jim800121chen
5c1c37d151
detection 畫框、classification 改在影像右上角疊標籤（不畫框）， 並在推論面板提供即時切換解析方式與上傳 label 檔。 - 新增 InferenceOverlay 依 taskType 分派；ClassificationOverlay 用 DOM 而非 canvas，讓 CJK 排版與 aria-live 交給瀏覽器處理 - 標籤防閃爍：挑戰者需連續 3 幀居冠才切換，或信心度領先 15% 直接切； 低於門檻立即清空（顯示過期標籤比空白更糟） - 身分比對優先用 classIndex，避免換 label 檔時被誤判為換類別 - 推論設定卡片：即時切 detection/classification、上傳 .txt label、 清除 label，皆不需重燒 - classification-result 原本無條件渲染，導致 detection 模式下側欄 永遠顯示「分類結果」與空圖表，改為依 taskType 切換 - 清掉 camera-overlay 每幀執行的 debug console.log - 補 ResizeObserver stub，原本任何渲染 InferencePanel 的測試都會 在 jsdom 直接拋錯 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
54 lines
1.5 KiB
TypeScript
54 lines
1.5 KiB
TypeScript
'use client';
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import type { InferenceResult } from '@/types/inference';
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import { isClassificationTask } from '@/lib/classification';
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import { CameraOverlay } from './camera-overlay';
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import { ClassificationOverlay } from './classification-overlay';
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interface InferenceOverlayProps {
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result: InferenceResult | null | undefined;
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width: number;
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height: number;
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confidenceThreshold: number;
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}
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/**
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* Dispatches the frame overlay based on the task type reported by the
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* inference result itself.
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*
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* `result.taskType` is preferred over the model metadata because it reflects
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* what the Python post-processor actually did — metadata can disagree with the
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* executed code path.
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*
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* Note the branch is written as "is this classification?" rather than "is this
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* detection?" on purpose: the detection task type string has been inconsistent
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* across the stack (`detection` vs `object_detection`, plan R-4), so detection
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* is the fall-through default and stays correct under either spelling.
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*/
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export function InferenceOverlay({
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result,
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width,
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height,
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confidenceThreshold,
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}: InferenceOverlayProps) {
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if (isClassificationTask(result?.taskType)) {
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return (
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<ClassificationOverlay
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classifications={result?.classifications || []}
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width={width}
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height={height}
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confidenceThreshold={confidenceThreshold}
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/>
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);
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}
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return (
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<CameraOverlay
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detections={result?.detections || []}
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width={width}
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height={height}
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confidenceThreshold={confidenceThreshold}
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/>
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);
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}
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