I am trying to use drake c++ on ubuntu 22.04 and I have installed it using nightly build. The installation is completed in opt folder and the example on drake-external-examples run fine.
Drake on ubuntu 22.04 is not supported by drake visualizer and I could not find the link of the visualizer in opt folder. I was struggling to find the equivalent format when installed using apt/tar format with cmake outside the drake source format. I have been able to run meshcat visualizer in drake source examples.
I will appreciate if there is a link to an example utilizing meshcat visualizer with apt/tar installation.
If you were previously using /opt/drake/bin/drake-visualizer, you'll probably be best suited to use Meldis as the next step. Meldis will listen for LCM visualizer traffic just like drake-visualizer used to do.
Here's the command when using apt installed into /opt/drake on Ubuntu 22.04 as of Drake v1.12.0:
env PYTHONPATH=${PYTHONPATH}:/opt/drake/lib/python3.10/site-packages python3 -m pydrake.visualization.meldis -w
Sorry, I know that's a mouthful. We'll work on adding a shortcut and better documentation in a future release.
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I am currently working on a project with ros2 humble that must be run on a raspberryPi, and i am currently in need of using a docker, since i could not find a way of installing ros2 humble native in a raspianOS, my question is, can you instal directly in raspian or do I need to make a new boot for a ubuntu server version in order to run it there.
You can try to install humble from source code, otherwise, install docker and try to run the docker pull command getting an arm architecture if necessary or the standard amd one.
I want to use USBIP in an Ubuntu 20.04 Docker Container. I tried installing the "linux-tools-generic" Package, but when i run USBIP afterwards i get the message:
You may need to install the following packages for this specific kernel:
linux-tools-5.10.16.3-microsoft-standard-WSL2
linux-cloud-tools-5.10.16.3-microsoft-standard-WSL2
You may also want to install one of the following packages to keep up to date:
linux-tools-standard-WSL2
linux-cloud-tools-standard-WSL2
How can i install these Packages ? Could'nt find them with apt-get.
Since Docker relies on the features of the Linux kernel, you'll need to make sure that you have the USB/IP module compiled into your WSL kernel. It is not there in the stock WSL kernel, so you'll need to build your own. I haven't done this with USB/IP myself, but there are reports from the Home Assistant (home automation) forums that indicate that it works.
See this answer for more details.
I'm trying to run the code from this repository: https://github.com/danielgordon10/thor-iqa-cvpr-2018
It has the following requirements
Python 3.5
CUDA 8 or 9
cuDNN
Tensorflow 1.4 or 1.5
Ubuntu 16.04, 18.04
an installation of darknet
My system satisfies neither of these. I don't want to reinstall tf/cuda/cudnn on my machine (especially if have to do that everytime I try to run deep learning code with different tensorflow requirements everytime).
I'm looking for a way to install the requirements and run the code regardless of the host.
To my knowledge that is exactly what Docker is for.
Looking into this there exist docker images from nvidia. For example one called "nvidia/cuda:9.1-cudnn7-runtime". Based on the name I assumed that any image build with this as the base comes with cuda installed. This does not seem to be the case as if I try to install darknet it will fail with the error that "cuda_runtime.h" is missing.
So what my question basicaly boils down to is: How do I keep multiple different versions of cuda and tensorflow on the same machine ? Ideally with docker (or similar) so I won't have to do the process to many times.
It feels like I'm missing and/or don't understand something obvious, because I can't imagine that it can be so hard to run tensorflow code with different versions without reinstalling things from scratch all the time.
I have an outdated neural network training python2.7 script which utilizes keras 2.1 on top of tensorflow 1.4; and I want it to be trained on my nVidia GPU; and I have CUDA SDK 10.2 installed on Linux. I thought Docker Hub is exactly for publishing frozen software packages which just work, but it seems there is no way to find a container with specific software set.
I know docker >=19.3 has native gpu support, and that nvidia-docker utility has cuda-agnostic layer; but the problem is i cannot install both keras-gpu and tensorflow-gpu of required versions, cannot find wheels, and this legacy script does not work with other versions.
Where did you get the idea tha Docker Hub hosts images with all possible library combinations?
If you cannot find an image that suits you, simply build your own.
I am following the beginner rosnode tutorial http://wiki.ros.org/ROS/Tutorials/UnderstandingNodes
The environment is Windows 10 / WSL. When I enter command "rosrun turtlesim turtlesim_node" after running "roscore", I get the following error:
wn-003% rosrun turtlesim turtlesim_node
QXcbConnection: Could not connect to display
zsh: abort (core dumped) rosrun turtlesim turtlesim_node
Are there any solutions to this? Thanks.
WLS doesn't support graphical interfaces. You need to initialize some "x server for windows" application, like Xming and then type this line in WLS terminal:
export DISPLAY=:0
ROS has a great open source ecosystem and support for Linux Operating system. For a beginner, it is better to get hands-on experience directly on a Linux machine as it is easier and you'll get good support for errors you encounter.
ROS does work on windows but it requires Windows Subsystem for Linux (WSL), which is a compatibility layer which allows running a whole bunch of Linux binaries natively on Windows 10. With the advent of the Windows 10 Creators Update, the WSL was heavily updated and now is able to run ROS lunar and melodic.
You will also need to install BASH shell on your windows 10 machine.
Follow this article by Microsoft for installing WSL and BASH : install WSL on windows
Then follow this great article by janbernloehr : https://janbernloehr.de/2017/06/10/ros-windows