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/WinFrameworks/Windows ML Test
Required plugins for this example: MBS WinFrameworks Plugin
You find this example project in your Plugins Download as a Xojo project file within the examples folder: /WinFrameworks/Windows ML Test
This example is the version from Tue, 28th Sep 2020.
Project "Windows ML Test.xojo_binary_project"
Class App Inherits Application
Const kEditClear = "&Delete"
Const kFileQuit = "&Quit"
Const kFileQuitShortcut = ""
End Class
Class MainWindow Inherits Window
Control List Inherits Listbox
ControlInstance List Inherits Listbox
End Control
EventHandler Sub Open() // Learn about Windows AI // // this example is based on Desktop version of SqueezeNetObjectDetection sample: // // get model here: Dim ModelFile As FolderItem =SpecialFolder.Desktop.Child("SqueezeNet.onnx") if not ModelFile.Exists then MsgBox "Please download model first!" quit end if dim model as WinLearningModelMBS = WinLearningModelMBS.LoadFromFile(ModelFile) if model = nil then msgbox "Failed to load model!" // Check path and you need Windows 10 quit End If List.AddRow "Author", model.Author List.AddRow "Description", model.Description List.AddRow "Domain", model.Domain List.AddRow "Name", model.Name List.AddRow "Version", Str(model.Version) list.AddRow "" dim metadata as Dictionary = model.Metadata if metadata <> Nil then for each key as Variant in metadata.keys list.AddRow key.StringValue, metadata.Value(key).StringValue next list.AddRow "" end if Dim inputFeatures() As WinLearningModelFeatureDescriptorMBS = model.InputFeatures for each feature as WinLearningModelFeatureDescriptorMBS in inputFeatures list.AddRow "Input "+feature.Name, feature.KindString + " " + feature.Extra + " " + feature.Description next dim outputFeatures() as WinLearningModelFeatureDescriptorMBS = model.OutputFeatures for each feature as WinLearningModelFeatureDescriptorMBS in outputFeatures list.AddRow "Output "+feature.Name, feature.KindString + " " + feature.Extra + " " + feature.Description next // try it // get image file here: dim ImageFile as FolderItem = SpecialFolder.Desktop.Child("kitten_224.png") if not ImageFile.Exists then return // first output should be tensor feature for this model and has the shape dim outputFeature as WinLearningModelTensorFeatureDescriptorMBS = WinLearningModelTensorFeatureDescriptorMBS(outputFeatures(0)) dim shape() as integer = outputFeature.Shape // { 1, 1000, 1, 1 } dim session as new WinLearningModelSessionMBS(model) dim binding as new WinLearningModelBindingMBS(session) binding.BindWithImage("data_0", ImageFile) // fill value with image binding.BindWithFloat("softmaxout_1", shape, nil) // create output array with right shape dim result as WinLearningModelEvaluationResultMBS = session.Evaluate(binding) // check result list.AddRow "" dim ErrorStatus as integer = result.ErrorStatus dim OutputNames() as string = result.OutputNames if result.Succeeded then dim values() as single = result.GetTensorFloat("softmaxout_1") // Labels.txt from dim LabelFile as FolderItem = SpecialFolder.Desktop.Child("Labels.txt") dim LabelDic as new Dictionary if LabelFile.Exists then dim t as TextInputStream = TextInputStream.Open(LabelFile) while not t.eof dim line as string = t.ReadLine if line.len > 0 then dim p as integer = line.instr(",") if p > 0 then Dim keyStr As String = line.Left(p-1) Dim keyInt As Integer = Val(keyStr) Dim ValueStr As String = line.Mid(p+1) LabelDic.Value(keyInt) = ValueStr end if end if wend end if dim Indexes() as integer for i as integer = 0 to values.Ubound indexes.Append i next values.SortWith(indexes) // show last 5 entries with highest priority dim u as integer = values.Ubound for i as integer = u downto u - 4 list.AddRow labeldic.Lookup(indexes(i), "no label"), Str(values(i)) Next end if End EventHandler
End Class
MenuBar MainMenuBar
MenuItem FileMenu = "&File"
MenuItem FileQuit = "#App.kFileQuit"
MenuItem EditMenu = "&Edit"
MenuItem EditUndo = "&Undo"
MenuItem EditSeparator1 = "-"
MenuItem EditCut = "Cu&t"
MenuItem EditCopy = "&Copy"
MenuItem EditPaste = "&Paste"
MenuItem EditClear = "#App.kEditClear"
MenuItem EditSeparator2 = "-"
MenuItem EditSelectAll = "Select &All"
End MenuBar
Module UtilModule
Function Extra(extends feature as WinLearningModelFeatureDescriptorMBS) As string if feature isa WinLearningModelTensorFeatureDescriptorMBS then dim f as WinLearningModelTensorFeatureDescriptorMBS = WinLearningModelTensorFeatureDescriptorMBS(feature) dim shape() as integer = f.Shape dim shapes() as string for each s as integer in shape shapes.Append Str(s) next return f.TensorKindName + " (" + join(shapes, ", ") + ")" end if if feature isa WinLearningModelImageFeatureDescriptorMBS then dim f as WinLearningModelImageFeatureDescriptorMBS = WinLearningModelImageFeatureDescriptorMBS(feature) Return Str(f.Width) + "x" + Str(f.Height) end if if feature isa WinLearningModelSequenceFeatureDescriptorMBS then dim f as WinLearningModelSequenceFeatureDescriptorMBS = WinLearningModelSequenceFeatureDescriptorMBS(feature) Return f.ElementDescriptor.Name+" "+f.ElementDescriptor.KindString end if if feature isa WinLearningModelMapFeatureDescriptorMBS then dim f as WinLearningModelMapFeatureDescriptorMBS = WinLearningModelMapFeatureDescriptorMBS(feature) Return f.ValueDescriptor.Name+" "+f.ValueDescriptor.KindString End If End Function
Function KindString(extends m as WinLearningModelFeatureDescriptorMBS) As string Select case m.Kind case m.KindImage return "Image" case m.KindMap return "Map" case m.KindSequence return "Sequence" case m.KindTensor return "Tensor" Else Return str(m.Kind) end Select End Function
Function TensorKindName(extends m as WinLearningModelTensorFeatureDescriptorMBS) As string Select case m.TensorKind case m.TensorKindBoolean return "Boolean" case m.TensorKindComplex128 return "Complex128" case m.TensorKindComplex64 return "Complex64" case m.TensorKindDouble return "Double" case m.TensorKindFloat return "Float" case m.TensorKindFloat16 return "Float16" case m.TensorKindInt16 return "Int16" case m.TensorKindInt32 return "Int32" case m.TensorKindInt64 return "Int64" case m.TensorKindInt8 return "Int8" case m.TensorKindString return "String" case m.TensorKindUInt16 return "UInt16" case m.TensorKindUInt32 return "UInt32" case m.TensorKindUInt64 return "UInt64" case m.TensorKindUInt8 return "UInt8" else Return str(m.TensorKind) end Select End Function
End Module
End Project

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