Pytorch implementation of Nueral Style transfer

Last update: Oct 15, 2022

Overview

Nueral Style Transfer

Pytorch implementation of Nueral style transfer algorithm , it is used to apply artistic styles to content images . Content is the layout or the sketch and Style being the painting or the colors.

Examples

Getting Started

Prerequisite

Python 3+ (tested on python 3.9)
pytorch
Nvidia Gpu(not necessary but it will significantly boost your training speed)

Installation

Clone the repo

git clone https://github.com/abhinav-TB/Neural-Style-Transfer.git

Install python packages
```
pip install -r requirements.txt
```

Training

Command line Arguments

Parameter	Type	Description
`-s`	`string`	Required. path to style image
`-c`	`string`	Required. path to content image
`-e`	`string`	Required. Number of training loops
`-o`	`string`	Output folder path

start training

python main.py

Example

python main.py -s ./style/style5.jpg -c ./content/trees.jpg -e 2500

Contributing

Contributions are what makes the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

Fork the Project
Create your Feature Branch (git checkout -b feature/AmazingFeature)
Commit your Changes (git commit -m 'Add some AmazingFeature')
Push to the Branch (git push origin feature/AmazingFeature)
Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.

Contact

@abhiGamez on Twitter

Acknowledgements

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Pytorch implementation of Nueral Style transfer

Related tags

Overview

Nueral Style Transfer

Examples

Getting Started

Prerequisite

Installation

Training

Contributing

License

Contact

Acknowledgements

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