From 1d42d6defeefc6e4f036ce53ba2f30ef5a350194 Mon Sep 17 00:00:00 2001
From: dianavermilya <dvermilya@onshape.com>
Date: Tue, 21 Jul 2015 11:27:37 -0400
Subject: [PATCH 1/3] FIX: check if data is a list to determine if batch or
 single request

---
 indicoio/__init__.py      |  24 ++++++++--
 indicoio/utils/api.py     |   7 ++-
 indicoio/utils/image.py   |  43 +-----------------
 tests/data/48by48.png     | Bin 0 -> 2420 bytes
 tests/data/48by48rgb.png  | Bin 0 -> 7028 bytes
 tests/data/48by48rgba.png | Bin 0 -> 88 bytes
 tests/data/64by64.png     | Bin 0 -> 4228 bytes
 tests/test_remote.py      |  93 +++++++++++++++++---------------------
 8 files changed, 69 insertions(+), 98 deletions(-)
 create mode 100644 tests/data/48by48.png
 create mode 100644 tests/data/48by48rgb.png
 create mode 100644 tests/data/48by48rgba.png
 create mode 100644 tests/data/64by64.png

diff --git a/indicoio/__init__.py b/indicoio/__init__.py
index 9db9de6..8bfa3e3 100644
--- a/indicoio/__init__.py
+++ b/indicoio/__init__.py
@@ -1,4 +1,5 @@
-from functools import partial
+from functools import wraps, partial
+import warnings
 
 Version, version, __version__, VERSION = ('0.8.1',) * 4
 
@@ -23,9 +24,26 @@ from indicoio.utils.multi import predict_image, predict_text
 
 from indicoio.config import API_NAMES
 
+def deprecation_decorator(f, api):
+    @wraps(f)
+    def wrapper(*args, **kwargs):
+        warnings.warn(
+            "'batch_" + api + "' will be deprecated in the next major update.  Please call '" + api + "' instead with the same arguments.",
+            DeprecationWarning
+        )
+        return f(*args, **kwargs)
+    return wrapper
 
+def detect_batch_decorator(f):
+    @wraps(f)
+    def wrapper(*args, **kwargs):
+        if isinstance(args[0], list):
+            kwargs['batch'] = True
+        return f(*args, **kwargs)
+    return wrapper
+    
 apis = dict((api, globals().get(api)) for api in API_NAMES)
 
 for api in apis:
-    globals()[api] = partial(apis[api])
-    globals()['batch_' + api] = partial(apis[api], batch=True)
+    globals()[api] = partial(detect_batch_decorator(apis[api]))
+    globals()['batch_' + api] = partial(deprecation_decorator(apis[api], api), batch=True)
diff --git a/indicoio/utils/api.py b/indicoio/utils/api.py
index 836b243..141cc0f 100644
--- a/indicoio/utils/api.py
+++ b/indicoio/utils/api.py
@@ -8,12 +8,15 @@ from indicoio.utils.errors import IndicoError, DataStructureException
 from indicoio import JSON_HEADERS
 from indicoio import config
 
-def api_handler(arg, cloud, api, url_params = {"batch":False, "api_key":None}, **kwargs):
+def api_handler(arg, cloud, api, url_params=None, **kwargs):
+    if url_params is None:
+        url_params = {"api_key":None, batch:False }
+
     data = {'data': arg}
     data.update(**kwargs)
     json_data = json.dumps(data)
     if not cloud:
-        cloud=config.cloud
+        cloud = config.cloud
 
     if cloud:
         host = "%s.indico.domains" % cloud
diff --git a/indicoio/utils/image.py b/indicoio/utils/image.py
index f0ab106..29b3312 100644
--- a/indicoio/utils/image.py
+++ b/indicoio/utils/image.py
@@ -26,14 +26,8 @@ def image_preprocess(image, size=(48,48), batch=False):
         elif B64_PATTERN.match(b64_str) is not None:
             return b64_str
         else:
-            raise IndicoError("Snose tring provided must be a valid filepath or base64 encoded string")
+            raise IndicoError("String provided must be a valid filepath or base64 encoded string")
 
-    elif isinstance(image, list): # image passed in is a list and not np.array
-        warnings.warn(
-            "Input as lists of pixels will be deprecated in the next major update",
-            DeprecationWarning
-        )
-        out_image = process_list_image(image)
     elif isinstance(image, Image.Image):
         out_image = image
     elif type(image).__name__ == "ndarray": # image is from numpy/scipy
@@ -80,38 +74,3 @@ def get_element_type(_list, dimens):
         elem = elem[0]
     return type(elem)
 
