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Using Python for Reading and Writing Optical Labels

Gain insights into using Python to read and write optical labels, explore 1D and 2D barcodes, and fiduciary markers for augmented reality, and discover relevant Python libraries and applications.

31 Lessons

2 Projects

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LEARNING OBJECTIVES

Familiarity with the most common 1D and 2D barcodes and fiduciary markers
Ability to use Python for reading and writing barcodes and fiduciary markers
Basic working knowledge of how to use fiduciary markers for practical applications, including AR
Knowledge of how to build simple user interfaces for reading barcodes
Hands-on experience applying Python libraries to read and write different types of optical labels

Learning Roadmap

31 Lessons1 Project7 Quizzes

Introduction to Machine-Readable Optical Labels

Get familiar with machine-readable optical labels, their types, applications, and industry benefits.

Introduction to the Course

An Overview of Machine-Readable Labels

An Overview of Barcodes

Look at the evolution and uses of 1D and 2D barcodes.

Basics of 1D Barcodes

Basics of 2D Barcodes

Quiz: An Overview of Barcodes

Reading and Writing 1D Barcodes With Python

3 Lessons

Work your way through creating and reading 1D barcodes using Python libraries.

Reading and Writing 2D Barcodes With Python

4 Lessons

Apply your skills to creating and interpreting various 2D barcodes with Python libraries.

Creating Fiduciary Markers With Python

4 Lessons

Map out the steps for creating and implementing fiduciary markers using OpenCV for precise positioning.

Reading Fiduciary Markers With Python

5 Lessons

Tackle reading and improving detection of fiduciary markers using Python and OpenCV techniques.

Fiduciary Marker Use Cases

3 Lessons

Build on Python techniques to measure distances and create AR with ArUco markers.

Build a User Interface With Gradio For Reading Barcodes

3 Lessons

Try out building a user-friendly barcode reader with Gradio, pyzbar, and OpenCV.

Build a Barcode Writing Application with Python

Project

Roundup

2 Lessons

Solve challenges with optical label generation, reading using Python, and continuous learning.

10.

Appendix

2 Lessons

Work your way through setting up and utilizing Python libraries for optical labels.

Tracking Moving Objects Using Python

Project

Premium

Certificate of Completion

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Developed by MAANG Engineers

ABOUT THIS COURSE

Machine-readable optical labels are visual representations of data that machines can read and interpret. These labels, often composed of simple geometric shapes or lines, are designed to encode various kinds of information, such as product details or reference numbers. In this course, you’ll be introduced to Python-based reading and writing of 1D and 2D barcodes and fiduciary markers. You’ll then learn the practical applications of barcodes and fiduciary markers in augmented reality and the creation of user interfaces for reading barcodes. Next, you’ll learn about different Python libraries and their usage to process different optical labels. By the end of the course, you’ll be proficient in using Python for handling barcodes and fiduciary markers. You’ll also have hands-on experience installing and using different Python libraries to manipulate optical labels.

ABOUT THE AUTHOR

Jes Fink-Jensen

Computer Scientist and educational consultant.

Learn more about Jes

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