The Smart Vision System is an AI-powered assistive technology designed to help visually impaired individuals perceive their surroundings. The system integrates image processing, object detection, speech recognition, and text-to-speech conversion to provide real-time audio feedback about detected objects and their distances.

• 🖼️ Object Detection: Uses SSD MobileNet to detect and classify objects in the environment.
• 🔢 Distance Calculation: Estimates the distance between detected objects.
• 🎤 Voice Commands: Supports voice input using Speech Recognition.
• 🔊 Audio Feedback: Converts detected objects into speech using pyttsx3.
• 📷 Real-time Processing: Captures and processes live video frames from a camera.

Smart-Vision-System/ │── models/ # Folder for AI models │ ├── ssd_mobilenet.tflite # If using TFLite │ ├── ssd_mobilenet.pb # If using TensorFlow │ │── src/ # Source code files │ ├── main.py # Main entry point │ ├── ai_integration.py # Handles AI model processing │ ├── image_processing.py # Processes images for object detection │ ├── speech_recognition.py # Voice input handling │ │── config/ # Configuration files │ ├── config.json # Stores settings │ │── docs/ # Documentation folder │ ├── README.md # Main project documentation │ │── requirements.txt # Python dependencies │── .gitignore # Ignore unnecessary files │── LICENSE # License file 

Ensure you have Python 3.8+ installed on your system.

git clone https://github.com/your-username/Smart-Vision-System.git cd Smart-Vision-System

pip install -r requirements.txt

python src/main.py

openai opencv-python numpy tensorflow pyttsx3 SpeechRecognition

1. Captures real-time video using OpenCV.
2. Processes frames using SSD MobileNet to detect objects.
3. Recognizes user voice commands for interaction.
4. Converts detected objects into speech output using pyttsx3.

• Python (Programming Language)
• OpenCV (Computer Vision)
• TensorFlow SSD MobileNet (AI Model for Object Detection)
• SpeechRecognition (Voice Input Handling)
• pyttsx3 (Text-to-Speech Conversion)

🤝 Contributing

1. Fork the repository
2. Create a new branch: git checkout -b feature-branch
3. Commit your changes: git commit -m 'Added new feature'
4. Push to the branch: git push origin feature-branch
5. Submit a pull request

📝 License This project is licensed under the MIT License.

📬 Contact 📧 Email: bharani232427@gmail.com
🐙 GitHub: https://github.com/bharani-coder-27 🚀 LinkedIn: www.linkedin.com/in/bharanidharan27