> 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/deployment/ja/roboflow-cloud/serverless-api.md).

# サーバーレスホスト型 API

## 概要

Roboflow にデプロイされたモデルには REST API が用意されており、それを通じて画像に対して推論を実行できます。このデプロイ方法は、デプロイ先デバイスに常時インターネット接続がある環境に最適です。

サーバーレスホスト型 API を使用できます:

* [Workflows で](/deployment/ja/roboflow-cloud/serverless-api/use-in-a-workflow.md)
* [REST API を使って](#http-api)
* 次を持つ [Inference Python SDK](#python-sdk)

### 推論サーバー

当社のサーバーレスホスト型 API は、 [Inference Server](https://docs.roboflow.com/reference/platform/rest-api/inference-server-openapi)によって提供されています。つまり、以下のように、サーバーレスホスト型 API とセルフホスト型オプションを簡単に切り替え、その逆も可能です。

```python
from inference_sdk import InferenceHTTPClient

CLIENT = InferenceHTTPClient(
    # api_url="http://localhost:9001" # セルフホスト型推論サーバー
    api_url="https://serverless.roboflow.com", # 当社のサーバーレスホスト型 API
    api_key="API_KEY" # 非公開モデルとデータにアクセスするためのオプション
)

result = CLIENT.infer("image.jpg", model_id="model-id/1")
print(result)
```

### 制限

当社のサーバーレスホスト型 API は、最大 20MB までのファイルアップロードをサポートしています。高解像度の画像では制限に達する場合があります。問題が発生した場合は、企業サポート担当者に連絡するか、次の場所にメッセージを投稿してください。 [フォーラム](https://discuss.roboflow.com).

{% hint style="info" %}
リクエストが大きすぎる場合は、添付画像のサイズを小さくすることを推奨します。画像はサーバーで受信された後、モデルアーキテクチャが受け付ける入力サイズまでいずれにせよ縮小されるため、通常、性能の低下にはつながりません。\
\
Python SDK など一部の SDK では、API に送信される前に画像をモデルアーキテクチャの入力サイズまで自動的に縮小します。
{% endhint %}

***

参照: [サーバーレスホスト型 API v1](/deployment/ja/regash/legacy-serverless.md) レガシー API のドキュメントを参照してください。

## HTTP API

### REST API で使用する

サーバーレスホスト型 API には、すべてのモデルと Workflows 用の単一のエンドポイントがあります:

```
https://serverless.roboflow.com
```

