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.
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If you download the samples ZIP, be sure to unzip the entire archive, not just the folder with the sample you want to build.
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Start Microsoft Visual Studio 2017 and select File > Open > Project/Solution.
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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.
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Press Ctrl+Shift+B, or select Build > Build Solution.
The next steps depend on whether you just want to deploy the sample or you want to both deploy and run it.
- Select Build > Deploy Solution.
- 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.