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https://github.com/osciiart/deepaa
make ASCII Art by Deep Learning
https://github.com/osciiart/deepaa
ascii-art deep-learning keras python tensorflow
Last synced: 4 days ago
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make ASCII Art by Deep Learning
- Host: GitHub
- URL: https://github.com/osciiart/deepaa
- Owner: OsciiArt
- License: mit
- Created: 2017-03-05T11:18:43.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2021-07-14T02:47:40.000Z (over 3 years ago)
- Last Synced: 2025-01-12T14:05:35.039Z (11 days ago)
- Topics: ascii-art, deep-learning, keras, python, tensorflow
- Language: Python
- Homepage:
- Size: 19.1 MB
- Stars: 1,530
- Watchers: 40
- Forks: 102
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
DeepAA
====
This is convolutional neural networks generating ASCII art.
This repository is under construction.
This work is accepted by [NIPS 2017 Workshop, Machine Learning for Creativity and Design](https://nips2017creativity.github.io/)
The paper: [ASCII Art Synthesis with Convolutional Networks](https://nips2017creativity.github.io/doc/ASCII_Art_Synthesis.pdf)
[Web application (using previous version model)](https://tar-bin.github.io/DeepAAonWeb/) (by [tar-bin](https://github.com/tar-bin))
## Change log
+ 2017/12/2 added light model
## Requirements
+ TensorFlow (1.3.0)
+ Keras (2.0.8)
+ NumPy (1.13.3)
+ Pillow (4.2.1)
+ Pandas (0.18.0)
+ Scikit-learn (0.19.0)
+ h5py (2.7.1)
+ model's weight (download it from [here](https://drive.google.com/open?id=0B90WglS_AQWebjBleG5uRXpmbUE) and place it in dir `model`.)
+ training data (additional, download it from [here](https://drive.google.com/open?id=1L5n5ICrsXtsWkT-aq2et1FTzp-RH3CeS), extract it and place the extracted directory in dir `data`.)
)
## How to use
please change the line 15 of `output.py `
```
image_path = 'sample images/original images/21 original.png' # put the path of the image that you convert.
```
into the path of image file that you use.
You should use a grayscale line image.
then run `output.py `.
converted images will be output at `output/ `.
You can select light model by change the line 13, 14 of `output.py ` into
```
model_path = "model/model_light.json"
weight_path = "model/weight_light.hdf5"
```
## License
The pre-trained models and the other files we have provided are licensed under the MIT License.