Style Transfer with PyTorch

سرفصل های دوره

This course covers the important aspects of neural style transfer, a technique for transforming images, and discusses Generative Adversarial Networks in order to efficiently create realistic images and videos.

1. Course Overview

1. Course Overview

2. Understanding Neural Style Transfer

01. Version Check

02. Module Overview

03. Prerequisites and Course Outline

04. Content, Style, and Target Images

05. Training the Target Image for Style Transfer

06. Content Loss

07. Style Loss - Cosine Similarity and Dot Products

08. Style Loss - Gram Matrix

09. Setting up a Deep Learning Virtual Machine

10. Using Convolution Filters to Detect Features

11. Module Summary

3. Implementing Neural Style Transfer in PyTorch

1. Module Overview

2. Pretrained Models for Style Transfer

3. Loading the VGG19 Pretrained Model

4. Exploring and Transforming the Content and Style Images

5. Extracting Feature Maps from the Content and Style Images

6. Calculating the Gram Matrix to Extract Style Information

7. Training the Target Image to Perform Style Transfer

8. Style Transfer Using AlexNet

9. Module Summary

4. Building Generative Adversarial Networks in PyTorch

01. Module Overview

02. Understanding Generative Adversarial Networks (GANs)

03. Training a GAN

04. Understanding the Leaky ReLU Activation Function

05. Loading and Exploring the MNIST Handwritten Digit Images

06. Setting up the Generator and Discriminator Neural Networks

07. Training the Discriminator

08. Training the Generator and Generating Fake Images

09. Cleaning up Resources

10. Summary and Further Study

439,000 تومان

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تولید کننده: PluralSight