client_train_neg.cpp

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 #include "peddetect.h"

class ImageConverter
{
  ros::NodeHandle nh_;
  image_transport::ImageTransport it_;
  image_transport::Subscriber image_sub_;
  image_transport::Publisher image_pub_;
  int ImgCount;
  cv_bridge::CvImagePtr cv_ptr;
  DVector features;
  CvRect region; 
  Size minSize;
  FtrVecParams2 randparams;
  vector<DVector> WindowFtrs;
  RNG rng;
  
public:

ImageConverter ():
  it_ (nh_)
  {
  
    ImgCount = 1;
    image_pub_ = it_.advertise ("Image_Out", 1);
    image_sub_ =
    it_.subscribe ("Image_In", 1, &ImageConverter::imageCb, this);
    
    region.x = 0; region.y = 0; region.width = 64; region.height = 128;
    minSize.width=region.width; minSize.height=region.height;
    
    GetRandParams(SEED,NRFEATURE2, randparams, region);
    rng(123);

  }

  ~ImageConverter ()
  {

  }

  void imageCb (const sensor_msgs::ImageConstPtr & msg)
  {
    
    try
    {

      cv_ptr = cv_bridge::toCvCopy (msg, "rgb8");

      cv_ptr->image.convertTo (cv_ptr->image, CV_8UC1);

    }
    catch (cv_bridge::Exception & e)
    {
      ROS_ERROR ("cv_bridge exception: %s", e.what ());
      return;
    }
    Mat Img = cv_ptr->image;

    if (Img.rows == 0)
      return;
    
        Size win; win.width=640; win.height=480;
        resize(Img, Img, win , 0, 0, INTER_LINEAR);

    region.x = 0; region.y = 0; region.width = DWWIDTH; region.height = DWHEIGHT;  
    

    cvtColor (Img, Img, CV_BGR2RGB, 0);

    features.clear ();
    WindowFtrs.clear();

    GetChnFtrsOverImagePyramid(Img , region , features, WindowFtrs ,0, minSize, 8 , randparams);
    
    fstream outfile;
    outfile.open ("/home/pedrobatista/workingcopy/lar3/perception/pedestrians/PedestrianDetect/train_10000.csv", fstream::in | fstream::out | fstream::app);
    
    int a=rng.uniform(0,WindowFtrs.size());
    int b=rng.uniform(0,WindowFtrs.size());
    int c=rng.uniform(0,WindowFtrs.size());
    int d=rng.uniform(0,WindowFtrs.size());
    
    outfile<<"2,";
    
    for (int i=0;i<NRFEATURE;i++)
    {
      if (i != NRFEATURE-1)
      outfile<<WindowFtrs[a][i]<<",";
      else
        outfile<<WindowFtrs[a][i];
    }
    
    outfile<<endl;
    outfile<<"2,";
    for (int i=0;i<NRFEATURE;i++)
    {
      if (i != NRFEATURE-1)
      outfile<<WindowFtrs[b][i]<<",";
      else
        outfile<<WindowFtrs[b][i];
    }
    
    
    outfile<<endl;
    outfile<<"2,";
        for (int i=0;i<NRFEATURE;i++)
    {
      if (i != NRFEATURE-1)
      outfile<<WindowFtrs[c][i]<<",";
      else
        outfile<<WindowFtrs[c][i];
    }
    
    outfile<<endl;
    outfile<<"2,";
    
    for (int i=0;i<NRFEATURE;i++)
    {
      if (i != NRFEATURE-1)
      outfile<<WindowFtrs[d][i]<<",";
      else
        outfile<<WindowFtrs[d][i];
    }
    
    outfile<<endl;
//     cout<<WindowFtrs.size()<<"   "<<features.size()<<endl;
    
    outfile.close();
    ROS_INFO ("Image nr %d\n", ImgCount++);
    


    
    


    cv_ptr->image = Img;



    sensor_msgs::ImagePtr msg_out = cv_ptr->toImageMsg ();
    msg_out->encoding = "rgb8";
    msg_out->header.frame_id = "Image_Out";
    msg_out->header.stamp = ros::Time::now ();


    image_pub_.publish (msg_out);



  }

};

int main (int argc, char **argv)
{
  fstream outfile("/home/pedrobatista/workingcopy/lar3/perception/pedestrians/PedestrianDetect/train_10000.csv");
  ros::init (argc, argv, "image_converter");
  ImageConverter ic;
  ros::spin ();
  return 0;
}