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191
DH.Devices.Vision/SimboVisionMLBase.cs
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191
DH.Devices.Vision/SimboVisionMLBase.cs
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using OpenCvSharp;
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using System;
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using System.Collections.Generic;
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using System.Drawing;
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using System.Runtime.InteropServices;
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namespace DH.Devices.Vision
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{
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public abstract class SimboVisionMLBase
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{
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public Mat ColorLut { get; set; }
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public byte[] ColorMap { get; set; }
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public MLModelType ModelType { get; set; }
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public IntPtr Model { get; set; }
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public abstract bool Load(MLInit mLInit);
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public abstract MLResult RunInference(MLRequest req);
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public void Dispose()
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{
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try
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{
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MLGPUEngine.FreePredictor(Model);
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}
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catch (Exception e) { }
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// MLEngine.FreePredictor(Model);
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}
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public void Dispose2()
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{
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try
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{
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MLEngine.FreePredictor(Model);
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}
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catch (Exception e) { }
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// MLEngine.FreePredictor(Model);
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}
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public SimboVisionMLBase()
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{
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// ColorMap = OpenCVHelper.GetColorMap(256);//使用3个通道
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// ColorLut = new Mat(1, 256, MatType.CV_8UC3, ColorMap);
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}
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}
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public class SegResult
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{
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public List<Result> SegmentResult;
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public class Result
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{
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public double fScore;
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public int classId;
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public string classname;
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public double area;
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public List<int> rect;
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}
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}
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public static class MLGPUEngine
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{
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// private const string sPath = @"D:\XHM\XHM\M018_NET7.0speed - 副本 - 副本\src\x64\Debug\HYolo.dll";
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[DllImport("HYolo.dll", EntryPoint = "InitModel")]
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//public static extern IntPtr InitModel(string model_path, int batch_size, float score_thre, int device_id, int number_of_warmup_runs);
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public static extern IntPtr InitModel(string model_path, int batch_size, float score_thre, int device_id, int number_of_warmup_runs,int request_infer);
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[DllImport("HYolo.dll", EntryPoint = "PreHot")]
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public static extern bool PreHot(IntPtr model, byte[] img, int W, int H, int C);
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[DllImport("HYolo.dll", EntryPoint = "Inference")]
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public static extern bool Inference(IntPtr model, byte[] img, int W, int H, int C,
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string labelText, ref byte Mask_output, ref byte label);
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[DllImport("HYolo.dll", EntryPoint = "Inference2")]
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public static extern bool Inference2(IntPtr model, byte[] img, int W, int H, int C,
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string labelText, ref byte label);
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[DllImport("HYolo.dll", EntryPoint = "FreePredictor")]
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public static extern void FreePredictor(IntPtr model);
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}
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public static class MLEngine
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{
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//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";
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[DllImport("QuickSegmentDynamic.dll", EntryPoint = "InitModel")]
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public static extern IntPtr InitModel(string model_filename, string inferenceDevice, string input_node_name, int bacth, int inferenceChannels, int InferenceWidth, int InferenceHeight,int request_infer);
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/// <summary>
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/// 分割
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/// </summary>
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/// <param name="model"></param>
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/// <param name="img"></param>
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/// <param name="W"></param>
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/// <param name="H"></param>
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/// <param name="C"></param>
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/// <param name="labelText"></param>
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/// <param name="conf_threshold"></param>
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/// <param name="IOU_THRESHOLD"></param>
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/// <param name="fScoreThre"></param>
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/// <param name="segmentWidth"></param>
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/// <param name="Mask_output"></param>
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/// <param name="label"></param>
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/// <returns></returns>
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[DllImport("QuickSegmentDynamic.dll", EntryPoint = "seg_ModelPredict")]
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public static extern bool seg_ModelPredict(IntPtr model, byte[] img, int W, int H, int C,
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string labelText, float conf_threshold, float IOU_THRESHOLD, float fScoreThre, int segmentWidth,
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ref byte Mask_output, ref byte label);
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/// <summary>
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/// 目标检测
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/// </summary>
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/// <param name="model"></param>
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/// <param name="img"></param>
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/// <param name="W"></param>
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/// <param name="H"></param>
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/// <param name="C"></param>
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/// <param name="nodes"></param>
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/// <param name="labelText"></param>
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/// <param name="conf_threshold"></param>
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/// <param name="IOU_THRESHOLD"></param>
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/// <param name="Mask_output"></param>
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/// <param name="label"></param>
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[DllImport("QuickSegmentDynamic.dll", EntryPoint = "det_ModelPredict")]
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public static extern bool det_ModelPredict(IntPtr model, byte[] img, int W, int H, int C,
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string nodes,// ++++++++++++++++++++++++++++++++++++
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string labelText, float conf_threshold, float IOU_THRESHOLD,
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ref byte Mask_output, ref byte label);
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[DllImport("QuickSegmentDynamic.dll", EntryPoint = "FreePredictor")]
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public static extern void FreePredictor(IntPtr model);
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}
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public static class MLEngine1
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{
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/**********************************************************************/
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/***************** 1.推理DLL导入实现 ****************/
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/**********************************************************************/
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//private const string sPath = @"D:\M018_NET7.0\src\Debug\model_infer.dll";
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// 加载推理相关方法
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[DllImport("model_infer.dll", EntryPoint = "InitModel")] // 模型统一初始化方法: 需要yml、pdmodel、pdiparams
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//[DllImport(sPath, EntryPoint = "InitModel")] // 模型统一初始化方法: 需要yml、pdmodel、pdiparams
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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);
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[DllImport("model_infer.dll", EntryPoint = "Det_ModelPredict")] // PaddleDetection模型推理方法
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public static extern bool Det_ModelPredict(IntPtr model, byte[] img, int W, int H, int C, IntPtr output, int[] BoxesNum, ref byte label);
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[DllImport("model_infer.dll", EntryPoint = "Seg_ModelPredict")] // PaddleSeg模型推理方法
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public static extern bool Seg_ModelPredict(IntPtr model, byte[] img, int W, int H, int C, ref byte output);
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[DllImport("model_infer.dll", EntryPoint = "Cls_ModelPredict")] // PaddleClas模型推理方法
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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);
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[DllImport("model_infer.dll", EntryPoint = "Mask_ModelPredict")] // Paddlex的MaskRCNN模型推理方法
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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);
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//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);
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[DllImport("model_infer.dll", EntryPoint = "DestructModel")] // 分割、检测、识别模型销毁方法
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public static extern void DestructModel(IntPtr model);
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}
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}
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