Object Detection Using YOLO

Detect objects in Live stream or any video

Project Description 

An AI-powered object detection system built using modern full-stack technologies to identify and locate objects in images, videos, and live camera streams. The system utilizes the YOLO (You Only Look Once) model from Ultralytics for fast and accurate object detection. A FastAPI backend handles model inference, while a React-based frontend provides an interactive interface for users to upload images, videos, or use live camera detection. The entire application is containerized using Docker for easy deployment and scalability. 

Features 

• Real-time object detection using a live camera stream.

• Image-based object detection through file upload.

• Video object detection with frame-by-frame processing.

• Real-time bounding boxes around detected objects.

• High-speed inference using the YOLO model.

• Full-stack AI application with a React frontend and FastAPI backend.

• Containerized deployment using Docker for portability and scalability.

Tech Stack

Backend

• Python

• FastAPI
  
  

Frontend

• React

• JavaScript

• HTML, CSS

AI / Computer Vision

• YOLO (Ultralytics)

• OpenCV

Deployment

• Docker

System Requirements

• Python 3.10+

• Anaconda

• No GPU is required

Deliverables 

• Project Code

• Setup over video call 

• WhatsApp support