Anomaly Detection for 3D-Printer Showcase

Usage

Examples for deployment in Docker or Kubernetes can be found in the examples directory:

• Docker Compose
• Kubernetes

Contributing

The source code of Anomaly Detection for 3D-Printer Showcase can be found on Github: https://github.com/innovation-hub-bergisches-rheinland/showcase-3d-printer-anomaly-detection/

We'd love to have you contribute! Please refer to our contribution guidelines for details.

License

Apache 2.0 License

Local Development

Install pyenv with the pyenv installer, configure your shell (log out and log back in for changes to take effect):

# Install pyenv
curl https://pyenv.run | bash
# Configure shell
echo 'export PYENV_ROOT="$HOME/.pyenv"' >> ~/.profile
echo 'export PATH="$PYENV_ROOT/bin:$PATH"' >> ~/.profile
echo 'eval "$(pyenv init --path)"' >> ~/.profile
echo 'eval "$(pyenv init -)"' >> ~/.bashrc
echo 'eval "$(pyenv virtualenv-init -)"' >> ~/.bashrc

Install and activate Python version specified in .python-version with pyenv:

# Install and activate Python version
pyenv install
# Check Python version
pyenv version

Install Poetry:

curl -sSL \
    https://raw.githubusercontent.com/python-poetry/poetry/master/install-poetry.py |
    python

Create project environment, install dependencies and activate the environment in your shell:

# Configure Poetry to create environments in project directories (OPTIONAL)
poetry config virtualenvs.in-project true
# Create project environment
poetry env use $(which python)
# Install dependencies
poetry install
# Activate project environment
poetry shell

You can build a Docker image locally with:

./build.sh