Deep Learning with PyTorch : Neural Style Transfer

4.3
50 個評分
提供方
Coursera Project Network
2,907 人已註冊
在此免費指導項目中,您將:

Understand Neural Style Transfer Practically

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

在面試中展現此實踐經驗

Clock2 Hours
Intermediate中級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

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.

您要培養的技能

  • Convolutional Neural Network
  • Deep Learning
  • pytorch
  • Neural Style Transfer

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  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

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

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