US
usmanyousaaf/sketch-to-image
This project leverages Generative Adversarial Networks (GANs) to convert hand-drawn sketches into realistic images. By training a GAN on a dataset of paired sketches and images, the model learns to generate detailed and accurate images from simple line drawings.
Sketch-to-Image Conversion using GAN
Overview
This project leverages Generative Adversarial Networks (GANs) to convert hand-drawn sketches into realistic images. By training a GAN on a dataset of paired sketches and images, the model learns to generate detailed and accurate images from simple line drawings.
Features
- Sketch-to-Image Conversion: Converts hand-drawn sketches into photorealistic images.
- Deep Learning: Utilizes GANs to perform the conversion, ensuring high-quality results.
- Customizable: Easily adaptable to different types of sketches and image styles.
- User-Friendly Interface: Simple and intuitive interface for users to upload sketches and get generated images.
How It Works
- Data Collection: Gather a dataset of paired sketches and corresponding images.
- Preprocessing: Prepare the dataset by normalizing images and converting sketches to a suitable format.
- Training the GAN: Train the GAN model on the dataset, optimizing it to generate realistic images from sketches.
- Image Generation: Use the trained model to convert new sketches into images.
Installation
- Clone the repository:
git clone https://github.com/yourusername/sketch-to-image.git
Results
- Include some example results showcasing the sketch-to-image conversion.
Contributing
- Contributions are welcome! Please fork the repository and create a pull request with your changes.
License
- This project is licensed under the MIT License. See the LICENSE file for details.
Acknowledgements
- Special thanks to the creators of the datasets and libraries used in this project.
- Inspired by various research papers and projects in the field of GANs and image generation.