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



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 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)
    {
        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;

    }


}
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 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 class MLResultModel
{
    public bool IsSuccess = false;
    public string ResultMessage;
    public Bitmap ResultMap;
    public List<DetectionResultDetail> ResultDetails = new List<DetectionResultDetail>();
    public string WashMachineBar;
    public string WashMachineBatch;
    public string WashMachineSN;
    public string WashMachineLanguage;
}
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);

}