void getCameraRay(const image_geometry::PinholeCameraModel& model, const cv::Point2d& pt, cv::Point3d* ray)
{
cv::Point2d rect_point;
rect_point = model.rectifyPoint(pt);
ROS_DEBUG("Rect Point: %f, %f",rect_point.x,rect_point.y);
*ray = model.projectPixelTo3dRay(rect_point);
}
pcl::PointCloud<pcl::PointXYZ>::Ptr Conversions::toPointCloud(const Eigen::Isometry3d &T, const image_geometry::PinholeCameraModel &cam, const cv::Mat &depth_img)
{
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>());
cloud->header.frame_id = "cam";
cloud->is_dense = false;
cloud->height = depth_img.rows;
cloud->width = depth_img.cols;
cloud->sensor_origin_ = Eigen::Vector4f( T.translation()(0), T.translation()(1), T.translation()(2), 1.f );
cloud->sensor_orientation_ = Eigen::Quaternionf(T.rotation().cast<float>());
cloud->points.resize( cloud->height * cloud->width );
size_t idx = 0;
const float* depthdata = reinterpret_cast<float*>( &depth_img.data[0] );
for(int v = 0; v < depth_img.rows; ++v) {
for(int u = 0; u < depth_img.cols; ++u) {
pcl::PointXYZ& p = cloud->points[ idx ]; ++idx;
float d = (*depthdata++);
if (d > 0 && !isnan(d)) {
p.z = d;
p.x = (u - cam.cx()) * d / cam.fx();
p.y = (v - cam.cy()) * d / cam.fy();
} else {
p.x = std::numeric_limits<float>::quiet_NaN();
p.y = std::numeric_limits<float>::quiet_NaN();
p.z = std::numeric_limits<float>::quiet_NaN();
}
}
}
return cloud;
}
void FindObjectOnPlane::generateStartPoints(
const cv::Point2f& point_2d,
const image_geometry::PinholeCameraModel& model,
const pcl::ModelCoefficients::Ptr& coefficients,
std::vector<cv::Point3f>& search_points_3d,
std::vector<cv::Point2f>& search_points_2d)
{
NODELET_INFO("generateStartPoints");
jsk_recognition_utils::Plane::Ptr plane
(new jsk_recognition_utils::Plane(coefficients->values));
cv::Point3d ray = model.projectPixelTo3dRay(point_2d);
Eigen::Vector3f projected_point = rayPlaneInteersect(ray, plane);
const double resolution_step = 0.01;
const int resolution = 5;
search_points_3d.clear();
search_points_2d.clear();
for (int i = - resolution; i < resolution; ++i) {
for (int j = - resolution; j < resolution; ++j) {
double x_diff = resolution_step * i;
double y_diff = resolution_step * j;
Eigen::Vector3f moved_point = projected_point + Eigen::Vector3f(x_diff, y_diff, 0);
Eigen::Vector3f projected_moved_point;
plane->project(moved_point, projected_moved_point);
cv::Point3f projected_moved_point_cv(projected_moved_point[0],
projected_moved_point[1],
projected_moved_point[2]);
search_points_3d.push_back(cv::Point3f(projected_moved_point_cv));
cv::Point2d p2d = model.project3dToPixel(projected_moved_point_cv);
search_points_2d.push_back(p2d);
}
}
}
void infoCallback(const sensor_msgs::CameraInfoConstPtr& info_msg)
{
if (calibrated)
return;
cam_model_.fromCameraInfo(info_msg);
pattern_detector_.setCameraMatrices(cam_model_.intrinsicMatrix(), cam_model_.distortionCoeffs());
calibrated = true;
image_sub_ = nh_.subscribe("/camera/rgb/image_mono", 1, &CalibrateKinectCheckerboard::imageCallback, this);
ROS_INFO("[calibrate] Got image info!");
}
void camerainfoCb(const sensor_msgs::CameraInfoConstPtr& info_msg)
{
ROS_INFO("infocallback :shutting down camerainfosub");
cam_model_.fromCameraInfo(info_msg);
camera_topic = info_msg->header.frame_id;
camerainfosub_.shutdown();
}
void projectPoints(const image_geometry::PinholeCameraModel &cam_model,
const cv::Point3d &points3D,
cv::Point2d *points2D)
{
*points2D = cam_model.project3dToPixel(points3D);
// *points2D = cam_model.rectifyPoint(*points2D);
}
void overlayPoints(pcl::PointCloud<pcl::PointXYZ> detector_points, tf::Transform &transform, cv_bridge::CvImagePtr& image)
{
// Overlay calibration points on the image
pcl::PointCloud<pcl::PointXYZ> transformed_detector_points;
pcl_ros::transformPointCloud(detector_points, transformed_detector_points, transform);
int font_face = cv::FONT_HERSHEY_SCRIPT_SIMPLEX;
double font_scale = 1;
int thickness = 2;
int radius = 5;
for (unsigned int i=0; i < transformed_detector_points.size(); i++)
{
pcl::PointXYZ pt = transformed_detector_points[i];
cv::Point3d pt_cv(pt.x, pt.y, pt.z);
cv::Point2d uv;
uv = cam_model_.project3dToPixel(pt_cv);
cv::circle(image->image, uv, radius, CV_RGB(255,0,0), -1);
cv::Size text_size;
int baseline = 0;
std::stringstream out;
out << i+1;
text_size = cv::getTextSize(out.str(), font_face, font_scale, thickness, &baseline);
cv::Point origin = cvPoint(uv.x - text_size.width / 2,
uv.y - radius - baseline/* - thickness*/);
cv::putText(image->image, out.str(), origin, font_face, font_scale, CV_RGB(255,0,0), thickness);
}
}
pcl::PointXYZ PointFromPixel(const cv::Point& pixel, const tf::Transform& cameraFrameToWorldFrame, image_geometry::PinholeCameraModel cam) {
cv::Point3d cameraRay = cam.projectPixelTo3dRay(pixel);
tf::Point worldCameraOrigin = cameraFrameToWorldFrame * tf::Vector3(0, 0, 0);
tf::Point worldCameraStep = cameraFrameToWorldFrame * tf::Vector3(cameraRay.x, cameraRay.y, cameraRay.z) - worldCameraOrigin;
double zScale = -worldCameraOrigin.z()/worldCameraStep.z();
tf::Point ret = worldCameraOrigin + zScale * worldCameraStep;
return pcl::PointXYZ(ret.x(), ret.y(), 0);
}
void cam_info_cb(const sensor_msgs::CameraInfo::ConstPtr& msg)
{
if( cam_model_.fromCameraInfo(msg) )
{
got_cam_info_ = true;
ROS_INFO("[bk_skeletal_tracker] Got RGB camera info.");
} else {
ROS_ERROR("[bk_skeletal_tracker] Couldn't read camera info.");
}
}
cv::Point2d FindObjectOnPlane::getUyEnd(
const cv::Point2d& ux_start,
const cv::Point2d& ux_end,
const image_geometry::PinholeCameraModel& model,
const jsk_recognition_utils::Plane::Ptr& plane)
{
cv::Point3d start_ray = model.projectPixelTo3dRay(ux_start);
cv::Point3d end_ray = model.projectPixelTo3dRay(ux_end);
Eigen::Vector3f ux_start_3d = rayPlaneInteersect(start_ray, plane);
Eigen::Vector3f ux_end_3d = rayPlaneInteersect(end_ray, plane);
Eigen::Vector3f ux_3d = ux_end_3d - ux_start_3d;
Eigen::Vector3f normal = plane->getNormal();
Eigen::Vector3f uy_3d = normal.cross(ux_3d).normalized();
Eigen::Vector3f uy_end_3d = ux_start_3d + uy_3d;
cv::Point2d uy_end = model.project3dToPixel(cv::Point3d(uy_end_3d[0],
uy_end_3d[1],
uy_end_3d[2]));
return uy_end;
}
void doOverlay(const sensor_msgs::ImageConstPtr& img_msg,
const sensor_msgs::CameraInfoConstPtr& info_msg) {
// convert camera image into opencv
cam_model.fromCameraInfo(info_msg);
cv_bridge::CvImagePtr cv_img = cv_bridge::toCvCopy(img_msg, sensor_msgs::image_encodings::RGB8);
double alpha_mult;
ros::param::param<double>("~alpha_mult", alpha_mult, 0.5);
uint8_t r, g, b;
if(aligned_pc) {
if(!tf_list->waitForTransform(img_msg->header.frame_id, "/base_link",
img_msg->header.stamp, ros::Duration(3)))
return;
tf::StampedTransform transform;
