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Demo

For a demonstration of the project, click here

Application Setup and Execution

Steps to Run the Application

  1. Download the Dataset

    • Obtain the Flickr8k dataset and store the images in a folder named Flicker8k_Dataset within the project directory.
    • Each image should have the path structure: Flicker8k_Dataset/<image_name>.jpg.

  2. Generate Output and Checkpoints

    • Open and execute each cell in the provided .ipynb notebook. This step allows you to view the output generated at each stage and to create checkpoints during model training.
    • The application will automatically save the 5 most recent checkpoints in a newly created checkpoints directory.
    • Note: If you only wish to run the application without additional training, pre-generated captions are stored in data.json.

  3. Run the Server

    • Start the application by running server.py, which contains the backend code.

Application Functionality

Upon uploading images, the application generates captions and saves them along with the image name as a JSON object. Uploaded images are also stored in a gallery folder for future reference.