feat(perception): add autonomous vegetation shadow lab

2026-08-27 23:26:35 +03:00
parent 7594c71dd1
commit 57204b3b0b
26 changed files with 2494 additions and 5 deletions
@@ -50,6 +50,7 @@ import { M48SFixedClassDetectorResultView } from "./M48SFixedClassDetectorResult
 import { M48TRiskQualityResultView } from "./M48TRiskQualityResult";
 import { M49TgsFailClosedResultView } from "./M49TgsFailClosedResult";
 import { M49TgsFullShadowResultView } from "./M49TgsFullShadowResult";
+import { VegetationShadowResultView } from "./VegetationShadowResult";

 export { isAdvancedLaboratoryWorkId };
 export type { AdvancedLaboratoryWorkId };
@@ -92,6 +93,9 @@ export function AdvancedLaboratoryResult({
  failedSessionId: string | null;
  replayError: string | null;
 }) {
+  if (workId === "lab-v1-vegetation-shadow" && results.vegetationShadow) {
+    return <VegetationShadowResultView rigLabel={rigLabel} result={results.vegetationShadow} />;
+  }
  if (workId === "m48-object-centric-quality" && results.m48) {
    return <M48ObjectCentricQualityResultView rigLabel={rigLabel} result={results.m48} />;
  }
@@ -0,0 +1,135 @@
+import {
+  LaboratoryEvidence,
+  LaboratoryResultSummary,
+  LaboratorySummary,
+  LaboratoryWorkTemplate,
+} from "../../components/laboratory/LaboratoryPresentation";
+import type { VegetationShadowResult } from "../../core/laboratory/vegetationShadow";
+import {
+  VegetationRouteVisual,
+  VegetationValidationVisual,
+} from "./VegetationShadowVisual";
+
+function decimal(value: number, digits = 1): string {
+  return value.toLocaleString("ru-RU", { maximumFractionDigits: digits });
+}
+
+export function VegetationShadowResultView({
+  rigLabel,
+  result,
+}: {
+  rigLabel: string;
+  result: VegetationShadowResult;
+}) {
+  const selected = result.candidates.find(
+    (candidate) => candidate.candidate === result.selectedCandidate,
+  )!;
+  const alternative = result.candidates.find(
+    (candidate) => candidate.candidate !== result.selectedCandidate,
+  )!;
+  return (
+    <LaboratoryWorkTemplate
+      summary={(
+        <LaboratorySummary
+          title="LAB V1 · растительность и mission-policy пресеты"
+          description="Две готовые fine-64 модели GOOSE проверены на полном validation split и перенесены в автономный визуальный shadow по RAVNOVES00. Интерфейс читает sealed-кадры локально и не зависит от доступности Worker 006."
+          status="Визуальный shadow готов · navigation authority OFF"
+          statusTone="warning"
+          facts={[
+            { label: "Источник", value: `${rigLabel} RIGHT · 12 raw KB4 кадров + GOOSE validation 962` },
+            { label: "Сравнение", value: "DDRNet-39 vs PPLiteSeg · official fine-64 weights" },
+            { label: "Policy", value: "Urban / rural / off-road · mission-configurable" },
+            { label: "Authority", value: "SHADOW ONLY · commands OFF · geometry stays authoritative" },
+          ]}
+          brief={{
+            question: "Можно ли взять готовую сегментацию растительности, увидеть её на нашем маршруте и сразу проверить разные правила миссии?",
+            approach: "Обе модели последовательно прогнаны в одном изолированном CUDA-runtime: сначала 962 размеченных GOOSE-кадра, затем 12 детерминированных кадров RAVNOVES00. Для каждого кадра запечатаны source, обе семантики и три policy-проекции.",
+            principalResult: `${selected.loadedModelName} выбран по vegetation IoU ${decimal(selected.vegetationMeanIouPercent, 2)}% при shadow p95 ${decimal(selected.shadowLatencyP95Ms, 2)} ms. Визуальный результат доступен локально без Worker.`,
+            limitation: "RAVNOVES00 не размечен по fine-64, поэтому это перенос и визуальная проверка, а не доказательство точности или безопасности. Камерная семантика не может очищать жёсткую LiDAR/TGS occupancy.",
+          }}
+          method={{
