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Automated Inspection with Computer Vision

Name: Automated Inspection with Computer Vision
Price: 59 USD
Author: Sébastien Gilbert

Gain insights into automated inspection using computer vision. Learn image analysis, feature detection, 2D/3D transformations, and train neural networks for object detection and image segmentation.

4.8

54 lessons

3 projects

15h

Created by Sébastien Gilbert

Automated Inspection with Computer Vision

What's included

54 lessons across 12 modules
22 quizzes with instant feedback
3 projects in preconfigured environments
AI Tutor on every lesson

Join 3.1 million developers at

What You'll Learn

Hands-on experience transforming image objects with OpenCV
An understanding of feature detection and blob analysis
The ability to use laser lines alongside 3D vision
Hands-on experience in labeling image datasets using CVAT
Working knowledge of convolutional neural networks for classification, object detection, and semantic segmentation with PyTorch

Learning Roadmap

54 Lessons1 Project22 Quizzes2 Assessments1 Challenge

Introduction

Get familiar with automated inspection using computer vision and its practical applications.

Automated Inspection: A Major Application of Computer Vision

Getting Started with Images

Get started with image I/O operations and annotation techniques in OpenCV.

I/O Operations on Images

Image Annotation

Quiz: Image I/O and Annotations

Image I/O and Annotations

Assessment

Color Spaces and Thresholding

4 Lessons

Work your way through color spaces, thresholding techniques, and adaptive thresholding for automated inspection.

Convert Color Spaces, Threshold

Assessment

Smoothing and Masking

3 Lessons

Enhance your skills in smoothing and masking techniques for improved automated image inspection.

Detection of Features

11 Lessons

Solve problems in automated feature detection using template matching, morphology, blob, edge, and corner detection techniques.

Image Registration

3 Lessons

Tackle image registration using homography transformations and perspective warping for object inspection.

3D Vision

4 Lessons

Master the steps to 3D topography capture, calibration, and visualization using laser line systems.

Getting Started with Neural Networks

5 Lessons

Step through neural networks, tensor manipulation, building blocks, training, and hands-on exercises.

Convolutional Neural Networks

8 Lessons

Walk through CNN fundamentals, training techniques, and leveraging pretrained networks for image classification.

Project: Create and Train a CNN for Classification

Project

10.

Object Detection and Semantic Segmentation

6 Lessons

Work your way through object detection and semantic segmentation using pre-trained CNN models.

Cats vs Dogs Classification with Convolutional Neural Networks

Project

Premium

11.

Dataset Annotation

4 Lessons

Apply your skills to annotate datasets for semantic segmentation using CVAT tools and formats.

12.

Final Remarks

2 Lessons

Map out the steps for automated inspection using recipes and understand key distinctions in approaches.

Recognize Handwritten Digits Using a Deep Neural Network

Project

Premium

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

About this course

WHY I WROTE THIS COURSE

Computer vision is essential for developers who wish to learn practical skills, e.g., in industrial manufacturing, automated inspection of products is crucial for quality assurance. In this course, you’ll apply computer vision and machine learning to analyze images for automated inspection. You’ll start by learning image I/O operations, thresholding, smoothing, and masking. You’ll learn feature detection using template matching and morphology. You’ll use the Sobel and Canny Edge Detectors, Harris Corner Detector, and Hough transform. You’ll learn about 2D transformations, including perspective and affine transformation, and 3D-to-2D projections. You’ll perform topography with a laser line to inspect the 3D shape of an object. Lastly, you’ll train convolutional neural networks for object detection and image segmentation and annotate datasets using CVAT. By the end of this course, you will have the skills to build inspection systems for industrial applications using computer vision and machine learning.

ABOUT THE AUTHOR

Sébastien Gilbert

Computer vision and machine learning engineer. I like to learn by building.

Learn more about Sébastien

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