{"reference_analysis":{"provider":"Amazon Rekognition","checked_at":"2026-10-08","source_access":{"en":"Reviewed official AWS documentation; the JavaScript command is linked from the API reference, but its dynamic page body was not extractable. No cloud calls or account eligibility checks were run.","zh-TW":"已核對 AWS 官方文件；JavaScript 指令由 API 文件連出，但其動態頁正文無法擷取。本輪未呼叫雲端或驗證帳號資格。"},"selection_basis":{"en":"Ten entry points for image and stored-video integrations, not an official ranking. Check the feature-availability reference before planning streaming or bulk analysis.","zh-TW":"依影像與已儲存影片整合選出十項入口，不是官方排名。規劃串流或批次分析前先查閱功能可用性引用。"},"about_url":"https://aws.amazon.com/about-aws/","about":[{"label":{"en":"Provider","zh-TW":"供應商"},"value":{"en":"Amazon Web Services is part of Amazon and launched in 2006.","zh-TW":"Amazon Web Services 隸屬 Amazon，於 2006 年推出。"}},{"label":{"en":"Who it serves","zh-TW":"服務對象"},"value":{"en":"Startups, enterprises, nonprofits and governments using cloud and AI infrastructure.","zh-TW":"使用雲端與 AI 基礎設施的新創、企業、非營利組織與政府。"}},{"label":{"en":"Company context","zh-TW":"公司資訊"},"value":{"en":"The About site covers origins, values, impact, people, customers and partners.","zh-TW":"About 網站提供起源、價值、影響、團隊、客戶與合作夥伴資訊。"}},{"label":{"en":"Product scope","zh-TW":"產品範圍"},"value":{"en":"Rekognition supplies managed image and video analysis; API-specific capabilities are compared below.","zh-TW":"Rekognition 提供託管影像與視訊分析；各 API 能力於下方逐项比較。"}}],"items":[{"id":"labels","name":"DetectLabels","kind":"Synchronous image API","url":"https://docs.aws.amazon.com/rekognition/latest/APIReference/API_DetectLabels.html","audience":{"en":"Backend / image catalogue team","zh-TW":"後端／影像目錄團隊"},"capability":{"en":"Detect general objects and scenes; optionally request image properties.","zh-TW":"偵測一般物件與場景，可選擇取得影像屬性。"},"io":{"en":"JPEG / PNG bytes or S3 object → labels and model version","zh-TW":"JPEG／PNG 位元組或 S3 物件 → 標籤與模型版本"},"runtime":{"en":"AWS regional cloud endpoint.","zh-TW":"AWS 區域雲端端點。"},"constraint":{"en":"Label confidence is 0–100. General labels do not establish custom defect recognition.","zh-TW":"標籤信心分數為 0–100；一般標籤不能證明能辨識特定缺陷。"},"validation":{"en":"Validate score conversion and empty results; compare labels against your inspection taxonomy.","zh-TW":"驗證分數轉換與空結果，比對實際巡檢分類。"}},{"id":"python","name":"Boto3 Rekognition client","kind":"Python SDK","url":"https://docs.aws.amazon.com/boto3/latest/reference/services/rekognition.html","audience":{"en":"Python / automation developer","zh-TW":"Python／自動化工程師"},"capability":{"en":"Call Rekognition using the AWS Python SDK.","zh-TW":"透過 AWS Python SDK 呼叫 Rekognition。"},"io":{"en":"Python arguments → response dictionaries","zh-TW":"Python 參數 → 回應字典"},"runtime":{"en":"Python backend with AWS credentials and region.","zh-TW":"具備 AWS 憑證與區域設定的 Python 後端。"},"constraint":{"en":"SDK installation does not grant API permissions or configure a region.","zh-TW":"安裝 SDK 不等於取得 API 權限或完成區域設定。"},"validation":{"en":"Record SDK version; test permitted inference and denied credentials separately.","zh-TW":"記錄 SDK 版本，分別測試授權推論與權限拒絕。"