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Platform for Situated Intelligence Samples

This repository contains a few small example applications written with Platform for Situated Intelligence. Some of the samples address specialized topics like how to leverage speech recognition components or how to bridge to ROS, but in general looking through them can give you more insight into programming with Platform for Situated Intelligence. Besides these samples, a good place to start reading about programming with \psi is the Brief Introduction and the set of Tutorials.

As indicated in the last column in the table below, some of the samples have a corresponding detailed walkthrough that explains how the samples are constructed and function, and provide further pointers to documentation and learning materials. Going through these walkthroughs can also help you learn more about programming with \psi.

Name Description Windows Linux Walkthrough
HelloWorld
Hello World preview image showing code snippet
This sample is the simplest possible starting point for creating a \psi application. Yes Yes Yes
SimpleVoiceActivityDetector
Preview image showing visualized audio and VAD result streams
This sample captures audio from a microphone and performs voice activity detection, i.e., it computes a boolean signal indicating whether or not the audio contains voiced speech. Yes Yes Yes
WebcamWithAudioSample
Preview gif showing webcam view of a person speaking and audio level changing
This sample illustrates how to display images from a camera and the audio energy level from a microphone. Yes - Yes
LinuxWebcamWithAudioSample This sample illustrates how to display images from a camera and the audio energy level from a microphone on Linux. - Yes Yes
AzureKinectSample
Sample output from Azure Kinect sample showing ASCII art of a person waving
This sample demonstrates how to use the Azure Kinect sensor with body tracking and how to use the Join() and Pair() operators to synchronize and fuse streams. Yes - Yes
WhatIsThat
Preview gif of visualized 3d output from What-is-That sample
This sample implements a simple application that uses an Azure Kinect sensor to detect the objects a person is pointing to. Yes - Yes
PsiBot
Preview image of the Teams Bot integration sample - a ball bouncing between the active speakers
This sample application shows how you can integrate \psi with the Teams bot architecture to develop bots that can participate in live meetings. Yes - Yes
KinectSample This sample illustrates how to augment an existing voice activity detector by leveraging information about lips motion extracted from Kinect face tracking. Yes - -
SpeechSample This sample illustrates how to use various speech recognition components. Yes - -
LinuxSpeechSample This sample illustrates how to use various speech recognition components on Linux. - Yes Yes
RosTurtleSample
Preview image of Ros Turtle sample
This sample illustrates how to connect Platform for Situated Intelligence to the turtlesim in ROS. Yes Yes Yes
RosArmControlSample This sample illustrates how to connect Platform for Situated Intelligence to control the uArm Metal using ROS. Yes Yes Yes
OpenCVSample This sample illustrates how to interop with OpenCV. Yes - -
HoloLensSample
Preview gif of visualized output streams from one of the HoloLens Sample demos
This sample demonstrates how to develop Mixed Reality \psi applications for the HoloLens 2. UWP - Yes

Building

To build the samples, you will need to install Visual Studio 2022 with the .NET desktop development workload on Windows, or .NET on Linux. Some samples may have additional prerequisites. Please see the README of each individual sample for more information.

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.

License

All Platform for Situated Intelligence samples are available under an MIT License.

Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.

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psi-samples's Issues

How to run "WhatIsThat" on GPU?

I've installed and configured CUDA, also set the parameter "CpuOnlyMode" to false in the AzureKincetBodyTrackerConfiguration. I am wondering how to configure the "WhatIsThat" project in Visual Studio 2019 to make it run by my GPU. Can you provide some instructions?

Configuration Of AzureKinectBodyTracker

Hello Microsoft Guys,
We have a very powerful HPC with a powerful Nvidia GPU(RTX 3080 ti).
When running the sample of What's that, we set TrackerProcessingMode as Cuda but the performance is not perefect.
Is it possible to use TensroRT in this sample? If so, do you have related experiences?

Not getting detected object boxes to render in PSI Studio

Using the WhatsThat example, I am able to write a <List<Tuple<System.Drawing.Rectangle, string>>> to the store. I am expecting to be able to drag and drop this on top of an image to overlay detected objects and their name. I'm following along with the example but the PSI Studio is not rendering the boxes.

here's a link to the code.

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