#### HTTP エンドポイント

## Legacy Infer From Request

> Legacy inference endpoint for object detection, instance segmentation, and classification.\
> \
> Args:\
>     background\_tasks: (BackgroundTasks) pool of fastapi background tasks\
>     dataset\_id (str): ID of a Roboflow dataset corresponding to the model to use for inference OR workspace ID\
>     version\_id (str): ID of a Roboflow dataset version corresponding to the model to use for inference OR model ID\
>     api\_key (Optional\[str], default None): Roboflow API Key passed to the model during initialization for artifact retrieval.\
>     \# Other parameters described in the function signature...\
> \
> Returns:\
>     Union\[InstanceSegmentationInferenceResponse, KeypointsDetectionInferenceRequest, ObjectDetectionInferenceResponse, ClassificationInferenceResponse, MultiLabelClassificationInferenceResponse, SemanticSegmentationInferenceResponse, Any]: The response containing the inference results.

```json
{"openapi":"3.1.0","info":{"title":"Roboflow Inference Server","version":"1.3.8"},"paths":{"/{dataset_id}/{version_id}":{"post":{"summary":"Legacy Infer From Request","description":"Legacy inference endpoint for object detection, instance segmentation, and classification.\n\nArgs:\n    background_tasks: (BackgroundTasks) pool of fastapi background tasks\n    dataset_id (str): ID of a Roboflow dataset corresponding to the model to use for inference OR workspace ID\n    version_id (str): ID of a Roboflow dataset version corresponding to the model to use for inference OR model ID\n    api_key (Optional[str], default None): Roboflow API Key passed to the model during initialization for artifact retrieval.\n    # Other parameters described in the function signature...\n\nReturns:\n    Union[InstanceSegmentationInferenceResponse, KeypointsDetectionInferenceRequest, ObjectDetectionInferenceResponse, ClassificationInferenceResponse, MultiLabelClassificationInferenceResponse, SemanticSegmentationInferenceResponse, Any]: The response containing the inference results.","operationId":"legacy_infer_from_request__dataset_id___version_id__post","parameters":[{"name":"dataset_id","in":"path","required":true,"schema":{"type":"string","description":"ID of a Roboflow dataset corresponding to the model to use for inference OR workspace ID","title":"Dataset Id"},"description":"ID of a Roboflow dataset corresponding to the model to use for inference OR workspace ID"},{"name":"version_id","in":"path","required":true,"schema":{"type":"string","description":"ID of a Roboflow dataset version corresponding to the model to use for inference OR model ID","title":"Version Id"},"description":"ID of a Roboflow dataset version corresponding to the model to use for inference OR model ID"},{"name":"api_key","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"description":"Roboflow API Key that will be passed to the model during initialization for artifact retrieval","title":"Api Key"},"description":"Roboflow API Key that will be passed to the model during initialization for artifact retrieval"},{"name":"confidence","in":"query","required":false,"schema":{"anyOf":[{"type":"number"},{"enum":["best","default"],"type":"string"}],"description":"The confidence threshold used to filter out predictions. Pass a float in [0, 1], or \"best\" to use F1-optimal thresholds from model evaluation, or \"default\" to use the model's built-in default.","default":0.4,"title":"Confidence"},"description":"The confidence threshold used to filter out predictions. Pass a float in [0, 1], or \"best\" to use F1-optimal thresholds from model evaluation, or \"default\" to use the model's built-in default."},{"name":"keypoint_confidence","in":"query","required":false,"schema":{"type":"number","description":"The confidence threshold used to filter out keypoints that are not visible based on model confidence","default":0,"title":"Keypoint Confidence"},"description":"The confidence threshold used to filter out keypoints that are not visible based on model confidence"},{"name":"format","in":"query","required":false,"schema":{"type":"string","description":"One of 'json' or 'image'. If 'json' prediction data is return as a JSON string. If 'image' prediction data is visualized and overlayed on the original input image.","default":"json","title":"Format"},"description":"One of 'json' or 'image'. If 'json' prediction data is return as a JSON string. If 'image' prediction data is visualized and overlayed on the original input image."},{"name":"image","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"description":"The publically accessible URL of an image to use for inference.","title":"Image"},"description":"The publically accessible URL of an image to use for inference."},{"name":"image_type","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"description":"One of base64 or numpy. Note, numpy input is not supported for Roboflow Hosted Inference.","default":"base64","title":"Image Type"},"description":"One of base64 or numpy. Note, numpy input is not supported for Roboflow Hosted Inference."},{"name":"labels","in":"query","required":false,"schema":{"anyOf":[{"type":"boolean"},{"type":"null"}],"description":"If true, labels will be include in any inference visualization.","default":false,"title":"Labels"},"description":"If true, labels will be include in any inference visualization."},{"name":"mask_decode_mode","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"description":"One of 'accurate' or 'fast'. If 'accurate' the mask will be decoded using the original image size. If 'fast' the mask will be decoded using the original mask size. 'accurate' is slower but more accurate.","default":"accurate","title":"Mask Decode Mode"},"description":"One of 'accurate' or 'fast'. If 'accurate' the mask will be decoded using the original image size. If 'fast' the mask will be decoded using the original mask size. 'accurate' is slower but more accurate."