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The people counter application is one of a series of IoT reference implementations aimed at instructing users on how to develop a working solution for a particular problem. It demonstrates how to create a smart video IoT solution using Intel® hardware and software tools. This solution detects people in a designated area, providing the number of people in the frame, average duration of people in frame, and total count.

Jupyter Notebook 16.42% Python 21.86% JavaScript 47.28% HTML 0.88% CSS 13.55%
openvino mqtt python intel iot people-counter

openvino-people-counter's Introduction

openvino-people-counter

Overview

The people counter application is one of a series of IoT reference implementations aimed at instructing users on how to develop a working solution for a particular problem. It demonstrates how to create a smart video IoT solution using Intel® hardware and software tools. This solution detects people in a designated area, providing the number of people in the frame, average duration of people in frame, and total count.

Working Principles

The counter uses the Inference Engine included in the Intel® Distribution of OpenVINO™ toolkit and the Intel® Deep Learning Deployment Toolkit. A pre-trained, SSD neural network detects people within a designated area by displaying a bounding box over them. It counts the number of people in the current frame, the duration that a person is in the frame (time elapsed between entering and exiting a frame) and the total count of people. It then sends the data to a local web server using the Paho MQTT Python package.

The DNN model used in this application is an Intel® optimized model that is part of the Intel® Distribution of OpenVINO™ toolkit.

/opt/intel/openvino/deployment_tools/intel_models/person-detection-retail-0013

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