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+#define cxx_server
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+using System;
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+using System.Collections.Generic;
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+using System.Diagnostics;
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+using System.IO;
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+using System.Linq;
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+using System.Net;
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+using System.Net.Http;
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+using System.Net.Http.Headers;
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+using System.Runtime.InteropServices.ComTypes;
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+using System.Text;
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+using System.Threading;
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+using System.Threading.Tasks;
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+using Newtonsoft.Json;
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+using OpenCvSharp;
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+using System.Drawing;
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+using OpenCvSharp.Extensions;
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+using Newtonsoft.Json.Linq;
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+using System.Runtime.InteropServices;
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+using System.Security.Policy;
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+using static OpenCvSharp.XImgProc.CvXImgProc;
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+
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+namespace OTSModelSharp.ServiceCenter
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+{
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+ public class class_result
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+ {
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+ public string Result { get; set; }
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+ public float Confidence { get; set; }
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+ }
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+ public class AI_HttpClient
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+ {
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+ /// <summary>
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+ /// 从分割模型获取二值图
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+ /// </summary>
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+ /// <param name="baseUrl">包括ip地址端口号</param>
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+ /// <param name="input">输入mat 3通道 bgr格式</param>
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+ /// <param name="output">输出mat 灰度图</param>
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+ /// <param name="catagory">模型类别和模型配置文件对应</param>
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+ /// <param name="item">模型序号和模型配置文件对应</param>
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+ /// <param name="filename">input mat 原图完整路径</param>
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+ public static void AI_SegmentImage(string baseUrl, Mat input, ref Mat output, int catagory = 1000, int item = 1, string filename = "1.jpg")
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+ {
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+#if cxx_server
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+ AI_SegmentImage_cxx(baseUrl, input, ref output, catagory, item, filename);
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+#else
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+AI_SegmentImage_cshape(baseUrl, input, ref output, catagory, item, filename);
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+#endif
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+ }
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+ /// <summary>
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+ /// 从模型获得分类结果 需做进一步筛选获得分类
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+ /// </summary>
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+ /// <param name="baseUrl"></param>
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+ /// <param name="input">输入mat 3通道 bgr格式</param>
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+ /// <param name="resultDic">label confiden 字典</param>
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+ /// <param name="catagory">模型类别和模型配置文件对应</param>
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+ /// <param name="item">模型序号和模型配置文件对应</param>
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+ /// <param name="filename">input mat 原图完整路径</param>
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+ public static void AI_ClassImage(string baseUrl, Mat input, ref Dictionary<string, string> resultDic, int catagory = 1000, int item = 2, string filename = "1.jpg")
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+ {
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+#if cxx_server
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+ AI_ClassImage_cxx(baseUrl, input, ref resultDic, catagory, item, filename);
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+#else
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+ AI_ClassImage_cshape(baseUrl, input, ref resultDic, catagory, item, filename);
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+#endif
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+ }
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+
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+ /// <summary>
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+ /// 从分割模型获取二值图 cshape httpserver
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+ /// </summary>
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+ /// <param name="baseUrl">包括ip地址端口号</param>
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+ /// <param name="input">输入mat 3通道 bgr格式</param>
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+ /// <param name="output">输出mat 灰度图</param>
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+ /// <param name="catagory">模型类别和模型配置文件对应</param>
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+ /// <param name="item">模型序号和模型配置文件对应</param>
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+ /// <param name="filename">input mat 原图完整路径</param>
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+ public static void AI_SegmentImage_cshape(string baseUrl, Mat input, ref Mat output, int catagory = 1000, int item = 1, string filename = "1.jpg")
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+ {
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+ string reqUrl = baseUrl + "/api/MetalAI/SegmentImage?catagory=" + catagory.ToString() + "&item=" + item.ToString();
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+ try
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+ {
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+
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+ HttpClient client = new HttpClient(new HttpClientHandler() { UseCookies = false });
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+ var postContent = new MultipartFormDataContent();
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+ string boundary = string.Format("--{0}", DateTime.Now.Ticks.ToString("x"));
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+ postContent.Headers.Add("ContentType", $"multipart/form-data, boundary={boundary}");
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+ MemoryStream ms = input.ToMemoryStream(".jpg");
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+ postContent.Add(new StreamContent(ms, (int)ms.Length), "formFiles", Path.GetFileName(filename));
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+ var response = client.PostAsync(reqUrl, postContent).Result;
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+ Console.WriteLine(response);
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+ if (response.IsSuccessStatusCode)
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+ {
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+ var streamFromService = response.Content.ReadAsStreamAsync().Result;
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+ Bitmap bmp = new Bitmap(streamFromService);
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+ output = BitmapConverter.ToMat(bmp);
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+ if (output.Channels() == 4)
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+ {
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+ Cv2.CvtColor(output, output, ColorConversionCodes.BGRA2GRAY);
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+ }
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+ return;
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+ }
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+ }
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+ catch (Exception ex)
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+ {
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+
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+ Console.WriteLine(ex.ToString());