-
-def process_list_image(_list):
-    """
-    Processes list to be [[(int, int, int), ...]]
-    """
-    # Check if list is empty
-    if not _list:
-        return _list
-
-    dimens = get_list_dimensions(_list)
-    data_type = get_element_type(_list, dimens)
-
-    seq_obj = []
-
-    out_image = Image.new("RGB", (dimens[0], dimens[1]))
-    for i in xrange(dimens[0]):
-        for j in xrange(dimens[1]):
-            elem = _list[i][j]
-            if len(dimens) >= 3:
-                #RGB(A)
-                if data_type == float:
-                    seq_obj.append((int(elem[0] * 255), int(elem[1] * 255), int(elem[2] * 255)))
-                else:
-                    seq_obj.append(tuple(elem[0:3]))
-            elif data_type == float:
-                #Grayscale 0 - 1.0f
-                seq_obj.append((int(elem * 255), ) * 3)
-            else:
-                #Grayscale 0 - 255
-                seq_obj.append((elem, ) * 3)
-
-    #Needs to be 0 - 255 in flattened list of (R, G, B)
-    out_image.putdata(data = seq_obj)
-
-    return out_image
diff --git a/tests/data/48by48.png b/tests/data/48by48.png
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diff --git a/tests/data/48by48rgba.png b/tests/data/48by48rgba.png
new file mode 100644
index 0000000000000000000000000000000000000000..91ffaf845ea1e77c7455941efa7da44d00802bac
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diff --git a/tests/data/64by64.png b/tests/data/64by64.png
new file mode 100644
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zSnF~Ds+lg)9ZqW678s;U^|2MrK`X+5*Ckdhwqrg#{E@u3Rz!4gV7q)l4d3xdD6HuR
zC7o$<-o3m+%ThQJf0v-40pTKtRSM==39RecR>Q%*9dscqKYXZGF7VefUNx~{%)T0x
zZ^svum)*Otq*!*U6Y}|Hx*g|4_aUCSclo4lCjpXmKXH(OTX{#}={og>!E;%hHZvPT
zxzy0;K=W-X!}s<Ay9^i^*3so`tTw(1i_3WsMUY<WYjyi-sBsNi|B3<Q6E|VW-@B0^
z0I}JiEzu#oA{gQ1idKYSOS$!e1NKCVz}H;M7<hkLBhxseMV~gClb`C%I|R^_XO5>P
zjVdnz@TGQ6I^SuF#N97Y(ewz7$QIGZJP_T|(T75sqnb`#y4^SHI^+|<`4Jc3qQ)~H
z)I}jToJ+$C$c^)|opR><0q{T96*axnYsZN#6ey_N=<pKEQ)m=fkPmlFc6{u6N1Elb
zzEqcBG?q5wz)4>uv?0<G?^{mw^~s{N^x2qRcmbBrXbmkPW2G2)TVYZ*>&LF+d)VTP
z2KuinzYTuH-Q$8H$q-+N_4TsnoH+S-eY8v{D!123Ak;@w0y3`2r2YZl&^D5}*bs>t
z?w0DKNxsC5mgdRlsfvFIePj$moS0UoP)Rub*HRVmE2qs}DumoK-Z=(J!S3Jh_GzUs
z@UfQxaA47dtShj)e9t*6G|WOoREy!eXeqgerAQy8%U`Tb1xHz~2H#HUn$p^FL1laL
zpN}B$G1~=hjwyRfBy?&60TcgsxU?_6S~Nka|2(l9z`3G%LI<vS_9e(g_V^I%_bvgw
zcD*A6NV)%4YvxQpjLPvK3%lCAd_8rwl72#exdESSkZ@nWws?d%_}jHvtF3)&qJse{
z=`9w!vp-Sk)2}2$BC2r+&0uIB9=wuQLjj}hx3U8P#au&ZtX>@-cpL#&j3lVORQ4}q
zg8^9GdJa#*ML?>km&()hbu6^`3|xoQ)W9H?<OPy6amZzxIu{pmA{d0ZPG<!nOA*Mn
aZoEYuKpZxu3thJW0000<MNUMnLSTXfE-9V>

literal 0
HcmV?d00001

diff --git a/tests/test_remote.py b/tests/test_remote.py
index 85c45b5..5fe482f 100644
--- a/tests/test_remote.py
+++ b/tests/test_remote.py
@@ -31,74 +31,74 @@ class BatchAPIRun(unittest.TestCase):
 
     def test_batch_texttags(self):
         test_data = ["On Monday, president Barack Obama will be..."]
-        response = batch_text_tags(test_data, api_key=self.api_key)
+        response = text_tags(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
 
     def test_batch_keywords(self):
         test_data = ["A working api is key to the success of our young company"]
         words = [set(text.lower().split()) for text in test_data]
-        response = batch_keywords(test_data, api_key=self.api_key)
+        response = keywords(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(set(response[0].keys()).issubset(words[0]))
 
