A Python Wrapper for indico. Use pre-built state of the art machine learning algorithms with a single line of code.
Project description
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.
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.
===============
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.
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.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
IndicoIo-0.4.12.tar.gz
(7.8 kB
view hashes)