🚀 Challenge: “Real-Time Image Processing Pipeline”

📋 Overview

Build a full-stack application where users can submit URLs for image processing.

The backend uses a BullMQ worker to process images, store results in Firebase, and the frontend displays progress in real-time.

API Endpoints:

• POST /api/jobs - Create a new image processing job
• GET /api/jobs/:id - Get job status
• GET /api/jobs - List all jobs

BullMQ Implementation:

1. Create a queue named imageProcessing
2. Implement a worker that processes jobs concurrently
3. Each job should:
   • Download an image from a provided URL
   • Perform transformations (like resize, grayscale, add watermark, etc)
     • Use any library available
   • Upload the result to Firebase Storage
   • Update job status in Firestore at each step

Frontend:

• Single page with a form to submit image URLs
• Real-time job list showing all jobs with their status
• Progress bar for each job showing completion percentage
• Display result image when completed