Add checks for 'None' to resolve #25.

openface/align_dlib.py

@@ -85,6 +85,9 @@ class AlignDlib:
         :param facePredictor: The path to dlib's
         :type facePredictor: str
         """
+
+        assert facePredictor is not None
+
         self.detector = dlib.get_frontal_face_detector()
         self.predictor = dlib.shape_predictor(facePredictor)
 
@@ -97,6 +100,9 @@ class AlignDlib:
         :return: All face bounding boxes in an image.
         :rtype: dlib.rectangles
         """
+
+        assert rgbImg is not None
+
         try:
             return self.detector(rgbImg, 1)
         except Exception as e:
@@ -113,6 +119,9 @@ class AlignDlib:
         :return: The largest face bounding box in an image, or None.
         :rtype: dlib.rectangle
         """
+
+        assert rgbImg is not None
+
         faces = self.getAllFaceBoundingBoxes(rgbImg)
         if len(faces) > 0:
             return max(faces, key=lambda rect: rect.width() * rect.height())
@@ -130,6 +139,10 @@ class AlignDlib:
         :return: Detected landmark locations.
         :rtype: list of (x,y) tuples
         """
+
+        assert rgbImg is not None
+        assert bb is not None
+
         points = self.predictor(rgbImg, bb)
         return list(map(lambda p: (p.x, p.y), points.parts()))
 
@@ -154,6 +167,11 @@ class AlignDlib:
         :return: The aligned RGB image. Shape: (imgDim, imgDim, 3)
         :rtype: numpy.ndarray
         """
+
+        assert imgDim is not None
+        assert rgbImg is not None
+        assert landmarkIndices is not None
+
         if bb is None:
             bb = self.getLargestFaceBoundingBox(rgbImg)
             if bb is None:

openface/data.py

@@ -35,6 +35,11 @@ class Image:
         :param path: Path to the image on disk.
         :type path: str
         """
+
+        assert cls is not None
+        assert name is not None
+        assert path is not None
+
         self.cls = cls
         self.name = name
         self.path = path
@@ -98,6 +103,9 @@ def iterImgs(directory):
     :type directory: str
     :return: An iterator over Image objects.
     """
+
+    assert directory is not None
+
     exts = [".jpg", ".png"]
 
     for subdir, dirs, files in os.walk(directory):

openface/helper.py

@@ -13,6 +13,9 @@ def mkdirP(path):
     :param path: The directory to create.
     :type path: str
     """
+
+    assert path is not None
+
     try:
         os.makedirs(path)
     except OSError as exc:  # Python >2.5

openface/torch_neural_net.py

@@ -53,6 +53,11 @@ class TorchNeuralNet:
         :param cuda: Flag to use CUDA in the subprocess.
         :type cuda: bool
         """
+
+        assert model is not None
+        assert imgDim is not None
+        assert cuda is not None
+
         self.cmd = ['/usr/bin/env', 'th', os.path.join(myDir, 'openface_server.lua'),
                     '-model', model, '-imgDim', str(imgDim)]
         if cuda:
@@ -74,6 +79,9 @@ class TorchNeuralNet:
         :return: Vector of features extracted with the neural network.
         :rtype: numpy.ndarray
         """
+
+        assert imgPath is not None
+
         rc = self.p.poll()
         if rc is not None and rc != 0:
             raise Exception("""
@@ -134,8 +142,9 @@ stderr: {}
         :return: Vector of features extracted from the neural network.
         :rtype: numpy.ndarray
         """
-        if rgbImg is None:
+
-            raise Exception("rgbImg=None passed into forward")
+        assert rgbImg is not None
+
         t = '/tmp/openface-torchwrap-{}.png'.format(
             binascii.b2a_hex(os.urandom(8)))
         bgrImg = cv2.cvtColor(rgbImg, cv2.COLOR_RGB2BGR)