+            completeness: "complete",
+            executionClass: "ai-inference",
+            pipelineId: "goose-fine64-ready-weights-to-ravnoves-policy-shadow/v1",
+            components: result.candidates.map((candidate) => ({
+              kind: "model" as const,
+              name: candidate.loadedModelName,
+              version: candidate.candidate,
+              role: candidate.candidate === result.selectedCandidate ? "selected policy provider" : "comparison candidate",
+              identitySha256: candidate.checkpointSha256,
+            })),
+          }}
+        />
+      )}
+      evidence={(
+        <>
+          <LaboratoryEvidence
+            eyebrow="RAVNOVES00 · AUTONOMOUS VISUAL SHADOW"
+            title="Источник, обе модели и три правила миссии на одинаковых кадрах"
+            kind="diagnostic-model"
+            resizable
+          >
+            <VegetationRouteVisual result={result} />
+          </LaboratoryEvidence>
+          <LaboratoryEvidence
+            eyebrow="GOOSE · EXTERNAL VALIDATION EVIDENCE"
+            title="Независимая разметка: truth против DDRNet и PPLiteSeg"
+            kind="diagnostic-model"
+            resizable
+          >
+            <VegetationValidationVisual result={result} />
+          </LaboratoryEvidence>
+        </>
+      )}
+      result={(
+        <LaboratoryResultSummary
+          title="Готовые веса дают рабочую точку старта, но ещё не право ехать"
+          status={`${selected.loadedModelName} выбран для shadow`}
+          statusTone="warning"
+          metrics={[
+            {
+              label: "GOOSE mIoU",
+              value: `${decimal(selected.meanIouPercent, 2)}% / ${decimal(alternative.meanIouPercent, 2)}%`,
+              hint: `${selected.candidate} / ${alternative.candidate} · полный validation split`,
+            },
+            {
+              label: "Vegetation IoU",
+              value: `${decimal(selected.vegetationMeanIouPercent, 2)}% / ${decimal(alternative.vegetationMeanIouPercent, 2)}%`,
+              hint: "агрегация классов grass/vegetation/bush/tree и родственных fine-64 labels",
+            },
+            {
+              label: "RAVNOVES p95",
+              value: `${decimal(selected.shadowLatencyP95Ms, 2)} / ${decimal(alternative.shadowLatencyP95Ms, 2)} ms`,
+              hint: "чистый inference · одна тяжёлая модель за раз",
+            },
+            {
+              label: "Cold prewarm",
+              value: `${decimal(selected.shadowPrewarmLatencyMs, 1)} / ${decimal(alternative.shadowPrewarmLatencyMs, 1)} ms`,
+              hint: "один явный inference до допуска кадров; исключён из steady-state p95",
+            },
+            {
+              label: "RAVNOVES throughput",
+              value: `${decimal(selected.shadowThroughputFps, 1)} / ${decimal(alternative.shadowThroughputFps, 1)} FPS`,
+              hint: "изолированный Worker 006 · не realtime graph целиком",
+            },
+            {
+              label: "Peak VRAM",
+              value: `${decimal(selected.peakReservedVramBytes / 1024 ** 3, 2)} / ${decimal(alternative.peakReservedVramBytes / 1024 ** 3, 2)} GiB`,
+              hint: `${selected.candidate} / ${alternative.candidate} · RTX 4090`,
+            },
+            {
+              label: "Autonomous evidence",
+              value: "12 route + 12 validation",
+              hint: "только текущий кадр загружается в viewer; Worker не требуется",
+            },
+          ]}
+          conclusion={{
+            proved: "Обе официальные fine-64 модели запускаются на Worker 006, проходят полный GOOSE validation и дают воспроизводимые растительные маски на 12 фиксированных RAVNOVES00 кадрах. Urban/rural/off-road policy-проекции формируются без повторного inference.",
