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indicoio-python

A wrapper for a series of APIs made by indico.

Check out the main site on:

http://indico.io

Check out our documentation on:

http://indicoiopython.s3-website-us-west-2.amazonaws.com/indicoio.html

Our APIs are totally free to use, and ready to be used in your application. No data or training required.

Documentation

Found here

Current APIs

Right now this wrapper supports the following apps:

  • Positive/Negative Sentiment Analysis
  • Political Sentiment Analysis
  • Image Feature Extraction
  • Facial Emotion Recognition
  • Facial Feature Extraction
  • Language Detection
  • Text Topic Tagging

Examples

>>> import numpy as np

>>> from indicoio import political, sentiment, fer, facial_features, language

>>> political("Guns don't kill people. People kill people.")
{u'Libertarian': 0.47740164630834825, u'Green': 0.08454409540443657, u'Liberal': 0.16617097211030055, u'Conservative': 0.2718832861769146}

>>> sentiment('Worst movie ever.')
{u'Sentiment': 0.07062467665597527}

>>> sentiment('Really enjoyed the movie.')
{u'Sentiment': 0.8105182526856075}

>>> tag_dict = text_tags("Facebook blog posts about Android tech make better journalism than most news outlets.")

>>> sorted(tag_dict.keys(), key=lambda x: tag_dict[x], reverse=True)[:5]
[u'investing', u'startups', u'business', u'entrepreneur', u'humor']

>>> tag_dict
{u'fashion': 0.011450126534350728, u'art': 0.00358698972755963, u'energy': 0.005537894035625527, ...}

>>> test_face = np.linspace(0,50,48*48).reshape(48,48).tolist()

>>> fer(test_face)
{u'Angry': 0.08843749137458341, u'Sad': 0.39091163159204684, u'Neutral': 0.1947947999669361, u'Surprise': 0.03443785859010413, u'Fear': 0.17574534848440568, u'Happy': 0.11567286999192382}

>>> facial_features(test_face)
[0.0, -0.02568680526917187, 0.21645604230056517, -0.1519435786033145, -0.5648621854611555, 3.0607368045577226, 0.11434321880792693, -0.02163810928547493, -0.44224330594186484, 0.3024315632285246, -2.6068048934495276, 2.497798330306638, 3.040558335205844, 0.741045340525325, 0.37198135618478817, -0.33132377802172325, -0.9804190889833034, 0.5046575784709395, -0.5609132323152847, 1.679107064439151, 0.6825037853544341, -1.5977176226648016, 1.8959464303080562, -0.7812860715595836, -2.998394007543733, -0.22637273967347724, -0.9642457010679496, 1.4557274834236749, 2.412244419186633, 2.3151771738421965, 0.7881483386786367, 1.6622850935863422, 0.1304768990234367, 1.9344501393866649, 3.1271558035162914, -0.10250886439220543, 1.4921395116492966, 2.761645355670677, 1.6903473594991179, 1.009209807271491, 0.07273926986120445, -1.4941708135718021, -2.082786362439631, 1.0160924044870847, 2.5326580674673895, -0.8328208491083264, 2.0390177029762935, 3.0342637531932777]

>>> language_dict = language('Quis custodiet ipsos custodes')

>>> sorted(language_dict.keys(), key=lambda x: language_dict[x], reverse=True)[:5]
[u'Latin', u'Dutch', u'Greek', u'Portuguese', u'Spanish']

>>> language_dict
{u'Swedish': 0.00033330636691921914, u'Lithuanian': 0.007328693814717631, u'Vietnamese': 0.0002686116137658802, u'Romanian': 8.133913804076592e-06, ...}

If you have a local indico server running, simply import from indicoio.local.

>>> from indicoio.local import political, sentiment, fer, facial_features, language

Installation

pip install indicoio

Announcement: Indico has partnered with Experfy, a data science consulting marketplace based in the Harvard Innovation Lab. Through Experfy, we are helping our data science community members find lucrative projects and advance their skills. Please signup for Experfy at https://www.experfy.com/ to get started.

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