ArtisticVision

This project focuses on applying artistic styles to images using deep learning techniques. The goal is to transform the visual appearance of an image to match the style of a reference image.

Table of Contents

• Introduction
• Features
• Installation
• Usage
• Examples
• Contributing
• License

Introduction

Style Transfer is a technique that applies the visual style of one image to another image. This project leverages neural networks to achieve high-quality style transfer.

Features

• Apply artistic styles to images
• Fast image processing
• Support for various neural network architectures
• Easy-to-use command-line interface

Installation

To get started with this project, clone the repository and install the required dependencies:

git clone https://github.com/Yuval728/ArtisticVision.git
cd ArtisticVision
pip install -r requirements.txt

Usage

To apply style transfer to an image, use the following command:

python stylize.py --content_image path/to/input/image.jpg --model model/model.pt --output_image path/to/output/image.jpg --preserve_color   

Examples

Here are some examples of images processed with different styles:

• Original Image:

• Styled Image 1:

• Styled Image 2 (Preserve Color):

Contributing

Contributions are welcome! Please read the contributing guidelines for more information.

License

This project is licensed under the MIT License. See the LICENSE file for details.