DaiPatrick/sr-home-mea_001-un-bathroom_c004_l1_f1-2026-06-09
SR-HOME-MEA_001-UN-BATHROOM_C004_L1_F1 High-quality synthetic render data-pack featuring a detailed residential bathroom scene, captured from Camera_04 with 100 rendered outputs and 1,200 files across 12 production-ready render passes. This dataset is designed for computer vision, 3D perception, material analysis, segmentation, depth estimation, and synthetic data workflows. It includes beauty renders plus rich auxiliary passes such as albedo, depth, normals, UVW, material index… See the full description on the dataset page: https://huggingface.co/datasets/DaiPatrick/sr-home-mea_001-un-bathroom_c004_l1_f1-2026-06-09.
SR-HOME-MEA001-UN-BATHROOMC004L1F1
High-quality synthetic render data-pack featuring a detailed residential bathroom scene, captured from Camera_04 with 100 rendered outputs and 1,200 files across 12 production-ready render passes. This dataset is designed for computer vision, 3D perception, material analysis, segmentation, depth estimation, and synthetic data workflows. It includes beauty renders plus rich auxiliary passes such as albedo, depth, normals, UVW, material index, attenuation, and colored depth, enabling robust model training, validation, and debugging from a single controlled interior environment. Ideal for teams building vision models that need clean, structured, multi-pass synthetic imagery with consistent camera setup and reproducible render metadata. Version + courte : Synthetic residential bathroom render dataset with 100 outputs and 1,200 files across 12 render passes, including beauty, depth, albedo, normals, UVW, material index, attenuation, and colored depth. Built for computer vision, 3D perception, segmentation, material understanding, and synthetic data pipelines.
This dataset mirrors public data-pack render outputs from Physicl.
Each row represents one render view. The image column contains a stable URL to the primary render image uploaded under /data; image_path stores the relative repository path and data_commit_sha pins the Hugging Face dataset commit used by those URLs.
Additional render passes are exposed as URL columns. Use metadata.pass_files to inspect the original S3 object key, Hugging Face /data path, URL, file name, and size for each render pass.
Dataset repo: https://huggingface.co/datasets/DaiPatrick/sr-home-mea001-un-bathroomc004l1f1-2026-06-09
