{
  "schema_version": "1.3.1",
  "job_id": "bulk_9_videos_933d5ad5",
  "batch": true,
  "video_count": 9,
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      },
      "sequence": {
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      },
      "sequence": {
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    },
    {
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      "fps": 60.0,
      "exported_frames": 948,
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        "frames_with_intel": 237,
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          "finger_active": 236,
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      },
      "sequence": {
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        "action_label": "Dexterous Hand movements",
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        "hip_center_displacement_mean_norm": 0.0,
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        "velocity_proxy_available": true,
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        "step_frequency": 60.0,
        "motion_consistency": 1.0
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  ],
  "aggregate": {
    "total_frames": 9112,
    "action_label": "Dexterous Hand movements",
    "stride": 1,
    "mean_quality_score": 0.9715,
    "mean_avg_landmark_visibility": 0.942951,
    "fps_mean": 34.98001998001998,
    "motion_intelligence": {
      "enabled": true,
      "domain": "hand_dexterous",
      "frames_with_intel": 2278,
      "mean_speed_combined": 0.631809,
      "mean_finger_tip_speed_mean": 0.631809,
      "mean_wrist_speed_norm_per_sec": 0.450045,
      "hand_activity_histogram": {
        "finger_active": 2240,
        "hand_translating": 1,
        "manipulation": 24,
        "static": 13
      },
      "grip_type_histogram": {
        "neutral": 3,
        "open": 1444,
        "pinch": 227,
        "power": 33,
        "precision": 571
      }
    },
    "buyer_marketing": {
      "tagline": "Train your AI on real hand motion data \u2014 ready in minutes.",
      "commercial_use": "Unlike many academic datasets, Quality Vision B2B exports are intended for commercial use under your agreed license terms \u2014 see LICENSE_EXPORT.txt in the ZIP and manifest.license / dataset_license (not limited to research-only).",
      "feature_highlights": [
        "21-point hand keypoints (MediaPipe-style)",
        "Temporal sequences with timestamps",
        "Per-frame action field + metadata/actions.csv (optional per-frame taxonomy via job payload)",
        "Hand\u2013object interaction metadata when hq.object_interaction is configured",
        "Optional camera_pov: first_person | third_person (manual)",
        "JSONL + optional COCO-like keypoints export",
        "PyTorch loader guide: examples/README_PYTORCH.md"
      ],
      "use_cases": [
        {
          "label": "Robotics",
          "emoji": "\ud83e\udd16"
        },
        {
          "label": "AR/VR",
          "emoji": "\ud83e\udd7d"
        },
        {
          "label": "Gesture recognition",
          "emoji": "\u270b"
        },
        {
          "label": "Human behavior AI",
          "emoji": "\ud83e\udde0"
        }
      ]
    }
  },
  "notes": "Batch export: `videos[]` holds one sequence block per source file. data.jsonl concatenates all frames with global frame_id and source_video_index; per_video/video_*.jsonl mirrors the same records split by source; see bulk_combined_manifest.json for paths."
}