physicl-test/pack-aez-of-my-project-tx0xdc-c4782676
RT-DETR Fridge Vegetable Detection Eval Evaluation dataset of 5 renders staged in a home kitchen, each framing vegetables inside a densely packed refrigerator, to measure how reliably an RT-DETR model detects and identifies them. Rendered at 640x640 with albedo and metric depth passes, per-frame annotations, under low morning sunlight. This dataset mirrors public data-pack render outputs from Physicl. Each row represents one render view. The image column contains a stable URL to… See the full description on the dataset page: https://huggingface.co/datasets/physicl-test/pack-aez-of-my-project-tx0xdc-c4782676.
RT-DETR Fridge Vegetable Detection Eval
Evaluation dataset of 5 renders staged in a home kitchen, each framing vegetables inside a densely packed refrigerator, to measure how reliably an RT-DETR model detects and identifies them. Rendered at 640x640 with albedo and metric depth passes, per-frame annotations, under low morning sunlight.
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, including .exr passes such as depth_metric that the dataset viewer cannot preview but that are downloadable from /data. The metadata column is the Core renderOutput.metadata value serialized as JSON, without Hugging Face-specific enrichment.
Dataset repo: https://huggingface.co/datasets/physicl-test/pack-aez-of-my-project-tx0xdc-c4782676