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+ }
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+ }
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+ /// <summary>
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+ /// 从模型获得分类结果 需做进一步筛选获得分类 cshape httpserver
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+ /// </summary>
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+ /// <param name="baseUrl"></param>
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+ /// <param name="input">输入mat 3通道 bgr格式</param>
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+ /// <param name="resultDic">label confiden 字典</param>
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+ /// <param name="catagory">模型类别和模型配置文件对应</param>
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+ /// <param name="item">模型序号和模型配置文件对应</param>
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+ /// <param name="filename">input mat 原图完整路径</param>
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+ public static void AI_ClassImage_cshape(string baseUrl, Mat input, ref Dictionary<string, string> resultDic, int catagory = 1000, int item = 2, string filename = "1.jpg")
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+ {
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+ string reqUrl = baseUrl + "/api/MetalAI/Classify?catagory=" + catagory.ToString() + "&item=" + item.ToString();
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+ try
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+ {
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+
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+ HttpClient client = new HttpClient(new HttpClientHandler() { UseCookies = false });
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+ var postContent = new MultipartFormDataContent();
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+ string boundary = string.Format("--{0}", DateTime.Now.Ticks.ToString("x"));
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+ postContent.Headers.Add("ContentType", $"multipart/form-data, boundary={boundary}");
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+ MemoryStream ms = input.ToMemoryStream(".jpg");
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+ postContent.Add(new StreamContent(ms, (int)ms.Length), "formFiles", Path.GetFileName(filename));
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+ var response = client.PostAsync(reqUrl, postContent).Result;
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+ //Console.WriteLine(response);
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+ if (response.IsSuccessStatusCode)
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+ {
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+ var streamFromService = response.Content.ReadAsStringAsync().Result;
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+ resultDic = JsonConvert.DeserializeObject<Dictionary<string, string>>(streamFromService);
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+ //var maxItem = resultDic.OrderByDescending(kvp => double.Parse(kvp.Value)).FirstOrDefault();//获取得分最大元素的方法
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+ return;
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+ }
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+ }
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+ catch (Exception ex)
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+ {
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+ // throw new Exception("保存file异常");
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+ Console.WriteLine(ex.ToString());
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+ }
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+ }
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+ public static bool AI_Test(string baseUrl)
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+ {
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+ bool connect=false;
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+ string reqUrl = baseUrl + "/api/metalai/Test";
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+ try
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+ {
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+
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+ HttpClient client = new HttpClient(new HttpClientHandler() { UseCookies = false });
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+ client.Timeout= TimeSpan.FromSeconds(3);
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+ var response = client.GetAsync(reqUrl).Result;
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+ //Console.WriteLine(response);
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+ if (response.IsSuccessStatusCode)
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+ {
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+
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+ connect=true;
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+ }
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+ }
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+ catch (Exception ex)
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+ {
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+ // throw new Exception("保存file异常");
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+ Console.WriteLine(ex.ToString());
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+ return false;
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+ }
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+ return connect;
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+ }
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+ /// <summary>
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+ /// c++ 服务器 分类模型
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+ /// </summary>
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+ /// <param name="baseUrl"></param>
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+ /// <param name="input"></param>
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+ /// <param name="resultDic"></param>
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+ /// <param name="catagory"></param>
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+ /// <param name="item"></param>
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+ /// <param name="filename"></param>
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+ public static void AI_ClassImage_cxx(string baseUrl, Mat input, ref Dictionary<string, string> resultDic, int catagory = 1000, int item = 2, string filename = "1.jpg")
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+ {
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+ baseUrl = baseUrl + "/api/MetalAI/Classify";
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+ if (input.Empty())
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+ {
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+ return;
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+ }
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+ class_result result = new class_result();
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+
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+ Dictionary<string, float> resluts = new Dictionary<string, float>();
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+ using (var client = new HttpClient())
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+ {
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+ // Create the query parameters
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+ var query = $"?category={catagory}&item={item}";
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+
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+ // Read the image into a byte array
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+ byte[] imageBytes;
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+ Cv2.ImEncode(".png", input, out imageBytes);
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+ // Create the content with image data
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+
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+
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+ var imageContent = new ByteArrayContent(imageBytes);
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+ //imageContent.Headers.ContentLength= imageBytes1.Length;
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+ Console.WriteLine(imageBytes.Length);
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+ // Send the POST request with query parameters
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+ var fullUrl = baseUrl + query;
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+ try
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+ {
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+
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+ }
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+ catch (Exception)
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+ {
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+
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+ throw;
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+ }
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+ var response = client.PostAsync(fullUrl, imageContent).Result;