tf_list->lookupTransform(img_msg->header.frame_id, "/base_link",
img_msg->header.stamp, transform);
PCRGB::Ptr tf_pc(new PCRGB());
pcl_ros::transformPointCloud<PRGB>(*aligned_pc, *tf_pc, transform);
for(uint32_t i=0;i<tf_pc->size();i++) {
cv::Point3d proj_pt_cv(tf_pc->points[i].x, tf_pc->points[i].y,
tf_pc->points[i].z);
cv::Point pt2d = cam_model.project3dToPixel(proj_pt_cv);
extractRGB(tf_pc->points[i].rgb, r, g, b);
if(pt2d.x >= 0 && pt2d.y >= 0 &&
pt2d.x < cv_img->image.rows && pt2d.y < cv_img->image.cols) {
double old_r = cv_img->image.at<cv::Vec3b>(pt2d.y, pt2d.x)[0];
double old_g = cv_img->image.at<cv::Vec3b>(pt2d.y, pt2d.x)[1];
double old_b = cv_img->image.at<cv::Vec3b>(pt2d.y, pt2d.x)[2];
cv_img->image.at<cv::Vec3b>(pt2d.y, pt2d.x)[0] =
(uint8_t) min(alpha_mult*old_r+r, 255.0);
cv_img->image.at<cv::Vec3b>(pt2d.y, pt2d.x)[1] =
(uint8_t) min(alpha_mult*old_g+g, 255.0);
cv_img->image.at<cv::Vec3b>(pt2d.y, pt2d.x)[2] =
(uint8_t) min(alpha_mult*old_b+b, 255.0);
}
}
}
overlay_pub.publish(cv_img->toImageMsg());
}
cv::Point3d GraphGridMapper::to3D(cv::Point3d &p, const Eigen::Isometry3d &camera_transform, const image_geometry::PinholeCameraModel &camera_model)
{
int width = camera_model.cameraInfo().width;
int height = camera_model.cameraInfo().height;
int u = round(p.x);
if(u < 0) {
u = 0;
} else if (u >= width) {
u = width -1;
}
int v = round(p.y);
if(v < 0) {
v = 0;
} else if (v >= height) {
v = height - 1;
}
cv::Point3d p3D(-1.0,-1.0,std::numeric_limits<double>::infinity());
if (p.z != 0 && !isnan(p.z))
{
p3D.x = (u - camera_model.cx()) * p.z / camera_model.fx();
p3D.y = (v - camera_model.cy()) * p.z / camera_model.fy();
p3D.z = p.z;
Eigen::Vector3d vec(p3D.x, p3D.y, p3D.z);
vec = camera_transform * vec.homogeneous();
p3D.x = vec(0);
p3D.y = vec(1);
p3D.z = vec(2);
}
return p3D;
}
size_t project_uv_to_cloud_index(const pcl::PointCloud<PointT>& cloud, const cv::Point2d& image_point,
const image_geometry::PinholeCameraModel camera_model, double& distance)
{
// Assumes camera is at origin, pointed in the normal direction
size_t pt_pcl_index;
cv::Point3d pt_cv;
pt_cv = camera_model.projectPixelTo3dRay(image_point);
Eigen::Vector3f direction_eig(pt_cv.x, pt_cv.y, pt_cv.z);
Eigen::Vector3f origin_eig(0.0, 0.0, 0.0);
pt_pcl_index = closest_point_index_rayOMP(cloud, direction_eig, origin_eig, distance);
return (pt_pcl_index);
}
void convert(const sensor_msgs::ImageConstPtr& depth_msg, PointCloud::Ptr& cloud_msg)
{
// Use correct principal point from calibration
float center_x = cameraModel.cx();
float center_y = cameraModel.cy();
// Combine unit conversion (if necessary) with scaling by focal length for computing (X,Y)
double unit_scaling = DepthTraits<T>::toMeters( T(1) );
float constant_x = unit_scaling / cameraModel.fx();
float constant_y = unit_scaling / cameraModel.fy();
float bad_point = std::numeric_limits<float>::quiet_NaN();
sensor_msgs::PointCloud2Iterator<float> iter_x(*cloud_msg, "x");
sensor_msgs::PointCloud2Iterator<float> iter_y(*cloud_msg, "y");
sensor_msgs::PointCloud2Iterator<float> iter_z(*cloud_msg, "z");
const T* depth_row = reinterpret_cast<const T*>(&depth_msg->data[0]);
int row_step = depth_msg->step / sizeof(T);
for (int v = 0; v < (int)cloud_msg->height; ++v, depth_row += row_step)
{
for (int u = 0; u < (int)cloud_msg->width; ++u, ++iter_x, ++iter_y, ++iter_z)
{
T depth = depth_row[u];
// Missing points denoted by NaNs
if (!DepthTraits<T>::valid(depth))
{
*iter_x = *iter_y = *iter_z = bad_point;
continue;
}
// Fill in XYZ
*iter_x = (u - center_x) * depth * constant_x;
*iter_y = (v - center_y) * depth * constant_y;
*iter_z = DepthTraits<T>::toMeters(depth);
}
}
}
bool objectSrv(jsk_smart_gui::point2screenpoint::Request &req,
jsk_smart_gui::point2screenpoint::Response &res)
{
ROS_INFO("3dtopixel request:x=%lf,y=%lf,z=%lf",req.point.point.x,req.point.point.y,req.point.point.z);
geometry_msgs::PointStamped point_transformed;
tf_listener_.transformPoint(camera_topic, req.point, point_transformed);
cv::Point3d xyz;
cv::Point2d uv_rect;
xyz.x = point_transformed.point.x;
xyz.y = point_transformed.point.y;
xyz.z = point_transformed.point.z;
uv_rect = cam_model_.project3dToPixel(xyz);
res.x=uv_rect.x;
res.y=uv_rect.y;
return true;
}
void infoCb(const sensor_msgs::CameraInfo& msg)
{
model.fromCameraInfo(msg);
//SHUTDOWN LATER #HACK
}
void imageCb2(const sensor_msgs::ImageConstPtr& msg, const sensor_msgs::CameraInfoConstPtr& info_msg) {
MySecond.clear();
Ccount++;
cam_model_right.fromCameraInfo(info_msg);
cv_bridge::CvImagePtr cv_ptr;
try
{
cv_ptr = cv_bridge::toCvCopy(msg, sensor_msgs::image_encodings::MONO8);
}
catch (cv_bridge::Exception& e)
{
ROS_ERROR("cv_bridge exception: %s", e.what());
return;
}
if (Ccount == 0)
return;
Mat image, gray, temp, mask;
image = cv_ptr->image;
mask = image.clone();
int niters = 1;
dilate(mask, temp, Mat(), Point(-1, -1), niters);
erode(temp, temp, Mat(), Point(-1, -1), niters * 2);
dilate(temp, temp, Mat(), Point(-1, -1), niters);
threshold(temp, temp, 200, 255, CV_THRESH_BINARY);
for (int i = 0; i <= 5; i++) {
for (int j = 1000; j < temp.cols; j++) {
temp.at<uchar>(i, j) = 0;
}
}
vector<vector<Point> > contours1, contours2;
vector<Vec4i> hierarchy;
findContours(temp, contours2, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);
int cmin = 0;
int cmax = 100;
for (int i = 0; i < contours2.size(); i++) {
if (contours2[i].size() < cmin || contours2[i].size() > cmax) {
continue;
}
else
contours1.push_back(contours2[i]);
}
image = Scalar(255, 255, 255);
std::vector<std::vector<cv::Point> > ::iterator itc;
itc = contours1.begin();
MyPoint TTEMP;
while (itc != contours1.end()) {
cv::Moments mom = cv::moments(cv::Mat(*itc++));
#ifdef DEBUG
cv::circle(image, cv::Point(mom.m10 / mom.m00, mom.m01 / mom.m00), 2, cv::Scalar(0), 2);
#endif
TTEMP.x = mom.m10 / mom.m00;
TTEMP.y = mom.m01 / mom.m00;
if (TTEMP.x == 0 && TTEMP.y == 0)
return;
MySecond.push_back(TTEMP);
}
#ifdef DEBUG
cv::imshow(OPENCV_WINDOW2, cv_ptr->image);
cv::waitKey(3);
#endif
}
void imageCb(const sensor_msgs::ImageConstPtr& msg, const sensor_msgs::CameraInfoConstPtr& info_msg) {
MyFirst.clear();
Ccount1++;
cv_bridge::CvImageConstPtr cv_ptr;
double cur = ros::Time::now().toSec();
// lpf_x.set_cutoff_freq(0);
// lpf_x.get_lpf(10);
try
{
cv_ptr = cv_bridge::toCvShare(msg, sensor_msgs::image_encodings::MONO8);
}
catch (cv_bridge::Exception& e)
{
ROS_ERROR("cv_bridge exception: %s", e.what());
return;
}
cam_model_left.fromCameraInfo(info_msg);
// cout << "dist " << info_msg->D[0] << " " << info_msg->D[1] << " " << info_msg->D[2] << " " << endl;
Mat image, gray, temp, mask;
image = cv_ptr->image;
mask = image.clone();
int niters = 1;
dilate(mask, temp, Mat(), Point(-1, -1), niters);
erode(temp, temp, Mat(), Point(-1, -1), niters * 2);
