Real Time Object Detection

What is Object Detection?

Object detection is a computer vision technique that identifies and locates objects within an image or video. Unlike image classification, which only determines what objects are present, object detection also provides the positions of these objects using bounding boxes.

Key Components:

Object Classification – Determines what objects are in the image.

Object Localization – Identifies where the objects are by drawing bounding boxes.

Multi-object Detection – Detects multiple objects in a single image.

Popular Object Detection Models:

YOLO (You Only Look Once) – Fast, real-time object detection.

Faster R-CNN – High accuracy but slower than YOLO.

SSD (Single Shot MultiBox Detector) – Balances speed and accuracy.

Detectron2 – A Facebook AI model for advanced object detection.

Applications:

Autonomous Vehicles – Detects pedestrians, traffic signs, and other vehicles.

Surveillance & Security – Identifies suspicious activities or unauthorized persons.

Retail & Inventory Management – Tracks stock levels and customer behavior.

Medical Imaging – Detects tumors, fractures, and other anomalies.

Why do we need Object detection?

1. Automation & Efficiency

Reduces human effort in repetitive tasks (e.g., security surveillance, quality control in manufacturing).

Speeds up processes (e.g., detecting defects in products faster than humans).

2. Safety & Security

Autonomous Vehicles: Helps cars detect pedestrians, other vehicles, and obstacles.

Surveillance: Identifies suspicious activities, intruders, or missing persons.

Healthcare: Detects tumors, fractures, or abnormalities in medical imaging.

3. Enhanced Human Capabilities

Augments human vision with AI-powered detection (e.g., blind-assist technologies).

Helps doctors, security personnel, and engineers make better decisions with AI assistance.

4. Data-Driven Insights

In retail, detects customer behavior and stock levels.

In sports analytics, tracks player movements and game strategies.

5. Real-time Applications

Used in self-checkout systems, delivery robots, and AR/VR applications.

Powers facial recognition, automated number plate recognition (ANPR), and wildlife monitoring.

Detect object within realtime video or webcam marked by bounding box , on custom trained dataset. Newly launched models YOLOv5/7/9/11 available. Note : For Jetson Devices hardware access will be required to install the setup.

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Completed work

Object detection using deep learning identifies and classifies objects in images or videos. Advanced applications include autonomous driving, surveillance.

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Timeline

Mar 16, 2024 - Mar 25, 2024