+            notProved: "Не доказаны accuracy на нашем fisheye-домене, различение тонкой травы от толстого ствола во всех условиях, temporal stability, collision safety и physical-live поведение ровера.",
+            decision: "Сохранить выбранную модель как shadow provider. Следующий критический блок — разметить небольшой hard-case island нашего офф-роуда: трава, папоротник, куст с толстыми стволами и дерево; затем калибровать policy без ослабления LiDAR/TGS fail-closed геометрии.",
+          }}
+        />
+      )}
+    />
+  );
+}
@@ -0,0 +1,157 @@
+import { useState } from "react";
+import { Icon, IconButton, StatusBadge } from "@nodedc/ui-react";
+
+import { LaboratoryEvidenceViewer } from "../../components/laboratory/LaboratoryEvidenceViewer";
+import type {
+  VegetationRouteMode,
+  VegetationShadowResult,
+  VegetationValidationMode,
+  VegetationVisualCase,
+} from "../../core/laboratory/vegetationShadow";
+
+const ROUTE_MODES = [
+  { value: "source", label: "SOURCE" },
+  { value: "ddrnet", label: "DDRNET" },
+  { value: "ppliteseg", label: "PPLITE" },
+  { value: "urban", label: "URBAN" },
+  { value: "rural", label: "RURAL" },
+  { value: "offroad", label: "OFF-ROAD" },
+] as const;
+
+const VALIDATION_MODES = [
+  { value: "source", label: "SOURCE" },
+  { value: "truth", label: "TRUTH" },
+  { value: "ddrnet", label: "DDRNET" },
+  { value: "ppliteseg", label: "PPLITE" },
+] as const;
+
+function VegetationScene({
+  item,
+  mode,
+}: {
+  item: VegetationVisualCase;
+  mode: string;
+}) {
+  const overlay = mode === "source" ? null : item.assets[mode];
+  return (
+    <div className="recorded-evidence-image-scene">
+      <img src={item.assets.source} alt="" draggable={false} />
+      {overlay ? <img src={overlay} alt="" draggable={false} /> : null}
+    </div>
+  );
+}
+
+export function VegetationRouteVisual({ result }: { result: VegetationShadowResult }) {
+  const [index, setIndex] = useState(0);
+  const [mode, setMode] = useState<VegetationRouteMode>("offroad");
+  const [expanded, setExpanded] = useState(false);
+  const item = result.routeCases[index] ?? null;
+  const selected = result.candidates.find(
+    (candidate) => candidate.candidate === result.selectedCandidate,
+  );
+  return (
+    <LaboratoryEvidenceViewer
+      label="RAVNOVES00 vegetation policy shadow"
+      className="m48-atlas-visual"
+      mode={mode}
+      modes={ROUTE_MODES}
+      expanded={expanded}
+      onModeChange={setMode}
+      onExpandedChange={setExpanded}
+      actions={(
+        <>
+          <IconButton
+            label="Предыдущий vegetation shadow кадр"
+            disabled={!result.routeCases.length}
+            onClick={() => setIndex((current) => (
+              current - 1 + result.routeCases.length
+            ) % result.routeCases.length)}
+          >
+            <Icon name="chevron-left" size={16} />
+          </IconButton>
+          <IconButton
+            label="Следующий vegetation shadow кадр"
+            disabled={!result.routeCases.length}
+            onClick={() => setIndex((current) => (current + 1) % result.routeCases.length)}
+          >
+            <Icon name="chevron-right" size={16} />
+          </IconButton>
+        </>
+      )}
+      overlay={item ? (
+        <div className="m48-atlas-visual__case">
+          <StatusBadge tone="warning">SHADOW ONLY</StatusBadge>
+          <strong>RAVNOVES00 · {item.caseId} · {mode.toUpperCase()}</strong>
+          <small>
+            {selected?.loadedModelName ?? result.selectedCandidate} policy provider
+            {" · "}center crop 600×600
+            {" · "}outside crop UNKNOWN
+          </small>
+        </div>
+      ) : null}
+    >
+      {item ? (
+        <VegetationScene item={item} mode={mode} />
+      ) : (
+        <div className="m48-atlas-visual__state" role="alert">
+          <Icon name="alert" size={18} />
+          RAVNOVES vegetation shadow каталог пуст.
