Values.DetectCustomLabelsResponseSourceThis operation applies only to Amazon Rekognition Custom Labels. Detects custom labels in a supplied image by using an Amazon Rekognition Custom Labels model. You specify which version of a model version to use by using the ProjectVersionArn input parameter. You pass the input image as base64-encoded image bytes or as a reference to an image in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations, passing image bytes is not supported. The image must be either a PNG or JPEG formatted file. For each object that the model version detects on an image, the API returns a (CustomLabel) object in an array (CustomLabels). Each CustomLabel object provides the label name (Name), the level of confidence that the image contains the object (Confidence), and object location information, if it exists, for the label on the image (Geometry). To filter labels that are returned, specify a value for MinConfidence. DetectCustomLabelsLabels only returns labels with a confidence that's higher than the specified value. The value of MinConfidence maps to the assumed threshold values created during training. For more information, see Assumed threshold in the Amazon Rekognition Custom Labels Developer Guide. Amazon Rekognition Custom Labels metrics expresses an assumed threshold as a floating point value between 0-1. The range of MinConfidence normalizes the threshold value to a percentage value (0-100). Confidence responses from DetectCustomLabels are also returned as a percentage. You can use MinConfidence to change the precision and recall or your model. For more information, see Analyzing an image in the Amazon Rekognition Custom Labels Developer Guide. If you don't specify a value for MinConfidence, DetectCustomLabels returns labels based on the assumed threshold of each label. This is a stateless API operation. That is, the operation does not persist any data. This operation requires permissions to perform the rekognition:DetectCustomLabels action. For more information, see Analyzing an image in the Amazon Rekognition Custom Labels Developer Guide.
type nonrec t = {customLabels : CustomLabels.t option;An array of custom labels detected in the input image.
*)}type nonrec error = [ | `AccessDeniedException of AccessDeniedException.t| `ImageTooLargeException of ImageTooLargeException.t| `InternalServerError of InternalServerError.t| `InvalidImageFormatException of InvalidImageFormatException.t| `InvalidParameterException of InvalidParameterException.t| `InvalidS3ObjectException of InvalidS3ObjectException.t| `LimitExceededException of LimitExceededException.t| `ProvisionedThroughputExceededException of
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| `InternalServerError of unit
| `InvalidImageFormatException of unit
| `InvalidParameterException of unit
| `InvalidS3ObjectException of unit
| `LimitExceededException of unit
| `ProvisionedThroughputExceededException of unit
| `ResourceNotFoundException of unit
| `ResourceNotReadyException of unit
| `ThrottlingException of unit
| `Unknown_operation_error of string * string option ]val error_of_xml :
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| `InternalServerError of unit
| `InvalidImageFormatException of unit
| `InvalidParameterException of unit
| `InvalidS3ObjectException of unit
| `LimitExceededException of unit
| `ProvisionedThroughputExceededException of unit
| `ResourceNotFoundException of unit
| `ResourceNotReadyException of unit
| `ThrottlingException of unit
| `Unknown_operation_error of string * string option ]val to_value :
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