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Image Processing with Python
David Dalsveen
David Dalsveen
Image processing has been used to create weird and beautiful modifications to pictures many of us have seen online. Older black and white photos can be brought to life using colorization techniques. On the other hand, color photos can be made to look like old...
Read more
Image processing has been used to create weird and beautiful modifications to pictures many of us have seen online. Older black and white photos can be brought to life using colorization techniques. On the other hand, color photos can be made to look like old...
Read more
Image processing has been used to create weird and beautiful modifications to pictures many of us have seen online. Older black and white photos can be brought to life using colorization techniques. On the other hand, color photos can be made to look like old black and white photos. In addition to distorting images for entertainment, image processing can be used for more serious applications, for example, to enhance medical imaging to screen patients for cancer or other diseases.
In this tutorial, you will create a Python application that reads from a list of images, modifies their size and appearance, and saves the images in another directory.
Note: This tutorial works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Register for this course and see more details by visiting:
OpenCourser.com/course/3e8cd3/image
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
This tutorial is geared toward learners based in North America, which may limit accessibility for learners in other regions
Introduces image processing techniques for both fun and serious applications, appealing to learners interested in both creative and practical uses
Focuses on Python for image processing, providing learners with a versatile and widely used programming language
Provides hands-on experience through code implementation, reinforcing practical skills
Covers fundamental image modification techniques, including resizing and color adjustments, building a solid foundation for further exploration
Suitable for beginners interested in image processing, providing a clear and accessible introduction to key concepts
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Save Image Processing with Python to your list so you can find it easily later:
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Reviews summary
Image processing made easy
Image Processing with Python is a course that uses Python to teach students the basics of image processing. This course assumes North American students, and takes a very simple and basic approach to the subject. As such, it is a good fit for novice learners with little to no current experience with Python for image processing.
Suitable for learning the fundamentals of image processing with OpenCV.
"Course covered basic application of opencv library using python."
"Recommended for those with a minimum understanding of image processing"
"I liked it a lot."
Course is useful for introducing image processing and getting started with OpenCV.
"Good guided project"
"Overall a good course to start OpenCV."
"great guided course for beginners it could be better if explained in more detail"
Good introduction to image processing; suitable for learners with no prior knowledge or experience.
"Great for beginners."
"Good for a quick introduction to image processing."
"Small and just right course."
Course assumes the location of the learner; may not be relevant to other regions.
"Note: This tutorial works best for learners who are based in the North America region."
"We’re currently working on providing the same experience in other regions."
Insufficient explanations of image processing techniques and functions.
"need more detail"
"Could be made better by improving the explanation."
"It's a reaaaaally basic course for people that need to learn how to manage images and make basic operations on them."
Lack of in-depth explanations and exploration of image processing topics.
"The course is too basic. Is about handling images with python not image processimg"
"The theory behind the sharpening and blurring is not explained."
"Very superficial"
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Image Processing with Python with these
activities:
Connect with experienced image processing professionals
Show steps
Gain valuable insights and guidance from experienced professionals in the field.
Browse courses on
Image Manipulation
Show steps
-
Identify experienced image processing professionals through online forums or social media.
-
Reach out to them and express your interest in connecting.
-
Set up a meeting to discuss your career goals and get advice.
Review image manipulation tools
Show steps
Solidify understanding of the tools used in image processing to better understand how images are modified.
Browse courses on
Image Manipulation
Show steps
-
Review online tutorials on tools like Photoshop or GIMP.
-
Practice using these tools to manipulate images on your own.
Follow tutorials on image processing techniques
Show steps
Gain practical experience with image processing techniques by following guided tutorials.
Browse courses on
Image Manipulation
Show steps
-
Search for tutorials on image processing techniques that interest you.
-
Follow the steps in the tutorials carefully.
-
Experiment with different techniques and settings.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Complete image processing exercises
Show steps
Reinforce your understanding of image processing techniques by completing practice exercises.
Browse courses on
Image Manipulation
Show steps
-
Find online exercises or practice problems related to image processing.
-
Attempt to solve the exercises on your own.
