🕵️ YOLO Thief Object Detection

📃 Features

• 🔍 Automatic Thief Detection: The system can automatically detect the presence of thieves in CCTV footage using the YOLOv5 detection model.
• 🚨 Alarm System: When a thief is detected, the system will trigger an alarm to alert the user or authorities.
• 📸 Perpetrator Image Capture: In addition to triggering the alarm, the system will also capture an image of the perpetrator for identification or further investigation purposes.
• 🎯 Region of Interest (ROI): Users can specify a specific area on the CCTV screen as the ROI, where the system will focus on detecting the presence of thieves.
• 🔄 Video Preprocessing: CCTV video recordings will be preprocessed to optimize image quality and proportions.
• 📊 Detection Visualization: Thief detection and ROI are visually displayed in the video footage, helping users understand the events taking place.

📺 Demo

demo.mp4

✍ Explanation Code

In this tutorial, I explain the code for building an Automatic Thief Detection system using CCTV footage. The tutorial walks through the implementation of the code demonstrated above, which utilizes YOLOv5 object detection along with Region of Interest (ROI) selection to detect potential thieves. Watch the full tutorial on YouTube for a step-by-step explanation and demonstration.

Click on the thumbnail to open the video☝️

📚 Documentation

Find detailed documentation about the YOLOv5 and OpenCV libraries. Learn more about YOLOv5’s visualization capabilities as well as OpenCV’s extensive computer vision functionality. Dive deeper into the documentation to discover tutorials, guidelines, and API specifications for YOLOv5 and OpenCV.