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#

people-counting

Here are 15 public repositories matching this topic...

Smart-City-Sample

The smart city reference pipeline shows how to integrate various media building blocks, with analytics powered by the OpenVINO™ Toolkit, for traffic or stadium sensing, analytics and management tasks.

  • UpdatedApr 30, 2024
  • Python

the large-scale data set for people counting (LOI counting)

  • UpdatedFeb 14, 2024

A Python 3 and Keras 2 implementation of MSCNN for people counting.

  • UpdatedJun 24, 2019
  • Python

Real-time Traffic and Pedestrian Counting (YOLOV3 in tensorflow2)

  • UpdatedMay 3, 2020
  • Python

This repository presents a method for people counting using a CNN trained with IR-UWB radar samples, in the COVID-19 and GDPR context. The purpose is the monitoring of the number of people inside a room, sending e-mail notifications every 10 minutes with the status of the room.

  • UpdatedAug 17, 2023
  • Python

Application on Door counter using the mmWave FMCW IWR1642

  • UpdatedDec 11, 2022
  • JavaScript

people counting

  • UpdatedNov 23, 2019
  • Python

Liblab, kütüphane doluluk oranı hakkında çalışmalar yapan IoT tabanlı bir görüntü işleme projesidir.

  • UpdatedMay 19, 2023
  • Python

Tensorflow implementation of a lightweight people counting CNN

  • UpdatedDec 14, 2021
  • PureBasic

The OpenCV project is dedicated to tracking and counting people present in both images and videos. With two distinct folders, this project performs people tracking and counting and also includes the ability to predict the distance from the camera and determine their direction.

  • UpdatedJan 10, 2024
  • Jupyter Notebook

Liblab, kütüphane doluluk oranı hakkında çalışmalar yapan IoT tabanlı bir görüntü işleme projesidir.

  • UpdatedFeb 21, 2023
  • Python

2018 云从人头技术冠军分享方案

  • UpdatedApr 4, 2019
  • Python

A simple Python web application with API to count people.

  • UpdatedJan 27, 2023
  • HTML

This repository contains a crowd counting model using the CSRNet architecture to estimate the number of people in crowded scenes. The model is trained on the Shanghaitech dataset and aims to provide accurate crowd density maps and count predictions. Data augmentation techniques are employed to enhance the model's performance.

  • UpdatedSep 12, 2024
  • Jupyter Notebook

Crowd Counting: A view around state-of-the-art

  • UpdatedFeb 3, 2025
  • Jupyter Notebook

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