A containerized Flask application serving potree to extract height profile from LiDAR data.
- You will need docker and docker-compose to run the application.
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
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