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Image Captioning with TensorFlow

This project demonstrates how to build an image captioning model using TensorFlow. The model combines a pre-trained Convolutional Neural Network (CNN) for image feature extraction and a Long Short-Term Memory (LSTM) network for generating captions.

Table of Contents

Introduction

Image captioning is the task of generating a descriptive sentence for a given image. This project uses a CNN to extract features from an image and an LSTM to generate a corresponding caption.

Requirements

  • Python 3.6 or higher
  • TensorFlow 2.x
  • NumPy
  • Pillow (PIL)

Installation

  1. Clone this repository:

    https://github.com/IcodeG00D/Image-Captioning-Using-CNN-and-LSTM.git

  2. Install the required packages:

    pip install tensorflow numpy pillow

Usage

  1. Place your image in the images folder.
  2. Update the image_path and caption in the script as needed.
  3. Run the script to train the model and generate captions.