},{"name":"tradeoff_factor","in":"query","required":false,"schema":{"anyOf":[{"type":"number"},{"type":"null"}],"description":"The amount to tradeoff between 0='fast' and 1='accurate'","default":0,"title":"Tradeoff Factor"},"description":"The amount to tradeoff between 0='fast' and 1='accurate'"},{"name":"max_detections","in":"query","required":false,"schema":{"type":"integer","description":"The maximum number of detections to return. This is used to limit the number of predictions returned by the model. The model may return more predictions than this number, but only the top `max_detections` predictions will be returned.","default":300,"title":"Max Detections"},"description":"The maximum number of detections to return. This is used to limit the number of predictions returned by the model. The model may return more predictions than this number, but only the top `max_detections` predictions will be returned."},{"name":"overlap","in":"query","required":false,"schema":{"type":"number","description":"The IoU threhsold that must be met for a box pair to be considered duplicate during NMS","default":0.3,"title":"Overlap"},"description":"The IoU threhsold that must be met for a box pair to be considered duplicate during NMS"},{"name":"stroke","in":"query","required":false,"schema":{"type":"integer","description":"The stroke width used when visualizing predictions","default":1,"title":"Stroke"},"description":"The stroke width used when visualizing predictions"},{"name":"disable_preproc_auto_orient","in":"query","required":false,"schema":{"anyOf":[{"type":"boolean"},{"type":"null"}],"description":"If true, disables automatic image orientation","default":false,"title":"Disable Preproc Auto Orient"},"description":"If true, disables automatic image orientation"},{"name":"disable_preproc_contrast","in":"query","required":false,"schema":{"anyOf":[{"type":"boolean"},{"type":"null"}],"description":"If true, disables automatic contrast adjustment","default":false,"title":"Disable Preproc Contrast"},"description":"If true, disables automatic contrast adjustment"},{"name":"disable_preproc_grayscale","in":"query","required":false,"schema":{"anyOf":[{"type":"boolean"},{"type":"null"}],"description":"If true, disables automatic grayscale conversion","default":false,"title":"Disable Preproc Grayscale"},"description":"If true, disables automatic grayscale conversion"},{"name":"disable_preproc_static_crop","in":"query","required":false,"schema":{"anyOf":[{"type":"boolean"},{"type":"null"}],"description":"If true, disables automatic static crop","default":false,"title":"Disable Preproc Static Crop"},"description":"If true, disables automatic static crop"},{"name":"disable_active_learning","in":"query","required":false,"schema":{"anyOf":[{"type":"boolean"},{"type":"null"}],"description":"If true, the predictions will be prevented from registration by Active Learning (if the functionality is enabled)","default":false,"title":"Disable Active Learning"},"description":"If true, the predictions will be prevented from registration by Active Learning (if the functionality is enabled)"},{"name":"active_learning_target_dataset","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"description":"Parameter to be used when Active Learning data registration should happen against different dataset than the one pointed by model_id","title":"Active Learning Target Dataset"},"description":"Parameter to be used when Active Learning data registration should happen against different dataset than the one pointed by model_id"},{"name":"source","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"description":"The source of the inference request","default":"external","title":"Source"},"description":"The source of the inference request"},{"name":"source_info","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"description":"The detailed source information of the inference request","default":"external","title":"Source Info"},"description":"The detailed source information of the inference request"},{"name":"response_mask_format","in":"query","required":false,"schema":{"anyOf":[{"enum":["polygon","rle"],"type":"string"},{"type":"null"}],"description":"The format of the prediction mask - polygon (default) or rle - applicable for instance segmentation models.","default":"polygon","title":"Response Mask Format"},"description":"The format of the prediction mask - polygon (default) or rle - applicable for instance segmentation models."}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"anyOf":[{"$ref":"#/components/schemas/InstanceSegmentationInferenceResponse"},{"$ref":"#/components/schemas/KeypointsDetectionInferenceResponse"},{"$ref":"#/components/schemas/ObjectDetectionInferenceResponse"},{"$ref":"#/components/schemas/ClassificationInferenceResponse"},{"$ref":"#/components/schemas/MultiLabelClassificationInferenceResponse"},{"$ref":"#/components/schemas/SemanticSegmentationInferenceResponse"},{"$ref":"#/components/schemas/StubResponse"},{}],"title":"Response Legacy Infer From Request  Dataset Id   Version Id  Post"}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}}},"components":{"schemas":{"InstanceSegmentationInferenceResponse":{"properties":{"visualization":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Visualization","description":"Base64 encoded string containing prediction visualization image data"},"inference_id":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Inference Id","description":"Unique identifier of inference"},"frame_id":{"anyOf":[{"type":"integer"},{"type":"null"}],"title":"Frame Id","description":"The frame id of the image used in inference if the input was a video"},"time":{"anyOf":[{"type":"number"},{"type":"null"}],"title":"Time","description":"The time in seconds it took to produce the predictions including image preprocessing"},"image":{"anyOf":[{"items":{"$ref":"#/components/schemas/InferenceResponseImage"},"type":"array"},{"$ref":"#/components/schemas/InferenceResponseImage"}],"title":"Image"},"predictions":{"items":{"anyOf":[{"$ref":"#/components/schemas/InstanceSegmentationPrediction"},{"$ref":"#/components/schemas/InstanceSegmentationRLEPrediction"}]},"type":"array","title":"Predictions"}},"type":"object","required":["image","predictions"],"title":"InstanceSegmentationInferenceResponse","description":"Instance Segmentation inference response.\n\nAttributes:\n    predictions (List[Union[\n        inference.core.entities.responses.inference.InstanceSegmentationPrediction,\n        inference.core.entities.responses.inference.InstanceSegmentationRLEPrediction\n    ]]): List of instance segmentation predictions."