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Pytree

A containerized Flask application serving potree to extract height profile from LiDAR data.

Requirements

  1. You will need docker and docker-compose to run the application.

Installation

First, clone this repository on your machine.

git clone [email protected]:yverdon/pytree.git && cd pytree

If you need another version of CPotree, extract its release files (namely extract_profile and liblaszip.so) into ./bin and make the file extract_profile actually executable:

chmod +x extract_profile

Otherwise, you can simply directly use the bin/ folder provided in this repos. Credit goes to M. Schuetz.

Then, create your .env file with a DEPLOY_ENV variable set to either DEV or PROD, a PORT variable specify which port of your host machine you want to use, and a DATA_DIR variable containing the absolute path to the directory containing your metadata.json file for your Potree LiDAR tiles (generated using PotreeConvert v2.x.x).
Check .env.sample for inspiration.

Thirdly, copy example_config.yml to pytree.yml and make sure to adapt the variable to your environment. Especially adapt the following four variables:

  • log_folder
  • cpotree_executable
  • pointclouds
  • default_point_cloud

Finally run the 2 following commands:

docker-compose down --remove-orphans -v
docker-compose up --build

Usage

The application runs at http://localhost:6001/pytree

Please chek https://github.com/potree/CPotree/blob/master/README.md for a comprehensive list of valid URL parameters to get a LiDAR profile.

You can also start a shell to further explore inside the running container and play around with the executable:

docker exec -it pytree_api_1 bash

Then execute extract_profile:

extract_profile data/processed/metadata.json -o "stdout" --coordinates "{2525528.12,1185781.87},{2525989.37,1185541.87}" --width 10 --min-level 0 --max-level 5 > data/output/test.las