commit 5e08f0b7d579515f348f8700ad9d6a81aae06285 Author: pscgyLancer <1971408908@qq.com> Date: Mon Jun 13 17:41:33 2022 +0800 frist commit diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..eab4de4 --- /dev/null +++ b/.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 +*.publishproj + +# Microsoft Azure Web App publish settings. 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+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 + { + /// + /// 上传文件：口罩验证 + /// + /// + /// + [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(); + } + + } +} + diff --git a/Mask.ML.WebApi/Mask.ML.WebApi.csproj b/Mask.ML.WebApi/Mask.ML.WebApi.csproj new file mode 100644 index 0000000..bb1dd8b --- /dev/null +++ b/Mask.ML.WebApi/Mask.ML.WebApi.csproj @@ -0,0 +1,15 @@ + + + + net5.0 + + + + + + + + + + + diff --git a/Mask.ML.WebApi/Program.cs b/Mask.ML.WebApi/Program.cs new file mode 100644 index 0000000..ab444bf --- /dev/null +++ b/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(); + }); + } +} diff --git a/Mask.ML.WebApi/Properties/launchSettings.json b/Mask.ML.WebApi/Properties/launchSettings.json new file mode 100644 index 0000000..2c7c41e --- /dev/null +++ b/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" + } + } + } +} diff --git a/Mask.ML.WebApi/Startup.cs b/Mask.ML.WebApi/Startup.cs new file mode 100644 index 0000000..74c6582 --- /dev/null +++ b/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(); + }); + } + } +} diff --git a/Mask.ML.WebApi/appsettings.Development.json b/Mask.ML.WebApi/appsettings.Development.json new file mode 100644 index 0000000..8983e0f --- /dev/null +++ b/Mask.ML.WebApi/appsettings.Development.json @@ -0,0 +1,9 @@ +{ + "Logging": { + "LogLevel": { + "Default": "Information", + "Microsoft": "Warning", + "Microsoft.Hosting.Lifetime": "Information" + } + } +} diff --git a/Mask.ML.WebApi/appsettings.json b/Mask.ML.WebApi/appsettings.json new file mode 100644 index 0000000..d9d9a9b --- /dev/null +++ b/Mask.ML.WebApi/appsettings.json @@ -0,0 +1,10 @@ +{ + "Logging": { + "LogLevel": { + "Default": "Information", + "Microsoft": "Warning", + "Microsoft.Hosting.Lifetime": "Information" + } + }, + "AllowedHosts": "*" +} diff --git a/Mask.ML.sln b/Mask.ML.sln new file mode 100644 index 0000000..170a5f0 --- /dev/null +++ b/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 diff --git a/Mask.MLML.ConsoleApp/Mask.MLML.ConsoleApp.csproj b/Mask.MLML.ConsoleApp/Mask.MLML.ConsoleApp.csproj new file mode 100644 index 0000000..ec6154d --- /dev/null +++ b/Mask.MLML.ConsoleApp/Mask.MLML.ConsoleApp.csproj @@ -0,0 +1,20 @@ + + + + Exe + netcoreapp3.1 + + + + + + + + + + + + + + + diff --git a/Mask.MLML.ConsoleApp/ModelBuilder.cs b/Mask.MLML.ConsoleApp/ModelBuilder.cs new file mode 100644 index 0000000..8b749c0 --- /dev/null +++ b/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( + path: TRAIN_DATA_FILEPATH, + hasHeader: true, + separatorChar: '\t', + allowQuoting: true, + allowSparse: false); + + // Build training pipeline + IEstimator 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 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 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 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($"************************************************************"); + } + + public static void PrintMulticlassClassificationFoldsAverageMetrics(IEnumerable> crossValResults) + { + var metricsInMultipleFolds = crossValResults.Select(r => r.Metrics); + + var microAccuracyValues = metricsInMultipleFolds.Select(m => m.MicroAccuracy); + var microAccuracyAverage = microAccuracyValues.Average(); + var microAccuraciesStdDeviation = CalculateStandardDeviation(microAccuracyValues); + var microAccuraciesConfidenceInterval95 = CalculateConfidenceInterval95(microAccuracyValues); + + var macroAccuracyValues = metricsInMultipleFolds.Select(m => m.MacroAccuracy); + var macroAccuracyAverage = macroAccuracyValues.Average(); + var macroAccuraciesStdDeviation = CalculateStandardDeviation(macroAccuracyValues); + var macroAccuraciesConfidenceInterval95 = CalculateConfidenceInterval95(macroAccuracyValues); + + var logLossValues = metricsInMultipleFolds.Select(m => m.LogLoss); + var logLossAverage = logLossValues.Average(); + var logLossStdDeviation = CalculateStandardDeviation(logLossValues); + var logLossConfidenceInterval95 = CalculateConfidenceInterval95(logLossValues); + + var logLossReductionValues = metricsInMultipleFolds.Select(m => m.LogLossReduction); + var logLossReductionAverage = logLossReductionValues.Average(); + var logLossReductionStdDeviation = CalculateStandardDeviation(logLossReductionValues); + var logLossReductionConfidenceInterval95 = CalculateConfidenceInterval95(logLossReductionValues); + + Console.WriteLine($"*************************************************************************************************************"); + 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($"*************************************************************************************************************"); + + } + + public static double CalculateStandardDeviation(IEnumerable values) + { + double average = values.Average(); + double sumOfSquaresOfDifferences = values.Select(val => (val - average) * (val - average)).Sum(); + double standardDeviation = Math.Sqrt(sumOfSquaresOfDifferences / (values.Count() - 1)); + return standardDeviation; + } + + public static double CalculateConfidenceInterval95(IEnumerable values) + { + double confidenceInterval95 = 1.96 * CalculateStandardDeviation(values) / Math.Sqrt((values.Count() - 1)); + return confidenceInterval95; + } + } +} diff --git a/Mask.MLML.ConsoleApp/Program.cs b/Mask.MLML.ConsoleApp/Program.cs new file mode 100644 index 0000000..6474a2a --- /dev/null +++ b/Mask.MLML.ConsoleApp/Program.cs @@ -0,0 +1,28 @@ +// This file was auto-generated by ML.NET Model Builder. + +using System; +using Mask_MLML.Model; + +namespace Mask_MLML.ConsoleApp +{ + class Program + { + static void Main(string[] args) + { + // Create single instance of sample data from first line of dataset for model input + ModelInput sampleData = new ModelInput() + { + ImageSource = @"D:\LancerProject\VsProject\Mask.ML\ImageData\已戴\1.jpg", + }; + + // Make a single prediction on the sample data and print results + var predictionResult = ConsumeModel.Predict(sampleData); + + Console.WriteLine("Using model to make single prediction -- Comparing actual Label with predicted Label from sample data...\n\n"); + Console.WriteLine($"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(); + } + } +} diff --git a/Mask.MLML.Model/ConsumeModel.cs b/Mask.MLML.Model/ConsumeModel.cs new file mode 100644 index 0000000..f48f563 --- /dev/null +++ b/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 = new Lazy>(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 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(mlModel); + + return predEngine; + } + } +} diff --git a/Mask.MLML.Model/MLModel.zip b/Mask.MLML.Model/MLModel.zip new file mode 100644 index 0000000..b182d4e Binary files /dev/null and b/Mask.MLML.Model/MLModel.zip differ diff --git a/Mask.MLML.Model/Mask.MLML.Model.csproj b/Mask.MLML.Model/Mask.MLML.Model.csproj new file mode 100644 index 0000000..077eb17 --- /dev/null +++ b/Mask.MLML.Model/Mask.MLML.Model.csproj @@ -0,0 +1,22 @@ + + + + netstandard2.0 + + + + + + + + + + + PreserveNewest + + + + + + + diff --git a/Mask.MLML.Model/ModelInput.cs b/Mask.MLML.Model/ModelInput.cs new file mode 100644 index 0000000..d0f6d19 --- /dev/null +++ b/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; } + + + } +} diff --git a/Mask.MLML.Model/ModelOutput.cs b/Mask.MLML.Model/ModelOutput.cs new file mode 100644 index 0000000..cc20cde --- /dev/null +++ b/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; } + } +}