-
- // Setup the points to register in the image
- // In the order of the *.ply file and starting at 1
- int n = 8;
- int pts[] = {1, 2, 3, 4, 5, 6, 7, 8}; // 3 -> 4
-
- /*
- * Set up some basic colors
- */
- cv::Scalar red(0, 0, 255);
- cv::Scalar green(0,255,0);
- cv::Scalar blue(255,0,0);
- cv::Scalar yellow(0,255,255);
-
- /*
- * CREATE MODEL REGISTRATION OBJECT
- * CREATE OBJECT MESH
- * CREATE OBJECT MODEL
- * CREATE PNP OBJECT
- */
- ModelRegistration registration;
- Model model;
- Mesh mesh;
- PnPProblem pnp_registration(params_CANON);
-
-
-// Mouse events for model registration
-static void onMouseModelRegistration( int event, int x, int y, int, void* )
-{
- if ( event == cv::EVENT_LBUTTONUP )
- {
- int n_regist = registration.getNumRegist();
- int n_vertex = pts[n_regist];
-
- cv::Point2f point_2d = cv::Point2f(x,y);
- cv::Point3f point_3d = mesh.getVertex(n_vertex-1);
-
- bool is_registrable = registration.is_registrable();
- if (is_registrable)
- {
- registration.registerPoint(point_2d, point_3d);
- if( registration.getNumRegist() == registration.getNumMax() ) end_registration = true;
- }
- }
-}
-
-/*
- * MAIN PROGRAM
- *
- */
-
-int main(int argc, char *argv[])
-{
-
- help();
-
- // load a mesh given the *.ply file path
- mesh.load(ply_read_path);
-
- // set parameters
- int numKeyPoints = 10000;
-
- //Instantiate robust matcher: detector, extractor, matcher
- RobustMatcher rmatcher;
- cv::FeatureDetector * detector = new cv::OrbFeatureDetector(numKeyPoints);
- rmatcher.setFeatureDetector(detector);
-
- /*
- * GROUND TRUTH OF THE FIRST IMAGE
- *
- * by the moment it is the reference image
- */
-
- // Create & Open Window
- cv::namedWindow("MODEL REGISTRATION", cv::WINDOW_KEEPRATIO);
-
- // Set up the mouse events
- cv::setMouseCallback("MODEL REGISTRATION", onMouseModelRegistration, 0 );
-
- // Open the image to register
- cv::Mat img_in = cv::imread(img_path, cv::IMREAD_COLOR);
- cv::Mat img_vis = img_in.clone();
-
- if (!img_in.data) {
- std::cout << "Could not open or find the image" << std::endl;
- return -1;
- }
-
- // Set the number of points to register
- int num_registrations = n;
- registration.setNumMax(num_registrations);
-
- std::cout << "Click the box corners ..." << std::endl;
- std::cout << "Waiting ..." << std::endl;
-
- // Loop until all the points are registered
- while ( cv::waitKey(30) < 0 )
- {
- // Refresh debug image
- img_vis = img_in.clone();
-
- // Current registered points
- std::vector<cv::Point2f> list_points2d = registration.get_points2d();
- std::vector<cv::Point3f> list_points3d = registration.get_points3d();
-
- // Draw current registered points
- drawPoints(img_vis, list_points2d, list_points3d, red);
-
- // If the registration is not finished, draw which 3D point we have to register.
- // If the registration is finished, breaks the loop.