},"InferenceResponseImage":{"properties":{"width":{"type":"integer","title":"Width","description":"The original width of the image used in inference"},"height":{"type":"integer","title":"Height","description":"The original height of the image used in inference"}},"type":"object","required":["width","height"],"title":"InferenceResponseImage","description":"Inference response image information.\n\nAttributes:\n    width (int): The original width of the image used in inference.\n    height (int): The original height of the image used in inference."},"InstanceSegmentationPrediction":{"properties":{"x":{"type":"number","title":"X","description":"The center x-axis pixel coordinate of the prediction"},"y":{"type":"number","title":"Y","description":"The center y-axis pixel coordinate of the prediction"},"width":{"type":"number","title":"Width","description":"The width of the prediction bounding box in number of pixels"},"height":{"type":"number","title":"Height","description":"The height of the prediction bounding box in number of pixels"},"confidence":{"type":"number","title":"Confidence","description":"The detection confidence as a fraction between 0 and 1"},"class":{"type":"string","title":"Class","description":"The predicted class label"},"class_id":{"type":"integer","title":"Class Id","description":"The class id of the prediction"},"detection_id":{"type":"string","title":"Detection Id","description":"Unique identifier of detection"},"parent_id":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Parent Id","description":"Identifier of parent image region"},"class_confidence":{"anyOf":[{"type":"number"},{"type":"null"}],"title":"Class Confidence","description":"The class label confidence as a fraction between 0 and 1"},"points":{"items":{"$ref":"#/components/schemas/Point-Output"},"type":"array","title":"Points","description":"The list of points that make up the instance polygon"},"mask_format":{"type":"string","const":"polygon","title":"Mask Format","description":"Type of mask format","default":"polygon"}},"type":"object","required":["x","y","width","height","confidence","class","class_id","points"],"title":"InstanceSegmentationPrediction"},"Point-Output":{"properties":{"x":{"type":"number","title":"X","description":"The x-axis pixel coordinate of the point"},"y":{"type":"number","title":"Y","description":"The y-axis pixel coordinate of the point"}},"type":"object","required":["x","y"],"title":"Point","description":"Point coordinates.\n\nAttributes:\n    x (float): The x-axis pixel coordinate of the point.\n    y (float): The y-axis pixel coordinate of the point."},"InstanceSegmentationRLEPrediction":{"properties":{"x":{"type":"number","title":"X","description":"The center x-axis pixel coordinate of the prediction"},"y":{"type":"number","title":"Y","description":"The center y-axis pixel coordinate of the prediction"},"width":{"type":"number","title":"Width","description":"The width of the prediction bounding box in number of pixels"},"height":{"type":"number","title":"Height","description":"The height of the prediction bounding box in number of pixels"},"confidence":{"type":"number","title":"Confidence","description":"The detection confidence as a fraction between 0 and 1"},"class":{"type":"string","title":"Class","description":"The predicted class label"},"class_id":{"type":"integer","title":"Class Id","description":"The class id of the prediction"},"detection_id":{"type":"string","title":"Detection Id","description":"Unique identifier of detection"},"parent_id":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Parent Id","description":"Identifier of parent image region"},"rle":{"additionalProperties":true,"type":"object","title":"Rle","description":"RLE-encoded mask in COCO format: {'size': [H, W], 'counts': '...'}"},"mask_format":{"type":"string","const":"rle","title":"Mask Format","description":"Type of mask format","default":"rle"}},"type":"object","required":["x","y","width","height","confidence","class","class_id","rle"],"title":"InstanceSegmentationRLEPrediction"},"KeypointsDetectionInferenceResponse":{"properties":{"visualization":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Visualization","description":"Base64 encoded string containing prediction visualization image data"},"inference_id":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Inference Id","description":"Unique identifier of inference"},"frame_id":{"anyOf":[{"type":"integer"},{"type":"null"}],"title":"Frame Id","description":"The frame id of the image used in inference if the input was a video"},"time":{"anyOf":[{"type":"number"},{"type":"null"}],"title":"Time","description":"The time in seconds it took to produce the predictions including image preprocessing"},"image":{"anyOf":[{"items":{"$ref":"#/components/schemas/InferenceResponseImage"},"type":"array"},{"$ref":"#/components/schemas/InferenceResponseImage"}],"title":"Image"},"predictions":{"items":{"$ref":"#/components/schemas/KeypointsPrediction"},"type":"array","title":"Predictions"}},"type":"object","required":["image","predictions"],"title":"KeypointsDetectionInferenceResponse"},"KeypointsPrediction":{"properties":{"x":{"type":"number","title":"X","description":"The center x-axis pixel coordinate of the prediction"},"y":{"type":"number","title":"Y","description":"The center y-axis pixel coordinate of the prediction"},"width":{"type":"number","title":"Width","description":"The width of the prediction bounding box in number of pixels"},"height":{"type":"number","title":"Height","description":"The height of the prediction bounding box in number of pixels"},"confidence":{"type":"number","title":"Confidence","description":"The detection confidence as a fraction between 0 and 1"},"class":{"type":"string","title":"Class","description":"The predicted class label"},"class_confidence":{"anyOf":[{"type":"number"},{"type":"null"}],"title":"Class Confidence","description":"The class label confidence as a fraction between 0 and 1"},"class_id":{"type":"integer","title":"Class Id","description":"The class id of the prediction"},"tracker_id":{"anyOf":[{"type":"integer"},{"type":"null"}],"title":"Tracker Id","description":"The tracker id of the prediction if tracking is enabled"},"detection_id":{"type":"string","title":"Detection Id","description":"Unique identifier of detection"},"parent_id":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Parent Id","description":"Identifier of parent image region. Useful when stack of detection-models is in use to refer the RoI being the input to inference"},"keypoints":{"items":{"$ref":"#/components/schemas/Keypoint"},"type":"array","title":"Keypoints"}},"type":"object","required":["x","y","width","height","confidence","class","class_id","keypoints"],"title":"KeypointsPrediction"},"Keypoint":{"properties":{"x":{"type":"number","title":"X","description":"The x-axis pixel coordinate of the point"},"y":{"type":"number","title":"Y","description":"The y-axis pixel coordinate of the point"},"confidence":{"type":"number","title":"Confidence","description":"Model confidence regarding keypoint visibility."