class mola::KittiOdometryDataset

Overview

RawDataSource from Kitti odometry/SLAM datasets. Each “sequence” directory contains these sensor streams:

image_0 & image_1 : A grayscale stereo camera pair
image_2 & image_3 : An RGB stereo camera pair
lidar : Velodyne 3D LIDAR
Ground truth poses

If the option clouds_as_organized_points is true, point cloud are published as mrpt::obs::CObservationRotatingScan. Otherwise (default), they are published as mrpt::obs::CObservationPointCloud with X,Y,Z,I channels.

The sequence to load is determined by the sequence parameter (e.g. via config yaml file), from these possible values:

sequence: 00|01|02|...|20|21

Expected contents under base_dir directory:

KITTI/
├── poses        # ground truth poses
│  ├── 00.txt
│  ├── 01.txt
│   ...
│  ├── 09.txt
│  └── 10.txt
│
├── sequences
│   ├ 00
│   │ ├── calib.txt
│   │ ├── times.txt
│   │ ├── image_0
│   │ |   ├── 000000.png
│   │ |   ├── 000001.png
│   │ |   ...
│   │ ├── image_1
│   │ |   ├── 000000.png
│   │ |   ├── 000001.png
│   │ |   ...
│   │ └── velodyne
│   │     ├── 000000.bin
│   │     ├── 000001.bin
... ...    ...
│   ├ 01
│   │ ├── calib.txt
... ...    ...

Example base_dir : /mnt/storage/KITTI/ (normally read from environment variable KITTI_BASE_DIR in mola-cli launch files).

#include <KittiOdometryDataset.h>

class KittiOdometryDataset:
    public mola::RawDataSourceBase,
    public mola::OfflineDatasetSource,
    public mola::Dataset_UI
{
public:
    // fields

    double VERTICAL_ANGLE_OFFSET = mrpt::DEG2RAD(0.205);

    // methods

    virtual void spinOnce();
    virtual bool hasGroundTruthTrajectory() const;
    virtual trajectory_t getGroundTruthTrajectory() const;
    std::shared_ptr<mrpt::obs::CObservation> getPointCloud(timestep_t step) const;

    std::shared_ptr<mrpt::obs::CObservationImage> getImage(
        const unsigned int cam_idx,
        timestep_t step
        ) const;

    virtual size_t datasetSize() const;
    virtual mrpt::obs::CSensoryFrame::Ptr datasetGetObservations(size_t timestep) const;
    virtual size_t datasetUI_size() const;
    virtual size_t datasetUI_lastQueriedTimestep() const;
    virtual double datasetUI_playback_speed() const;
    virtual void datasetUI_playback_speed(double speed);
    virtual bool datasetUI_paused() const;
    virtual void datasetUI_paused(bool paused);
    virtual void datasetUI_teleport(size_t timestep);
};

Inherited Members

public:
    // structs

    struct SensorViewerImpl;

    // methods

    virtual void initialize(const Yaml& cfg) = 0;
    virtual size_t datasetSize() const = 0;
    virtual mrpt::obs::CSensoryFrame::Ptr datasetGetObservations(size_t timestep) const = 0;
    virtual bool hasGroundTruthTrajectory() const;
    virtual trajectory_t getGroundTruthTrajectory() const;
    virtual size_t datasetUI_size() const = 0;
    virtual size_t datasetUI_lastQueriedTimestep() const = 0;
    virtual double datasetUI_playback_speed() const = 0;
    virtual void datasetUI_playback_speed(double speed) = 0;
    virtual bool datasetUI_paused() const = 0;
    virtual void datasetUI_paused(bool paused) = 0;
    virtual void datasetUI_teleport(size_t timestep) = 0;

Fields

double VERTICAL_ANGLE_OFFSET = mrpt::DEG2RAD(0.205)

See: “IMLS-SLAM: scan-to-model matching based on 3D data”, JE Deschaud, 2018.

Methods

virtual void spinOnce()

Runs any required action on a timely manner

virtual bool hasGroundTruthTrajectory() const

Returns true if a groundtruth is available for the vehicle trajectory.