Intel System Studio project code samples using the Intel® IoT Developer Kit libraries.

Sample Code for the Xkit. The perfect way to get started with Sigfox, the Thinxtra devkit Xkit boasts a full suite of features and accessories to empower anyone to set up an IoT solution, even with very little hardware experience. Perfect for start-ups, design houses, universities and schools, the kit has everything you need to hit the ground running using the globally available Sigfox network.

Usage: This project contains a python script called people_detection.py, a folder named haarcascades and two test videos. The download links for the two test videos are: Test_video_1.mp4: https://github.com/intel-iot-devkit/sample-videos/blob/master/worker-zone-detection.mp4 Test_video_2.mp4: https://www.pexels.com/video/man-transporting-garden-sand-using-a-cart-7714807/ You need execute the following statement to run the python script. > python3 people_detection.py -v ./test_video_1.mp4 -face_detec False The python script needs to pass in two parameters, namely “-v” and “-face_detec”, where “-v” refers to the video path that needs to be tested, and “-face_detec” refers to the need for face detection(If there is no face in the video, set to False). This python script first modifies the shape of each frame in the video, then performs corner detection, and then performs optical flow tracking on the detected corners, then execute human detection and face detection in turn, and draws frames and ellipses on the image respectively in.

Sample showing how to connect the MXChip devkit through IoT Edge

This is the sample codes for MXChip IoT DevKit using IoT Plug and Play. Sample code to connect the DevKit to your Azure IoT Central application..

Microsoft MXChip IoT DevKit Samples

iot-devkit-samples intel

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Barometer Sample for IoT DevKit

Azure RTOS samples running on MXChip AZ3166 IoT DevKit

An expanded version of the Azure IoT DevKit Getting Started sample

INTELXDK

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