},"class_id":{"type":"integer","title":"Class Id","description":"Identifier of keypoint."},"class":{"type":"string","title":"Class","description":"Type of keypoint."}},"type":"object","required":["x","y","confidence","class_id","class"],"title":"Keypoint"},"ObjectDetectionInferenceResponse":{"properties":{"visualization":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Visualization","description":"Base64 encoded string containing prediction visualization image data"},"inference_id":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Inference Id","description":"Unique identifier of inference"},"frame_id":{"anyOf":[{"type":"integer"},{"type":"null"}],"title":"Frame Id","description":"The frame id of the image used in inference if the input was a video"},"time":{"anyOf":[{"type":"number"},{"type":"null"}],"title":"Time","description":"The time in seconds it took to produce the predictions including image preprocessing"},"image":{"anyOf":[{"items":{"$ref":"#/components/schemas/InferenceResponseImage"},"type":"array"},{"$ref":"#/components/schemas/InferenceResponseImage"}],"title":"Image"},"predictions":{"items":{"$ref":"#/components/schemas/ObjectDetectionPrediction"},"type":"array","title":"Predictions"}},"type":"object","required":["image","predictions"],"title":"ObjectDetectionInferenceResponse","description":"Object Detection inference response.\n\nAttributes:\n    predictions (List[inference.core.entities.responses.inference.ObjectDetectionPrediction]): List of object detection predictions."},"ObjectDetectionPrediction":{"properties":{"x":{"type":"number","title":"X","description":"The center x-axis pixel coordinate of the prediction"},"y":{"type":"number","title":"Y","description":"The center y-axis pixel coordinate of the prediction"},"width":{"type":"number","title":"Width","description":"The width of the prediction bounding box in number of pixels"},"height":{"type":"number","title":"Height","description":"The height of the prediction bounding box in number of pixels"},"confidence":{"type":"number","title":"Confidence","description":"The detection confidence as a fraction between 0 and 1"},"class":{"type":"string","title":"Class","description":"The predicted class label"},"class_confidence":{"anyOf":[{"type":"number"},{"type":"null"}],"title":"Class Confidence","description":"The class label confidence as a fraction between 0 and 1"},"class_id":{"type":"integer","title":"Class Id","description":"The class id of the prediction"},"tracker_id":{"anyOf":[{"type":"integer"},{"type":"null"}],"title":"Tracker Id","description":"The tracker id of the prediction if tracking is enabled"},"detection_id":{"type":"string","title":"Detection Id","description":"Unique identifier of detection"},"parent_id":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Parent Id","description":"Identifier of parent image region. Useful when stack of detection-models is in use to refer the RoI being the input to inference"}},"type":"object","required":["x","y","width","height","confidence","class","class_id"],"title":"ObjectDetectionPrediction","description":"Object Detection prediction.\n\nAttributes:\n    x (float): The center x-axis pixel coordinate of the prediction.\n    y (float): The center y-axis pixel coordinate of the prediction.\n    width (float): The width of the prediction bounding box in number of pixels.\n    height (float): The height of the prediction bounding box in number of pixels.\n    confidence (float): The detection confidence as a fraction between 0 and 1.\n    class_name (str): The predicted class label.\n    class_confidence (Union[float, None]): The class label confidence as a fraction between 0 and 1.\n    class_id (int): The class id of the prediction"},"ClassificationInferenceResponse":{"properties":{"visualization":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Visualization","description":"Base64 encoded string containing prediction visualization image data"},"inference_id":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Inference Id","description":"Unique identifier of inference"},"frame_id":{"anyOf":[{"type":"integer"},{"type":"null"}],"title":"Frame Id","description":"The frame id of the image used in inference if the input was a video"},"time":{"anyOf":[{"type":"number"},{"type":"null"}],"title":"Time","description":"The time in seconds it took to produce the predictions including image preprocessing"},"image":{"anyOf":[{"items":{"$ref":"#/components/schemas/InferenceResponseImage"},"type":"array"},{"$ref":"#/components/schemas/InferenceResponseImage"}],"title":"Image"},"predictions":{"items":{"$ref":"#/components/schemas/ClassificationPrediction"},"type":"array","title":"Predictions"},"top":{"type":"string","title":"Top","description":"The top predicted class label","default":""},"confidence":{"type":"number","title":"Confidence","description":"The confidence of the top predicted class label","default":0},"parent_id":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Parent Id","description":"Identifier of parent image region. Useful when stack of detection-models is in use to refer the RoI being the input to inference"}},"type":"object","required":["image","predictions"],"title":"ClassificationInferenceResponse","description":"Classification inference response.\n\nAttributes:\n    predictions (List[inference.core.entities.responses.inference.ClassificationPrediction]): List of classification predictions.\n    top (str): The top predicted class label.\n    confidence (float): The confidence of the top predicted class label."