🤟 Sign Language Detection Web App

A real-time sign language detection web application using YOLOv5, Flask, and JavaScript — deployed on Hugging Face Spaces.

🌟 Features

• Real-time gesture detection via webcam 📷
• Trained YOLOv5 model with 6 ASL gestures:
  • Hello
  • I Love You
  • No
  • Please
  • Thanks
  • Yes
• Text-to-speech output using JavaScript 🗣️
• Clean, responsive frontend with HTML/CSS/JS
• Easy to access from any device 🌐
• Deployed on Hugging Face Spaces 🚀

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🔧 Tech Stack

• Frontend: HTML, CSS, JavaScript
• Backend: Python (Flask)
• Model: YOLOv5 (best.pt)
• Deployment: Hugging Face Spaces

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🧠 Model Architecture

🧠 Sign Language Detection with YOLOv5

A real-time American Sign Language (ASL) recognition web app powered by YOLOv5, webcam integration, and speech synthesis — making communication more accessible and interactive! 🤟✨

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🧠 Model Info

Trained on a custom dataset featuring 6 American Sign Language gestures, this model uses YOLOv5 for fast and accurate gesture detection.
🔁 Processes input frame-by-frame directly from the webcam.

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🔊 Speech Synthesis

The app converts detected sign language gestures into spoken words using the browser's SpeechSynthesis API 🗣️
This creates a smooth, hands-free, and voice-assisted experience — great for accessibility and real-world communication.

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🙌 Acknowledgements

• YOLOv5 by Ultralytics
• Hugging Face Spaces for deployment
• JavaScript Web Speech API for speech synthesis

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📬 Contact

Have questions, ideas, or feedback?
Feel free to reach out — we’d love to hear from you!

• 📧 Email: [[email protected]]
• 💼 LinkedIn: [Shubham Tiwari]

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