def METHOD_NAME(index, pascal_root):
    """
    This code is borrowed from Ross Girshick's FAST-RCNN code
    (https://github.com/rbgirshick/fast-rcnn).
    It parses the PASCAL .xml metadata files.
    See publication for further details: (http://arxiv.org/abs/1504.08083).
    Thanks Ross!
    """
    classes = ('__background__',  # always index 0
               'aeroplane', 'bicycle', 'bird', 'boat',
               'bottle', 'bus', 'car', 'cat', 'chair',
                         'cow', 'diningtable', 'dog', 'horse',
                         'motorbike', 'person', 'pottedplant',
                         'sheep', 'sofa', 'train', 'tvmonitor')
    class_to_ind = dict(zip(classes, xrange(21)))
    filename = osp.join(pascal_root, 'Annotations', index + '.xml')
    # print 'Loading: {}'.format(filename)
    def get_data_from_tag(node, tag):
        return node.getElementsByTagName(tag)[0].childNodes[0].data
    with open(filename) as f:
        data = minidom.parseString(f.read())
    objs = data.getElementsByTagName('object')
    num_objs = len(objs)
    boxes = np.zeros((num_objs, 4), dtype=np.uint16)
    gt_classes = np.zeros((num_objs), dtype=np.int32)
    overlaps = np.zeros((num_objs, 21), dtype=np.float32)
    # Load object bounding boxes into a data frame.
    for ix, obj in enumerate(objs):
        # Make pixel indexes 0-based
        x1 = float(get_data_from_tag(obj, 'xmin')) - 1
        y1 = float(get_data_from_tag(obj, 'ymin')) - 1
        x2 = float(get_data_from_tag(obj, 'xmax')) - 1
        y2 = float(get_data_from_tag(obj, 'ymax')) - 1
        cls = class_to_ind[
            str(get_data_from_tag(obj, "name")).lower().strip()]
        boxes[ix, :] = [x1, y1, x2, y2]
        gt_classes[ix] = cls
        overlaps[ix, cls] = 1.0
    overlaps = scipy.sparse.csr_matrix(overlaps)
    return {'boxes': boxes,
            'gt_classes': gt_classes,
            'gt_overlaps': overlaps,
            'flipped': False,
            'index': index}