          """ Return the cv2 DNN backend """
          if backend == "OPENCL":
              logger.info("Using OpenCL backend. If the process runs, you can safely ignore any of "
                          "the failure messages.")
          retval = getattr(cv2.dnn, "DNN_TARGET_{}".format(backend))  # pylint: disable=no-member
          return retval
  
      def predict(self, face):
          """ Return encodings for given image from vgg_face """
          if face.shape[0] != self.input_size:
 
</s> remove         blob = cv2.dnn.blobFromImage(face[..., :3],  # pylint: disable=no-member
 </s> add         blob = cv2.dnn.blobFromImage(face[..., :3], </s> remove         if face.shape[0] < self.input_size:
            interpolation = cv2.INTER_CUBIC  # pylint:disable=no-member
        else:
            interpolation = cv2.INTER_AREA  # pylint:disable=no-member

        face = cv2.resize(face,  # pylint:disable=no-member
                          dsize=(self.input_size, self.input_size),
                          interpolation=interpolation)
 </s> add         sizes = (self.input_size, self.input_size)
        interpolation = cv2.INTER_CUBIC if face.shape[0] < self.input_size else cv2.INTER_AREA
        face = cv2.resize(face, dsize=sizes, interpolation=interpolation) </s> remove         if face.shape[0] < self.input_size:
            interpolation = cv2.INTER_CUBIC  # pylint:disable=no-member
        else:
            interpolation = cv2.INTER_AREA  # pylint:disable=no-member

        face = cv2.resize(face,  # pylint:disable=no-member
                          dsize=(self.input_size, self.input_size),
                          interpolation=interpolation)
 </s> add         sizes = (self.input_size, self.input_size)
        interpolation = cv2.INTER_CUBIC if face.shape[0] < self.input_size else cv2.INTER_AREA
        face = cv2.resize(face, dsize=sizes, interpolation=interpolation) </s> remove         interpln = cv2.INTER_CUBIC if scale > 1.0 else cv2.INTER_AREA  # pylint:disable=no-member
 </s> add         interpln = cv2.INTER_CUBIC if scale > 1.0 else cv2.INTER_AREA </s> remove                                     cv2.BORDER_CONSTANT,  # pylint: disable=no-member
 </s> add                                     cv2.BORDER_CONSTANT,
        retval = getattr(cv2.dnn, "DNN_TARGET_{}".format(backend))
          """ Return the cv2 DNN backend """
          if backend == "OPENCL":
              logger.info("Using OpenCL backend. If the process runs, you can safely ignore any of "
                          "the failure messages.")
        retval = getattr(cv2.dnn, "DNN_TARGET_{}".format(backend))
          return retval
  
      def predict(self, face):
          """ Return encodings for given image from vgg_face """
          if face.shape[0] != self.input_size:
keep keep keep keep replace keep keep keep keep keep
 # pylint:disable=no-member cleanup (#927)

# pylint:disable=no-member cleanup 
lib/vgg_face.py