OTS/OTSAlgrithm/AI/AIHttpClient.cs

using OpenCvSharp;
using OpenCvSharp.Extensions;
using System.Net.Http;
using System.IO;
using System;
using System.Collections.Generic;
using System.Drawing;
using OTSAlgrithm.Serialization;

namespace OTSAlgrithm.AI
{
    public class AIHttpClient
    {

        protected static NLog.Logger log ;
        /// <summary>
        /// 从分割模型获取二值图
        /// </summary>
        /// <param name="baseUrl"></param>
        /// <param name="input">输入mat 3通道 bgr格式</param>
        /// <param name="output">输出mat 灰度图</param>
        /// <param name="catagory">模型类别和模型配置文件对应</param>
        /// <param name="item">模型序号和模型配置文件对应</param>
        /// <param name="filename">input mat 原图完整路径</param>
        public static void SegmentImage(string baseUrl, Mat input, ref Mat output, string catagory, string item, string filename = "1.jpg")
        {
            string reqUrl = baseUrl + "/api/MetalAI/SegmentImage?catagory=" + catagory + "&item=" + item;
            try
            {

                HttpClient client = new HttpClient(new HttpClientHandler() { UseCookies = false });
                var postContent = new MultipartFormDataContent();
                string boundary = string.Format("--{0}", DateTime.Now.Ticks.ToString("x"));
                postContent.Headers.Add("ContentType", $"multipart/form-data, boundary={boundary}");
                MemoryStream ms = input.ToMemoryStream(".jpg");
                postContent.Add(new StreamContent(ms, (int)ms.Length), "formFiles", Path.GetFileName(filename));
                var response = client.PostAsync(reqUrl, postContent).Result;
                Console.WriteLine(response);
                if (response.IsSuccessStatusCode)
                {
                    var streamFromService = response.Content.ReadAsStreamAsync().Result;
                    Bitmap bmp = new Bitmap(streamFromService);
                    output = OpenCvSharp.Extensions.BitmapConverter.ToMat(bmp);
                    if (output.Channels() == 4)
                    {
                        Cv2.CvtColor(output, output, ColorConversionCodes.BGRA2GRAY);
                    }
                    else if (output.Channels() == 3)
                    {
                        Cv2.CvtColor(output, output, ColorConversionCodes.BGR2GRAY);
                    }

                    //if (item >= 8)
                    //{
                    //    Mat gray = new Mat();
                    //    Cv2.CvtColor(output, gray, ColorConversionCodes.BGR2GRAY);

                    //    //Mat thin = new Mat();
                    //    //CvXImgProc.Thinning(gray, gray, ThinningTypes.ZHANGSUEN);

                    //    //Cv2.BitwiseNot(gray, gray);

                    //    //gray = PostProcessor.Run(gray);

                    //    //gray = WaterSegmentation.WatershedSegment(gray);

                    //    //Cv2.BitwiseNot(gray, gray);
                    //    //Cv2.Dilate(gray, gray, Cv2.GetStructuringElement(MorphShapes.Rect, new OpenCvSharp.Size(3, 3)));

                    //    Cv2.CvtColor(gray, output, ColorConversionCodes.GRAY2BGR);
                    //}
                    //else if (item >= 5 && item <= 7)
                    //{
                    //    Cv2.BitwiseNot(output, output);
                    //}

                    return;
                }
            }
            catch (Exception ex)
            {
                //LogHelper.Error(ex);
                Console.WriteLine(ex.ToString());
            }
        }

        /// <summary>
        /// 从模型获得分类结果 需做进一步筛选获得分类
        /// </summary>
        /// <param name="baseUrl"></param>
        /// <param name="input">输入mat 3通道 bgr格式</param>
        /// <param name="resultDic">label confiden 字典</param>
        /// <param name="catagory">模型类别和模型配置文件对应</param>
        /// <param name="item">模型序号和模型配置文件对应</param>
        /// <param name="filename">input mat 原图完整路径</param>
        public static void AI_ClassImage(string baseUrl, Mat input, ref Dictionary<string, string> resultDic, int catagory = 1000, int item = 2, string filename = "1.jpg")
        {
            string reqUrl = baseUrl + "/api/MetalAI/Classify?catagory=" + catagory.ToString() + "&item=" + item.ToString();
            try
            {

