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
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.
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.
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.
- 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
- 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
- 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 thebackend
parameter value is set totensorflow
. If it istheano
- simply remove that file, and on next execution Keras will find your Tensorflow install and create the correct configuration file.