Automated sparse control network generation to support photogrammetric control of planetary image data.
- Documentation: https://usgs-astrogeology.github.io/autocnet/
We suggest using Anaconda Python to install Autocnet within a virtual environment. These steps will walk you through the process.
#. [Download](https://www.continuum.io/downloads) and install the Python 3.x Miniconda installer. Respond Yes
when [![FOSSA Status](https://app.fossa.io/api/projects/git%2Bgithub.com%2Fjlaura%2Fautocnet.svg?type=shield)](https://app.fossa.io/projects/git%2Bgithub.com%2Fjlaura%2Fautocnet?ref=badge_shield)
prompted to add conda to your BASH profile.
(Optional) We like to sequester applications in their own environments to avoid any dependency conflicts. To do this:
conda create -n <your_environment_name> python=3 && source activate <your_environment_name>
Note, that you might want to specify either
python=3.5
orpython=3.6
, depending on your requirements. Both are currently supported by autocnet.- Make the newly created environment the active one:
conda activate <your_environment_name>
(orsource activate
on an older conda system)
- Bring up a command line and add three channels to your conda environment-specific config file:
conda config --env --add channels conda-forge
conda config --env --add channels menpo
conda config --env --add channels usgs-astrogeology
- Finally, install autocnet:
conda install autocnet
## License [![FOSSA Status](https://app.fossa.io/api/projects/git%2Bgithub.com%2Fjlaura%2Fautocnet.svg?type=large)](https://app.fossa.io/projects/git%2Bgithub.com%2Fjlaura%2Fautocnet?ref=badge_large)