https://github.com/shaadclt/image-generation-app-dall-e-huggingface-diffusers
This project is a Streamlit-based web app that enables users to generate AI-generated images using text prompts. The app integrates two powerful image generation models: OpenAI's DALL-E and Huggingface's Diffusion models.
https://github.com/shaadclt/image-generation-app-dall-e-huggingface-diffusers
dall-e huggingface-diffusers
Last synced: 6 months ago
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This project is a Streamlit-based web app that enables users to generate AI-generated images using text prompts. The app integrates two powerful image generation models: OpenAI's DALL-E and Huggingface's Diffusion models.
- Host: GitHub
- URL: https://github.com/shaadclt/image-generation-app-dall-e-huggingface-diffusers
- Owner: shaadclt
- License: mit
- Created: 2024-10-22T07:06:15.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2024-10-22T07:15:53.000Z (12 months ago)
- Last Synced: 2025-04-10T01:10:40.328Z (6 months ago)
- Topics: dall-e, huggingface-diffusers
- Language: Python
- Homepage:
- Size: 10.7 KB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
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README
# Image Generation App with DALL-E and Huggingface Diffusers
This project is a Streamlit-based web app that enables users to generate AI-generated images using text prompts. The app integrates two powerful image generation models: OpenAI's DALL-E and Huggingface's Diffusion models.
## Features
- **DALL-E Integration:** Generates images using OpenAI's DALL-E model.
- **Huggingface Diffusers Integration:** Generates images using Huggingface's Stable Diffusion model.
- **Simple UI:** Intuitive user interface to input text prompts and view generated images.
- **CUDA Support:** Utilizes GPU for faster image generation using Huggingface's Diffusers.
## Setup Instructions
1. **Clone the Repository**
```bash
git clone https://github.com/shaadclt/Image-Generation-App-DALL-E-Huggingface-Diffusers.git
cd Image-Generation-App-DALL-E-Huggingface-Diffusers
```
2. **Install Dependencies**
Use the requirements.txt file to install the necessary packages:
```bash
pip install -r requirements.txt
```
3. **Set Up API Keys**
Create a `.env` file in the root directory and add your OpenAI API key:
```bash
OPENAI_API_KEY=your_openai_api_key
```
4. **Run the App**
Run the Streamlit app:
```bash
streamlit run app.py
```
5. **CUDA Setup** (Optional for Diffusers)
Ensure you have the necessary GPU drivers and libraries for running Stable Diffusion with CUDA. This improves image generation performance.
## Usage
1. Select the model you want to use from the sidebar (`DALL-E` or `Huggingface Diffusers`).
2. Input your text prompt in the provided field.
3. Click the "Generate Image" button.
4. View the generated image in the app interface.
## Contributing
Feel free to contribute by opening issues or submitting pull requests.
## License
This project is licensed under the [MIT License](LICENSE.txt).