                HttpClient client = new HttpClient(new HttpClientHandler() { UseCookies = false });
                var postContent = new MultipartFormDataContent();
                string boundary = string.Format("--{0}", DateTime.Now.Ticks.ToString("x"));
                postContent.Headers.Add("ContentType", $"multipart/form-data, boundary={boundary}");
                MemoryStream ms = input.ToMemoryStream(".jpg");
                postContent.Add(new StreamContent(ms, (int)ms.Length), "formFiles", Path.GetFileName(filename));
                var response = client.PostAsync(reqUrl, postContent).Result;
                //Console.WriteLine(response);
                if (response.IsSuccessStatusCode)
                {
                    var streamFromService = response.Content.ReadAsStringAsync().Result;
                    //resultDic = JsonConvert.DeserializeObject<Dictionary<string, string>>(streamFromService);
                    //var maxItem = resultDic.OrderByDescending(kvp => double.Parse(kvp.Value)).FirstOrDefault();//获取得分最大元素的方法
                    return;
                }
            }
            catch (Exception ex)
            {
                // throw new Exception("保存file异常");
                Console.WriteLine(ex.ToString());
            }
        }
        
        public static bool AI_Test(string baseUrl)
        {
            bool connect = false;
            string reqUrl = baseUrl + "/api/metalai/Test";
            try
            {

                HttpClient client = new HttpClient(new HttpClientHandler() { UseCookies = false });
                client.Timeout = TimeSpan.FromSeconds(3);
                var response = client.GetAsync(reqUrl).Result;
                //Console.WriteLine(response);
                if (response.IsSuccessStatusCode)
                {

                    connect = true;
                }
            }
            catch (Exception ex)
            {
                // throw new Exception("保存file异常");
                Console.WriteLine(ex.ToString());
                return false;
            }
            return connect;
        }

        /// <summary>
        /// 20250611锡球增加 WQ
        /// </summary>
        /// <param name="baseUrl"></param>
        /// <param name="input"></param>
        /// <param name="output"></param>
        /// <param name="catagory"></param>
        /// <param name="item"></param>
        /// <param name="filename"></param>
        public static void SegmentImage(string baseUrl, Mat input, ref Mat output, int catagory = 1000, int item = 1, string filename = "1.jpg")
        {
            string reqUrl = baseUrl + "/api/MetalAI/SegmentImage?catagory=" + catagory.ToString() + "&item=" + item.ToString();
            try
            {

                HttpClient client = new HttpClient(new HttpClientHandler() { UseCookies = false });
                var postContent = new MultipartFormDataContent();
                string boundary = string.Format("--{0}", DateTime.Now.Ticks.ToString("x"));
                postContent.Headers.Add("ContentType", $"multipart/form-data, boundary={boundary}");
                MemoryStream ms = input.ToMemoryStream(".jpg");
                postContent.Add(new StreamContent(ms, (int)ms.Length), "formFiles", Path.GetFileName(filename));
                var response = client.PostAsync(reqUrl, postContent).Result;
                Console.WriteLine(response);
                if (response.IsSuccessStatusCode)
                {
                    var streamFromService = response.Content.ReadAsStreamAsync().Result;
                    Bitmap bmp = new Bitmap(streamFromService);
                    output = BitmapConverter.ToMat(bmp);
                    if (output.Channels() == 4)
                    {
                        Cv2.CvtColor(output, output, ColorConversionCodes.BGRA2BGR);
                    }
                    else if (output.Channels() == 1)
                    {
                        Cv2.CvtColor(output, output, ColorConversionCodes.GRAY2BGR);
                    }

                    //if(item >= 4)
                    //{
                    //    Mat gray = new Mat();
                    //    Cv2.CvtColor(output, gray, ColorConversionCodes.BGR2GRAY);

                    //    //Mat thin = new Mat();
                    //    //CvXImgProc.Thinning(gray, gray, ThinningTypes.ZHANGSUEN);

                    //    //Cv2.BitwiseNot(gray, gray);

                    //    gray = PostProcessor.Run(gray);

                    //    //gray = WaterSegmentation.WatershedSegment(gray);

                    //    //Cv2.BitwiseNot(gray, gray);
                    //    //Cv2.Dilate(gray, gray, Cv2.GetStructuringElement(MorphShapes.Rect, new OpenCvSharp.Size(3, 3)));

                    //    Cv2.CvtColor(gray, output, ColorConversionCodes.GRAY2BGR);
                    //}
                    //else if ((item >= 5) && (item <= 7))
                    //{
                    //    Cv2.BitwiseNot(output, output);
                    //}

                    return;
                }
            }
            catch (Exception ex)
            {
                //LogHelper.Error(ex);
                Console.WriteLine(ex.ToString());
            }
        }

