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Fast Neural Style Transfer works like this: Each style image is actually trained on a neural network outside of the browser (using Python on Tensorflow) for aro
by reiinakano 9y ago
Fast Neural Style Transfer works like this: Each style image is actually trained on a neural network outside of the browser (using Python on Tensorflow) for around 6+ hours with a GPU.
The output is a neural network that can take any content image and outputs it in the style it was trained on.
The browser does this:
1. Downloads the model (6.6MB~) for the particular style.
2. Does one pass through the content image and outputs the styled image.
No training is done in the browser whatsoever.
- TekMol 9y agoYes, I am aware of that. But I would like to know how the training works. How does a NN learn the style of an image?
- reiinakano 9y agoAhh I see, these are some resources that should help you. The original Neural Style Transfer paper should help you understand the loss functions involved: https://arxiv.org/abs/1508.06576 https://arxiv.org/abs/1508.06576 The paper introducing Real-Time Style Transfer is basically the algorithm used here: https://arxiv.org/abs/1603.08155 https://arxiv.org/abs/1603.08155
- SamBam 9y agoI think you can consider one single image as a large corpus of data, in the same was that you could train a simple Markov model from a large paragraph of text. It doesn't matter to the model whether the original text was 500 words in one piece of text, or five 100-word texts. It's mostly looking at local regions and seeing what guesses it can make about the next region given one region. (If I understand correctly).