  
          if rotation.lower() == "on":
              rotation_angles.extend(range(90, 360, 90))
          else:
              passed_angles = [int(angle)
                               for angle in rotation.split(",")]
              if len(passed_angles) == 1:
                  rotation_step_size = passed_angles[0]
                  rotation_angles.extend(range(rotation_step_size,
                                               360,
                                               rotation_step_size))
 
</s> remove         if scale == 1.0:
            return image

 </s> add  </s> remove                     predicted = self.predict(feed_faces)
 </s> add                     batch_size = None
                    if is_plaidml and feed_faces.shape[0] != self.batchsize:
                        logger.verbose("Fallback to BS=1")
                        batch_size = 1
                    predicted = self.predict(feed_faces, batch_size) </s> remove     def scale_image(image, scale):
        """ Scale the image """
 </s> add     def scale_image(image, scale, pad_to=None):
        """ Scale the image and optional pad to given size """ </s> remove         predicted = self.predictor(feed)
 </s> add         predicted = self.predictor(feed, batch_size=batch_size) </s> remove         dims = (int(width * scale), int(height * scale))

        if scale < 1.0:
            logger.trace("Resizing image from %sx%s to %s.",
                         width, height, "x".join(str(i) for i in dims))
 </s> add         if scale != 1.0:
            dims = (int(width * scale), int(height * scale))
            if scale < 1.0:
                logger.verbose("Resizing image from %sx%s to %s. Scale=%s",
                               width, height, "x".join(str(i) for i in dims), scale)
            image = cv2.resize(image, dims, interpolation=interpln)
        if pad_to:
            image = Detector.pad_image(image, pad_to)
        return image
            passed_angles = [
                int(angle)
                for angle in rotation.split(",")
                if int(angle) != 0
            ]
  
          if rotation.lower() == "on":
              rotation_angles.extend(range(90, 360, 90))
          else:
            passed_angles = [
                int(angle)
                for angle in rotation.split(",")
                if int(angle) != 0
            ]
            passed_angles = [
                int(angle)
                for angle in rotation.split(",")
                if int(angle) != 0
            ]
              if len(passed_angles) == 1:
                  rotation_step_size = passed_angles[0]
                  rotation_angles.extend(range(rotation_step_size,
                                               360,
                                               rotation_step_size))
keep keep keep keep replace replace keep keep keep keep keep
 Added s3fd-amd + minor fixes (#837) 
plugins/extract/detect/_base.py