Detect Custom Labels
| rekognition_detect_custom_labels | R Documentation |
This operation applies only to Amazon Rekognition Custom Labels¶
Description¶
This 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
detect_custom_labels 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, detect_custom_labels
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.
Usage¶
rekognition_detect_custom_labels(ProjectVersionArn, Image, MaxResults,
MinConfidence)
Arguments¶
ProjectVersionArn |
[required] The ARN of the model version that you want to use. Only models associated with Custom Labels projects accepted by the operation. If a provided ARN refers to a model version associated with a project for a different feature type, then an InvalidParameterException is returned. |
Image |
[required] Provides the input image either as bytes or an S3 object. You pass image bytes to an Amazon Rekognition API operation by using
the For more information, see Analyzing an Image Loaded from a Local File System in the Amazon Rekognition Developer Guide. You pass images stored in an S3 bucket to an Amazon Rekognition API
operation by using the The region for the S3 bucket containing the S3 object must match the region you use for Amazon Rekognition operations. If you use the AWS CLI to call Amazon Rekognition operations, passing image bytes using the Bytes property is not supported. You must first upload the image to an Amazon S3 bucket and then call the operation using the S3Object property. For Amazon Rekognition to process an S3 object, the user must have permission to access the S3 object. For more information, see How Amazon Rekognition works with IAM in the Amazon Rekognition Developer Guide. |
MaxResults |
Maximum number of results you want the service to return in the response. The service returns the specified number of highest confidence labels ranked from highest confidence to lowest. |
MinConfidence |
Specifies the minimum confidence level for the labels to return.
|
Value¶
A list with the following syntax:
list(
CustomLabels = list(
list(
Name = "string",
Confidence = 123.0,
Geometry = list(
BoundingBox = list(
Width = 123.0,
Height = 123.0,
Left = 123.0,
Top = 123.0
),
Polygon = list(
list(
X = 123.0,
Y = 123.0
)
)
)
)
)
)
Request syntax¶
svc$detect_custom_labels(
ProjectVersionArn = "string",
Image = list(
Bytes = raw,
S3Object = list(
Bucket = "string",
Name = "string",
Version = "string"
)
),
MaxResults = 123,
MinConfidence = 123.0
)