Running OpenSfM on a cluster computer setup
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 3.8k
- Forks
- 899
- PR merge metrics
- No merged PRs in 30d
Description
I am thinking of build my own cluster computer setup
I am wondering if OpenSfM can be used on a cluster computer setup
i've read https://opensfm.readthedocs.io/en/latest/large.html
Only the GPS positions of the images and the ground control points will determine the alignment.
the feature extraction and matching can also be done before creating the submodels. This makes it possible for each submodel to reuse the features and matches of the common images.
but the match_features is the slowest part, so I was think can I running this step of a group computer to speed it up?
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No files, tests, or implementation entry points are named. Start with the large-scale documentation and trace the match_features step to understand its current execution model. Before implementation, define the supported cluster workflow and a measurable completion criterion for speeding up feature extraction or matching.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- distributed-systems, performance
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100