Is it possible to get multiple prediction from FaceRecognizer

edit

I modified the predict functions from LBPH part (the same code can be applied to eigenfaces and fisherfaces parts):

    void LBPH::predict(InputArray _src, std::vector<int> &minClass, std::vector<double> &minDist, int maxN) const {
    if (_histograms.empty()) {
        // throw error if no data (or simply return -1?)
        String error_message = "This LBPH model is not computed yet. Did you call the train method?";
        CV_Error(Error::StsBadArg, error_message);
    }
    Mat src = _src.getMat();
    // get the spatial histogram from input image
    Mat lbp_image = elbp(src, _radius, _neighbors);
    Mat query = spatial_histogram(
        lbp_image, /* lbp_image */
        static_cast<int>(std::pow(2.0, static_cast<double>(_neighbors))), /* number of possible patterns */
        _grid_x, /* grid size x */
        _grid_y, /* grid size y */
        true /* normed histograms */);

    // find first maxN nearest neighbors
    // using priority for keeping maxN min distances and maxN min classes
    // remember to include queue header file and algorithm for greater<double>
    std::priority_queue<double, std::vector<double>, std::greater<double>> minDist1;
    std::priority_queue<int, std::vector<int>, std::greater<int>> minClass1;

    for (size_t sampleIdx = 0; sampleIdx < _histograms.size(); sampleIdx++) {
        double dist = compareHist(_histograms[sampleIdx], query, HISTCMP_CHISQR_ALT);
        if (dist < _threshold)
        {
            if (minDist1.size() < maxN)
            {
                minDist1.push(dist);
                minClass1.push(_labels.at<int>((int)sampleIdx));
            }
            else if (dist < minDist1.top())
            {
                minDist1.pop();
                minClass1.pop();
                minDist1.push(dist);
                minClass1.push(_labels.at<int>((int)sampleIdx));
            }
        }
    }
    minDist = std::vector<double>(minDist1.size());
    minClass = std::vector<int>(minClass1.size());
    // storing the results back to vector objects
    while (!minDist1.empty())
    {
        minDist.emplace_back(minDist1.top());
        minClass.emplace_back(minClass1.top());
        minDist1.pop();
        minClass1.pop();
    }
}

std::vector<std::pair<int, double>> LBPH::predict(InputArray _src, int maxN) const {
    std::vector<int> label;
    std::vector<double> weight;
    predict(_src, label, weight, maxN);
    std::vector<std::pair<int, double>> result(label.size());
    for (int i = 0; i < label.size(); i++)
        result[i] = std::make_pair(label[i], weight[i]);
    return result;
}

Hope this helps.