Copyright	(c) 2013-2021 Brendan Hay
License	Mozilla Public License, v. 2.0.
Maintainer	Brendan Hay <brendan.g.hay+amazonka@gmail.com>
Stability	auto-generated
Portability	non-portable (GHC extensions)
Safe Haskell	None

Amazonka.Rekognition.DetectLabels

Contents

Creating a Request
Request Lenses
Destructuring the Response
Response Lenses

Description

Detects instances of real-world entities within an image (JPEG or PNG) provided as input. This includes objects like flower, tree, and table; events like wedding, graduation, and birthday party; and concepts like landscape, evening, and nature.

For an example, see Analyzing Images Stored in an Amazon S3 Bucket in the Amazon Rekognition Developer Guide.

DetectLabels does not support the detection of activities. However, activity detection is supported for label detection in videos. For more information, see StartLabelDetection in the Amazon Rekognition Developer Guide.

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, scene, and concept the API returns one or more labels. Each label provides the object name, and the level of confidence that the image contains the object. For example, suppose the input image has a lighthouse, the sea, and a rock. The response includes all three labels, one for each object.

{Name: lighthouse, Confidence: 98.4629}

{Name: rock,Confidence: 79.2097}

 {Name: sea,Confidence: 75.061}

In the preceding example, the operation returns one label for each of the three objects. The operation can also return multiple labels for the same object in the image. For example, if the input image shows a flower (for example, a tulip), the operation might return the following three labels.

{Name: flower,Confidence: 99.0562}

{Name: plant,Confidence: 99.0562}

{Name: tulip,Confidence: 99.0562}

In this example, the detection algorithm more precisely identifies the flower as a tulip.

In response, the API returns an array of labels. In addition, the response also includes the orientation correction. Optionally, you can specify MinConfidence to control the confidence threshold for the labels returned. The default is 55%. You can also add the MaxLabels parameter to limit the number of labels returned.

If the object detected is a person, the operation doesn't provide the same facial details that the DetectFaces operation provides.

DetectLabels returns bounding boxes for instances of common object labels in an array of Instance objects. An Instance object contains a BoundingBox object, for the location of the label on the image. It also includes the confidence by which the bounding box was detected.

DetectLabels also returns a hierarchical taxonomy of detected labels. For example, a detected car might be assigned the label car. The label car has two parent labels: Vehicle (its parent) and Transportation (its grandparent). The response returns the entire list of ancestors for a label. Each ancestor is a unique label in the response. In the previous example, Car, Vehicle, and Transportation are returned as unique labels in the response.

This is a stateless API operation. That is, the operation does not persist any data.

This operation requires permissions to perform the rekognition:DetectLabels action.

Synopsis

data DetectLabels = DetectLabels' {
- minConfidence :: Maybe Double
- maxLabels :: Maybe Natural
- image :: Image
}
newDetectLabels :: Image -> DetectLabels
detectLabels_minConfidence :: Lens' DetectLabels (Maybe Double)
detectLabels_maxLabels :: Lens' DetectLabels (Maybe Natural)
detectLabels_image :: Lens' DetectLabels Image
data DetectLabelsResponse = DetectLabelsResponse' {
- labels :: Maybe [Label]
- orientationCorrection :: Maybe OrientationCorrection
- labelModelVersion :: Maybe Text
- httpStatus :: Int
}
newDetectLabelsResponse :: Int -> DetectLabelsResponse
detectLabelsResponse_labels :: Lens' DetectLabelsResponse (Maybe [Label])
detectLabelsResponse_orientationCorrection :: Lens' DetectLabelsResponse (Maybe OrientationCorrection)
detectLabelsResponse_labelModelVersion :: Lens' DetectLabelsResponse (Maybe Text)
detectLabelsResponse_httpStatus :: Lens' DetectLabelsResponse Int

Creating a Request

data DetectLabels Source #

See: newDetectLabels smart constructor.

Constructors

DetectLabels'

Fields

minConfidence :: Maybe Double
Specifies the minimum confidence level for the labels to return. Amazon Rekognition doesn't return any labels with confidence lower than this specified value.
If MinConfidence is not specified, the operation returns labels with a confidence values greater than or equal to 55 percent.
maxLabels :: Maybe Natural
Maximum number of labels you want the service to return in the response. The service returns the specified number of highest confidence labels.
image :: Image
The input image as base64-encoded bytes or an S3 object. If you use the AWS CLI to call Amazon Rekognition operations, passing image bytes is not supported. Images stored in an S3 Bucket do not need to be base64-encoded.
If you are using an AWS SDK to call Amazon Rekognition, you might not need to base64-encode image bytes passed using the Bytes field. For more information, see Images in the Amazon Rekognition developer guide.

