Don't choke on images that use 32 bits per channel. Downsample them.

face_recognition/api.py

@@ -44,14 +44,15 @@ def _face_distance(faces, face_to_compare):
     return np.array([np.linalg.norm(face - face_to_compare) for face in faces])
 
 
-def load_image_file(filename):
+def load_image_file(filename, mode='RGB'):
     """
     Loads an image file (.jpg, .png, etc) into a numpy array
 
     :param filename: image file to load
+    :param mode: format to convert the image to. Only 'RGB' (8-bit RGB, 3 channels) and 'L' (black and white) are supported.
     :return: image contents as numpy array
     """
-    return scipy.misc.imread(filename)
+    return scipy.misc.imread(filename, mode=mode)
 
 
 def _raw_face_locations(img, number_of_times_to_upsample=1):

tests/test_face_recognition.py

@@ -21,9 +21,12 @@ class Test_face_recognition(unittest.TestCase):
 
     def test_load_image_file(self):
         img = api.load_image_file(os.path.join(os.path.dirname(__file__), "test_images", "obama.jpg"))
-
         assert img.shape == (1137, 910, 3)
 
+    def test_load_image_file_32bit(self):
+        img = api.load_image_file(os.path.join(os.path.dirname(__file__), "test_images", "32bit.png"))
+        assert img.shape == (1200, 626, 3)
+
     def test_raw_face_locations(self):
         img = api.load_image_file(os.path.join(os.path.dirname(__file__), "test_images", "obama.jpg"))
         detected_faces = api._raw_face_locations(img)
@@ -32,6 +35,14 @@ class Test_face_recognition(unittest.TestCase):
         assert detected_faces[0].top() == 142
         assert detected_faces[0].bottom() == 409
 
+    def test_raw_face_locations_32bit_image(self):
+        img = api.load_image_file(os.path.join(os.path.dirname(__file__), "test_images", "32bit.png"))
+        detected_faces = api._raw_face_locations(img)
+
+        assert len(detected_faces) == 1
+        assert detected_faces[0].top() == 290
+        assert detected_faces[0].bottom() == 558
+
     def test_face_locations(self):
         img = api.load_image_file(os.path.join(os.path.dirname(__file__), "test_images", "obama.jpg"))
         detected_faces = api.face_locations(img)