Using Tensorflow for Image Style Transfer

Offered By
Coursera Project Network
In this Guided Project, you will:

Transfer artistic styles from one image and apply them to another image

Clock2 hours
IntermediateIntermediate
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

Have you ever wished you could paint like Van Gogh, Monet or even Picasso? Better yet, have you wished for an easy way to convert your own images into new ones incorporating the style of these famous artists? With Neural Style Transfer, Convolutional Neural Networks (CNNs) distill the essence of the style of any famous artist it is fed, and are able to transfer that style to any other image. In this project-based course, you will learn how to utilize Python and Tensorflow to build a Neural Style Transfer (NST) model using a VGG19 CNN. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Introducing Neural Style Transfer with Examples

  2. Setup and Configure Modules and Visualizing the Inputs

  3. Defining content and style representations

  4. Building the model and calculating and extracting style with intermediate feature maps

  5. Training the Model

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Frequently asked questions

Frequently Asked Questions

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