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Could someone explains whats is going on here? What are the steps? Why those colorful artifacts appear before the final result?
by motoboi 9y ago
Could someone explains whats is going on here? What are the steps? Why those colorful artifacts appear before the final result?
- dordoka 9y agoIt´s just a demo of an upcoming open source API that allows running deep neural network models on the browser. Steps (disclaimer: I´m not related to the creators, so this is just what I understand it does) 1.- You upload your image 2.- Select an image to be the origin of the style 3.- Downloading Model: downloads a trained (on style transfering) deep neural net 4.- Colorful artifacts: the model is applied to your image. Probably the artifacts are a visualization of the network weights being transformed to WebGL shaders, or just a simple visualization of the internal hidden steps of the transformation 5.- You get your image with the style applied
- antimatter15 9y agoIt's showing a visualization of all the intermediate activations of the style transfer network. The intermediate pictures are 4D, so they're visualized as a sequence of tiles. The network being run is defined here https://github.com/lengstrom/fast-style-transfer/blob/master/src/transform.py#L5 https://github.com/lengstrom/fast-style-transfer/blob/master... This post provides a pretty good explanation of what's happening: https://shafeentejani.github.io/2017-01-03/fast-style-transfer/#image-transformation-network https://shafeentejani.github.io/2017-01-03/fast-style-transf... There's a sequence of 9x9 and 3x3 convolutions that transforms that one big input image into a bunch of smaller images. They're processed by a sequence of residual convolutions. Finally, these tiny tiles are merged together back into a stylized image of the same size as the original input with a few deconvolution operations.