}},{"id":"javascript","name":"AWS SDK for JavaScript v3","kind":"JavaScript SDK","url":"https://docs.aws.amazon.com/AWSJavaScriptSDK/v3/latest/client/rekognition/command/DetectLabelsCommand/","audience":{"en":"Node.js / TypeScript backend","zh-TW":"Node.js／TypeScript 後端"},"capability":{"en":"Use the official Rekognition client and DetectLabels command.","zh-TW":"使用官方 Rekognition client 與 DetectLabels 指令。"},"io":{"en":"Command input → service response","zh-TW":"指令輸入 → 服務回應"},"runtime":{"en":"Server-side JavaScript with AWS authentication.","zh-TW":"搭配 AWS 認證的伺服器端 JavaScript。"},"constraint":{"en":"Confirm runtime compatibility and keep credentials out of client-side bundles.","zh-TW":"確認執行環境相容性，憑證不得進入前端程式包。"},"validation":{"en":"Build the actual server target and confirm only sanitized output reaches the browser.","zh-TW":"建置實際伺服器目標，確認瀏覽器只收到去敏後輸出。"}},{"id":"cli","name":"AWS CLI Rekognition","kind":"Command-line interface","url":"https://docs.aws.amazon.com/cli/latest/reference/rekognition/","audience":{"en":"QA / platform engineer","zh-TW":"QA／平台工程師"},"capability":{"en":"Inspect and call Rekognition operations from the terminal.","zh-TW":"從終端檢視並呼叫 Rekognition 操作。"},"io":{"en":"CLI options → JSON output","zh-TW":"CLI 參數 → JSON 輸出"},"runtime":{"en":"Configured AWS CLI environment.","zh-TW":"已設定的 AWS CLI 環境。"},"constraint":{"en":"Image operations through the CLI use S3 references; do not assume SDK byte examples transfer unchanged.","zh-TW":"CLI 影像操作使用 S3 引用，不能原封不動套用 SDK 位元組範例。"},"validation":{"en":"Record profile, region and object version; compare one result with the SDK path.","zh-TW":"記錄 profile、區域與物件版本，比對一次 SDK 結果。"}},{"id":"text","name":"DetectText","kind":"Image text API","url":"https://docs.aws.amazon.com/rekognition/latest/APIReference/API_DetectText.html","audience":{"en":"Packaging / visual metadata developer","zh-TW":"包裝／視覺中繼資料工程師"},"capability":{"en":"Extract words and lines from an image.","zh-TW":"從影像擷取文字與文字行。"},"io":{"en":"Image → text, geometry and type","zh-TW":"影像 → 文字、幾何位置與型態"},"runtime":{"en":"AWS regional cloud service.","zh-TW":"AWS 區域雲端服務。"},"constraint":{"en":"Use the word/line relationship; do not double-count text appearing in both.","zh-TW":"使用字詞與文字行關係，避免同一文字重複計算。"},"validation":{"en":"Check actual packaging fonts, rotation and language; measure exact serial-number accuracy.","zh-TW":"測試實際包裝字型、旋轉與語言，量測序號完全正確率。"}},{"id":"ppe","name":"DetectProtectiveEquipment","kind":"Image equipment API","url":"https://docs.aws.amazon.com/rekognition/latest/APIReference/API_DetectProtectiveEquipment.html","audience":{"en":"Factory application / safety review team","zh-TW":"工廠應用／安全複核團隊"},"capability":{"en":"Detect face, hand and head coverings on people in an image.","zh-TW":"偵測影像中人員的臉部、手部與頭部覆蓋裝備。"},"io":{"en":"Image → person, body-part and equipment detections","zh-TW":"影像 → 人員、身體部位與裝備偵測"},"runtime":{"en":"AWS image analysis endpoint.","zh-TW":"AWS 影像分析端點。"},"constraint":{"en":"Unknown coverage must remain unknown; detection is not a safety certification.","zh-TW":"無法判定的覆蓋狀態需保留未知；偵測結果不是安全認證。"},"validation":{"en":"Test occlusion and low light with human review; measure missed equipment and false alarms.","zh-TW":"搭配人工複核測試遮擋與弱光，量測漏檢與誤報。"