frist commit

.gitignore

@@ -0,0 +1,343 @@
+## Ignore Visual Studio temporary files, build results, and
+## files generated by popular Visual Studio add-ons.
+##
+## Get latest from https://github.com/github/gitignore/blob/master/VisualStudio.gitignore
+
+# User-specific files
+*.rsuser
+*.suo
+*.user
+*.userosscache
+*.sln.docstates
+
+# User-specific files (MonoDevelop/Xamarin Studio)
+*.userprefs
+
+# Build results
+[Dd]ebug/
+[Dd]ebugPublic/
+[Rr]elease/
+[Rr]eleases/
+x64/
+x86/
+[Aa][Rr][Mm]/
+[Aa][Rr][Mm]64/
+bld/
+[Bb]in/
+[Oo]bj/
+[Ll]og/
+
+# Visual Studio 2015/2017 cache/options directory
+.vs/
+# Uncomment if you have tasks that create the project's static files in wwwroot
+#wwwroot/
+
+# Visual Studio 2017 auto generated files
+Generated\ Files/
+
+# MSTest test Results
+[Tt]est[Rr]esult*/
+[Bb]uild[Ll]og.*
+
+# NUNIT
+*.VisualState.xml
+TestResult.xml
+
+# Build Results of an ATL Project
+[Dd]ebugPS/
+[Rr]eleasePS/
+dlldata.c
+
+# Benchmark Results
+BenchmarkDotNet.Artifacts/
+
+# .NET Core
+project.lock.json
+project.fragment.lock.json
+artifacts/
+
+# StyleCop
+StyleCopReport.xml
+
+# Files built by Visual Studio
+*_i.c
+*_p.c
+*_h.h
+*.ilk
+*.meta
+*.obj
+*.iobj
+*.pch
+*.pdb
+*.ipdb
+*.pgc
+*.pgd
+*.rsp
+*.sbr
+*.tlb
+*.tli
+*.tlh
+*.tmp
+*.tmp_proj
+*_wpftmp.csproj
+*.log
+*.vspscc
+*.vssscc
+.builds
+*.pidb
+*.svclog
+*.scc
+
+# Chutzpah Test files
+_Chutzpah*
+
+# Visual C++ cache files
+ipch/
+*.aps
+*.ncb
+*.opendb
+*.opensdf
+*.sdf
+*.cachefile
+*.VC.db
+*.VC.VC.opendb
+
+# Visual Studio profiler
+*.psess
+*.vsp
+*.vspx
+*.sap
+
+# Visual Studio Trace Files
+*.e2e
+
+# TFS 2012 Local Workspace
+$tf/
+
+# Guidance Automation Toolkit
+*.gpState
+
+# ReSharper is a .NET coding add-in
+_ReSharper*/
+*.[Rr]e[Ss]harper
+*.DotSettings.user
+
+# JustCode is a .NET coding add-in
+.JustCode
+
+# TeamCity is a build add-in
+_TeamCity*
+
+# DotCover is a Code Coverage Tool
+*.dotCover
+
+# AxoCover is a Code Coverage Tool
+.axoCover/*
+!.axoCover/settings.json
+
+# Visual Studio code coverage results
+*.coverage
+*.coveragexml
+
+# NCrunch
+_NCrunch_*
+.*crunch*.local.xml
+nCrunchTemp_*
+
+# MightyMoose
+*.mm.*
+AutoTest.Net/
+
+# Web workbench (sass)
+.sass-cache/
+
+# Installshield output folder
+[Ee]xpress/
+
+# DocProject is a documentation generator add-in
+DocProject/buildhelp/
+DocProject/Help/*.HxT
+DocProject/Help/*.HxC
+DocProject/Help/*.hhc
+DocProject/Help/*.hhk
+DocProject/Help/*.hhp
+DocProject/Help/Html2
+DocProject/Help/html
+
+# Click-Once directory
+publish/
+
+# Publish Web Output
+*.[Pp]ublish.xml
+*.azurePubxml
+# Note: Comment the next line if you want to checkin your web deploy settings,
+# but database connection strings (with potential passwords) will be unencrypted
+*.pubxml
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+
+# Microsoft Azure Web App publish settings. Comment the next line if you want to
+# checkin your Azure Web App publish settings, but sensitive information contained
+# in these scripts will be unencrypted
+PublishScripts/
+
+# NuGet Packages
+*.nupkg
+# The packages folder can be ignored because of Package Restore
