      @staticmethod
      def get_pts_from_predict(batch):
          """ Get points from predictor """
          for prediction, roi in zip(batch["prediction"], batch["roi"]):
              points = np.array(prediction).flatten()
              points = np.reshape(points, (-1, 2))
              points *= (roi[2] - roi[0])
              points[:, 0] += roi[0]
              points[:, 1] += roi[1]
              batch.setdefault("landmarks", []).append(points)
          logger.trace("Predicted Landmarks: %s", batch["landmarks"])
 
</s> remove             right += abs(left)
            left += abs(left)
 </s> add             shift_right = abs(left)
            right += shift_right
            left += shift_right </s> remove                 batch[idx, ...] = cv2.resize(images[idx, ...],  # pylint:disable=no-member
                                             (rwidth, rheight))
 </s> add                 batch[idx, ...] = cv2.resize(images[idx, ...], (rwidth, rheight)) </s> remove         rotation_matrix = cv2.getRotationMatrix2D(  # pylint: disable=no-member
            image_center, -1.*angle, 1.)
 </s> add         rotation_matrix = cv2.getRotationMatrix2D(image_center, -1.*angle, 1.) </s> remove         image = cv2.warpAffine(image,  # pylint: disable=no-member
                               rotation_matrix,
                               (self.input_size, self.input_size))
 </s> add         image = cv2.warpAffine(image, rotation_matrix, (self.input_size, self.input_size)) </s> remove             bottom += abs(top)
            top += abs(top)
 </s> add             shift_down = abs(top)
            bottom += shift_down
            top += shift_down
            points = np.reshape(prediction, (-1, 2))
      @staticmethod
      def get_pts_from_predict(batch):
          """ Get points from predictor """
          for prediction, roi in zip(batch["prediction"], batch["roi"]):
            points = np.reshape(prediction, (-1, 2))
            points = np.reshape(prediction, (-1, 2))
              points *= (roi[2] - roi[0])
              points[:, 0] += roi[0]
              points[:, 1] += roi[1]
              batch.setdefault("landmarks", []).append(points)
          logger.trace("Predicted Landmarks: %s", batch["landmarks"])
keep keep keep keep replace replace keep keep keep keep keep
 # pylint:disable=no-member cleanup (#927)

# pylint:disable=no-member cleanup 
plugins/extract/align/cv2_dnn.py