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language detection added

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Slater-Victoroff
2014-08-01 02:30:22 -04:00
parent b5ece3d51b
commit d5087188fc
10 changed files with 95 additions and 43 deletions
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CHANGES.txt
+4
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@@ -1,3 +1,7 @@
v0.2.8, Tue May 13 -- Added Description, Authors file, changelog. Cleaned up import paths and modified corresponding examples and tests
v0.2.10, Mon Jun 2 -- API now supports normalization, updating documentation to reflect this.
v0.2.11, Fri Jun 6 -- Switched sentiment api to more general version with much higher quality. updated docs to reflect this. Also changed unintuitive posneg to more intuitive Sentiment. Kept old posneg for backward compatibility.
v0.3.0, Mon Jul 21 -- Switched api over to new high-volume version, using api.indico.io instead
v0.3.1, Mon Jul 21 -- Added __version__ to module
v0.3.2, Tue Jul 22 -- Removed spam detection due to instability
v0.3.3, Fri Aug 1 -- Added language detection api
IndicoIo/__init__.py
+3 -1
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@@ -1,6 +1,8 @@
JSON_HEADERS = {'Content-type': 'application/json', 'Accept': 'text/plain'}
__version__ = '0.3.3'
from text.sentiment import political, spam, posneg
from text.sentiment import political, posneg
from text.sentiment import posneg as sentiment
from text.lang import language
from images.fer import fer
from images.features import facial_features
IndicoIo/images/features.py
+1 -1
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@@ -5,7 +5,7 @@ import numpy as np
from IndicoIo import JSON_HEADERS
base_url = lambda c: "http://indico.io/api/%s" % c
base_url = lambda c: "http://api.indico.io/%s" % c
def facial_features(face):
data_dict = json.dumps({"face": face})
IndicoIo/images/fer.py
+1 -1
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@@ -4,7 +4,7 @@ import requests
import numpy as np
from IndicoIo import JSON_HEADERS
base_url = "http://indico.io/api/fer"
base_url = "http://api.indico.io/fer"
def fer(face):
data_dict = json.dumps({"face": face})
IndicoIo/text/lang.py
+11
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@@ -0,0 +1,11 @@
import requests
import json
from IndicoIo import JSON_HEADERS
base_url = lambda c: "http://api.indico.io/%s" % c
def language(test_text):
data_dict = json.dumps({'text': test_text})
response = requests.post(base_url("language"), data=data_dict, headers=JSON_HEADERS)
return json.loads(response.content)
IndicoIo/text/sentiment.py
+1 -6
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@@ -4,18 +4,13 @@ import json
from IndicoIo import JSON_HEADERS
from IndicoIo.utils import normalize
base_url = lambda c: "http://indico.io/api/%s" % c
base_url = lambda c: "http://api.indico.io/%s" % c
def political(test_text):
data_dict = json.dumps({'text': test_text})
response = requests.post(base_url("political"), data=data_dict, headers=JSON_HEADERS)
return json.loads(response.content)
def spam(test_text):
data_dict = json.dumps({'text': test_text})
response = requests.post(base_url("spam"), data=data_dict, headers=JSON_HEADERS)
return json.loads(response.content)
def posneg(test_text):
data_dict = json.dumps({'text': test_text})
response = requests.post(base_url("sentiment"), data=data_dict, headers=JSON_HEADERS)
README
+4 -5
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@@ -15,24 +15,21 @@ 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
- Language Detection
Examples
--------
```
>>> import numpy as np
>>> from IndicoIo import political, spam, sentiment, fer, facial_features
>>> from IndicoIo import political, sentiment, fer, facial_features, language
>>> 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}
>>> sentiment('Worst movie ever.')