dilate(temp, temp, Mat(), Point(-1, -1), niters);
threshold(temp, temp, 200, 255, CV_THRESH_BINARY);
for (int i = 0; i <= 5; i++) {
for (int j = 1000; j < temp.cols; j++) {
temp.at<uchar>(i, j) = 0;
}
}
vector<vector<Point> > contours1, contours2;
vector<Vec4i> hierarchy;
findContours(temp, contours2, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);
int cmin = 0;
int cmax = 100;
for (int i = 0; i < contours2.size(); i++) {
if (contours2[i].size() < cmin || contours2[i].size() > cmax) {
continue;
}
else
contours1.push_back(contours2[i]);
}
image = Scalar(255, 255, 255);
std::vector<std::vector<cv::Point> > ::iterator itc;
itc = contours1.begin();
MyPoint TTEMP;
while (itc != contours1.end()) {
cv::Moments mom = cv::moments(cv::Mat(*itc++));
#ifdef DEBUG
cv::circle(image, cv::Point(mom.m10 / mom.m00, mom.m01 / mom.m00), 2, cv::Scalar(0), 2);
#endif
TTEMP.x = mom.m10 / mom.m00;
TTEMP.y = mom.m01 / mom.m00;
MyFirst.push_back(TTEMP);
}
#ifdef DEBUG
cv::imshow(OPENCV_WINDOW, cv_ptr->image);
//Rect rect(MyFirst[0].x - 50, MyFirst[0].y- 50, 100, 100);
//Mat subimage = cv_ptr->image(rect);
//cv::imshow(OPENCV_WINDOW, subimage);
cv::waitKey(3);
#endif
vector<My3DPoint> myvec;
My3DPoint myTempVec;
#ifdef DEBUG
//cout << Ccount << " " << MyFirst[0].y << " " << MySecond[0].y << endl;
#endif
// cout << "size : " << MyFirst.size() << "," << MySecond.size() << endl;
if (MyFirst.size() && MySecond.size()) {
// cout << MyFirst[0].x << "," << MyFirst[0].y << endl;
cv::Point2d left_pt(MyFirst[0].x, MyFirst[0].y);
cv::Point2d right_pt(MySecond[0].x, MySecond[0].y);
cam_model_left.rectifyPoint(left_pt);
Matrix<float, 3, 1> Z;
Matrix<float, 6, 1> RES_KALMAN;
Z<<
MyFirst[0].x,
MySecond[0].x,
(MyFirst[0].y + MySecond[0].y) / 2.0f;
RES_KALMAN = kalman_xyz.getKalman(Z);
cout << "???" << endl;
cout << RES_KALMAN << endl;;
// cout << cam_model_left.rectifyPoint(left_pt).x << "," << cam_model_left.rectifyPoint(left_pt).y << "rectified" << endl;
// cout << cam_model_right.rectifyPoint(right_pt).x << "," << cam_model_right.rectifyPoint(right_pt).y << "rectified" << endl;
// cout << "notcal :: " << MyFirst[0].y - MySecond[0].y << endl;
// cout << "calibr :: " << cam_model_left.rectifyPoint(left_pt).y - cam_model_right.rectifyPoint(right_pt).y << endl;
float leftpt_y = MyFirst[0].y;
Matrix<float, 2, 1> X_kalman = kalman_x.getKalman(leftpt_y);
// cout << "KALMAN" << kalman_x.getKalman_1(leftpt_y) << "," << leftpt_y << endl;;
geometry_msgs::Point drone1_msg;
drone1_msg.x = leftpt_y;//get_lpf(&lpf_x,10);
drone1_msg.y = X_kalman(0, 0); //get_lpf(&lpf_z,10);
drone1_msg.z = X_kalman(1, 0); //get_lpf(&lpf_y,5);
pub_drone[0].publish(drone1_msg);
cv::Point3d ptr_left = cam_model_left.projectPixelTo3dRay(left_pt);
cv::Point3d ptr_right = cam_model_right.projectPixelTo3dRay(right_pt);
// getKalman_1();
// cout << ptr_left.y - ptr_right.y << endl;
// cout << "left 3d :: " << ptr_left.x << "," << ptr_left.y << "," << ptr_left.z << endl;
// cout << "right 3d :: " << ptr_right.x << "," << ptr_right.y << "," << ptr_right.z << endl << endl;
ptr_left = cam_model_left.projectPixelTo3dRay(cam_model_left.rectifyPoint(left_pt));
ptr_right = cam_model_right.projectPixelTo3dRay(cam_model_right.rectifyPoint(right_pt));
// cout << ptr_left.y - ptr_right.y << endl;
// cout << "left 3d :: " << ptr_left.x << "," << ptr_left.y << "," << ptr_left.z << endl;
// cout << "right 3d :: " << ptr_right.x << "," << ptr_right.y << "," << ptr_right.z << endl;
}
// cout << MySecond[0].x << "," << MySecond[0].y << endl;
if (Ccount == 1) {
sort(MyFirst.begin(), MyFirst.end(), MyCompare);
sort(MySecond.begin(), MySecond.end(), MyCompare);
Dron_size = MyFirst.size();
for (int i = 0; i < Dron_size; i++) {
double a1, b1, c1;
// cout << "hello " << MyFirst[i].x - MySecond[i].x << endl;
c1 = 2.97 * 450 / ((MyFirst[i].x - MySecond[i].x) * 0.00375);
a1 = (2.97 * 450 / ((MyFirst[i].x - MySecond[i].x) * 0.00375)) * (0.00375 * (MyFirst[i].x + MySecond[i].x - 1280)) / (2 * 2.97);
b1 = (-0.00375) * ((MyFirst[i].y + MySecond[i].y) / 2 - 480) * (2.97 * 450 / ((MyFirst[i].x - MySecond[i].x) * 0.00375)) / 2.97;
Current_Loc[i].x = a1;
Current_Loc[i].y = b1 * cos(Angle * PI / 180.0) - c1 * sin(Angle * PI / 180.0);
Current_Loc[i].z = b1 * sin(Angle * PI / 180.0) + c1 * cos(Angle * PI / 180.0);
a1 = Current_Loc[i].x;
b1 = Current_Loc[i].y;
c1 = Current_Loc[i].z;
Current_Loc[i].x = a1 * cos(Angle2 * PI / 180.0) - b1 * sin(Angle2 * PI / 180.0);
Current_Loc[i].y = a1 * sin(Angle2 * PI / 180.0) + b1 * cos(Angle2 * PI / 180.0);
Current_Loc[i].z = c1;
a1 = Current_Loc[i].x;
b1 = Current_Loc[i].y;
c1 = Current_Loc[i].z;
Current_Loc[i].x = a1 * cos(Angle3 * PI / 180.0) + c1 * sin(Angle3 * PI / 180.0);
Current_Loc[i].y = b1;
Current_Loc[i].z = -a1 * sin(Angle3 * PI / 180.0) + c1 * cos(Angle3 * PI / 180.0);
}
for (int i = 0; i < Dron_size; i++) {
Real_Dron_Loc[i].x = (Current_Loc[i].x);
Real_Dron_Loc[i].y = (Current_Loc[i].y);
Real_Dron_Loc[i].z = (Current_Loc[i].z);
}
Frame_S_time = clock();
for (int i = 0; i < Dron_size; i++) {
Velocity[i].x = 0;
Velocity[i].y = 0;
Velocity[i].z = 0;
}
}
else {
if (MyFirst.size() != Dron_size || MySecond.size() != Dron_size)
return;
Frame_E_time = clock();
Time = (double)(Frame_E_time - Frame_S_time) / CLOCKS_PER_SEC;
Frame_S_time = Frame_E_time;
for (int i = 0; i < Dron_size; i++) {
Acummulate_Time[i] += Time;
Track_Loc[i].x = Current_Loc[i].x;// + Acummulate_Time[i] * Velocity[i].x;
Track_Loc[i].y = Current_Loc[i].y;// + Acummulate_Time[i] * Velocity[i].y;
Track_Loc[i].z = Current_Loc[i].z;// + Acummulate_Time[i] * Velocity[i].z;
}
for (int k = 0; k < Dron_size; k++) {
double closest_dis = 987654321;
My3DPoint closest_3DPoint;
closest_3DPoint.x = 0;
closest_3DPoint.y = 0;
closest_3DPoint.z = 0;
int flag = 0;
int AA = 999, BB = 888;
for (int i = 0; i < MyFirst.size(); i++) {
for (int j = 0; j < MySecond.size(); j++) {
double a1, b1, c1;
double aa1, bb1, cc1;
cout << "depth : " << MyFirst[i].x - MySecond[j].x << endl;
c1 = 2.97 * 450.0 / ((MyFirst[i].x - MySecond[j].x) * 0.00375);
a1 = (2.97 * 450.0 / ((MyFirst[i].x - MySecond[j].x) * 0.00375)) * (0.00375 * (MyFirst[i].x + MySecond[j].x - 1280.0)) / (2.0 * 2.97);
b1 = (-0.00375) * ((MyFirst[i].y + MySecond[j].y) / 2 - 480.0) * (2.97 * 450.0 / ((MyFirst[i].x - MySecond[j].x) * 0.00375)) / 2.97;
aa1 = a1;
bb1 = b1 * cos(Angle * PI / 180.0) - c1 * sin(Angle * PI / 180.0);
cc1 = b1 * sin(Angle * PI / 180.0) + c1 * cos(Angle * PI / 180.0);
a1 = aa1;
b1 = bb1;
c1 = cc1;
aa1 = a1 * cos(Angle2 * PI / 180.0) - b1 * sin(Angle2 * PI / 180.0);
bb1 = a1 * sin(Angle2 * PI / 180.0) + b1 * cos(Angle2 * PI / 180.0);
cc1 = c1;
a1 = aa1;
b1 = bb1;
c1 = cc1;
aa1 = a1 * cos(Angle3 * PI / 180.0) + c1 * sin(Angle3 * PI / 180.0);
