          -------
          list
              List of cropped images for the batch
          """
          logger.debug("Cropping images")
          batch_shape = center_scale.shape[:2]
          resolutions = np.full(batch_shape, self.input_size, dtype='float32')
          matrix_ones = np.ones(batch_shape + (3,), dtype='float32')
          matrix_size = np.full(batch_shape + (3,), self.input_size, dtype='float32')
          matrix_size[..., 2] = 1.0
 
</s> remove         logger.trace("Calculating center and scale")  # type:ignore
 </s> add         logger.trace("Calculating center and scale")  # type:ignore[attr-defined] </s> remove         logger.debug("Transforming Points")
 </s> add         logger.trace("Transforming Points")  # type:ignore[attr-defined] </s> remove         logger.trace("Calculated center and scale: %s", center_scale)  # type:ignore
 </s> add         logger.trace("Calculated center and scale: %s", center_scale)  # type:ignore[attr-defined] </s> remove         logger.trace("Obtain points from prediction")  # type:ignore
 </s> add         logger.trace("Obtain points from prediction")  # type:ignore[attr-defined] </s> remove         logger.trace("Transformed Points: %s", retval)  # type:ignore
 </s> add         logger.trace("Transformed Points: %s", retval)  # type:ignore[attr-defined]
        logger.trace("Cropping images")  # type:ignore[attr-defined]
          -------
          list
              List of cropped images for the batch
          """
        logger.trace("Cropping images")  # type:ignore[attr-defined]
          batch_shape = center_scale.shape[:2]
          resolutions = np.full(batch_shape, self.input_size, dtype='float32')
          matrix_ones = np.ones(batch_shape + (3,), dtype='float32')
          matrix_size = np.full(batch_shape + (3,), self.input_size, dtype='float32')
          matrix_size[..., 2] = 1.0
keep keep keep keep replace keep keep keep keep keep
 Bugfix - Extract - re-align with identity filtering enabled 
plugins/extract/align/fan.py