[PRE REVIEW]: Segment-Lidar: Automatic Unsupervised LiDAR-Segmentation using Segment-Anything Model (SAM)

[editorialbot]

Submitting author: @Yarroudh (Anass Yarroudh)
Repository: https://github.com/Yarroudh/segment-lidar
Branch with paper.md (empty if default branch): main
Version: v0.2.1
Editor: Pending
Reviewers: Pending
Managing EiC: Arfon Smith

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Software report:

github.com/AlDanial/cloc v 1.88  T=0.04 s (949.5 files/s, 189569.1 lines/s)
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SUM:                            42            924            638           6823
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gitinspector failed to run statistical information for the repository

[editorialbot]

Wordcount for paper.md is 1372

[editorialbot]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.21105/joss.05663 is OK
- 10.3390/rs8060501 is OK
- 10.3390/rs14225649 is OK

MISSING DOIs

- 10.1049/cp.2019.0255 may be a valid DOI for title: A Benchmark Dataset for RGB-D Sphere Based Calibration

INVALID DOIs

- https://doi.org/10.1016/B978-0-08-102696-0.00016-6 is INVALID because of 'https://doi.org/' prefix

[editorialbot]

👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

[editorialbot]

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[arfon]

Thanks for your submission to JOSS @Yarroudh. Could you please explain what the software contribution of this project is? From the looks of things, this is ~500 lines of Python that interacts with some models. Is that correct?

[Yarroudh]

Hello @arfon,
Thanks for responding to my submission. The software contribute to 3D point cloud automatic segmentation using an image-based approach. The view module handles the projection of the point cloud into an image plane, this includes a simple top view for aerial LiDAR data and a Pinhole camera for customized views. The resulting image is segmented using Segment-Anything-Model (SAM) to extract all masks from the image. The results are reprojected on the 3D point cloud to extract individual instances. Other features are implemented like text prompts for specific objects extraction and ground points filtering for enhanced segmentation of aerial LiDAR data.

[arfon]

@editorialbot query scope

OK, thanks for the input. As this is on the smaller-size of what we publish in JOSS, I'm going to initiate a scope review with the JOSS editorial team. This will take a couple of weeks to complete.

[editorialbot]

Submission flagged for editorial review.

[Yarroudh]

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[Yarroudh]

@editorialbot generate preprint

[editorialbot]

📄 Preprint file created: Find it here in the Artifacts list 📄

[arfon]

@Yarroudh - thanks for your submission to JOSS. Unfortunately, after review by the JOSS editorial team we've determined that this submission doesn't meet our substantial scholarly effort criterion.

One possible alternative to JOSS is to follow GitHub's guide on how to create a permanent archive and DOI for your software. This DOI can then be used by others to cite your work.

[arfon]

@editorialbot reject

[editorialbot]

Paper rejected.