Windows Machine Learning Explorer Sample
Windows Machine Learning Explorer is a data driven and generic sample application that serves as a launch pad to bootstrap ML models to be evaluated by Windows ML. It currently includes a scenario of circuit board defect detection model that can detect defects on pictures and a real-time camera feed of a printed circuit board.
For more information about this sample application, go to: How three lines of code and Windows Machine Learning empower .NET developers to run AI locally on Windows 10 devices.
For a guide to learn how to get started with Windows Machine Learning development, go to: Windows Machine Learning - Get Started.
Build the sample
If you download the samples ZIP, be sure to unzip the entire archive, not just the folder with the sample you want to build.
Start Microsoft Visual Studio 2017 and select File > Open > Project/Solution.
Starting in the folder where you unzipped the samples, go to the Samples subfolder, then the UWP subfolder for the platform, then WinMLExplorer subfolder for this sample application. Double-click the Visual Studio Solution (.sln) file.
Press Ctrl+Shift+B, or select Build > Build Solution.
Run the sample
The next steps depend on whether you just want to deploy the sample or you want to both deploy and run it.
Deploying the sample
- Select Build > Deploy Solution.
Deploying and running the sample
- To debug the sample and then run it, press F5 or select Debug > Start Debugging. To run the sample without debugging, press Ctrl+F5 or selectDebug > Start Without Debugging.
MIT. See LICENSE file.