System Requirements#

This page provides detailed hardware and software requirements to help set up and run the application efficiently.

Hardware Requirements#

Component

Minimum

Recommended

Processor

11th Gen Intel® Core™ Processor

Intel® Core™ Ultra 7 Processor 155H

Memory

8 GB

8 GB

Disk Space

256 GB SSD

256 GB SSD

GPU/Accelerator

Intel® UHD Graphics

Intel® Arc™ Graphics

Software Requirements#

  • OS: Ubuntu 24.04.1 LTS (native installation, or as a WSL 2 distribution on Windows).

  • Docker Engine version 20.10 or higher. Docker Desktop is not supported on Linux, because its virtual machine cannot access the host /dev/dri render nodes required for GPU acceleration.

  • For GPU and/or NPU usage, appropriate drivers must be installed. The recommended method is to use the DL Streamer installation script, which detects available devices and installs the required drivers. Follow the Prerequisites section in DL Streamer Install Guide - Ubuntu.

Network Requirements#

An outbound internet connection is required. ViPPET is not supported in air-gapped or fully offline environments: container images, sample videos, models, and Python packages are all fetched on demand and are not bundled with the tool.

When

What is downloaded

From

Installation

Docker Engine, GPU/NPU drivers, git, make, curl

Ubuntu and Docker apt repositories

Installation

ViPPET repository sources

github.com

First make run

Pre-built container images

docker.io (Docker Hub)

First start

model-download plugin virtual environments (Python packages)

pypi.org, files.pythonhosted.org

First start

Default sample recordings listed in shared/videos/default_recordings.yaml

storage.openvinotoolkit.org, github.com, pexels.com

Model installation

Model weights and metadata for the selected hub

huggingface.co, ultralytics.com, storage.openvinotoolkit.org, Intel® Geti™

Build from source

Base images, apt packages, Python and npm dependencies

docker.io, distribution and language package registries

UI and API docs in use

Web fonts and the Swagger UI bundle

fonts.googleapis.com, cdn.jsdelivr.net

Note

  • Downloaded artifacts are cached under shared/, so subsequent starts need far less bandwidth. A connection is still needed whenever a new model or sample video is installed, or after make clean.

  • The first start can take several minutes and download several GB, depending on the selected models.

  • Behind a corporate proxy, export http_proxy, https_proxy, and no_proxy in the shell before running make run, and configure the Docker daemon proxy so that image pulls succeed. compose.yml already appends the internal service names to no_proxy.

  • Access to the Hugging Face Hub additionally requires a token for gated or private repositories. See Pre-Installation Steps.

  • Inbound access is not required. The UI is served on port 80 and is reachable at http://localhost or http://<HOST-IP> on the local network.

Windows Subsystem for Linux (WSL)#

Ubuntu 24.04 running under WSL 2 on Windows is supported. The installation steps are identical to a native Ubuntu installation - run all commands (Use Pre-Built Docker Images or Build from Source) inside the Ubuntu 24.04 WSL distribution.

setup_env.sh detects /dev/dxg and selects the gpu-wsl Compose profile automatically, so no manual configuration is required.

Supported pipeline variants under WSL#

Variant

Supported under WSL

CPU

Yes

GPU (WSL)

Yes

GPU (native)

No

NPU

No

Pipelines expose a dedicated GPU (WSL) variant that is shown only when the application runs under WSL. Native GPU and NPU variants are hidden in that environment.