- if (!end_registration)
- {
- // Draw debug text
- int n_regist = registration.getNumRegist();
- int n_vertex = pts[n_regist];
- cv::Point3f current_poin3d = mesh.getVertex(n_vertex-1);
-
- drawQuestion(img_vis, current_poin3d, green);
- drawCounter(img_vis, registration.getNumRegist(), registration.getNumMax(), red);
- }
- else
- {
- // Draw debug text
- drawText(img_vis, "END REGISTRATION", green);
- drawCounter(img_vis, registration.getNumRegist(), registration.getNumMax(), green);
- break;
- }
-
- // Show the image
- cv::imshow("MODEL REGISTRATION", img_vis);
- }
-
-
- /*
- *
- * COMPUTE CAMERA POSE
- *
- */
-
- std::cout << "COMPUTING POSE ..." << std::endl;
-
- // The list of registered points
- std::vector<cv::Point2f> list_points2d = registration.get_points2d();
- std::vector<cv::Point3f> list_points3d = registration.get_points3d();
-
- // Estimate pose given the registered points
- bool is_correspondence = pnp_registration.estimatePose(list_points3d, list_points2d, cv::ITERATIVE);
- if ( is_correspondence )
- {
- std::cout << "Correspondence found" << std::endl;
-
- // Compute all the 2D points of the mesh to verify the algorithm and draw it
- std::vector<cv::Point2f> list_points2d_mesh = pnp_registration.verify_points(&mesh);
- draw2DPoints(img_vis, list_points2d_mesh, green);
-
- } else {
- std::cout << "Correspondence not found" << std::endl << std::endl;
- }
-
- // Show the image
- cv::imshow("MODEL REGISTRATION", img_vis);
-
- // Show image until ESC pressed
- cv::waitKey(0);
-
-
- /*
- *
- * COMPUTE 3D of the image Keypoints
- *
- */
-
-
- // Containers for keypoints and descriptors of the model
- std::vector<cv::KeyPoint> keypoints_model;
- cv::Mat descriptors;
-
- // Compute keypoints and descriptors
- rmatcher.computeKeyPoints(img_in, keypoints_model);
- rmatcher.computeDescriptors(img_in, keypoints_model, descriptors);
-
- // Check if keypoints are on the surface of the registration image and add to the model
- for (unsigned int i = 0; i < keypoints_model.size(); ++i) {
- cv::Point2f point2d(keypoints_model[i].pt);
- cv::Point3f point3d;
- bool on_surface = pnp_registration.backproject2DPoint(&mesh, point2d, point3d);
- if (on_surface)
- {
- model.add_correspondence(point2d, point3d);
- model.add_descriptor(descriptors.row(i));
- model.add_keypoint(keypoints_model[i]);
- }
- else
- {
- model.add_outlier(point2d);
- }
- }
-
- // save the model into a *.yaml file
- model.save(write_path);
-
- // Out image
- img_vis = img_in.clone();
-
- // The list of the points2d of the model
- std::vector<cv::Point2f> list_points_in = model.get_points2d_in();
- std::vector<cv::Point2f> list_points_out = model.get_points2d_out();
-
- // Draw some debug text
- std::string num = IntToString(list_points_in.size());
- std::string text = "There are " + num + " inliers";
- drawText(img_vis, text, green);
-
- // Draw some debug text
- num = IntToString(list_points_out.size());
- text = "There are " + num + " outliers";
- drawText2(img_vis, text, red);
-
- // Draw the object mesh
- drawObjectMesh(img_vis, &mesh, &pnp_registration, blue);
-
- // Draw found keypoints depending on if are or not on the surface
- draw2DPoints(img_vis, list_points_in, green);
- draw2DPoints(img_vis, list_points_out, red);
-
- // Show the image
- cv::imshow("MODEL REGISTRATION", img_vis);
-
- // Wait until ESC pressed
- cv::waitKey(0);
-
- // Close and Destroy Window
- cv::destroyWindow("MODEL REGISTRATION");
-
- std::cout << "GOODBYE" << std::endl;
-
-}
+++ /dev/null
-#include <iostream>
-
-#include "cv.h"
-#include "highgui.h"
-
-#include <opencv2/core/core.hpp>
-#include <opencv2/imgproc/imgproc.hpp>
-#include <opencv2/nonfree/features2d.hpp>
-#include <opencv2/calib3d/calib3d.hpp>
-
-#include "Mesh.h"
-#include "Model.h"
-#include "PnPProblem.h"
