hisence-yolo-detection/HisenceYoloDetection/SimboVisionMLBase.cs


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


public class XK_HisenceWord
{
    public string? OcrBar;
    public string? OneblockPath;
    public string? OneblockMainWord;
    public string? OneblockText;
    public string? TwoRect;
    public bool? TwoIFWhile;
    public string? TwoblockPath;
    public string? TwoblockMainWord;
    public string? TwoblockText;
    public string? ThreeblockPath;
    public string? ThreeblockMainWord;
    public string? ThreeblockText;
    public string? FourblockPath;
    public string? FourblockMainWord;
    public string? FourblockText;
    public string? FiveblockPath;
    public string? FiveblockMainWord;
    public string? FiveblockText;
    public string? SixblockPath;
    public string? SixblockMainWord;
    public string? SixblockText;
    public string? SevenblockPath;
    public string? SevenblockMainWord;
    public string? SevenblockText;
    public string? EightblockPath;
    public string? EightblockMainWord;
    public string? EightblockText;

    public XK_HisenceWord()
    {

    }

    public XK_HisenceWord(string? ocrBar, string? oneblockPath, string? oneblockMainWord, string? oneblockText, string? twoRect, bool? twoIFWhile, string? twoblockPath, string? twoblockMainWord, string? twoblockText, string? threeblockPath, string? threeblockMainWord, string? threeblockText, string? fourblockPath, string? fourblockMainWord, string? fourblockText, string? fiveblockPath, string? fiveblockMainWord, string? fiveblockText, string? sixblockPath, string? sixblockMainWord, string? sixblockText, string? sevenblockPath, string? sevenblockMainWord, string? sevenblockText, string? eightblockPath, string? eightblockMainWord, string? eightblockText)
    {
        OcrBar = ocrBar;
        OneblockPath = oneblockPath;
        OneblockMainWord = oneblockMainWord;
        OneblockText = oneblockText;
        TwoRect = twoRect;
        TwoIFWhile = twoIFWhile;
        TwoblockPath = twoblockPath;
        TwoblockMainWord = twoblockMainWord;
        TwoblockText = twoblockText;
        ThreeblockPath = threeblockPath;
        ThreeblockMainWord = threeblockMainWord;
        ThreeblockText = threeblockText;
        FourblockPath = fourblockPath;
        FourblockMainWord = fourblockMainWord;
        FourblockText = fourblockText;
        FiveblockPath = fiveblockPath;
        FiveblockMainWord = fiveblockMainWord;
        FiveblockText = fiveblockText;
        SixblockPath = sixblockPath;
        SixblockMainWord = sixblockMainWord;
        SixblockText = sixblockText;
        SevenblockPath = sevenblockPath;
        SevenblockMainWord = sevenblockMainWord;
        SevenblockText = sevenblockText;
        EightblockPath = eightblockPath;
        EightblockMainWord = eightblockMainWord;
        EightblockText = eightblockText;
    }

   }


public class XKHisence
{
   public int Number;
    public string ?Type;
    public string ?OcrBar;
   
    public int MoveX;
    public int MoveY;
    public int MoveZ;
    public string ?Detect;
    public string ?OcrText;
    public int MoveTwoX;
    public int MoveTwoY;
    public int MoveTwoZ;
    public string ?OcrParm;
    public string ?Language;
    public string? FuzzyOcrText;
    public XKHisence()
    {

    }

    public XKHisence(string type,string ocrBar,int MoveX,int MoveY,int MoveZ,string Detect,string ocrText,int MoveTwoX,int MoveTwoY,int MoveTwoZ,string OcrParm,string Language,string FuzzyOcrText)
    {
        this.Type = type;
        this.OcrBar = ocrBar;
        this.MoveX = MoveX;
        this.MoveY = MoveY;
        this.MoveZ= MoveZ;
        this.Detect = Detect;
        this.OcrText= ocrText;
        this.MoveTwoX = MoveTwoX;
        this.MoveTwoY = MoveTwoY;   
        this.MoveTwoZ = MoveTwoZ;
        this.OcrParm = OcrParm;
        this.Language = Language;
        this.FuzzyOcrText = FuzzyOcrText;

    }


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


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 static class OcrEngine
{

    // private const string sPath = @"F:\OOOCR\PaddleOCRsourcecodeGPU\PROJECTS\OcrDetForm\bin\Release\net7.0-windows\ocrInference.dll";



    [DllImport("ocrInference.dll", EntryPoint = "InitModel")]
    public static extern IntPtr InitModel(string model_ParaPath, string device_id);





    [DllImport("ocrInference.dll", EntryPoint = "Inference")]
    public static extern bool Inference(IntPtr model, byte[] img, int W, int H, int C,

         ref byte Mask_output, ref byte label);


    [DllImport("ocrInference.dll", EntryPoint = "FreePredictor")]
    public static extern void FreePredictor(IntPtr model);
}
public static class MLEngine1
{
    /**********************************************************************/
    /*****************          1.推理DLL导入实现          ****************/
    /**********************************************************************/
    //private const string sPath = @"D:\M018_NET7.0\src\Debug\model_infer.dll";
    // 加载推理相关方法
    [DllImport("model_infer.dll", EntryPoint = "InitModel")] // 模型统一初始化方法: 需要yml、pdmodel、pdiparams
                                                             //[DllImport(sPath, EntryPoint = "InitModel")] // 模型统一初始化方法: 需要yml、pdmodel、pdiparams
    public static extern IntPtr InitModel(string model_type, string model_filename, string params_filename, string cfg_file, bool use_gpu, int gpu_id, ref byte paddlex_model_type);

    [DllImport("model_infer.dll", EntryPoint = "Det_ModelPredict")]  // PaddleDetection模型推理方法
    public static extern bool Det_ModelPredict(IntPtr model, byte[] img, int W, int H, int C, IntPtr output, int[] BoxesNum, ref byte label);

    [DllImport("model_infer.dll", EntryPoint = "Seg_ModelPredict")]  // PaddleSeg模型推理方法
    public static extern bool Seg_ModelPredict(IntPtr model, byte[] img, int W, int H, int C, ref byte output);

    [DllImport("model_infer.dll", EntryPoint = "Cls_ModelPredict")]  // PaddleClas模型推理方法
    public static extern bool Cls_ModelPredict(IntPtr model, byte[] img, int W, int H, int C, ref float score, ref byte category, ref int category_id);

    [DllImport("model_infer.dll", EntryPoint = "Mask_ModelPredict")]  // Paddlex的MaskRCNN模型推理方法
    public static extern bool Mask_ModelPredict(IntPtr model, byte[] img, int W, int H, int C, IntPtr output, ref byte Mask_output, int[] BoxesNum, ref byte label);
    //public static extern bool Mask_ModelPredict(IntPtr model, IntPtr img, int W, int H, int C, IntPtr output, ref byte Mask_output, int[] BoxesNum, ref byte label);
    [DllImport("model_infer.dll", EntryPoint = "DestructModel")]  // 分割、检测、识别模型销毁方法
    public static extern void DestructModel(IntPtr model);

}