mirror of
https://github.com/wassname/IndicoIo-python.git
synced 2026-06-27 16:10:34 +08:00
Madison May
100 lines
2.8 KiB
ReStructuredText
100 lines
2.8 KiB
ReStructuredText
indicoio-python
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===============
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A wrapper for the `indico API <http://indico.io>`__.
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The indico API is free to use, and no training data is required.
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Installation
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------------
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From PyPI:
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.. code:: bash
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pip install indicoio
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From source:
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.. code:: bash
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git clone https://github.com/IndicoDataSolutions/IndicoIo-python.git
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python setup.py install
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API Keys + Setup
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----------------
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For API key registration and setup, checkout our `quickstart
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guide <https://dash.readme.io/project/indico/v2.0/docs/api-keys>`__.
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Full Documentation
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------------------
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Detailed documentation and further code examples are available at
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`indico.reame.io <http://indico.readme.io/v2.0/docs/python>`__.
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Supported APIs:
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---------------
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- Positive/Negative Sentiment Analysis
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- Political Sentiment Analysis
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- Image Feature Extraction
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- Facial Emotion Recognition
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- Facial Feature Extraction
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- Language Detection
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- Text Topic Tagging
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Examples
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--------
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.. code:: python
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>>> from indicoio import political, sentiment, language, text_tags, fer, facial_features, image_features
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>>> indicoio.config.api_key = "YOUR_API_KEY"
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>>> political("Guns don't kill people. People kill people.")
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{u'Libertarian': 0.47740164630834825, u'Green': 0.08454409540443657, u'Liberal': 0.16617097211030055, u'Conservative': 0.2718832861769146}
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>>> sentiment('Worst movie ever.')
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0.07062467665597527
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>>> sentiment('Really enjoyed the movie.')
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0.8105182526856075
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>>> text_tags("Facebook blog posts about Android tech make better journalism than most news outlets.")
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>>> text_tags(test_text, threshold=0.1) # return only keys with value > 0.1
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{u'startups_and_entrepreneurship': 0.21888586688354486}
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>>> text_tags(test_text, top_n=1) # return only keys with top_n values
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{u'startups_and_entrepreneurship': 0.21888586688354486}
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>>> import numpy as np
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>>> test_face = np.linspace(0,50,48*48).reshape(48,48).tolist()
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>>> fer(test_face)
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{u'Angry': 0.08843749137458341, u'Sad': 0.39091163159204684, u'Neutral': 0.1947947999669361, u'Surprise': 0.03443785859010413, u'Fear': 0.17574534848440568, u'Happy': 0.11567286999192382}
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>>> facial_features(test_face)
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[0.0, -0.02568680526917187, 0.21645604230056517, ..., 3.0342637531932777]
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>>> language('Quis custodiet ipsos custodes')
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{u'Swedish': 0.00033330636691921914, u'Lithuanian': 0.007328693814717631, u'Vietnamese': 0.0002686116137658802, u'Romanian': 8.133913804076592e-06, ...}
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Batch API Access
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----------------
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Each ``indicoio`` function has a corresponding batch function for
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analyzing many examples with a single request. Simply pass in a list of
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inputs and receive a list of results in return.
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.. code:: python
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>>> from indicoio import batch_sentiment
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>>> batch_sentiment(['Best day ever', 'Worst day ever'])
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[0.9899001220871786, 0.005709885173415242]
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