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added license
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awentzonline committed Mar 10, 2016
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19 changes: 19 additions & 0 deletions LICENSE.txt
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The MIT License (MIT)
Copyright (c) 2016 Adam Wentz

Permission is hereby granted, free of charge, to any person obtaining a copy of
this software and associated documentation files (the "Software"), to deal in the
Software without restriction, including without limitation the rights to use,
copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the
Software, and to permit persons to whom the Software is furnished to do so,
subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
7 changes: 7 additions & 0 deletions README.md
Expand Up @@ -95,3 +95,10 @@ analogy loss on for some extra style guidance.
If you'd like to only visualize the analogy target to see what's happening, If you'd like to only visualize the analogy target to see what's happening,
set the MRF and content loss to zero: `--mrf-w=0 --content-w=0` This is also set the MRF and content loss to zero: `--mrf-w=0 --content-w=0` This is also
much faster as MRF loss is the slowest part of the algorithm. much faster as MRF loss is the slowest part of the algorithm.

License
-------
The code for this implementation is provided under the MIT license.

I'm not familiar with whatever legal encumbrances may exist with the
algorithms themselves or using the pre-trained VGG16 model.

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