microsoft / microsoft/GlobalMLBuildingFootprints
350.000 'buildings' in Spitsbergen
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- Dominant language
- Python
- Stars
- 2k
- Forks
- 277
- PR merge metrics
- No merged PRs in 30d
Description
The dataset contains many false positive buildings around Spitsbergen. It seems that the algorithm may have difficulties with icebergs or rocks? They appear all around the island, but it seems most are in the sea right next to the coast.
There are false positives all around the world, but I haven't seen this many errors in one place yet.
Contributor guide
No contributing guide indexed for this repository
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
Begin by reproducing the Spitsbergen area from the dataset and reviewing the attached image, then trace the Python algorithm or model stage responsible for those detections. Done should mean the false positives are characterized and a concrete cause or correction path is established, but the issue names no files or tests to guide that work.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-vision, machine-learning
- Issue type
- Bug
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100