S3DIS image inputs and visibility files are referenced but preprocessing pipeline is missing
Nobody has claimed this yet.
Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 45/100
- Issue type
- Feature
- Clarity
- Mostly clear
- Activity status
- Quiet
- Tech stack
- python
- Domain
- computer-vision, data-engineering
Research direction
Start by reading pointcept/datasets/s3dis.py and pointcept/datasets/preprocessing/s3dis/preprocess_s3dis.py to trace the referenced *_mask.npy, *_points.npy, and *.png inputs. Identify the raw data source and preprocessing steps needed for data/s3dis_images and data/s3dis_visibility. Done means the repository documents the source and reproducible steps, or includes a script that generates both directories.
Written by the indexing model from the issue text.
Description
Hi, thanks for the great project.
I noticed that the S3DIS image-based model refers to the following data paths:
data/s3dis_images/{Area}/{Room}/color/data/s3dis_visibility/{Area}/{Room}/visibility/
These files are consumed by pointcept/datasets/s3dis.py through:
*_mask.npy*_points.npy*.png
However, in the current repository I could not find a preprocessing or generation script that produces these two directories for S3DIS.
What I found:
pointcept/datasets/preprocessing/s3dis/preprocess_s3dis.pyonly generates the 3D room-level files such ascoord.npy,color.npy,segment.npy, andinstance.npy- I could not find a script in the repo that generates:
data/s3dis_images/...data/s3dis_visibility/...
Could you please clarify:
- How are
s3dis_imagesands3dis_visibilitygenerated? - Are they derived from Stanford 2D-3D / a separate preprocessing pipeline?
- Is there any script, dataset source, or documentation that should be added to the repository?
If possible, it would be very helpful to include:
- the exact preprocessing steps,
- required raw data sources,
- and a script to generate these files reproducibly.
Thanks!
- Dominant language
- Python
- Stars
- 113
- Forks
- 8
- PR merge metrics
- No merged PRs in 30d
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.
More from VisualComputingInstitute/ditr
-
Difficulty 3/5 1-2 days Newbie friendliness 48/100
-
Difficulty 4/5 3-5 days Newbie friendliness 52/100
VisualComputingInstitute/ditr#15 · 1 comment ·
-
Difficulty 5/5 Over a week Newbie friendliness 25/100
VisualComputingInstitute/ditr#13 · 1 comment ·
-
Inference demo Open
Difficulty 4/5 3-5 days Newbie friendliness 35/100
VisualComputingInstitute/ditr#12 · 7 comments ·
All issues in VisualComputingInstitute/ditr
Similar issues
-
Difficulty 2/5 1-3 hours Newbie friendliness 88/100
-
Difficulty 2/5 1-3 hours Newbie friendliness 82/100
-
Difficulty 2/5 1-3 hours Newbie friendliness 78/100
-
enhancement
Difficulty 2/5 1-3 hours Newbie friendliness 72/100
-
Difficulty 2/5 1-3 hours Newbie friendliness 74/100