Installation

Set up a virtual environment

We use Anaconda] to manage and isolate dependencies. The provided environment setup script also installs Mamba, which gets on top of conda for faster environment installs.

# clone project
git clone https://github.com/IGNF/lidar-prod-quality-control
cd lidar-prod-quality-control

# install conda
# see https://www.anaconda.com/products/individual

# you need to install postgis to request a public database
sudo apt-get install postgis

# create conda environment
source setup_env/setup_env.sh

# activate the virtual env
conda activate lidar_prod

Install the app as a python module

To run the application from anywhere, you can install as a module in a your virtual environment.

# activate your env
conda activate lidar_prod

# install the package from github directly, using production branch
pip install --upgrade https://github.com/IGNF/lidar-prod-quality-control/tarball/prod

During development, install in editable mode directly from source with

pip install --editable .

Then, refert to the usage page.

Provide credentials

To help identify buildings, the BD_UNI database is used. To provide credentials, copy bd_uni_connection_params/credentials_template.yaml to bd_uni_connection_params/credentials.yaml cp bd_uni_connection_params/credentials_template.yaml bd_uni_connection_params/credentials.yaml Then fill the blanks in the file, specifically “user” and “pwd”.