+**/[Pp]ackages/*
+# except build/, which is used as an MSBuild target.
+!**/[Pp]ackages/build/
+# Uncomment if necessary however generally it will be regenerated when needed
+#!**/[Pp]ackages/repositories.config
+# NuGet v3's project.json files produces more ignorable files
+*.nuget.props
+*.nuget.targets
+
+# Microsoft Azure Build Output
+csx/
+*.build.csdef
+
+# Microsoft Azure Emulator
+ecf/
+rcf/
+
+# Windows Store app package directories and files
+AppPackages/
+BundleArtifacts/
+Package.StoreAssociation.xml
+_pkginfo.txt
+*.appx
+
+# Visual Studio cache files
+# files ending in .cache can be ignored
+*.[Cc]ache
+# but keep track of directories ending in .cache
+!?*.[Cc]ache/
+
+# Others
+ClientBin/
+~$*
+*~
+*.dbmdl
+*.dbproj.schemaview
+*.jfm
+*.pfx
+*.publishsettings
+orleans.codegen.cs
+
+# Including strong name files can present a security risk
+# (https://github.com/github/gitignore/pull/2483#issue-259490424)
+#*.snk
+
+# Since there are multiple workflows, uncomment next line to ignore bower_components
+# (https://github.com/github/gitignore/pull/1529#issuecomment-104372622)
+#bower_components/
+# ASP.NET Core default setup: bower directory is configured as wwwroot/lib/ and bower restore is true
+**/wwwroot/lib/
+
+# RIA/Silverlight projects
+Generated_Code/
+
+# Backup & report files from converting an old project file
+# to a newer Visual Studio version. Backup files are not needed,
+# because we have git ;-)
+_UpgradeReport_Files/
+Backup*/
+UpgradeLog*.XML
+UpgradeLog*.htm
+ServiceFabricBackup/
+*.rptproj.bak
+
+# SQL Server files
+*.mdf
+*.ldf
+*.ndf
+
+# Business Intelligence projects
+*.rdl.data
+*.bim.layout
+*.bim_*.settings
+*.rptproj.rsuser
+
+# Microsoft Fakes
+FakesAssemblies/
+
+# GhostDoc plugin setting file
+*.GhostDoc.xml
+
+# Node.js Tools for Visual Studio
+.ntvs_analysis.dat
+node_modules/
+
+# Visual Studio 6 build log
+*.plg
+
+# Visual Studio 6 workspace options file
+*.opt
+
+# Visual Studio 6 auto-generated workspace file (contains which files were open etc.)
+*.vbw
+
+# Visual Studio LightSwitch build output
+**/*.HTMLClient/GeneratedArtifacts
+**/*.DesktopClient/GeneratedArtifacts
+**/*.DesktopClient/ModelManifest.xml
+**/*.Server/GeneratedArtifacts
+**/*.Server/ModelManifest.xml
+_Pvt_Extensions
+
+# Paket dependency manager
+.paket/paket.exe
+paket-files/
+
+# FAKE - F# Make
+.fake/
+
+# JetBrains Rider
+.idea/
+*.sln.iml
+
+# CodeRush personal settings
+.cr/personal
+
+# Python Tools for Visual Studio (PTVS)
+__pycache__/
+*.pyc
+
+# Cake - Uncomment if you are using it
+# tools/**
+# !tools/packages.config
+
+# Tabs Studio
+*.tss
+
+# Telerik's JustMock configuration file
+*.jmconfig
+
+# BizTalk build output
+*.btp.cs
+*.btm.cs
+*.odx.cs
+*.xsd.cs
+
+# OpenCover UI analysis results
+OpenCover/
+
+# Azure Stream Analytics local run output
+ASALocalRun/
+
+# MSBuild Binary and Structured Log
+*.binlog
+
+# NVidia Nsight GPU debugger configuration file
+*.nvuser
+
+# MFractors (Xamarin productivity tool) working folder
+.mfractor/
+
+# Local History for Visual Studio
+.localhistory/
+
+# BeatPulse healthcheck temp database 
+healthchecksdb
+
+

