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AutoCNet

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Documentation Status

'Stories in Ready'

Automated sparse control network generation to support photogrammetric control of planetary image data.

Installation Instructions

We suggest using Anaconda Python to install Autocnet within a virtual environment. These steps will walk you through the process.

  1. [Download](https://www.continuum.io/downloads) and install the Python 3.x Miniconda installer. Respond Yes when prompted to add conda to your BASH profile.

  2. (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 or python=3.6, depending on your requirements. Both are currently supported by autocnet.

  3. Make the newly created environment the active one:

    • conda activate <your_environment_name> (or source activate on an older conda system)
  4. 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
  5. Finally, install autocnet: conda install autocnet

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Automatic control network generation

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  • Jupyter Notebook 78.3%
  • Python 21.7%