LIDARtoolkit

**Currently in development

A python toolkit published on pypi for simplifying LIDAR point cloud processing and rapid prototyping.

Requirements

• Python 3.5+
• Numpy

Install

$ pip3 install LiDARtoolkit
or
$ python3 -m pip install LiDARtoolkit

Note: This toolkit is not compatible for python versions below 3.5

Tools

removeGround(pointcloud, bin_size = 0.0625, error_limit = 0.2)

Returns: Pointcloud without ground

This function removes the ground points in the point cloud data by binning the points in the x-y plane and removing the lowermost points. Resolution and quality of output can be changed by changing the bin_size parameter. error_limit defines the margin to which the points will be removed from the bottom.

separateObjects(pointcloud, min_samples = 15, eps = 0.8, dim = 2)

Returns: Object array, Color array

This function separates the objects in the point cloud by performing density based clustering on the points either in 3 dimensions or in the x-y plane as specified by the dim parameter (3 for 3d and 2 for 2d). min_samples define minimum number of points to be called as a cluster while eps defines the maximum distance between these points. The color array is used just for plotting the points with different colors.

rotateBy(point, theta)

Returns: Transformed point

This function returns the point rotated by angle theta in the x-y plane by just multipying by the rotation matrix.

def findBox(object)

Returns: Array of eight points of bounding box, angle of the bounding box in x-y plane

This function returns the minimum bounding box of the object point cloud by rotating the object and finding the rectangle of minimum area that bounds it.

PyPi

https://pypi.org/project/LiDARtoolkit/