VLM driven tool that processes surveillance videos, extracts frames, and generates insightful annotations using a fine-tuned Florence-2 Vision-Language Model. Includes a Gradio-based interface for querying and analyzing video footage.

DeepEYE utilizes computer vision to detect anomalies in video surveillance, offering a proactive security solution. By employing advanced machine learning algorithms, it distinguishes between normal activities and potential threats, enhancing surveillance across sectors like public safety, industry, and smart cities.

Developed a Real-Time Emotion Recognition System using Deepface. The system can detect and recognize Emotions in a Real-Time streaming video or through a live webcam and display the results in the screen.