}},{"id":"custom","name":"DetectCustomLabels","kind":"Custom-model image API","url":"https://docs.aws.amazon.com/rekognition/latest/APIReference/API_DetectCustomLabels.html","audience":{"en":"ML / industrial inspection team","zh-TW":"ML／工業巡檢團隊"},"capability":{"en":"Run a specific Custom Labels model version against an image.","zh-TW":"對影像執行指定版本的 Custom Labels 模型。"},"io":{"en":"Image + project version ARN → custom labels","zh-TW":"影像＋專案版本 ARN → 自訂標籤"},"runtime":{"en":"Custom Labels model in AWS.","zh-TW":"AWS 上的 Custom Labels 模型。"},"constraint":{"en":"Requires a suitable trained model; generic labels are not a substitute for your defect dataset.","zh-TW":"需要適當的已訓練模型；一般標籤不能取代缺陷資料集。"},"validation":{"en":"Hold out production-like samples; record the version ARN and per-defect recall before rollout.","zh-TW":"保留近似產線的獨立樣本，上線前記錄版本 ARN 與各缺陷召回率。"}},{"id":"stored-video","name":"StartLabelDetection","kind":"Asynchronous stored-video API","url":"https://docs.aws.amazon.com/rekognition/latest/APIReference/API_StartLabelDetection.html","audience":{"en":"Video pipeline / backend engineer","zh-TW":"視訊管線／後端工程師"},"capability":{"en":"Start label analysis of a video stored in S3.","zh-TW":"啟動 S3 已儲存影片的標籤分析。"},"io":{"en":"S3 video → job ID, then completed results","zh-TW":"S3 影片 → 工作 ID，再取得完成結果"},"runtime":{"en":"AWS asynchronous job with optional SNS notification.","zh-TW":"AWS 非同步工作，可使用 SNS 通知。"},"constraint":{"en":"A returned job ID is not a completed analysis; retain idempotency tokens.","zh-TW":"取得工作 ID 不代表分析完成；應保留冪等識別值。"},"validation":{"en":"Test pending, failed and succeeded jobs, then retrieve every result page.","zh-TW":"測試等待、失敗與成功狀態，再取回所有結果分頁。"}},{"id":"segments","name":"StartSegmentDetection","kind":"Video segmentation API","url":"https://docs.aws.amazon.com/rekognition/latest/APIReference/API_StartSegmentDetection.html","audience":{"en":"Media operations / evidence review","zh-TW":"媒體作業／證據複核團隊"},"capability":{"en":"Start shot or technical-cue analysis of stored video.","zh-TW":"啟動已儲存影片的鏡頭或技術提示分析。"},"io":{"en":"S3 video + segment types → job identifier","zh-TW":"S3 影片＋片段類型 → 工作識別碼"},"runtime":{"en":"AWS asynchronous stored-video analysis.","zh-TW":"AWS 非同步已儲存影片分析。"},"constraint":{"en":"Shot boundaries are media structure, not proof of an industrial event.","zh-TW":"鏡頭邊界是媒體結構，不是工業事件的證據。"},"validation":{"en":"Compare segment timestamps with a manually reviewed clip and preserve original time references.","zh-TW":"與人工複核影片比對片段時間，保留原始時間基準。"}},{"id":"moderation","name":"DetectModerationLabels","kind":"Image moderation API","url":"https://docs.aws.amazon.com/rekognition/latest/APIReference/API_DetectModerationLabels.html","audience":{"en":"Content review / platform team","zh-TW":"內容審核／平台團隊"},"capability":{"en":"Return moderation labels to support an application policy.","zh-TW":"回傳內容審核標籤，支援應用政策判斷。"},"io":{"en":"JPEG / PNG image → moderation labels and confidence","zh-TW":"JPEG／PNG 影像 → 審核標籤與信心分數"},"runtime":{"en":"AWS regional image service.","zh-TW":"AWS 區域影像服務。"},"constraint":{"en":"A model score is not the application decision; preserve a human review route.","zh-TW":"模型分數不等於應用決策；應保留人工複核流程。"},"validation":{"en":"Evaluate false positives on legitimate industrial imagery before blocking uploads.","zh-TW":"阻擋上傳前，先評估正常工業影像的誤判情況。"}}],"supporting_references":[{"id":"overview","name":"Rekognition overview","url":"https://docs.aws.amazon.com/rekognition/latest/dg/what-is.html","audience":{"en":"PM / buyer: map image and video needs to a managed service.","zh-TW":"PM／採購：將影像與視訊需求對應至託管服務。"