Mask.ML.WebApi/Controllers/DiscernController.cs

@@ -0,0 +1,78 @@
+using Mask_MLML.Model;
+using Microsoft.AspNetCore.Http;
+using Microsoft.AspNetCore.Mvc;
+using System;
+using System.IO;
+using System.Linq;
+
+namespace Mask.ML.WebApi.Controllers
+{
+    [ApiController]
+    public class DiscernController : ControllerBase
+    {
+        /// <summary>
+        /// 上传文件：口罩验证
+        /// </summary>
+        /// <param name="stream"></param>
+        /// <param name="fileName"></param>
+        [HttpPost("upload")]
+        [Route("api/discern/upload")]
+        public IActionResult UploadFile([FromForm] IFormCollection collection)
+        {
+            //申明返回的结果
+            string result = "";
+            FormFileCollection filelist = (FormFileCollection)collection.Files;
+            //检查是否有文件提交上来
+            if (filelist != null && filelist.Any())
+            {
+                //我们只做第一个文件的检查
+                IFormFile file = filelist[0];
+                //做随机数，用到文件夹名字上，防重名
+                Random random = new Random();
+                string r = "";
+                int i;
+                for (i = 1; i < 11; i++)
+                {
+                    r += random.Next(0, 9).ToString();
+                }
+                //文件路径
+                string FilePath = AppDomain.CurrentDomain.BaseDirectory+"/TempFiles/";
+                string name = file.FileName;
+                string FileName = DateTime.Now.ToString("yyyyMMddHHmmssfff") + r;
+                //获取文件类型
+                string type = System.IO.Path.GetExtension(name);
+                DirectoryInfo di = new DirectoryInfo(FilePath);
+                if (!di.Exists)
+                {
+                    di.Create();
+                }
+                //文件保存的路径
+                var filefullname = FilePath + FileName + type;
+                using (FileStream fs = System.IO.File.Create(filefullname))
+                {
+                    // 复制文件
+                    file.CopyTo(fs);
+                    // 清空缓冲区数据
+                    fs.Flush();
+                    fs.Close();
+                    fs.Dispose();
+                }
+                //成功提示赋值到返回结果中
+                //result = "文件上传成功";
+
+                // 创建样例数据的单个实例对模型输入数据集的第一行
+                ModelInput sampleData = new ModelInput()
+                {
+                    ImageSource = filefullname,
+                };
+                // 获取预测结果
+                var predictionResult = ConsumeModel.Predict(sampleData);
+                //System.IO.File.Delete(filefullname);
+                return Ok(predictionResult.Prediction);
+            }
+            return NoContent();
+        }
+
+    }
+}
+

Mask.ML.WebApi/Mask.ML.WebApi.csproj

@@ -0,0 +1,15 @@
+<Project Sdk="Microsoft.NET.Sdk.Web">
+
+  <PropertyGroup>
+    <TargetFramework>net5.0</TargetFramework>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Swashbuckle.AspNetCore" Version="5.6.3" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\Mask.MLML.Model\Mask.MLML.Model.csproj" />
+  </ItemGroup>
+
+</Project>

Mask.ML.WebApi/Program.cs

@@ -0,0 +1,26 @@
+using Microsoft.AspNetCore.Hosting;
+using Microsoft.Extensions.Configuration;
+using Microsoft.Extensions.Hosting;
+using Microsoft.Extensions.Logging;
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Threading.Tasks;
+
+namespace Mask.ML.WebApi
+{
+    public class Program
+    {
+        public static void Main(string[] args)
+        {
+            CreateHostBuilder(args).Build().Run();
+        }
+
+        public static IHostBuilder CreateHostBuilder(string[] args) =>
+            Host.CreateDefaultBuilder(args)
+                .ConfigureWebHostDefaults(webBuilder =>
+                {
+                    webBuilder.UseStartup<Startup>();
+                });
+    }
+}

