Pictor is a 'pictures interactions predictor': Given an input dataset, with about 50 different data from ~350000 pictures from social networks, pictor tries to predict the interactions over any other picture, with that same info.

A requirements.txt file is included. This file contains the python pip dependencies. In order to execute the script, you need to have installed virtualenv.

Then create a new virtualenv by executing:

$ virtualenv some_new_venv

Activate the virtualenv just created:

$ source some_new_venv/bin/activate

Clone this project into this virtualenv, and install requirements by executing:

$ pip install -r requirements.txt

This will install the following dependencies inside locally to the virtualenv:

• scikit-learn
• NumPy
• SciPy
• matplotlib

In order to execute pictor, just call this module as argument of the python interpreter:

$ python pictor.py <args>

Were args must be:

• --csv="": Specify the input csv file. If it is not specified, then is assumed that the file is named 'consolidated_features.csv' and is located in the same path.
• --feat="": Specify the input file with features to discard. The file should be a plain text file with one feature name by file. Lines beginning with '#' are discarded. The file used with this project is 'features_to_discard.txt' and is located inside data folder.

For example:

$ python pictor.py --csv="../consolidated_features.csv" --feat="../data/features_to_discard.txt"

[machine-learning] ml, [sklearn] sk, [python] py, [prediction] pr, [pictures] pi, [interactions] in