bb1 = b1;
cc1 = -a1 * sin(Angle3 * PI / 180.0) + c1 * cos(Angle3 * PI / 180.0);
if ((sqrt(pow(Track_Loc[k].x - aa1, 2) + pow(Track_Loc[k].y - bb1, 2) + pow(Track_Loc[k].z - cc1, 2)) < closest_dis) && sqrt(pow(Track_Loc[k].x - aa1, 2) + pow(Track_Loc[k].y - bb1, 2) + pow(Track_Loc[k].z - cc1, 2)) < 300 ) {
closest_dis = sqrt(pow(Track_Loc[k].x - aa1, 2) + pow(Track_Loc[k].y - bb1, 2) + pow(Track_Loc[k].z - cc1, 2));
closest_3DPoint.x = aa1;
closest_3DPoint.y = bb1;
closest_3DPoint.z = cc1;
AA = i;
BB = j;
}
}
}
#ifdef DEBUG
cout << MyFirst.size() << " " << MySecond.size() << endl;
cout << AA << " " << BB << endl;
cout << closest_dis << endl;
cout << closest_3DPoint.x << " " << closest_3DPoint.y << " " << closest_3DPoint.z << endl;
#endif
if (closest_dis == 987654321) {
continue;
}
else {
// pass
Acummulate_Time[k] = 0;
Current_Loc[k].x = closest_3DPoint.x;
Current_Loc[k].y = closest_3DPoint.y;
Current_Loc[k].z = closest_3DPoint.z;
}
cout << "Curren " << Current_Loc[k].x << " " << Current_Loc[k].y << " " << Current_Loc[k].z << endl;
cout << "-------------------------------------------------------------------------------" << endl << endl;
}
std_msgs::Float64 drone1_x_msg;
std_msgs::Float64 drone1_y_msg;
std_msgs::Float64 drone1_z_msg;
geometry_msgs::Point drone1_msg;
geometry_msgs::Point drone2_msg;
for (int i = 0; i < Dron_size; i++) {
Real_Dron_Loc[i].x = Current_Loc[i].x;
Real_Dron_Loc[i].y = Current_Loc[i].y;
Real_Dron_Loc[i].z = Current_Loc[i].z;
#ifdef DEBUG
cout << setw(10) << Real_Dron_Loc[i].x << " " << setw(10) << Real_Dron_Loc[i].y << " " << setw(10) << Real_Dron_Loc[i].z << endl;
#endif
static lpf_t lpf_x = {0, };
static lpf_t lpf_y = {0, };
static lpf_t lpf_z = {0, };
lpf_x.cur_time = lpf_y.cur_time = lpf_z.cur_time = ros::Time::now().toSec();
lpf_x.input = Real_Dron_Loc[i].x;
lpf_y.input = Real_Dron_Loc[i].y;
lpf_z.input = Real_Dron_Loc[i].z;
drone1_msg.x = Real_Dron_Loc[i].x;//get_lpf(&lpf_x,10);
drone1_msg.y = Real_Dron_Loc[i].z;//get_lpf(&lpf_z,10);
drone1_msg.z = Real_Dron_Loc[i].y;//get_lpf(&lpf_y,5);
drone2_msg.x = get_lpf(&lpf_x, 10);
drone2_msg.y = get_lpf(&lpf_z, 10);
drone2_msg.z = get_lpf(&lpf_y, 5);
// pub_drone[i].publish(drone1_msg);
// Nasang[i].publish(drone2_msg);
}
}
cout << "cb1 cycletime : " << ros::Time::now().toSec() - cur << endl;;
}
inline void
hit_same_point( const image_geometry::PinholeCameraModel &camera_model,
const pcl::PointCloud<PointT> &in,
pcl::PointCloud<PointT> &out,
int rows,
int cols,
float z_threshold = 0.3)
{
std::vector<std::vector <std::vector<PointT> > > hit( cols, std::vector< std::vector<PointT> >(rows, std::vector<PointT>()));
// Project points into image space
for(unsigned int i=0; i < in.points.size(); ++i){
const PointT* pt = &in.points.at(i);
if( pt->z > 1) { // min distance from camera 1m
cv::Point2i point_image = camera_model.project3dToPixel(cv::Point3d(pt->x, pt->y, pt->z));
if( between<int>(0, point_image.x, cols )
&& between<int>( 0, point_image.y, rows )
)
{
// Sort all points into image
{
hit[point_image.x][point_image.y].push_back(in.points.at(i));
}
}
}
}
assert(out.empty());
for(int x = 0; x < hit.size(); ++x ){
for(int y = 0; y < hit[0].size(); ++y){
if(hit[x][y].size()>1){
PointT min_z = hit[x][y][0];
float max_z = min_z.z;
for(int p = 1; p < hit[x][y].size(); ++p){
// find min and max z
max_z = MAX(max_z, hit[x][y][p].z);
#ifdef DEBUG
std::cout << hit[x][y].size() << "\t";
#endif
if(hit[x][y][p].z < min_z.z)
{
min_z = hit[x][y][p];
}
}
#ifdef DEBUG
std::cout << min_z.z << "\t" << max_z << "\t";
#endif
if(max_z - min_z.z > z_threshold){
#ifdef DEBUG
std::cout << min_z << std::endl;
#endif
out.push_back(min_z);
}
}
}
}
#ifdef DEBUG
std::cout << "hit_same_point in: "<< in.size() << "\t out: " << out.size() << "\n";
#endif
}
void FeatureTracker::image_callback(const sensor_msgs::ImageConstPtr& msg, const sensor_msgs::CameraInfoConstPtr& info_msg) {
//need pose data for each picture, need to publish a camera pose
ros::Time acquisition_time = msg->header.stamp;
geometry_msgs::PoseStamped basePose;
geometry_msgs::PoseStamped mapPose;
basePose.pose.orientation.w=1.0;
ros::Duration timeout(3);
basePose.header.frame_id="/base_link";
mapPose.header.frame_id="/map";
try {
tf_listener_.waitForTransform("/camera_1_link", "/map", acquisition_time, timeout);
tf_listener_.transformPose("/map", acquisition_time,basePose,"/camera_1_link",mapPose);
printf("pose #%d %f %f %f\n",pic_number++,mapPose.pose.position.x, mapPose.pose.position.y, tf::getYaw(mapPose.pose.orientation));
}
catch (tf::TransformException& ex) {
ROS_WARN("[map_maker] TF exception:\n%s", ex.what());
printf("[map_maker] TF exception:\n%s", ex.what());
return;
}
cam_model.fromCameraInfo(info_msg);
// printf("callback called\n");
try
{
// if you want to work with color images, change from mono8 to bgr8
if(image_rect==NULL){
image_rect = cvCloneImage(bridge.imgMsgToCv(msg, "mono8"));
last_image= cvCloneImage(bridge.imgMsgToCv(msg, "mono8"));
pyrA=cvCreateImage(cvSize(last_image->width+8,last_image->height/3.0), IPL_DEPTH_32F, 1);
pyrB=cvCloneImage(pyrA);
// printf("cloned image\n");
}
else{
//save the last image
cvCopy(image_rect,last_image);
cvCopy(bridge.imgMsgToCv(msg, "mono8"),image_rect);
// printf("copied image\n");
}
if(output_image==NULL){
output_image =cvCloneImage(image_rect);
}
if(eigImage==NULL){
eigImage =cvCloneImage(image_rect);
}
if(tempImage==NULL){
tempImage =cvCloneImage(image_rect);
}
}
catch (sensor_msgs::CvBridgeException& e)
{
ROS_ERROR("Could not convert from '%s' to 'mono8'.", msg->encoding.c_str());
return;
}
if(image_rect!=NULL) {
cvCopy(image_rect,output_image);
printf("got image\n");
track_features(mapPose);
//draw features on the image
for(int i=0;i<last_feature_count;i++){
CvPoint center=cvPoint((int)features[i].x,(int)features[i].y);
cvCircle(output_image,center,10,cvScalar(150),2);
char strbuf [10];
int n=sprintf(strbuf,"%d",current_feature_id[ i] );
std::string text=std::string(strbuf,n);
CvFont font;
cvInitFont(&font,CV_FONT_HERSHEY_SIMPLEX,1,1);
cvPutText(output_image,text.c_str(),cvPoint(center.x,center.y+20),&font,cvScalar(255));
cv::Point3d tempRay;
cv::Point2d tempPoint=cv::Point2d(features[i]);
cam_model.projectPixelTo3dRay(tempPoint,tempRay);
// printf("%f x %f y %f z\n",tempRay.x,tempRay.y,tempRay.z);
}
// featureList[0].print();
//determine error gradient
int min_features=10;
// printf("ypr %f %f %f\n",yaw,pitch,roll);
cv::Point3d error_sum=calc_error(min_features,0, 0, 0);
printf("total error is : %f\n",error_sum.x);
for(int i=0;i<featureList.size();i++){
if(min_features<featureList[i].numFeatures()){
printf("\n\n\nfeature %d\n",i);
printf("mean: %f %f %f\n",featureList[i].currentMean.x, featureList[i].currentMean.y, featureList[i].currentMean.z);