},"validation":{"en":"Choose a specific API and account region before estimating effort.","zh-TW":"估算投入前先選定 API 與帳號區域。"}},{"id":"availability","name":"Feature availability changes","url":"https://docs.aws.amazon.com/rekognition/latest/dg/rekognition-availability-changes.html","audience":{"en":"Architect / buyer: verify account eligibility.","zh-TW":"架構師／採購：確認帳號可用資格。"},"validation":{"en":"Streaming Video and Bulk Image Analysis closed to new customers on April 30, 2026. AWS says other features are unaffected. This guide selects image and stored-video paths; verify your intended operation.","zh-TW":"Streaming Video 與 Bulk Image Analysis 自 2026-04-30 起不再開放新客戶；AWS 說明其他功能不受影響。本指南選用影像及已儲存影片路徑，仍需確認預定操作。"}},{"id":"video-results","name":"GetLabelDetection","url":"https://docs.aws.amazon.com/rekognition/latest/APIReference/API_GetLabelDetection.html","audience":{"en":"Backend / QA: complete the asynchronous label pipeline.","zh-TW":"後端／QA：完成非同步標籤管線。"},"validation":{"en":"Wait for success, use the same job ID and follow NextToken until no page remains.","zh-TW":"等待成功，使用相同工作 ID，依 NextToken 取得所有分頁。"}},{"id":"credentials","name":"Boto3 credentials","url":"https://docs.aws.amazon.com/boto3/latest/guide/credentials.html","audience":{"en":"Platform engineer: configure temporary role or SSO credentials.","zh-TW":"平台工程師：設定臨時角色或 SSO 憑證。"},"validation":{"en":"Use the standard credential chain; verify least necessary access without embedding secrets.","zh-TW":"使用標準憑證鏈，確認必要最小權限，不將機密寫入程式。"}},{"id":"timeouts","name":"Botocore configuration","url":"https://docs.aws.amazon.com/botocore/latest/reference/config.html","audience":{"en":"Backend engineer: make timeouts and retry behavior explicit.","zh-TW":"後端工程師：明確設定逾時與重試行為。"},"validation":{"en":"The starter uses one attempt with connection/read timeouts; production also needs an overall task deadline.","zh-TW":"範例只嘗試一次，設定連線／讀取逾時；正式使用仍需整體任務截止時間。"}}]},"content_coverage":{"reference_guide":true,"developer_starter":true,"integration_test":"not-run","updated_at":"2026-10-08"},"developer_starter":{"version":"1.0.0","verification":"offline-fixtures-only;live-provider-not-run","filename":"rekognition_smoke.py","code":"\"\"\"One authorized JPEG/PNG sent to AWS DetectLabels; no automatic retry.\"\"\"\nimport json\nimport math\nimport os\nimport sys\nfrom datetime import datetime, timezone\nfrom importlib.metadata import version\nfrom pathlib import Path\nfrom time import monotonic\n\n\ndef normalize(raw):\n    if not isinstance(raw, dict) or not isinstance(raw.get('Labels'), list):\n        raise ValueError('unexpected_schema')\n    output = []\n    for item in raw['Labels']:\n        if not isinstance(item, dict) or not isinstance(item.get('Name'), str):\n            raise ValueError('unexpected_schema')\n        confidence = item.get('Confidence')\n        if type(confidence) not in (int, float) or not math.isfinite(confidence) or not 0 <= confidence <= 100:\n            raise ValueError('unexpected_schema')\n        output.append({'label': item['Name'], 'score': confidence / 100})\n    model = raw.get('LabelModelVersion')\n    if model is not None and not isinstance(model, str):\n        raise ValueError('unexpected_schema')\n    return output, model\n\n\ndef create_client(region):\n    import boto3\n    from botocore.config import Config\n    settings = Config(connect_timeout=5, read_timeout=30,\n                      retries={'mode': 'standard', 'total_max_attempts': 1})\n    # Standard AWS credentials chain; no access keys in source code.