Seed image with arbitrary images#3
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You might want to make the version number even higher here, but before keras 1.1.0 you'll get the error: `ModuleNotFoundError: No module named 'keras.applications'`. Before keras 2.0.0 you'll get the error: `ImportError: cannot import name 'conv_utils'`
If I let this default to the the Theano backend, I get:
```
Traceback (most recent call last):
File "synthesize.py", line 91, in <module>
pyramid_model = gram.make_pyramid_model(args.octaves, args.padding_mode)
File "/Users/ryan/mess/2017/42/subjective-functions/gram.py", line 242, in make_pyramid_model
level = reduce_layer(padding_mode=padding_mode)(gaussian_pyramid[-1])
File "/usr/local/lib/python3.6/site-packages/keras/engine/topology.py", line 602, in __call__
output = self.call(inputs, **kwargs)
File "/usr/local/lib/python3.6/site-packages/keras/layers/core.py", line 650, in call
return self.function(inputs, **arguments)
File "/Users/ryan/mess/2017/42/subjective-functions/gram.py", line 150, in fn
return K.conv2d(K.conv2d(x, kernel_3d, strides=(2,1)),
File "/usr/local/lib/python3.6/site-packages/keras/backend/theano_backend.py", line 1878, in conv2d
kernel_shape = kernel.eval().shape
AttributeError: 'numpy.ndarray' object has no attribute 'eval'
```
Specify TensorFlow backend in README
Update requirements.txt
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I don't know if you're interested in this at all, but I wanted to play around with it and thought you might find it useful. Add the argument "--seed-image /path/to/seed/image.jpg" to seed with an arbitrary image file. Note that adjusting the output size can only be done with "output_width" and maintains the aspect ratio of the input image. So, if you give a seed image and specify only output_height, the original image size is used.