feat(control-station): review native raw fisheye risk cases

This commit is contained in:
DCCONSTRUCTIONS
2026-08-26 10:15:56 +03:00
parent f9a76fed0e
commit 932c5216dc
8 changed files with 694 additions and 18 deletions
@@ -136,7 +136,7 @@ const RESULT_PREFIX: Readonly<Record<AdvancedLaboratoryWorkId, string>> = {
"m48-object-centric-quality": "m48-object-quality-(?:pack|result)",
"m48-small-static-passage-regression": "m48-small-static-passage-regression",
"m48s-fixed-class-detector": "m48s-fixed-class-detector-lab",
"m48t-risk-quality-temporal": "m48t-risk-quality-temporal-lab",
"m48t-risk-quality-temporal": "(?:m48t-risk-quality-temporal-lab|m48q-native-risk-quality-lab)",
"m47-reference-graph-shadow": "m47-reference-graph-lab",
"m4-replay-threat": "m4-threat-replay",
"l3-pointpillars-visual-audit": "l3-pointpillars-visual-audit",
@@ -19,7 +19,8 @@ export interface M48TReviewCase {
sha256: string;
}
export interface M48TRiskQualityResult {
export interface M48TLegacyRiskQualityResult {
variant: "legacy-coco-quality";
resultId: string;
createdAtUtc: string;
source: {
@@ -93,6 +94,90 @@ export interface M48TRiskQualityResult {
limitations: readonly string[];
}
export type M48QRiskFamily = "person" | "animal" | "light-road-user" | "vehicle";
export interface M48QNativeProposal {
proposalId: string;
className: string;
riskFamily: M48QRiskFamily;
score: number;
boxXyxy: readonly [number, number, number, number];
}
export interface M48QNativeReviewCase {
caseId: string;
sequence: number;
frameId: string;
evidenceTimeNs: number;
imageUrl: string;
width: 800;
height: 600;
byteLength: number;
sha256: string;
selectionBuckets: readonly string[];
nativeDetectionCount: number;
legacyDetectionCount: number;
matchedDetectionCount: number;
proposals: readonly M48QNativeProposal[];
}
export interface M48QNativeRiskQualityResult {
variant: "native-risk-review";
resultId: string;
createdAtUtc: string;
source: {
sourceId: "RAVNOVES00";
frameCount: 4489;
width: 800;
height: 600;
geometricResampling: false;
};
candidate: {
providerId: string;
modelId: "rf_detr_large_native_kb4:1";
preprocessId: "raw-kb4-uint8-fused-mask-rgb-pad8-imagenet-trt/v0";
minimumScore: 0.25;
};
execution: {
effectiveWorldStateFps: number;
worldStateCompletionP95Ms: number;
detectorTotalP95Ms: number;
gpuUtilizationP95Percent: number;
gpuMemoryMaximumMib: number;
additionalInferencePasses: 0;
};
selection: {
caseCount: 24;
minimumSequenceSeparation: number;
bucketCoverage: Readonly<Record<string, number>>;
classCounts: Readonly<Record<string, number>>;
};
runtime: {
deliveryRatio: number;
integratedGatePassed: true;
operatingTargetGatePassed: true;
};
parity: {
precision: number;
recall: number;
meanIou: number;
};
acceptance: {
reviewReady: true;
independentQualityEvaluated: false;
semanticCandidateAccepted: false;
};
review: {
cases: readonly M48QNativeReviewCase[];
};
method: M48TLaboratoryMethod;
limitations: readonly string[];
}
export type M48TRiskQualityResult =
| M48TLegacyRiskQualityResult
| M48QNativeRiskQualityResult;
type LaboratoryFetch = (input: RequestInfo | URL, init?: RequestInit) => Promise<Response>;
export class M48TContractError extends Error {}
@@ -173,9 +258,10 @@ function method(value: unknown): M48TLaboratoryMethod {
};
}
function parseResult(value: unknown, expectedResultId: string): M48TRiskQualityResult {
function parseLegacyResult(value: unknown, expectedResultId: string): M48TLegacyRiskQualityResult {
const raw = object(value, "M4.8T result");
exact(raw.schema_version, "missioncore.m48t-risk-quality-temporal-view/v1", "M4.8T schema");
exact(raw.variant, "legacy-coco-quality", "M4.8T variant");
exact(raw.result_id, expectedResultId, "M4.8T identity");
