https://github.com/jihoonerd/a-neural-algorithm-of-artistic-style
📖 Paper: A Neural Algorithm of Artistic Style 🖼️
https://github.com/jihoonerd/a-neural-algorithm-of-artistic-style
deep-learning style-transfer tensorflow2 vgg19
Last synced: 7 months ago
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📖 Paper: A Neural Algorithm of Artistic Style 🖼️
- Host: GitHub
- URL: https://github.com/jihoonerd/a-neural-algorithm-of-artistic-style
- Owner: jihoonerd
- License: mit
- Created: 2019-11-25T10:15:40.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2024-04-19T15:04:18.000Z (over 1 year ago)
- Last Synced: 2025-01-15T17:32:08.552Z (9 months ago)
- Topics: deep-learning, style-transfer, tensorflow2, vgg19
- Language: Python
- Homepage:
- Size: 354 KB
- Stars: 2
- Watchers: 4
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# A Neural Algorithm of Artistic Style
|Content|Style|Style Transfer|
|---|---|---|
||||
||||
||||
This repository implements the paper: **[A Neural Algorithm of Artistic Style](https://arxiv.org/abs/1508.06576)**.
## Features
* Employed ***TensorFlow 2*** with performance optimization
* Simple structure
* Easy to reproduce
## Model Structure
As mentioned in paper, this approache make use of the VGG network. I used VGG19 structure and weight from built-in tensorflow library. (`tf.keras.applications.VGG19`)
I used `block4_conv2` as a content layer and `['block1_conv1', 'block2_conv1', 'block3_conv1', 'block4_conv1', 'block5_conv1']` as style layers. And average pooling is used instead of max pooling as noted in the paper.
## Requirements
Install packages through `requirements.txt`.
Also, you need trained `VGG19` network unless you already have it. First call `VGG19` will automatically download the network. If you want to download model weight without running whole script, you can do as follow:
```bash
$ python download_vgg.py
```
### GPU Settings
Tensorflow 2 code is optimized for GPU running.
***Default running environment is assumed to be CPU-ONLY. If you want to run this repo on GPU machine, just replace `tensorflow` to `tensorflow-gpu` in package lists.***
## How to install
### `virtualenv`
```bash
$ virtualenv venv
$ source venv/bin/activate
$ pip install -r requirements.txt
```
### `venv`
```bash
$ python3 -m venv venv
$ source venv/bin/activate
$ pip install -r requirements.txt
```
## How to run
```bash
$ python main.py --help
usage: main.py [-h] [--content_url CONTENT_URL] [--style_url STYLE_URL]
[--quick] [--train_epochs TRAIN_EPOCHS]
[--log_interval LOG_INTERVAL]
A Neural Algorithm of Artistic Style
optional arguments:
-h, --help show this help message and exit
--content_url CONTENT_URL
Content image url
--style_url STYLE_URL
Style image url
--quick Set input image as the content image
--train_epochs TRAIN_EPOCHS
--log_interval LOG_INTERVAL
```
You can give custom image url to `content_url` and `style_url` arguemtns.
If you set `quick`, style transfer will start from your content image instead of white noise. This will give you the result much faster than starting from white noise.
## Test
`pytest` is used for testing.
```bash
============================= test session starts ==============================
platform linux -- Python 3.6.9, pytest-5.0.1, py-1.8.0, pluggy-0.13.1
rootdir: /home/jihoon/Documents/A-Neural-Algorithm-of-Artistic-Style
collected 3 items
test/test_styletf.py ... [100%]
=============================== warnings summary ===============================
venv/lib/python3.6/site-packages/tensorflow_core/python/pywrap_tensorflow_internal.py:15
/home/jihoon/Documents/A-Neural-Algorithm-of-Artistic-Style/venv/lib/python3.6/site-packages/tensorflow_core/python/pywrap_tensorflow_internal.py:15: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp
-- Docs: https://docs.pytest.org/en/latest/warnings.html
==================== 3 passed, 1 warnings in 24.53 seconds =====================
```
## BibTeX
```
@article{DBLP:journals/corr/GatysEB15a,
author = {Leon A. Gatys and
Alexander S. Ecker and
Matthias Bethge},
title = {A Neural Algorithm of Artistic Style},
journal = {CoRR},
volume = {abs/1508.06576},
year = {2015},
url = {http://arxiv.org/abs/1508.06576},
archivePrefix = {arXiv},
eprint = {1508.06576},
timestamp = {Mon, 13 Aug 2018 16:48:03 +0200},
biburl = {https://dblp.org/rec/bib/journals/corr/GatysEB15a},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
```
## Author
Jihoon Kim ([@jihoonerd](https://github.com/jihoonerd))