VisionVault

VisionVault is an innovative project that transforms the way we capture and document moments. By integrating an ESP32-CAM mounted on goggles, this system allows users to stream a live video feed and capture images effortlessly with a keystroke. The captured images are processed through the Gemmini Vision API to generate detailed descriptions, creating a virtual memory bank.

Features

• Live Video Feed: Stream visuals from an ESP32-CAM in real-time.
• Instant Image Capture: Press "c" to save an image from the feed.
• Image Description: Generate meaningful descriptions via the Gemmini Vision API.
• Hands-Free Operation: Capture moments without using a phone or camera.

Demo Video

Check out the demo video to see VisionVault in action:

Click the image above or this link to watch the demo video.

Applications

• Personal memory archival
• Remote surveillance
• Assistive technology for visually impaired individuals

How It Works

1. Hardware Setup: Mount the ESP32-CAM on goggles or a suitable frame and connect it to a network.
2. Live Feed Streaming: A Python script streams the live feed from the ESP32-CAM.
3. Image Capture: Press "c" to capture an image from the live feed.
4. Description Generation: The captured image is sent to the Gemmini Vision API, which returns a detailed description.

Prerequisites

• Hardware:

  • ESP32-CAM module
  • Goggles or a mountable frame

• Software:

  • Arduino IDE (for ESP32-CAM setup)
  • Python 3.7+
  • Required libraries:
    • opencv-python
    • requests
    • flask

• API: Access to the Gemmini Vision API

Installation

1. Clone the repository:

   git clone https://github.com/your-username/VisionVault.git
   cd VisionVault

2. Install dependencies:

   pip install -r requirements.txt

3. Add your Gemmini Vision API key to the .env file:

   GENAI_API_KEY="your-gemmini-api-key"

Usage

1. Run the Python script:

   python file_name.py

2. View the live feed on the displayed window.
3. Press "c" to capture an image and generate its description.

Future Enhancements

• Voice Commands: Integrate speech-to-text functionality for hands-free control.
• Mobile App: Develop a companion app for easier accessibility.
• API Expansion: Support additional APIs for varied use cases.

Contributing

Contributions are welcome! Here's how you can contribute:

1. Fork the repository
2. Create a feature branch:

   git checkout -b feature-name

3. Commit your changes:

   git commit -m "Description of feature"

4. Push to the branch:

   git push origin feature-name

5. Submit a pull request

Acknowledgments

• The Gemmini Vision API for image description generation
• The OpenCV community for their robust computer vision tools
• The Python community for supporting open-source projects