A framework to construct a transformation pipeline based on some specification from users.
Spatial Transformations (from GDAL): cropping, regirdding, resampling, etc. Model-specific Transformations: Topoflow, PIHM, Cycles, Econ, etc.
A list of available transformations can be found in the wiki
The easiest way to install and use the software is using docker:
- Clone the repository
git clone https://github.com/mintproject/MINT-Transformation.git
cd MINT-Transformation
- Build docker image
docker build -t mint_dt .
However, you can directly install the software without docker by replacing the second step with:
conda env create -f environment.yml
Post installation steps: (will be removed in the future)
mkdir /tmp
chmod 1777 /tmp
You can use the software through the command line application or through the web application.
With conda environment
- Activate the environment first
conda activate mintdt
- Run the pipeline:
dotenv -f [env_path] run python -m dtran.main exec_pipeline --config [config_path]
Arguments:
env_path: Path of .env file (sample).config_path: Path to the transformation pipeline configuration file (Topoflow config/Sample input).
With docker
docker run --rm -v $(pwd):/ws -v /tmp:/tmp mintproject/mint_dt [config_path]
With conda environment
- Start the server by running the following command from the root folder:
PYTHONPATH=$(pwd)/webapp:$(pwd) dotenv run python webapp/api/app.py
Open URL http://0.0.0.0:10010 on your browser
With docker
Run image with local mount and port 5000 exposed
docker run --rm -p 5000:5000 -v $(pwd):/ws -it --entrypoint=/bin/bash mint_dt
Public server
We have a deployed transformation service running here. Demo video on how to use the service can be found here