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#include <iostream>
#include <vector>
#include <getopt.h>
#include <opencv2/opencv.hpp>
#include "inference.h"
using namespace std;
using namespace cv;
int main(int argc, char **argv)
{
std::string projectBasePath = "/home/user/ultralytics"; // Set your ultralytics base path
bool runOnGPU = true;
//
// Pass in either:
//
// "yolov8s.onnx" or "yolov5s.onnx"
//
// To run Inference with yolov8/yolov5 (ONNX)
//
// Note that in this example the classes are hard-coded and 'classes.txt' is a place holder.
Inference inf(projectBasePath + "/yolov8s.onnx", cv::Size(640, 480), "classes.txt", runOnGPU);
std::vector<std::string> imageNames;
imageNames.push_back(projectBasePath + "/ultralytics/assets/bus.jpg");
imageNames.push_back(projectBasePath + "/ultralytics/assets/zidane.jpg");
for (int i = 0; i < imageNames.size(); ++i)
{
cv::Mat frame = cv::imread(imageNames[i]);
// Inference starts here...
std::vector<Detection> output = inf.runInference(frame);
int detections = output.size();
std::cout << "Number of detections:" << detections << std::endl;
for (int i = 0; i < detections; ++i)
{
Detection detection = output[i];
cv::Rect box = detection.box;
cv::Scalar color = detection.color;
// Detection box
cv::rectangle(frame, box, color, 2);
// Detection box text
std::string classString = detection.className + ' ' + std::to_string(detection.confidence).substr(0, 4);
cv::Size textSize = cv::getTextSize(classString, cv::FONT_HERSHEY_DUPLEX, 1, 2, 0);
cv::Rect textBox(box.x, box.y - 40, textSize.width + 10, textSize.height + 20);
cv::rectangle(frame, textBox, color, cv::FILLED);
cv::putText(frame, classString, cv::Point(box.x + 5, box.y - 10), cv::FONT_HERSHEY_DUPLEX, 1, cv::Scalar(0, 0, 0), 2, 0);
}
// Inference ends here...
// This is only for preview purposes
float scale = 0.8;
cv::resize(frame, frame, cv::Size(frame.cols*scale, frame.rows*scale));
cv::imshow("Inference", frame);
cv::waitKey(-1);
}
}
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