This is an useful toolbox for the developers who need to process the point cloud collected by various types of sensors like LiDAR.

Dependencies

• python
• numpy
• open3d
• opencv

pip install open3d
pip install numpy
pip install opencv-contrib-python

Usage

python tutorial.py

tutorial.py contains several functions, you can comment/uncomment different functions to run the corresponding demos. Here are the functions:

• vis_sequential_object() will read the configs and visualize the point cloud with OBB(Oriented Bounding Boxes) in a blocking manner (the non-blocking program is still under developing)

  • N: Next Frame
  • B: Previous Frame

• vis_sequential_sem_inst_motion() will read the configs and visualize the point cloud with Semantic/Instance/Motion labels in a non-blocking manner

  • N: Next Frame
  • B: Previous Frame
  • S: Semantic Mode
  • I: Instance Mode
  • M: Motion Mode

• test_visualizer() contains various kinds of visualizations, you can dive into it.

• test_dataloader_visualizer() contains dataloader that can load point cloud from .bin or .pcd

• test_kitti_mapper() reads the poses.txt, calib.txt,*.bin,*.label and build a dense map

• test_bev() convert the point cloud to BEV(Bird's Eye View) image

Developing

The functions of this toolbox include:

• dataloader
  • load xyz from *.bin
  • load xyzi from *.bin
  • load xyzi and crop to certain ROI from *.bin
  • load semantic/instance label from *.label
  • load xyz from *.pcd
  • load xyz and downsize from *.pcd
  • load xyzi from *.pcd
  • load xyzi and downsize from *.pcd
• visualize single frame data
  • visualize point cloud $[n,3]$
  • visualize point cloud with label $[n,3]$ + $[n,1]$
  • ……
• visualize sequential data
  • semantic segmentation
  • instance segmentation
  • moving object segmentation
  • object detection blocking
  • object detection non-blocking
• mapping with sequential data and poses
  • mapping with kitti-like data
• visualize kitti point cloud map
• lidar-bev transform

Contribute

https://github.com/chaomath/open3d-kitti-visualization https://github.com/PRBonn/semantic-kitti-api https://github.com/yknapp/lidar2bev