facebookresearch / facebookresearch/sam-3d-objects
Evaluation Data: IM-MA mesh geometry defect breakdown across 101 exports
- Dominant language
- Python
- Stars
- 7.4k
- Forks
- 878
- PR merge metrics
- No merged PRs in 30d
Description
Hi IM-3D / Meta GenAI team,
I ran an open, reproducible geometry QA census (`3dqa-benchmark`) across 2,307 generative exports from 23 models.
**IM-MA Metrics (n=101):**
- Non-watertight: 84.2%
- Non-manifold edges: 53.5%
- Missing UVs: 100%
- Vertex-colour-only exports: 100%
- Exceeding 30k budget: 0.0%
Full reproducible CLI runner (`pip install 3dqa`) and aggregate reports are available at:
https://github.com/alza123123/3dqa-benchmark
Contributor guide
Research direction
Start with the linked 3dqa-benchmark CLI runner and its aggregate reports to reproduce the IM-MA measurements. The issue names no repository files, tests, or specific requested change; completion would require clarifying which geometry defect to address and how the 101 exports should be evaluated.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-graphics, testing-qa
- Issue type
- Bug
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100