Performing inference with NCNN

ncnnInference.cpp

#include <iostream>
#include "ncnn/net.h"
#include "opencv2/opencv.hpp"

void normalize(std::vector<float>& arr) {
    double mod = 0.0;

    for (float i : arr) {
        mod += i * i;
    }

    double mag = std::sqrt(mod);

    if (mag == 0) {
        throw std::logic_error("The input vector is a zero vector");
    }

    for (float & i : arr) {
        i /= mag;
    }
}

double getSimilarity(const std::vector<float>& v1, const std::vector<float>& v2) {
    if (v1.size() != v2.size())
        throw std::invalid_argument("Wrong size");

    double mul = 0;
    for (size_t i = 0; i < v1.size(); ++i) {
        mul += v1[i] * v2[i];
    }

    if (mul < 0) {
        return 0;
    }

    return mul;
}

std::vector<float> getTemplate(const std::string& imagePath, ncnn::Net& net) {
    cv::Mat data = cv::imread(imagePath);
    ncnn::Mat in = ncnn::Mat::from_pixels(data.data, ncnn::Mat::PIXEL_RGB, data.cols, data.rows);
    ncnn::Extractor ex = net.create_extractor();
    ex.input("data", in);
    ncnn::Mat out;
    ex.extract("fc1", out);
    std::vector<float> vec;
    for (int i = 0; i < out.w; ++i) {
        vec.emplace_back(*(static_cast<float*>(out.data) + i));
    }
    normalize(vec);
    return vec;
}

int main() {
    ncnn::Net net;
    net.load_param("../models/ncnn.param");
    net.load_model("../models/ncnn.bin");

    // Two images of the same person
    const std::string person1imgAPath = "../images/chip1.jpg";
    const std::string person1imgBPath = "../images/chip2.jpg";

    // One image of a different person
    const std::string person2imgPath = "../images/chip17.jpg";

    const auto person1ATempl = getTemplate(person1imgAPath, net);
    const auto person1BTempl = getTemplate(person1imgBPath, net);
    const auto person2Templ = getTemplate(person2imgPath, net);

    // Get score for two images of the same person
    const auto scoreSimilar = getSimilarity(person1ATempl, person1BTempl);
    std::cout << "Similarity score: " << scoreSimilar << "\n";

    // Get score for two images of different people
    const auto scoreDissimilar = getSimilarity(person1ATempl, person2Templ);
    std::cout << "Similarity score: " << scoreDissimilar << "\n";
    
    return 0;
}