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ML.NET DirectML ONNX Runtime Execution Provider Sample - Image Classification

This sample shows how to use the DirectML ONNX Runtime Execution Provider inside an ML.NET pipeline for image classification

This is a modified version of the Image Recognition tutorial on the ONNX Runtime documentation site.

Prerequisites

The DirectML Onnx Runtime Execution Provider only supports Windows.

Project Overview

This project adds a few CustomMapping transforms to an ML.NET pipeline which:

  1. Normalize image pixel data to a range between 0-1.
  2. Configure and run an ORT inference session with DirectML enabled.
  3. Post-process inference session results.

Instructions

  1. Download the ResNet50 v2 ONNX model and save it in the DirectMLONNXText project directory. Make sure to rename the file to model.onnx or update the modelPath variable in Program.cs.

  2. Download the dog.jpeg image file and save it in the DirectMLONNXText project directory.

  3. Update the Device ID in sessionOptions.AppendExecutionProvider_DML(0) to your GPUs Device ID (Usually it's 0 or 1).

  4. Use the dotnet CLI or Visual Studio to run your application. If successful, the resulting output should look similar to the following:

    2023-01-06 16:55:51.7609747 [W:onnxruntime:, inference_session.cc:491 onnxruntime::InferenceSession::RegisterExecutionProvider] Having memory pattern enabled is not supported while using the DML Execution Provider. So disabling it for this session since it uses the DML Execution Provider.
Top 10 predictions for ResNet50 v2...
--------------------------------------------------------------
Label: "Golden Retriever", Confidence: 0.7697107
Label: "Kuvasz", Confidence: 0.1426687
Label: "Otterhound", Confidence: 0.015724588
Label: "Clumber Spaniel", Confidence: 0.009826223
Label: "Saluki", Confidence: 0.0062108114
Label: "Tibetan Terrier", Confidence: 0.0057344614
Label: "Pyrenean Mountain Dog", Confidence: 0.0050382884
Label: "Sussex Spaniel", Confidence: 0.004918177
Label: "Labrador Retriever", Confidence: 0.0040683337
Label: "Tibetan Mastiff", Confidence: 0.0037927858