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---
license: cc-by-4.0
pretty_name: HyperKD-RS
tags:
- remote-sensing
- segmentation
- knowledge-distillation
- time-series
---
# HyperKD-RS: hypergraphical knowledge-distillation targets for remote sensing
Teacher harvest for distilling a tiny promptable segmenter (PicoSAM3) along
**exact** hypergraph edges, plus the multispectral series the neural codec
("Planet-JEPA") trains on. Built for the OpenCV AI Competition 2026 entry
*Places Not Pixels* (Team Picasso).
Unlike HyperKD (MobileSAM2), which infers hyperedges from embedding
distances, the hyperedges here are exact:
- **temporal** — Hungarian identity tracks across up to 41 annual passes
(1985–2025); each track collapsed into a per-pixel majority-vote
**consensus mask** that serves as the training target,
- **granularity** — all three SAM scale masks (s0 subpart / s1 part /
s2 whole) per prompt, QC-gated per scale, plus laminar **containment
parents** between chosen-scale masks.
## Source
Landsat 4/5/7/8/9 (Microsoft Planetary Computer STAC), 4.8 km windows at
30 m, best annual pass per spot, SLC-off striping screened out (≤5% nodata).
Teacher: SAM 2.1 hiera-base-plus (int8), grid-prompted at 8×8 + half-stride
densify — the production tokenizer of the entry.
## Layout
One shard per AOI: `shards/shard_<tag>.npz`
| array | shape | meaning |
|---|---|---|
| `images` | (S,256,256,3) u8 | display RGB per pass |
| `multispec` | (S,160,160,4) f16 | raw reflectance r,g,b,nir08 |
| `dates`, `platforms` | (S,) str | exact acquisition date, platform |
| `masks` | (M,256,256) u8 | all QC-passing scale masks + consensus masks |
| `samples` | (N,11) f32 | one row per accepted prompt |
`samples` columns: `scene, cx, cy, s0, s1, s2, chosen, track, parent, target,
is_consensus` — `s0..s2` index into `masks` (−1 = failed that scale's QC),
`chosen` is the production pick, `parent` the laminar containment parent
within the pass (−1 = top-level), `target` the distillation target
(track consensus where the track has ≥2 observations), `cx,cy` in the
800×800 prompt frame.
Labels are **never baked into geometry**: concept annotations (SAM 3.1,
calibrated per concept via the taxonomy's `visual` prompts and thresholds)
ship separately as INFERRED facts.
## Follow along
The complete pipeline — fetchers, tri-scale harvester, SAM 3.1 labeller,
PicoSAM3 distillation harness, taxonomy, AOI manifest, and the QC audit
trail — ships in [`harness/`](./tree/main/harness) (also bundled as
[`harness.zip`](./blob/main/harness.zip)); run order is in its README.
## AOIs
32 spots across 12 domains (farmland, grazing, aquaculture, coastal, fire,
flood, protected, water, urban/infrastructure, mining, forestry, nuisance) —
**complete: 32 annual shards (1,217 scenes, 1985–2025) + 6 event shards
(`_ev`, 73 monthly passes inside documented fire/flood windows), every shard
with a matching `labels/labels_<tag>.npz`** (SAM 3.1 INFERRED concepts +
per-scene cloud masks).