Mask.ML.WebApi/Properties/launchSettings.json

@@ -0,0 +1,23 @@
+{
+  "$schema": "http://json.schemastore.org/launchsettings.json",
+  "iisSettings": {
+    "windowsAuthentication": false,
+    "anonymousAuthentication": true,
+    "iisExpress": {
+      "applicationUrl": "http://localhost:16529",
+      "sslPort": 0
+    }
+  },
+  "profiles": {
+    "Mask.ML.WebApi": {
+      "commandName": "Project",
+      "dotnetRunMessages": "true",
+      "launchBrowser": true,
+      "launchUrl": "",
+      "applicationUrl": "http://localhost:5000",
+      "environmentVariables": {
+        "ASPNETCORE_ENVIRONMENT": "Development"
+      }
+    }
+  }
+}

Mask.ML.WebApi/Startup.cs

@@ -0,0 +1,50 @@
+using Microsoft.AspNetCore.Builder;
+using Microsoft.AspNetCore.Hosting;
+using Microsoft.AspNetCore.Mvc;
+using Microsoft.Extensions.Configuration;
+using Microsoft.Extensions.DependencyInjection;
+using Microsoft.Extensions.Hosting;
+using Microsoft.Extensions.Logging;
+using Microsoft.OpenApi.Models;
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Threading.Tasks;
+
+namespace Mask.ML.WebApi
+{
+    public class Startup
+    {
+        public Startup(IConfiguration configuration)
+        {
+            Configuration = configuration;
+        }
+
+        public IConfiguration Configuration { get; }
+
+        // This method gets called by the runtime. Use this method to add services to the container.
+        public void ConfigureServices(IServiceCollection services)
+        {
+
+            services.AddControllers();
+        }
+
+        // This method gets called by the runtime. Use this method to configure the HTTP request pipeline.
+        public void Configure(IApplicationBuilder app, IWebHostEnvironment env)
+        {
+            if (env.IsDevelopment())
+            {
+                app.UseDeveloperExceptionPage();
+            }
+
+            app.UseRouting();
+
+            app.UseAuthorization();
+
+            app.UseEndpoints(endpoints =>
+            {
+                endpoints.MapControllers();
+            });
+        }
+    }
+}

Mask.ML.WebApi/appsettings.Development.json

@@ -0,0 +1,9 @@
+{
+  "Logging": {
+    "LogLevel": {
+      "Default": "Information",
+      "Microsoft": "Warning",
+      "Microsoft.Hosting.Lifetime": "Information"
+    }
+  }
+}

Mask.ML.WebApi/appsettings.json

@@ -0,0 +1,10 @@
+{
+  "Logging": {
+    "LogLevel": {
+      "Default": "Information",
+      "Microsoft": "Warning",
+      "Microsoft.Hosting.Lifetime": "Information"
+    }
+  },
+  "AllowedHosts": "*"
+}

