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Repository for Intel Edge AI for IoT projects. Computer vision projects applicable to the service, manufacturing, and transport industry. Another project controls the computer mouse using eye gaze and head pose estimation.
Demonstrates the ability to run multiple models on the OpenVINO toolkit on one edge device to control a computer pointer by staring at different locations on the screen
This repository contains code for running Convolutional Neural Networks (CNNs) on CircuitPython. It contains code to train models using Tensorflow on computers and convert them to CircuitPython.
The people counter application demonstrated how to create a smart video IoT solution using Intel® hardware and software tools. The app detects people in a designated area and provide the number of people in the frame, average duration of people in frame, and the total count.
Object detection using tiny-YOLOv3 on a Raspberry Pi with the help of the Intel OpenVINO library and an Intel Neural Compute Stick 2 as featured in my Medium article "Edge AI - Computer vision inference on the edge".
This repository is to share the EdgeAI Lab with Microcontrollers Series material to the entire community. We will share documents, presentations and source code of two demo applications.
Build custom queuing systems for the retail, manufacturing and transportation sectors and use the Intel® DevCloud for the Edge to test your solutions performance.
Investigate different pre-trained models for person detection, and detect the number of people in the frame, and the time spent there. https://youtu.be/PxbYqBZgbQE
Launched in March 2020 in response to the coronavirus disease 2019 (COVID-19) pandemic, COVID-Net is a global open source, open access initiative dedicated to accelerating advancement in machine learning to aid front-line healthcare workers and clinical institutions around the world fighting the continuing pandemic. Towards this goal, our global…