}
}
// double error_up= calc_error(min_features,yalpha, 0, 0);
// printf("total up yaw error is : %f\n",error_up);
// double error_down= calc_error(min_features,-yalpha, 0, 0);
// printf("total down yaw error is : %f\n",error_down);
/*
double yaw_change=0;
if(error_up<error_sum && error_up<error_down){
yaw_change=yalpha;
}else if(error_down<error_sum && error_down<error_up){
yaw_change=-yalpha;
}else if(error_down!=error_sum&&error_sum!=error_up){
yalpha/=2;
}
error_up= calc_error(min_features,0,palpha, 0);
// printf("total up pitch error is : %f\n",error_up);
error_down= calc_error(min_features,0,-palpha, 0);
// printf("total down pitch error is : %f\n",error_down);
double pitch_change=0;
if(error_up<error_sum && error_up<error_down){
pitch_change=palpha;
}else if(error_down<error_sum && error_down<error_up){
pitch_change=-palpha;
}else if(error_down!=error_sum&&error_sum!=error_up){
//palpha/=2;
}
error_up= calc_error(min_features,0,0,ralpha);
// printf("total up roll error is : %f\n",error_up);
error_down= calc_error(min_features,0,0,-ralpha);
// printf("total down roll error is : %f\n",error_down);
double roll_change=0;
if(error_up<error_sum && error_up<error_down){
roll_change=ralpha;
}else if(error_down<error_sum && error_down<error_up){
roll_change=-ralpha;
}else if(error_down!=error_sum&&error_sum!=error_up){
ralpha/=2;
}
// yaw+=yaw_change;
// pitch+=pitch_change;
// roll+=roll_change;
*/
try{
sensor_msgs::Image output_image_cvim =*bridge.cvToImgMsg(output_image, "mono8");
output_image_cvim.header.stamp=msg->header.stamp;
analyzed_pub_.publish(output_image_cvim);
}
catch (sensor_msgs::CvBridgeException& e){
ROS_ERROR("Could not convert from '%s' to 'mono8'.", msg->encoding.c_str());
return;
}
// printf("displaying image\n");
}else{
// printf("null image_rect\n");
}
}
// this function is called each frame
void glutDisplay (void)
{
static ros::Duration pub_interval(1.0/pub_rate_temp_);
static ros::Time last_pub(0.0);
static int num_skipped = 0;
num_skipped++;
ros::Time now_time = ros::Time::now();
// Update stuff from OpenNI
XnStatus status = g_Context.WaitAndUpdateAll();
if( status != XN_STATUS_OK ){
ROS_ERROR_STREAM("Updating context failed: " << status);
return;
}
xn::SceneMetaData sceneMD;
xn::DepthMetaData depthMD;
xn::ImageMetaData imageMD;
g_DepthGenerator.GetMetaData(depthMD);
g_UserGenerator.GetUserPixels(0, sceneMD);
//g_ImageGenerator.GetMetaData(imageMD);
cv::Mat depth_image;
getDepthImage(depthMD, depth_image);
double minval, maxval;
cv::minMaxLoc(depth_image, &minval, &maxval);
// Convert user pixels to an OpenCV image
cv::Mat label_image;
getUserLabelImage(sceneMD, label_image);
sensor_msgs::PointCloud cloud;
cloud.header.stamp = now_time;
cloud.header.frame_id = frame_id_;
cloud.channels.resize(1);
cloud.channels[0].name = "intensity";
// Convert users into better format
XnUserID aUsers[15];
XnUInt16 nUsers = 15;
g_UserGenerator.GetUsers(aUsers, nUsers);
cv::Mat this_mask;
XnPoint3D center_mass;
double pixel_area;
cv::Scalar s;
vector<user> users;
if( g_bhasCal && now_time-last_pub > pub_interval )
{
bool has_lock = false;
last_pub = now_time;
ROS_DEBUG_STREAM(num_skipped << " refreshes inbetween publishing");
num_skipped = 0;
cv::imshow( "Tracked user" , user_cal_.getImage() );
cv::imshow( "Original calibration", original_cal_.getImage() );
cv::Mat rgb, rgb_mask;
// getRGB(rgb, rgb_mask);
rgb = getRGB(imageMD);
for (unsigned int i = 0; i < nUsers; i++)
{
user this_user;
this_user.uid = aUsers[i];
// Bitwise mask of pixels belonging to this user
this_mask = (label_image == this_user.uid);
this_user.numpixels = cv::countNonZero(this_mask);
// Compare this user to the target
this_user.pc.init(rgb, this_mask);
double similarity = this_user.pc.compare(user_cal_ );
double sim_to_orig = this_user.pc.compare(original_cal_);
this_user.similarity = similarity;
this_user.similarity_to_orig = sim_to_orig;
/*
ros::Time t1 = ros::Time::now();
double emd = this_user.pc.getEMD (user_cal_ );
double emd_to_orig = this_user.pc.getEMD (original_cal_);
ros::Duration d = (ros::Time::now() - t1);
ROS_INFO_STREAM("EMD took " << (d.sec) );*/
if( now_time > save_timer_ ){
ROS_WARN_STREAM("[bk_skeletal_tracker] Say Cheezbuger");
save_timer_ = now_time + ros::Duration(60*60*24);
g_bSaveFrame = true;
}
if( g_bSaveFrame )
{
time_t t = ros::WallTime::now().sec;
char buf[1024] = "";
struct tm* tms = localtime(&t);
strftime(buf, 1024, "%Y-%m-%d-%H-%M-%S", tms);
std::string prefix = ( boost::format("capture_%s_user%d") % buf % this_user.uid ).str();
cv::Mat rgb_masked;
rgb.copyTo(rgb_masked, this_mask);
saveMat(rgb_masked , prefix + "_rgb" );
saveMat(this_mask , prefix + "_mask" );
saveMat(this_user.pc.getHist() , prefix + "_hist" );
saveMat(this_user.pc.getImage(), prefix + "_himg" );
}
// Mean depth
this_user.meandepth = cv::mean(depth_image, this_mask)[0];
this_user.silhouette_area = 0;
// Find the area of the silhouette in cartesian space
for( int i=0; i<this_mask.rows; i++) {
for( int j=0; j<this_mask.cols; j++ ) {
if( this_mask.at<uchar>(i,j) != 0 )
{
pixel_area = cam_model_.getDeltaX(1, depth_image.at<float>(i,j))
* cam_model_.getDeltaY(1, depth_image.at<float>(i,j));
this_user.silhouette_area += pixel_area;
}
}
}
// Find the center in 3D
g_UserGenerator.GetCoM(this_user.uid, center_mass);
this_user.center3d.point = vecToPt(center_mass);
ROS_DEBUG_STREAM(boost::format("User %d: area %.3fm^2, mean depth %.3fm")
% (unsigned int)this_user.uid % this_user.silhouette_area % this_user.meandepth);
// Screen out unlikely users based on area
if( this_user.meandepth > min_dist_ && this_user.silhouette_area < max_area_ && this_user.silhouette_area > min_area_ )
{
ROS_INFO_STREAM(boost::format("User %d new: %.0f --- orig: %.0f")
% ((int)this_user.uid) % (100*similarity) % (100*sim_to_orig) );
/*ROS_INFO_STREAM(boost::format("EMD new: %.2f --- orig: %.2f")
% (emd) % (emd_to_orig) );*/
if( similarity > PersonCal::getMatchThresh() ) {
user_cal_.update(rgb, this_mask);
}
else{
if( sim_to_orig > PersonCal::getMatchThresh() ) {
ROS_WARN_STREAM("Reset to original calibration");
user_cal_ = original_cal_;
}
}
std::stringstream window_name;
window_name << "user_" << ((int)this_user.uid);
cv::imshow(window_name.str(), this_user.pc.getImage());
ROS_DEBUG("Accepted user");
users.push_back(this_user);
// Visualization
geometry_msgs::Point32 p;
p.x = this_user.center3d.point.x;
p.y = this_user.center3d.point.y;
p.z = this_user.center3d.point.z;
cloud.points.push_back(p);
cloud.channels[0].values.push_back(0.0f);
}
}
// Try to associate the tracker with a user
if( latest_tracker_.first != "" )
{
// Transform the tracker to this time. Note that the pos time is updated but not the restamp.
