Weapon detection using OpenCV and YOLO (You Only Look Once) involves leveraging computer vision and deep learning techniques to identify and locate weapons in real-time video streams or images. YOLO, a fast and accurate object detection model, processes the input frame and predicts bounding boxes and class probabilities for potential weapons. OpenCV handles the video capture and pre-processing tasks, such as resizing and color space conversion. The combined system efficiently detects weapons by passing the processed frames through the YOLO model, drawing bounding boxes around detected weapons, and displaying the results, enabling prompt and effective security responses.
Weapon detection using OpenCV and YOLO (You Only Look Once) involves leveraging computer vision and deep learning techniques to identify and locate weapons in real-time video streams or images. YOLO, a fast and accurate object detection model, processes the input frame and predicts bounding boxes and class probabilities for potential weapons. OpenCV handles the video capture and pre-processing tasks, such as resizing and color space conversion. The combined system efficiently detects weapons by passing the processed frames through the YOLO model, drawing bounding boxes around detected weapons, and displaying the results, enabling prompt and effective security responses.