     def test_batch_posneg(self):
         test_data = ['Worst song ever', 'Best song ever']
-        response = batch_sentiment(test_data, api_key=self.api_key)
+        response = sentiment(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(response[0] < 0.5)
 
     def test_batch_sentiment_hq(self):
         test_data = ['Worst song ever', 'Best song ever']
-        response = batch_sentiment_hq(test_data, api_key=self.api_key)
+        response = sentiment_hq(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(response[0] < 0.5)
 
     def test_batch_political(self):
         test_data = ["Guns don't kill people, people kill people."]
-        response = batch_political(test_data, api_key=self.api_key)
+        response = political(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
 
     def test_batch_fer(self):
-        test_data = [generate_array((48,48))]
-        response = batch_fer(test_data, api_key=self.api_key)
+        test_data = [os.path.normpath(os.path.join(DIR, "data/48by48.png"))]
+        response = fer(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(isinstance(response[0], dict))
 
     def test_batch_content_filtering(self):
-        test_data = [generate_array((48,48))]
-        response = batch_content_filtering(test_data, api_key=self.api_key)
+        test_data = [os.path.normpath(os.path.join(DIR, "data/48by48.png"))]
+        response = content_filtering(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(isinstance(response[0], float))
 
     def test_batch_fer_bad_b64(self):
         test_data = ["$bad#FI jeaf9(#0"]
-        self.assertRaises(IndicoError, batch_fer, test_data, api_key=self.api_key)
+        self.assertRaises(IndicoError, fer, test_data, api_key=self.api_key)
 
     def test_batch_fer_good_b64(self):
         test_data = ["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"]
-        response = batch_fer(test_data, api_key=self.api_key)
+        response = fer(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(isinstance(response[0], dict))
 
     def test_batch_fer_filepath(self):
         test_data = [os.path.normpath(os.path.join(DIR, "data/fear.png"))]
-        response = batch_fer(test_data, api_key=self.api_key)
+        response = fer(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(isinstance(response[0], dict))
 
     def test_batch_fer_pil_image(self):
         test_data = [Image.open(os.path.normpath(os.path.join(DIR, "data/fear.png")))]
-        response = batch_fer(test_data, api_key=self.api_key)
+        response = fer(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(isinstance(response[0], dict))
 
     def test_batch_fer_nonexistant_filepath(self):
         test_data = ["data/unhappy.png"]
-        self.assertRaises(IndicoError, batch_fer, test_data, api_key=self.api_key)
+        self.assertRaises(IndicoError, fer, test_data, api_key=self.api_key)
 
     def test_batch_facial_features(self):
-        test_data = [generate_array((48,48))]
-        response = batch_facial_features(test_data, api_key=self.api_key)
+        test_data = [os.path.normpath(os.path.join(DIR, "data/48by48.png"))]
+        response = facial_features(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(isinstance(response[0], list))
         self.assertEqual(len(response[0]), 48)
@@ -117,22 +117,22 @@ class BatchAPIRun(unittest.TestCase):
     # have decided how we are dealing with them
 
     def test_batch_image_features_greyscale(self):
-        test_data = [generate_array((48,48))]
-        response = batch_image_features(test_data, api_key=self.api_key)
+        test_data = [os.path.normpath(os.path.join(DIR, "data/48by48.png"))]
+        response = image_features(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(isinstance(response[0], list))
         self.assertEqual(len(response[0]), 2048)
 
     def test_batch_image_features_rgb(self):
-        test_data = [generate_array((48,48))]
-        response = batch_image_features(test_data, api_key=self.api_key)
+        test_data = [os.path.normpath(os.path.join(DIR, "data/48by48rgb.png"))]
+        response = image_features(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(isinstance(response[0], list))
         self.assertEqual(len(response[0]), 2048)
 
     def test_batch_language(self):
         test_data = ['clearly an english sentence']
-        response = batch_language(test_data, api_key=self.api_key)
+        response = language(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(response[0]['English'] > 0.25)
 