},"ClassificationPrediction":{"properties":{"class":{"type":"string","title":"Class","description":"The predicted class label"},"class_id":{"type":"integer","title":"Class Id","description":"Numeric ID associated with the class label"},"confidence":{"type":"number","title":"Confidence","description":"The class label confidence as a fraction between 0 and 1"}},"type":"object","required":["class","class_id","confidence"],"title":"ClassificationPrediction","description":"Classification prediction.\n\nAttributes:\n    class_name (str): The predicted class label.\n    class_id (int): Numeric ID associated with the class label.\n    confidence (float): The class label confidence as a fraction between 0 and 1."},"MultiLabelClassificationInferenceResponse":{"properties":{"visualization":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Visualization","description":"Base64 encoded string containing prediction visualization image data"},"inference_id":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Inference Id","description":"Unique identifier of inference"},"frame_id":{"anyOf":[{"type":"integer"},{"type":"null"}],"title":"Frame Id","description":"The frame id of the image used in inference if the input was a video"},"time":{"anyOf":[{"type":"number"},{"type":"null"}],"title":"Time","description":"The time in seconds it took to produce the predictions including image preprocessing"},"image":{"anyOf":[{"items":{"$ref":"#/components/schemas/InferenceResponseImage"},"type":"array"},{"$ref":"#/components/schemas/InferenceResponseImage"}],"title":"Image"},"predictions":{"additionalProperties":{"$ref":"#/components/schemas/MultiLabelClassificationPrediction"},"type":"object","title":"Predictions"},"predicted_classes":{"items":{"type":"string"},"type":"array","title":"Predicted Classes","description":"The list of predicted classes"},"parent_id":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Parent Id","description":"Identifier of parent image region. Useful when stack of detection-models is in use to refer the RoI being the input to inference"}},"type":"object","required":["image","predictions","predicted_classes"],"title":"MultiLabelClassificationInferenceResponse","description":"Multi-label Classification inference response.\n\nAttributes:\n    predictions (Dict[str, inference.core.entities.responses.inference.MultiLabelClassificationPrediction]): Dictionary of multi-label classification predictions.\n    predicted_classes (List[str]): The list of predicted classes."},"MultiLabelClassificationPrediction":{"properties":{"confidence":{"type":"number","title":"Confidence","description":"The class label confidence as a fraction between 0 and 1"},"class_id":{"type":"integer","title":"Class Id","description":"Numeric ID associated with the class label"}},"type":"object","required":["confidence","class_id"],"title":"MultiLabelClassificationPrediction","description":"Multi-label Classification prediction.\n\nAttributes:\n    confidence (float): The class label confidence as a fraction between 0 and 1."},"SemanticSegmentationInferenceResponse":{"properties":{"visualization":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Visualization","description":"Base64 encoded string containing prediction visualization image data"},"inference_id":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Inference Id","description":"Unique identifier of inference"},"frame_id":{"anyOf":[{"type":"integer"},{"type":"null"}],"title":"Frame Id","description":"The frame id of the image used in inference if the input was a video"},"time":{"anyOf":[{"type":"number"},{"type":"null"}],"title":"Time","description":"The time in seconds it took to produce the predictions including image preprocessing"},"image":{"anyOf":[{"items":{"$ref":"#/components/schemas/InferenceResponseImage"},"type":"array"},{"$ref":"#/components/schemas/InferenceResponseImage"}],"title":"Image"},"predictions":{"$ref":"#/components/schemas/SemanticSegmentationPrediction"}},"type":"object","required":["image","predictions"],"title":"SemanticSegmentationInferenceResponse","description":"Semantic Segmentation inference response.\n\nAttributes:\n    predictions (inference.core.entities.responses.inference.SemanticSegmentationPrediction): Semantic segmentation predictions."},"SemanticSegmentationPrediction":{"properties":{"segmentation_mask":{"type":"string","title":"Segmentation Mask","description":"base64-encoded PNG of predicted class label at each pixel"},"class_map":{"additionalProperties":{"type":"string"},"type":"object","title":"Class Map","description":"Map of pixel intensity value to class label"},"confidence_mask":{"type":"string","title":"Confidence Mask","description":"base64-encoded PNG of predicted class confidence at each pixel"}},"type":"object","required":["segmentation_mask","class_map","confidence_mask"],"title":"SemanticSegmentationPrediction"},"StubResponse":{"properties":{"visualization":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Visualization","description":"Base64 encoded string containing prediction visualization image data"},"inference_id":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Inference Id","description":"Unique identifier of inference"},"frame_id":{"anyOf":[{"type":"integer"},{"type":"null"}],"title":"Frame Id","description":"The frame id of the image used in inference if the input was a video"},"time":{"anyOf":[{"type":"number"},{"type":"null"}],"title":"Time","description":"The time in seconds it took to produce the predictions including image preprocessing"},"is_stub":{"type":"boolean","title":"Is Stub","description":"Field to mark prediction type as stub"},"model_id":{"type":"string","title":"Model Id","description":"Identifier of a model stub that was called"},"task_type":{"type":"string","title":"Task Type","description":"Task type of the project"}},"type":"object","required":["is_stub","model_id","task_type"],"title":"StubResponse"},"HTTPValidationError":{"properties":{"detail":{"items":{"$ref":"#/components/schemas/ValidationError"},"type":"array","title":"Detail"}},"type":"object","title":"HTTPValidationError"},"ValidationError":{"properties":{"loc":{"items":{"anyOf":[{"type":"string"},{"type":"integer"}]},"type":"array","title":"Location"},"msg":{"type":"string","title":"Message"},"type":{"type":"string","title":"Error Type"}},"type":"object","required":["loc","msg","type"],"title":"ValidationError"}}}}
```