exact(raw.status, "complete-quality-gate-failed-temporal-invariant-passed", "M4.8T status");
exact(raw.access, "read-only", "M4.8T access");
@@ -234,6 +320,7 @@ function parseResult(value: unknown, expectedResultId: string): M48TRiskQualityR
for (const [key, count] of Object.entries(failures)) parsedFailures[key] = integer(count, `M4.8T failure ${key}`);
const temporalConfiguration = object(configuration.temporal, "M4.8T temporal configuration");
return {
variant: "legacy-coco-quality",
resultId: expectedResultId,
createdAtUtc: text(raw.created_at_utc, "M4.8T created at"),
source: {
@@ -306,6 +393,207 @@ function parseResult(value: unknown, expectedResultId: string): M48TRiskQualityR
};
}
function numberRecord(value: unknown, label: string): Readonly<Record<string, number>> {
const raw = object(value, label);
const parsed: Record<string, number> = {};
for (const [key, item] of Object.entries(raw)) parsed[key] = integer(item, `${label}.${key}`);
return parsed;
}
function nativeRiskFamily(value: unknown): M48QRiskFamily {
const parsed = text(value, "M4.8Q risk family");
if (!["person", "animal", "light-road-user", "vehicle"].includes(parsed)) {
throw new M48TContractError("M4.8Q risk family: неизвестное значение.");
}
return parsed as M48QRiskFamily;
}
function nativeProposal(value: unknown): M48QNativeProposal {
const raw = object(value, "M4.8Q proposal");
const coordinates = array(raw.box_xyxy, "M4.8Q proposal box").map((item) =>
number(item, "M4.8Q proposal coordinate")
);
if (
coordinates.length !== 4
|| coordinates[0] >= coordinates[2]
|| coordinates[1] >= coordinates[3]
|| coordinates[2] > 800
|| coordinates[3] > 600
) {
throw new M48TContractError("M4.8Q proposal box: нарушена raw-raster геометрия.");
}
const score = number(raw.score, "M4.8Q proposal score");
if (score < 0.25 || score > 1) throw new M48TContractError("M4.8Q proposal score: нарушен threshold.");
return {
proposalId: text(raw.proposal_id, "M4.8Q proposal id"),
className: text(raw.class_name, "M4.8Q proposal class"),
riskFamily: nativeRiskFamily(raw.risk_family),
score,
boxXyxy: coordinates as [number, number, number, number],
};
}
function parseNativeResult(value: unknown, expectedResultId: string): M48QNativeRiskQualityResult {
const raw = object(value, "M4.8Q result");
exact(raw.schema_version, "missioncore.m48q-native-risk-quality-view/v1", "M4.8Q schema");
exact(raw.variant, "native-risk-review", "M4.8Q variant");
exact(raw.result_id, expectedResultId, "M4.8Q identity");
exact(raw.status, "complete-review-ready-quality-not-adjudicated", "M4.8Q status");
exact(raw.access, "read-only", "M4.8Q access");
exact(raw.ground_truth, false, "M4.8Q ground truth");
const source = object(raw.source, "M4.8Q source");
exact(source.source_id, "RAVNOVES00", "M4.8Q source id");
exact(source.frame_count, 4489, "M4.8Q source frames");
exact(source.raster_width, 800, "M4.8Q source width");
exact(source.raster_height, 600, "M4.8Q source height");
exact(source.geometric_resampling, false, "M4.8Q source resampling");
exact(source.rectification, false, "M4.8Q source rectification");
exact(source.warp, false, "M4.8Q source warp");
const configuration = object(raw.configuration, "M4.8Q configuration");
const candidate = object(configuration.candidate, "M4.8Q candidate");
const execution = object(raw.execution, "M4.8Q execution");
const metrics = object(raw.metrics, "M4.8Q metrics");
const selection = object(metrics.selection, "M4.8Q selection");
const runtime = object(metrics.runtime, "M4.8Q runtime");
const parity = object(metrics.native_tensor_parity, "M4.8Q parity");
const acceptance = object(raw.acceptance, "M4.8Q acceptance");
exact(acceptance.review_ready, true, "M4.8Q review readiness");
exact(acceptance.integrated_runtime_gate_passed, true, "M4.8Q runtime gate");