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+
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+ if (response.IsSuccessStatusCode)
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+ {
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+ var responseData = response.Content.ReadAsStringAsync().Result;
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+ // var result1 = JsonConvert.DeserializeObject<class_result>(responseData);
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+ resluts = JsonConvert.DeserializeObject<Dictionary<string, float>>(responseData);
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+ foreach (var reslt in resluts)
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+ {
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+ resultDic.Add(reslt.Key, reslt.Value.ToString());
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+ }
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+
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+ }
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+ else
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+ {
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+ Console.WriteLine($"HTTP request failed with status code {response.StatusCode}");
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+ }
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+ }
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+
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+ }
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+ /// <summary>
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+ /// c++服务器 unet
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+ /// </summary>
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+ /// <param name="baseUrl"></param>
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+ /// <param name="input"></param>
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+ /// <param name="output"></param>
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+ /// <param name="catagory"></param>
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+ /// <param name="item"></param>
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+ /// <param name="filename"></param>
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+ public static void AI_SegmentImage_cxx(string baseUrl, Mat input, ref Mat output, int catagory = 1000, int item = 1, string filename = "1.jpg")
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+ {
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+ baseUrl = baseUrl + "/api/MetalAI/SegmentImage";
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+ if (input.Empty())
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+ {
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+ return;
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+ }
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+ // Create the query parameters
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+ var query = $"?category={catagory}&item={item}";
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+ var fullUrl = baseUrl + query;
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+ send_image(fullUrl, input, ref output);
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+
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+ }
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+ public static void UploadFile(string url, string filePath)
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+ {
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+ using (var client = new HttpClient())
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+ using (var content = new MultipartFormDataContent())
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+ {
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+ var fileContent = new StreamContent(new FileStream(filePath, FileMode.Open, FileAccess.Read));
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+ fileContent.Headers.ContentType = MediaTypeHeaderValue.Parse("image/jpeg"); // 设置正确的MIME类型
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+ content.Add(fileContent, "file", Path.GetFileName(filePath)); // "file"是服务器期望的表单字段名
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+
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+ var response = client.PostAsync(url, content).Result; // 使用.Result等待异步操作完成，这将阻塞当前线程
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+
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+ if (response.IsSuccessStatusCode)
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+ {
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+ Console.WriteLine("File uploaded successfully.");
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+ }
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+ else
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+ {
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+ Console.WriteLine("Error uploading file: " + response.StatusCode);
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+ }
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+ }
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+ }
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+ public static void send_image(string fullUrl, Mat input, ref Mat output)
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+ {
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+ using (var client = new HttpClient())
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+ {
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+ // Create the query parameters
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+
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+
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+ // Read the image into a byte array
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+ byte[] imageBytes;
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+ Cv2.ImEncode(".png", input, out imageBytes);
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+ // Create the content with image data
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+ var imageContent = new ByteArrayContent(imageBytes);
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+ Console.WriteLine(imageBytes.Length);
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+ // Send the POST request with query parameters
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+
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+ var response = client.PostAsync(fullUrl, imageContent).Result;
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+ if (response.IsSuccessStatusCode)
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+ {
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+ //var responseData = response.Content.ReadAsStringAsync().Result;
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+ var streamFromService = response.Content.ReadAsByteArrayAsync().Result;
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+ try
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+ {
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+ output = Cv2.ImDecode(streamFromService, ImreadModes.Grayscale);
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+ }
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+ catch (Exception)
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+ {
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+
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+ throw;
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+ }
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+ }
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+ else
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+ {
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+ Console.WriteLine($"HTTP request failed with status code {response.StatusCode} ");
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+ }
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+ }
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+
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+ }
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+ public static void AI_SegformerImage_cxx(string baseUrl, Mat input, ref Mat output, int catagory = 1000, int item = 1)
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+ {
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+ baseUrl = baseUrl + "/api/MetalAI/SegformerImage";
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+ if (input.Empty())
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+ {
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+ return;
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+ }
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+ var query = $"?category={catagory}&item={item}";
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+ var fullUrl = baseUrl + query;
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+ send_image(fullUrl, input, ref output);
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+ }
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+
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+ }
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+}
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zym198098