+        </div>
+      )}
+    </LaboratoryEvidenceViewer>
+  );
+}
+
+export function VegetationValidationVisual({ result }: { result: VegetationShadowResult }) {
+  const [index, setIndex] = useState(0);
+  const [mode, setMode] = useState<VegetationValidationMode>("truth");
+  const [expanded, setExpanded] = useState(false);
+  const item = result.validationCases[index] ?? null;
+  return (
+    <LaboratoryEvidenceViewer
+      label="GOOSE validation vegetation comparison"
+      className="m48-atlas-visual"
+      mode={mode}
+      modes={VALIDATION_MODES}
+      expanded={expanded}
+      onModeChange={setMode}
+      onExpandedChange={setExpanded}
+      actions={(
+        <>
+          <IconButton
+            label="Предыдущий GOOSE validation кадр"
+            disabled={!result.validationCases.length}
+            onClick={() => setIndex((current) => (
+              current - 1 + result.validationCases.length
+            ) % result.validationCases.length)}
+          >
+            <Icon name="chevron-left" size={16} />
+          </IconButton>
+          <IconButton
+            label="Следующий GOOSE validation кадр"
+            disabled={!result.validationCases.length}
+            onClick={() => setIndex((current) => (current + 1) % result.validationCases.length)}
+          >
+            <Icon name="chevron-right" size={16} />
+          </IconButton>
+        </>
+      )}
+      overlay={item ? (
+        <div className="m48-atlas-visual__case">
+          <StatusBadge tone="accent">GOOSE VALIDATION</StatusBadge>
+          <strong>{item.caseId} · {mode.toUpperCase()}</strong>
+          <small>official fine-64 labels · fixed 512×512 preprocessing · visual sample</small>
+        </div>
+      ) : null}
+    >
+      {item ? (
+        <VegetationScene item={item} mode={mode} />
+      ) : (
+        <div className="m48-atlas-visual__state" role="alert">
+          <Icon name="alert" size={18} />
+          GOOSE validation каталог пуст.
+        </div>
+      )}
+    </LaboratoryEvidenceViewer>
+  );
+}
@@ -63,6 +63,13 @@ interface KnownWorkDefinition {
 const rig = (rigLabel: string): string => rigLabel.trim() || "Сенсорный риг";

 const KNOWN_WORKS: Readonly<Record<Exclude<LaboratoryWorkId, `session:${string}`>, KnownWorkDefinition>> = {
+  "lab-v1-vegetation-shadow": {
+    profileId: "rig-ravnoves-perception-gate-v1",
+    profileName: (rigLabel) => `${rig(rigLabel)} RIGHT · RAVNOVES00 vegetation shadow`,
+    experimentId: "lab-v1-vegetation-mission-policy",
+    experimentName: "GOOSE ready weights → RAVNOVES vegetation policy",
+    variantName: "LAB V1 · DDRNet vs PPLiteSeg · urban/rural/off-road presets",
+  },
  "m48-object-centric-quality": {
    profileId: "rig-dual-evidence-virtual-corridor-v1",
    profileName: (rigLabel) => `${rig(rigLabel)} RIGHT · Camera + prediction-free spatial evidence`,
@@ -18,6 +18,7 @@ function mergeResults(
  next: AdvancedLaboratoryResults,
 ): AdvancedLaboratoryResults {
  return {
+    vegetationShadow: next.vegetationShadow ?? current.vegetationShadow,
    m47Graph: next.m47Graph ?? current.m47Graph,
    m48: next.m48 ?? current.m48,
    m48SmallStatic: next.m48SmallStatic ?? current.m48SmallStatic,
@@ -121,6 +122,7 @@ export function useAdvancedLaboratoryCatalog({
    const indexedResultId = index.find((item) => item.workId === selectedWorkId)?.resultId;
    if (
      [
+        "lab-v1-vegetation-shadow",
        "m47-reference-graph-shadow",
        "m48-object-centric-quality",
        "m48-small-static-passage-regression",