                  logger.trace("Faces found for all images")  # type:ignore
                  break
  
          batch.prediction = np.array(found_faces, dtype="object")
          logger.trace("detect_prediction output: (filenames: %s, prediction: %s, "  # type:ignore
                       "rotmat: %s)", batch.filename, batch.prediction, batch.rotation_matrix)
          return batch
  
      # <<< DETECTION IMAGE COMPILATION METHODS >>> #
      def _compile_detection_image(self, item: ExtractMedia
                                   ) -> Tuple[np.ndarray, float, Tuple[int, int]]:
 
</s> remove                 logger.trace("Faces found for all images")  # type:ignore
 </s> add                 logger.trace("Faces found for all images")  # type:ignore[attr-defined] </s> remove         logger.trace("Padded image shape: %s", image.shape)  # type:ignore
 </s> add         logger.trace("Padded image shape: %s", image.shape)  # type:ignore[attr-defined] </s> remove                 batch.prediction = self.predict(batch.feed)
                logger.trace("angle: %s, filenames: %s, prediction: %s",  # type:ignore
                             angle, batch.filename, batch.prediction)
 </s> add                 pred = self.predict(batch.feed)
                if angle == 0:
                    batch.prediction = pred
                else:
                    batch.prediction = np.array([b if b.any() else p
                                                 for b, p in zip(batch.prediction, pred)])
                logger.trace("angle: %s, filenames: %s, "  # type:ignore[attr-defined]
                             "prediction: %s",
                             angle, batch.filename, pred) </s> remove             logger.trace("final output: (filename: '%s', image shape: %s, "  # type:ignore
                         "detected_faces: %s, item: %s", output.filename, output.image_shape,
                         output.detected_faces, output)
 </s> add             logger.trace("final output: (filename: '%s', "  # type:ignore[attr-defined]
                         "image shape: %s, detected_faces: %s, item: %s",
                         output.filename, output.image_shape, output.detected_faces, output) </s> remove         logger.trace("compiled: (images shape: %s, scale: %s, pad: %s)",  # type:ignore
 </s> add         logger.trace("compiled: (images shape: %s, "  # type:ignore[attr-defined]
                     "scale: %s, pad: %s)",
        logger.trace("detect_prediction output: (filenames: %s, "  # type:ignore[attr-defined]
                     "prediction: %s, rotmat: %s)",
                     batch.filename, batch.prediction, batch.rotation_matrix)
                  logger.trace("Faces found for all images")  # type:ignore
                  break
  
          batch.prediction = np.array(found_faces, dtype="object")
        logger.trace("detect_prediction output: (filenames: %s, "  # type:ignore[attr-defined]
                     "prediction: %s, rotmat: %s)",
                     batch.filename, batch.prediction, batch.rotation_matrix)
        logger.trace("detect_prediction output: (filenames: %s, "  # type:ignore[attr-defined]
                     "prediction: %s, rotmat: %s)",
                     batch.filename, batch.prediction, batch.rotation_matrix)
          return batch
  
      # <<< DETECTION IMAGE COMPILATION METHODS >>> #
      def _compile_detection_image(self, item: ExtractMedia
                                   ) -> Tuple[np.ndarray, float, Tuple[int, int]]:
keep keep keep keep replace replace keep keep keep keep keep
 bugfix: Extract - rotation in detection 
plugins/extract/detect/_base.py