-
Check your answers and learn from your mistakes.
Develop a portfolio of image processing projects
Show steps
Demonstrate your image processing skills by creating a portfolio of projects.
Browse courses on
Image Manipulation
Show steps
-
Choose a variety of image processing techniques to showcase.
-
Create several projects that demonstrate your proficiency in these techniques.
-
Organize your projects into a portfolio that you can share with potential employers or clients.
Participate in open-source image processing projects
Show steps
Contribute to the image processing community while gaining practical experience.
Browse courses on
Image Manipulation
Show steps
-
Find open-source image processing projects that interest you.
-
Identify ways that you can contribute to these projects.
-
Submit your contributions to the project.
Mentor other students in image processing
Show steps
Enhance your understanding of image processing by teaching it to others.
Browse courses on
Image Processing
Show steps
-
Identify students who could benefit from your help.
-
Offer to mentor them in image processing.
-
Meet with them regularly to provide guidance and support.
Connect with experienced image processing professionals
Show steps
Gain valuable insights and guidance from experienced professionals in the field.
Browse courses on
Image Manipulation
Show steps
Show steps
Show steps
- Identify experienced image processing professionals through online forums or social media.
- Reach out to them and express your interest in connecting.
- Set up a meeting to discuss your career goals and get advice.
Review image manipulation tools
Show steps
Solidify understanding of the tools used in image processing to better understand how images are modified.
Browse courses on
Image Manipulation
Show steps
Show steps
Show steps
- Review online tutorials on tools like Photoshop or GIMP.
- Practice using these tools to manipulate images on your own.
Follow tutorials on image processing techniques
Show steps
Gain practical experience with image processing techniques by following guided tutorials.
Browse courses on
Image Manipulation
Show steps
Show steps
Show steps
- Search for tutorials on image processing techniques that interest you.
- Follow the steps in the tutorials carefully.
- Experiment with different techniques and settings.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Complete image processing exercises
Show steps
Reinforce your understanding of image processing techniques by completing practice exercises.
Browse courses on
Image Manipulation
Show steps
Show steps
Show steps
- Find online exercises or practice problems related to image processing.
- Attempt to solve the exercises on your own.
- Check your answers and learn from your mistakes.
Develop a portfolio of image processing projects
Show steps
Demonstrate your image processing skills by creating a portfolio of projects.
Browse courses on
Image Manipulation
Show steps
Show steps
Show steps
- Choose a variety of image processing techniques to showcase.
- Create several projects that demonstrate your proficiency in these techniques.
- Organize your projects into a portfolio that you can share with potential employers or clients.
Participate in open-source image processing projects
Show steps
Contribute to the image processing community while gaining practical experience.
Browse courses on
Image Manipulation
Show steps
Show steps
Show steps
- Find open-source image processing projects that interest you.
- Identify ways that you can contribute to these projects.
- Submit your contributions to the project.
Mentor other students in image processing
Show steps
Enhance your understanding of image processing by teaching it to others.
Browse courses on
Image Processing
Show steps
Show steps
Show steps
- Identify students who could benefit from your help.
- Offer to mentor them in image processing.
- Meet with them regularly to provide guidance and support.
Career center
Learners who complete Image Processing with Python will develop knowledge and skills
that may be useful to these careers:
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers use their knowledge of image processing to develop algorithms that allow computers to interpret images and video. In that, an understanding of what image processing involves is beneficial for this role. Additionally, this course can provide foundational knowledge around the use of Python, which is used in Computer Vision.
Medical Imaging Analyst
Medical Imaging Analyst
Medical Imaging Analysts apply image processing techniques to analyze medical images such as X-rays, CT scans, and MRIs. Course material will be helpful in understanding general image processing techniques.
Data Scientist
Data Scientist
Data Scientists may use image processing techniques as a part of their analysis. In that, knowing the basics of image processing can be helpful for understanding this field.
Software Engineer
Software Engineer
Software Engineers who work with image processing would benefit from having knowledge of the Python programming language, as this course provides.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers may use image processing techniques as a part of their work. In that, knowing the basics of image processing can be helpful for understanding this field.
