IN THIS ARTICLE
macOS
Windows XP
Linux
Remote access and virtual machine
Distributed or parallel processing
macOS
For more information: Beta macOS version of PIX4Dmapper 3.0.
Alternatively, PIX4Dmapper can be installed on Windows using Boot Camp. Mac Systems using parallel are not supported, as they use a virtual Operating System which may give problems with the display of the rayCloud and may fail processing.
Note: Boot camp is available only on Intel-based macOS devices. More information here: Boot Camp Assistant User Guide (external link).
Windows XP
PIX4Dmapper is not supported on Windows XP. It may work but it is not guaranteed since Microsoft no longer supports Windows XP. Almost all software and hardware providers stopped taking Windows XP into consideration for their drivers updates.
The recommended Operating System is Windows 10. For more information about the System Requirements: Computer requirements - PIX4Dmapper
Linux
The Linux version is only available with PIX4Dengine. For more information, contact Sales team.
Remote access and virtual machine
We do not test PIX4Dmapper for remote access, and thus we do not officially support it. The processing may be successful, yet most probably, the rayCloud will not display properly due to the OpenGL error. A solution to this problem was described in the Error e0094: It was not possible to initialize OpenGL article.
An alternative is to use the software TeamViewer which permits the visualization of a remote desktop using a different technology. It must be installed both on the remote and the local desktop using the same version. Note that the free license gives errors when used with Windows server 2008 or 2010.
Distributed or parallel processing
PIX4Dmapper cannot distribute processing over multiple computers. However, it is optimized to take advantage of multi-Cores and multi-Processors.
It is possible to:
- Process faster by adjusting the processing options to generate less 3D points: How to change the Processing Options to generate fewer 3D Points .
- Divide the dataset in several sub projects, process the sub projects on different computers and merge them: Processing Large Datasets.
By default, the software will use all the cores and all the RAM available. It is possible to select the number of cores and the amount of RAM to be used for processing: How to modify the resources (cores and RAM) assigned for processing.