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Merge pull request #502 from microsoft/user/linneamay/stream-readme
add streaming readme
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Samples/WinMLSamplesGallery/README.md

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- [DX Resource Binding in ORT](./WinMLSamplesGallery/Samples/DXResourceBindingORT): Learn how to bind and evaluate DirectX Resources using [ONNX Runtime](https://onnxruntime.ai/docs/).
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- [Stream Effect](./WinMLSamplesGallery/Samples/StreamEffect): Learn how to use [Windows ML](https://docs.microsoft.com/en-us/windows/ai/windows-ml/) with real-time inference on video streams.
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## Feedback
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Please file an issue [here](https://github.com/microsoft/Windows-Machine-Learning/issues/new) if you encounter any issues with the WinML Samples Gallery or wish to request a new sample.
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# Windows ML Samples Gallery: Stream Effect
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Apply backbround blurring effect to a live video stream.
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The sample showcases how to use Windows ML with a real-time video stream.
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<img src="Docs/demo.gif" width="650"/>
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- [Getting Started](#getting-started)
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- [Feedback](#feedback)
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- [External Links](#external-links)
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## Getting Started
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- Check out the [C# source](https://github.com/microsoft/Windows-Machine-Learning/blob/master/Samples/WinMLSamplesGallery/WinMLSamplesGallery/Samples/StreamEffect/StreamEffect.xaml.cs).
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- Check out the [C++ source](https://github.com/microsoft/Windows-Machine-Learning/blob/master/Samples/WinMLSamplesGallery/WinMLSamplesGalleryNative/StreamEffect.cpp).
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- Learn how to [chain together custom LearningModels](https://github.com/microsoft/Windows-Machine-Learning/blob/master/Samples/WinMLSamplesGallery/WinMLSamplesGalleryNative/SegmentModel.h#L31)
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- Learn how to [write an async Media Foundation Transform](https://github.com/microsoft/Windows-Machine-Learning/blob/master/Samples/WinMLSamplesGallery/WinMLSamplesGalleryNative/TransformAsync.h)
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## Feedback
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Please file an issue [here](https://github.com/microsoft/Windows-Machine-Learning/issues/new) if you encounter any issues with the Windows ML Samples Gallery or wish to request a new sample.
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## External Links
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### Windows Machine Learning
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| Resource | Description |
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|-------------------------------|----------------------------------------------------------------------------------------|
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| [WinML Experimental API ](https://github.com/microsoft/onnxruntime/blob/5fbfca3d58b88d0da29c6b206c36980052a4392c/winml/api/Microsoft.AI.MachineLearning.Experimental.idl)| Documentation for the LearningModelBuilder and LearningModelJoinOptions |
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| [ORT model building unit tests ](https://github.com/microsoft/onnxruntime/blob/22739137c419bb8a86b8f9ff5c8def60b63370c7/winml/test/api/LearningModelSessionAPITest.cpp#L962)| A good intro to building models with LearningModelBuilder and LearningModelJoinOptions |
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| [ONNX operators schema ](https://github.com/onnx/onnx/blob/main/docs/Operators.md)| ONNX operators that can be used when building a model with LearningModelBuilder |
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| [ONNX Model Zoo FCN ](https://github.com/onnx/models/tree/main/vision/object_detection_segmentation/fcn)| Open-source models in the ONNX format |
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### Media Foundation
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| Resource | Description |
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|-------------------------------|----------------------------------------------------------------------------------------|
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| [Introduction to Media Foundation Transforms](https://docs.microsoft.com/en-us/windows/win32/medfound/media-foundation-transforms)| Start here to learn more about Media Foundation Transforms as a model for processing media data|
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| [Windows Async MFT Sample ](https://github.com/microsoft/Windows-classic-samples/tree/main/Samples/MediaFoundationTransformDecoder)| Demonstrates how to create an asynchronous Media Foundation Transform |
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| [Windows Capture Engine Sample ](https://github.com/microsoft/Windows-classic-samples/tree/main/Samples/CaptureEngineVideoCapture)| Demonstrates how to use the Media Foundation [CaptureEngine](https://docs.microsoft.com/en-us/windows/win32/api/mfcaptureengine/nn-mfcaptureengine-imfcaptureengine) to capture video|

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