-#include "RobustMatcher.h"
-#include "ModelRegistration.h"
-#include "Utils.h"
-
-#include "CsvWriter.h"
-
-
- /*
- * Set up the images paths
- */
-
- std::string img_verification_path = "../Data/resized_IMG_3872.JPG";
- std::string ply_read_path = "../Data/box.ply";
- std::string yml_read_path = "../Data/cookies_ORB.yml";
-
- // Boolean the know if the registration it's done
- bool end_registration = false;
-
- // Setup the points to register in the image
- // In the order of the *.ply file and starting at 1
- int n = 7;
- int pts[] = {1, 2, 3, 5, 6, 7, 8};
-
- /*
- * Set up the intrinsic camera parameters: CANON
- */
- double f = 43;
- double sx = 22.3, sy = 14.9;
- double width = 718, height = 480;
- double params_CANON[] = { width*f/sx, // fx
- height*f/sy, // fy
- width/2, // cx
- height/2}; // cy
-
- /*
- * Set up some basic colors
- */
- cv::Scalar red(0, 0, 255);
- cv::Scalar green(0,255,0);
- cv::Scalar blue(255,0,0);
- cv::Scalar yellow(0,255,255);
-
- /*
- * CREATE MODEL REGISTRATION OBJECT
- * CREATE OBJECT MESH
- * CREATE OBJECT MODEL
- * CREATE PNP OBJECT
- */
- Mesh mesh;
- ModelRegistration registration;
- PnPProblem pnp_verification_epnp(params_CANON);
- PnPProblem pnp_verification_iter(params_CANON);
- PnPProblem pnp_verification_p3p(params_CANON);
- PnPProblem pnp_verification_dls(params_CANON);
- PnPProblem pnp_verification_gt(params_CANON); // groud truth
-
-
-// Mouse events for model registration
-static void onMouseModelVerification( int event, int x, int y, int, void* )
-{
- if ( event == cv::EVENT_LBUTTONUP )
- {
- int n_regist = registration.getNumRegist();
- int n_vertex = pts[n_regist];
-
- cv::Point2f point_2d = cv::Point2f(x,y);
- cv::Point3f point_3d = mesh.getVertex(n_vertex-1);
-
- bool is_registrable = registration.is_registrable();
- if (is_registrable)
- {
- registration.registerPoint(point_2d, point_3d);
- if( registration.getNumRegist() == registration.getNumMax() ) end_registration = true;
- }
- }
-}
-
-
-/*
- * MAIN PROGRAM
- *
- */
-
-int main(int, char**)
-{
-
- std::cout << "!!!Hello Verification!!!" << std::endl; // prints !!!Hello World!!!
-
- // load a mesh given the *.ply file path
- mesh.load(ply_read_path);
-
- // load the 3D textured object model
- Model model;
- model.load(yml_read_path);
-
- // set parameters
- int numKeyPoints = 10000;
-
- //Instantiate robust matcher: detector, extractor, matcher
- RobustMatcher rmatcher;
- cv::FeatureDetector * detector = new cv::OrbFeatureDetector(numKeyPoints);
- rmatcher.setFeatureDetector(detector);
- rmatcher.setRatio(0.80);
-
- // RANSAC parameters
- int iterationsCount = 500;
- float reprojectionError = 2.0;
- float confidence = 0.99;
-
-
- /*
- * GROUND TRUTH SECOND IMAGE
- *
- */
-
- cv::Mat img_in, img_vis;
-
- // Setup for new registration
- registration.setNumMax(n);
-
- // Create & Open Window
- cv::namedWindow("MODEL GROUND TRUTH", CV_WINDOW_KEEPRATIO);
-
- // Set up the mouse events
- cv::setMouseCallback("MODEL GROUND TRUTH", onMouseModelVerification, 0 );
-
- // Open the image to register
- img_in = cv::imread(img_verification_path, cv::IMREAD_COLOR);
-
- if (!img_in.data)
- {
- std::cout << "Could not open or find the image" << std::endl;
- return -1;
- }
-
- std::cout << "Click the box corners ..." << std::endl;
- std::cout << "Waiting ..." << std::endl;
-
- // Loop until all the points are registered
- while ( cv::waitKey(30) < 0 )
- {
- // Refresh debug image
- img_vis = img_in.clone();
-
- // Current registered points
- std::vector<cv::Point2f> list_points2d = registration.get_points2d();
- std::vector<cv::Point3f> list_points3d = registration.get_points3d();
-
- // Draw current registered points
- drawPoints(img_vis, list_points2d, list_points3d, red);
-
- // If the registration is not finished, draw which 3D point we have to register.
