vehicle-demo/test/yolov5.cpp

#include <iostream>
#include <opencv2/opencv.hpp>
#include <opencv2/dnn/dnn.hpp>
#include <string>
#include <vector>

using cv::Mat;
using std::cout;
using std::endl;
using std::string;
using std::vector;

static const vector<string> class_name = { "cat", "chicken", "cow", "dog", "fox", "goat", "horse", "person", "racoon", "skunk" };

vector<vector<float>> get_info(const Mat& result, float conf = 0.7, int len_data = 15)
{
    float* pdata = (float*)result.data;
    vector<vector<float>> info;
    for (int i = 0; i < result.total() / len_data; i++)
    {
        if (pdata[4] > conf)
        {
            vector<float> info_line;
            for (int j = 0; j < len_data; j++)
            {
                // cout << pdata[j] << " ";
                info_line.push_back(pdata[j]);
            }
            // cout << endl;
            info.push_back(info_line);
        }
        pdata += len_data;
    }
    return info;
}

void info_simplify(vector<vector<float>>& info)
{
    for (auto i = 0; i < info.size(); i++)
    {
        info[i][5] = std::max_element(info[i].cbegin() + 5, info[i].cend()) - (info[i].cbegin() + 5);
        info[i].resize(6);
        float x = info[i][0];
        float y = info[i][1];
        float w = info[i][2];
        float h = info[i][3];
        info[i][0] = x - w / 2.0;
        info[i][1] = y - h / 2.0;
        info[i][2] = x + w / 2.0;
        info[i][3] = y + h / 2.0;
    }
}

vector<vector<vector<float>>> split_info(vector<vector<float>>& info)
{
    vector<vector<vector<float>>> info_split;
    vector<int> class_id;
    for (auto i = 0; i < info.size(); i++)
    {
        if (std::find(class_id.begin(), class_id.end(), (int)info[i][5]) == class_id.end())
        {
            class_id.push_back((int)info[i][5]);
            vector<vector<float>> info_;
            info_split.push_back(info_);
        }
        info_split[std::find(class_id.begin(), class_id.end(), (int)info[i][5]) - class_id.begin()].push_back(info[i]);
    }
    return info_split;
}

void nms(vector<vector<float>>& info, float iou = 0.4)
{
    int counter = 0;
    vector<vector<float>> return_info;
    while (counter < info.size())
    {
        return_info.clear();
        float x1 = 0;
        float x2 = 0;
        float y1 = 0;
        float y2 = 0;
        std::sort(info.begin(), info.end(), [](vector<float> p1, vector<float> p2)
            { return p1[4] > p2[4]; });
        for (auto i = 0; i < info.size(); i++)
        {
            if (i < counter)
            {
                return_info.push_back(info[i]);
                continue;
            }
            if (i == counter)
            {
                x1 = info[i][0];
                y1 = info[i][1];
                x2 = info[i][2];
                y2 = info[i][3];
                return_info.push_back(info[i]);
                continue;
            }
            if (info[i][0] > x2 or info[i][2] < x1 or info[i][1] > y2 or info[i][3] < y1)
            {
                return_info.push_back(info[i]);
            }
            else
            {
                float over_x1 = std::max(x1, info[i][0]);
                float over_y1 = std::max(y1, info[i][1]);
                float over_x2 = std::min(x2, info[i][2]);
                float over_y2 = std::min(y2, info[i][3]);
                float s_over = (over_x2 - over_x1) * (over_y2 - over_y1);
                float s_total = (x2 - x1) * (y2 - y1) + (info[i][0] - info[i][2]) * (info[i][1] - info[i][3]) - s_over;
                if (s_over / s_total < iou)
                {
                    return_info.push_back(info[i]);
                }
            }
        }
        info = return_info;
        counter += 1;
    }
}

void draw_box(Mat& img, const vector<vector<float>>& info)
{
    for (int i = 0; i < info.size(); i++)
    {
        cv::Point topLeft(info[i][0], info[i][1]);
        cv::Point bottomRight(info[i][2], info[i][3]);
        int thickness = 2;
        cv::Scalar color(0, 255, 0);
        int lineType = cv::LINE_8;
        const int cornerRadius = 5;
        cv::rectangle(img, topLeft, bottomRight, color, thickness, lineType);
        string label = class_name[static_cast<int>(info[i][5])] + " " + std::to_string(info[i][4]);
        cv::Size textSize = cv::getTextSize(label, cv::FONT_HERSHEY_SIMPLEX, 0.6, 1, nullptr);
        cv::Rect textBgRect(topLeft.x, topLeft.y - textSize.height - 5, textSize.width + 10, textSize.height + 5);
        cv::rectangle(img, textBgRect, color, cv::FILLED);
        cv::putText(img, label, cv::Point(topLeft.x + 5, topLeft.y - 5), cv::FONT_HERSHEY_SIMPLEX, 0.6, CV_RGB(255, 255, 255), 2);
    }
}

int main()
{
    // Load the network and set the backend to CUDA
    cv::dnn::Net net = cv::dnn::readNetFromONNX("best.onnx");

    // Set the DNN backend to CUDA and target to CUDA
    net.setPreferableBackend(cv::dnn::DNN_BACKEND_CUDA);
    net.setPreferableTarget(cv::dnn::DNN_TARGET_CUDA);

    Mat img = cv::imread("fox.jpg");
    cv::resize(img, img, cv::Size(640, 640));
    Mat blob = cv::dnn::blobFromImage(img, 1.0 / 255.0, cv::Size(640, 640), cv::Scalar(), true);
    net.setInput(blob);
    vector<Mat> netoutput;
    vector<string> out_name = { "output" };
    net.forward(netoutput, out_name);
    Mat result = netoutput[0];
    vector<vector<float>> info = get_info(result);
    info_simplify(info);
    vector<vector<vector<float>>> info_split = split_info(info);

    for (auto i = 0; i < info_split.size(); i++)
    {
        nms(info_split[i]);
        draw_box(img, info_split[i]);
    }
    cv::imshow("test", img);
    cv::waitKey(0);
    return 0;
}