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Leather Defect Detection — Thesis Design project by YenkoDev

Leather Defect Detection

Software as a Service

No

Category

Thesis Design

Clients

Southern Luzon State University

Techstack

PythonYOLOv5Raspberry PiOpenCVPyQt

Purpose

Southern Luzon State University needed an affordable quality-control aid for leather production — a prototype that automatically spots surface defects so flawed material can be caught before it reaches finished products.

Description

A Raspberry Pi vision prototype that inspects leather surfaces using a custom-trained YOLOv5 model. Camera frames are processed on-device and passed through the detector, which localizes and classifies surface defects in real time, with detections displayed in a PyQt interface. The build includes both detection and non-detection viewing modes and an installation package tailored to the Raspberry Pi, keeping the whole rig compact and low-cost.

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