def reset_class(self, classes, reuse_weights=None):
        """Reset class categories and class predictors.

        Parameters
        ----------
        classes : iterable of str
            The new categories. ['apple', 'orange'] for example.
        reuse_weights : dict
            A {new_integer : old_integer} or mapping dict or {new_name : old_name} mapping dict,
            or a list of [name0, name1,...] if class names don't change.
            This allows the new predictor to reuse the
            previously trained weights specified.

        Example
        -------
        >>> net = gluoncv.model_zoo.get_model('faster_rcnn_resnet50_v1b_coco', pretrained=True)
        >>> # use direct name to name mapping to reuse weights
        >>> net.reset_class(classes=['person'], reuse_weights={'person':'person'})
        >>> # or use interger mapping, person is the 14th category in VOC
        >>> net.reset_class(classes=['person'], reuse_weights={0:14})
        >>> # you can even mix them
        >>> net.reset_class(classes=['person'], reuse_weights={'person':14})
        >>> # or use a list of string if class name don't change
        >>> net.reset_class(classes=['person'], reuse_weights=['person'])

        """
        super(FasterRCNN, self).reset_class(classes, reuse_weights)
        self._target_generator = RCNNTargetGenerator(
            self.num_class, self.sampler._max_pos, self._batch_size
        )
Reset class categories and class predictors.

        Parameters
        ----------
        classes : iterable of str
            The new categories. ['apple', 'orange'] for example.
        reuse_weights : dict
            A {new_integer : old_integer} or mapping dict or {new_name : old_name} mapping dict,
            or a list of [name0, name1,...] if class names don't change.
            This allows the new predictor to reuse the
            previously trained weights specified.

        Example
        -------
        >>> net = gluoncv.model_zoo.get_model('faster_rcnn_resnet50_v1b_coco', pretrained=True)
        >>> # use direct name to name mapping to reuse weights
        >>> net.reset_class(classes=['person'], reuse_weights={'person':'person'})
        >>> # or use interger mapping, person is the 14th category in VOC
        >>> net.reset_class(classes=['person'], reuse_weights={0:14})
        >>> # you can even mix them
        >>> net.reset_class(classes=['person'], reuse_weights={'person':14})
        >>> # or use a list of string if class name don't change
        >>> net.reset_class(classes=['person'], reuse_weights=['person'])

        
examples/mxnet/scenegraph/model/faster_rcnn.py