Deep Learning with PyTorch : Neural Style Transfer

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Coursera Project Network
在此免费指导项目中,您将:

Understand Neural Style Transfer Practically

Be able to create artistic style image by applying style transfer using pytorch

Showcase this hands-on experience in an interview

Clock2 Hours
Intermediate中级
Cloud无需下载
Video分屏视频
Comment Dots英语(English)
Laptop仅限桌面

In this 2 hour-long project-based course, you will learn to implement neural style transfer using PyTorch. Neural Style Transfer is an optimization technique used to take a content and a style image and blend them together so the output image looks like the content image but painted in the style of the style image. We will create artistic style image using content and given style image. We will compute the content and style loss function. We will minimize this loss function using optimization techniques to get an artistic style image that retains content features and style features. This guided project is for learners who want to apply neural style transfer practically using PyTorch. In order to be successful in this guided project, you should be familiar with the theoretical concept of neural style transfer, python programming, and convolutional neural networks.A google account is needed to use the Google colab environment.

您要培养的技能

Convolutional Neural NetworkDeep LearningpytorchNeural Style Transfer

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

  1. Set google colab runtime

  2. Loading VGG-19 pretrained model

  3. Preprocess Image

  4. Deprocess Image

  5. Create content and style loss

  6. Get content,style features and create gram matrix

  7. Training loop

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

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