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Image style transfer is a deep learning technique that allows you to take the artistic style of one image and apply it to the content of another image, creating a unique and visually stunning hybrid image.

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AnishaVS07/Image_Style_Transfer-Deep_Learning_Project

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Deep Learning Image Style Transfer

This repository contains an implementation of the Neural Style Transfer algorithm, which combines the content of one image with the artistic style of another image using deep learning techniques. The model is based on the approach proposed in the seminal paper "A Neural Algorithm of Artistic Style" by Gatys et al. (2015).

Overview :

Style transfer is the process of rendering a content image in the artistic style of a style image, creating visually appealing and artistic outputs. The algorithm optimizes a loss function that captures both the content representation of the content image and the style representation of the style image. The content loss is computed using a pre-trained convolutional neural network (CNN), typically a VGG network, which extracts high-level features from the content image. The style loss is also computed using the same CNN, but it captures the style information by comparing the Gram matrices of the feature maps between the style image and the generated output image.

Features :

~ Style Transfer: Render a content image in the artistic style of a given style image.

~ Multiple Style Images: Support for transferring the style from multiple style images onto a single content image.

~ Content Weight: Adjust the relative importance of the content image compared to the style image(s).

~ Style Weight: Control the strength of the style transfer effect.

~ Content Layers: Specify the layers of the CNN to be used for computing the content loss.

~ Style Layers: Specify the layers of the CNN to be used for computing the style loss.

~ GPU Support: Leverage GPU acceleration for faster training and style transfer.

Examples :

Check out the examples directory for sample content and style images, as well as the generated stylized outputs.

Contributing :

Contributions are welcome! Please feel free to submit issues or pull requests for bug fixes, improvements, or new features.

License :

This project is licensed under the MIT License.

References :

Gatys, L. A., Ecker, A. S., & Bethge, M. (2015). A Neural Algorithm of Artistic Style. arXiv preprint arXiv:1508.06576. https://www.tensorflow.org/tutorials/generative/style_transfer

Contact If you have any questions, suggestions, or feedback, feel free to contact me.

Email ID : [email protected]

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Image style transfer is a deep learning technique that allows you to take the artistic style of one image and apply it to the content of another image, creating a unique and visually stunning hybrid image.

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