ADD: basic min axis content resizing

.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.
+

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)

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

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):

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))