Vision Hub – Research Demo Platform

This project lets you deploy and visualize research demos in Docker containers, with a modern web interface.

Prerequisites

• Docker & Docker Compose
• webcam (V4L2-compatible is a bonus)
• NVIDIA GPU + drivers + nvidia-docker for CUDA acceleration (optional, but recommended for best performance)

Quick Start

1. Clone the repo and go to the vision-hub directory.
2. Copy .env.example to .env and adjust variables as needed.
3. Launch the stack:

   docker compose up --build

4. Access the interfaces:
   • Astro frontend: http://localhost:4321
   • Web API: http://localhost:8080
   • RTSP: rtsp://localhost:8554/cam

Main Environment Variables

See .env.example for the full list. Key variables:

• CAMERA_DEVICE: Path to the local camera (e.g. /dev/video0 or /dev/v4l/by-id/...)
• RTSP_URL: RTSP stream URL to use (default: rtsp://mediamtx:8554/cam)
• MODEL: YOLO model to use (e.g. yolov8n.pt)
• IMG_SIZE: Input resolution for inference (e.g. 640)
• JPEG_QUALITY: JPEG quality for MJPEG stream (e.g. 80)
• FORCE_CPU: Set to 1 to force CPU usage even if a GPU is available
• CONF, IOU, MAX_DET: Detection thresholds

Usage Notes

• Besides global variables, there's always default ones, these are they I use on my own computer
• For GPU acceleration, ensure Docker is configured with the correct runtime (--gpus all or devices: - nvidia.com/gpu=all).
• Startup logs will indicate whether GPU or CPU is used.

Custom Demos

Add your own models or demos by creating a dedicated folder and adapting the Dockerfile + app.py.

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For questions or contributions, ask me directly at tom.burellier@associated.ltu.se