Containerized Automated Quality Control Pipeline

A containerised computer-vision system that inspects products in real time on a manufacturing line. I built the pipeline in Python with OpenCV for the vision work and Docker for clean, portable deployment — automating quality control that would otherwise rely on manual checks.

Manual visual inspection is slow, inconsistent, and doesn't scale with production speed. The client needed an automated system that could catch defects in real time, run reliably in a factory environment, and deploy consistently across machines without dependency headaches.

A real-time computer-vision inspection pipeline in Python using OpenCV

Defect-detection logic tuned for the client's specific product and line speed

Full Docker containerisation for portable, reproducible deployment

A processing pipeline designed for reliability in a production manufacturing setting

Python, OpenCV, and Docker.

The manufacturer gained automated, real-time quality control — catching defects faster and more consistently than manual inspection, in a containerised system that deploys cleanly wherever it's needed.