✨ Image Captioning Project 🎈

Welcome to the Image Captioning project! Unleash the power of AI to generate captivating captions for your images.

🚀 Overview

Harness the capabilities of Vision Transformer (ViT) and GPT-2 for creating an Image Captioning web application. This Flask-based project allows users to upload images and receive multiple AI-generated captions.

🧠 Models Used

• Vision Transformer (ViT): Processes images and extracts features.
• GPT-2 (Generative Pre-trained Transformer 2): Generates creative and contextually relevant captions.

✨ Features

• Upload images to receive captivating captions.
• Dynamically generate multiple captions for a single image.
• Real-time visualization of uploaded image and generated captions.

🛠 Dependencies

• Flask: A micro web framework for Python.
• Transformers Library: Utilized for integrating ViT and GPT-2 models.
• PIL (Pillow): Python Imaging Library for image processing.
• Matplotlib: Plotting library for creating result images.

🚀 How to Run

1. Clone this repository.
2. Install dependencies using pip install -r requirements.txt.
3. Run the Flask application with python app.py.
4. Open your browser and go to http://localhost:5000.

🌐 Web Interface

• Home Page (index.html): Allows users to upload images and set the number of captions to generate.
• Result Page (result.html): Displays the uploaded image along with multiple AI-generated captions.

🌈 Project Structure

• app.py: Flask application handling image upload and caption generation.
• templates: Folder containing HTML templates for web pages.
• static: Folder for storing static files like images.

🌍 External Services

• nlpconnect/vit-gpt2-image-captioning Model: Pre-trained model for ViT and GPT-2.

👩‍💻 Usage

1. Upload an image on the home page.
2. Set the desired number of captions to generate.
3. Click "Upload" and behold the magic of AI-generated captions!

🤝 Contributing

Contributions are welcome! Feel free to open issues and pull requests.

Happy Developing🎉