### 画像でモデルを実行する

Roboflow は複数のランタイムを通じて推論を提供しています。適切な選択は、単一のモデルを呼び出すのか Workflow を呼び出すのか、必要なスループット量、そしてワークロードがどこで実行されるかによって異なります。

このページは簡単な概要です。詳細な推論リファレンスは、 [製品ドキュメント](/deployment/ja/readme.md)にあります。これは同じドキュメントサイトの一部です。より詳細な内容がある場所への相互リンクが提供されています。

#### 推論ランタイム

| ランタイム                                                 | 使用する場面                                                     | 参照                                                                                                                                                         |
| ----------------------------------------------------- | ---------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Serverless Hosted API** (`serverless.roboflow.com`) | デフォルト。ホスト型、自動スケーリング、モデルと Workflows をサポートします。               | [Serverless Hosted API](/deployment/ja/roboflow-cloud/serverless-api.md)                                                                                   |
| **Dedicated Deployment**                              | 予測可能なレイテンシ、高スループット、または固定の GPU 種別が必要な場合。Roboflow が管理します。    | [Dedicated Deployment](/deployment/ja/roboflow-cloud/dedicated-deployments.md#http-api) および [製品概要](/deployment/ja/roboflow-cloud/dedicated-deployments.md) |
| **Roboflow Inference** （セルフホスト型）                      | オンプレミス、エッジデバイス、エアギャップ環境、または VPC の外に出せないワークロード向け。オープンソースです。 | [セルフホスト型デプロイメント](/deployment/ja/serufuhosuto/self-hosted.md)                                                                                               |

#### サーバーレスホスト型 API の呼び出し

モデルを実行:

```bash
curl -F "file=@photo.jpg" \\
  "https://serverless.roboflow.com/<project>/<version>?api_key=$ROBOFLOW_API_KEY&confidence=0.5"
```

Workflow を実行:

```bash
curl -X POST "https://serverless.roboflow.com/infer/workflows/<workspace>/<workflow>" \\
  -H "Content-Type: application/json" \\
  -d '{
    "api_key": "'$ROBOFLOW_API_KEY'",
    "inputs": { "image": { "type": "url", "value": "https://example.com/photo.jpg" } }
  }'
```

ライブ動画については、 [サーバーレス動画ストリーミング API](/deployment/ja/roboflow-cloud/serverless-api/serverless-video-streaming-api.md)を参照してください。大規模な画像・動画セットの非同期処理については、 [バッチ処理](/deployment/ja/roboflow-cloud/batch-processing.md).

#### 非推奨: Serverless v1

レガシーなタスク固有のエンドポイント - `detect.roboflow.com`, `classify.roboflow.com`, `outline.roboflow.com`, `segment.roboflow.com` は **非推奨です**。後方互換性のために引き続き応答しますが、新しいコードでは `serverless.roboflow.com` を代わりに使用してください。

もし `*.roboflow.com` のタスクホストを指すスニペットを見つけたら、それはレガシーとして扱い、上記のサーバーレスホスト型 API 形式に変換してください。

## Python SDK

### Python SDK で使用する

Python で作業しているなら、サーバーレス API とやり取りする最も便利な方法は Inference Python SDK を使うことです。

を使用するには、 [Inference SDK](https://docs.roboflow.com/reference/inference/inference-sdk)まずインストールします:

```
pip install inference-sdk
```

サーバーレスホスト型 API にリクエストを送るには、次のコードを使用します:

<pre class="language-python"><code class="lang-python"><strong>from inference_sdk import InferenceHTTPClient
</strong>
CLIENT = InferenceHTTPClient(
    api_url="https://serverless.roboflow.com",
    api_key="API_KEY"
)

result = CLIENT.infer("image.jpg", model_id="model-id/1")
print(result)
</code></pre>

