Add align_dlib.align for backwards compatibility.

openface/align_dlib.py

@@ -146,6 +146,39 @@ def findLandmarks(self, rgbImg, bb):
         points = self.predictor(rgbImg, bb)
         return list(map(lambda p: (p.x, p.y), points.parts()))
 
+    def align(self, imgDim, rgbImg, bb=None,
+              landmarks=None, landmarkIndices=INNER_EYES_AND_BOTTOM_LIP,
+              skipMulti=False, version=1):
+        r"""align(imgDim, rgbImg, bb=None, landmarks=None, landmarkIndices=INNER_EYES_AND_BOTTOM_LIP, version=1)
+
+        Transform and align a face in an image.
+
+        :param imgDim: The edge length in pixels of the square the image is resized to.
+        :type imgDim: int
+        :param rgbImg: RGB image to process. Shape: (height, width, 3)
+        :type rgbImg: numpy.ndarray
+        :param bb: Bounding box around the face to align. \
+                   Defaults to the largest face.
+        :type bb: dlib.rectangle
+        :param landmarks: Detected landmark locations. \
+                          Landmarks found on `bb` if not provided.
+        :type landmarks: list of (x,y) tuples
+        :param landmarkIndices: The indices to transform to.
+        :type landmarkIndices: list of ints
+        :param skipMulti: Skip image if more than one face detected.
+        :type skipMulti: bool
+        :param version: int
+        :return: The aligned RGB image. Shape: (imgDim, imgDim, 3)
+        :rtype: numpy.ndarray
+        """
+
+        if version == 1:
+            self.align_v1(imgDim, rgbImg, bb, landmarks, landmarkIndices, skipMulti)
+        elif version == 2:
+            self.align_v2(imgDim, rgbImg, bb, landmarks, landmarkIndices, skipMulti)
+        else:
+            assert False
+
     def align_v1(self, imgDim, rgbImg, bb=None,
                  landmarks=None, landmarkIndices=INNER_EYES_AND_BOTTOM_LIP,
                  skipMulti=False):