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Toolkit to Explore 3D data for 3D object detection, point cloud visualization, bev map gen etc. Using KITTI as dummy data

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lucasjinreal/3d_detection_kit

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3D Detection Kit

This repo contains several useful scripts which using for 3D detection algorithm development. Including:

  • Loading and visualization on lidar point cloud;

  • Generate bev map(bird view map);

  • Showing 3D Bounding box on point cloud;

  • Project 3D Bounding Box on image with calib params;

  • Showing bbox on bev image angle;

Updates

  • 2020-: to be continue.
  • 2019-02-27: Update vis_3d, it can using mayavi visualization point cloud with 3D bounding box now.

Usage

directly using:

python3 show_pc.py

and you can see point cloud. you should also install open3d first, using:

sudo pip3 install open3d-python

Tutorials

to get more information, you can visit our community forum to talk: http://talk.strangeai.pro

convert point cloud to bev map

To get an bev map for point cloud. it should construct a image with certain width and height, then every pixel value should be the z, if there is no point from top view, then z should be 0, so that bev image would be black. So to construct a bev map, should crop the point cloud first, then make x,y coordinates min to be 0, which is mapping x, y to image coordinates. After that, mapping z values to 0~255 which will be using for pixel values. There mainly 3 things to make it done:

  • Crop the point cloud to certain range, like left-right range, back-forward range;
  • Shifting x, y values to min be 0;
  • Mapping z to image pixel values.

Copyright

The codes opensource under MIT license. All right belongs to Jin Fagang

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Toolkit to Explore 3D data for 3D object detection, point cloud visualization, bev map gen etc. Using KITTI as dummy data

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