installation.md

Installation:

1: Setting Up The Virtual Environment

VirtualEnv

To install virtualenv, follow this guide: virtualenv installation guide

Once virtualenv is installed, create a new environment to run pic2vec:

    $ virtualenv pic2vec

Then activate the environment:

    $ source pic2vec/bin/activate

Conda

To install Anaconda, follow this guide: Anaconda installation guide

Once Anaconda is installed, create a new environment to run pic2vec:

    $ conda create --name pic2vec

When Conda asks for confirmation, type 'y' for 'yes'.

To activate the environment on OS X or Linux:

    $ source activate pic2vec

To activate the environment on Windows:

    $ activate pic2vec

Once in a virtual environment, there are several ways to install the pic2vec package.

2: Installing The Pic2Vec Package

Pip Installation

To install pic2vec through pip on OS X or Linux, run this command in your terminal:

    $ pip install pic2vec

To install through pip on Windows, run this command in terminal:

    $ python -m pip install pic2vec

This is the preferred method to install pic2vec, as it will always install the most recent stable release.

If you don't have pip installed, this Python installation guide can guide you through the process.

Installing From setup.py

The sources for pic2vec can be downloaded from the Github repo.

You can either clone the public repository:

    $ git clone git@github.com:datarobot/pic2vec.git

Or download the tarball:

    $ curl  -OL https://github.com/datarobot/pic2vec/tarball/master

Once you have a copy of the source, you can build a binary distribution and install it from inside the directory with:

    $ python setup.py bdist_wheel
    $ cd dist/
    $ pip install pic2vec-{VERSION}-py2.py3-none-any.whl

Check the dist folder to see what you need to fill in for the {VERSION} section.

3: Troubleshooting

1. If you see an error similar to TypeError: find_packages() got an unexpected keyword argument 'include' then you need to upgrade your setuptools.

pip install -U setuptools

2. If you see an error similar to No local packages or working download links found for tensorflow then you need to upgrade your pip.

pip install -U pip

3. If you have problems with tests or strange runtime exceptions, make sure your Keras installation isn't configured for Theano use. Open ~/.keras/keras.json and check that the backend parameter value is set to tensorflow. If it is theano - simply remove that file, and on next execution Keras will find your Tensorflow install and create the correct configuration file.