| #include <iostream> |
| #include <vector> |
| #include <getopt.h> |
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| #include <opencv2/opencv.hpp> |
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| #include "inference.h" |
|
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| using namespace std; |
| using namespace cv; |
|
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| int main(int argc, char **argv) |
| { |
| std::string projectBasePath = "/home/user/ultralytics"; |
|
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| bool runOnGPU = true; |
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| Inference inf(projectBasePath + "/yolov8s.onnx", cv::Size(640, 640), "classes.txt", runOnGPU); |
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| std::vector<std::string> imageNames; |
| imageNames.push_back(projectBasePath + "/ultralytics/assets/bus.jpg"); |
| imageNames.push_back(projectBasePath + "/ultralytics/assets/zidane.jpg"); |
|
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| for (int i = 0; i < imageNames.size(); ++i) |
| { |
| cv::Mat frame = cv::imread(imageNames[i]); |
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| |
| std::vector<Detection> output = inf.runInference(frame); |
|
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| int detections = output.size(); |
| std::cout << "Number of detections:" << detections << std::endl; |
|
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| for (int i = 0; i < detections; ++i) |
| { |
| Detection detection = output[i]; |
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| cv::Rect box = detection.box; |
| cv::Scalar color = detection.color; |
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| |
| cv::rectangle(frame, box, color, 2); |
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| |
| 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); |
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| 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); |
| } |
| |
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| |
| float scale = 0.8; |
| cv::resize(frame, frame, cv::Size(frame.cols*scale, frame.rows*scale)); |
| cv::imshow("Inference", frame); |
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| cv::waitKey(-1); |
| } |
| } |
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