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Docker Build for PyCuVSLAM with RealSense Support

Multi-architecture (aarch64/x86_64) Docker setup for PyCuVSLAM with RealSense camera support

Available Docker Images

File Ubuntu CUDA Python librealsense
Dockerfile.realsense-cu12 22.04 12.6 3.10 v2.57.6
Dockerfile.realsense-cu13 24.04 13.0 3.12 v2.57.6

Quick Start

Build

All commands should be run from the repository root (the Dockerfiles build cuVSLAM & PyCuVSLAM from sources).

# Ubuntu 22.04 + CUDA 12
docker build -f docker/Dockerfile.realsense-cu12 -t pycuvslam:realsense-cu12 .

# Ubuntu 24.04 + CUDA 13
docker build -f docker/Dockerfile.realsense-cu13 -t pycuvslam:realsense-cu13 .

Run

# Ubuntu 22.04 + CUDA 12 (default)
./docker/run_docker.sh

# Ubuntu 24.04 + CUDA 13
./docker/run_docker.sh 24

Minimum Driver Versions

Image CUDA Minimum NVIDIA Driver
Dockerfile.realsense-cu12 12.6 >= 560
Dockerfile.realsense-cu13 13.0 >= 580

Check your driver version with nvidia-smi.

Jetson Orin Support

On Jetson Orin devices (aarch64) with CUDA 12, the run script automatically mounts the host's CUDA installation into the container.

The script:

  • Detects Jetson/aarch64 architecture automatically
  • Mounts the host's /usr/local/cuda-12.6 directory read-only
  • Uses CUDA headers from the host for compilation

Note: On Jetson devices with old CUDA (e.g. JetPack 6.0 with CUDA 12.2), you may need to set NVIDIA_DISABLE_REQUIRE=1 when running the container, since the container's CUDA version (12.6) is newer than the host's. Add -e NVIDIA_DISABLE_REQUIRE=1 to your docker run command.

Key Features

Multi-Architecture Support

  • Both Dockerfiles work on x86_64 and aarch64 (Jetson)
  • Docker automatically pulls the correct architecture

RealSense Integration

  • Builds librealsense from source with Python bindings
  • Uses stable release branch (v2.57.6)
  • Includes udev rules for RealSense camera access
  • Sets up proper Python path for pyrealsense2 import

GUI Support

  • Includes all necessary X11 and GUI libraries for rerun-sdk
  • Proper X11 forwarding setup for GUI applications
  • Support for RealSense camera visualization

Automatic Build and Installation

  • Builds cuVSLAM from source during docker build
  • Installs PyCuVSLAM Python bindings into the image
  • Installs all Python dependencies from requirements.txt
  • Ready to run examples immediately after container startup

Dependencies Included

  • Build tools (cmake, make, gcc)
  • Python development headers
  • USB and graphics libraries
  • X11 and GUI libraries for rerun-sdk
  • CUDA development environment

Usage Example

cuVSLAM and PyCuVSLAM are pre-built inside the image.

After starting the container, run stereo tracking with RealSense camera:

python3 examples/realsense/run_stereo.py