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AI-Powered Package Detection and Analysis System
This project is a real-time AI-powered package detection system designed for conveyor belts and warehouse environments. It detects and tracks packages, analyzes their condition using Google Gemini AI, and triggers alerts when damaged or open boxes are detected.
Project Overview
This AI-powered package inspection system combines YOLO object detection with Google Gemini AI to monitor packages in real time. It tracks packages on conveyor belts, analyzes their physical condition, logs results automatically, and provides instant alerts for compromised shipments.
Key Features
YOLO-Based Package Detection & Tracking
- 📦 Detects packages in real-time video streams.
- 🆔 Assigns unique tracking IDs to each package.
AI-Based Package Condition Analysis
- 🧠 Integrates Google Gemini AI for image analysis.
- 📂 Detects if the front flap is open (Yes / No).
- ⚠️ Identifies damaged packages automatically.
Automated Cropping & Data Logging
- ✂️ Crops package images when crossing a detection line.
- 📝 Logs package details into daily text files.
Real-Time Alerts System
- 🔊 Triggers audio alerts for damaged or open boxes.
- ⏹️ Automatically stops alerts when issues are resolved.
High Performance with Multithreading
- 🧵 Runs AI analysis in separate threads.
- ⚡ Ensures smooth real-time video processing.
Technology Stack
- 🐍 Programming Language: Python
- 🎥 Computer Vision: OpenCV
- 🧠 Object Detection & Tracking: YOLO (Ultralytics)
- 🤖 AI Analysis: Google Gemini AI
- 🔊 Audio Alerts: Pygame
- 🖥️ Visualization: CVZone
Use Cases
- 🏭 Warehouse Automation – Detect damaged or open packages.
- 🚚 Logistics & Supply Chain – Ensure shipment quality.
- 🛒 Retail & E-commerce – Monitor package integrity before delivery.
Conclusion
This AI-powered package detection and analysis system provides an intelligent solution for real-time quality control in warehouses and logistics centers. By combining YOLO and Google Gemini AI, it delivers accurate detection, automated inspection, and instant alerts to improve operational efficiency and reduce losses.