> 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-ko/deploy.md).

# 배포

- [모델 또는 Workflow 배포](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/deployment-overview.md): Roboflow에서 학습했거나 업로드한 workflow와 model을 배포하는 방법을 알아보세요.
- [지원되는 모델](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models.md): Roboflow로 배포할 수 있는 모든 model입니다.
- [Roboflow 3.0](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/roboflow-3.md): Serverless Hosted API를 통해 Roboflow 3.0 model family를 사용합니다
- [Roboflow 2.0](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/roboflow-2.md): Serverless Hosted API를 통해 Roboflow 2.0 semantic segmentation model을 사용합니다
- [Roboflow Instant](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/roboflow-instant.md): Serverless Hosted API를 통해 Roboflow Instant few-shot object detection model을 실행합니다.
- [RF-DETR](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/rf-detr.md): Serverless Hosted API를 통해 Roboflow의 RF-DETR 모델 사용
- [YOLO11](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/yolo11.md): Serverless Hosted API를 통해 YOLO11 model family를 사용합니다
- [YOLOv12](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/yolov12.md): Serverless Hosted API를 통해 YOLOv12 object detection model을 사용합니다
- [YOLO26](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/yolo26.md): Serverless Hosted API를 통해 YOLO26 model family를 사용합니다
- [YOLOv9](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/yolov9.md): Serverless Hosted API를 통해 YOLOv9 object detection을 사용합니다
- [YOLOv7](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/yolov7.md): Serverless Hosted API를 통해 YOLOv7 instance segmentation을 사용합니다
- [YOLOv5](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/yolov5.md): Serverless Hosted API를 통해 YOLOv5 model family를 사용합니다
- [YOLOLite](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/yololite.md): Serverless Hosted API를 통해 YOLOlite model family를 사용합니다
- [YOLO-World](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/yolo-world.md): Serverless Hosted API를 통해 YOLO-World open-vocabulary object detection을 사용합니다
- [SAM3](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/sam3.md): Serverless Hosted API를 통해 Meta의 SAM3 모델 사용
- [SAM2](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/sam2.md): Serverless Hosted API를 통해 Meta의 SAM2 모델 사용
- [ViT](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/vit.md): Serverless Hosted API를 통해 Roboflow에서 학습된 ViT 분류 모델 실행
- [ResNet](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/resnet.md): Serverless Hosted API를 통해 ResNet 이미지 분류 사용
- [Dino v3](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/dino-v3.md): Serverless Hosted API를 통해 Roboflow에서 학습된 DINOv3 분류 모델 실행
- [PaliGemma 2](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/paligemma2.md): Google의 PaliGemma 2 비전-언어 모델을 Serverless Hosted API를 통해 사용합니다
- [Qwen3-VL](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/qwen3-vl.md): Alibaba의 Qwen3-VL 비전-언어 모델을 Serverless Hosted API를 통해 사용합니다
- [Qwen3.5](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/qwen3-5.md): Alibaba의 Qwen3.5-VL 비전-언어 모델을 Dedicated Deployment 또는 self-hosted Inference에서 사용합니다
- [SmolVLM2](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/smolvlm2.md): HuggingFace의 SmolVLM2 비전-언어 모델을 Dedicated Deployment 또는 self-hosted Inference에서 사용합니다
- [Moondream2](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/moondream2.md): Moondream2를 Dedicated Deployment 또는 self-hosted Inference에서 open-vocabulary detection에 사용합니다
- [Florence 2](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/florence-2.md): Serverless Hosted API를 통해 Microsoft의 Florence 2 멀티모달 모델 사용
- [CLIP](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/clip.md): Serverless Hosted API를 통해 OpenAI의 CLIP 모델 사용
- [Perception Encoder](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/perception-encoder.md): Meta의 Perception Encoder를 사용해 Dedicated Deployment 또는 self-hosted Inference에서 이미지와 텍스트 임베딩을 계산합니다
- [OwlV2](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/owlv2.md): OwlV2를 Dedicated Deployment 또는 self-hosted Inference에서 one-shot object detection에 사용합니다
- [Grounding DINO](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/grounding-dino.md): Grounding DINO를 Dedicated Deployment 또는 self-hosted Inference에서 text-prompted object detection에 사용합니다
- [DocTR](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/doctr.md): Serverless Hosted API를 통해 DocTR OCR 모델 사용
- [EasyOCR](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/easyocr.md): Serverless Hosted API를 통해 EasyOCR 다국어 OCR 모델 사용
- [TrOCR](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/trocr.md): Microsoft의 TrOCR를 Dedicated Deployment 또는 self-hosted Inference에서 텍스트 인식에 사용합니다
- [GLM-OCR](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/glm-ocr.md): GLM-OCR을 Serverless Hosted API를 통해 이미지 OCR에 사용합니다
- [Depth Anything V2](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/depth-anything-v2.md): Depth Anything V2를 Dedicated Deployment 또는 self-hosted Inference에서 monocular depth estimation에 사용합니다
- [L2Cs-Net](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/l2cs-net.md): Serverless Hosted API를 통해 L2Cs-Net 시선 감지 모델 사용
- [Serverless Hosted API](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/serverless-hosted-api-v2.md): Roboflow cloud의 GPU 가속 자동 확장 인프라에서 Workflow와 Model Inference를 실행합니다.