@@ -140,14 +140,15 @@ class BatchAPIRun(unittest.TestCase):
         batch = ["London Underground's boss Mike Brown warned that the strike ..."]
         expected_entities = ("London Underground", "Mike Brown")
         expected_keys = set(["categories", "confidence"])
-        entities = batch_named_entities(batch)[0]
+        entities = named_entities(batch)[0]
         for entity in expected_entities:
             assert entity in expected_entities
             assert not (set(entities[entity]) - expected_keys)
 
     def test_batch_multi_api_image(self):
-        test_data = [generate_array((48,48)), generate_int_array((48,48))]
-        response = batch_predict_image(test_data, apis=config.IMAGE_APIS, api_key=self.api_key)
+        test_data = [os.path.normpath(os.path.join(DIR, "data/48by48.png")),
+                     os.path.normpath(os.path.join(DIR, "data/48by48.png"))]
+        response = predict_image(test_data, apis=config.IMAGE_APIS, api_key=self.api_key)
 
         self.assertTrue(isinstance(response, dict))
         self.assertTrue(set(response.keys()) == set(config.IMAGE_APIS))
@@ -155,21 +156,21 @@ class BatchAPIRun(unittest.TestCase):
 
     def test_batch_multi_api_text(self):
         test_data = ['clearly an english sentence']
-        response = batch_predict_text(test_data, apis=config.TEXT_APIS, api_key=self.api_key)
+        response = predict_text(test_data, apis=config.TEXT_APIS, api_key=self.api_key)
 
         self.assertTrue(isinstance(response, dict))
         self.assertTrue(set(response.keys()) == set(config.TEXT_APIS))
 
     def test_default_multi_api_text(self):
         test_data = ['clearly an english sentence']
-        response = batch_predict_text(test_data, api_key=self.api_key)
+        response = predict_text(test_data, api_key=self.api_key)
 
         self.assertTrue(isinstance(response, dict))
         self.assertTrue(set(response.keys()) == set(config.TEXT_APIS))
 
     def test_multi_api_bad_api(self):
         self.assertRaises(IndicoError,
-                          batch_predict_text,
+                          predict_text,
                           "this shouldn't work",
                           apis=["sentiment", "somethingbad"])
 
@@ -180,14 +181,14 @@ class BatchAPIRun(unittest.TestCase):
                             apis=["fer", "sentiment", "facial_features"])
     def test_batch_multi_bad_mixed_api(self):
         self.assertRaises(IndicoError,
-                            batch_predict_text,
+                            predict_text,
                             ["this shouldn't work"],
                             apis=["fer", "sentiment", "facial_features"])
 
     def test_batch_set_cloud(self):
         test_data = ['clearly an english sentence']
         self.assertRaises(ConnectionError,
-                          batch_language,
+                          language,
                           test_data,
                           api_key=self.api_key,
                           cloud='invalid/cloud')
@@ -290,7 +291,7 @@ class FullAPIRun(unittest.TestCase):
 
     def test_good_fer(self):
         fer_set = set(['Angry', 'Sad', 'Neutral', 'Surprise', 'Fear', 'Happy'])
-        test_face = generate_array((48,48))
+        test_face = os.path.normpath(os.path.join(DIR, "data/48by48.png"))
         response = fer(test_face)
 
         self.assertTrue(isinstance(response, dict))
@@ -298,14 +299,14 @@ class FullAPIRun(unittest.TestCase):
 
     def test_good_int_array_fer(self):
         fer_set = set(['Angry', 'Sad', 'Neutral', 'Surprise', 'Fear', 'Happy'])
-        test_face = generate_int_array((48,48))
+        test_face = os.path.normpath(os.path.join(DIR, "data/48by48.png"))
         response = fer(test_face)
 
         self.assertTrue(isinstance(response, dict))
         self.assertEqual(fer_set, set(response.keys()))
 
     def test_happy_fer(self):
-        test_face = self.load_image("data/happy.png", as_grey=True)
+        test_face = os.path.normpath(os.path.join(DIR, "data/happy.png"))
         response = fer(test_face)
         self.assertTrue(isinstance(response, dict))
         self.assertTrue(response['Happy'] > 0.5)
@@ -317,26 +318,26 @@ class FullAPIRun(unittest.TestCase):
         self.assertTrue(response['Happy'] > 0.5)
 
     def test_fear_fer(self):
-        test_face = self.load_image("data/fear.png", as_grey=True)
+        test_face = os.path.normpath(os.path.join(DIR, "data/fear.png"))
         response = fer(test_face)
         self.assertTrue(isinstance(response, dict))
         self.assertTrue(response['Fear'] > 0.25)
 
     def test_bad_fer(self):
         fer_set = set(['Angry', 'Sad', 'Neutral', 'Surprise', 'Fear', 'Happy'])
-        test_face = generate_array((56, 56))
+        test_face = os.path.normpath(os.path.join(DIR, "data/64by64.png"))
         response = fer(test_face)
 
         self.assertTrue(isinstance(response, dict))
         self.assertEqual(fer_set, set(response.keys()))
 
     def test_safe_content_filtering(self):
-        test_face = self.load_image("data/happy.png", as_grey=True)
+        test_face = os.path.normpath(os.path.join(DIR, "data/happy.png"))
         response = content_filtering(test_face)
         self.assertTrue(response < 0.5)
 