\n    return boto3.client('rekognition', region_name=region, config=settings)\n\n\ndef classify_error(exc):\n    code = getattr(exc, 'response', {}).get('Error', {}).get('Code')\n    if code in ('AccessDeniedException', 'UnrecognizedClientException', 'InvalidSignatureException', 'ExpiredTokenException'):\n        return 'authorization_failure'\n    if code in ('ThrottlingException', 'ProvisionedThroughputExceededException'):\n        return 'throttled'\n    if code in ('InvalidImageFormatException', 'ImageTooLargeException', 'InvalidParameterException'):\n        return 'provider_input_failure'\n    if type(exc).__name__ in ('NoCredentialsError', 'PartialCredentialsError', 'ProfileNotFound'):\n        return 'credentials_missing'\n    if type(exc).__name__ in ('ReadTimeoutError', 'ConnectTimeoutError', 'EndpointConnectionError'):\n        return 'transport_failure'\n    return 'provider_or_transport_failure'\n\n\ndef run(client_factory=create_client):\n    start = monotonic()\n    result = {'schema_version': '1.0.0', 'provider': 'Amazon Rekognition', 'status': 'error',\n              'model_version': None, 'data': None, 'error': None,\n              'captured_at': datetime.now(timezone.utc).isoformat()}\n    try:\n        region = os.environ['AWS_REGION'].strip()\n        filename = Path(os.environ['IMAGE_PATH'])\n        if not region or filename.suffix.lower() not in ('.jpg', '.jpeg', '.png'):\n            raise ValueError('configuration')\n        # Bounded read: this starter's cap is 4 MiB, not a claimed service limit.\n        with filename.open('rb') as image:\n            content = image.read(4 * 1024 * 1024 + 1)\n        if not content or len(content) > 4 * 1024 * 1024:\n            raise ValueError('input_size')\n        client = client_factory(region)\n        try:\n            raw = client.detect_labels(Image={'Bytes': content}, MaxLabels=20,\n                                       MinConfidence=70, Features=['GENERAL_LABELS'])\n            result['data'], result['model_version'] = normalize(raw)\n        finally:\n            client.close()\n        result['region'] = region\n        result['status'] = 'ok'\n    except (KeyError, OSError):\n        result['error'] = 'configuration'\n    except (ValueError, TypeError):\n        result['error'] = 'configuration_or_schema'\n    except ImportError:\n        result['error'] = 'dependency_missing'\n    except Exception as exc:\n        result['error'] = classify_error(exc)\n    if result['status'] != 'ok':\n        result['data'] = None\n    result['elapsed_ms'] = round((monotonic() - start) * 1000)\n    return result\n\n\nif __name__ == '__main__':\n    output = run()\n    print(json.dumps(output, ensure_ascii=False, allow_nan=False))\n    sys.exit(0 if output['status'] == 'ok' else 1)\n","scope":{"en":"Single-image general labels, not custom defect detection, face identification or live video. Confidence is normalized from 0–100 to 0–1.","zh-TW":"單張影像一般標籤；不是自訂缺陷偵測、人臉識別或即時視訊。