SignSense Detection System Welcome to the SignSense Detection System repository! This project is focused on detecting and interpreting sign language actions using advanced machine learning techniques and computer vision.
Table of Contents:
- Overview
- Features
- Installation
- Usage
- Model Training
- License
Overview SignSense Detection System is designed to bridge the communication gap for the hearing-impaired community by recognizing sign language gestures in real-time. The system utilizes Long Short-Term Memory (LSTM) networks for training and OpenCV for video capture and processing.
Features
- Real-time Gesture Recognition: Detects and interprets sign language gestures from live video feed.
- LSTM Model: Uses a robust LSTM model to handle the sequential nature of sign language.
- OpenCV Integration: Leverages OpenCV for efficient video capture and preprocessing.
- User-Friendly Interface: Simple to use with clear instructions and an intuitive interface.
Installation To set up the SignSense Detection System, follow these steps:
-
Clone the repository: git clone https://github.com/your-username/SignSense-Detection-System.git cd SignSense-Detection-System
-
Install dependencies and other files for importation purposes:
- !pip install tensorflow opencv-python mediapipe sklearn matplotlib = for jupyter notebook
- %pip install tensorflow opencv-python mediapipe sklearn matplotlib = for VScode
- Ensure you have OpenCV installed: pip install opencv-python
- Download pre-trained model (if available): LSTM Model
- import cv2
- import numpy as np
- import os.
- from matplotlib import pyplot as plt
- import time
- import mediapipe as mp(for vscode you have to downl;oad it)
Usage Run the application: python main.py
Instructions:
- Ensure your webcam is connected and properly configured.
- The system will start capturing video and recognizing gestures in real-time.
- Detected gestures will be displayed on the screen.
- Model Training To train your own LSTM model, follow these steps:
- Prepare your dataset: Organize your sign language gesture videos into appropriate training and testing directories.
License This project is licensed under the MIT License. See the LICENSE file for details.
Follow and Star If you find this project useful, please consider following me and starring the repository on GitHub. Your support is greatly appreciated!
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Thank you for using SignSense Detection System! Let's make sign language recognition more accessible and effective together