Building a Vision Detection Algorithm for Manufacturing Defect Detection in Python

Introduction

In the manufacturing industry, ensuring product quality and minimizing defects are critical for maintaining customer satisfaction and reducing costs. Vision detection algorithms have become essential tools for automating the process of defect detection, providing a reliable and efficient means to identify defects early in the production line.

In this blog post, we will walk through the steps to create a vision detection algorithm in Python for manufacturing defect detection using popular libraries such as OpenCV and TensorFlow.

Setting Up the Environment

Before we start coding, let’s set up our development environment. We will need Python installed along with the necessary libraries. You can install these libraries using pip:

pip install opencv-python-headless tensorflow numpy matplotlib

Loading and Pre-Processing the Data

The first step in creating a vision detection algorithm is to load and pre-process the data. We will use OpenCV to load images of the manufactured products and pre-process them to prepare for defect detection.

import cv2
import numpy as np
import…