Image Caption Generator

This project implements an image caption generator using a combination of LSTM for text generation and VGG16 for image feature extraction. The model is trained on the Flickr 8k dataset.

Model Architecture

1. Image Feature Extraction: VGG16 pre-trained on ImageNet
2. Text Generation: Long Short-Term Memory (LSTM) network

Dataset

The model is trained on the Flickr 8k dataset, which contains:

• 8,000 images
• 5 captions per image

Requirements

• Python 3.7+
• TensorFlow 2.0
• Keras
• NumPy
• Matplotlib

Usage

1. Clone the repository: git clone https://github.com/Roronoa-17/Image_Caption_Generator.git

2. Install the required packages: pip install -r requirements.txt

3. Run the caption generator: streamlit run app.py

Training

1. Download the Flickr 8k dataset
2. Open the python notebook for further instructions.