exact(acceptance.independent_quality_evaluated, false, "M4.8Q quality state");
exact(acceptance.semantic_candidate_accepted, false, "M4.8Q candidate state");
exact(selection.case_count, 24, "M4.8Q selected cases");
const review = object(raw.review, "M4.8Q review");
const raster = object(review.source_raster, "M4.8Q review raster");
exact(raster.width, 800, "M4.8Q review width");
exact(raster.height, 600, "M4.8Q review height");
const overlay = object(review.overlay, "M4.8Q overlay");
exact(overlay.client_rendered, true, "M4.8Q client overlay");
exact(overlay.toggleable, true, "M4.8Q overlay toggle");
const cases = array(review.cases, "M4.8Q review cases").map((value) => {
const item = object(value, "M4.8Q review case");
const caseId = text(item.case_id, "M4.8Q case id");
if (!/^[0-9]{6}$/.test(caseId)) throw new M48TContractError("M4.8Q case identity нарушена.");
const sequence = integer(item.sequence, "M4.8Q case sequence");
exact(caseId, sequence.toString().padStart(6, "0"), "M4.8Q case/sequence identity");
exact(item.frame_id, `frame-${caseId}`, "M4.8Q frame identity");
exact(item.media_type, "image/jpeg", "M4.8Q case media");
exact(item.width, 800, "M4.8Q case width");
exact(item.height, 600, "M4.8Q case height");
exact(item.geometric_resampling, false, "M4.8Q case resampling");
const comparison = object(item.comparison, "M4.8Q comparison");
const proposals = array(item.proposals, "M4.8Q proposals").map(nativeProposal);
if (!proposals.length) throw new M48TContractError("M4.8Q proposals: пустой review case.");
return {
caseId,
sequence,
frameId: `frame-${caseId}`,
evidenceTimeNs: integer(item.evidence_time_ns, "M4.8Q evidence time"),
imageUrl: text(item.image_url, "M4.8Q image URL"),
width: 800 as const,
height: 600 as const,
byteLength: integer(item.byte_length, "M4.8Q image bytes"),
sha256: sha(item.sha256, "M4.8Q image SHA"),
selectionBuckets: array(item.selection_buckets, "M4.8Q selection buckets").map((bucket) =>
text(bucket, "M4.8Q selection bucket")
),
nativeDetectionCount: integer(comparison.native_detection_count, "M4.8Q native count"),
legacyDetectionCount: integer(comparison.legacy_704_detection_count, "M4.8Q legacy count"),
matchedDetectionCount: integer(
comparison.matched_detection_count_iou_at_least_0_5,
"M4.8Q matched count",
),
proposals,
};
});
if (cases.length !== 24 || new Set(cases.map(({ caseId }) => caseId)).size !== 24) {
throw new M48TContractError("M4.8Q review catalog: нарушен размер.");
}
return {
variant: "native-risk-review",
resultId: expectedResultId,
createdAtUtc: text(raw.created_at_utc, "M4.8Q created at"),
source: {
sourceId: "RAVNOVES00",
frameCount: 4489,
width: 800,
height: 600,
geometricResampling: false,
},
candidate: {
providerId: text(candidate.provider_id, "M4.8Q provider"),
modelId: exact(candidate.model_id, "rf_detr_large_native_kb4:1", "M4.8Q model"),
preprocessId: exact(
candidate.preprocess_id,
"raw-kb4-uint8-fused-mask-rgb-pad8-imagenet-trt/v0",
"M4.8Q preprocess",
),
minimumScore: exact(candidate.minimum_score, 0.25, "M4.8Q threshold"),
},
execution: {
effectiveWorldStateFps: number(execution.effective_world_state_fps, "M4.8Q FPS"),
worldStateCompletionP95Ms: number(
execution.world_state_completion_p95_ms,
"M4.8Q world-state p95",
),
detectorTotalP95Ms: number(execution.detector_total_p95_ms, "M4.8Q detector p95"),
gpuUtilizationP95Percent: number(
execution.gpu_utilization_p95_percent,
"M4.8Q GPU p95",
),
gpuMemoryMaximumMib: number(
execution.gpu_memory_used_maximum_mib,
"M4.8Q VRAM maximum",
),
additionalInferencePasses: exact(
execution.additional_inference_passes,
0,
"M4.8Q inference passes",
),
},
selection: {
caseCount: 24,
minimumSequenceSeparation: integer(
selection.minimum_sequence_separation,