- [Workflow에서 사용](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/serverless-hosted-api-v2/use-in-a-workflow.md): Roboflow Workflows와 함께 Serverless Hosted API를 사용할 수 있습니다.
- [REST API와 함께 사용](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/serverless-hosted-api-v2/use-with-the-rest-api.md)
- [Python SDK와 함께 사용](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/serverless-hosted-api-v2/use-with-python-sdk.md): Roboflow의 Serverless Hosted API를 Python SDK와 함께 사용합니다
- [가격](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/serverless-hosted-api-v2/pricing.md): Serverless Hosted API 가격 페이지
- [Serverless Video Streaming API](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/serverless-video-streaming-api.md): Roboflow Cloud에서 라이브 비디오에 Roboflow Workflows를 실행합니다. 웹캠, RTSP 카메라 또는 비디오 파일에서 WebRTC를 통해 입력을 스트리밍하고, inference 결과를 애플리케이션으로 다시 받습니다.
- [Batch Processing](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/batch-processing.md)
- [API Reference](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/batch-processing/api-reference.md): Batch Processing 엔드포인트의 REST API 참조입니다.
- [CLI 사용법](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/batch-processing/cli-usage.md): Roboflow CLI를 사용해 Batch Processing job을 만들고 관리합니다.
- [문제 해결](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/batch-processing/troubleshooting.md): 타임아웃, SAHI 성능, OOM 오류를 포함한 일반적인 Batch Processing 문제를 해결합니다.
- [Dedicated Deployments](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/dedicated-deployments.md): Roboflow와 함께 전용 서버에서 Vision Model을 실행하세요
- [Dedicated Deployment 만들기](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/dedicated-deployments/create-a-dedicated-deployment.md): Roboflow 웹 인터페이스 또는 CLI에서 Dedicated Deployment를 만들 수 있습니다.
- [Dedicated Deployment 일시 중지 및 재개](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/dedicated-deployments/pause-and-resume-a-dedicated-deployment.md)
- [Dedicated Deployment 삭제](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/dedicated-deployments/delete-a-dedicated-deployment.md)
- [Dedicated Deployment에 요청 보내기](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/dedicated-deployments/make-requests-to-a-dedicated-deployment.md): Python SDK, HTTP API 또는 Workflows 웹 인터페이스를 사용해 Dedicated Deployment에 직접 요청을 보낼 수 있습니다.
- [API로 Dedicated Deployments 관리](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/dedicated-deployments/manage-dedicated-deployments-with-an-api.md): HTTP API를 사용해 dedicated deployment를 관리하세요.
- [Managed Deployments](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/roboflow-managed-deployments-overview.md)
- [Self-Hosted Deployment](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/self-hosted-deployment.md): Roboflow model과 Workflow를 자체 하드웨어에서 실행할 수 있습니다.
- [다른 SDK](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/sdks.md)
- [Python inference-sdk](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/sdks/python-inference-sdk.md): inference-sk에 대한 정보
- [웹 브라우저](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/sdks/web-browser.md)
- [Web inference.js](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/sdks/web-browser/web-inference.js.md): inference.js를 사용하여 브라우저의 엣지에서 실시간 예측 실행
- [inferencejs 참고](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/sdks/web-browser/web-inference.js/inferencejs-reference.md): Roboflow로 구축한 컴퓨터 비전 애플리케이션을 웹/JavaScript 환경에 배포하기 위한 edge library인 \`inferencejs\`에 대한 참고 자료입니다
- [inferencejs 요구사항](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/sdks/web-browser/web-inference.js/inferencejs-requirements.md): \`inferencejs\` 실행을 위한 요구사항
- [Web inference-sdk](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/sdks/web-browser/web-inference-sdk.md): inference-sdk를 사용해 Roboflow cloud에서 브라우저 기반 실시간 비디오 inference를 실행합니다
- [Lens Studio](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/sdks/lens-studio.md): Snap Lens 제작에 사용할 수 있도록 model을 Lens Studio에 배포합니다.
- [Changelog - Lens Studio](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/sdks/lens-studio/changelog-lens-studio.md): Lens Studio 통합의 공개 변경 사항 목록입니다
- [Luxonis OAK](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/sdks/luxonis-oak.md): Myriad X VPU 가속을 사용해 Roboflow Train model을 OpenCV AI Kit에 배포합니다.