- // If the registration is finished, breaks the loop.
- if (!end_registration)
- {
- // Draw debug text
- int n_regist = registration.getNumRegist();
- int n_vertex = pts[n_regist];
- cv::Point3f current_poin3d = mesh.getVertex(n_vertex-1);
-
- drawQuestion(img_vis, current_poin3d, green);
- drawCounter(img_vis, registration.getNumRegist(), registration.getNumMax(), red);
- }
- else
- {
- // Draw debug text
- drawText(img_vis, "GROUND TRUTH", green);
- drawCounter(img_vis, registration.getNumRegist(), registration.getNumMax(), green);
- break;
- }
-
- // Show the image
- cv::imshow("MODEL GROUND TRUTH", img_vis);
- }
-
- // The list of registered points
- std::vector<cv::Point2f> list_points2d = registration.get_points2d();
- std::vector<cv::Point3f> list_points3d = registration.get_points3d();
-
- // Estimate pose given the registered points
- bool is_correspondence = pnp_verification_gt.estimatePose(list_points3d, list_points2d, cv::ITERATIVE);
-
- // Compute and draw all mesh object 2D points
- std::vector<cv::Point2f> pts_2d_ground_truth = pnp_verification_gt.verify_points(&mesh);
- draw2DPoints(img_vis, pts_2d_ground_truth, green);
-
- // Draw the ground truth mesh
- drawObjectMesh(img_vis, &mesh, &pnp_verification_gt, blue);
-
- // Show the image
- cv::imshow("MODEL GROUND TRUTH", img_vis);
-
- // Show image until ESC pressed
- cv::waitKey(0);
-
-
- /*
- * EXTRACT CORRRESPONDENCES
- *
- */
-
- // refresh visualisation image
- img_vis = img_in.clone();
-
- // Get the MODEL INFO
- std::vector<cv::Point2f> list_points2d_model = model.get_points2d_in();
- std::vector<cv::Point3f> list_points3d_model = model.get_points3d();
- std::vector<cv::KeyPoint> keypoints_model = model.get_keypoints();
- cv::Mat descriptors_model = model.get_descriptors();
-
- // -- Step 1: Robust matching between model descriptors and scene descriptors
-
- std::vector<cv::DMatch> good_matches; // to obtain the 3D points of the model
- std::vector<cv::KeyPoint> keypoints_scene; // to obtain the 2D points of the scene
-
- //rmatcher.fastRobustMatch(frame, good_matches, keypoints_scene, descriptors_model);
- rmatcher.robustMatch(img_vis, good_matches, keypoints_scene, descriptors_model);
-
- cv::Mat inliers_idx;
- std::vector<cv::DMatch> matches_inliers;
- std::vector<cv::Point2f> list_points2d_inliers;
- std::vector<cv::Point3f> list_points3d_inliers;
-
- // -- Step 2: Find out the 2D/3D correspondences
-
- std::vector<cv::Point3f> list_points3d_model_match; // container for the model 3D coordinates found in the scene
- std::vector<cv::Point2f> list_points2d_scene_match; // container for the model 2D coordinates found in the scene
-
- for(unsigned int match_index = 0; match_index < good_matches.size(); ++match_index)
- {
- cv::Point3f point3d_model = list_points3d_model[ good_matches[match_index].trainIdx ]; // 3D point from model
- cv::Point2f point2d_scene = keypoints_scene[ good_matches[match_index].queryIdx ].pt; // 2D point from the scene
- list_points3d_model_match.push_back(point3d_model); // add 3D point
- list_points2d_scene_match.push_back(point2d_scene); // add 2D point
- }
-
- // Draw outliers
- //draw2DPoints(img_vis, list_points2d_scene_match, red);
-
- /*
- * COMPUTE PNP ERRORS:
- * Calculation of the rotation and translation error
