Neural Style Transfer Application 🚀

This is a PyQt-based application for performing Neural Style Transfer on images, videos, and live camera feeds. It leverages TensorFlow Hub for pre-trained models and CUDA for accelerated processing on compatible GPUs.

Demo

Features

• Image Styling: Apply artistic styles to static images.
• Video Styling: Process and stylize videos frame by frame efficiently.
• Live Camera Feed: Real-time style transfer for live camera input.
• Model Flexibility: Select models from TensorFlow Hub or your system.
• Interactive UI:
  • Select input images and videos via file dialogs.
  • Preview and process results directly in the application.
  • Output display with zoom for images and playback for videos.
• Processing Status: Animated popups indicating processing progress.

Installation

Prerequisites

• Python 3.8+
• CUDA Toolkit (if using GPU acceleration)
• Required Python libraries (install via requirements.txt)

Setup

1. Clone the repository:

   git clone https://github.com/jayeshrdeotalu/Nest-Neural-Style-Transfer.git   
   cd Nest-Neural-Style-Transfer

2. Install the dependencies:

     pip install -r requirements.txt

3. Ensure CUDA is installed and properly configured for GPU acceleration (optional).

Usage

1. Run the application:

   python app.py
   

2. Select the operation:

• Style an Image: Choose an input image and a style model.
• Style a Video: Select a video and apply the chosen style.

3. Process the selected input:

• Click on "Process the Styling" to apply the effect.
• View the results directly in the application.

4. Save outputs:

• Output is saved in the same input folder.

License

This project is licensed under the MIT License.

Acknowledgments

• TensorFlow Hub: For providing pre-trained models.
• PyQt: For the UI framework.
• CUDA: For GPU acceleration.