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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:
Demo Video

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