{"id":24247385,"url":"https://github.com/daaanishhh002/signwave","last_synced_at":"2025-03-04T16:16:56.299Z","repository":{"id":271252894,"uuid":"910149773","full_name":"daaanishhh002/SignWave","owner":"daaanishhh002","description":"This repository contains code for a real-time hand gesture recognition system using flex sensors and an IMU6050 sensor in gloves. It translates sign language gestures into text and converts them to speech. 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The system translates gestures into **text** and converts them to **speech** for better accessibility. 🎙️💬\n\n---\n\n## 📌 Features  \n✔️ **Real-time gesture recognition** using sensor-based gloves  \n✔️ **Sign language to text** conversion 📝  \n✔️ **Text-to-speech (TTS) integration** 🔊  \n✔️ **Machine Learning for accurate classification** 🤖  \n✔️ **Potential NLP and online learning enhancements**  \n✔️ **Cloud deployment on AWS EC2 (planned)** ☁️  \n\n---\n\n## 🛠️ Hardware Used  \n\nThe following components are used to build the **gesture recognition glove**:  \n\n| 🔧 Component  | 🏷️ Description |\n|--------------|-------------|\n| 🧤 **Glove**  | Base for mounting sensors |\n| 🏗️ **Flex Sensors** | Detects finger bending |\n| 🎯 **IMU6050 (Accelerometer + Gyroscope)** | Tracks hand motion and orientation |\n| 🔌 **ESP32** | Microcontroller for processing signals |\n| 📱 **Smart Phone** | Converts text to speech |\n| 🌐 **AWS EC2 (Future)** | Cloud-based processing |\n\n---\n\n## 🖥️ Software \u0026 Libraries  \n\n📌 **Programming Languages:**  \n- Python 🐍  \n- C++ (for microcontroller programming)  \n\n📌 **Libraries \u0026 Dependencies:**  \n- `numpy` ➜ Data processing  \n- `scikit-learn` ➜ Machine Learning model  \n- `TensorFlow / PyTorch` ➜ (Future deep learning integration)  \n- `speechRecognition` ➜ Text-to-Speech conversion  \n- `Flask` ➜ Websocket-based data transfer  \n- `AWS SDK` ➜ Cloud deployment  \n\n---\n\n## 🚀 How It Works  \n\n1️⃣ **Sensors detect gestures:**  \n   - **Flex sensors** measure finger bending angles  \n   - **IMU6050** tracks hand movements  \n\n2️⃣ **Data Processing:**  \n   - Sensor data is sent to a **microcontroller**  \n   - Features are extracted and sent to a **gesture classification model**  \n\n3️⃣ **Classification:**  \n   - Machine Learning model **predicts the gesture**  \n   - Text output is generated  \n\n4️⃣ **Speech Conversion:**  \n   - The text is passed through a **Text-to-Speech (TTS) engine**  \n   - The recognized word/sentence is **spoken aloud** 🔊  \n\n---\n\n## 🛠️ Installation \u0026 Setup  \n\n1️⃣ **Clone the Repository**  \n```bash\ngit clone https://github.com/daaanishhh002/SignWave.git\ncd SignWave\n```\n\n2️⃣ **Install Dependencies**\n```bash\npip install -r requirements.txt\n```\n\n### 🌍 Future Enhancements\n✨ Deep Learning Model for improved accuracy  \n✨ Real-time Streaming for live sign language translation  \n✨ NLP-based contextual learning  \n✨ AWS Cloud Integration for remote accessibility  \n\n### 📜 License\nThis project is open-source under the MIT License. Feel free to modify and contribute! 🎉\n\n### 📞 Contact\n💡 Authors: Danish Ahmed, Syed Zeeshan, Syed Mubeen Ali, Shaik Abdul Sami  \n📧 Email: ahmed.daanish002@gmail.com  \n🐙 GitHub: daaanishhh002  \n\n\n\u003cp align=\"center\"\u003e\n  🌟 If you like this project, give it a star ⭐ on GitHub!\n\u003c/p\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdaaanishhh002%2Fsignwave","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdaaanishhh002%2Fsignwave","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdaaanishhh002%2Fsignwave/lists"}