--- 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_.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_.npz`** (SAM 3.1 INFERRED concepts + per-scene cloud masks).