Use_Device_Camera

/*****************************************************************************
*   Number Plate Recognition using SVM and Neural Networks
******************************************************************************
*   by Ronnie Leon Ochieng, 26th March 2024
******************************************************************************/

// Main entry code OpenCV

#include <opencv2/opencv.hpp>
#include <opencv2/imgcodecs.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/calib3d.hpp>
#include <opencv2/ml.hpp>
#include <opencv2/core/types.hpp>
#include <opencv2/imgproc/imgproc_c.h>
#include <opencv2/highgui/highgui_c.h>

#include <iostream>
#include <vector>

#include "DetectRegions.h"
#include "OCR.h"
#include "Plate.h"

using namespace std;
using namespace cv;

#define CV_TERMCRIT_ITER 1

string getFilename(string s) {

    char sep = '/';
    char sepExt='.';

    // #ifdef _WIN32
    //     sep = '\\';
    // #endif

    size_t i = s.rfind(sep, s.length( ));
    if (i != string::npos) {
        string fn= (s.substr(i+1, s.length( ) - i));
        size_t j = fn.rfind(sepExt, fn.length( ));
        if (i != string::npos) {
            return fn.substr(0,j);
        }else{
            return fn;
        }
    }else{
        return "";
    }
}

int main ( int argc, char** argv )
{
    cout << "OpenCV Automatic Number Plate Recognition\n";
    Mat input_image;

    // Open the camera device
    VideoCapture cap(0);
    if (!cap.isOpened()) {
        cout << "Failed to open the camera device" << endl;
        return -1;
    }

    while (true) {
        // Capture a frame from the camera
        cap >> input_image;

        // Check if the frame is empty
        if (input_image.empty()) {
            cout << "Failed to capture a frame" << endl;
            break;
        }

        // Detect possible plate regions
        DetectRegions detectRegions;
        detectRegions.saveRegions = false;
        detectRegions.showSteps = false;
        vector<Plate> possible_regions = detectRegions.run(input_image);

        // SVM for each plate region to get valid car plates
        FileStorage fs;
        fs.open("SVM.xml", FileStorage::READ);
        Mat SVM_TrainingData;
        Mat SVM_Classes;
        fs["TrainingData"] >> SVM_TrainingData;
        fs["classes"] >> SVM_Classes;
        cv::Ptr<cv::ml::SVM> svm = cv::ml::SVM::create();
        svm->setType(cv::ml::SVM::C_SVC);
        svm->setKernel(cv::ml::SVM::LINEAR);
        svm->setDegree(0);
        svm->setGamma(1);
        svm->setCoef0(0);
        svm->setC(1);
        svm->setNu(0);
        svm->setP(0);
        svm->setTermCriteria(cv::TermCriteria(cv::TermCriteria::MAX_ITER + cv::TermCriteria::EPS, 1000, 0.01));
        svm->train(SVM_TrainingData, cv::ml::ROW_SAMPLE, SVM_Classes);

        // For each possible plate, classify with SVM if it's a plate or not
        vector<Plate> plates;
        for (int i = 0; i < possible_regions.size(); i++) {
            Mat img = possible_regions[i].plateImg;
            Mat p = img.reshape(1, 1);
            p.convertTo(p, CV_32F);

            if (p.cols != svm->getVarCount()) {
                cerr << "Error: Number of features in p does not match the number of features the SVM was trained on." << endl;
            } else {
                int response = (int)svm->predict(p);
                if (response == 1)
                    plates.push_back(possible_regions[i]);
            }
        }

        // For each plate detected, recognize it with OCR
        OCR ocr("OCR.xml");
        ocr.saveSegments = true;
        ocr.DEBUG = false;
        for (int i = 0; i < plates.size(); i++) {
            Plate plate = plates[i];
            string plateNumber = ocr.run(&plate);
            string licensePlate = plate.str();
            cout << "================================================\n";
            cout << "License plate number: " << licensePlate << "\n";
            cout << "================================================\n";
            rectangle(input_image, plate.position, Scalar(0, 0, 200));
            putText(input_image, licensePlate, Point(plate.position.x, plate.position.y), CV_FONT_HERSHEY_SIMPLEX, 1, Scalar(0, 0, 200), 2);
        }

        // Display the processed frame
        imshow("Automatic Number Plate Recognition", input_image);

        // Break the loop if the 'Esc' key is pressed
        if (waitKey(1) == 27)
            break;
    }

    return 0;
}