tf::Point pt;
tf::pointMsgToTF(latest_tracker_.second.pos.pos, pt);
tf::Stamped<tf::Point> loc(pt, latest_tracker_.second.pos.header.stamp, latest_tracker_.second.pos.header.frame_id);
try {
tfl_->transformPoint(frame_id_, now_time-ros::Duration(.1), loc, latest_tracker_.second.pos.header.frame_id, loc);
latest_tracker_.second.pos.header.stamp = now_time;
latest_tracker_.second.pos.header.frame_id = frame_id_;
latest_tracker_.second.pos.pos.x = loc[0];
latest_tracker_.second.pos.pos.y = loc[1];
latest_tracker_.second.pos.pos.z = loc[2];
}
catch (tf::TransformException& ex) {
ROS_ERROR("(finding) Could not transform person to this time");
}
people_msgs::PositionMeasurement pos;
if( users.size() > 0 )
{
std::stringstream users_ss;
users_ss << boost::format("(finding) Tracker \"%s\" = (%.2f,%.2f) Users = ")
% latest_tracker_.first % latest_tracker_.second.pos.pos.x % latest_tracker_.second.pos.pos.y;
// Find the closest user to the tracker
user closest;
closest.distance = BIGDIST_M;
foreach(user u, users)
{
u.distance = pow(latest_tracker_.second.pos.pos.x - u.center3d.point.x, 2.0)
+ pow(latest_tracker_.second.pos.pos.y - u.center3d.point.y, 2.0);
users_ss << boost::format("(%.2f,%.2f), ") % u.center3d.point.x % u.center3d.point.y;
if( u.distance < closest.distance )
{
if( u.similarity > PersonCal::getMatchThresh() ) {
closest = u;
}
else {
ROS_WARN_STREAM("Ignored close user not matching (" << u.uid << ")");
}
}
}//foreach
void depthCallback(const sensor_msgs::ImageConstPtr& original_image, const sensor_msgs::CameraInfoConstPtr& info)
{
if(is_robot_running==0 && balls_written==1 && ball_chosen==0){
cv_bridge::CvImagePtr cv_ptr;
try
{
cv_ptr = cv_bridge::toCvCopy(original_image, sensor_msgs::image_encodings::TYPE_16UC1);
}
catch (cv_bridge::Exception& e)
{
ROS_ERROR("tutorialROSOpenCV::main.cpp::cv_bridge exception: %s", e.what());
return;
}
cam_model.fromCameraInfo(info);
Mat depth_image = cv_ptr->image;
if(balls_written == 1){
for( size_t i = 0; i < circles_all.size(); i++ ){
if (pilki[i]!=0){
cv::Point2d uv_point(circles_all[i][0], circles_all[i][1]);
unsigned short ball_depth;
ball_depth = depth_image.at<unsigned short>(circles_all[i][1], circles_all[i][0])+20;
cv::Point3d xy_point;
xy_point = cam_model.projectPixelTo3dRay(uv_point);
xy_point = xy_point * ball_depth;
geometry_msgs::PointStamped xy_point_stamped, odom_point_stamped;
xy_point_stamped.header.frame_id = "/camera_rgb_optical_frame";
xy_point_stamped.header.stamp = ros::Time::now();
xy_point_stamped.point.x = 0.001*xy_point.x;
xy_point_stamped.point.y = 0.001*xy_point.y;
xy_point_stamped.point.z = 0.001*xy_point.z;
try {
tf_listener->waitForTransform("/base_link", "/camera_rgb_optical_frame", ros::Time::now(), ros::Duration(10.0) );
tf_listener->transformPoint("/base_link", xy_point_stamped, odom_point_stamped);
}
catch (tf::TransformException ex) {
ROS_ERROR("%s",ex.what());
}
if(odom_point_stamped.point.z > 0.05 || odom_point_stamped.point.z < 0.001){
std::cout << "Srodek pilki na wysokosci: " << odom_point_stamped.point.z << ".\n";
std::cout << "Skondensowane pilki: to nie pilka, jest za wysoko albo za nisko! \n";
pilki[i]=0;
}
}
}
depth_written = 1;
std::cout << "Policzylem wysokosc dla skondensowanych pilek \n";
int closest_ball = choose_closest_ball();
if(closest_ball == -1){
std::cout << "NIE WYBRANO ZADNEJ PILKI \n";
send_no_balls();
}
if(closest_ball != -1){
int wybrana_x = circles_all[closest_ball][0];
int wybrana_y = circles_all[closest_ball][1];
int wybrana_z = circles_all[closest_ball][2];
ball_chosen = 1;
std::cout << "Wybrana jedna pilka \n";
last_circle[0] = wybrana_x;
last_circle[1] = wybrana_y;
last_circle[2] = wybrana_z;
wybrana.x = last_circle[0];
wybrana.y = last_circle[1];
wybrana.z = last_circle[2];
draw_balls = 1;
cv::Point2d uv_point(wybrana.x, wybrana.y);
unsigned short ball_depth;
ball_depth = depth_image.at<unsigned short>(wybrana.y,wybrana.x)+20;
geometry_msgs::Point message_selected;
cv::Point3d xy_point;
xy_point = cam_model.projectPixelTo3dRay(uv_point);
xy_point = xy_point * ball_depth;
geometry_msgs::PointStamped xy_point_stamped, odom_point_stamped;
xy_point_stamped.header.frame_id = "/camera_rgb_optical_frame";
xy_point_stamped.header.stamp = ros::Time::now();
xy_point_stamped.point.x = 0.001*xy_point.x;
xy_point_stamped.point.y = 0.001*xy_point.y;
xy_point_stamped.point.z = 0.001*xy_point.z;
try {
tf_listener->waitForTransform("/odom", "/camera_rgb_optical_frame", ros::Time::now(), ros::Duration(10.0) );
tf_listener->transformPoint("/odom", xy_point_stamped, odom_point_stamped);
}
catch (tf::TransformException ex) {
ROS_ERROR("%s",ex.what());
}
if(odom_point_stamped.point.z > 0.05){
std::cout << "Wybrana pilka to nie pilka, jest za wysoko! \n";
}
std::cout << "Policzylem dla wybranej pilki i publikuje \n";
//balls.publish(wybrana);
selected_ball.publish(odom_point_stamped);
licznik_depth = 0;
ball_chosen = 0;
circles_all.clear();
pilki.clear();
licznik_wybrane = 0;
no_balls_counter = 0;
balls_written = 0;
depth_written = 0;
is_robot_running = 1;
}
}
}
}
void locator()
{
namedWindow("Tracking");
int hMin, hMax, sMin, sMax, vMin, vMax,area_min;
hMin = 0;
//hMax = 124; // night values/???
