Duplicate check should include FOV
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Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 25/100
Research direction
The issue names no files, tests, or entry points. Start by locating the duplicate-checking behavior and the available image metadata, then determine how horizontal and vertical FOV should be represented and configured. Done means duplicate detection can distinguish images with different FOVs without breaking existing checks.
Written by the indexing model from the issue text.
Description
I sometimes take pictures with different FOV, e.g. one with my wide-sensor, and one with the main sensor. Or even a panorama or 360° picture. In consequence those have the same location, and the same angle, despite having different information.
There should be an option to consider those pictures not to be duplicates, as they may contain vastly different information.
Not sure if there should be a separate value for vertical and horizontal, e.g. to distinguish 360° image spheres from panoramas, which may span 360° in horizontal direction, but may be limited vertically.
- Dominant language
- Python
- Stars
- 316
- Forks
- 145
- Avg merge
- 2d 18h
- Merged PRs (30d)
- 4
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