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TensorFlow-neural-style-transfer

Overview ☁️

This project demonstrates how to use TensorFlow to implement neural style transfer, a technique for blending the artistic style of one image with the content of another. Neural style transfer uses deep learning to combine the content of an image with the style of another, producing a new image that retains the content of the original image while adopting the artistic style of the style image.

Features 🛠️

  • Content and Style Images: Use any two images to blend their content and style.
  • Customizable Weights: Adjust the weights for content and style loss to fine-tune the output.
  • Image Optimization: Iteratively update the output image to minimize the loss function.
  • TensorFlow Implementation: Leverages TensorFlow's capabilities for efficient computation and model building.

Prerequisites ⚙️

pip install tensorflow-hub
pip install tensorflow
pip install matplotlib
pip install numpy
pip install opencv-pyton
pip install streamlit

How to Run 🧭

streamlit run style_transfer.py

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