"M4.8Q case separation",
),
bucketCoverage: numberRecord(selection.selected_bucket_coverage, "M4.8Q bucket coverage"),
classCounts: numberRecord(selection.selected_class_counts, "M4.8Q class counts"),
},
runtime: {
deliveryRatio: number(runtime.delivery_ratio, "M4.8Q delivery ratio"),
integratedGatePassed: exact(
runtime.integrated_runtime_gate_passed,
true,
"M4.8Q integrated gate",
),
operatingTargetGatePassed: exact(
runtime.operating_target_gate_passed,
true,
"M4.8Q target gate",
),
},
parity: {
precision: number(parity.risk_detection_precision, "M4.8Q parity precision"),
recall: number(parity.risk_detection_recall, "M4.8Q parity recall"),
meanIou: number(parity.matched_mean_iou, "M4.8Q parity IoU"),
},
acceptance: {
reviewReady: true,
independentQualityEvaluated: false,
semanticCandidateAccepted: false,
},
review: { cases },
method: method(raw.method),
limitations: array(raw.limitations, "M4.8Q limitations").map((item) =>
text(item, "M4.8Q limitation")
),
};
}
export async function fetchM48TRiskQualityResult(
resultId: string,
{
@@ -313,7 +601,7 @@ export async function fetchM48TRiskQualityResult(
signal,
}: { fetcher?: LaboratoryFetch; signal?: AbortSignal } = {},
): Promise<M48TRiskQualityResult> {
if (!/^m48t-risk-quality-temporal-lab-[a-f0-9]{64}$/.test(resultId)) {
if (!/^(?:m48t-risk-quality-temporal-lab|m48q-native-risk-quality-lab)-[a-f0-9]{64}$/.test(resultId)) {
throw new M48TContractError("M4.8T result identity недопустима.");
}
const response = await fetcher(`/api/v1/laboratory/m48t/risk-quality/results/${resultId}`, {
@@ -322,5 +610,9 @@ export async function fetchM48TRiskQualityResult(
signal,
});
if (!response.ok) throw new M48TContractError(`M4.8T недоступен: HTTP ${response.status}.`);
return parseResult(await response.json(), resultId);
const payload: unknown = await response.json();
const raw = object(payload, "M4.8T/M4.8Q result");
return raw.schema_version === "missioncore.m48q-native-risk-quality-view/v1"
? parseNativeResult(payload, resultId)
: parseLegacyResult(payload, resultId);
}
@@ -4,7 +4,11 @@ import {
LaboratorySummary,
LaboratoryWorkTemplate,
} from "../../components/laboratory/LaboratoryPresentation";
import type { M48TRiskQualityResult } from "../../core/laboratory/m48tRiskQuality";
import type {
M48QNativeRiskQualityResult,
M48TLegacyRiskQualityResult,
M48TRiskQualityResult,
} from "../../core/laboratory/m48tRiskQuality";
import { M48TRiskQualityVisual } from "./M48TRiskQualityVisual";
function percent(value: number, digits = 1): string {
@@ -21,6 +25,19 @@ export function M48TRiskQualityResultView({
}: {
rigLabel: string;
result: M48TRiskQualityResult;
}) {
if (result.variant === "native-risk-review") {
return <M48QNativeRiskQualityResultView rigLabel={rigLabel} result={result} />;
}
return <M48TLegacyRiskQualityResultView rigLabel={rigLabel} result={result} />;
}
function M48TLegacyRiskQualityResultView({
rigLabel,
result,
}: {
rigLabel: string;
result: M48TLegacyRiskQualityResult;
}) {
return (
<LaboratoryWorkTemplate
@@ -77,3 +94,69 @@ export function M48TRiskQualityResultView({
/>
);
}
function M48QNativeRiskQualityResultView({
rigLabel,
result,
}: {
rigLabel: string;
result: M48QNativeRiskQualityResult;
}) {
const classes = Object.entries(result.selection.classCounts)
.map(([name, count]) => `${name} ${count}`)
.join(" · ");
return (
<LaboratoryWorkTemplate
summary={(
<LaboratorySummary
title="M4.8Q · native raw-fisheye risk review"
description="Нативный RF-DETR прогнан внутри полного reference graph прямо на исходном KB4 raster 800×600: без rectification, warp, resize и обратного преобразования. Из immutable frame ledger детерминированно отобраны реальные risk-кейсы для операторской проверки в существующем M4.8 image-case instrument."
