> For the complete documentation index, see [llms.txt](https://docs.roboflow.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.roboflow.com/roboflow/roboflow-jp/deploy.md).

# Deploy

- [Model または Workflow をデプロイ](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/deployment-overview.md): Roboflow 上で学習した、またはアップロードした workflows と models をデプロイする方法を学びます。
- [Supported Models](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models.md): Roboflow でデプロイできるすべての models です。
- [Roboflow 3.0](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/roboflow-3.md): Roboflow 3.0 model family を当社の Serverless Hosted API 経由で使用します
- [Roboflow 2.0](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/roboflow-2.md): Roboflow 2.0 semantic segmentation model を当社の Serverless Hosted API 経由で使用します
- [Roboflow Instant](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/roboflow-instant.md): Serverless Hosted API 経由で Roboflow Instant の few-shot object detection model を実行します。
- [RF-DETR](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/rf-detr.md): Serverless Hosted API を通じて Roboflow の RF-DETR model を使用する
- [YOLO11](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/yolo11.md): YOLO11 model family を当社の Serverless Hosted API 経由で使用します
- [YOLOv12](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/yolov12.md): YOLOv12 object detection model を当社の Serverless Hosted API 経由で使用します
- [YOLO26](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/yolo26.md): YOLO26 model family を当社の Serverless Hosted API 経由で使用します
- [YOLOv9](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/yolov9.md): YOLOv9 object detection を当社の Serverless Hosted API 経由で使用します
- [YOLOv7](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/yolov7.md): YOLOv7 instance segmentation を当社の Serverless Hosted API 経由で使用します
- [YOLOv5](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/yolov5.md): YOLOv5 model family を当社の Serverless Hosted API 経由で使用します
- [YOLOLite](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/yololite.md): YOLOlite model family を当社の Serverless Hosted API 経由で使用します
- [YOLO-World](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/yolo-world.md): Serverless Hosted API を通じて YOLO-World の open-vocabulary object detection を使用する
- [SAM3](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/sam3.md): Serverless Hosted API を通じて Meta の SAM3 model を使用する
- [SAM2](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/sam2.md): Serverless Hosted API を通じて Meta の SAM2 モデルを使用する
- [ViT](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/vit.md): Serverless Hosted API を通じて、Roboflow で学習された ViT classification models を実行する
- [ResNet](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/resnet.md): Serverless Hosted API を通じて ResNet image classification を使用する
- [Dino v3](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/dino-v3.md): Serverless Hosted API を通じて、Roboflow で学習された DINOv3 classification models を実行する
- [PaliGemma 2](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/paligemma2.md): Google の PaliGemma 2 視覚言語モデルを、当社の Serverless Hosted API 経由で使用します
- [Qwen3-VL](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/qwen3-vl.md): Alibaba の Qwen3-VL 視覚言語モデルを、当社の Serverless Hosted API 経由で使用します
- [Qwen3.5](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/qwen3-5.md): Alibaba の Qwen3.5-VL 視覚言語モデルを、Dedicated Deployment または self-hosted Inference で使用します
- [SmolVLM2](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/smolvlm2.md): HuggingFace の SmolVLM2 視覚言語モデルを、Dedicated Deployment または self-hosted Inference で使用します
- [Moondream2](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/moondream2.md): Moondream2 を、Dedicated Deployment または self-hosted Inference での open-vocabulary detection に使用します
- [Florence 2](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/florence-2.md): Serverless Hosted API を通じて Microsoft の Florence 2 multimodal model を使用する
- [CLIP](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/clip.md): Serverless Hosted API を通じて OpenAI の CLIP model を使用する
- [Perception Encoder](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/perception-encoder.md): Meta の Perception Encoder を使用して、Dedicated Deployment または self-hosted Inference 上で画像とテキストの埋め込みを計算します
- [OwlV2](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/owlv2.md): OwlV2 を、Dedicated Deployment または self-hosted Inference での one-shot object detection に使用します
- [Grounding DINO](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/grounding-dino.md): Grounding DINO を、Dedicated Deployment または self-hosted Inference での text-prompted object detection に使用します
- [DocTR](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/doctr.md): Serverless Hosted API を通じて DocTR OCR model を使用する
- [EasyOCR](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/easyocr.md): Serverless Hosted API を通じて EasyOCR multilingual OCR model を使用する
- [TrOCR](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/trocr.md): Microsoft の TrOCR を、Dedicated Deployment または self-hosted Inference での text recognition に使用します
- [GLM-OCR](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/glm-ocr.md): GLM-OCR を当社の Serverless Hosted API 経由で image OCR に使用します
