3D Point Cloud Study in Python
A client engagement reproducing a point cloud study in Python with 3D display, documented step by step and generalised so the code runs on arbitrary point clouds rather than one fixed dataset.
- Year
- 2024
- Engagement
- Client engagement
- Focus
- AI/ML, Data Engineering
- Status
- Open source
01 — The problem
An existing point cloud study needed to be reproduced in Python and, more importantly, made to work on point clouds other than the one it was written for.
02 — Our solution
Rebuild the study as documented, generalised Python: 3D display working end to end, with the basic steps written down so the process can be repeated on new data.
How it works
The pipeline, step by step — from the first input to the final output.
- 01
Load
Point cloud data is read into a working representation.
- 02
Process
The study's processing steps are reimplemented in Python.
- 03
Display
Results are rendered as 3D visualisation.
- 04
Generalise
Hardcoded assumptions are removed so the code accepts any point cloud.
What we built
The outcomes
01
Delivered and rated 5.0 by the client
02
Reusable code that runs beyond the original dataset
Challenges we solved
Generalisation over reproduction
Matching one dataset is straightforward; working on any input means finding and removing every implicit assumption.
Technology stack
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