Getting Started

Prerequisites

Necessary Software to install on your machine:

• Python version 3.9 or higher.

We recommend using a virtual environment to avoid potential package conflicts. Below are instructions for setting up with virtualenv or conda.

Installing

virtualenvconda

If you don't have virtualenv installed:

pip install virtualenv

To create and activate a new virtual environment named syclops:

WindowsLinux

virtualenv syclops_venv
.\syclops_venv\Scripts\activate

virtualenv syclops_venv
source syclops_venv/bin/activate

If you use Anaconda or Miniconda, you can create a new environment:

conda create --name syclops_venv python=3.9
conda activate syclops_venv

Installing Syclops

Once you have your environment set up and activated:

From PyPIFrom Source

pip install syclops

To install Syclops directly from the source code:

git clone https://github.com/DFKI-NI/syclops.git
cd syclops
pip install .

Warning

pip install . -e does not work with the current setup.

Run a job

Next, the assets need to be crawled by the pipeline. This only needs to be done once, or if new assets are added.

syclops -c

To run a job, a job file is needed. You can find an example in the syclops/__example_assets__ folder.

To test the installation with the example job file run:

syclops --example-job

To run a specific job, simply pass the path to the job file to the syclops command:

syclops -j path/to/job.syclops.yaml

That's all you need to know to render images! 🎉

The rendered data will be in output/<timestamp> inside of your specified syclops directory. To quickly visuzalize the data, you can use the dataset viewer tool.

Adjust the output path accordingly.

syclops -da output/2022-09-01_12-00-00