Develop Docker Image for Camera Integration with Florence-2 Model

Create a Docker image that directly interacts with a camera to capture and process live data. Under the hood, the Florence-2 model will operate to analyze the data and communicate the current pressure to our chat application.

The key requirements are:

Camera Integration: Ensure seamless interaction between the Docker container and the camera hardware.
Florence-2 Model Implementation: Integrate and deploy the Florence-2 model within the container to process the captured data.
Data Communication: Establish a mechanism for the model to send the current pressure values to our chat system in real-time.

The issue requires integrating a camera with a Docker container, deploying the Florence-2 model for real-time analysis, and setting up communication to a chat system. Start by examining the existing codebase for AI model integration and any camera handling modules. Look for existing Dockerfiles or CI/CD configurations to understand the deployment setup. Determine how the chat system receives data, possibly through an API or message queue.

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