Nepali Sign Language Detection Using CNN

This repository contains a project for detecting Nepali Sign Language using Convolutional Neural Networks (CNN). The project aims to facilitate communication for the deaf and hard-of-hearing community by translating Nepali sign language into text.

Features

• Sign Language Detection: Recognizes various Nepali sign language gestures.
• Deep Learning Model: Utilizes CNN for accurate detection and classification.
• User-Friendly Interface: Easy-to-use interface for users to interact with the system.

Getting Started

Prerequisites

• Python 3.x
• TensorFlow
• Keras
• OpenCV

Installation

1. Clone the repository:

   git clone https://github.com/krispyarena/nepali-sign-language-detection-using-CNN.git
   cd nepali-sign-language-detection-using-CNN

2. Install the required packages:

   pip install -r requirements.txt

Usage

1. Train the model:

   python train_model.py

2. Run the application:

   python app.py

Data

• The dataset used for training and testing is included in the data folder.
• Ensure the data is preprocessed correctly before training.

Technologies Used

• Python
• TensorFlow
• Keras
• OpenCV

Tools Used

• Jupyter Notebook
• Visual Studio Code
• Github

Extra Resources

• Link to Presentation : Project Presentation
• Link to Report : Project Report

Contributing

Contributions are welcome! Please fork the repository and submit pull requests for any enhancements or bug fixes.

License

This project is licensed under the MIT License.