README.md

Image Caption Generator

Overview

This project focuses on building an image captioning system using Python. The system processes images and generates descriptive captions, leveraging various libraries and tools to achieve this functionality.

Prerequisites

Before you start, make sure you have the following:

• Python 3.x installed on your system
• The necessary Python libraries, which you can install as outlined below

Installation

To get everything set up, you'll need to install a few libraries. You can do this by running the following commands:

pip install pycocotools

How to Use This Notebook

1. Library Setup:

   • Ensure you have all the required libraries installed using the command above.

2. Running the Notebook:

   • Open Image_Captioning.ipynb in Jupyter Notebook or any compatible environment.
   • Execute the cells one by one to see the code in action and understand how it works.

What's Inside

Here's a quick rundown of what you'll find in the notebook:

1. Library Installation and Imports:

   • Commands to install the required libraries.
   • Import statements for all the libraries used in the notebook.

2. Image Processing:

   • Code to handle image input, including downloading and extracting image datasets.

3. Caption Generation:

   • Steps to process the images and generate descriptive captions using pre-trained models and custom algorithms.

Code Highlights

Here are some snippets of the key parts of the notebook:

Installing Libraries

import os 
import sys
from pycocotools.coco import COCO
import urllib
import zipfile

Setting Up Paths

path=os.getcwd()
path

Example of Image Processing and Caption Generation

# Example code for downloading and processing images
def download_images(url, path):
    # Code to download and extract images
    pass

# Example code for generating captions
def generate_captions(image_path):
    # Code to generate captions for the image
    pass