status="Runtime принят · 24 native cases готовы · quality ещё не adjudicated"
statusTone="success"
facts={[
{ label: "Source", value: `${rigLabel} · ${result.source.frameCount.toLocaleString("ru-RU")} raw frames · 800×600` },
{ label: "Candidate", value: `${result.candidate.modelId} · score ≥ ${decimal(result.candidate.minimumScore, 2)}` },
{ label: "Image path", value: "RAW KB4 → fused GPU graph · geometric resampling NO" },
{ label: "Authority", value: "SHADOW ONLY · independent quality NO · production NO" },
]}
brief={{
question: "Работает ли нативная risk-классификация на нашей исходной fisheye-картинке в realtime envelope, и какие реальные кадры надо проверить человеком?",
approach: `Полный ${result.source.frameCount.toLocaleString("ru-RU")}-кадровый native graph оставлен неизменным. Повторной инференс-сессии для лабы нет: 24 кадра выбраны из его hash-bound ledger по person, animal, light-road-user, vehicle, low-confidence, fisheye-edge и расхождениям с диагностической legacy 704 веткой.`,
principalResult: `${decimal(result.execution.effectiveWorldStateFps, 3)} FPS при detector p95 ${decimal(result.execution.detectorTotalP95Ms, 2)} ms и world-state p95 ${decimal(result.execution.worldStateCompletionP95Ms, 2)} ms. В review pack реально попали ${classes}.`,
limitation: "Это диагностическая выборка маршрута без независимой разметки. Наличие бокса и класса можно осмотреть, но precision/recall и корректность каждого класса этой фазой ещё не доказаны.",
}}
method={result.method}
/>
)}
evidence={(
<LaboratoryEvidence
eyebrow="M4.8Q VISUAL EVIDENCE · NATIVE RAW KB4"
title="24 исходных fisheye-кадра с отключаемым client-side overlay"
kind="diagnostic-model"
resizable
>
<M48TRiskQualityVisual result={result} />
</LaboratoryEvidence>
)}
result={(
<LaboratoryResultSummary
title="Native runtime закрыт; следующий честный шаг — adjudication этих кейсов"
status="Review-ready · quality-not-adjudicated"
statusTone="success"
metrics={[
{ label: "Full graph", value: `${decimal(result.execution.effectiveWorldStateFps, 3)} FPS`, hint: `delivery ${percent(result.runtime.deliveryRatio, 2)} · 4 489/4 489` },
{ label: "Detector / world-state p95", value: `${decimal(result.execution.detectorTotalP95Ms, 2)} / ${decimal(result.execution.worldStateCompletionP95Ms, 2)} ms`, hint: "один native pass · additional inference 0" },
{ label: "GPU / VRAM peak", value: `${decimal(result.execution.gpuUtilizationP95Percent, 1)}% / ${decimal(result.execution.gpuMemoryMaximumMib / 1024, 2)} GiB`, hint: "Worker 006 · RTX 4090 envelope" },
{ label: "Native parity", value: `${percent(result.parity.precision, 2)} / ${percent(result.parity.recall, 2)}`, hint: `precision / recall · mean IoU ${percent(result.parity.meanIou, 2)}` },
{ label: "Review pack", value: `${result.selection.caseCount}/24 cases`, hint: "8 diagnostic buckets · raw 800×600" },
]}
conclusion={{
proved: `Полный reference graph доставил все ${result.source.frameCount.toLocaleString("ru-RU")} world states на ${decimal(result.execution.effectiveWorldStateFps, 3)} FPS. Детектор использовал ровно один native 800×600 KB4 pass без геометрического resampling. Hash-bound review содержит person, dog, bicycle, skateboard, car и truck; боксы рисуются поверх чистого кадра и отключаются кнопкой.`,
notProved: "Не доказаны route-domain precision/recall, истинность 24 классов и боксов, child/adult, поведение объектов, физическая track identity и безопасность навигации. Legacy 704 count delta остаётся только диагностикой, потому что старая ветка растягивала 4:3 raster.",
