KB Quality grade is Kinetic Blocks' own grade, A+ to F, measured from the files across four pillars: Technical, Temporal integrity, Content, Completeness.
KB Quality grade is Kinetic Blocks' own grade, A+ to F, measured from the files across four pillars: Technical, Temporal integrity, Content, Completeness. How grading works
What you get
Measured hours
0.3 h
Measured by Kinetic Blocks from the files, not declared by the seller.
Clips
3 clips
KB Quality grade
A+
Task
Cooking & food prep
Modality
2D RGB video
Region
Asia
Capture
Egocentric (camera worn by the person, first-person view)
Declared by the seller. Kinetic Blocks does not yet check the viewpoint against the files; open the free sample to see it.
File formats
json, csv, parquet
Licence
Commercial Standard
Commercial use permitted, across your organisation. You may not redistribute, resell, or publish the dataset. Read more
Sale mode
Non-exclusive, can be sold to multiple buyers
Plain-English summary. The Data Licence Agreement you accept governs. Read the full terms
You pay Kinetic Blocks, never the seller. You get 5 business days to check the files against the dataset card. Reject for a material mismatch and, once we uphold it, you are refunded in full. How payment works
What we checked against the files
5 of 6 claims verified against the files
5 verified
1 can't confirm
0 doesn't match
Dataset card check
✓verified
Episode count check
✓verified
Total Size
✓verified
Total duration check
✓verified
Episode Index
✓verified
IMU check
Declared by the seller, not yet verified.
?can't confirm
KB Quality grade A+, by pillar
A+
A
A-
B+
B
B-
C+
C
C-
D
F
Technical quality30%
100
Temporal integrity25%
100
Content usefulness30%
98
Completeness15%
100
Dead time is mapped, not cut.
100% active task footage (0.3 h of 0.3 h)
Violet is task action, grey is idle, measured by Kinetic Blocks in every clip. Idle stretches lower the grade; they are never cut from the files.
Scores out of 100. Every seller is graded on the same versioned weights. How grading works
Egocentric human hand demonstration: slicing, dicing and peeling produce.
Overview
First-person video of a person's hands slicing, dicing and peeling produce in a commercial kitchen, recorded with a head-mounted camera. Includes 4K video, IMU, 3D hand landmarks and camera calibration for every episode, delivered in LeRobot format.
Dataset card
# Vegetable & Fruit Cutting, first person
## Summary
First-person video of a person's hands slicing, dicing and peeling produce in a commercial kitchen,
recorded with a head-mounted camera. One continuous take per episode.
Every episode includes 3D hand landmarks, IMU and intrinsic camera calibration.
## Contents
- Episode count: 3
- Total duration: 0.30 hours (1085.101 s)
- Total size: 16.4 GB (15.3 GiB)
- Frame rate: 59.94 fps (60000/1001)
- Resolution: 3840x2160
- Codec: HEVC, 10-bit (yuv420p10le), stream-copied from the camera
- Audio: included (AAC, 48 kHz, 2-channel, inside each video file)
- Capture: Egocentric
- In frame: Human hands
- IMU: accelerometer and gyroscope, about 197 Hz (the camera's native rate)
- Hand pose: 21 landmarks per hand, per frame (Google MediaPipe Hand Landmarker, Apache 2.0)
- Camera calibration: intrinsic (focal length, optical centre, lens distortion), one file per episode
- Format: LeRobot v3.0 (Parquet, MP4, JSON, CSV)
- Licence: Commercial Standard
## Layout
One video per episode: videos/observation.images.head/chunk-000/file-000.mp4 to file-002.mp4.
Per-episode files: rizlytics/episodes/episode_000000/ to episode_000002/, each with
episode_NNNNNN_imu.csv (timestamp, accel_c0-c2, gyro_c0-c2), hands.csv, calibration.json and manifest.json.
Frame-aligned data in data/chunk-000/*.parquet, metadata in meta/, checksums in SHA256SUMS.
## Capture
Head-mounted GoPro HERO11 Black, linear lens, single camera. Indoor, commercial kitchen, Pakistan (Asia).
Human demonstration, no robot. Every person in frame is covered by a signed release.
## Intended use
Imitation learning and video pretraining for knife work and food prep; hand-object interaction and hand-pose models.