- *
- */
-
- pnp_verification_epnp.estimatePose( list_points3d_model_match, list_points2d_scene_match, cv::EPNP);
- pnp_verification_iter.estimatePose( list_points3d_model_match, list_points2d_scene_match, cv::ITERATIVE);
- //pnp_verification_p3p.estimatePose( list_points3d_model_match, list_points2d_scene_match, cv::P3P);
- pnp_verification_dls.estimatePose( list_points3d_model_match, list_points2d_scene_match, cv::DLS);
-
- // Draw mesh
- drawObjectMesh(img_vis, &mesh, &pnp_verification_dls, green);
- drawObjectMesh(img_vis, &mesh, &pnp_verification_gt, yellow);
-
- cv::imshow("MODEL GROUND TRUTH", img_vis);
-
- cv::Mat t_true = pnp_verification_gt.get_t_matrix();
- cv::Mat t_epnp = pnp_verification_epnp.get_t_matrix();
- cv::Mat t_iter = pnp_verification_iter.get_t_matrix();
- cv::Mat t_p3p = pnp_verification_p3p.get_t_matrix();
- cv::Mat t_dls = pnp_verification_dls.get_t_matrix();
-
- cv::Mat R_true = pnp_verification_gt.get_R_matrix();
- cv::Mat R_epnp = pnp_verification_epnp.get_R_matrix();
- cv::Mat R_iter = pnp_verification_iter.get_R_matrix();
- cv::Mat R_p3p = pnp_verification_p3p.get_R_matrix();
- cv::Mat R_dls = pnp_verification_dls.get_R_matrix();
-
- double error_trans_epnp = get_translation_error(t_true, t_epnp);
- double error_rot_epnp = get_rotation_error(R_true, R_epnp)*180/CV_PI;
-
- double error_trans_iter = get_translation_error(t_true, t_iter);
- double error_rot_iter = get_rotation_error(R_true, R_iter)*180/CV_PI;
-
- double error_trans_p3p = get_translation_error(t_true, t_p3p);
- double error_rot_p3p = get_rotation_error(R_true, R_p3p)*180/CV_PI;
-
- double error_trans_dls = get_translation_error(t_true, t_dls);
- double error_rot_dls = get_rotation_error(R_true, R_dls)*180/CV_PI;
-
-
- std::cout << std::endl << "**** EPNP ERRORS **** " << std::endl;
-
- std::cout << "Translation error: " << error_trans_epnp << " m." << std::endl;
- std::cout << "Rotation error: " << error_rot_epnp << " deg." << std::endl;
-
-
- std::cout << std::endl << "**** ITERATIVE ERRORS **** " << std::endl;
-
- std::cout << "Translation error: " << error_trans_iter << " m." << std::endl;
- std::cout << "Rotation error: " << error_rot_iter << " deg." << std::endl;
-
-
- std::cout << std::endl << "**** P3P ERRORS **** " << std::endl;
-
- std::cout << "Translation error: " << error_trans_p3p << " m." << std::endl;
- std::cout << "Rotation error: " << error_rot_p3p << " deg." << std::endl;
-
-
- std::cout << std::endl << "**** DLS ERRORS **** " << std::endl;
-
- std::cout << "Translation error: " << error_trans_dls << " m." << std::endl;
- std::cout << "Rotation error: " << error_rot_dls << " deg." << std::endl;
-
-
- // Show image until ESC pressed
- cv::waitKey(0);
-
- // Close and Destroy Window
- cv::destroyWindow("MODEL GROUND TRUTH");
-
- std::cout << "GOODBYE" << std::endl;
-
-}
+++ /dev/null
-#include <opencv2/core/core.hpp>
-#include <opencv2/calib3d/calib3d.hpp>
-#include <opencv2/contrib/contrib.hpp>
-
-#include <iostream>
-#include <fstream>
-
-using namespace std;
-using namespace cv;
-
-void generate3DPointCloud(vector<Point3f>& points, Point3f pmin = Point3f(-1,
- -1, 5), Point3f pmax = Point3f(1, 1, 10))
- {
- const Point3f delta = pmax - pmin;
- for (size_t i = 0; i < points.size(); i++)
- {
