LuJiaYi/Define.cs

using OpenCvSharp;
using System;
using System.Collections.Generic;
using System.ComponentModel;
using System.Drawing;
using System.Runtime.InteropServices;


public class LuJiaYi
{
    // 使用属性而不是字段
    public string Product { get; set; }
    public int Num { get; set; }
    public double Distance { get; set; }
    public int Hole { get; set; }
    public string Load { get; set; }

    // 默认构造函数
    public LuJiaYi()
    {
    }

    // 带参数的构造函数
    public LuJiaYi(string product, int num, double distance, int hole, string load)
    {
        Product = product;
        Num = num;
        Distance = distance;
        Hole = hole;
        Load = load;
    }
}


public class MLRequest
{
    public int ImageChannels = 3;
    public Mat currentMat;
    public int ResizeWidth;
    public int ResizeHeight;

    public float confThreshold;

    public float iouThreshold;

    //public int ImageResizeCount;

    public string in_node_name;

    public string out_node_name;

    public string in_lable_path;
    public int ResizeImageSize;
    public int segmentWidth;
    public int ImageWidth;
    public float Score;

    public MLRequest()
    {

    }

}
public class DetectionResultDetail
{
    public string LabelBGR { get; set; }//识别到对象的标签BGR


    public int LabelNo { get; set; }   // 识别到对象的标签索引

    public string LabelName { get; set; }//识别到对象的标签名称

    public double Score { get; set; }//识别目标结果的可能性、得分

    public string LabelDisplay { get; set; }//识别到对象的 显示信息

    public double Area { get; set; }//识别目标的区域面积

    public Rectangle Rect { get; set; }//识别目标的外接矩形

    public RotatedRect MinRect { get; set; }//识别目标的最小外接矩形(带角度)

    //public ResultState InferenceResult { get; set; }//只是模型推理 label的结果

    public double DistanceToImageCenter { get; set; }  //计算矩形框到图像中心的距离



    // public ResultState FinalResult { get; set; }//模型推理+其他视觉、逻辑判断后 label结果
}
public class MLResult
{
    public bool IsSuccess = false;
    public string ResultMessage;
    public Bitmap ResultMap;
    public List<DetectionResultDetail> ResultDetails = new List<DetectionResultDetail>();
    public string JsonString { get; set; }
}
public static class MLEngine
{

    //private const string sPath = @"D:\\C#\磁环项目\\OpenVinoYolo\\openvino_Yolov5_v7_v2.0\\openvino_Yolov5_v7\\Program\ConsoleProject\\x64\\Release\\QuickSegmentDynamic.dll";


    [DllImport("QuickSegmentDynamic.dll", EntryPoint = "InitModel")]
    public static extern IntPtr InitModel(string model_filename, string inferenceDevice, string input_node_name, int bacth, int inferenceChannels, int InferenceWidth, int InferenceHeight);


    /// <summary>
    /// 分割
    /// </summary>
    /// <param name="model"></param>
    /// <param name="img"></param>
    /// <param name="W"></param>
    /// <param name="H"></param>
    /// <param name="C"></param>
    /// <param name="labelText"></param>
    /// <param name="conf_threshold"></param>
    /// <param name="IOU_THRESHOLD"></param>
    /// <param name="fScoreThre"></param>
    /// <param name="segmentWidth"></param>
    /// <param name="Mask_output"></param>
    /// <param name="label"></param>
    /// <returns></returns>
    [DllImport("QuickSegmentDynamic.dll", EntryPoint = "seg_ModelPredict")]

    public static extern bool seg_ModelPredict(IntPtr model, byte[] img, int W, int H, int C,
        string labelText, float conf_threshold, float IOU_THRESHOLD, float fScoreThre, int segmentWidth,
        ref byte Mask_output, ref byte label);



    /// <summary>
    /// 目标检测
    /// </summary>
    /// <param name="model"></param>
    /// <param name="img"></param>
    /// <param name="W"></param>
    /// <param name="H"></param>
    /// <param name="C"></param>
    /// <param name="nodes"></param>
    /// <param name="labelText"></param>
    /// <param name="conf_threshold"></param>
    /// <param name="IOU_THRESHOLD"></param>
    /// <param name="Mask_output"></param>
    /// <param name="label"></param>
    [DllImport("QuickSegmentDynamic.dll", EntryPoint = "det_ModelPredict")]
    public static extern bool det_ModelPredict(IntPtr model, byte[] img, int W, int H, int C,
        string nodes,// ++++++++++++++++++++++++++++++++++++
        string labelText, float conf_threshold, float IOU_THRESHOLD,
        ref byte Mask_output, ref byte label);


    [DllImport("QuickSegmentDynamic.dll", EntryPoint = "FreePredictor")]
    public static extern void FreePredictor(IntPtr model);


}

public enum ResultState
{
    [Description("检测NG")]
    DetectNG = 0,
    [Description("OK")]
    OK = 1,
}