Overview

• The project:ObjectDetection a Cloud-based Web-service designed to perform real-time object detection on images.
• The system leverages the YOLO (You Only Look Once) library and OpenCV for image processing and object detection.
• The service is hosted within Docker containers managed by a Kubernetes cluster on the Oracle Cloud Infrastructure (OCI).

Project Description

• Developed a web-based object detection system using Python's Flask, YOLO, and OpenCV, enabling real-time image processing and object detection.
• Containerized the application with Docker and deployed it on a Kubernetes cluster hosted on Oracle Cloud Infrastructure (OCI), ensuring scalability and efficient resource management.
• Conducted performance testing and load generation using Locust, optimizing the system to handle varying loads and concurrent users effectively.
• Documented and reported experimental results, demonstrating proficiency in cloud services, container orchestration, and performance optimization techniques.

System Diagram

Technology Used

• Docker
• K8s
• Oracle Cloud Instances
• Flask
• Locust
• Python

URL and Endpoint

• Service Endpoint: NA