Criminal Seeker
The project aims to identify criminals by analyzing images, such as those captured from CCTV footage or other sources. Using advanced image recognition technology, it can match facial features, detect suspicious activity, and apply filters to efficiently search and track potential suspects, enhancing security and law enforcement efforts.
This project is built using Flask, a lightweight web framework, to create a powerful system for identifying criminals through image recognition. It processes CCTV footage and other visual data, utilizing advanced machine learning algorithms to analyze and match faces, recognize suspicious activity, and search for known criminals.
The application allows users to upload or stream footage, where the system then extracts relevant images for analysis. By comparing facial features against a database of known criminals, it helps law enforcement or security teams quickly identify suspects. Filters and search functionalities are implemented, enabling efficient tracking of potential criminals based on visual data.
The Flask-based interface is user-friendly, providing easy access to all features, including real-time searches and image uploads. Additionally, the system supports multiple image formats and offers integration with security systems for continuous monitoring. This project aims to improve public safety by automating the criminal identification process.