OpenDroneMap / OpenDroneMap/ODM
DJI P1 Sensor is not being handled correctly for SFM Triangulation
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- Dominant language
- Python
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Description
How did you install ODM? (Docker, installer, natively, ...)?
Docker 3.0.5
What is the problem?
Camera orientation isn't being parsed correctly, as evidenced with attached dataset (21 images). Incremental process works fine, triangulation does not.
https://community.opendronemap.org/t/sfm-triangulation-and-orthophotos-very-strange-results/14597/9
What should be the expected behavior? If this is a feature request, please describe in detail the changes you think should be made to the code, citing files and lines where changes should be made, if possible.
SFM triangulation should produce an ortho that isn't 'garbled'.
Examples from sample provided dataset:
Triangulation:

Incremental:

How can we reproduce this? What steps did you do to trigger the problem? If this is an issue with processing a dataset, YOU MUST include a copy of your dataset AND task output log, uploaded on Google Drive or Dropbox (otherwise we cannot reproduce this).
docker run -ti --detach --rm --tty --name odm_container -v /odm/datasets/project:/datasets/code opendronemap/odm --project-path /datasets
--auto-boundary
--orthophoto-resolution 1.5
--gps-accuracy 0.03
--sfm-algorithm triangulation
--rerun-from dataset
21 image dataset here: https://drive.google.com/drive/folders/1TVp9oM4i6AEL60KjhxL45CdB5RvP1eoN?usp=share_link
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
Start by reproducing the Docker command with the linked 21-image dataset, comparing the SFM triangulation output with the incremental output. Trace how camera orientation is parsed and passed into triangulation; done means the triangulated orthophoto is not garbled.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- docker
- Domain
- computer-vision
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100