Exploring Neural Filters in Adobe Photoshop
In this sample chapter from Adobe Photoshop Classroom in a Book 2024 Release, author Conrad Chavez explores the integration of machine learning with traditional Photoshop algorithms to enhance image processing. This chapter guides users through the capabilities and setup of Neural Filters in Adobe Photoshop, including photo restoration and colorization. It discusses performance requirements, practical applications, and output options, and also touches on Adobe's efforts to refine these filters based on user feedback and usage data.
This chapter is from the book
This chapter is from the book
This chapter is from the book
LESSON OVERVIEW
In this lesson, you’ll learn how to do the following:
Understand how Neural Filters are different than other filters and effects in Photoshop.
Explore the Neural Filters workspace.
Apply a Neural Filter to an image.
Combine multiple Neural Filters in a single layer or document.
This lesson will take about 30 minutes to complete. To get the lesson files used in this chapter, download them from the web page for this book at peachpit.com/PhotoshopCIB2024. For more information, see “Accessing the lesson files and Web Edition” in the Getting Started section at the beginning of this book.
As you work on this lesson, you’ll preserve the start files. If you need to restore the start files, download them from your Account page.
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PROJECT: COMPOSITING WITH NEURAL FILTERS
Landscape: © Jurik Peter, Shutterstock; superhero: © sunlight19, Shutterstock
Neural Filters are advanced filters trained using machine learning. You can explore ideas that would be more labor-intensive, or sometimes impossible, with conventional digital photo filters and effects.
Understanding Neural Filters
If you worked through the earlier lessons in this book, you’ve used Photoshop filters such as Surface Blur, Smart Sharpen, Clouds, and Liquify. Those are conventional filters that produce their results with algorithms—procedural programs where the code itself determines the result.
The newer Neural Filters produce results in a different way, combining traditional algorithms with machine learning and other advanced techniques. Machine learning means that a filter in Neural Filters can be trained using many examples of desirable and undesirable results, potentially creating better images than what could be achieved with procedural computer code alone.
Neural Filters are different from other Photoshop effects in the following ways:
Neural Filters are trained using machine learning techniques.
Some filters need to be downloaded before the first time you use them. This is partly to save space on your computer, because some Neural Filters and their machine-learning models can be large. If you need to download a Neural Filter, you can do it with one click in the Neural Filters workspace.
Some filters display a message saying that they process image data in the cloud (on Adobe Creative Cloud servers). They may need more power than a desktop computer has, or a machine-learning model may be too large to download.
It’s possible to use some Neural Filters without an Internet connection, but you get the most options when your computer is connected to the Internet.