Mastering Neural Style Transfer: Tensorflow, Keras & Python

سرفصل های دوره

Hands-on Neural Style Transfer: Creating Artistic Images using Tensorflow, Keras, Python, and Google Colab

1 - Fundamentals

1 - Introduction

2 - What is Neural Style Transfer

3 - About this Project

4 - Why Should we Learn

5 - Applications

6 - Why Keras and Python

7 - Why Google Colab

2 - Model Building and Prediction

8 - Setup the Working Directory

8 - code.zip

8 - content-image.zip

8 - style-image.zip

9 - Contents in Directory

10 - Activate GPU

11 - Checking the availability and usage of GPUs

12 - Mount Google Drive to Google Colab

13 - Necessary library imports

14 - Setting the directory path

15 - Displaying the base image and the style reference

16 - Defining the desired dimensions

17 - Preprocesses an image

18 - Convert the generated image back to its original format

19 - Calculate the Gram matrix

20 - Calculates the style loss

21 - Calculates the content loss

22 - Calculates the total variation loss

23 - Loading the VGG19

24 - Creating a dictionary

25 - Building a feature extraction model

26 - Define the names of the style layers and the content layer

27 - Set the weights

28 - Calculates the total loss

29 - Computes the loss and gradients

30 - Set up the optimizer

31 - Preprocess the base image style reference image and combination image

32 - Perform the style transfer optimization loop

33 - Save and display the final generated image

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تولید کننده: Udemy-Training