     def test_good_facial_features(self):
-        test_face = generate_array((48,48))
+        test_face = os.path.normpath(os.path.join(DIR, "data/48by48.png"))
         response = facial_features(test_face)
 
         self.assertTrue(isinstance(response, list))
@@ -344,7 +345,7 @@ class FullAPIRun(unittest.TestCase):
         self.check_range(response)
 
     def test_rgba_int_array_facial_features(self):
-        test_face = generate_rgba_int_array((48, 48))
+        test_face = os.path.normpath(os.path.join(DIR, "data/48by48rgba.png"))
         response = facial_features(test_face)
 
         self.assertTrue(isinstance(response, list))
@@ -353,7 +354,7 @@ class FullAPIRun(unittest.TestCase):
 
     def test_good_int_array_facial_features(self):
         fer_set = set(['Angry', 'Sad', 'Neutral', 'Surprise', 'Fear', 'Happy'])
-        test_face = generate_int_array((48,48))
+        test_face = os.path.normpath(os.path.join(DIR, "data/48by48.png"))
         response = facial_features(test_face)
 
         self.assertTrue(isinstance(response, list))
@@ -371,7 +372,7 @@ class FullAPIRun(unittest.TestCase):
     #     self.check_range(response)
 
     def test_good_image_features_greyscale(self):
-        test_image = generate_array((48,48))
+        test_image = os.path.normpath(os.path.join(DIR, "data/48by48.png"))
         response = image_features(test_image)
 
         self.assertTrue(isinstance(response, list))
@@ -379,7 +380,7 @@ class FullAPIRun(unittest.TestCase):
         self.check_range(response)
 
     def test_good_image_features_rgb(self):
-        test_image = [[(random.random(),) * 3 for _ in xrange(48)] for _ in xrange(48)]
+        test_image = os.path.normpath(os.path.join(DIR, "data/48by48rgb.png"))
         response = image_features(test_image)
 
         self.assertTrue(isinstance(response, list))
@@ -387,7 +388,7 @@ class FullAPIRun(unittest.TestCase):
         self.check_range(response)
 
     def test_multi_api_image(self):
-        test_data = generate_array((48,48))
+        test_data = os.path.normpath(os.path.join(DIR, "data/48by48.png"))
         response = predict_image(test_data, apis=config.IMAGE_APIS, api_key=self.api_key)
 
         self.assertTrue(isinstance(response, dict))
@@ -558,15 +559,5 @@ def flatten(container):
         else:
             yield i
 
-def generate_array(size):
-    return [[random.random() for _ in xrange(size[0])] for _ in xrange(size[1])]
-
-def generate_int_array(size):
-    return [[random.randint(0, 255) for _ in xrange(size[0])] for _ in xrange(size[1])]
-
-def generate_rgba_int_array(size):
-    return [[[random.randint(0, 255) for _ in xrange(3)] for _ in xrange(size[0])] for _ in xrange(size[1])]
-
-
 if __name__ == "__main__":
     unittest.main()

From d00b669a16279b12433918181dd56bd9d6cb579a Mon Sep 17 00:00:00 2001
From: dianavermilya <dvermilya@onshape.com>
Date: Tue, 21 Jul 2015 18:29:30 -0400
Subject: [PATCH 2/3] ADD: basic min axis content resizing

---
 .eggs/README.txt             |  6 ++++++
 indicoio/images/filtering.py |  2 +-
 indicoio/utils/image.py      | 25 +++++++++++++++++++++----
 tests/test_remote.py         | 10 ++++++++++
 tests/unit_test.py           | 16 ++++++++++++++++
 5 files changed, 54 insertions(+), 5 deletions(-)
 create mode 100644 .eggs/README.txt
 create mode 100644 tests/unit_test.py

diff --git a/.eggs/README.txt b/.eggs/README.txt
new file mode 100644
index 0000000..5d01668
--- /dev/null
+++ b/.eggs/README.txt
@@ -0,0 +1,6 @@
+This directory contains eggs that were downloaded by setuptools to build, test, and run plug-ins.
+
+This directory caches those eggs to prevent repeated downloads.
+
+However, it is safe to delete this directory.
+
diff --git a/indicoio/images/filtering.py b/indicoio/images/filtering.py
index 3851b8f..3eb697b 100644
--- a/indicoio/images/filtering.py
+++ b/indicoio/images/filtering.py
@@ -24,6 +24,6 @@ def content_filtering(image, cloud=None, batch=False, api_key=None, **kwargs):
     :type image: list of lists
     :rtype: float of nsfwness
     """
-    image = image_preprocess(image, batch=batch, size=None)
+    image = image_preprocess(image, batch=batch, size=None, min_axis=128)
     url_params = {"batch": batch, "api_key": api_key}
     return api_handler(image, cloud=cloud, api="contentfiltering", url_params=url_params, **kwargs)
diff --git a/indicoio/utils/image.py b/indicoio/utils/image.py
index 29b3312..8db17d7 100644
--- a/indicoio/utils/image.py
+++ b/indicoio/utils/image.py
@@ -10,7 +10,7 @@ from indicoio.utils.errors import IndicoError, DataStructureException
 