decision: "Не добавлять второй detector и не менять realtime graph. Использовать эти 24 кейса как вход существующего M4.8 review/correction workflow; только после независимой adjudication считать route-domain semantic quality.",
}}
/>
)}
/>
);
}
@@ -1,18 +1,35 @@
import { useState } from "react";
import { useMemo, useState } from "react";
import { Icon, IconButton } from "@nodedc/ui-react";
import { LaboratoryEvidenceViewer } from "../../components/laboratory/LaboratoryEvidenceViewer";
import type { M48TRiskQualityResult } from "../../core/laboratory/m48tRiskQuality";
import { RecordedEvidenceImageScene } from "../../components/laboratory/RecordedEvidenceImageScene";
import type {
RecordedEvidenceBox,
RecordedEvidenceBoxTone,
} from "../../components/laboratory/RecordedEvidenceBoxOverlay";
import type {
M48QNativeRiskQualityResult,
M48QRiskFamily,
M48TLegacyRiskQualityResult,
M48TRiskQualityResult,
} from "../../core/laboratory/m48tRiskQuality";
export function M48TRiskQualityVisual({ result }: { result: M48TRiskQualityResult }) {
function navigateIndex(current: number, offset: -1 | 1, length: number): number {
return (current + offset + length) % length;
}
function familyTone(family: M48QRiskFamily): RecordedEvidenceBoxTone {
if (family === "person" || family === "animal") return "danger";
if (family === "light-road-user") return "warning";
return "accent";
}
function LegacyVisual({ result }: { result: M48TLegacyRiskQualityResult }) {
const [index, setIndex] = useState(0);
const [expanded, setExpanded] = useState(false);
const item = result.review.cases[index] ?? null;
const navigate = (offset: -1 | 1) => {
setIndex((current) => (
current + offset + result.review.cases.length
) % result.review.cases.length);
};
const navigate = (offset: -1 | 1) =>
setIndex((current) => navigateIndex(current, offset, result.review.cases.length));
return (
<div className="l3-visual-audit">
@@ -61,3 +78,85 @@ export function M48TRiskQualityVisual({ result }: { result: M48TRiskQualityResul
</div>
);
}
function NativeVisual({ result }: { result: M48QNativeRiskQualityResult }) {
const [index, setIndex] = useState(0);
const [expanded, setExpanded] = useState(false);
const [boxesVisible, setBoxesVisible] = useState(true);
const item = result.review.cases[index] ?? null;
const boxes = useMemo<readonly RecordedEvidenceBox[]>(() => {
if (!item || !boxesVisible) return [];
return item.proposals.map((proposal) => ({
boxXyxy: proposal.boxXyxy,
label: `${proposal.className} · ${proposal.score.toFixed(2)}`,
tone: familyTone(proposal.riskFamily),
}));
}, [boxesVisible, item]);
const navigate = (offset: -1 | 1) =>
setIndex((current) => navigateIndex(current, offset, result.review.cases.length));
return (
<div className="l3-visual-audit">
<LaboratoryEvidenceViewer
label="M4.8Q native raw-fisheye risk review"
mode="native"
modes={[{ value: "native", label: "NATIVE RF-DETR" }]}
expanded={expanded}
onModeChange={() => undefined}
onExpandedChange={setExpanded}
actions={(
<div className="l3-visual-audit__pagination">
<IconButton label="Предыдущий M4.8Q review case" onClick={() => navigate(-1)}>
<Icon name="chevron-left" size={16} />
</IconButton>
<IconButton label="Следующий M4.8Q review case" onClick={() => navigate(1)}>
<Icon name="chevron-right" size={16} />
</IconButton>