Mask.ML.sln

@@ -0,0 +1,37 @@
+
+Microsoft Visual Studio Solution File, Format Version 12.00
+# Visual Studio Version 16
+VisualStudioVersion = 16.0.31205.134
+MinimumVisualStudioVersion = 10.0.40219.1
+Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Mask.MLML.Model", "Mask.MLML.Model\Mask.MLML.Model.csproj", "{952B032F-6FFE-45E8-B7B0-5A806DDBD922}"
+EndProject
+Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Mask.MLML.ConsoleApp", "Mask.MLML.ConsoleApp\Mask.MLML.ConsoleApp.csproj", "{B3C06518-648F-4430-815D-FEC905FE3DD7}"
+EndProject
+Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "Mask.ML.WebApi", "Mask.ML.WebApi\Mask.ML.WebApi.csproj", "{64704ACF-F0F9-4442-BEC5-3279C27B332C}"
+EndProject
+Global
+	GlobalSection(SolutionConfigurationPlatforms) = preSolution
+		Debug|Any CPU = Debug|Any CPU
+		Release|Any CPU = Release|Any CPU
+	EndGlobalSection
+	GlobalSection(ProjectConfigurationPlatforms) = postSolution
+		{952B032F-6FFE-45E8-B7B0-5A806DDBD922}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{952B032F-6FFE-45E8-B7B0-5A806DDBD922}.Debug|Any CPU.Build.0 = Debug|Any CPU
+		{952B032F-6FFE-45E8-B7B0-5A806DDBD922}.Release|Any CPU.ActiveCfg = Release|Any CPU
+		{952B032F-6FFE-45E8-B7B0-5A806DDBD922}.Release|Any CPU.Build.0 = Release|Any CPU
+		{B3C06518-648F-4430-815D-FEC905FE3DD7}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{B3C06518-648F-4430-815D-FEC905FE3DD7}.Debug|Any CPU.Build.0 = Debug|Any CPU
+		{B3C06518-648F-4430-815D-FEC905FE3DD7}.Release|Any CPU.ActiveCfg = Release|Any CPU
+		{B3C06518-648F-4430-815D-FEC905FE3DD7}.Release|Any CPU.Build.0 = Release|Any CPU
+		{64704ACF-F0F9-4442-BEC5-3279C27B332C}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{64704ACF-F0F9-4442-BEC5-3279C27B332C}.Debug|Any CPU.Build.0 = Debug|Any CPU
+		{64704ACF-F0F9-4442-BEC5-3279C27B332C}.Release|Any CPU.ActiveCfg = Release|Any CPU
+		{64704ACF-F0F9-4442-BEC5-3279C27B332C}.Release|Any CPU.Build.0 = Release|Any CPU
+	EndGlobalSection
+	GlobalSection(SolutionProperties) = preSolution
+		HideSolutionNode = FALSE
+	EndGlobalSection
+	GlobalSection(ExtensibilityGlobals) = postSolution
+		SolutionGuid = {657EECC1-C95E-4F8E-BD19-7DEF54F69392}
+	EndGlobalSection
+EndGlobal

Mask.MLML.ConsoleApp/Mask.MLML.ConsoleApp.csproj

@@ -0,0 +1,20 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>netcoreapp3.1</TargetFramework>
+  </PropertyGroup>
+  <ItemGroup>
+    <PackageReference Include="Microsoft.ML" Version="1.5.0-preview2" />
+    <PackageReference Include="Microsoft.ML.ImageAnalytics" Version="1.5.0-preview2" />
+    <PackageReference Include="Microsoft.ML.Vision" Version="1.5.0-preview2" />
+	<PackageReference Include="SciSharp.TensorFlow.Redist" Version="1.14.0" />
+  </ItemGroup>
+  <ItemGroup>
+    <ProjectReference Include="..\Mask.MLML.Model\Mask.MLML.Model.csproj" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectCapability Include="ModelBuilderGenerated" />
+  </ItemGroup>
+</Project>

