Windows.ai.machinelearning | Web |

// 1. Preprocess: resize to model input size (224x224) var resized = await ImageHelper.ResizeBitmap(bitmap, 224, 224); // 2. Convert to float tensor (channel-first, normalized) var tensor = ImageHelper.BitmapToTensor(resized);

var result = await session.EvaluateAsync(binding, ""); var classId = result.Outputs["softmaxout"] as TensorFloat; windows.ai.machinelearning

var session = new LearningModelSession(model, device); normalized) var tensor = ImageHelper.BitmapToTensor(resized)

LearningModelSessionOptions options = new LearningModelSessionOptions(); options.CloseModelOnSessionCreation = false; options.LoggingName = "MyModel"; var result = await session.EvaluateAsync(binding

// 3. Load model (cache globally) var model = await App.ModelLoader.GetModelAsync();

// Force GPU var device = new LearningModelDevice(LearningModelDeviceKind.DirectXHighPerformance); // Force NPU (Windows 11 24H2+) var device = new LearningModelDevice(LearningModelDeviceKind.Npu);