granular op• Data kinds: any × scalar × scalar × signal → table
• Call: import fullseye as fs; fs.ledger.dispense_mass_from_video(frames, pitch: 'float', bulk_density: 'float', times, ground=None) -> 'dict' (to call the implementation directly, import granular; granular.dispense_mass_from_video(frames, pitch: 'float', bulk_density: 'float', times, ground=None) -> 'dict'; from the registry, opsdrive.get("dispense_mass_from_video"))
Dispensed mass and discharge rate from a sequence of heightmaps — heap volume of each frame × ρ_b, and a linear fit against time (least squares).
Returns: masses [kg], rate (slope [kg/s]), total (last − first), rms (linear-fit residual [kg]). Raises ValueError: fewer than 2 frames / number of timestamps does not match / timestamps not monotonic. The image's volume resolution is of the order of pitch³ ρ_b (1.5 mg/pixel³ at 1 mm and 1500 kg/m³, but the uncertainty of 1 pixel at the edge is multiplied by area × pitch, so in practice it is gram-level). Leave milligram-level to a scale.
• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).
• Operator provenance and references — the sources of the research/methods this op family came from.
• The canonical algorithm (author, year) and its uses are named in the family usage guide above.
• poc_granular_heap_repose — py -3.11 examples/poc_granular_heap_repose.py
table as input)course_layout · course_occupancy · course_contains · world_build · world_camera · world_move · lidar_scan · rss_longitudinal_same
granular)heap_volume_cone · heap_mass · heap_volume_heightmap · beverloo_rate · beverloo_fit · discharge_synth · hopper_discharge_rate · spoon_tilt_critical
*Provenance: granular.py — DRIVE operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.