Image Captioning Streamlit App

This Streamlit app uses a pre-trained Vision Encoder-Decoder model based on ViT-GPT2 for image captioning. Users can upload an image, and the app will generate a caption for the image.

Installation

1. Clone the repository:

   git clone https://github.com/your-username/your-image-captioning-app.git
   cd image_captioning
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Run the Streamlit app:

   streamlit run app.py
   

4. Open your browser and go to http://localhost:8501 to access the app.

Usage

1. Upload an image using the file uploader.
2. Click the "Generate Caption" button.
3. View the generated caption for the uploaded image.

Dependencies

• torch
• transformers
• streamlit
• Pillow

Credits

• The image captioning model is based on the Hugging Face Transformers library.
• Streamlit is used for building the user interface.

License

This project is licensed under the MIT License - see the LICENSE file for details.