Copyright	(c) 2013-2023 Brendan Hay
License	Mozilla Public License, v. 2.0.
Maintainer	Brendan Hay
Stability	auto-generated
Portability	non-portable (GHC extensions)
Safe Haskell	Safe-Inferred
Language	Haskell2010

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.

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.

Optional Parameters

You can specify one or both of the GENERAL_LABELS and IMAGE_PROPERTIES feature types when calling the DetectLabels API. Including GENERAL_LABELS will ensure the response includes the labels detected in the input image, while including IMAGE_PROPERTIES will ensure the response includes information about the image quality and color.

When using GENERAL_LABELS and/or IMAGE_PROPERTIES you can provide filtering criteria to the Settings parameter. You can filter with sets of individual labels or with label categories. You can specify inclusive filters, exclusive filters, or a combination of inclusive and exclusive filters. For more information on filtering see Detecting Labels in an Image.

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. The default and upper limit is 1000 labels.

Response Elements

For each object, scene, and concept the API returns one or more labels. The API returns the following types of information regarding labels:

Name - The name of the detected label.
Confidence - The level of confidence in the label assigned to a detected object.
Parents - The ancestor labels for a detected label. DetectLabels 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 includes the all ancestors for a label, where every ancestor is a unique label. In the previous example, Car, Vehicle, and Transportation are returned as unique labels in the response.
Aliases - Possible Aliases for the label.
Categories - The label categories that the detected label belongs to.
BoundingBox — Bounding boxes are described for all instances of detected common object labels, returned in an array of Instance objects. An Instance object contains a BoundingBox object, describing the location of the label on the input image. It also includes the confidence for the accuracy of the detected bounding box.

The API returns the following information regarding the image, as part of the ImageProperties structure:

Quality - Information about the Sharpness, Brightness, and Contrast of the input image, scored between 0 to 100. Image quality is returned for the entire image, as well as the background and the foreground.
Dominant Color - An array of the dominant colors in the image.
Foreground - Information about the sharpness, brightness, and dominant colors of the input image’s foreground.
Background - Information about the sharpness, brightness, and dominant colors of the input image’s background.

The list of returned labels will include at least one label for every detected object, along with information about that label. In the following example, suppose the input image has a lighthouse, the sea, and a rock. The response includes all three labels, one for each object, as well as the confidence in the label:

{Name: lighthouse, Confidence: 98.4629}

{Name: rock,Confidence: 79.2097}

 {Name: sea,Confidence: 75.061}

The list of labels can include multiple labels for the same object. 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.

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

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

Creating a Request

data DetectLabels Source #

See: newDetectLabels smart constructor.

Constructors

DetectLabels'

Fields

features :: Maybe [DetectLabelsFeatureName]
A list of the types of analysis to perform. Specifying GENERAL_LABELS uses the label detection feature, while specifying IMAGE_PROPERTIES returns information regarding image color and quality. If no option is specified GENERAL_LABELS is used by default.
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.
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.
settings :: Maybe DetectLabelsSettings
A list of the filters to be applied to returned detected labels and image properties. Specified filters can be inclusive, exclusive, or a combination of both. Filters can be used for individual labels or label categories. The exact label names or label categories must be supplied. For a full list of labels and label categories, see LINK HERE.
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

ToJSON DetectLabels Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Methods toJSON :: DetectLabels -> Value # toEncoding :: DetectLabels -> Encoding # toJSONList :: [DetectLabels] -> Value # toEncodingList :: [DetectLabels] -> Encoding #
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 #
AWSRequest DetectLabels Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Associated Types type AWSResponse DetectLabels # Methods request :: (Service -> Service) -> DetectLabels -> Request DetectLabels # response :: MonadResource m => (ByteStringLazy -> IO ByteStringLazy) -> Service -> Proxy DetectLabels -> ClientResponse ClientBody -> m (Either Error (ClientResponse (AWSResponse DetectLabels))) #
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 #
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 #
NFData DetectLabels Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Methods rnf :: DetectLabels -> () #
Eq DetectLabels Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Methods (==) :: DetectLabels -> DetectLabels -> Bool # (/=) :: DetectLabels -> DetectLabels -> Bool #
Hashable DetectLabels Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Methods hashWithSalt :: Int -> DetectLabels -> Int # hash :: DetectLabels -> Int #
type AWSResponse DetectLabels Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels type AWSResponse DetectLabels = DetectLabelsResponse
type Rep DetectLabels Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels type Rep DetectLabels = D1 ('MetaData "DetectLabels" "Amazonka.Rekognition.DetectLabels" "amazonka-rekognition-2.0-EaCrS9R3rWADqefEZvOx5B" 'False) (C1 ('MetaCons "DetectLabels'" 'PrefixI 'True) ((S1 ('MetaSel ('Just "features") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe [DetectLabelsFeatureName])) :: S1 ('MetaSel ('Just "maxLabels") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Natural))) :: (S1 ('MetaSel ('Just "minConfidence") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Double)) :: (S1 ('MetaSel ('Just "settings") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe DetectLabelsSettings)) :: S1 ('MetaSel ('Just "image") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Image)))))