- Point3f p(float(rand()) / RAND_MAX, float(rand()) / RAND_MAX,
- float(rand()) / RAND_MAX);
- p.x *= delta.x;
- p.y *= delta.y;
- p.z *= delta.z;
- p = p + pmin;
- points[i] = p;
- }
- }
-
-void generateCameraMatrix(Mat& cameraMatrix, RNG& rng)
-{
- const double fcMinVal = 1e-3;
- const double fcMaxVal = 100;
- cameraMatrix.create(3, 3, CV_64FC1);
- cameraMatrix.setTo(Scalar(0));
- cameraMatrix.at<double>(0,0) = rng.uniform(fcMinVal, fcMaxVal);
- cameraMatrix.at<double>(1,1) = rng.uniform(fcMinVal, fcMaxVal);
- cameraMatrix.at<double>(0,2) = rng.uniform(fcMinVal, fcMaxVal);
- cameraMatrix.at<double>(1,2) = rng.uniform(fcMinVal, fcMaxVal);
- cameraMatrix.at<double>(2,2) = 1;
-}
-
-void generateDistCoeffs(Mat& distCoeffs, RNG& rng)
-{
- distCoeffs = Mat::zeros(4, 1, CV_64FC1);
- for (int i = 0; i < 3; i++)
- distCoeffs.at<double>(i,0) = rng.uniform(0.0, 1.0e-6);
-}
-
-void generatePose(Mat& rvec, Mat& tvec, RNG& rng)
-{
- const double minVal = 1.0e-3;
- const double maxVal = 1.0;
- rvec.create(3, 1, CV_64FC1);
- tvec.create(3, 1, CV_64FC1);
- for (int i = 0; i < 3; i++)
- {
- rvec.at<double>(i,0) = rng.uniform(minVal, maxVal);
- tvec.at<double>(i,0) = rng.uniform(minVal, maxVal/10);
- }
-}
-
-void data2file(const string& path, const vector<vector<double> >& data)
-{
- std::fstream fs;
- fs.open(path.c_str(), std::fstream::in | std::fstream::out | std::fstream::app);
-
- for (int method = 0; method < data.size(); ++method)
- {
- for (int i = 0; i < data[method].size(); ++i)
- {
- fs << data[method][i] << " ";
- }
- fs << endl;
- }
-
- fs.close();
-}
-
-
-int main(int argc, char *argv[])
-{
-
- RNG rng;
- // TickMeter tm;
- vector<vector<double> > error_trans(4), error_rot(4), comp_time(4);
-
- int maxpoints = 2000;
- for (int npoints = 10; npoints < maxpoints+10; ++npoints)
- {
- // generate 3D point cloud
- vector<Point3f> points;
- points.resize(npoints);
- generate3DPointCloud(points);
-
- // generate cameramatrix
- Mat rvec, tvec;
- Mat trueRvec, trueTvec;
- Mat intrinsics, distCoeffs;
- generateCameraMatrix(intrinsics, rng);
-
- // generate distorsion coefficients
- generateDistCoeffs(distCoeffs, rng);
-
- // generate groud truth pose
- generatePose(trueRvec, trueTvec, rng);
-
- for (int method = 0; method < 4; ++method)
- {
- std::vector<Point3f> opoints;
- if (method == 2)
- {
- opoints = std::vector<Point3f>(points.begin(), points.begin()+4);
- }
- else
- opoints = points;
-
- vector<Point2f> projectedPoints;
- projectedPoints.resize(opoints.size());
- projectPoints(Mat(opoints), trueRvec, trueTvec, intrinsics, distCoeffs, projectedPoints);
-
- //tm.reset(); tm.start();
-
- solvePnP(opoints, projectedPoints, intrinsics, distCoeffs, rvec, tvec, false, method);
-
- // tm.stop();
-
- // double compTime = tm.getTimeMilli();
- double rvecDiff = norm(rvec-trueRvec), tvecDiff = norm(tvec-trueTvec);
-
- error_rot[method].push_back(rvecDiff);
- error_trans[method].push_back(tvecDiff);
- //comp_time[method].push_back(compTime);
-
- }
-
- //system("clear");
- cout << "Completed " << npoints+1 << "/" << maxpoints << endl;
-
- }
-
- data2file("translation_error.txt", error_trans);
- data2file("rotation_error.txt", error_rot);
- data2file("computation_time.txt", comp_time);
-
-}
projects / platform / upstream / opencv.git / commitdiff