Mask.MLML.ConsoleApp/ModelBuilder.cs

@@ -0,0 +1,161 @@
+// This file was auto-generated by ML.NET Model Builder. 
+
+using System;
+using System.Collections.Generic;
+using System.IO;
+using System.Linq;
+using Microsoft.ML;
+using Microsoft.ML.Data;
+using Mask_MLML.Model;
+using Microsoft.ML.Vision;
+
+namespace Mask_MLML.ConsoleApp
+{
+    public static class ModelBuilder
+    {
+        private static string TRAIN_DATA_FILEPATH = @"C:\Users\HUAWEI\AppData\Local\Temp\b441e20c-6f79-4437-a21a-be0014456e13.tsv";
+        private static string MODEL_FILEPATH = @"C:\Users\HUAWEI\AppData\Local\Temp\MLVSTools\Mask.MLML\Mask.MLML.Model\MLModel.zip";
+        // Create MLContext to be shared across the model creation workflow objects 
+        // Set a random seed for repeatable/deterministic results across multiple trainings.
+        private static MLContext mlContext = new MLContext(seed: 1);
+
+        public static void CreateModel()
+        {
+            // Load Data
+            IDataView trainingDataView = mlContext.Data.LoadFromTextFile<ModelInput>(
+                                            path: TRAIN_DATA_FILEPATH,
+                                            hasHeader: true,
+                                            separatorChar: '\t',
+                                            allowQuoting: true,
+                                            allowSparse: false);
+
+            // Build training pipeline
+            IEstimator<ITransformer> trainingPipeline = BuildTrainingPipeline(mlContext);
+
+            // Train Model
+            ITransformer mlModel = TrainModel(mlContext, trainingDataView, trainingPipeline);
+
+            // Evaluate quality of Model
+            Evaluate(mlContext, trainingDataView, trainingPipeline);
+
+            // Save model
+            SaveModel(mlContext, mlModel, MODEL_FILEPATH, trainingDataView.Schema);
+        }
+
+        public static IEstimator<ITransformer> BuildTrainingPipeline(MLContext mlContext)
+        {
+            // Data process configuration with pipeline data transformations 
+            var dataProcessPipeline = mlContext.Transforms.Conversion.MapValueToKey("Label", "Label")
+                                      .Append(mlContext.Transforms.LoadRawImageBytes("ImageSource_featurized", null, "ImageSource"))
+                                      .Append(mlContext.Transforms.CopyColumns("Features", "ImageSource_featurized"));
+            // Set the training algorithm 
+            var trainer = mlContext.MulticlassClassification.Trainers.ImageClassification(new ImageClassificationTrainer.Options() { LabelColumnName = "Label", FeatureColumnName = "Features" })
+                                      .Append(mlContext.Transforms.Conversion.MapKeyToValue("PredictedLabel", "PredictedLabel"));
+
+            var trainingPipeline = dataProcessPipeline.Append(trainer);
+
+            return trainingPipeline;
+        }
+
+        public static ITransformer TrainModel(MLContext mlContext, IDataView trainingDataView, IEstimator<ITransformer> trainingPipeline)
+        {
+            Console.WriteLine("=============== Training  model ===============");
+
+            ITransformer model = trainingPipeline.Fit(trainingDataView);
+
+            Console.WriteLine("=============== End of training process ===============");
+            return model;
+        }
+
+        private static void Evaluate(MLContext mlContext, IDataView trainingDataView, IEstimator<ITransformer> trainingPipeline)
+        {
+            // Cross-Validate with single dataset (since we don't have two datasets, one for training and for evaluate)
+            // in order to evaluate and get the model's accuracy metrics
+            Console.WriteLine("=============== Cross-validating to get model's accuracy metrics ===============");
+            var crossValidationResults = mlContext.MulticlassClassification.CrossValidate(trainingDataView, trainingPipeline, numberOfFolds: 5, labelColumnName: "Label");
+            PrintMulticlassClassificationFoldsAverageMetrics(crossValidationResults);
+        }
+
+        private static void SaveModel(MLContext mlContext, ITransformer mlModel, string modelRelativePath, DataViewSchema modelInputSchema)
+        {
+            // Save/persist the trained model to a .ZIP file
+            Console.WriteLine($"=============== Saving the model  ===============");
+            mlContext.Model.Save(mlModel, modelInputSchema, GetAbsolutePath(modelRelativePath));
+            Console.WriteLine("The model is saved to {0}", GetAbsolutePath(modelRelativePath));
+        }
+
+        public static string GetAbsolutePath(string relativePath)
+        {
+            FileInfo _dataRoot = new FileInfo(typeof(Program).Assembly.Location);
+            string assemblyFolderPath = _dataRoot.Directory.FullName;
+
+            string fullPath = Path.Combine(assemblyFolderPath, relativePath);
+
+            return fullPath;
+        }
+