AI Engineer
AI Engineer
AI Engineers may use image processing techniques as a part of their work. In that, knowing the basics of image processing can be helpful for understanding this field.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts may use image processing techniques as a part of their work. In that, knowing the basics of image processing can be helpful for understanding this field.
Computer Graphics Specialist
Computer Graphics Specialist
Computer Graphics Specialists use image processing techniques in order to create realistic images. Knowledge of general image processing concepts can be helpful for this role.
Robotics Engineer
Robotics Engineer
Robotics Engineers who work on computer vision may use image processing techniques. In that, understanding how images are processed by computers can be helpful.
Game Developer
Game Developer
Game Developers who are responsible for graphics may use image processing techniques. In that, knowing the basics of image processing can be helpful.
Web Developer
Web Developer
Web Developers who work on image-heavy websites may use image processing techniques. In that, knowing the basics of image processing can be helpful.
Art Director
Art Director
Art Directors who work in digital media or computer graphics may benefit from having knowledge of image processing.
Photographer
Photographer
Photographers who edit their images digitally can benefit from learning about image processing techniques.
Graphic designer
Graphic designer
Graphic Designers who work with digital images may benefit from having knowledge of image processing.
UX Designer
UX Designer
UX Designers who work on image-heavy websites or apps can benefit from having knowledge of image processing.
For more career information including salaries, visit:
OpenCourser.com/course/3e8cd3/image
Reading list
We've selected 11 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Image Processing with Python.
Provides a comprehensive overview of computer vision. It covers a wide range of topics, from basic concepts to advanced techniques. It valuable resource for anyone who wants to learn more about computer vision.
Provides a comprehensive overview of image analysis and recognition. It covers a wide range of topics, from basic concepts to advanced techniques. It valuable resource for anyone who wants to learn more about image analysis and recognition.
Classic textbook on digital image processing. It covers a wide range of topics, from basic concepts to advanced techniques. It valuable resource for anyone who wants to learn more about image processing.
Save
Provides a comprehensive overview of deep learning. It covers a wide range of topics, from basic concepts to advanced techniques. It valuable resource for anyone who wants to learn more about deep learning.
Provides a comprehensive overview of neural networks and deep learning. It covers a wide range of topics, from basic concepts to advanced techniques. It valuable resource for anyone who wants to learn more about neural networks and deep learning.
Provides a comprehensive overview of statistical learning. It covers a wide range of topics, from basic concepts to advanced techniques. It valuable resource for anyone who wants to learn more about statistical learning.
Provides a comprehensive overview of machine learning. It covers a wide range of topics, from basic concepts to advanced techniques. It valuable resource for anyone who wants to learn more about machine learning.
Provides a comprehensive overview of machine learning from a probabilistic perspective. It covers a wide range of topics, from basic concepts to advanced techniques. It valuable resource for anyone who wants to learn more about machine learning from a probabilistic perspective.
Provides a comprehensive overview of probabilistic graphical models. It covers a wide range of topics, from basic concepts to advanced techniques. It valuable resource for anyone who wants to learn more about probabilistic graphical models.
Save
Provides a comprehensive overview of computer vision algorithms and applications. It valuable resource for anyone who wants to learn more about computer vision.
Save
Provides a comprehensive overview of pattern recognition and machine learning. It covers a wide range of topics, from basic concepts to advanced techniques. It valuable resource for anyone who wants to learn more about pattern recognition and machine learning.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/3e8cd3/image
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Via
Coursera
Institution
Coursera Project Network
Instructor
David Dalsveen
Good to know
This tutorial is geared toward learners based in North America, which may limit accessibility for learners in other regions
Introduces image processing techniques for both fun and serious applications, appealing to learners interested in both creative and practical uses
Focuses on Python for image processing, providing learners with a versatile and widely used programming language
Provides hands-on experience through code implementation, reinforcing practical skills
Covers fundamental image modification techniques, including resizing and color adjustments, building a solid foundation for further exploration
Suitable for beginners interested in image processing, providing a clear and accessible introduction to key concepts
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