- [Depth Anything V2](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/depth-anything-v2.md): Depth Anything V2 を、Dedicated Deployment または self-hosted Inference での monocular depth estimation に使用します
- [L2Cs-Net](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/supported-models/l2cs-net.md): Serverless Hosted API を通じて L2Cs-Net gaze detection model を使用する
- [Serverless Hosted API](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/serverless-hosted-api-v2.md): Roboflow cloud 上の GPU アクセラレーションされた自動スケーリング基盤で、Workflows と Model Inference を実行します。
- [Workflow で使用](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/serverless-hosted-api-v2/use-in-a-workflow.md): Serverless Hosted API は Roboflow Workflows で使用できます。
- [REST API で使用](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/serverless-hosted-api-v2/use-with-the-rest-api.md)
- [Python SDK で使用](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/serverless-hosted-api-v2/use-with-python-sdk.md): Roboflow の Serverless Hosted API を Python SDK で使用します
- [料金](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/serverless-hosted-api-v2/pricing.md): Serverless Hosted API の料金ページ
- [Serverless Video Streaming API](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/serverless-video-streaming-api.md): Roboflow Cloud 上のライブ動画で Roboflow Workflows を実行します。Webcam、RTSP カメラ、または動画ファイルから WebRTC 経由で入力をストリーミングし、推論結果をアプリケーションに返します。
- [Batch Processing](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/batch-processing.md)
- [API Reference](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/batch-processing/api-reference.md): Batch Processing エンドポイントの REST API リファレンスです。
- [CLI Usage](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/batch-processing/cli-usage.md): Roboflow CLI を使って Batch Processing jobs を作成・管理します。
- [トラブルシューティング](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/batch-processing/troubleshooting.md): タイムアウト、SAHI の性能、OOM エラーなど、Batch Processing の一般的な問題を解決します。
- [Dedicated Deployments](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/dedicated-deployments.md): Roboflow で専用サーバー上に Vision Models を実行します
- [Dedicated Deployment を作成](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/dedicated-deployments/create-a-dedicated-deployment.md): Dedicated Deployment は Roboflow の Web インターフェースまたは CLI で作成できます。
- [Dedicated Deployment を一時停止・再開](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/dedicated-deployments/pause-and-resume-a-dedicated-deployment.md)
- [Dedicated Deployment を削除](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/dedicated-deployments/delete-a-dedicated-deployment.md)
- [Dedicated Deployment にリクエストを送る](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/dedicated-deployments/make-requests-to-a-dedicated-deployment.md): Dedicated Deployment には、Python SDK、HTTP API、または Workflows の Web インターフェースを使って直接リクエストできます。
- [API で Dedicated Deployments を管理](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/dedicated-deployments/manage-dedicated-deployments-with-an-api.md): HTTP API を使用して dedicated deployment を管理します。
- [Managed Deployments](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/roboflow-managed-deployments-overview.md)
- [Self-Hosted Deployment](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/self-hosted-deployment.md): Roboflow の models と Workflows を自分のハードウェアで実行できます。
- [Other SDKs](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/sdks.md)
- [Python inference-sdk](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/sdks/python-inference-sdk.md): inference-sk に関する情報
- [Web Browser](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/sdks/web-browser.md)
- [Web inference.js](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/sdks/web-browser/web-inference.js.md): inference.js を使って、ブラウザー上のエッジでリアルタイム予測を実行する
- [inferencejs Reference](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/sdks/web-browser/web-inference.js/inferencejs-reference.md): Roboflow で構築したコンピュータビジョンアプリケーションを web/JavaScript 環境にデプロイするためのエッジライブラリ、\`inferencejs\` のリファレンスです
- [inferencejs Requirements](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/sdks/web-browser/web-inference.js/inferencejs-requirements.md): \`inferencejs\` を実行するための要件
- [Web inference-sdk](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/sdks/web-browser/web-inference-sdk.md): inference-sdk を使って、Roboflow cloud 上でブラウザーからリアルタイム動画推論を実行します
- [Lens Studio](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/sdks/lens-studio.md): Snap Lens の作成に使用するため、モデルを Lens Studio にデプロイします。
- [Changelog - Lens Studio](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/sdks/lens-studio/changelog-lens-studio.md): Lens Studio 連携に関する公開変更点の一覧です
- [Luxonis OAK](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/sdks/luxonis-oak.md): Myriad X VPU アクセラレーションを使って、Roboflow Train モデルを OpenCV AI Kit にデプロイします。
- [OpenMV](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/sdks/openmv.md): 超低消費電力のエッジカメラにコンピュータビジョンモデルをデプロイします。
- [iOS SDK](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/sdks/ios-sdk.md): 学習済み Roboflow model を iOS アプリにデプロイします