信心分數由 0–100 正規化為 0–1。"},"setup":{"en":"Install boto3 in a Python environment and record the installed version. Configure an AWS role or SSO profile with rekognition:DetectLabels permission. Set AWS_REGION and IMAGE_PATH; optionally select AWS_PROFILE. Save as rekognition_smoke.py and run python rekognition_smoke.py. No account, credentials or cloud call is provided by this page.","zh-TW":"在 Python 環境安裝 boto3 並記錄版本。設定具有 rekognition:DetectLabels 權限的 AWS 角色或 SSO profile。設定 AWS_REGION 與 IMAGE_PATH，必要時指定 AWS_PROFILE。另存為 rekognition_smoke.py 並執行 python rekognition_smoke.py。本頁不提供帳號、憑證或代呼叫雲端。"},"decisions":[[{"en":"Result contract","zh-TW":"結果契約"},{"en":"ok contains validated label/score pairs, including a valid empty list; error contains null data and a redacted category. Record LabelModelVersion returned by AWS; general DetectLabels does not let this sample pin a model version.","zh-TW":"ok 包含已驗證 label／score，允許有效空陣列；error 的 data 為 null，只回傳去敏錯誤類別。記錄 AWS 回傳的 LabelModelVersion；此一般 DetectLabels 範例不能指定固定模型版本。"}],[{"en":"Operational limits","zh-TW":"操作限制"},{"en":"One attempt, 5-second connection timeout and 30-second read timeout. These are not an overall process deadline. Input is capped locally at 4 MiB; threshold 70 and maximum 20 labels are starter choices, not validated business thresholds.","zh-TW":"只嘗試一次，連線逾時 5 秒、讀取逾時 30 秒；這不是整體程序截止時間。本地輸入上限 4 MiB；門檻 70、最多 20 個標籤是範例設定，不是已驗證的商業門檻。"}],[{"en":"Failure decisions","zh-TW":"失敗決策"},{"en":"Separate authorization, throttling, invalid input and transport failure. Fix configuration errors first; introduce bounded retries only after reviewing duplicate cost and total deadlines.","zh-TW":"區分授權、節流、輸入與傳輸失敗。先修正設定錯誤，再評估重複成本與整體截止時間，才加入有限重試。"}],[{"en":"Data and cost","zh-TW":"資料與成本"},{"en":"Image bytes leave your machine for the configured AWS region. Confirm account terms and data handling; measure usage with one small sample. No price, latency or defect accuracy was measured.","zh-TW":"影像位元組會送至設定的 AWS 區域。確認帳號條件與資料處理方式，先以小樣本量測用量。本輪未量測價格、延遲或缺陷準確率。"}],[{"en":"Proposed acceptance","zh-TW":"建議驗收"},{"en":"Use 20 authorized representative images plus empty, malformed, denied-access and timeout cases. Require zero silent failures and correct confidence scaling; agree label usefulness and latency targets before live evaluation. Keep industrial defect acceptance separate.","zh-TW":"使用 20 張經授權代表影像，加上空檔、格式錯誤、權限拒絕與逾時案例。要求零筆隱藏失敗與正確分數轉換；實測前先約定標籤實用性與延遲目標。工業缺陷驗收需另外定義。"}]]},"schema_version":"1.0.0","type":"development-proposal","product_id":"industrial-api:AmazonRekognition","name":"Amazon Rekognition","provider":"AWS","url":"https://smart-tools.ai/product/AmazonRekognition","localized_urls":{"en":"https://smart-tools.ai/product/AmazonRekognition","zh-TW":"https://smart-tools.ai/zh-tw/product/AmazonRekognition"},"category":"vision","capability_id":"cap:computer-vision","technology_hub":"https://smart-tools.ai/industrial-ai/computer-vision","interface_kind":"API / SDK","deployment":"cloud","official_documentation":"https://docs.aws.amazon.com/rekognition/latest/dg/what-is.html","sources":["https://docs.aws.amazon.com/rekognition/latest/dg/what-is.html","https://aws.amazon.com/about-aws/","https://docs.aws.amazon.com/rekognition/latest/APIReference/API_DetectLabels.html","https://docs.aws.amazon.com/boto3/latest/reference/services/rekognition.html","https://docs.aws.amazon.com/AWSJavaScriptSDK/v3/latest/client/rekognition/command/DetectLabelsCommand/","https://docs.aws.amazon.com/cli/latest/reference/rekognition/","https://docs.aws.amazon.com/rekognition/latest/APIReference/API_DetectText.html","https://docs.aws.amazon.com/rekognition/latest/APIReference/API_DetectProtectiveEquipment.html","https://docs.aws.amazon.com/rekognition/latest/APIReference/API_DetectCustomLabels.html","https://docs.aws.amazon.com/rekognition/latest/APIReference/API_StartLabelDetection.html","https://docs.aws.amazon.com/rekognition/latest/APIReference/API_StartSegmentDetection.html","https://docs.aws.amazon.com/rekognition/latest/APIReference/API_DetectModerationLabels.html","https://docs.aws.amazon.com/rekognition/latest/dg/rekognition-availability-changes.html","https://docs.aws.amazon.com/rekognition/latest/APIReference/API_GetLabelDetection.html","https://docs.aws.amazon.com/boto3/latest/guide/credentials.html","https://docs.aws.amazon.com/botocore/latest/reference/config.html"],"source_review":{"level":"P1","status":"official-source-reviewed","checked_at":"2026-10-08"},"provider_summary":{"en":"Analyze image and video content with managed detection capabilities.","zh-TW":"透過雲端偵測能力分析圖片與影片內容。"},"proposed_product":{"en":"Site image index","zh-TW":"場域影像索引工作台"},"feasibility":{"tier":"prototype","rationale":{"en":"Test one documented operation with a small real sample after access is confirmed. This is a development judgment, not a delivery estimate.","zh-TW":"確認存取後，用少量真實樣本測試一個有文件的操作。此為開發判斷，不是交期估算。"},"basis":"development-judgment;not-traffic-ranked"},"proposed_inputs":{"en":"A small authorized image dataset, task definition and reference annotations.","zh-TW":"少量經授權影像、任務定義與參考標註。"},"proposed_deliverable":{"en":"A reviewable result with image references, labels or annotation state; keep original files.","zh-TW":"可審核的影像引用、標籤或標註狀態；保留原始檔案。"},"acceptance_criterion":{"en":"Compare the supported operation against a labeled sample; report errors and missing results separately.","zh-TW":"用已標註樣本比對支援的操作；錯誤與缺漏結果分開呈現。"},"dependencies":{"en":"Dataset access, image rights and a supported model or annotation project.","zh-TW":"資料集存取、影像使用權與支援的模型或標註專案。"},"integration_condition":null,"proposed_adapter_envelope":{"provider":"AWS","operation":"chosen-documented-operation","source_url":"https://docs.aws.amazon.com/rekognition/latest/dg/what-is.html","captured_at":"ISO-8601 timestamp","status":"ok|pending|unknown|failed","data":"provider response mapped by the team","evidence":"source references","errors":"explicit error details"},"adapter_envelope_status":"proposed-internal-contract;not-a-provider-response","development_status":"concept-specification","integration_test":"not-run","pricing_status":"provider-terms-review-required","estimate_status":"requires-access-and-sample-validation","traffic_status":"not-measured-in-this-assessment","measurement_events":["product_view","product_to_docs","product_to_spec","bridge_to_industrial_ai"]}