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Data Visualization

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Joey Wilson edited this page Feb 8, 2022 · 7 revisions

Processed Scenes

  • ConcatLiDAR.py

    • Given a source directory, loads point clouds and transforms by their pose to world coordinates.
    • Iterates through frames, adding point clouds without removing previous ones.
    • The result is a scene with occlusions and traces, however it can be used to test the point clouds and coordinate transformations.

  • VisualizeScene.py

    • Visualize completed semantic scene in either Cylindrical or Cartesian coordinates.
    • Samples points from each valid cell, and displays a colored point cloud in Open3D.
    • Also loads a bird's eye view image for each frame to verify the scene is correct.

  • VisualizeDBKI.py

    • Similar to VisualizeScene.py, however visualizes semantic mapping data, which includes an extra split.
    • Not directly used for MotionSC.

Raw Data

  • VisualizeLidar.py

    • Visualize raw sensor data before processed into a semantic scene.
    • Transforms all sensors to world coordinates, then displays the union of all semantic point clouds in Open3D.
    • Used to check all sensors.

Predictions

  • plot_voxels.py

    • ROS Node for visualizing all baseline model predictions simultaneously with ground truth bird's eye view image.
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