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https://github.com/zsdonghao/text-to-image
Generative Adversarial Text to Image Synthesis / Please Star -->
https://github.com/zsdonghao/text-to-image
gan tensorflow tensorlayer text-to-image
Last synced: 21 days ago
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Generative Adversarial Text to Image Synthesis / Please Star -->
- Host: GitHub
- URL: https://github.com/zsdonghao/text-to-image
- Owner: zsdonghao
- Created: 2016-11-02T13:50:16.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2021-01-22T07:11:25.000Z (almost 4 years ago)
- Last Synced: 2024-11-20T09:24:15.342Z (24 days ago)
- Topics: gan, tensorflow, tensorlayer, text-to-image
- Language: Python
- Homepage: https://github.com/zsdonghao/tensorlayer
- Size: 755 KB
- Stars: 600
- Watchers: 30
- Forks: 162
- Open Issues: 35
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-tensorlayer - GAN-CLS for Text to Image Synthesis
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README
# Text To Image Synthesis
This is a tensorflow implementation of synthesizing images. The images are synthesized using the GAN-CLS Algorithm from the paper [Generative Adversarial Text-to-Image Synthesis][2]. This implementation is built on top of the excellent [DCGAN in Tensorflow][3].
Plese star https://github.com/tensorlayer/tensorlayer
![Model architecture](http://i.imgur.com/dNl2HkZ.jpg)
Image Source : [Generative Adversarial Text-to-Image Synthesis][2] Paper
## Requirements
- [TensorFlow][4] 1.0+
- [TensorLayer](https://github.com/zsdonghao/tensorlayer) 1.4+
- [NLTK][8] : for tokenizer## Datasets
- The model is currently trained on the [flowers dataset][9]. Download the images from [here][9] and save them in ```102flowers/102flowers/*.jpg```. Also download the captions from [this link][10]. Extract the archive, copy the ```text_c10``` folder and paste it in ```102flowers/text_c10/class_*```.**N.B** You can downloads all data files needed manually or simply run the downloads.py and put the correct files to the right directories.
```python
python downloads.py
```## Codes
- `downloads.py` download Oxford-102 flower dataset and caption files(run this first).
- `data_loader.py` load data for further processing.
- `train_txt2im.py` train a text to image model.
- `utils.py` helper functions.
- `model.py` models.## References
- [Generative Adversarial Text-to-Image Synthesis][2] Paper
- [Generative Adversarial Text-to-Image Synthesis][11] Torch Code
- [Skip Thought Vectors][1] Paper
- [Skip Thought Vectors][12] Code
- [Generative Adversarial Text-to-Image Synthesis with Skip Thought Vectors](https://github.com/paarthneekhara/text-to-image) TensorFlow code
- [DCGAN in Tensorflow][3]## Results
- the flower shown has yellow anther red pistil and bright red petals.
- this flower has petals that are yellow, white and purple and has dark lines
- the petals on this flower are white with a yellow center
- this flower has a lot of small round pink petals.
- this flower is orange in color, and has petals that are ruffled and rounded.
- the flower has yellow petals and the center of it is brown
- this flower has petals that are blue and white.
- these white flowers have petals that start off white in color and end in a white towards the tips.## License
Apache 2.0[1]:http://arxiv.org/abs/1506.06726
[2]:http://arxiv.org/abs/1605.05396
[3]:https://github.com/zsdonghao/dcgan
[4]:https://github.com/tensorflow/tensorflow
[5]:http://www.h5py.org/
[6]:https://github.com/Theano/Theano
[7]:http://scikit-learn.org/stable/index.html
[8]:http://www.nltk.org/
[9]:http://www.robots.ox.ac.uk/~vgg/data/flowers/102/
[10]:https://drive.google.com/file/d/0B0ywwgffWnLLcms2WWJQRFNSWXM/view
[11]:https://github.com/reedscot/icml2016
[12]:https://github.com/ryankiros/skip-thoughts
[13]:https://github.com/ryankiros/skip-thoughts#getting-started
[14]:https://bitbucket.org/paarth_neekhara/texttomimagemodel/raw/74a4bbaeee26fe31e148a54c4f495694680e2c31/latest_model_flowers_temp.ckpt