For anyone using OpenDroneMap to process really large datasets, some good news came through early last year with improvements to how OpenSfM handles large datasets. This came in the form of an innovative, first of it’s kind, hybrid SfM method which combines the better attributes of global and incremental SfM approaches.
TLDR: This helps make processing large datasets orders of magnitude faster, and can be tuned to be even faster (at some accuracy expense), which is really exciting and wonderful work by the folks (especially Pau) over at Mapillary.
But this change was not enough for OpenDroneMap. After the SfM step, we have several more processing steps, all challenges with respect to data processing techniques, memory usage, and other issues which crop up when you adapt a bunch of libraries meant for one thing to another set of much larger things.
Enter: split-merge. Since early last year, we have also had some scripts to help split up large datasets into smaller pieces, keeping those smaller pieces aligned with each other, and helping with some of the merging of those data back into a cohesive whole at the end. This was a great work-around for processing those larger datasets, but for a variety of reasons (funding and time being the big two), never got completed.
Now a big phase of that work is wrapping up. You can find that work in Pull Request #979. Do you have a really large dataset that needs processing on the ODM command line? Try the following:
./run.sh --project-path /path/to/datasets --split <target number of pictures per submodel> mydataset
Coming soon to a WebODM near you… .