+        public static void PrintMulticlassClassificationMetrics(MulticlassClassificationMetrics metrics)
+        {
+            Console.WriteLine($"************************************************************");
+            Console.WriteLine($"*    Metrics for multi-class classification model   ");
+            Console.WriteLine($"*-----------------------------------------------------------");
+            Console.WriteLine($"    MacroAccuracy = {metrics.MacroAccuracy:0.####}, a value between 0 and 1, the closer to 1, the better");
+            Console.WriteLine($"    MicroAccuracy = {metrics.MicroAccuracy:0.####}, a value between 0 and 1, the closer to 1, the better");
+            Console.WriteLine($"    LogLoss = {metrics.LogLoss:0.####}, the closer to 0, the better");
+            for (int i = 0; i < metrics.PerClassLogLoss.Count; i++)
+            {
+                Console.WriteLine($"    LogLoss for class {i + 1} = {metrics.PerClassLogLoss[i]:0.####}, the closer to 0, the better");
+            }
+            Console.WriteLine($"************************************************************");
+        }
+
+        public static void PrintMulticlassClassificationFoldsAverageMetrics(IEnumerable<TrainCatalogBase.CrossValidationResult<MulticlassClassificationMetrics>> crossValResults)
+        {
+            var metricsInMultipleFolds = crossValResults.Select(r => r.Metrics);
+
+            var microAccuracyValues = metricsInMultipleFolds.Select(m => m.MicroAccuracy);
+            var microAccuracyAverage = microAccuracyValues.Average();
+            var microAccuraciesStdDeviation = CalculateStandardDeviation(microAccuracyValues);
+            var microAccuraciesConfidenceInterval95 = CalculateConfidenceInterval95(microAccuracyValues);
+
+            var macroAccuracyValues = metricsInMultipleFolds.Select(m => m.MacroAccuracy);
+            var macroAccuracyAverage = macroAccuracyValues.Average();
+            var macroAccuraciesStdDeviation = CalculateStandardDeviation(macroAccuracyValues);
+            var macroAccuraciesConfidenceInterval95 = CalculateConfidenceInterval95(macroAccuracyValues);
+
+            var logLossValues = metricsInMultipleFolds.Select(m => m.LogLoss);
+            var logLossAverage = logLossValues.Average();
+            var logLossStdDeviation = CalculateStandardDeviation(logLossValues);
+            var logLossConfidenceInterval95 = CalculateConfidenceInterval95(logLossValues);
+
+            var logLossReductionValues = metricsInMultipleFolds.Select(m => m.LogLossReduction);
+            var logLossReductionAverage = logLossReductionValues.Average();
+            var logLossReductionStdDeviation = CalculateStandardDeviation(logLossReductionValues);
+            var logLossReductionConfidenceInterval95 = CalculateConfidenceInterval95(logLossReductionValues);
+
+            Console.WriteLine($"*************************************************************************************************************");
+            Console.WriteLine($"*       Metrics for Multi-class Classification model      ");
+            Console.WriteLine($"*------------------------------------------------------------------------------------------------------------");
+            Console.WriteLine($"*       Average MicroAccuracy:    {microAccuracyAverage:0.###}  - Standard deviation: ({microAccuraciesStdDeviation:#.###})  - Confidence Interval 95%: ({microAccuraciesConfidenceInterval95:#.###})");
+            Console.WriteLine($"*       Average MacroAccuracy:    {macroAccuracyAverage:0.###}  - Standard deviation: ({macroAccuraciesStdDeviation:#.###})  - Confidence Interval 95%: ({macroAccuraciesConfidenceInterval95:#.###})");
+            Console.WriteLine($"*       Average LogLoss:          {logLossAverage:#.###}  - Standard deviation: ({logLossStdDeviation:#.###})  - Confidence Interval 95%: ({logLossConfidenceInterval95:#.###})");
+            Console.WriteLine($"*       Average LogLossReduction: {logLossReductionAverage:#.###}  - Standard deviation: ({logLossReductionStdDeviation:#.###})  - Confidence Interval 95%: ({logLossReductionConfidenceInterval95:#.###})");
+            Console.WriteLine($"*************************************************************************************************************");
+
+        }
+
+        public static double CalculateStandardDeviation(IEnumerable<double> values)
+        {
+            double average = values.Average();
+            double sumOfSquaresOfDifferences = values.Select(val => (val - average) * (val - average)).Sum();
+            double standardDeviation = Math.Sqrt(sumOfSquaresOfDifferences / (values.Count() - 1));
+            return standardDeviation;
+        }
+
+        public static double CalculateConfidenceInterval95(IEnumerable<double> values)
+        {
+            double confidenceInterval95 = 1.96 * CalculateStandardDeviation(values) / Math.Sqrt((values.Count() - 1));
+            return confidenceInterval95;
+        }
+    }
+}

