HuaRui/SimboVisionMLBase.cs


using HZH_Controls.Controls;
using OpenCvSharp;
using System;
using System.Collections.Generic;
using System.ComponentModel.DataAnnotations;
using System.Drawing;
using System.Runtime.InteropServices;


//public abstract class SimboVisionMLBase
//{
//    public Mat ColorLut { get; set; }
//    public byte[] ColorMap { get; set; }

//    public MLModelType ModelType { get; set; }

//    public IntPtr Model { get; set; }

//    public abstract bool Load(MLInit mLInit);

//    public abstract MLResult RunInference(MLRequest req);

//    public void Dispose()
//    {
//        MLEngine.FreePredictor(Model);
//    }

//    public SimboVisionMLBase()
//    {
//        ColorMap = OpenCVHelper.GetColorMap(256);//使用3个通道
//        ColorLut = new Mat(1, 256, MatType.CV_8UC3, ColorMap);
//    }
//}
public class MLInit
{
    public string ModelFile;
    public string InferenceDevice;


    public int InferenceWidth;
    public int InferenceHeight;

    public string InputNodeName;




    public MLInit(string modelFile, string inputNodeName, string inferenceDevice, int inferenceWidth, int inferenceHeight)
    {
        ModelFile = modelFile;
        InferenceDevice = inferenceDevice;

        InferenceWidth = inferenceWidth;
        InferenceHeight = inferenceHeight;
        InputNodeName = inputNodeName;


    }
}
public class MLResult
{
    public bool IsSuccess = false;
    public string ResultMessage;
    public Bitmap ResultMap;
    public List<DetectionResultDetail> ResultDetails = new List<DetectionResultDetail>();
}
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 int Snapshot;

    public string SnapshotName;

    //public List<labelStringBase> OkClassTxtList;


  //  public List<ModelLabel> LabelNames;

    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 XKOCROfficeWord 
{
    [StringLength(50)]
    public int ID { get; set; }
    [StringLength(50)]
    public string Name { get; set; } = "";

    public int PageNum { get; set; } = 0;

    [StringLength(100)]
    public string filePath { get; set; } = "";
    public string jsonpath { get; set; } = "";


    public int LeftTopX { get; set; } = 0;

    public int LeftTopY { get; set; } = 0;

    public int RightBottmX { get; set; } = 0;

    public int RightBottmY { get; set; } = 0;

    public string ResultStr { 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 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);

    }