</div>
)}
trailingActions={(
<IconButton
label={boxesVisible ? "Скрыть native RF-DETR боксы" : "Показать native RF-DETR боксы"}
onClick={() => setBoxesVisible((visible) => !visible)}
>
<Icon name={boxesVisible ? "eye-off" : "eye"} size={16} />
</IconButton>
)}
overlay={item ? (
<div className="l3-visual-audit__overlay">
<div>
<span>RAVNOVES00 · raw KB4 800×600 · resampling NO</span>
<strong>
case {index + 1}/{result.review.cases.length} · frame {item.sequence} · {item.proposals.length} native boxes
</strong>
<small>
{item.selectionBuckets.join(" · ")} · native/legacy {item.nativeDetectionCount}/{item.legacyDetectionCount} (diagnostic only)
</small>
</div>
</div>
) : null}
>
{item ? (
<RecordedEvidenceImageScene
src={item.imageUrl}
imageWidth={item.width}
imageHeight={item.height}
boxes={boxes}
ariaLabel={`M4.8Q frame ${item.sequence}: ${boxes.length} visible native risk boxes`}
/>
) : (
<div className="l3-visual-audit__state" role="alert">
<Icon name="alert" size={18} />
M4.8Q native visual evidence недоступно.
</div>
)}
</LaboratoryEvidenceViewer>
</div>
);
}
export function M48TRiskQualityVisual({ result }: { result: M48TRiskQualityResult }) {
return result.variant === "native-risk-review"
? <NativeVisual result={result} />
: <LegacyVisual result={result} />;
}
@@ -86,10 +86,10 @@ const KNOWN_WORKS: Readonly<Record<Exclude<LaboratoryWorkId, `session:${string}`
},
"m48t-risk-quality-temporal": {
profileId: "rig-ravnoves-perception-gate-v1",
profileName: (rigLabel) => `${rig(rigLabel)} RIGHT · COCO quality + bounded temporal identity`,
profileName: (rigLabel) => `${rig(rigLabel)} RIGHT · Native raw-fisheye perception gate`,
experimentId: "m48t-risk-quality-temporal",
experimentName: "RF-DETR independent semantic quality and temporal identity",
variantName: "M4.8T · COCO val2017 truth + RAVNOVES00 temporal shadow",
experimentName: "RF-DETR native risk review and temporal identity",
variantName: "M4.8Q · native raw KB4 review · quality not adjudicated",
},
"m47-reference-graph-shadow": {
profileId: "rig-dual-evidence-virtual-corridor-v1",
@@ -0,0 +1,172 @@
import assert from "node:assert/strict";
import { after, before, test } from "node:test";
import { readFile } from "node:fs/promises";
import { createServer } from "vite";
let server;
let fetchM48TRiskQualityResult;
const resultId = `m48q-native-risk-quality-lab-${"a".repeat(64)}`;
before(async () => {
server = await createServer({
appType: "custom",
logLevel: "silent",
server: { middlewareMode: true },
});
({ fetchM48TRiskQualityResult } = await server.ssrLoadModule(
"/src/core/laboratory/m48tRiskQuality.ts",
));
});
after(async () => server?.close());
function response(value) {
return { ok: true, status: 200, json: async () => value };
}
function payload() {
return {
schema_version: "missioncore.m48q-native-risk-quality-view/v1",
variant: "native-risk-review",
result_id: resultId,
created_at_utc: "2026-08-26T10:00:00Z",
status: "complete-review-ready-quality-not-adjudicated",
access: "read-only",
ground_truth: false,
source: {
source_id: "RAVNOVES00",
frame_count: 4489,
raster_width: 800,
raster_height: 600,
geometric_resampling: false,
rectification: false,
warp: false,
},
configuration: {
candidate: {
provider_id: "triton-rf-detr-large-coco-native-kb4-risk-fp16-shadow/v0",
model_id: "rf_detr_large_native_kb4:1",
preprocess_id: "raw-kb4-uint8-fused-mask-rgb-pad8-imagenet-trt/v0",
minimum_score: 0.25,
},
},
