Violence Detection In Real Life videos Using Pre-Trained Models

Real-world video violence identification is a critical task with broad implications for guaranteeing security, content control, and public safety.In order to reliably identify violent scenes in real-time videos, this study suggests an automated approach for violence identification utilizing pre-trained models.Modern pre-trained convolutional neural networks (CNNs) for visual processing are combined in the system.The system provides robustness and higher accuracy in detecting violent content by combining the data from the two modalities.The progress is efficient enough to enable real-time processing, allowing quick analysis of video streams and quick detection of violent situations.The progress alerts the appropriate authorities or content moderators when it detects violent behaviour.To ensure prompt action, a timing and location of the identified violent incident are included in an email message sent to predetermined recipients