The MobileNetV2 model is used in the carefully designed CCTV crime detection system to provide reliable and effective object recognition. With its lightweight architecture, MobileNetV2 guarantees best performance for real-time video analysis. Using deep learning, the system is intended to identify and evaluate questionable behaviour through sophisticated video analytics.
This project stands out for its flawless real-time alert integration with Telegram. The solution instantly notifies users via Telegram in the case of a possible security breach, enabling quick and remote monitoring. The system is more responsive as a result of this connection, giving administrators or security staff fast updates. Accuracy and prompt action are prioritised in a complete CCTV crime detection solution that is enhanced by the integration of Telegram with MobileNetV2.
🚀 CCTV CRIME DETECTION
This project is brought to you by Team YAAR. Special thanks to the following contributors for their valuable contributions:
- Mohamed Yasin -> https://github.com/yasin-coder.
- Aryan Deshmukh
- Apurva Shirke
- Raj Gandhi -> https://github.com/Rajgandhi04. Feel free to check out our profiles and fork the repo for further ideas.
STEPS FOR RUNNING THE PROJECT:
git clone the repo
cd CRIME_DETECTION
cd final
pip install requirements.txt
py cam.py
(Use this command for detection with an live camera/web cam).
py app.py
(Use this command for web interface).
For Credits TAG: -Raj Gandhi : https://github.com/Rajgandhi04.
-Mohamed Yasin : https://github.com/yasin-13.