akash-rajak/Real-Time-Human-Detection-Counting

A tensorflow based Faster RCNN inception v2 python model to detect and count humans in real time images, videos & camera.

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This project helps operations managers or event organizers automatically count people in real-time from images, videos, or live camera feeds. You provide the visual input, and it outputs the number of humans detected, alongside plots showing human count over time and average detection accuracy. It also generates a PDF crowd report summarizing key metrics like maximum human count and average accuracy.

No commits in the last 6 months.

Use this if you need to monitor crowd density or track human presence in a specific area using existing cameras or stored media.

Not ideal if you need to identify individuals, track specific people, or require very high accuracy in extremely dense or obscured crowd scenarios.

crowd-monitoring security-management event-management operations-analysis occupancy-tracking
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 16 / 25
Community 20 / 25

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Stars

97

Forks

29

Language

Python

License

MIT

Last pushed

Jun 13, 2024

Commits (30d)

0

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