An implementation of "Optimal Textures: Fast and Robust Texture Synthesis and Style Transfer through Optimal Transport"

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Deep Learning OptimalTextures
Overview

Optex

An implementation of Optimal Textures: Fast and Robust Texture Synthesis and Style Transfer through Optimal Transport for TU Delft CS4240.

Simplified diagram of the algorithm

You can find a more in-depth summary of the implementation in this blog post.

Installation

git clone https://github.com/JCBrouwer/OptimalTextures
cd OptimalTextures
pip install -r requirements.txt
python optex.py -h

Texture synthesis

Generate a texture based on an example:

python optex.py --style style/graffiti.jpg --size 512

Style transfer

Supply two images and synthesize one in the style of the other.

python optex.py --style style/lava-small.jpg --content content/rocket.jpg --content_strength 0.2

Texture mixing

Blend two textures together.

python optex.py --style style/zebra.jpg style/pattern-small.jpg --mixing_alpha 0.5

Color transfer

Perform style transfer but keep the original colors of the content.

python optex.py --style style/green-paint-large.jpg --content content/city.jpg --style_scale 0.5 --content_strength 0.2 --color_transfer opt --size 1024
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Comments
  • numpy can't convert cuda tensor

    numpy can't convert cuda tensor

    Out of the box (using conda python 3.8.5 and pytorch 1.8.1) was getting this error:

    TypeError: can't convert cuda:0 device type tensor to numpy. Use Tensor.cpu() to copy the tensor to host memory first.

    With this trace:

      File "optex.py", line 304, in <module>
    output = optimal_texture(**vars(args))
  File "optex.py", line 55, in optimal_texture
    style_layers, style_eigvs, content_layers = encode_inputs(styles, content, use_pca=use_pca)
  File "optex.py", line 141, in encode_inputs
    style_layers[l], eigvecs = fit_pca(style_layers[l])  # PCA
  File "optex.py", line 160, in fit_pca
    k = np.argmax(np.cumsum([i / total_variance for i in eigvals.cpu()]) > 0.9)
  File "<__array_function__ internals>", line 5, in cumsum
  File ".../numpy/core/fromnumeric.py", line 2511, in cumsum
    return _wrapfunc(a, 'cumsum', axis=axis, dtype=dtype, out=out)
  File ".../numpy/core/fromnumeric.py", line 55, in _wrapfunc
    return _wrapit(obj, method, *args, **kwds)
  File ".../numpy/core/fromnumeric.py", line 44, in _wrapit
    result = getattr(asarray(obj), method)(*args, **kwds)
  File ".../numpy/core/_asarray.py", line 102, in asarray
    return array(a, dtype, copy=False, order=order)
  File ".../torch/tensor.py", line 621, in __array__
    return self.numpy()

    Converting the total_variance and eigvals in fit_pca() to cpu seemed to fix it though.

    Really enjoying playing with this!

    opened by RKelln 2
Owner
Hans Brouwer
Hans Brouwer
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