System Requirements#

Software Requirements#

  • Ubuntu 24.04 LTS (recommended and validated).

  • Other recent 64-bit Linux distributions may work, but are not fully validated.

  • Python 3.12

  • Docker Engine 24.0 or later recommended

  • Docker Compose v2.x (docker compose command, not docker-compose)

  • Git for cloning the repository

Hardware Requirements#

  • CPU:

    • 8 physical cores (16 threads) or more recommended.

    • x86_64 architecture with support for AVX2.

  • System Memory (RAM):

    • Minimum: 16 GB.

    • Recommended: 32 GB or more for smoother multi-service operation and headroom for the VLM.

  • Storage:

    • Minimum free disk space: 30 GB.

    • Recommended: 60 GB+ to accommodate Docker images, OpenVINO™ models, the VLM weights (Qwen2.5-VL is several GB), and frame storage.

  • Graphics / Accelerators:

    • Required: Intel CPU.

    • Optional (recommended for full experience):

      • Intel integrated or discrete GPU supported by Intel® Graphics Compute Runtime for VLM inference with Qwen2.5-VL-7B-Instruct (GPU-backed recommended)

Required Ports#

The service communicates via MQTT messaging; no external ports are typically required. Port exposure depends on the deployment environment (e.g., container-to-container networking within Docker Compose).

External Services Required#

The following services must be running and accessible for the behavioral-analysis service to operate:

Service

Purpose

Default Address

SeaweedFS

Frame storage (S3-compatible object store)

http://seaweedfs:8333

MQTT Broker

Event messaging (ba/requests / ba/results)

broker.scenescape.intel.com:1883

OpenVINO Model Server (OVMS)

VLM inference (Qwen2.5-VL-7B-Instruct)

http://ovms-vlm:8001

Note: OVMS is only required when VLM_ENABLED=true. VLM is disabled by default, and the service starts and functions for pose-only detection unless it is explicitly enabled.

YOLO-Pose Model#

The service requires a YOLO26n-pose model in OpenVINO IR format (.xml + .bin):

Item

Details

Model format

OpenVINO IR (.xml + .bin)

Expected path

/models/yolo_models/yolo26n-pose/yolo26n-pose.xml (inside container)

Host mount

${DOWNLOADED_MODEL_PATH:-./models}:/models:ro

Inference Device#

Environment Variable

Default

Options

GST_INFERENCE_DEVICE

CPU

CPU, GPU (any device supported by the installed OpenVINO Runtime)

Network Requirements#

  • The container must be able to reach SeaweedFS, the MQTT broker, and OVMS by hostname.

  • In Docker Compose, all services share the ba-network network by default.

  • No inbound internet access is required at runtime.

  • http_proxy, https_proxy, and no_proxy environment variables are forwarded to the container for environments behind a corporate proxy.