🧠 Object Detection using OpenCV and Deep Learning

This project demonstrates real-time object detection using OpenCV, NumPy, and pre-trained deep learning models such as YOLO or MobileNet-SSD.
It detects and highlights objects in images or videos with bounding boxes, labels, and confidence scores.

🚀 Features

• Real-time object detection from images, videos, or webcam
• Uses pre-trained models (YOLO / MobileNet-SSD) for accurate detection
• Displays bounding boxes and confidence levels for each detected object
• Simple and well-documented Jupyter Notebook implementation
• Easily customizable for new datasets or model types

🧩 Technologies Used

• Python 3.x
• OpenCV (for image processing and DNN module)
• NumPy (for numerical operations)
• Jupyter Notebook (for demonstration and visualization)
• Pre-trained Models (Caffe, TensorFlow, or YOLO weights)

⚙️ Installation and Setup

1. Clone the repository

   git clone https://github.com/Afza1112/Object-Detection.git
   cd Object-Detection