 B64_PATTERN = re.compile("^([A-Za-z0-9+/]{4})*([A-Za-z0-9+/]{4}|[A-Za-z0-9+/]{3}=|[A-Za-z0-9+/]{2}==)")
 
-def image_preprocess(image, size=(48,48), batch=False):
+def image_preprocess(image, size=(48,48), min_axis=None, batch=False):
     """
     Takes an image and prepares it for sending to the api including
     resizing and image data/structure standardizing.
@@ -41,9 +41,7 @@ def image_preprocess(image, size=(48,48), batch=False):
     else:
         raise IndicoError("Image must be a filepath, base64 encoded string, or a numpy array")
 
-    # image resizing
-    if size:
-        out_image = out_image.resize(size)
+    out_image = resize_image(out_image, size, min_axis)
 
     # convert to base64
     temp_output = StringIO.StringIO()
@@ -54,6 +52,25 @@ def image_preprocess(image, size=(48,48), batch=False):
     return base64.b64encode(output_s)
 
 
+def resize_image(image, size, min_axis):
+    if size:
+        image = image.resize(size)
+    if min_axis:
+        min_idx, other_idx = (0,1) if image.size[0] < image.size[1] else (1,0)
+        aspect = image.size[other_idx]/float(image.size[min_idx])
+        if aspect > 10:
+            warnings.warn(
+                "An aspect ratio greater than 10:1 is not recommended",
+                Warning
+            )          
+        size_arr = [0,0]
+        size_arr[min_idx] = min_axis
+        size_arr[other_idx] = int(min_axis * aspect)
+        image = image.resize(tuple(size_arr))
+
+    return image
+
+
 def get_list_dimensions(_list):
     """
     Takes a nested list and returns the size of each dimension followed
diff --git a/tests/test_remote.py b/tests/test_remote.py
index 5fe482f..f41f31a 100644
--- a/tests/test_remote.py
+++ b/tests/test_remote.py
@@ -336,6 +336,11 @@ class FullAPIRun(unittest.TestCase):
         response = content_filtering(test_face)
         self.assertTrue(response < 0.5)
 
+    def test_resize_content_filtering(self):
+        test_face = os.path.normpath(os.path.join(DIR, "data/happy.png"))
+        response = content_filtering(test_face)
+        self.assertTrue(isinstance(response, float))
+
     def test_good_facial_features(self):
         test_face = os.path.normpath(os.path.join(DIR, "data/48by48.png"))
         response = facial_features(test_face)
@@ -551,6 +556,11 @@ class NumpyImagesRun(FullAPIRun):
         test_image = np.random.randint(255, 300, size=(48,48, 5))
         self.assertRaises(IndicoError, image_features, test_image)
 
+    def test_resize_content_filtering_numpy_arrays(self):
+        test_image = np.random.randint(0, 255, size=(480,248, 3))
+        response = content_filtering(test_image)
+        self.assertTrue(isinstance(response, float))
+
 def flatten(container):
     for i in container:
         if isinstance(i, list) or isinstance(i, tuple):
diff --git a/tests/unit_test.py b/tests/unit_test.py
new file mode 100644
index 0000000..437c62e
--- /dev/null
+++ b/tests/unit_test.py
@@ -0,0 +1,16 @@
+from indicoio.utils.image import image_preprocess
+from PIL import Image
+import os, unittest, base64, StringIO
+
+DIR = os.path.dirname(os.path.realpath(__file__))
+
+class ResizeTests(unittest.TestCase):
+    """
+    test image resizing
+    """
+    def test_min_axis_resize(self):
+        test_image = os.path.normpath(os.path.join(DIR, "data/fear.png"))
+        resized_image = image_preprocess(test_image, min_axis=360)
+        image_string = StringIO.StringIO(base64.b64decode(resized_image))
+        image = Image.open(image_string)
+        self.assertEqual(image.size, (360.0, 360.0))

From b51e374efacefd76671088cb727a74bfdcc2ace5 Mon Sep 17 00:00:00 2001
From: Madison May <madison@indico.io>
Date: Tue, 28 Jul 2015 17:11:30 -0400
Subject: [PATCH 3/3] UPDATE: version number, README, CHANGES.txt