Instances

Instances details

Eq DetectLabels Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Methods (==) :: DetectLabels -> DetectLabels -> Bool # (/=) :: DetectLabels -> DetectLabels -> Bool #
Read DetectLabels Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Methods readsPrec :: Int -> ReadS DetectLabels # readList :: ReadS [DetectLabels] # readPrec :: ReadPrec DetectLabels # readListPrec :: ReadPrec [DetectLabels] #
Show DetectLabels Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Methods showsPrec :: Int -> DetectLabels -> ShowS # show :: DetectLabels -> String # showList :: [DetectLabels] -> ShowS #
Generic DetectLabels Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Associated Types type Rep DetectLabels :: Type -> Type # Methods from :: DetectLabels -> Rep DetectLabels x # to :: Rep DetectLabels x -> DetectLabels #
NFData DetectLabels Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Methods rnf :: DetectLabels -> () #
Hashable DetectLabels Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Methods hashWithSalt :: Int -> DetectLabels -> Int # hash :: DetectLabels -> Int #
ToJSON DetectLabels Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Methods toJSON :: DetectLabels -> Value # toEncoding :: DetectLabels -> Encoding # toJSONList :: [DetectLabels] -> Value # toEncodingList :: [DetectLabels] -> Encoding #
AWSRequest DetectLabels Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Associated Types type AWSResponse DetectLabels # Methods request :: DetectLabels -> Request DetectLabels # response :: MonadResource m => Logger -> Service -> Proxy DetectLabels -> ClientResponse ClientBody -> m (Either Error (ClientResponse (AWSResponse DetectLabels))) #
ToHeaders DetectLabels Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Methods toHeaders :: DetectLabels -> [Header] #
ToPath DetectLabels Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Methods toPath :: DetectLabels -> ByteString #
ToQuery DetectLabels Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Methods toQuery :: DetectLabels -> QueryString #
type Rep DetectLabels Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels type Rep DetectLabels = D1 ('MetaData "DetectLabels" "Amazonka.Rekognition.DetectLabels" "libZSservicesZSamazonka-rekognitionZSamazonka-rekognition" 'False) (C1 ('MetaCons "DetectLabels'" 'PrefixI 'True) (S1 ('MetaSel ('Just "minConfidence") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Double)) :: (S1 ('MetaSel ('Just "maxLabels") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Natural)) :: S1 ('MetaSel ('Just "image") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Image))))
type AWSResponse DetectLabels Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels type AWSResponse DetectLabels = DetectLabelsResponse

newDetectLabels Source #

Arguments

:: Image	`$sel:image:DetectLabels'`
-> DetectLabels

Create a value of DetectLabels with all optional fields omitted.

Use generic-lens or optics to modify other optional fields.

The following record fields are available, with the corresponding lenses provided for backwards compatibility:

$sel:minConfidence:DetectLabels', detectLabels_minConfidence - Specifies the minimum confidence level for the labels to return. Amazon Rekognition doesn't return any labels with confidence lower than this specified value.

If MinConfidence is not specified, the operation returns labels with a confidence values greater than or equal to 55 percent.

$sel:maxLabels:DetectLabels', detectLabels_maxLabels - Maximum number of labels you want the service to return in the response. The service returns the specified number of highest confidence labels.

$sel:image:DetectLabels', detectLabels_image - The input image as base64-encoded bytes or an S3 object. If you use the AWS CLI to call Amazon Rekognition operations, passing image bytes is not supported. Images stored in an S3 Bucket do not need to be base64-encoded.

If you are using an AWS SDK to call Amazon Rekognition, you might not need to base64-encode image bytes passed using the Bytes field. For more information, see Images in the Amazon Rekognition developer guide.

Request Lenses

detectLabels_minConfidence :: Lens' DetectLabels (Maybe Double) Source #

Specifies the minimum confidence level for the labels to return. Amazon Rekognition doesn't return any labels with confidence lower than this specified value.

If MinConfidence is not specified, the operation returns labels with a confidence values greater than or equal to 55 percent.

detectLabels_maxLabels :: Lens' DetectLabels (Maybe Natural) Source #

Maximum number of labels you want the service to return in the response. The service returns the specified number of highest confidence labels.

detectLabels_image :: Lens' DetectLabels Image Source #

The input image as base64-encoded bytes or an S3 object. If you use the AWS CLI to call Amazon Rekognition operations, passing image bytes is not supported. Images stored in an S3 Bucket do not need to be base64-encoded.

If you are using an AWS SDK to call Amazon Rekognition, you might not need to base64-encode image bytes passed using the Bytes field. For more information, see Images in the Amazon Rekognition developer guide.

Destructuring the Response

data DetectLabelsResponse Source #

See: newDetectLabelsResponse smart constructor.

