feat(PCSegSAM2): auto pointcloud segmentation using SAM2 and GroundingDino #44
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- non-neded files are present, but since a squash merge is expected, it should not be an issue - sam2 for t4datasets - projective approach to segment pointclouds missing: - temporal consistency criteria - hardcoded filters for pointcloud segmentation Signed-off-by: Kenzo Lobos-Tsunekawa <[email protected]>
Signed-off-by: Kenzo Lobos-Tsunekawa <[email protected]>
Signed-off-by: Kenzo Lobos-Tsunekawa <[email protected]>
Signed-off-by: Kenzo Lobos-Tsunekawa <[email protected]>
…environment Signed-off-by: Kenzo Lobos-Tsunekawa <[email protected]>
Signed-off-by: Kenzo Lobos-Tsunekawa <[email protected]>
Signed-off-by: Kenzo Lobos-Tsunekawa <[email protected]>
Signed-off-by: Kenzo Lobos-Tsunekawa <[email protected]>
Signed-off-by: Kenzo Lobos-Tsunekawa <[email protected]>
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Summary
Since we lack large segmentation databases I leveraged the use of SAM2, GroundingDino, and the vehicle calibration to segment pointclouds using open source foundation models.
This project allows to:
This project essentially copies
https://github.com/IDEA-Research/Grounded-SAM-2/tree/main
and implement the necessary features.
I asked @scepter914 and there was no reticence to just paste all the required code as long as there was no issues with the licences.
Change point
Add a new project for automatic pointcloud segmentation
Note
Since it is a new project with an independent docker, it does not affect any other project in the codebase
Test performed
Build docker, run all tasks presented in the README, and segmented t4data (during April)