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:features:DetectLabels', detectLabels_features - A list of the types of analysis to perform. Specifying GENERAL_LABELS uses the label detection feature, while specifying IMAGE_PROPERTIES returns information regarding image color and quality. If no option is specified GENERAL_LABELS is used by default.

$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.

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:settings:DetectLabels', detectLabels_settings - A list of the filters to be applied to returned detected labels and image properties. Specified filters can be inclusive, exclusive, or a combination of both. Filters can be used for individual labels or label categories. The exact label names or label categories must be supplied. For a full list of labels and label categories, see LINK HERE.

$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_features :: Lens' DetectLabels (Maybe [DetectLabelsFeatureName]) Source #

A list of the types of analysis to perform. Specifying GENERAL_LABELS uses the label detection feature, while specifying IMAGE_PROPERTIES returns information regarding image color and quality. If no option is specified GENERAL_LABELS is used by default.

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_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_settings :: Lens' DetectLabels (Maybe DetectLabelsSettings) Source #

A list of the filters to be applied to returned detected labels and image properties. Specified filters can be inclusive, exclusive, or a combination of both. Filters can be used for individual labels or label categories. The exact label names or label categories must be supplied. For a full list of labels and label categories, see LINK HERE.

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

imageProperties :: Maybe DetectLabelsImageProperties
Information about the properties of the input image, such as brightness, sharpness, contrast, and dominant colors.
labelModelVersion :: Maybe Text
Version number of the label detection model that was used to detect labels.
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.
httpStatus :: Int
The response's http status code.

Instances

Instances details

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 #
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 #
NFData DetectLabelsResponse Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Methods rnf :: DetectLabelsResponse -> () #
Eq DetectLabelsResponse Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels Methods (==) :: DetectLabelsResponse -> DetectLabelsResponse -> Bool # (/=) :: DetectLabelsResponse -> DetectLabelsResponse -> Bool #
type Rep DetectLabelsResponse Source #
Instance details Defined in Amazonka.Rekognition.DetectLabels type Rep DetectLabelsResponse = D1 ('MetaData "DetectLabelsResponse" "Amazonka.Rekognition.DetectLabels" "amazonka-rekognition-2.0-EaCrS9R3rWADqefEZvOx5B" 'False) (C1 ('MetaCons "DetectLabelsResponse'" 'PrefixI 'True) ((S1 ('MetaSel ('Just "imageProperties") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe DetectLabelsImageProperties)) :: S1 ('MetaSel ('Just "labelModelVersion") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text))) :: (S1 ('MetaSel ('Just "labels") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe [Label])) :: (S1 ('MetaSel ('Just "orientationCorrection") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe OrientationCorrection)) :: 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:

DetectLabelsResponse, detectLabelsResponse_imageProperties - Information about the properties of the input image, such as brightness, sharpness, contrast, and dominant colors.

$sel:labelModelVersion:DetectLabelsResponse', detectLabelsResponse_labelModelVersion - Version number of the label detection model that was used to detect 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:httpStatus:DetectLabelsResponse', detectLabelsResponse_httpStatus - The response's http status code.

Response Lenses

detectLabelsResponse_imageProperties :: Lens' DetectLabelsResponse (Maybe DetectLabelsImageProperties) Source #

Information about the properties of the input image, such as brightness, sharpness, contrast, and dominant colors.

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

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

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_httpStatus :: Lens' DetectLabelsResponse Int Source #

The response's http status code.