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
). Note that for the DetectCustomLabelsLabels
operation,
Polygons
are not returned in the Geometry
section of the response.
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¶
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]
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.
detect_custom_labels
doesn't return any labels with a confidence value that's lower than this specified value. If you specify a value of 0,detect_custom_labels
returns all labels, regardless of the assumed threshold applied to each label. If you don't specify a value forMinConfidence
,detect_custom_labels
returns labels based on the assumed threshold of each label.
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$detect_custom_labels(
ProjectVersionArn = "string",
Image = list(
Bytes = raw,
S3Object = list(
Bucket = "string",
Name = "string",
Version = "string"
)
),
MaxResults = 123,
MinConfidence = 123.0
)
Examples¶
## Not run:
# Detects custom labels in an image with an Amazon Rekognition Custom
# Labels model
svc$detect_custom_labels(
Image = list(
S3Object = list(
Bucket = "custom-labels-console-us-east-1-1111111111",
Name = "assets/flowers_1_test_dataset/camellia4.jpg"
)
),
MaxResults = 100L,
MinConfidence = 50L,
ProjectVersionArn = "arn:aws:rekognition:us-east-1:111122223333:project/m..."
)
## End(Not run)