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
- Clone this repository:
git clone https://github.com/your-username/neural-style-transfer.git
- Navigate to the project directory:
cd neural-style-transfer
-
Place your content images in the
content_images
directory and your style images in thestyle_images
directory. -
Run the ipynb notebook to perform style transfer and contrastive learning:
-
The stylized images will be saved in the
output_stylized_images
directory.