This repository contains Dockerfiles for the Open3D and will be updated regularly with updated versions to include various other libraries required to carry out 3D-perception.
Currently, the repo has two Dockerfiles under the docker folder and both of them are tested with a base example is testfor an x86_64:
System | Version |
---|---|
Ubuntu | 20.04 |
Docker | 20.10.14 |
with :
System | Version |
---|---|
pip | 20.3 |
Python | 3.8 |
Open3D | 0.15.2 |
System Prerequisites:
- Docker
The PyPI has open3d with version no. 0.15.2 instead of 0.15.1 . I believe it is just a new commit fully resolved with any issues from 0.15.1
- Has PyTorch cuda Ops built for Open3D
- Open3D built from source
System | Version |
---|---|
CUDA | 11.6 |
Open3D | 0.15.1 |
pip | 20.3 |
Python | 3.8 |
Pytorch | 1.13 |
System Prerequisites:
- Docker
- >=22 GB storage memory
- Nvidia Drivers>=515
- Nvidia runtime container toolkit installed on host
Clone this repository:
~$ git clone https://github.com/raghavduddala/3d-perception-dockerfiles.git
~$ cd 3d-obstacle-detection/
Edit the Makefile
with the correct DOCKERFILE
for the required docker image you want to built.
for example for building the Open3D-PyTorch container, in Makefile
line 4
DOCKERFILE := Dockerfile.pt3d
and use the Makefile
commands to building, launching and extending terminals to the containers
In the first terminal, to build and launch the Open3D Docker Container
~$ make build
~$ make dev
or the command below to launch the cuda-related containers.
make cuda-dev
In the Second terminal, to attach a terminal to the container
~$ make shell
After the docker container is launched, run the basic test file from Open3D tutorials here to check if the installation and build is fine.
~$ cd src/
~$ python3 test_open3d.py
A sample .ply file containing a Point cloud from Open 3D is downloaded and visualized in the following way.
My Repos using this include https://github.com/raghavduddala/point_clouds_open3d.git
where the repo we want to run can be cloned under the src
directory of this docker workspace
folder.
Please support by giving a star if you find this repo helpful for building the current containers with the dockerfiles or in building your custom docker images