{u'Sentiment': 0.07062467665597527}
@@ -47,6 +44,8 @@ Examples
>>> 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('Clearly an english phrase')
```
Installation
README.md
+4 -5
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@@ -15,24 +15,21 @@ 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
- Language Detection
Examples
--------
```
>>> import numpy as np
>>> from IndicoIo import political, spam, sentiment, fer, facial_features
>>> from IndicoIo import political, sentiment, fer, facial_features, language
>>> 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}
>>> sentiment('Worst movie ever.')
{u'Sentiment': 0.07062467665597527}
@@ -47,6 +44,8 @@ Examples
>>> 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('Clearly an english phrase')
```
Installation
setup.py
+25 -15
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@@ -1,22 +1,32 @@
"""
Setup for indicoio apis
"""
try:
from setuptools import setup
except ImportError:
from distutils.core import setup
setup(
name = "IndicoIo",
version = '0.2.11',
packages = [
"IndicoIo",
"IndicoIo.text",
"IndicoIo.images",
"IndicoIo.utils",
"tests",
],
description = "A Python Wrapper for IndicoIo. Use pre-built state of the art machine learning algorithms with a single line of code.",
license = "MIT License (See LICENSE)",
long_description = open("README").read(),
url = "https://github.com/IndicoDataSolutions/IndicoIo-python",
author = "Alec Radford, Slater Victoroff, Aidan McLaughlin",
author_email = "Alec Radford <alec@indicodatasolutions.com>, Slater Victoroff <slater@indicodatasolutions.com>, Aidan McLaughlin <aidan@indicodatasolutions.com>",
name="IndicoIo",
version='0.3.3',
packages=[
"IndicoIo",
"IndicoIo.text",
"IndicoIo.images",
"IndicoIo.utils",
"tests",
],
description="""
A Python Wrapper for IndicoIo.
Use pre-built state of the art machine learning algorithms with a single line of code.
""",
license="MIT License (See LICENSE)",
long_description=open("README").read(),
url="https://github.com/IndicoDataSolutions/IndicoIo-python",
author="Alec Radford, Slater Victoroff, Aidan McLaughlin",
author_email="""
Alec Radford <alec@indicodatasolutions.com>,
Slater Victoroff <slater@indicodatasolutions.com>,
Aidan McLaughlin <aidan@indicodatasolutions.com>
""",
)
tests/test_run.py
+41 -9
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@@ -2,7 +2,7 @@ import unittest
import numpy as np
from IndicoIo import political, spam, sentiment, fer, facial_features
from IndicoIo import political, sentiment, fer, facial_features, language
class FullAPIRun(unittest.TestCase):
@@ -15,14 +15,6 @@ class FullAPIRun(unittest.TestCase):
self.assertTrue(isinstance(response, dict))
self.assertEqual(political_set, set(response.keys()))
def test_spam(self):
spam_set = set(['Spam', 'Ham'])
test_string = "Buy a new car!!"
response = spam(test_string)
self.assertTrue(isinstance(response, dict))
self.assertEqual(spam_set, set(response.keys()))
def test_posneg(self):
posneg_set = set(['Sentiment'])
test_string = "Worst song ever."
@@ -54,6 +46,46 @@ class FullAPIRun(unittest.TestCase):
self.assertTrue(isinstance(response, list))
self.assertEqual(len(response), 48)
def test_language(self):
language_set = set([
'English',
'Spanish',
'Tagalog',
'Esperanto',
'French',
'Chinese',
'French',
'Bulgarian',
'Latin',
'Slovak',
'Hebrew',
'Russian',
'German',
'Japanese',
'Korean',
'Portuguese',
'Italian',
'Polish',
'Turkish',
'Dutch',
'Arabic',
'Persian (Farsi)',
'Czech',
'Swedish',
'Indonesian',
'Vietnamese',
'Romanian',
'Greek',
'Danish',
'Hungarian',
'Thai',
'Finnish',
'Norwegian',
'Lithuanian'
])
language_dict = language('clearly an english sentence')
self.assertEqual(language_set, set(language_dict.keys()))
if __name__ == "__main__":
unittest.main()