hMax = 255;
//sMin = 95;
sMin = 126;
sMax = 255;
//vMin = 139;
vMin = 173;
vMax = 255;
area_min = 100;
Mat smoothed, hsvImg, t_img;
createTrackbar("blob min area","Tracking" ,&area_min ,1000);
createTrackbar("Hue Min", "Tracking", &hMin, 255);
createTrackbar("Hue Max", "Tracking", &hMax, 255);
createTrackbar("Sat Min", "Tracking", &sMin, 255);
createTrackbar("Sat Max", "Tracking", &sMax, 255);
createTrackbar("Val Min", "Tracking", &vMin, 255);
createTrackbar("Val MaX", "Tracking", &vMax, 255);
while(ros::ok())
{
Mat source = imageB;
Mat copy = imageB.clone();
GaussianBlur(source, smoothed, Size(9,9), 4);
cvtColor(smoothed, hsvImg, CV_BGR2HSV);
inRange(hsvImg, Scalar(hMin, sMin, vMin), Scalar(hMax, sMax, vMax), t_img);
CBlobResult blob;
IplImage i_img = t_img;
blob = CBlobResult(&i_img,NULL,0);
int num_blobs = blob.GetNumBlobs();
blob.Filter(blob, B_INCLUDE, CBlobGetArea(), B_INSIDE, area_min, blob_area_absolute_max_);
num_blobs = blob.GetNumBlobs();
std::string reference_frame = "/virtual_table"; // Table frame at ball_radius above the actual table plane
tf::StampedTransform transform;
tf_.waitForTransform(reference_frame, model.tfFrame(), ros::Time(0), ros::Duration(0.5));
tf_.lookupTransform(reference_frame, model.tfFrame(), ros::Time(0), transform);
for(int i =0;i<num_blobs;i++)
{
CBlob* bl = blob.GetBlob(i);
Point2d uv(CBlobGetXCenter()(*bl), CBlobGetYCenter()(*bl));
//Use the width as the height
uv.y = bl->MinY() + (bl->MaxX() - bl->MinX()) * 0.5;
circle(copy,uv,50,Scalar(255,0,0),5);
cv::Point3d xyz;
model.projectPixelTo3dRay(uv, xyz);
// Intersect ray with plane in virtual table frame
//Origin of camera frame wrt virtual table frame
tf::Point P0 = transform.getOrigin();
//Point at end of unit ray wrt virtual table frame
tf::Point P1 = transform * tf::Point(xyz.x, xyz.y, xyz.z);
// Origin of virtual table frame
tf::Point V0 = tf::Point(0.0,0.0,0.0);
// normal to the table plane
tf::Vector3 n(0, 0, 1);
// finding scaling value
double scale = (n.dot(V0-P0))/(n.dot(P1-P0));
tf::Point ball_pos = P0 + (P1-P0)*scale;
cout <<ball_pos.x() << " " << ball_pos.y() << " " << ball_pos.z() <<endl;
}
imshow(WINDOW, copy);
waitKey(3);
imshow("edited", t_img);
waitKey(3);
ros::spinOnce();
}
}
void cameraInfoCallback(const sensor_msgs::CameraInfoConstPtr& infoMsg)
{
cameraModel.fromCameraInfo(infoMsg);
}
void FeatureTracker::track_features(geometry_msgs::PoseStamped mapPose){
//set the initial number of features to the max number we want to find
int feature_count=num_features;
printf("pose %f %f %f\n",mapPose.pose.position.x, mapPose.pose.position.y, tf::getYaw(mapPose.pose.orientation));
int edge_pixels=5;
//check if there were features from the last image to keep tracking
if(last_feature_count>0){
//if there were call cvCalcOpticalFlowPyrLK();
//find matches between last good features and current image features
// store matches in featuresB
cvCalcOpticalFlowPyrLK(last_image,image_rect,pyrA,pyrB,features,featuresB, last_feature_count,cvSize(win_size,win_size) ,4,last_features_status,track_error, cvTermCriteria(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS,20,.3),0);
}
printf("got image flow\n");
// assign last_feature_id values for matched features and set the non matched spots to -1
//find new features and subpixel them
//I SHOULD ADD THE IMAGE FLOW VALUES AS FEATURES NOW BEFORE FINDING NEW FEATURES
//find all good features
cvGoodFeaturesToTrack(image_rect, eigImage, tempImage, features, &feature_count, quality_level, min_distance, NULL, block_size);
//subpixel good features
cvFindCornerSubPix(image_rect,features,feature_count,cvSize(win_size,win_size),cvSize(-1,-1),cvTermCriteria(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS,20,0.03));
printf("subpixeled image\n");
//for all the features in features B, find their matches in the newly found features
//add all the matches to their correct featuremanager, for the non matching, make a new
//feature manager and add them to it
//for all features by now we need their ray and the robot pose at that location
//draw dots on image where features are
//set the feature ids to a control value
for(int i=0;i<num_features;i++){
current_feature_id[i]=-1;
}
for(int i=0;i<last_feature_count;i++){
//for the previously found features in list b
if(last_features_status[i]>0){
for(int j=0;j<feature_count;j++){
//for every feature found in this image
//determine if the two overlap in a meaningful way
int xdiff=featuresB[i].x-features[j].x;
int ydiff=featuresB[i].y-features[j].y;
//if the pixels are within some margin of eachother
if(sqrt(xdiff*xdiff + ydiff*ydiff)<pixel_tracking_margin){
//if they do set the current id for j to the id of i
current_feature_id[j]=last_feature_id[i];
printf("feature found %d %d",last_feature_id[i],i);
}
}
}
}
printf("assigned IDs image\n");
for(int i=0;i<feature_count;i++){
printf("looping\n");
if(current_feature_id[i]>=0){
printf("prev feature match\n");
//if we matched a previous feature
//add our new feature to the previous features list
cv::Point3d tempRay;
cv::Point2d tempPoint=cv::Point2d(features[i]);
cam_model.projectPixelTo3dRay(tempPoint,tempRay);
if(tempPoint.x> edge_pixels && tempPoint.x < last_image->width- edge_pixels &&
tempPoint.y> edge_pixels && tempPoint.y<last_image->height- edge_pixels){
featureList[current_feature_id[i]].add(RawFeature(mapPose.pose.position.x, mapPose.pose.position.y, tf::getYaw(mapPose.pose.orientation), tempPoint,tempRay));
}else{
current_feature_id[i]=-1;
}
}else{
printf("new feature \n");
cv::Point3d tempRay;
cv::Point2d tempPoint=cv::Point2d(features[i]);
cam_model.projectPixelTo3dRay(tempPoint,tempRay);
if(tempPoint.x> edge_pixels && tempPoint.x < last_image->width- edge_pixels &&
tempPoint.y> edge_pixels && tempPoint.y<last_image->height- edge_pixels){
printf("new good feature \n");
//if we didn't
//create a new feature group in the list
current_feature_id[i]=feature_number;
//add the new feature to the feature list
featureList.push_back(FeatureManager());
featureList[feature_number].add(RawFeature(mapPose.pose.position.x, mapPose.pose.position.y, tf::getYaw(mapPose.pose.orientation), tempPoint,tempRay));
++feature_number;
}
}
}
// printf("features: ");
for(int i=0;i<num_features;i++){
if(i<feature_count){
last_feature_id[i]=current_feature_id[i];
}
else{
last_feature_id[i]=-1;
}
// printf(" %d ",current_feature_id[i]);
}
printf("\n");
last_feature_count=feature_count;
}
void PointXYZtoCameraPointXY(const geometry_msgs::Point input, geometry_msgs::Point &output, const image_geometry::PinholeCameraModel& model) {
output.x = (input.x*model.fx()/input.z)+model.cx();
output.y = (input.y*model.fy()/input.z)+model.cy();
}
cv::Mat projectWithEigen()
{
// Transform meshes into camera frame
// For each frame in vector
for (int frame = 0; frame < mMeshFrameIDs.size(); frame++)
{
// Lookup current transform
Eigen::Isometry3 transform;
transform = transforms.at(mMeshFrameIDs[frame]);
// Get copy of mesh for each frame
ap::Mesh* sourceMesh;
ap::Mesh* transformedMesh;
//std::cerr << "Getting frame " << frame << " : " << mMeshFrameIDs[frame] << std::endl;
MeshMap::iterator scene_i = scenes.find(mMeshFrameIDs[frame]);
if (scenes.end() == scene_i) { continue; }
sourceMesh = scene_i->second;
MeshMap::iterator scene_t = transformedScenes.find(mMeshFrameIDs[frame]);
if (transformedScenes.end() == scene_t) { continue; }
transformedMesh = scene_t->second;
// Transform mesh into camera frame
for (int i = 0; i < sourceMesh->vertices.size(); i++)
{
Eigen::Vector3 newVertex = transform * sourceMesh->vertices[i];
//std::cerr << mesh->vertices[i].transpose() << "\t->\t" << newVertex.transpose() << std::endl;
transformedMesh->vertices[i] = newVertex;
}
}
// For each pixel in camera image
cv::Mat robotImage(mCameraModel.cameraInfo().height, mCameraModel.cameraInfo().width, CV_32F);
float* pixelPtr = (float*)robotImage.data;
float maxDepth = 0;
for (int v = 0; v < robotImage.rows; v++)
{
for (int u = 0; u < robotImage.cols; u++)
{
// Create a ray through the pixel
int pixelIdx = u + (v * robotImage.cols);
//std::cerr << "Pixel (" << u << "," << v << ")" << std::endl;
cv::Point2d pixel = cv::Point2d(u, v);
cv::Point3d cvRay = mCameraModel.projectPixelTo3dRay(pixel);
// Convert cvRay to ap::Ray
ap::Ray ray;
ray.point = Eigen::Vector3::Zero();
ray.vector.x() = cvRay.x; ray.vector.y() = cvRay.y; ray.vector.z() = cvRay.z;
ray.vector.normalize();
//std::cerr << ray.vector.transpose() << std::endl;
// For each frame in vector
for (int frame = 0; frame < mMeshFrameIDs.size(); frame++)
{
MeshMap::iterator scene_i = transformedScenes.find(mMeshFrameIDs[frame]);
if (transformedScenes.end() == scene_i)
{
continue;
}
ap::Mesh* mesh = scene_i->second;
// For each triangle in mesh
for (int i = 0; i < mesh->faces.size(); i++)
{
// Check for intersection. If finite, set distance
ap::Triangle triangle(mesh->vertices[mesh->faces[i].vertices[0]],
mesh->vertices[mesh->faces[i].vertices[1]],
mesh->vertices[mesh->faces[i].vertices[2]]);
Eigen::Vector3 intersection = ap::intersectRayTriangle(ray, triangle);
if (std::isfinite(intersection.x()))
{
float d = intersection.norm();
float val = pixelPtr[pixelIdx];
if (val == 0 || val > d)
{
pixelPtr[pixelIdx] = d;
}
if (d > maxDepth)
{
maxDepth = d;
}
}
}
}
}
}
// Return the matrix
if (maxDepth == 0) { maxDepth = 1;}
return robotImage/maxDepth;
}
inline void
filter_depth_projection( const image_geometry::PinholeCameraModel &camera_model,
const pcl::PointCloud<PointT> &in,
pcl::PointCloud<PointT> &out,
int rows,
int cols,
int k_neighbors = 2,
float threshold = 0.3)
{
std::vector<std::vector<bool> > hit( cols, std::vector<bool>(rows));
std::vector<int> points2d_indices;
pcl::PointCloud<pcl::PointXY> points2d;
pcl::PointCloud<PointT> z_filtred;
#ifdef DEBUG
std::cout << "in points: "<< in.size() << " width: " << cols << " height: " << rows << "\n";
#endif
project2d::Points2d<PointT> point_map;
point_map.init(camera_model, in, rows, cols);
point_map.get_points(z_filtred, 25);
// Project points into image space
for(unsigned int i=0; i < z_filtred.size(); ++i){
const PointT* pt = &z_filtred.points.at(i);
//if( pt->z > 1)
{ // min distance from camera 1m
cv::Point2i point_image = camera_model.project3dToPixel(cv::Point3d(pt->x, pt->y, pt->z));
if( between<int>(0, point_image.x, cols )
&& between<int>( 0, point_image.y, rows )
)
{
// Point allready at this position?