Constructors

DetectLabelsResponse'

Fields

labels :: Maybe [Label]
An array of labels for the real-world objects detected.
orientationCorrection :: Maybe OrientationCorrection
The value of OrientationCorrection is always null.
If the input image is in .jpeg format, it might contain exchangeable image file format (Exif) metadata that includes the image's orientation. Amazon Rekognition uses this orientation information to perform image correction. The bounding box coordinates are translated to represent object locations after the orientation information in the Exif metadata is used to correct the image orientation. Images in .png format don't contain Exif metadata.
Amazon Rekognition doesn’t perform image correction for images in .png format and .jpeg images without orientation information in the image Exif metadata. The bounding box coordinates aren't translated and represent the object locations before the image is rotated.
labelModelVersion :: Maybe Text
Version number of the label detection model that was used to detect labels.
httpStatus :: Int
The response's http status code.

Instances

Instances details

Eq DetectLabelsResponse Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Methods (==) :: DetectLabelsResponse -> DetectLabelsResponse -> Bool # (/=) :: DetectLabelsResponse -> DetectLabelsResponse -> Bool #
Read DetectLabelsResponse Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Methods readsPrec :: Int -> ReadS DetectLabelsResponse # readList :: ReadS [DetectLabelsResponse] # readPrec :: ReadPrec DetectLabelsResponse # readListPrec :: ReadPrec [DetectLabelsResponse] #
Show DetectLabelsResponse Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Methods showsPrec :: Int -> DetectLabelsResponse -> ShowS # show :: DetectLabelsResponse -> String # showList :: [DetectLabelsResponse] -> ShowS #
Generic DetectLabelsResponse Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Associated Types type Rep DetectLabelsResponse :: Type -> Type # Methods from :: DetectLabelsResponse -> Rep DetectLabelsResponse x # to :: Rep DetectLabelsResponse x -> DetectLabelsResponse #
NFData DetectLabelsResponse Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Methods rnf :: DetectLabelsResponse -> () #
type Rep DetectLabelsResponse Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels type Rep DetectLabelsResponse = D1 ('MetaData "DetectLabelsResponse" "Amazonka.Rekognition.DetectLabels" "libZSservicesZSamazonka-rekognitionZSamazonka-rekognition" 'False) (C1 ('MetaCons "DetectLabelsResponse'" 'PrefixI 'True) ((S1 ('MetaSel ('Just "labels") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe [Label])) :: S1 ('MetaSel ('Just "orientationCorrection") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe OrientationCorrection))) :: (S1 ('MetaSel ('Just "labelModelVersion") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :*: S1 ('MetaSel ('Just "httpStatus") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Int))))

newDetectLabelsResponse Source #

Arguments

:: Int	`$sel:httpStatus:DetectLabelsResponse'`
-> DetectLabelsResponse

Create a value of DetectLabelsResponse with all optional fields omitted.

Use generic-lens or optics to modify other optional fields.

The following record fields are available, with the corresponding lenses provided for backwards compatibility:

$sel:labels:DetectLabelsResponse', detectLabelsResponse_labels - An array of labels for the real-world objects detected.

$sel:orientationCorrection:DetectLabelsResponse', detectLabelsResponse_orientationCorrection - The value of OrientationCorrection is always null.

If the input image is in .jpeg format, it might contain exchangeable image file format (Exif) metadata that includes the image's orientation. Amazon Rekognition uses this orientation information to perform image correction. The bounding box coordinates are translated to represent object locations after the orientation information in the Exif metadata is used to correct the image orientation. Images in .png format don't contain Exif metadata.

Amazon Rekognition doesn’t perform image correction for images in .png format and .jpeg images without orientation information in the image Exif metadata. The bounding box coordinates aren't translated and represent the object locations before the image is rotated.

$sel:labelModelVersion:DetectLabelsResponse', detectLabelsResponse_labelModelVersion - Version number of the label detection model that was used to detect labels.

$sel:httpStatus:DetectLabelsResponse', detectLabelsResponse_httpStatus - The response's http status code.

Response Lenses

detectLabelsResponse_labels :: Lens' DetectLabelsResponse (Maybe [Label]) Source #

An array of labels for the real-world objects detected.

detectLabelsResponse_orientationCorrection :: Lens' DetectLabelsResponse (Maybe OrientationCorrection) Source #

The value of OrientationCorrection is always null.

If the input image is in .jpeg format, it might contain exchangeable image file format (Exif) metadata that includes the image's orientation. Amazon Rekognition uses this orientation information to perform image correction. The bounding box coordinates are translated to represent object locations after the orientation information in the Exif metadata is used to correct the image orientation. Images in .png format don't contain Exif metadata.

Amazon Rekognition doesn’t perform image correction for images in .png format and .jpeg images without orientation information in the image Exif metadata. The bounding box coordinates aren't translated and represent the object locations before the image is rotated.

detectLabelsResponse_labelModelVersion :: Lens' DetectLabelsResponse (Maybe Text) Source #

Version number of the label detection model that was used to detect labels.

detectLabelsResponse_httpStatus :: Lens' DetectLabelsResponse Int Source #

The response's http status code.