method: {
schema_version: "missioncore.laboratory-method/v1",
completeness: "complete",
execution_class: "hybrid",
pipeline_id: "m48q-native-raw-fisheye-risk-case-review/v1",
components: [{
kind: "model",
name: "RF-DETR-L native KB4 TensorRT",
version: "rf_detr_large_native_kb4:1",
role: "risk proposals",
identity_sha256: "b".repeat(64),
}],
},
execution: {
effective_world_state_fps: 11.84338,
world_state_completion_p95_ms: 47.940779,
detector_total_p95_ms: 21.19895,
gpu_utilization_p95_percent: 53,
gpu_memory_used_maximum_mib: 9718,
additional_inference_passes: 0,
},
metrics: {
selection: {
case_count: 24,
minimum_sequence_separation: 12,
selected_bucket_coverage: { person: 22, animal: 3 },
selected_class_counts: { person: 44, dog: 3 },
},
runtime: {
delivery_ratio: 1,
integrated_runtime_gate_passed: true,
operating_target_gate_passed: true,
},
native_tensor_parity: {
risk_detection_precision: 0.9887,
risk_detection_recall: 0.9831,
matched_mean_iou: 0.9882,
},
},
acceptance: {
review_ready: true,
integrated_runtime_gate_passed: true,
independent_quality_evaluated: false,
semantic_candidate_accepted: false,
},
review: {
source_raster: { width: 800, height: 600 },
overlay: { client_rendered: true, toggleable: true },
cases: Array.from({ length: 24 }, (_, index) => {
const caseId = String(index * 20 + 12).padStart(6, "0");
return {
case_id: caseId,
sequence: Number(caseId),
frame_id: `frame-${caseId}`,
evidence_time_ns: 35_000_000_000 + index * 1_000_000,
image_url: `/review/${caseId}.jpg`,
media_type: "image/jpeg",
width: 800,
height: 600,
byte_length: 1000 + index,
sha256: String(index.toString(16)).padStart(64, "0"),
geometric_resampling: false,
selection_buckets: [index % 2 ? "person" : "animal"],
comparison: {
native_detection_count: 1,
legacy_704_detection_count: 1,
matched_detection_count_iou_at_least_0_5: 1,
},
proposals: [{
proposal_id: `proposal-${index}-0`,
class_name: index % 2 ? "person" : "dog",
risk_family: index % 2 ? "person" : "animal",
score: 0.75,
box_xyxy: [10, 20, 100, 200],
}],
};
}),
},
limitations: ["No independent route truth."],
};
}
test("M4.8Q parser accepts only the native 800x600 no-resampling review contract", async () => {
const result = await fetchM48TRiskQualityResult(resultId, {
fetcher: async () => response(payload()),
});
assert.equal(result.variant, "native-risk-review");
assert.equal(result.review.cases.length, 24);
assert.equal(result.review.cases[0].width, 800);
assert.equal(result.review.cases[0].proposals[0].className, "dog");
assert.equal(result.execution.additionalInferencePasses, 0);
assert.equal(result.acceptance.independentQualityEvaluated, false);
});
test("M4.8Q parser fails closed if raw-fisheye geometry is resampled", async () => {
const invalid = payload();
invalid.source.geometric_resampling = true;
await assert.rejects(
fetchM48TRiskQualityResult(resultId, {
fetcher: async () => response(invalid),
}),
/source resampling/,
);
});
test("M4.8Q reuses the canonical image scene and viewer overlay toggle", async () => {
const source = await readFile(
new URL("../src/workspaces/laboratory/M48TRiskQualityVisual.tsx", import.meta.url),
"utf8",
);
assert.match(source, /<LaboratoryEvidenceViewer/);
assert.match(source, /<RecordedEvidenceImageScene/);
assert.match(source, /name=\{boxesVisible \? "eye-off" : "eye"\}/);
assert.match(source, /raw KB4 800×600 · resampling NO/);
assert.doesNotMatch(source, /<canvas/);
});