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

This is my solution and documentation to the people counter app project at Udacity and Intel Edge A.I. for IoT Developers Nanodegree program. The app can detect people in a live feed, saved video or image and return the number of people in the frame, average time spent people in the frame, and the total count of people detected. It also sends an…

Build custom queuing systems for the retail, manufacturing and transportation sectors and use the Intel® DevCloud for the Edge to test your solutions performance.

This includes the basics of AI at the Edge, leverage pre-trained models available with the Intel® Distribution of OpenVINO Toolkit™, convert and optimize other models with the Model Optimizer, and perform inference with the Inference Engine.

A HIAS compatible Acute Lymphoblastic Leukemia classifier trained using Intel Distribution for Python and Intel Optimized Tensorflow. Uses OpenVINO to deploy the model to a Raspberry Pi and Neural Compute Stick 2 for inference on the edge.

Hands-on workshop contents to learn Intel distribution of OpenVINO toolkit - a deep learning inferencing library

The people counter application demonstrates how to create a smart video IoT solution using Intel® hardware and software tools. The app will detect people in a designated area, providing the number of people in the frame, average duration of people in frame, and total count. This project is a part of Intel Edge AI for IOT Developers Nanodegree pr…

The people counter application is a smart video IoT solution, using Intel® hardware and software tools. The app detects people in a designated area, providing the number of people in the frame, average duration of people in frame, and total count.