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int main() { Yolov8Onnx yolov8; string modelPath = "/path/to/model.onnx"; bool isCuda = true; // or false for CPU inference int cudaID = 0; // optional bool warmUp = true; // optional if (!yolov8.ReadModel(modelPath, isCuda, cudaID, warmUp)) { std::cerr << "Failed to load model." << std::endl; return -1; } string imgPath = "/path/to/image.jpg"; cv::Mat img = cv::imread(imgPath); if (img.empty()) { std::cerr << "Failed to load image." << std::endl; return -1; } std::vector<OutputParams> output; if (!yolov8.OnnxDetect(img, output)) { std::cerr << "Failed to detect objects." << std::endl; return -1; } for (const auto& obj : output) { cv::Rect roi = obj.box; cv::Mat croppedImg = img(roi); // Save the cropped image to a file string outputFolder = "cropped"; string outputFile = "image_" + std::to_string(obj.id) + ".jpg"; string outputPath = outputFolder + "/" + outputFile; if (cv::imwrite(outputPath, croppedImg)) { std::cout << "Image saved: " << outputPath << std::endl; } else { std::cout << "Error saving image: " << outputPath << std::endl; } } return 0; }
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