if(!hit[point_image.x][point_image.y]){
hit[point_image.x][point_image.y] = true;
pcl::PointXY p_image;
p_image.x = point_image.x;
p_image.y = point_image.y;
points2d.push_back(p_image);
points2d_indices.push_back(i);
}
else{
#ifdef DEBUG
std::cout << "[" << point_image.x << "][" << point_image.y << "] already inserted " << pt << "\n";
#endif
}
}
}
}
#ifdef DEBUG
std::cout << "Z_filtred: " << z_filtred.size() << " projected 2d points: "<< points2d.size() << " indices: " << points2d_indices.size() << "\n";
#endif
pcl::search::KdTree<pcl::PointXY> tree_n;
tree_n.setInputCloud(points2d.makeShared());
tree_n.setEpsilon(0.5);
for(unsigned int i=0; i < points2d.size(); ++i){
std::vector<int> k_indices;
std::vector<float> square_distance;
//tree_n.nearestKSearch(points2d.at(i), k_neighbors, k_indices, square_distance);
tree_n.radiusSearch(points2d.at(i), k_neighbors, k_indices, square_distance);
look_up_indices(points2d_indices, k_indices);
float distance_value;
if(is_edge_threshold(z_filtred, points2d_indices.at(i), k_indices, square_distance, distance_value, threshold)){
out.push_back(z_filtred.points.at(points2d_indices.at(i)));
out.at(out.size()-1).intensity = sqrt(distance_value);
}
}
#ifdef DEBUG
std::cout << "out 2d points: "<< out.size() << "\n";
#endif
}
void depthCallback(const sensor_msgs::ImageConstPtr& original_image, const sensor_msgs::CameraInfoConstPtr& info){
if(need_for_wall==2){
need_for_wall = 0;
cv_bridge::CvImagePtr cv_ptr;
try
{
cv_ptr = cv_bridge::toCvCopy(original_image, enc::TYPE_16UC1);
}
catch (cv_bridge::Exception& e)
{
ROS_ERROR("tutorialROSOpenCV::main.cpp::cv_bridge exception: %s", e.what());
return;
}
cam_model.fromCameraInfo(info);
Mat depth_image = cv_ptr->image;
float x = 0;
float y = 360;
float wall_height = 0;
geometry_msgs::PointStamped xy_point_stamped, pipe_point_stamped;
walls_detection::Walls walls_all_message;
for(int i = 100; i<600; i+=110){
wall_height = 0;
y = 360;
x = i;
unsigned short wall_depth;
while(wall_height < 0.05 && y > 0){
cv::Point2d uv_point(x,y);
unsigned short wall_depth;
wall_depth = depth_image.at<unsigned short>(y, x);
cv::Point3d xy_point;
xy_point = cam_model.projectPixelTo3dRay(uv_point);
xy_point = xy_point * wall_depth;
xy_point_stamped.header.frame_id = "/camera_rgb_optical_frame";
xy_point_stamped.header.stamp = ros::Time::now();
xy_point_stamped.point.x = 0.001*xy_point.x;
xy_point_stamped.point.y = 0.001*xy_point.y;
xy_point_stamped.point.z = 0.001*xy_point.z;
try {
tf_listener->waitForTransform("/pipe_link", "/camera_rgb_optical_frame", ros::Time::now(), ros::Duration(10.0) );
tf_listener->transformPoint("/pipe_link", xy_point_stamped, pipe_point_stamped);
}
catch (tf::TransformException ex) {
ROS_ERROR("%s",ex.what());
}
wall_height = pipe_point_stamped.point.z;
y = y - 120;
}
std::cout<<"Sciana nr "<< i <<" - x: "<< pipe_point_stamped.point.x <<", y: "<< pipe_point_stamped.point.y <<", z: "<< pipe_point_stamped.point.z <<"\n";
if(wall_height < 0.05){
std::cout << "Nie ma sciany\n";
pipe_point_stamped.point.x = 0;
pipe_point_stamped.point.y = 0;
pipe_point_stamped.point.z = 0;
}
switch(i){
case 100:
walls_all_message.wall1 = pipe_point_stamped;
break;
case 210:
walls_all_message.wall2 = pipe_point_stamped;
break;
case 320:
walls_all_message.wall3 = pipe_point_stamped;
break;
case 430:
walls_all_message.wall4 = pipe_point_stamped;
break;
case 540:
walls_all_message.wall5 = pipe_point_stamped;
break;
}
}
walls_all.publish(walls_all_message);
}
}
inline void
remove_cluster_2d( const image_geometry::PinholeCameraModel &camera_model,
const pcl::PointCloud<PointT> &in,
pcl::PointCloud<PointT> &out,
int rows,
int cols,
int k_neighbors = 4,
int border = 25)
{
std::vector<int> points2d_indices;
pcl::PointCloud<pcl::PointXY> points2d;
#ifdef DEBUG
std::cout << "in points: "<< in.size() << "\n";
#endif
// Project points into image space
for(unsigned int i=0; i < in.points.size(); ++i){
const PointT* pt = &in.points.at(i);
if( pt->z > 1) { // min distance from camera 1m
cv::Point2i point_image = camera_model.project3dToPixel(cv::Point3d(pt->x, pt->y, pt->z));
if( between<int>(0+border, point_image.x, cols-border )
&& between<int>( 0+border, point_image.y, rows-border )
)
{
pcl::PointXY p_image;
p_image.x = point_image.x;
p_image.y = point_image.y;
points2d.push_back(p_image);
points2d_indices.push_back(i);
}
}
}
#ifdef DEBUG
std::cout << "projected 2d points: "<< points2d.size() << " indices: " << points2d_indices.size() << "\n";
#endif
pcl::search::KdTree<pcl::PointXY> tree_n;
tree_n.setInputCloud(points2d.makeShared());
tree_n.setEpsilon(0.1);
for(unsigned int i=0; i < points2d.size(); ++i){
std::vector<int> k_indices;
std::vector<float> square_distance;
//tree_n.nearestKSearch(points2d.at(i), k_neighbors, k_indices, square_distance);
tree_n.radiusSearch(points2d.at(i), k_neighbors, k_indices, square_distance);
if(k_indices.empty()) continue; // Dont add points without neighbors
look_up_indices(points2d_indices, k_indices);
float edginess = 0;
if(is_edge_z(in, points2d_indices.at(i), k_indices, square_distance, edginess, 0.1)){
out.push_back(in.points.at(points2d_indices.at(i)));
out.at(out.size()-1).intensity = edginess;
}
}
#ifdef DEBUG
std::cout << "out 2d points: "<< out.size() << "\n";
#endif
}
