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Download QUALITY.md from diffracting/egocentric-maintenance-sample: direct link, hf CLI and curl.
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https://huggingface.co/datasets/diffracting/egocentric-maintenance-sample/resolve/main/QUALITY.md
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hf download hf://datasets/diffracting/egocentric-maintenance-sample/QUALITY.md
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curl -L -o QUALITY.md https://huggingface.co/datasets/diffracting/egocentric-maintenance-sample/resolve/main/QUALITY.md
3.37 kB
| # Quality and review | |
| All 5,308 training frames are checked against source-frame mappings. Full video decode and standalone reader checks are recorded in [validation.json](validation.json). Face detection ran on every displayed training frame and returned zero detections for these excerpts. Audio and source location/container metadata are omitted from public videos. | |
| The assistant reviewed RGB storyboards at approximately two-second intervals and clip endpoints, and estimated-overlay frames near the start, middle and end. No visible faces or identifying private text were found in inspected frames. This is a sampled visual review, not an exhaustive manual privacy audit or an independent annotation-accuracy evaluation. | |
| ## Estimated annotation coverage | |
| Hand keypoints were requested at 10 Hz and object detection at 5 Hz. Counts below describe timestamps with emitted estimates; they do not measure recall against visible objects/hands. Unknown percentages use temporal hand instances (one track at one timestamp), not keypoint rows. A track is not an independent person or physical entity. | |
| | Excerpt | Raw hand timestamps | Unknown handedness | Max temporal hands at one timestamp | Object timestamps | | |
| |---|---:|---:|---:|---:| | |
| | remove-tape | 290 | 24.2% | 2 | 145 | | |
| | brush-front-grille | 300 | 50.0% | 2 | 150 | | |
| | brush-housing | 300 | 100.0% | 2 | 137 | | |
| | brush-panel-channels | 300 | 99.3% | 3 | 144 | | |
| | wipe-panel | 300 | 13.7% | 3 | 150 | | |
| | wipe-panel-corners | 280 | 24.0% | 3 | 135 | | |
| The raw hand candidate selection caps detections at two per timestamp. Temporal interpolation can briefly retain extra tracks. The public tables preserve raw and temporal estimates separately, with null z/world coordinates and explicit provenance. Some visible hands are missed; finger placement, small-tool boxes and handedness are imperfect. An object track may change ID during one manipulation. Review overlays intentionally expose these errors. Overlays use a constant-frame-rate display clock and are visual aids, not the alignment reference. | |
| ## Language and grouping | |
| The assistant prepared the instructions and 13 action intervals from visual review. Boundaries are approximate to two seconds and have not been independently checked by a human annotator. The intervals describe observed actions, not task success or robot commands. One conservative session group covers all six excerpts; do not split excerpts from this session between training and evaluation and then claim independent generalization. | |
| ## Capture limitations and next collection | |
| This release covers one camera wearer, one appliance/work area and one apparent session. Viewpoint is chest-mounted according to the owner. The public 1920 x 1080 images are tone-mapped from iPhone HLG HDR; full original MOV files remain with the owner. Exposure changes, motion blur, self-occlusion and repetitive activity are visible. Metric geometry, forces, tactile measurements and robot control/state are unavailable. | |
| For a paid capture pilot, agree on target tasks, full task sequences, multiple workers/sites, tool visibility and acceptance criteria. A labeled evaluation subset and held-out sessions would support measured annotation quality and downstream utility. This sample establishes delivery structure and inspectable footage; it does not report training gains. | |