Gesture2Text: An Image Processing Approach Using LSTM & CNN Models

This repository contains the code and resources for our project on comparing Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) models for hand gesture recognition and converting them into text.

Installation

To get started with this project, clone the repository and install the necessary dependencies.

git clone "https://github.com/VintellX/Gesture2Text.git"
pip3 install -r requirements.txt

Model Architechture

The project consists of two models:

• CNN Model
• LSTM Model

CNN

The Convolutional Neural Network (CNN) model extracts spatial features from images using multiple convolutional layers, pooling layers, fully connected layers, and an output layer.

LSTM

The Long Short-Term Memory (LSTM) model processes sequences of spatial features extracted from image sequences, capturing temporal dependencies with LSTM layers.

License

This project is licensed under the GNU General Public License v3.0.