'Load the indexes listed in this dataset\'s image set file.'

def _load_image_set_index(self):

    kitti_train_nums = [154, 447, 233, 144, 314, 297, 270, 800, 390, 803, 294, 373, 78, 340, 106, 376, 209, 145, 339, 1059, 837]
    kitti_test_nums = [465, 147, 243, 257, 421, 809, 114, 215, 165, 349, 1176, 774, 694, 152, 850, 701, 510, 305, 180, 404, 173, 203, 436, 430, 316, 176, 170, 85, 175]
    if ((self._seq_name == 'train') or (self._seq_name == 'trainval')):
        assert (self._image_set == 'training'), 'Use    train    set    or    trainval    set    in    testing'
        if (self._seq_name == 'train'):
            seq_index = [0, 1, 2, 3, 4, 5, 12, 13, 14, 15, 16]
        else:
            seq_index = range(0, 21)
        image_index = []
        for i in xrange(len(seq_index)):
            seq_idx = seq_index[i]
            num = kitti_train_nums[seq_idx]
            for j in xrange(num):
                image_index.append('{:04d}/{:06d}'.format(seq_idx, j))
    else:
        seq_num = int(self._seq_name)
        if (self._image_set == 'training'):
            num = kitti_train_nums[seq_num]
        else:
            num = kitti_test_nums[seq_num]
        image_index = []
        for i in xrange(num):
            image_index.append('{:04d}/{:06d}'.format(seq_num, i))
    return image_index