Mask.MLML.ConsoleApp/Program.cs

@@ -0,0 +1,28 @@
+// This file was auto-generated by ML.NET Model Builder. 
+
+using System;
+using Mask_MLML.Model;
+
+namespace Mask_MLML.ConsoleApp
+{
+    class Program
+    {
+        static void Main(string[] args)
+        {
+            // Create single instance of sample data from first line of dataset for model input
+            ModelInput sampleData = new ModelInput()
+            {
+                ImageSource = @"D:\LancerProject\VsProject\Mask.ML\ImageData\已戴\1.jpg",
+            };
+
+            // Make a single prediction on the sample data and print results
+            var predictionResult = ConsumeModel.Predict(sampleData);
+
+            Console.WriteLine("Using model to make single prediction -- Comparing actual Label with predicted Label from sample data...\n\n");
+            Console.WriteLine($"ImageSource: {sampleData.ImageSource}");
+            Console.WriteLine($"\n\nPredicted Label value {predictionResult.Prediction} \nPredicted Label scores: [{String.Join(",", predictionResult.Score)}]\n\n");
+            Console.WriteLine("=============== End of process, hit any key to finish ===============");
+            Console.ReadKey();
+        }
+    }
+}

Mask.MLML.Model/ConsumeModel.cs

@@ -0,0 +1,37 @@
+// This file was auto-generated by ML.NET Model Builder. 
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using Microsoft.ML;
+using Mask_MLML.Model;
+
+namespace Mask_MLML.Model
+{
+    public class ConsumeModel
+    {
+        private static Lazy<PredictionEngine<ModelInput, ModelOutput>> PredictionEngine = new Lazy<PredictionEngine<ModelInput, ModelOutput>>(CreatePredictionEngine);
+
+        // For more info on consuming ML.NET models, visit https://aka.ms/mlnet-consume
+        // Method for consuming model in your app
+        public static ModelOutput Predict(ModelInput input)
+        {
+            ModelOutput result = PredictionEngine.Value.Predict(input);
+            return result;
+        }
+
+        public static PredictionEngine<ModelInput, ModelOutput> CreatePredictionEngine()
+        {
+            // Create new MLContext
+            MLContext mlContext = new MLContext();
+
+            // Load model & create prediction engine
+            string modelPath = @"C:\Users\HUAWEI\AppData\Local\Temp\MLVSTools\Mask.MLML\Mask.MLML.Model\MLModel.zip";
+            ITransformer mlModel = mlContext.Model.Load(modelPath, out var modelInputSchema);
+            var predEngine = mlContext.Model.CreatePredictionEngine<ModelInput, ModelOutput>(mlModel);
+
+            return predEngine;
+        }
+    }
+}

Mask.MLML.Model/Mask.MLML.Model.csproj

@@ -0,0 +1,22 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <TargetFramework>netstandard2.0</TargetFramework>
+  </PropertyGroup>
+  <ItemGroup>
+    <PackageReference Include="Microsoft.ML" Version="1.5.0-preview2" />
+    <PackageReference Include="Microsoft.ML.ImageAnalytics" Version="1.5.0-preview2" />
+    <PackageReference Include="Microsoft.ML.Vision" Version="1.5.0-preview2" />
+	<PackageReference Include="SciSharp.TensorFlow.Redist" Version="1.14.0" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <None Update="MLModel.zip">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </None>
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectCapability Include="ModelBuilderGenerated" />
+  </ItemGroup>
+</Project>

Mask.MLML.Model/ModelInput.cs

@@ -0,0 +1,18 @@
+// This file was auto-generated by ML.NET Model Builder. 
+
+using Microsoft.ML.Data;
+
+namespace Mask_MLML.Model
+{
+    public class ModelInput
+    {
+        [ColumnName("Label"), LoadColumn(0)]
+        public string Label { get; set; }
+
+
+        [ColumnName("ImageSource"), LoadColumn(1)]
+        public string ImageSource { get; set; }
+
+
+    }
+}

Mask.MLML.Model/ModelOutput.cs

@@ -0,0 +1,16 @@
+// This file was auto-generated by ML.NET Model Builder. 
+
+using System;
+using Microsoft.ML.Data;
+
+namespace Mask_MLML.Model
+{
+    public class ModelOutput
+    {
+        // ColumnName attribute is used to change the column name from
+        // its default value, which is the name of the field.
+        [ColumnName("PredictedLabel")]
+        public String Prediction { get; set; }
+        public float[] Score { get; set; }
+    }
+}