'turn selective search proposals into selective search roidb
:param gt_roidb: [image_index][\'boxes\', \'gt_classes\', \'gt_overlaps\', \'flipped\']
:return: roidb: [image_index][\'boxes\', \'gt_classes\', \'gt_overlaps\', \'flipped\']'

def load_selective_search_roidb(self, gt_roidb):

    import scipy.io
    matfile = os.path.join(self.root_path, 'selective_search_data', (self.name + '.mat'))
    assert os.path.exists(matfile), 'selective    search    data    does    not    exist:    {}'.format(matfile)
    raw_data = scipy.io.loadmat(matfile)['boxes'].ravel()
    box_list = []
    for i in range(raw_data.shape[0]):
        boxes = (raw_data[i][:, (1, 0, 3, 2)] - 1)
        keep = unique_boxes(boxes)
        boxes = boxes[keep, :]
        keep = filter_small_boxes(boxes, self.config['min_size'])
        boxes = boxes[keep, :]
        box_list.append(boxes)
    return self.create_roidb_from_box_list(box_list, gt_roidb)