        /// <summary>
        /// 20250611锡球增加 WQ
        /// </summary>
        /// <param name="baseUrl"></param>
        /// <param name="input"></param>
        /// <param name="catagory"></param>
        /// <param name="item"></param>
        /// <param name="filename"></param>
        /// <returns></returns>
        public static AIAnalysisResult DetectObject(string baseUrl, Mat input, string catagory, string item, string filename = "1.jpg")
        {
            string reqUrl = baseUrl + "/api/ObjectDetector?catagory=" + catagory.ToString() + "&item=" + item.ToString();
            try
            {

                HttpClient client = new HttpClient(new HttpClientHandler() { UseCookies = false });
                var postContent = new MultipartFormDataContent();
                string boundary = string.Format("--{0}", DateTime.Now.Ticks.ToString("x"));
                postContent.Headers.Add("ContentType", $"multipart/form-data, boundary={boundary}");
                MemoryStream ms = input.ToMemoryStream(".jpg");
                postContent.Add(new StreamContent(ms, (int)ms.Length), "formFiles", Path.GetFileName(filename));
                var response = client.PostAsync(reqUrl, postContent).Result;
                Console.WriteLine(response);
                if (response.IsSuccessStatusCode)
                {
                    var streamFromService = response.Content.ReadAsStringAsync().Result;
                    var obj = JsonHelper.Deserialize<AIAnalysisResult>(streamFromService);
                    return obj;
                }
            }
            catch (Exception ex)
            {
                //LogHelper.Error(ex);
                Console.WriteLine(ex.ToString());
            }

            return new AIAnalysisResult();
        }

        /// <summary>
        /// 20250611锡球增加 WQ
        /// </summary>
        /// <param name="baseUrl"></param>
        /// <param name="input"></param>
        /// <param name="category"></param>
        /// <param name="item"></param>
        /// <param name="filename"></param>
        /// <returns></returns>
        public static AIAnalysisResult SegmentImageJson(string baseUrl, Mat input, string category = "1000", string item = "1", string filename = "1.jpg")
        {
            log = NLog.LogManager.GetCurrentClassLogger();
            string reqUrl = baseUrl + "/api/MetalAI/SegmentImageJson?catagory=" + category + "&item=" + item;
            try
            {

                HttpClient client = new HttpClient(new HttpClientHandler() { UseCookies = false });
                var postContent = new MultipartFormDataContent();
                string boundary = string.Format("--{0}", DateTime.Now.Ticks.ToString("x"));
                postContent.Headers.Add("ContentType", $"multipart/form-data, boundary={boundary}");
                MemoryStream ms = input.ToMemoryStream(".jpg");
                postContent.Add(new StreamContent(ms, (int)ms.Length), "formFiles", Path.GetFileName(filename));
                var response = client.PostAsync(reqUrl, postContent).Result;
                Console.WriteLine(response);
                if (response.IsSuccessStatusCode)
                {
                    var streamFromService = response.Content.ReadAsStringAsync().Result;
                    var obj = JsonHelper.Deserialize<AIAnalysisResult>(streamFromService);
                    return obj;
                }
            }
            catch (Exception ex)
            {
                log.Error(ex.ToString());
            }

            return new AIAnalysisResult();
        }

        public static AIAnalysisResult SegmentImageGranule(string baseUrl, Mat input, string category = "1000", string item = "1", float diameter = 0.0f, string filename = "1.jpg")
        {
            string reqUrl = baseUrl + "/api/MetalAI/SegmentImageGranule?catagory=" + category + "&item=" + item + "&diameter=" + diameter.ToString();
            try
            {

                HttpClient client = new HttpClient(new HttpClientHandler() { UseCookies = false });
                var postContent = new MultipartFormDataContent();
                string boundary = string.Format("--{0}", DateTime.Now.Ticks.ToString("x"));
                postContent.Headers.Add("ContentType", $"multipart/form-data, boundary={boundary}");
                MemoryStream ms = input.ToMemoryStream(".jpg");
                postContent.Add(new StreamContent(ms, (int)ms.Length), "formFiles", Path.GetFileName(filename));
                var response = client.PostAsync(reqUrl, postContent).Result;
                Console.WriteLine(response);
                if (response.IsSuccessStatusCode)
                {
                    var streamFromService = response.Content.ReadAsStringAsync().Result;
                    var obj = JsonHelper.Deserialize<AIAnalysisResult>(streamFromService);
                    return obj;
                }
            }
            catch (Exception ex)
            {
                //LogHelper.Error(ex);
                Console.WriteLine(ex.ToString());
            }

            return new AIAnalysisResult();
        }
    }
}