VisionAid: Real-Time Object Detection Web Application

🚀 Project Overview

VisionAid is a web-based object detection application that uses YOLOv5 to perform real-time object recognition through your webcam. The application provides instant identification and confidence scores for detected objects. This model is pre-trained on the COCO dataset on roughly 80 objects.

🔧 Technologies Used

• Backend: Flask (Python)
• Object Detection: YOLOv5 (ultralytics)
• Frontend: HTML5, JavaScript
• Computer Vision: OpenCV, Torch

✨ Features

• Real-time webcam object detection
• Instant object identification
• Confidence score for each detected object
• Simple, intuitive web interface

📦 Prerequisites

• Python 3.8+
• Webcam-enabled device

🛠️ Installation

1. Clone the Repository

git clone git@github.com:Eng-M-Abdrabbou/Object-Detection-Python-YOLO.git
cd Object-Detection-Python-YOLO

2. Install Dependencies

pip install -r requirements.txt

3. Run the Application

python app.py

🖥️ How It Works

1. The application accesses your webcam
2. Captures video frames in real-time
3. Processes each frame using YOLOv5 object detection
4. Displays detected objects with confidence scores

🔍 Supported Object Classes

The application can detect a wide range of objects using the YOLOv5n pre-trained model, including:

• People
• Vehicles
• Animals
• Everyday objects
• And many more!

📸 Screenshots

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

This project is licensed under the MIT License.

🙏 Acknowledgments

• Ultralytics for YOLOv5
• Flask Web Framework