This is a web application built using Python, Streamlit, and the Hugging Face Transformers library. It allows users to generate detailed descriptions of paintings based on a provided theme or prompt, and then generate corresponding images using the Stability AI Inference API.
- Painting Description Generation: Users can input a painting theme or prompt, and the app will use a pre-trained language model from the Hugging Face Transformers library to generate a detailed textual description of a painting based on that theme.
- Image Generation: After receiving the painting description, users can choose to generate an image based on the textual description using the Stability AI Inference API.
- Interactive User Interface: The app provides a user-friendly interface powered by Streamlit, where users can input their desired painting theme, view the generated description, and initiate the image generation process.
- Customizable Image Generation Parameters: Users can customize various parameters for the image generation process, such as image dimensions, number of inference steps, and more.
- Image Display: The generated image is displayed on the web page once the generation process is complete.
- Python
- Streamlit (for building the web app)
- Hugging Face Transformers (for text generation)
- Stability AI Inference API (for image generation)
- Clone the repository:
git clone https://github.com/your-repo/painting-app.git - Install the required Python packages:
pip install -r requirements.txt - Set up your Stability AI API credentials in the appropriate configuration file.
- Start the Streamlit app:
streamlit run app.py - The app will open in your default web browser.
Contributions are welcome! If you find any issues or have suggestions for improvements, please open an issue or submit a pull request.
This project is licensed under the MIT License.