mirror of
https://github.com/wassname/IndicoIo-python.git
synced 2026-06-27 16:10:34 +08:00
Slater-Victoroff
54 lines
2.2 KiB
Plaintext
54 lines
2.2 KiB
Plaintext
IndicoIo-python
|
|
===============
|
|
|
|
A wrapper for a series of APIs made by Indico Data Solutions.
|
|
|
|
Check out the main site on:
|
|
|
|
http://indico.io
|
|
|
|
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:
|
|
|
|
- Political Sentiment Analysis
|
|
- Spam Detection
|
|
- Positive/Negative Sentiment Analysis
|
|
- Facial Emotion Recognition
|
|
- Facial Feature Extraction
|
|
|
|
Examples
|
|
--------
|
|
```
|
|
>>> import numpy as np
|
|
|
|
>>> from IndicoIo import political, spam, posneg, fer, facial_features
|
|
|
|
>>> political("Guns don't kill people. People kill people.")
|
|
{u'Libertarian': 0.22934946808893228, u'Liberal': 0.2025395008382684, u'Green': 0.0, u'Conservative': 1.0}
|
|
|
|
>>> spam("Free car!")
|
|
{u'Ham': 0.0, u'Spam': 1.0}
|
|
|
|
>>> posneg("Would not stay in this hotel ever again.")
|
|
{u'Positive': 0.0, u'Negative': 1.0}
|
|
|
|
>>> 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]
|
|
|
|
```
|
|
|
|
Installation
|
|
------------
|
|
```
|
|
pip install indicoio
|
|
```
|