---
 .eggs/README.txt     |  6 ------
 CHANGES.txt          |  3 ++-
 README.md            | 12 ++++++------
 README.rst           | 16 ++++++++--------
 indicoio/__init__.py |  2 +-
 setup.py             |  2 +-
 6 files changed, 18 insertions(+), 23 deletions(-)
 delete mode 100644 .eggs/README.txt

diff --git a/.eggs/README.txt b/.eggs/README.txt
deleted file mode 100644
index 5d01668..0000000
--- a/.eggs/README.txt
+++ /dev/null
@@ -1,6 +0,0 @@
-This directory contains eggs that were downloaded by setuptools to build, test, and run plug-ins.
-
-This directory caches those eggs to prevent repeated downloads.
-
-However, it is safe to delete this directory.
-
diff --git a/CHANGES.txt b/CHANGES.txt
index 581a418..fa5f937 100644
--- a/CHANGES.txt
+++ b/CHANGES.txt
@@ -31,4 +31,5 @@ v0.7.4 Mon Jun 22 -- Fix for setup.py issues
 v0.7.5 Wed Jul 1 -- Public access to sentimentHQ api
 v0.7.6 Tue Jul 7 -- Add Keywords API
 v0.8.0 Fri Jul 10 -- Add Content Filtering API, Named Entities API, Facial Emotion with Localization
-v0.8.1 Wed Fri 22 -- Add Sentiment HQ to predict_text API
+v0.8.1 Wed Jul 22 -- Add Sentiment HQ to predict_text API
+v0.9.0 Tue Jul 28 -- Deprecate batch function calls in favor of type inference
diff --git a/README.md b/README.md
index b90a5ad..f01b5ef 100644
--- a/README.md
+++ b/README.md
@@ -83,11 +83,11 @@ Examples
 
 Batch API
 ---------
-Each `indicoio` function has a corresponding batch function for analyzing many examples with a single request. Simply pass in a list of inputs and receive a list of results in return.
+Each `indicoio` function can process many examples with a single request. Simply pass in a list of inputs and receive a list of results in return.
 ```python
->>> from indicoio import batch_sentiment
+>>> from indicoio import sentiment
 
->>> batch_sentiment(['Best day ever', 'Worst day ever'])
+>>> sentiment(['Best day ever', 'Worst day ever'])
 [0.9899001220871786, 0.005709885173415242]
 ```
 
@@ -101,12 +101,12 @@ Accepted text API names: `text_tags, political, sentiment, language`
 Accepted image API names: `fer, facial_features, image_features`
 
 ```python
->>> from indicoio import predict_text, predict_image, batch_predict_text, batch_predict_image
+>>> from indicoio import predict_text, predict_image, predict_text, predict_image
 
 >>> predict_text('Best day ever', apis=["sentiment", "language"])
 {'sentiment': 0.9899001220871786, 'language': {u'Swedish': 0.0022464881013042294, u'Vietnamese': 9.887170914498351e-05, ...}}
 
->>> batch_predict_text(['Best day ever', 'Worst day ever'], apis=["sentiment", "language"])
+>>> predict_text(['Best day ever', 'Worst day ever'], apis=["sentiment", "language"])
 {'sentiment': [0.9899001220871786, 0.005709885173415242], 'language': [{u'Swedish': 0.0022464881013042294, u'Vietnamese': 9.887170914498351e-05, u'Romanian': 0.00010661175919993216, ...}, {u'Swedish': 0.4924352805804646, u'Vietnamese': 0.028574824174911372, u'Romanian': 0.004185623723173551, u'Dutch': 0.000717033819689362, u'Korean': 0.0030093489153785826, ...}]}
 
 >>> import numpy as np
@@ -116,6 +116,6 @@ Accepted image API names: `fer, facial_features, image_features`
 >>> predict_image(test_face, apis=["fer", "facial_features"])
 {'facial_features': [0.0, -0.026176479280200796, 0.20707644777495776, ...], 'fer': {u'Angry': 0.08877494466353497, u'Sad': 0.3933999409104264, u'Neutral': 0.1910612654566151, u'Surprise': 0.0346146405941845, u'Fear': 0.17682159820518667, u'Happy': 0.11532761017005204}}
 
->>> batch_predict_image([test_face, test_face], apis=["fer", "facial_features"])
+>>> predict_image([test_face, test_face], apis=["fer", "facial_features"])
 {'facial_features': [[0.0, -0.026176479280200796, 0.20707644777495776, ...], [0.0, -0.026176479280200796, 0.20707644777495776, ...]], 'fer': [{u'Angry': 0.08877494466353497, u'Sad': 0.3933999409104264, u'Neutral': 0.1910612654566151, u'Surprise': 0.0346146405941845, u'Fear': 0.17682159820518667, u'Happy': 0.11532761017005204}, { u'Angry': 0.08877494466353497, u'Sad': 0.3933999409104264, u'Neutral': 0.1910612654566151, u'Surprise': 0.0346146405941845, u'Fear': 0.17682159820518667, u'Happy': 0.11532761017005204}]}
 ```
diff --git a/README.rst b/README.rst
index 0ea9ef4..c3cde27 100644
--- a/README.rst
+++ b/README.rst
@@ -91,15 +91,15 @@ Examples
 Batch API
 ---------
 
