SentinelML

1. 1Build a firearm detection model using YOLOv8
2. 2Configure a cloud-native infrastructure for real-time alerting
3. 3Deploy SentinelML framework for modular and scalable detection
4. 4Test the framework with sample datasets and evaluate performance
5. 5Apply fine-tuning techniques to improve model accuracy

Developers and data scientists working on computer vision and AI-powered security systems can benefit from this framework to build and deploy real-time detection models

💡 SentinelML provides a modular and open-source framework for real-time firearm detection and alerting

Real-time firearm detection with SentinelML and YOLOv8