https://github.com/nourmorsy/nueral_style_transform

https://github.com/nourmorsy/nueral_style_transform

Last synced: 5 days ago
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• Host: GitHub
• URL: https://github.com/nourmorsy/nueral_style_transform
• Owner: nourmorsy
• Created: 2023-12-15T01:02:22.000Z (11 months ago)
• Default Branch: main
• Last Pushed: 2023-12-15T01:04:27.000Z (11 months ago)
• Last Synced: 2023-12-15T02:53:14.239Z (11 months ago)
• Language: Jupyter Notebook
• Size: 6.17 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Neural Style Transfer Project

## Overview and Goal

This project implements neural style transfer techniques, inspired by the paper [A Neural Algorithm of Artistic Style](https://arxiv.org/abs/1508.06576). The objective is to blend the artistic style of one image with the content of another, creating a visually compelling result that merges elements from both images. Using the VGG network as a feature extractor, this project reconstructs artistic styles in a way that mimics the work detailed in the referenced paper.

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## Dependencies

To run this project, you’ll need:

- Python 3.x

- Jupyter Notebook

- Required Python libraries:

  ```bash

  pip install torch torchvision opencv-python numpy matplotlib

  ```

---

## Files Description

- **nueral_style_transform.ipynb**: The primary notebook that implements neural style transfer, using deep learning techniques and the VGG model as a feature extractor.

- **vgg.ipynb** : A supporting notebook focused on loading and visualizing VGG network layers, used in feature extraction for style transfer.

## Usage

 - Open the **nueral_style_transform.ipynb** notebook in Jupyter

  ```bash

  jupyter notebook nueral_style_transform.ipynb

  ```

- Follow the instructions within the notebook to load images and apply style transfer.