This project provides a web application that captures media streams from various sources such as a webcam, desktop, or specific applications. It captures frames at intervals and uses AI to analyze and summarize the frames, providing insights using GPT-4.

• https://huggingface.co/spaces/ruv/ai-video

• Media Stream Capture: Capture video streams from a webcam, screen, or specific applications.
• Frame Analysis: Use OpenAI's GPT-4 to analyze captured frames for text, objects, context, and other details.
• Customizable Prompts: Customize the prompt used for frame analysis.
• API Integration: Integrate with OpenAI's API for frame analysis.

• app.py: The main server-side application code using Quart.
• templates/index.html: The HTML template for the web application.
• static/script.js: The client-side JavaScript for handling media streams and interaction with the backend.

• GET /: Serves the main web application.
• POST /process_frame: Processes a captured frame and returns the analysis result.

• Request Body:

  {
      "image": "data:image/jpeg;base64,<base64-encoded-image>",
      "prompt": "Analyze this frame",
      "api_key": "<OpenAI API Key>"
  }

• Response:

  {
      "response": "<Analysis result in markdown format>"
  }

• Remote Monitoring: Capture and analyze video streams for remote monitoring applications.
• Educational Purposes: Use AI to analyze and summarize educational video content.
• Content Creation: Automate the analysis and summarization of video content for creators.

• Prompts: Customize the analysis prompt via the settings panel in the web application.
• Refresh Rate: Adjust the frame capture interval through the settings panel.
• API Key: Configure the OpenAI API key via the settings panel.

1. Clone the Repository:

   git clone https://github.com/ruvnet/ai-video.git
   cd ai-video

2. Install Dependencies:

   pip install -r requirements.txt

3. Set Environment Variables:

   export OPENAI_API_KEY=<your_openai_api_key>

4. Run the Application:

   python app.py

5. Access the Application: Open your web browser and navigate to http://localhost:5000.

quart
opencv-python-headless
httpx
numpy

Feel free to fork the repository and submit pull requests. For major changes, please open an issue first to discuss what you would like to change.

MIT