2D Avatar Generator using conditional deep convolutional GANs

This project provides an interactive interface to generate images based on user-defined attributes. Users can tweak various parameters using sliders and instantly visualize the output images.

>> Kaggle Notebook link [Implementation with dataset]: https://www.kaggle.com/code/paraglondhe/cdcgans-with-embeddings

Setup and Installation

Prerequisites

• Python 3.8+
• Virtual environment (recommended)

Installation Steps

1. Clone the repository:

   git clone https://github.com/paraglondhe098/2D_Avatar_Generation.git
   cd 2D_Avatar_Generation

2. Install required Python libraries:

   pip install -r requirements.txt

3. Run the Streamlit app:

   streamlit run app.py

Usage

1. Start the application by running the Streamlit app command.
2. Use the sidebar sliders to adjust the attributes for image generation:
   • Example attributes include Eye Angle, Chin Length, Hair Color, and more.
3. Generated images will be displayed in a grid layout.
4. Adjust sliders to modify attributes and generate new images.