physicl-community/pack-b2b-of-my-project-rl9b43-3b59c896
Kitchen Robustness Evaluation for YOLOv8 Evaluation dataset of 40 renders across 12 varied kitchen scenes with maximum asset variation across locations, used to measure the robustness of a YOLOv8 object-detection model. Rendered at 640x640 with albedo and metric depth passes plus per-frame annotations (bounding boxes, camera pose, product labels). This dataset mirrors public data-pack render outputs from Physicl. Each row represents one render view. The image column contains a… See the full description on the dataset page: https://huggingface.co/datasets/physicl-community/pack-b2b-of-my-project-rl9b43-3b59c896.
Kitchen Robustness Evaluation for YOLOv8
Evaluation dataset of 40 renders across 12 varied kitchen scenes with maximum asset variation across locations, used to measure the robustness of a YOLOv8 object-detection model. Rendered at 640x640 with albedo and metric depth passes plus per-frame annotations (bounding boxes, camera pose, product labels).
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. Files are uploaded as downloaded unless optional PNG recompression is enabled by the sync operator.
Additional render passes are exposed as URL columns. The metadata column is the Core renderOutput.metadata value serialized as JSON, without Hugging Face-specific enrichment.
Dataset repo: https://huggingface.co/datasets/physicl-community/pack-b2b-of-my-project-rl9b43-3b59c896