-Each ``indicoio`` function has a corresponding batch function for
-analyzing many examples with a single request. Simply pass in a list of
-inputs and receive a list of results in return.
+Each ``indicoio`` function can process many examples with a single
+request. Simply pass in a list of inputs and receive a list of results
+in return.
 
 .. code:: python
 
-    >>> from indicoio import batch_sentiment
+    >>> from indicoio import sentiment
 
-    >>> batch_sentiment(['Best day ever', 'Worst day ever'])
+    >>> sentiment(['Best day ever', 'Worst day ever'])
     [0.9899001220871786, 0.005709885173415242]
 
 Calling multiple APIs with a single function
@@ -119,12 +119,12 @@ Accepted image API names: ``fer, facial_features, image_features``
 
 .. code:: python
 
-    >>> from indicoio import predict_text, predict_image, batch_predict_text, batch_predict_image
+    >>> from indicoio import predict_text, predict_image, predict_text, predict_image
 
     >>> predict_text('Best day ever', apis=["sentiment", "language"])
     {'sentiment': 0.9899001220871786, 'language': {u'Swedish': 0.0022464881013042294, u'Vietnamese': 9.887170914498351e-05, ...}}
 
-    >>> batch_predict_text(['Best day ever', 'Worst day ever'], apis=["sentiment", "language"])
+    >>> predict_text(['Best day ever', 'Worst day ever'], apis=["sentiment", "language"])
     {'sentiment': [0.9899001220871786, 0.005709885173415242], 'language': [{u'Swedish': 0.0022464881013042294, u'Vietnamese': 9.887170914498351e-05, u'Romanian': 0.00010661175919993216, ...}, {u'Swedish': 0.4924352805804646, u'Vietnamese': 0.028574824174911372, u'Romanian': 0.004185623723173551, u'Dutch': 0.000717033819689362, u'Korean': 0.0030093489153785826, ...}]}
 
     >>> import numpy as np
@@ -134,6 +134,6 @@ Accepted image API names: ``fer, facial_features, image_features``
     >>> predict_image(test_face, apis=["fer", "facial_features"])
     {'facial_features': [0.0, -0.026176479280200796, 0.20707644777495776, ...], 'fer': {u'Angry': 0.08877494466353497, u'Sad': 0.3933999409104264, u'Neutral': 0.1910612654566151, u'Surprise': 0.0346146405941845, u'Fear': 0.17682159820518667, u'Happy': 0.11532761017005204}}
 
-    >>> batch_predict_image([test_face, test_face], apis=["fer", "facial_features"])
+    >>> predict_image([test_face, test_face], apis=["fer", "facial_features"])
     {'facial_features': [[0.0, -0.026176479280200796, 0.20707644777495776, ...], [0.0, -0.026176479280200796, 0.20707644777495776, ...]], 'fer': [{u'Angry': 0.08877494466353497, u'Sad': 0.3933999409104264, u'Neutral': 0.1910612654566151, u'Surprise': 0.0346146405941845, u'Fear': 0.17682159820518667, u'Happy': 0.11532761017005204}, { u'Angry': 0.08877494466353497, u'Sad': 0.3933999409104264, u'Neutral': 0.1910612654566151, u'Surprise': 0.0346146405941845, u'Fear': 0.17682159820518667, u'Happy': 0.11532761017005204}]}
 
diff --git a/indicoio/__init__.py b/indicoio/__init__.py
index 8bfa3e3..1225c9c 100644
--- a/indicoio/__init__.py
+++ b/indicoio/__init__.py
@@ -1,7 +1,7 @@
 from functools import wraps, partial
 import warnings
 
-Version, version, __version__, VERSION = ('0.8.1',) * 4
+Version, version, __version__, VERSION = ('0.9.0',) * 4
 
 JSON_HEADERS = {
     'Content-type': 'application/json',
diff --git a/setup.py b/setup.py
index b34cec7..cbdc19d 100644
--- a/setup.py
+++ b/setup.py
@@ -9,7 +9,7 @@ except ImportError:
 
 setup(
     name="IndicoIo",
-    version="0.8.1",
+    version="0.9.0",
     packages=[
         "indicoio",
         "indicoio.text",