Neural style transfer is an optimization technique used to take two images—a content image and a style reference image and blend them together so the output image looks like the content image, but “painted” in the style of the style reference image.
- For fun
- To learn
Neural Image Style Transfer Project was implemented using Pytorch framework. Used a pre-trained VGG-19 convolutional neural network as a feature extractor for content image and style image and later backpropagated it to minimize the loss function to get the required target image.
- Jupyter Notebook
- Pythorch framework
- General ML Libraries
- To deploy the project using cloud services to get better result.