Image Caption Django Project

This Django project serves a crucial purpose in the field of computer vision and natural language processing by converting images to captions. It employs an encoder-decoder model with carefully selected checkpoints:

• Encoder Checkpoint: "nlpconnect/vit-gpt2-image-captioning"
• Decoder Checkpoint: "nlpconnect/vit-gpt2-image-captioning"
• Model Checkpoint: "nlpconnect/vit-gpt2-image-captioning"

GitHub Repository

The source code for this project is hosted on GitHub, providing transparency and collaboration opportunities: Image Caption Repository

Installation

Setting up this project locally allows users to harness its capabilities seamlessly:

1. Clone the GitHub repository to your local machine:

   git clone https://github.com/Adarsh-aot/Image_Caption.git

2. Navigate to the project directory:

   cd Image_Caption

3. Install the required dependencies using pip and the provided requirements.txt file:

   pip install -r requirements.txt

Django Setup

Configuring the Django project involves a few essential steps:

1. Apply migrations:

   python manage.py migrate

2. Run the development server:

   python manage.py runserver

3. Access the project in your web browser at http://localhost:8000/.

Usage

This project empowers users to analyze and interpret images effectively:

• Upload images through the web interface.
• The system generates captions for uploaded images utilizing the provided encoder and decoder checkpoints.

Importance

Combining computer vision with natural language processing opens avenues for various applications, including:

• Accessibility tools for visually impaired individuals.
• Content moderation and analysis for social media platforms.
• Enhancing search functionality in image databases.
• Augmenting educational resources with image descriptions.
• Improving user experience in photo-sharing applications.

Note

Proper permissions to access and utilize the provided encoder and decoder checkpoints are crucial for the project's functionality. Adjust paths or configurations as needed within the Django project.

Conclusion

In conclusion, the Image Caption Django Project represents a significant advancement in the intersection of computer vision and natural language processing. By seamlessly converting images into descriptive captions using encoder-decoder models, this project offers a versatile solution with wide-ranging applications. With its robust features and broad impact, the Image Caption Django Project stands poised to make a meaningful contribution to the advancement of technology and its applications in real-world scenarios.