- #Alternatives to xquartz for mac install#
- #Alternatives to xquartz for mac driver#
- #Alternatives to xquartz for mac code#
#Alternatives to xquartz for mac install#
This will install a macOS-compatible X Server and a variety of tools and libraries (such as xeyes, OpenGL 1.4, and the glxgears test app). Setup up the MacĪssumming a macOS Catalina (10.15.4) and brew, install XQuartz using brew cask install xquartz. ORB-SLAM2’s visualization module is happy with OpenGL 1.4 from 2002, so it’s still worth a try. But surprisingly, at least for research purposes, libraries often do not require the late versions of OpenGL - e. However, Apple does not support newer versions of OpenGL anymore and has instead promoted its own Metal 3D graphics library. ORB-SLAM2 and ROS2 RViz2 depend on the OpenGL API for 3D rendering which is is run in Mac land and not in container land.
#Alternatives to xquartz for mac code#
This, of course, defeats the idea of containerizing the code in the first place and defining all dependencies through software.
#Alternatives to xquartz for mac driver#
Communication between the code running inside the container and the GUI is done using X in the omnipresent version from 2012, X11.Īpart from latency issues, the main problem of the alternative described in this post, is that the GPU driver software must be correctly installed on macOS and it must be compatible with the code running inside the container. In the context of this post, the main idea is to run the actual SLAM algorithms with all their dependencies in a container and only run the visualization outside of it. The X Window System follows a client-server approach where the X Server is connected to the user I/O devices (screen, keyboard, mouse) and an X client can communicate to the X Server through the X protocol, either on the same host or over the network. using a GPU-accelerated VM at AWS) and simply tether the rendering results to the developer machine using VNC.Īn alternative to VNC is to render the hardware-accelerated GUI on the developer machine’s GPU using the X Window System. Analogously, it might be interesting to compute the SLAM visualizations in real-time on a remote GPU (e. The solution for CUDA-based ML is to simply not use the Mac and instead do it on remote Linuxes (see my post on remote docker hosts for ML. Not only does the GPU cause overheating if you do crazy things such as connecting a second display, and, hence, heat-throttling, but also developing against it is also very not fun. Of course, anything that involves GPUs on macOS is a nightmare. for visualization, things get a bit more complicated. However, once the software also comprises graphical UIs, e. Of course, Docker makes it easy to run libraries for Linux. Since VSLAM libraries are designated for running efficiently on embedded systems, they are generally programmed in C/C++ and designed with just Linux in mind (even though, for example, in version 2, ROS also aims for compatibility with MacOS).Īs a MacBook user, this becomes “interesting”. For my latest research, I am looking into visual SLAM (e.
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