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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
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# PixelCNN & PixelRNN in TensorFlow
TensorFlow implementation of [Pixel Recurrent Neural Networks](https://arxiv.org/abs/1601.06759). This implementation contains:
1. PixelCNN
- Masked Convolution (A, B)
2. PixelRNN
- Row LSTM (in progress)
- Diagonal BiLSTM (skew, unskew)
- Residual Connections
- Multi-Scale PixelRNN (in progress)
3. Datasets
- MNIST
- cifar10 (in progress)
- ImageNet (in progress)
## Requirements
- Python 2.7
- [Scipy](https://www.scipy.org/)
- [TensorFlow](https://www.tensorflow.org/) 0.9+
## Usage
First, install prerequisites with:
$ pip install tqdm gym[all]
To train a `pixel_rnn` model with `mnist` data (slow iteration, fast convergence):
$ python main.py --data=mnist --model=pixel_rnn
To train a `pixel_cnn` model with `mnist` data (fast iteration, slow convergence):
$ python main.py --data=mnist --model=pixel_cnn --hidden_dims=64 --recurrent_length=2 --out_hidden_dims=64
To generate images with trained model:
$ python main.py --data=mnist --model=pixel_rnn --is_train=False
## Samples
Samples generated with `pixel_cnn` after 50 epochs.
## Training details
Below results uses two different parameters
[1] `--hidden_dims=16 --recurrent_length=7 --out_hidden_dims=32`
[2] `--hidden_dims=64 --recurrent_length=2 --out_hidden_dims=64`
Training results of `pixel_rnn` with \[1\] (yellow) and \[2\] (green) with `epoch` as x-axis:
Training results of `pixel_cnn` with \[1\] (orange) and \[2\] (purple) with `epoch` as x-axis:
Training results of `pixel_rnn` (yellow, green) and `pixel_cnn` (orange, purple) with `hour` as x-axis:
## References
- [Pixel Recurrent Neural Networks](https://arxiv.org/abs/1601.06759)
- [Conditional Image Generation with PixelCNN Decoders](https://arxiv.org/abs/1606.05328)
- [Review by Kyle Kastner](https://github.com/tensorflow/magenta/blob/master/magenta/reviews/pixelrnn.md)
- [igul222/pixel_rnn](https://github.com/igul222/pixel_rnn)
- [kundan2510/pixelCNN](https://github.com/kundan2510/pixelCNN)
## Author
Taehoon Kim / [@carpedm20](http://carpedm20.github.io/)
Excerpt of 2,353 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:911ebe4f2f6c70ef, topic:tensorflow