nathankimnguyen412/houdini-lego-sdg

Houdini Lego SDG Dataset

Synthetic datasets generated by a procedural Houdini-based data generation pipeline for Lego brick instance segmentation and object detection. All images were rendered using Karma XPU in Houdini Solaris. Annotations were extracted automatically using Cryptomatte AOVs with no manual labeling on training data.

GitHub: nathankimnguyen412/houdini-sdg-pipeline

Dataset Versions

Version	Images	Classes	Description
v1	1,000	1	Baseline: no distractor objects, 29 domain randomization axes
v2	1,000	1	Distractor objects across 3 domain randomization axes added (bringing total axes from 29 to 32), 13 additional textures
v3	3,000	7	7-class scale-up
v4	7,000	7	Full-scale primary dataset

Classes (v3 and v4)

ID	Name
1	1x1_plate
2	2x4_plate
3	1x3_plate
4	1x2_plate_with_2_U_Clips
5	2x2_brick
6	1x1_brick_stud_on_side
7	1x1_round_brick

Format

Each version contains an images/ folder of 512×512 PNG renders and an annotations.json in COCO instance segmentation format.

Each version also includes a logs/wedge_log.csv containing every domain randomization parameter value for every rendered scene, generated automatically by the TOPs/PDG pipeline during dataset generation.

Citation

See the GitHub repository for citation information.

License

CC BY 4.0 — free to use for any purpose with attribution.