What is Style Transfer?
Def :- Style transfer is an optimization problem. Where we try to apply a pre-calculated model (the style) to an input image.
Input Image + Style Image -> Output Image (Styled Input)
How we do ?
For this, we define a loss function that we want to minimize—this is a weighted sum of the error (loss) between the original image and the produced image, and the error between the original style and the applied one. By adjusting the weighting parameters, we can give more importance to the original image (the content image) or the style used (extracted from the style image).
There is a pre-trained Convolutional Neural Network (VGG16).
Use cases :-
- It is used for creating creative art works or styling the image of your choice. For example websites like deepart.io allow users to create their own artwork.
- Want to make you look the way you want in the camera or in image.
- Used in mobile applications for selfie/photo styling purpose.
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