Host Prerequisites

This guide explains how to prepare an Ubuntu host for a native build and run of this project. If you only want to validate the project, choose the published Docker image in the Docker Workflow README on GH; after installing Docker Engine and the host driver packages, you can skip the native dependency installation and local build steps below.

Supported Environment

Component	Version
Base OS	Ubuntu 24.04
oneAPI	2025.3
Custom OpenVINO	2026.1.0
Intel GPU compute runtime	26.14.37833.4
Intel Graphics Compiler	2.32.7+21184
GMM	22.9.0
Level Zero loader	1.28.2+u24.04
Intel NPU driver	v1.32.1.20260422-24767473183
xpu-smi	v1.3.6
Boost	1.83.0
OpenCL-SDK	v2025.07.23

1. Before You Start

• Use Ubuntu 24.04 x86_64.

• Make sure sudo is available.

• Expect at least one Intel GPU.

• If the driver script upgrades the kernel or installs NPU packages, reboot before continuing.

• Run all commands from the deployment project root unless noted otherwise.

2. Install Driver-Related Packages

bash install_driver_related_libs.sh

The script installs the GPU runtime packages, media stack, monitoring tools, and NPU packages when supported hardware is present.

Useful environment variables:

• SKIP_KERNEL_UPGRADE=1: keep the current kernel.

• SKIP_NPU_DRIVER=1: skip the NPU path.

• SKIP_XPU_SMI=1: skip xpu-smi installation.

• KEEP_BUILD_DIR=1: keep the temporary download directory under $HOME/3rd_build.

After the script completes:

• Reboot if the script asks for it.

• Refresh group membership with newgrp render or log out and back in.

• Use xpu-smi or clinfo to confirm that the GPU is visible.

3. Optional: Validate With The Published Docker Image

If you only need a smoke test of the project, install Docker Engine and Docker Compose by following https://github.com/open-edge-platform/edge-ai-suites/blob/main/metro-ai-suite/sensor-fusion-for-traffic-management/intermediate-fusion/deploy/docker/README_Docker.md, then use the published image:

docker pull intel/tfcc:bevfusion
bash autotest_docker.sh --image intel/tfcc:bevfusion

The published image keeps the intel/tfcc:bevfusion name after pull. If you want the shorter local tag used by some helper defaults, add it yourself:

docker tag intel/tfcc:bevfusion tfcc:bevfusion

To open an interactive shell in the published image:

bash docker/run_docker.sh intel/tfcc:bevfusion

If this container workflow is sufficient, you do not need to continue with the native dependency installation below.

4. Native Host Build: Install Project Dependencies

bash install_project_related_libs.sh

The script installs the build toolchain, runtime libraries, Boost, oneAPI, OpenCL-SDK, and custom OpenVINO under /opt/intel/openvino.

Useful environment variables:

• USE_SYSTEM_BOOST=1: use Ubuntu Boost packages.

• SKIP_ONEAPI=1: skip oneAPI installation when it is already present.

• SKIP_OPENVINO=1: skip the custom OpenVINO installation when it is already present.

• SKIP_OPENCL_SDK=1: skip the OpenCL-SDK build.

5. Source The Runtime Environment

Use the following commands in each new shell:

source /opt/intel/oneapi/setvars.sh
source /opt/intel/openvino/setupvars.sh

6. Build The Project

bash build.sh

The build output is written to build/.

7. Check The Dataset Layout

Expected layout:

<dataset_root>/
  calib/
  image_2/
  label_2/
  velodyne/

Supported input file types:

• image_2: .jpg, .jpeg, .png, or encoded .bin

• velodyne: .bin or .pcd

• calib: .txt

• label_2: .txt

Encoded .bin image files are supported by the loader.

8. Smoke Test The Native Environment

From build/:

./test_bev_pool 1 5
./bevfusion ../data/v2xfusion/dataset

Typical successful output includes:

Using discrete OpenCL GPU (in-order queue): Intel(R) Arc(TM) B580 Graphics
=== BEVPool Latency ===
Avg: 0.693 ms

Detected 0 boxes
[perf] frames=1, avg_lidar=7.463 ms, avg_camera_bev=8.703 ms, avg_fusion+post=3.979 ms, avg_total=12.685 ms

The bundled release models are dummy weights, so Detected 0 boxes is expected in this smoke check. Use your own exported weights if you need meaningful detections.

If the native smoke tests pass, continue with GSG.md and Testing.md.