cs501r_f2016:lab13
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| ====Description:==== | ====Description:==== | ||
| - | For this lab, you should implement the style transfer algorithm referenced above. We are providing the following: | + | For this lab, you should implement the style transfer algorithm referenced above. We are providing the following, [[https://www.dropbox.com/sh/tt0ctms12aumgui/AACRKSSof6kw-wi8vs1v8ls3a?dl=0 |
| + | |available from a dropbox folder]]: | ||
| + | |||
| + | - lab10_scaffold.py - Lab 10 scaffolding code | ||
| + | - vgg16.py - The VGG16 model | ||
| + | - content.png - An example content image | ||
| + | - style.png - An example style image | ||
| + | |||
| + | You will also need the VGG16 pre-trained weights: | ||
| - | - [[http://liftothers.org/byu/lab10_scaffold.py.txt|Lab 10 scaffolding code]] | ||
| - | - [[http://liftothers.org/byu/vgg16.py.txt|The VGG16 model]] | ||
| - [[http://liftothers.org/byu/vgg16_weights.npz|VGG16 weights]] | - [[http://liftothers.org/byu/vgg16_weights.npz|VGG16 weights]] | ||
| - | - [[http://liftothers.org/byu/content.png|An example content image]] | + | |
| - | - [[http://liftothers.org/byu/style.png|An example style image]] | + | |
| In the scaffolding code, you will find some examples of how to use the provided VGG model. (This model is a slightly modified version of [[https://www.cs.toronto.edu/~frossard/post/vgg16/|code available here]]). | In the scaffolding code, you will find some examples of how to use the provided VGG model. (This model is a slightly modified version of [[https://www.cs.toronto.edu/~frossard/post/vgg16/|code available here]]). | ||
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| I found that it was important to clip pixel values to be in [0,255]. To do that, every 100 iterations I extracted the image, clipped it, and then assigned it back in. | I found that it was important to clip pixel values to be in [0,255]. To do that, every 100 iterations I extracted the image, clipped it, and then assigned it back in. | ||
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| + | ...although now that I think about it, perhaps I should have been operating on whitened images from the beginning! You should probably try that. | ||
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| + | ---- | ||
| + | ====Bonus:==== | ||
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| + | There's no official extra credit for this lab, but have some fun with it! Try different content and different styles. See if you can get nicer, higher resolution images out of it. | ||
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| + | Also, take a look at the vgg16.py code. What happens if you swap out max pooling for average pooling? | ||
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| + | What difference does whitening the input images make? | ||
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| + | Show me the awesome results you can generate! | ||
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cs501r_f2016/lab13.txt · Last modified: 2021/06/30 23:42 (external edit)
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