Artistic Style Transfer
An implementation of Advanced Neural Style Transfer Algorithm using Pytorch. This project demonstrates neural style transfer using deep learning techniques. Neural style transfer is a fascinating concept that combines the style of one image (typically an artwork) with the content of another image to create a unique artistic output.
Neural style transfer utilizes a pre-trained convolutional neural network (CNN) to extract features from both the style image and the content image. By minimizing the difference between the extracted features of the content image and the generated image, while also matching the style features of the style image, we can create a visually appealing image that combines the style and content. This project provides a Python implementation of neural style transfer using the popular deep learning library, Pytorch.
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