- [OpenMV](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/sdks/openmv.md): 매우 저전력 edge camera에 computer vision model을 배포합니다.
- [iOS SDK](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/sdks/ios-sdk.md): 학습한 Roboflow model을 iOS 앱에 배포합니다
- [Custom Model Weight 업로드](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/upload-custom-weights.md): Roboflow는 모델 배포를 위해 사용자 지정 학습 모델의 weight를 Roboflow project에 업로드할 수 있는 기능을 제공합니다.
- [Model Weight 다운로드](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/download-roboflow-model-weights.md): Roboflow model을 자체 하드웨어에서 실행하려면 Roboflow Inference(권장되는 자동 방식)를 사용하거나, 필요한 특정 경우에 Model Weight를 수동으로 다운로드할 수 있습니다.
- [Enterprise Deployment](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/enterprise-deployment.md)
- [License Server](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/enterprise-deployment/license-server.md): Roboflow License server를 사용해 Roboflow Deployment server에 필요한 경로를 회사의 DMZ로 프록시할 수 있습니다
- [오프라인 모드](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/enterprise-deployment/offline-mode.md): Roboflow Enterprise 고객은 오프라인으로 모델을 배포할 수 있습니다.
- [Kubernetes](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/enterprise-deployment/kubernetes.md): Kubernetes에서 Roboflow Inference 시작하기
- [Docker Compose](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/enterprise-deployment/docker-compose.md): Docker Compose를 통해 다중 컨테이너 애플리케이션을 구축하기 위해 다른 docker container와 함께 Roboflow inference server를 실행합니다.
- [Deployment Manager](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/device-manager.md): edge 하드웨어에 배포된 computer vision model을 관리하고 모니터링합니다.
- [설정](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/device-manager/setting-up.md)
- [하드웨어 요구사항](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/device-manager/setting-up/hardware-requirements.md)
- [Device 추가](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/device-manager/setting-up/add-a-device.md): Deployment Manager를 사용해 Workflow를 배포하는 데 필요한 모든 것을 포함하여 device를 설정합니다.
- [Stream 추가](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/device-manager/setting-up/add-a-stream.md): Workflow를 실행하는 데 사용할 수 있는 stream을 구성하는 방법을 알아보세요.
- [유지보수 창 설정](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/device-manager/setting-up/setup-maintenance-windows.md)
- [Device 알림 설정](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/device-manager/setting-up/set-up-device-alerts.md)
- [모니터링](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/device-manager/monitoring.md)
- [Stream 보기](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/device-manager/monitoring/view-a-stream.md): Deployment Manager로 구성된 Stream을 보는 방법을 알아보세요.
- [Device 로그 보기](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/device-manager/monitoring/view-device-logs.md)
- [Resource Monitor 보기](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/device-manager/monitoring/view-the-resource-monitor.md)
- [변경하기](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/device-manager/making-changes.md)
- [Device 구성 업데이트](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/device-manager/making-changes/update-device-configuration.md)
- [Deployment Manager 다시 배포](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/device-manager/making-changes/redeploy-deployment-manager.md)
- [Device Manager용 API 키](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/device-manager/making-changes/api-keys-for-device-manager.md)
- [Stream 종료](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/device-manager/making-changes/delete-a-stream.md)
- [Stream 일시 중지 및 재개](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/device-manager/making-changes/stop-a-stream.md)
- [Device 삭제](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/device-manager/making-changes/delete-a-device.md)
- [PLC Relay](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/device-manager/plc-relay.md): Allen-Bradley, Modbus TCP 또는 Siemens S7를 통해 PLC 태그를 읽고 쓰도록 PLC Relay를 구성합니다.
- [Model Monitoring](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/model-monitoring.md): Roboflow를 사용한 Model Monitoring 가이드입니다.
- [알림](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/model-monitoring/alerting.md)
- [Vision Events](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/vision-events.md): 배포된 컴퓨터 비전 model이 프로덕션에서 보는 것을 기록, 검색, 분석합니다.
- [Use Cases](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/vision-events/use-cases.md): Use Case를 사용해 목적별로 Vision Event를 그룹화합니다.
- [이벤트 전송](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/vision-events/send-events.md): 배포된 model에서 Vision Event를 보내는 세 가지 방법입니다.
- [이벤트 조회](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/vision-events/query-events.md): 대시보드와 API를 통해 Vision Events를 검색, 필터링 및 탐색
- [이벤트 삭제](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/vision-events/delete-events.md): 대시보드 또는 API를 통해 Use Case에서 Vision Event를 제거합니다.
- [Operator 피드백](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/vision-events/operator-feedback.md): Operator가 Vision Event를 검토하고 올바름, 잘못됨 또는 판단 불가로 표시하도록 합니다.
- [학습용 이미지 추가](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/vision-events/add-images-for-training.md): Vision Event의 이미지를 Roboflow 프로젝트로 보내 학습에 사용합니다.


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