Train CPPNs as a Generative Model, using Generative Adversarial Networks and Variational Autoencoder techniques to produce high resolution images.

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Deep Learning cppn-gan-vae-tensorflow
Overview

cppn-gan-vae tensorflow

Train Compositional Pattern Producing Network as a Generative Model, using Generative Adversarial Networks and Variational Autoencoder techniques to produce high resolution images.

Morphing

Run python train.py from the command line to train from scratch and experiment with different settings.

sampler.py can be used inside IPython to interactively see results from the models being trained.

See my blog post at blog.otoro.net for more details.

I tested the implementation on TensorFlow 0.60.

Used images2gif.py written by Almar Klein, Ant1, Marius van Voorden.

License

BSD - images2gif.py

MIT - everything else

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Comments
  • tensorflow.python.framework.errors.NotFoundError: save/save

    tensorflow.python.framework.errors.NotFoundError: save/save

    rzai@rzai00:~/prj/cppn-gan-vae-tensorflow$ CUDA_VISIBLE_DEVICES=1 python train.py I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcublas.so locally I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcudnn.so locally I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcufft.so locally I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcuda.so.1 locally I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcurand.so locally ('Extracting', 'MNIST_data/train-images-idx3-ubyte.gz') /usr/lib/python2.7/gzip.py:268: VisibleDeprecationWarning: converting an array with ndim > 0 to an index will result in an error in the future chunk = self.extrabuf[offset: offset + size] /home/rzai/prj/cppn-gan-vae-tensorflow/mnist_data.py:38: VisibleDeprecationWarning: converting an array with ndim > 0 to an index will result in an error in the future data = data.reshape(num_images, rows, cols, 1) ('Extracting', 'MNIST_data/train-labels-idx1-ubyte.gz') ('Extracting', 'MNIST_data/t10k-images-idx3-ubyte.gz') ('Extracting', 'MNIST_data/t10k-labels-idx1-ubyte.gz') WARNING:tensorflow:tf.op_scope(values, name, default_name) is deprecated, use tf.name_scope(name, default_name, values) WARNING:tensorflow:tf.op_scope(values, name, default_name) is deprecated, use tf.name_scope(name, default_name, values) WARNING:tensorflow:tf.op_scope(values, name, default_name) is deprecated, use tf.name_scope(name, default_name, values) I tensorflow/core/common_runtime/gpu/gpu_device.cc:951] Found device 0 with properties: name: GeForce GTX 1080 major: 6 minor: 1 memoryClockRate (GHz) 1.7335 pciBusID 0000:01:00.0 Total memory: 7.92GiB Free memory: 7.41GiB I tensorflow/core/common_runtime/gpu/gpu_device.cc:972] DMA: 0 I tensorflow/core/common_runtime/gpu/gpu_device.cc:982] 0: Y I tensorflow/core/common_runtime/gpu/gpu_device.cc:1041] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 1080, pci bus id: 0000:01:00.0) loading model: save/model.ckpt-0 Traceback (most recent call last): File "train.py", line 124, in main() File "train.py", line 45, in main return train(args) File "train.py", line 73, in train cppnvae.load_model(dirname) File "/home/rzai/prj/cppn-gan-vae-tensorflow/model.py", line 323, in load_model self.saver.restore(self.sess, checkpoint_path+'/'+ckpt.model_checkpoint_path) File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/saver.py", line 1340, in restore if not file_io.get_matching_files(file_path): File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/lib/io/file_io.py", line 231, in get_matching_files compat.as_bytes(filename), status)] File "/usr/lib/python2.7/contextlib.py", line 24, in exit self.gen.next() File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/errors.py", line 463, in raise_exception_on_not_ok_status pywrap_tensorflow.TF_GetCode(status)) tensorflow.python.framework.errors.NotFoundError: save/save rzai@rzai00:~/prj/cppn-gan-vae-tensorflow$

    opened by loveJasmine 0
Owner
hardmaru
I make simple things with neural networks.
hardmaru
GitHub
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