The metaroom_xml_parser package is used to parse previously saved room observations. The data will be read into an appropriate data structure containing: merged point cloud, individual point clouds, individual RGB and depth images and corresponding camera parameters.
- Parsing one file
The load_single_file application reads in one room observation.
rosrun metaroom_xml_parser load_single_file /path/to/xml
- Parsing multiple observations
The 'load_multiple_files' application reads in multiple room observations and returns a vector. It takes as input the root folder where the observations are stored.
rosrun metaroom_xml_parser load_multiple_files /path/to/folder
- Parsing labelled data
The load_labelled_data application reads labelled data for observations taken at a particular waypoint. The waypoint id and the folder where the observations are stored are taken in as parameters.
rosrun metaroom_xml_parser load_labelled_data` /path/to/sweeps WayPointXYZ
A number of utilities are provided by this package, for easy data manipulation. The definitions can be seen in the file load_utilities.h
The complete cloud datatype is:
template <class PointType> boost::shared_ptr<pcl::PointCloud<PointType>>
The utilities for loading only the merged cloud are:
loadMergedCloudFromSingleSweep# returns one cloudloadMergedCloudFromMultipleSweeps# returns a vector of merged clouds, one for each sweeploadMergedCloudForTopologicalWaypoint# same as above
The intermediate cloud datatype is:
template <class PointType>
struct IntermediateCloudCompleteData
{
std::vector<boost::shared_ptr<pcl::PointCloud<PointType>>> vIntermediateRoomClouds;
std::vector<tf::StampedTransform> vIntermediateRoomCloudTransforms;
std::vector<image_geometry::PinholeCameraModel> vIntermediateRoomCloudCamParams;
std::vector<tf::StampedTransform> vIntermediateRoomCloudTransformsRegistered;
std::vector<image_geometry::PinholeCameraModel> vIntermediateRoomCloudCamParamsCorrected;
std::vector<cv::Mat> vIntermediateRGBImages; // type CV_8UC3
std::vector<cv::Mat> vIntermediateDepthImages; // type CV_16UC1
};
The utilities for loading the intermediate clouds are:
loadIntermediateCloudsFromSingleSweep# just the point cloudsloadIntermediateCloudsCompleteDataFromSingleSweep# complete data, with transforms and imagesloadIntermediateCloudsFromMultipleSweepsloadIntermediateCloudsCompleteDataFromMultipleSweepsloadIntermediateCloudsForTopologicalWaypointloadIntermediateCloudsCompleteDataForTopologicalWaypoint
The sweep XML is an std::string
The utilities for finding sweep XMLS are:
getSweepXmls# takes a folder where to search as argument. Returns avector<string>getSweepXmlsForTopologicalWaypoint
The dynamic clusters type is:
template <class PointType> std::vector<boost::shared_ptr<pcl::PointCloud<PointType>>>
The dynamic cluster utilities are:
loadDynamicClustersFromSingleSweeploadDynamicClustersFromMultipleSweepsloadDynamicClustersForTopologicalWaypoint
The labelled data type is:
template <class PointType>
struct LabelledData
{
boost::shared_ptr<pcl::PointCloud<PointType>> completeCloud;
tf::StampedTransform transformToGlobal;
tf::Vector3 sweepCenter;
std::vector<boost::shared_ptr<pcl::PointCloud<PointType>>> objectClouds;
std::vector<std::string> objectLabels;
boost::posix_time::ptime sweepTime;
std::string waypoint;
};
The labelled data utilities are:
loadLabelledDataFromSingleSweep