fixed up README and did some housecleaning

IndicoIo/__init__.py

@@ -0,0 +1 @@
+JSON_HEADERS = {'Content-type': 'application/json', 'Accept': 'text/plain'}

IndicoIo/images/facial_features.py

@@ -3,10 +3,11 @@ import json
 import requests
 import numpy as np
 
+from IndicoIo import JSON_HEADERS
+
 base_url = lambda c: "http://indico.io/api/features/%s" % c
-headers = {'Content-type': 'application/json', 'Accept': 'text/plain'}
 
 def facial(face):
     data_dict = json.dumps({"datums": face})
-    response = requests.post(base_url("facial"), data=data_dict, headers=headers)
-    return response.content
+    response = requests.post(base_url("facial"), data=data_dict, headers=JSON_HEADERS)
+    return json.loads(response.content)

IndicoIo/images/fer.py

@@ -2,11 +2,11 @@ import json
 
 import requests
 import numpy as np
+from IndicoIo import JSON_HEADERS
 
 base_url = "http://indico.io/api/fer/classify"
-headers = {'Content-type': 'application/json', 'Accept': 'text/plain'}
 
 def fer(face):
     data_dict = json.dumps({"image": face})
-    response = requests.post(base_url, data=data_dict, headers=headers)
-    return response.content
+    response = requests.post(base_url, data=data_dict, headers=JSON_HEADERS)
+    return json.loads(response.content)

IndicoIo/text/sentiment.py

@@ -1,20 +1,20 @@
 import requests
 import json
+from IndicoIo import JSON_HEADERS
 
 base_url = lambda c: "http://indico.io/api/sentiment/%s/classify" % c
-headers = {'Content-type': 'application/json', 'Accept': 'text/plain'}
 
 def political(test_text):
     data_dict = json.dumps({'text': test_text})
-    response = requests.post(base_url("political"), data=data_dict, headers=headers)
+    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=headers)
+    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=headers)
+    response = requests.post(base_url("sentiment"), data=data_dict, headers=JSON_HEADERS)
     return json.loads(response.content)

README

@@ -1,4 +1,47 @@
 IndicoIo-python
 ===============
 
-Python repository for Indico API wrapper
+A wrapper for a series of APIs made by Indico Data Solutions.
+
+Check out the main site on:
+
+http://indico.io
+
+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.text.sentiment import political, spam, posneg
+>>> from IndicoIo.images.fer import fer
+>>> from IndicoIo.images.facial_features import facial
+
+>>> political("Guns don't kill people, people kill people")
+{u'Libertarian': 1.000094905588269, u'Liberal': 1.000194776694221, u'Green': 1.0000989185747784, u'Conservative': 1.000114308739228}
+
+>>> spam("Buy a new car!!")
+{u'Ham': 1.0001470818000544, u'Spam': 1.0003137966593707}
+
+>>> posneg("Would not stay in this hotel ever again.")
+{u'Positive': 1.0002370406887562, u'Negative': 1.0002938352112363}
+
+>>> 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(test_face)
+{u'feature_vector': u'[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]'}
+
+```