A Python Wrapper for indico. Use pre-built state of the art machine learning algorithms with a single line of code.
Project description
A wrapper for the indico API.
The indico API is free to use, and no training data is required.
Installation
From PyPI:
pip install indicoio
From source:
git clone https://github.com/IndicoDataSolutions/IndicoIo-python.git
python setup.py install
API Keys + Setup
For API key registration and setup, checkout our quickstart guide.
Full Documentation
Detailed documentation and further code examples are available at indico.io/docs.
Supported APIs:
Positive/Negative Sentiment Analysis
Political Sentiment Analysis
Image Feature Extraction
Facial Emotion Recognition
Facial Feature Extraction
Language Detection
Text Topic Tagging
Examples
>>> from indicoio import political, sentiment, language, text_tags, keywords, fer, facial_features, image_features
>>> indicoio.config.api_key = "YOUR_API_KEY"
>>> 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.')
0.07062467665597527
>>> sentiment('Really enjoyed the movie.')
0.8105182526856075
>>> text_tags("Facebook blog posts about Android tech make better journalism than most news outlets.")
>>> text_tags(test_text, threshold=0.1) # return only keys with value > 0.1
{u'startups_and_entrepreneurship': 0.21888586688354486}
>>> text_tags(test_text, top_n=1) # return only keys with top_n values
{u'startups_and_entrepreneurship': 0.21888586688354486}
>>> import numpy as np
>>> test_face = np.linspace(0,50,48*48).reshape(48,48)
>>> 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, ..., 3.0342637531932777]
>>> language('Quis custodiet ipsos custodes')
{u'Swedish': 0.00033330636691921914, u'Lithuanian': 0.007328693814717631, u'Vietnamese': 0.0002686116137658802, u'Romanian': 8.133913804076592e-06, ...}
>>> keywords("Facebook blog posts about Android tech make better journalism than most news outlets.", top_n=3)
{u'android': 0.10602030910588661,
u'journalism': 0.13466866170166855,
u'outlets': 0.13930405357808642}
Batch API
Each indicoio function can process many examples with a single request. Simply pass in a list of inputs and receive a list of results in return.
>>> from indicoio import sentiment
>>> sentiment(['Best day ever', 'Worst day ever'])
[0.9899001220871786, 0.005709885173415242]
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