上記では、あなたの [モデルID](https://docs.roboflow.com/reference/authentication/authentication/workspace-and-project-ids) および [API key](https://docs.roboflow.com/reference/authentication/authentication/find-your-roboflow-api-key)を指定してください。このコードはモデルを実行し、結果を返します。

#### Roboflow Instant Model

サーバーレス API は、Roboflow の [Instant Model](https://docs.roboflow.com/models/train/roboflow-instant)の実行もサポートしています。Instant Model は他のモデルと同じように実行できますが、信頼度しきい値は Instant Model では感度が高い場合がある点に注意してください。

{% hint style="info" %}
最適な信頼度は、モデルが学習した画像の枚数によって異なります。最適なしきい値は通常 0.85 から 0.99 の範囲です。
{% endhint %}

```python
configuration = InferenceConfiguration(
    confidence_threshold=0.95
)
CLIENT.configure(configuration)

result = CLIENT.infer("image.jpg", model_id="roboflow-instant-model-id/1")
```

### Python SDK で動画をストリーミングする

Inference SDK の WebRTC クライアントを使って、動画上で物体検出モデルを実行します。サーバーレス動画ストリーミング API は Roboflow Cloud で動画を処理し、各フレームごとの予測を返します。

SDK とその WebRTC 依存関係をインストールし、 `supervision`:

```bash
pip install "inference-sdk[webrtc]" supervision
```

```python
import cv2
import supervision as sv
from inference_sdk import InferenceHTTPClient
from inference_sdk.webrtc import VideoFileSource

client = InferenceHTTPClient(
    api_url="https://serverless.roboflow.com",
    api_key="API_KEY",
)

session = client.webrtc.stream(
    source=VideoFileSource("video.mp4"),
    model_id="model-id/1",
)

box_annotator = sv.BoxAnnotator()
label_annotator = sv.LabelAnnotator()

@session.on_frame
def show(frame, data):
    if data is None:
        return

    detections = sv.Detections.from_inference(data)
    annotated = box_annotator.annotate(frame.copy(), detections)
    annotated = label_annotator.annotate(annotated, detections)
    cv2.imshow("Predictions", annotated)

    if cv2.waitKey(1) & 0xFF == ord("q"):
        session.close()

session.run()
cv2.destroyAllWindows()
```

置き換えてください `API_KEY` および `model-id/1` にあなたの API キーとモデル ID を指定してください。ウェブカメラや RTSP カメラからのストリーミング、すべてのフレームの処理、または次のガイドで Workflow を実行する方法を学べます。 [サーバーレス動画ストリーミング API ガイド](/deployment/ja/roboflow-cloud/serverless-api/serverless-video-streaming-api.md).

## CLI

Roboflow で学習したモデル、または次で利用できるオープンソースモデルを実行するために Roboflow CLI を使用できます。 [Roboflow Universe](https://universe.roboflow.com).

実行することで `roboflow infer` をコマンドラインで実行すると、CLI は画像を Roboflow API に送信し、予測結果を表示します。

### コマンド

```bash
roboflow infer <image-path> -m <project/version>
```

#### オプション

| フラグ                  | 説明                                                                                                |
| -------------------- | ------------------------------------------------------------------------------------------------- |
| `-m`, `--model`      | のモデル ID `project/version` 形式（必須）                                                                  |
| `-c`, `--confidence` | 信頼度しきい値、0.0〜1.0（デフォルト: 0.5）                                                                       |
| `-o`, `--overlap`    | 重なり/NMS しきい値、0.0〜1.0（デフォルト: 0.5）                                                                  |
| `-t`, `--type`       | モデルの種類（自動検出をスキップ）: `物体検出`, `分類`, `インスタンスセグメンテーション`, `semantic-segmentation`, `keypoint-detection` |

### 例

Roboflow Universe のオープンソースモデルを使って推論を実行します。たとえば、 [poker-cards](https://universe.roboflow.com/roboflow-100/poker-cards-cxcvz/model/1) データセット:

```bash
roboflow infer ~/Downloads/ace.jpg -m poker-cards-cxcvz/1 -c 0.7
```

ワークスペースは、設定済みのワークスペースが既定値になります。別のワークスペースのモデルを使うには:

```bash
roboflow infer photo.jpg -m poker-cards-cxcvz/1 -w roboflow-100
```

自動検出 API 呼び出しをスキップするには、モデルの種類を指定します:

```bash
roboflow infer photo.jpg -m my-project/3 -t object-detection
```

### JSON出力

次を使用します `--json` スクリプト作成や自動化のために構造化された予測データを取得するには:

```bash
roboflow infer photo.jpg -m my-project/3 --json
```

```json
{
  "predictions": [
    {
      "x": 1230.0,
      "y": 814.5,
      "width": 840.0,
      "height": 1273.0,
      "confidence": 0.882,
      "class": "Scissors",
      "class_id": 2
    }
  ]
}
```

対応しているすべてのパラメータは次で確認できます `roboflow infer --help`.