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Docker for $D^2$SLAM

Our Docker image includes:

  • ros-noetic
  • ceres-2.1.0
  • onnxruntime-gpu-1.12.1
  • libtorch-latest
  • LCM
  • faiss
  • OpenCV4 with CUDA
  • OpenGV
  • Backward
  • $D^2$SLAM

Docker PC

To build the Docker image for PC, run the following command:

$ make pc

Docker for Jetson

This Docker file can be built on a MacBook with Apple Silicon (M1 or M2), X86_64 PC with qemu support or on Jetson. However, in our tests, building on Jetson is takes hours and building on Qemu is even more slow.

We highly recommend building the image on a MacBook Pro with M1/M2 Max. This is possibly the fastest way.

To build the Docker image for $D^2$ SLAM, run:

$ make jetson

Build Base Container (Optional)

To build the base image for $D^2$SLAM (which contains the environment for those who would like to modify it), run:

$ make jetson_base

Then, in Dockerfile_jetson_D2SLAM, change:

FROM xuhao1/d2slam:jetson_base_35.1.0

to your own image name:

FROM your-image-name/d2slam:jetson_base_35.1.0

This Docker image has been tested on Jetpack 5.0.2/35.1.0 with Xavier NX.