├── .github └── FUNDING.yml ├── LICENSE ├── README.md ├── RealTimeSignLanguageDetection.ipynb ├── Train.ipynb ├── model.h5 └── model_weights.h5 /.github/FUNDING.yml: -------------------------------------------------------------------------------- 1 | # These are supported funding model platforms 2 | 3 | github: [avishakeadhikary] # Replace with up to 4 GitHub Sponsors-enabled usernames e.g., [user1, user2] 4 | patreon: avishakeadhikary # Replace with a single Patreon username 5 | open_collective: # Replace with a single Open Collective username 6 | ko_fi: avishakeadhikary # Replace with a single Ko-fi username 7 | tidelift: # Replace with a single Tidelift platform-name/package-name e.g., npm/babel 8 | community_bridge: # Replace with a single Community Bridge project-name e.g., cloud-foundry 9 | liberapay: # Replace with a single Liberapay username 10 | issuehunt: # Replace with a single IssueHunt username 11 | lfx_crowdfunding: # Replace with a single LFX Crowdfunding project-name e.g., cloud-foundry 12 | polar: # Replace with a single Polar username 13 | buy_me_a_coffee: avishake69 # Replace with a single Buy Me a Coffee username 14 | custom: # Replace with up to 4 custom sponsorship URLs e.g., ['link1', 'link2'] 15 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2023 Avhishek Adhikary 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Realtime Sign Language Detection Using LSTM Model 2 | 3 | ![Mediapipe Detection](https://github.com/AvhishekAdhikary/Realtime-Sign-Language-Detection-Using-LSTM-Model/assets/32614982/4d6a7542-2409-424f-9c9f-6b90a3236ea6) 4 | 5 | 6 | > The Realtime Sign Language Detection Using LSTM Model is a deep learning-based project that aims to recognize and interpret sign language gestures in real-time. It utilizes a Long Short-Term Memory (LSTM) neural network architecture to learn and classify sign language gestures captured from a video feed. The project provides a user-friendly interface where users can perform sign language gestures in front of a camera, and the system will instantly detect and interpret the gestures. This can be used as an assistive technology for individuals with hearing impairments to communicate effectively. Key features of the project include real-time gesture detection, high accuracy in recognition, and the ability to add and train new sign language gestures. The system is built using Python, TensorFlow, OpenCV, and Numpy, making it accessible and easy to customize. With the Realtime Sign Language Detection Using LSTM Model, we aim to bridge the communication gap and empower individuals with hearing impairments 7 | 8 | 9 | ## Table of Contents 10 | 11 | - [About the Project](#about-the-project) 12 | - [Demo](#demo) 13 | - [Features](#features) 14 | - [Getting Started](#getting-started) 15 | - [Usage](#usage) 16 | - [Contributing](#contributing) 17 | - [License](#license) 18 | - [Contact](#contact) 19 | 20 | ## About the Project 21 | 22 | This section provides an overview of the Realtime Sign Language Detection Using LSTM Model project. It describes the project's purpose, which is to develop a system that can accurately detect and interpret sign language gestures in real time. It also highlights the use of LSTM (Long Short-Term Memory) models for this task and emphasizes the project's significance in improving communication accessibility for the deaf and hard of hearing community. 23 | 24 | ## Demo 25 | 26 | This section showcases a demonstration of the Realtime Sign Language Detection Using LSTM Model project. 27 | 28 | 29 | https://github.com/AvhishekAdhikary/Realtime-Sign-Language-Detection-Using-LSTM-Model/assets/32614982/16bd1d47-cc3f-488c-8d0e-e400004dc716 30 | 31 | 32 | The demo allows viewers to see how the system accurately interprets sign language gestures and provides real-time results. 33 | 34 | ## Features 35 | 36 | ![model h5](https://github.com/AvhishekAdhikary/Realtime-Sign-Language-Detection-Using-LSTM-Model/assets/32614982/ece8ef5e-295c-4cfd-beb5-255ea88c8b76) 37 | 38 | 39 | - Real-time sign language detection: The system can detect and interpret sign language gestures in real time, providing immediate results. 40 | - High accuracy: The LSTM (Long Short-Term Memory) model used in the project ensures accurate recognition of a wide range of sign language gestures. 41 | - Multi-gesture support: The system can recognize and interpret various sign language gestures, allowing for effective communication. 42 | - Easy integration: The project provides code snippets and examples for seamless integration into other applications or projects. 43 | - Accessibility improvement: The Realtime Sign Language Detection Using LSTM Model project contributes to enhancing communication accessibility for the deaf and hard of hearing community. 44 | - Customization options: The system supports customization of gestures, allowing users to adapt it to their specific needs. 45 | - Language flexibility: The model can be trained to recognize sign language gestures from different languages, making it adaptable to various communication contexts. 46 | - User-friendly interface: The project includes a user-friendly interface that simplifies the interaction with the system, ensuring a smooth user experience. 47 | - Open-source: The Realtime Sign Language Detection Using LSTM Model is an open-source project, encouraging contributions and fostering collaboration in the development community. 48 | 49 | ![Neural Network](https://github.com/AvhishekAdhikary/Realtime-Sign-Language-Detection-Using-LSTM-Model/assets/32614982/2adabb2c-db8e-47a3-a7ae-f2ce7175cc82) 50 | 51 | 52 | ## Getting Started 53 | 54 | To get started with the Realtime Sign Language Detection Using LSTM Model, follow these steps: 55 | 56 | ### Prerequisites 57 | 58 | - Python 59 | - TensorFlow 60 | - OpenCV 61 | - Numpy 62 | 63 | ### Installation 64 | 65 | 1. Clone the repository: 66 | 67 | ```shell 68 | git clone https://github.com/AvhishekAdhikary/Realtime-Sign-Language-Detection-Using-LSTM-Model.git 69 | ``` 70 | 2. Install Dependencies: 71 | 72 | ```shell 73 | pip install notebook 74 | ``` 75 | 3. Run Jupyter Notebook: 76 | 77 | ```shell 78 | jupyter notebook 79 | ``` 80 | 81 | ## Usage 82 | 83 | Simply run all the cells inside the 'RealTimeSignLanguageDetection.ipynb' file. 84 | 85 | ## Contributing 86 | 87 | Contributions are welcome! If you have any ideas, suggestions, or bug fixes, please open an issue or submit a pull request. 88 | 89 | ## License 90 | 91 | This section states that the Realtime Sign Language Detection Using LSTM Model project is released under the MIT License. It briefly describes the terms and conditions of the license, such as the permission to use, modify, and distribute the project, with appropriate attribution. It provides a link to the full text of the MIT License for further reference. 92 | 93 | ## Contact 94 | 95 | For any questions or inquiries, feel free to contact me at avhishe.adhikary11@gmail.com. 96 | -------------------------------------------------------------------------------- /model.h5: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AvishakeAdhikary/Realtime-Sign-Language-Detection-Using-LSTM-Model/83281372c5c53519991054139fefbada3336beab/model.h5 -------------------------------------------------------------------------------- /model_weights.h5: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AvishakeAdhikary/Realtime-Sign-Language-Detection-Using-LSTM-Model/83281372c5c53519991054139fefbada3336beab/model_weights.h5 --------------------------------------------------------------------------------