- [Custom Model Weights をアップロード](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/upload-custom-weights.md): Roboflow では、カスタム学習した models の model weights を Roboflow projects にアップロードしてデプロイできます。
- [Model Weights をダウンロード](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/download-roboflow-model-weights.md): Roboflow models を自分のハードウェアで実行するには、Roboflow Inference（推奨される自動方式）を使うか、Model Weights を手動でダウンロードする（特定の例外ケース向け）ことができます。
- [Enterprise Deployment](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/enterprise-deployment.md)
- [License Server](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/enterprise-deployment/license-server.md): Roboflow License server を使用して、Roboflow Deployment servers に必要なルートを会社の DMZ にプロキシできます
- [Offline Mode](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/enterprise-deployment/offline-mode.md): Roboflow Enterprise のお客様は、models をオフラインでデプロイできます。
- [Kubernetes](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/enterprise-deployment/kubernetes.md): Kubernetes 上での Roboflow Inference の使い始め
- [Docker Compose](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/enterprise-deployment/docker-compose.md): Roboflow inference server を他の docker containers と並行して実行し、Docker Compose を使ってマルチコンテナアプリケーションを構築します。
- [Deployment Manager](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/device-manager.md): エッジハードウェアにデプロイされたコンピュータビジョン models を管理・監視します。
- [セットアップ](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/device-manager/setting-up.md)
- [Hardware Requirements](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/device-manager/setting-up/hardware-requirements.md)
- [Device を追加](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/device-manager/setting-up/add-a-device.md): Deployment Manager を使って Workflow をデプロイするのに必要なものをすべて含めて device をセットアップします。
- [Stream を追加](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/device-manager/setting-up/add-a-stream.md): Workflow を実行するために使用できる stream を設定する方法を学びます。
- [メンテナンス時間を設定](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/device-manager/setting-up/setup-maintenance-windows.md)
- [Device Alerts を設定](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/device-manager/setting-up/set-up-device-alerts.md)
- [Monitoring](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/device-manager/monitoring.md)
- [Stream を表示](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/device-manager/monitoring/view-a-stream.md): Deployment Manager で構成された stream の表示方法を学びます。
- [Device Logs を表示](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/device-manager/monitoring/view-device-logs.md)
- [Resource Monitor を表示](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/device-manager/monitoring/view-the-resource-monitor.md)
- [変更を行う](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/device-manager/making-changes.md)
- [Device Configuration を更新](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/device-manager/making-changes/update-device-configuration.md)
- [Deployment Manager を再デプロイ](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/device-manager/making-changes/redeploy-deployment-manager.md)
- [Device Manager の API Keys](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/device-manager/making-changes/api-keys-for-device-manager.md)
- [Stream を終了](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/device-manager/making-changes/delete-a-stream.md)
- [Stream を一時停止・再開](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/device-manager/making-changes/stop-a-stream.md)
- [Device を削除](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/device-manager/making-changes/delete-a-device.md)
- [PLC Relay](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/device-manager/plc-relay.md): PLC Relay を構成して、Allen-Bradley、Modbus TCP、または Siemens S7 経由で PLC タグの読み書きを行います。
- [Model Monitoring](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/model-monitoring.md): Roboflow を使った Model Monitoring のガイドです。
- [Alerting](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/model-monitoring/alerting.md)
- [Vision Events](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/vision-events.md): デプロイしたコンピュータビジョン models が本番環境で何を見ているかを記録、検索、分析します。
- [Use Cases](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/vision-events/use-cases.md): Use Cases を使って、目的ごとに Vision Events をグループ化します。
- [Events を送信](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/vision-events/send-events.md): デプロイ済み models から Vision Events を送る 3 つの方法があります。
- [Query Events](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/vision-events/query-events.md): ダッシュボードおよび API 経由で Vision Events を検索、フィルタリング、閲覧します
- [Events を削除](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/vision-events/delete-events.md): ダッシュボードまたは API から Use Case の Vision Events を削除します。
- [Operator Feedback](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/vision-events/operator-feedback.md): オペレーターが Vision Events を確認し、正しい、誤り、または判定不能としてマークできるようにします。
- [学習用画像を追加](https://docs.roboflow.com/roboflow/roboflow-jp/deploy/vision-events/add-images-for-training.md): Vision Events からの画像を、学習用に Roboflow project に送信します。


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