Point Cloud Tree Detection Example

This code was adapted from work by Neal Swayze and Wade Tinkham (2022) to ingest raw point cloud data for processing and analysis of forest structure metrics.

Project site

Point Cloud Tree Detection Python Interface

This R-Python interface allows program to run under CLI, and convert R code to Python environment for further ML development. The environment was packed into a container by apptainer

Use the container image (recommend)

#install Apptainer (for ubuntu)
sudo add-apt-repository -y ppa:apptainer/ppa
sudo apt update
sudo apt install -y apptainer

#Download container image
apptainer remote add --no-login SylabsCloud cloud.sycloud.io
apptainer remote use SylabsCloud
apptainer pull lastree.sif library://jldz9/lastree/image:1.0

#Execute the lastree
apptainer exec lastree.tif lastree -h

Install use pip

In this method, no R environment was installed, you will need to config R environment by yourself (Which is painful, trust me)

#install lastree
pip install lastree

#run lastree
lastree -h

Using the source code

#clone this repository 
git clone https:/jldz9/point_cloud_tree_detection_ex.git

lastree usage

#Get example data
apptainer exec lastree.sif las_tree --example_data

#Generate CONFIG file
apptainer exec las_tree_container.sif las_tree.py --generate_config

#Run the point cloud tree detection
apptainer exec las_tree_container.sif las_tree.py -p ./CONFIG