jiangnanboy / layout_detection

利用c++加载yolov8模型，进行版面检测。yolov8-c++ is used to detect the layout of Chinese document images

c++ yolov8实现版面检测

利用c++加载yolov8模型，进行推理。

yolov8-c++ is used to detect the layout of Chinese document images

数据

本项目根据开源中文版面数据CDLA ，利用yolov8进行训练

CDLA是一个中文文档版面分析数据集，面向中文文献类（论文）场景。包含以下10个label：

正文	标题	图片	图片标题	表格	表格标题	页眉	页脚	注释	公式
Text	Title	Figure	Figure caption	Table	Table caption	Header	Footer	Reference	Equation

推理：src/main/main.cpp

int main() {
    const string modelPath = "E:\\clion_project\\layout_onnx_cplusplus\\models\\model_det.onnx";
    const string labelNamesPath = "E:\\clion_project\\layout_onnx_cplusplus\\models\\label.names";
    filesystem::path imagePath = "E:\\clion_project\\layout_onnx_cplusplus\\test_img\\test.jpeg";
    const string savePath = "E:\\clion_project\\layout_onnx_cplusplus\\test_img_result";

    float confThreshold = 0.4f;
    float iouThreshold = 0.4f;
    float maskThreshold = 0.5f;
    bool isGPU = false;

    const vector<string> labelNames = initLabelName(labelNamesPath);

    if (labelNames.empty())
    {
        cerr << "Error: Label names file is empty!" << endl;
        return -1;
    }
    if (!filesystem::exists(modelPath))
    {
        cerr << "Error: Model path is empty!" << endl;
        return -1;
    }
    YOLOPredictor predictor = initModel(modelPath, isGPU, confThreshold, iouThreshold, maskThreshold);
    assert(labelNames.size() == predictor.classNums);
    regex pattern(".+\\.(jpg|jpeg|png|gif)$");
    cout << "Start inferring..." << endl;

    clock_t startTime, endTime;
    startTime = clock();
    if(filesystem::is_regular_file(imagePath) && regex_match(imagePath.string(), pattern)) {
        cv::Mat image = cv::imread(imagePath.string());
        vector<Yolov8Result> result = predictor.predict(image);
        utils::visualizeDetection(image, result, labelNames);
        cv::imwrite(savePath + "\\" + imagePath.filename().string(), image);
    }
    endTime = clock();
    cout << "Time consumption : " << (double)(endTime - startTime) / CLOCKS_PER_SEC << "seconds" << endl;
    cout << "##########DONE################" << endl;

    return 0;
}

requirement and environment:

• clion
• toolchains vs17
• onnxruntime-win-x64-1.15.1
• opencv-4.5.2-vc14_vc15
• OS: Win
• CPU

contact

1、github：https://github.com/jiangnanboy

2、博客：https://www.cnblogs.com/little-horse/

3、邮件:[e-mail]

reference

https://github.com/jiangnanboy/layout_analysis

https://github.com/ultralytics/ultralytics

https://github.com/buptlihang/CDLA

https://github.com/microsoft/onnxruntime-inference-examples

https://github.com/Li-99/yolov8_onnxruntime