NboxTrainer 1.0.0.2
dotnet add package NboxTrainer --version 1.0.0.2
NuGet\Install-Package NboxTrainer -Version 1.0.0.2
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.
<PackageReference Include="NboxTrainer" Version="1.0.0.2" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add NboxTrainer --version 1.0.0.2
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
#r "nuget: NboxTrainer, 1.0.0.2"
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.
// Install NboxTrainer as a Cake Addin #addin nuget:?package=NboxTrainer&version=1.0.0.2 // Install NboxTrainer as a Cake Tool #tool nuget:?package=NboxTrainer&version=1.0.0.2
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
NBox Trainer
Nbox Trainer is library-wrapper for easy creating trainer ml models of image classification with GPU acceleration. Also you can test prediction with prediction service.
Packages
- Microsoft.ML [1.5.4]
- Microsoft.ML.ImageAnalytics [1.5.4]
- Microsoft.ML.Vision [1.5.4]
- SciSharp.TensorFlow.Redist-Windows-GPU [1.5.1]
- CUDA 10.0;
- Cudnn 7.6.4;
Example struct dataset
+---flower_photos
| +---daisy
| +---dandelion
| +---roses
| +---sunflowers
| +---tulips
|--------------------
All top subfolders of dataset catalog will use as label of categories
Example using trainer with fluent builder
string dirDatasets = "D:\\Downloads\\flower_photos\\";
TrainerService trainer = new TrainerService(AppContext.BaseDirectory, "flower")
.setArchitecture(ImageClassificationTrainer.Architecture.MobilenetV2)
.setEpoch(1000)
.setBatchSize(5)
.setLearningRate(0.01F)
.setReuseTrainBottleneckCache(true)
.setReuseValidationBottleneckCache(true)
.setCriteriaEarlyStopping(new ImageClassificationTrainer.EarlyStopping(0.1F, 500,
ImageClassificationTrainer.EarlyStoppingMetric.Accuracy))
.setPathToDataset(dirDatasets)
.setSplitPercent(0.3F);
trainer.onStateChanged += state => { Console.Title = $"Current Stage: {state}"; };
trainer.onTrainMetrics += Trainer_onTrainMetrics;
await trainer.Train();
var _metrics = await trainer.GetMetrics();
await trainer.SaveModel();
Example using prediction service with fluent builder
PredictorService service = new PredictorService("D:\\flower_photos\\test_fraction\\")
.setPathToModel("D:\\21-01-10_flower.zip");
service.onPrediction += prediction => Console.WriteLine(prediction);
await service.Process();
/* output log with event onPrediction
*
*File: 100080576_f52e8ee070_n.jpg | Predicted: daisy | Accuracy: 0,9956813
*File: 102841525_bd6628ae3c.jpg | Predicted: daisy | Accuracy: 0,99993706
*File: 105806915_a9c13e2106_n.jpg | Predicted: daisy | Accuracy: 0,99083275
*File: 107592979_aaa9cdfe78_m.jpg | Predicted: daisy | Accuracy: 0,9820342
*File: 113902743_8f537f769b_n.jpg | Predicted: tulips | Accuracy: 0,9946406
*File: 113960470_38fab8f2fb_m.jpg | Predicted: tulips | Accuracy: 0,9788831
*File: 116343334_9cb4acdc57_n.jpg | Predicted: tulips | Accuracy: 0,99646
*File: 122450705_9885fff3c4_n.jpg | Predicted: tulips | Accuracy: 0,9952939
*/
Product | Versions Compatible and additional computed target framework versions. |
---|---|
.NET | net5.0 is compatible. net5.0-windows was computed. net6.0 was computed. net6.0-android was computed. net6.0-ios was computed. net6.0-maccatalyst was computed. net6.0-macos was computed. net6.0-tvos was computed. net6.0-windows was computed. net7.0 was computed. net7.0-android was computed. net7.0-ios was computed. net7.0-maccatalyst was computed. net7.0-macos was computed. net7.0-tvos was computed. net7.0-windows was computed. net8.0 was computed. net8.0-android was computed. net8.0-browser was computed. net8.0-ios was computed. net8.0-maccatalyst was computed. net8.0-macos was computed. net8.0-tvos was computed. net8.0-windows was computed. |
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.
-
net5.0
- Microsoft.ML (>= 1.5.4)
- Microsoft.ML.ImageAnalytics (>= 1.5.4)
- Microsoft.ML.Vision (>= 1.5.4)
- SciSharp.TensorFlow.Redist-Windows-GPU (>= 1.15.1)
NuGet packages
This package is not used by any NuGet packages.
GitHub repositories
This package is not used by any popular GitHub repositories.