This project implements Neural Style Transfer (NST) using VGG19 as the feature extractor and a logistic regression classifier trained with contrastive learning to distinguish between stylized images generated from the same content image with different styles and stylized images generated from different content images.

• Python 3.x
• TensorFlow
• Keras
• OpenCV
• NumPy
• Matplotlib
• scikit-learn

You can install the required packages using the following command:

pip install -r requirements.txt

1. Clone this repository:

git clone https://github.com/your-username/neural-style-transfer.git

2. Navigate to the project directory:

cd neural-style-transfer

3. Place your content images in the content_images directory and your style images in the style_images directory.

4. Run the ipynb notebook to perform style transfer and contrastive learning:

5. The stylized images will be saved in the output_stylized_images directory.