libZSservicesZSamazonka-rekognitionZSamazonka-rekognition
Copyright(c) 2013-2021 Brendan Hay
LicenseMozilla Public License, v. 2.0.
MaintainerBrendan Hay <brendan.g.hay+amazonka@gmail.com>
Stabilityauto-generated
Portabilitynon-portable (GHC extensions)
Safe HaskellNone

Amazonka.Rekognition.IndexFaces

Description

Detects faces in the input image and adds them to the specified collection.

Amazon Rekognition doesn't save the actual faces that are detected. Instead, the underlying detection algorithm first detects the faces in the input image. For each face, the algorithm extracts facial features into a feature vector, and stores it in the backend database. Amazon Rekognition uses feature vectors when it performs face match and search operations using the SearchFaces and SearchFacesByImage operations.

For more information, see Adding Faces to a Collection in the Amazon Rekognition Developer Guide.

To get the number of faces in a collection, call DescribeCollection.

If you're using version 1.0 of the face detection model, IndexFaces indexes the 15 largest faces in the input image. Later versions of the face detection model index the 100 largest faces in the input image.

If you're using version 4 or later of the face model, image orientation information is not returned in the OrientationCorrection field.

To determine which version of the model you're using, call DescribeCollection and supply the collection ID. You can also get the model version from the value of FaceModelVersion in the response from IndexFaces

For more information, see Model Versioning in the Amazon Rekognition Developer Guide.

If you provide the optional ExternalImageId for the input image you provided, Amazon Rekognition associates this ID with all faces that it detects. When you call the ListFaces operation, the response returns the external ID. You can use this external image ID to create a client-side index to associate the faces with each image. You can then use the index to find all faces in an image.

You can specify the maximum number of faces to index with the MaxFaces input parameter. This is useful when you want to index the largest faces in an image and don't want to index smaller faces, such as those belonging to people standing in the background.

The QualityFilter input parameter allows you to filter out detected faces that don’t meet a required quality bar. The quality bar is based on a variety of common use cases. By default, IndexFaces chooses the quality bar that's used to filter faces. You can also explicitly choose the quality bar. Use QualityFilter, to set the quality bar by specifying LOW, MEDIUM, or HIGH. If you do not want to filter detected faces, specify NONE.

To use quality filtering, you need a collection associated with version 3 of the face model or higher. To get the version of the face model associated with a collection, call DescribeCollection.

Information about faces detected in an image, but not indexed, is returned in an array of UnindexedFace objects, UnindexedFaces. Faces aren't indexed for reasons such as:

  • The number of faces detected exceeds the value of the MaxFaces request parameter.
  • The face is too small compared to the image dimensions.
  • The face is too blurry.
  • The image is too dark.
  • The face has an extreme pose.
  • The face doesn’t have enough detail to be suitable for face search.

In response, the IndexFaces operation returns an array of metadata for all detected faces, FaceRecords. This includes:

  • The bounding box, BoundingBox, of the detected face.
  • A confidence value, Confidence, which indicates the confidence that the bounding box contains a face.
  • A face ID, FaceId, assigned by the service for each face that's detected and stored.
  • An image ID, ImageId, assigned by the service for the input image.

If you request all facial attributes (by using the detectionAttributes parameter), Amazon Rekognition returns detailed facial attributes, such as facial landmarks (for example, location of eye and mouth) and other facial attributes. If you provide the same image, specify the same collection, and use the same external ID in the IndexFaces operation, Amazon Rekognition doesn't save duplicate face metadata.

The input image is passed either 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 isn't supported. The image must be formatted as a PNG or JPEG file.

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

Synopsis

Creating a Request

data IndexFaces Source #

See: newIndexFaces smart constructor.

Constructors

IndexFaces' 

Fields

  • externalImageId :: Maybe Text

    The ID you want to assign to all the faces detected in the image.

  • qualityFilter :: Maybe QualityFilter

    A filter that specifies a quality bar for how much filtering is done to identify faces. Filtered faces aren't indexed. If you specify AUTO, Amazon Rekognition chooses the quality bar. If you specify LOW, MEDIUM, or HIGH, filtering removes all faces that don’t meet the chosen quality bar. The default value is AUTO. The quality bar is based on a variety of common use cases. Low-quality detections can occur for a number of reasons. Some examples are an object that's misidentified as a face, a face that's too blurry, or a face with a pose that's too extreme to use. If you specify NONE, no filtering is performed.

    To use quality filtering, the collection you are using must be associated with version 3 of the face model or higher.

  • maxFaces :: Maybe Natural

    The maximum number of faces to index. The value of MaxFaces must be greater than or equal to 1. IndexFaces returns no more than 100 detected faces in an image, even if you specify a larger value for MaxFaces.

    If IndexFaces detects more faces than the value of MaxFaces, the faces with the lowest quality are filtered out first. If there are still more faces than the value of MaxFaces, the faces with the smallest bounding boxes are filtered out (up to the number that's needed to satisfy the value of MaxFaces). Information about the unindexed faces is available in the UnindexedFaces array.

    The faces that are returned by IndexFaces are sorted by the largest face bounding box size to the smallest size, in descending order.

    MaxFaces can be used with a collection associated with any version of the face model.

  • detectionAttributes :: Maybe [Attribute]

    An array of facial attributes that you want to be returned. This can be the default list of attributes or all attributes. If you don't specify a value for Attributes or if you specify ["DEFAULT"], the API returns the following subset of facial attributes: BoundingBox, Confidence, Pose, Quality, and Landmarks. If you provide ["ALL"], all facial attributes are returned, but the operation takes longer to complete.

    If you provide both, ["ALL", "DEFAULT"], the service uses a logical AND operator to determine which attributes to return (in this case, all attributes).

  • collectionId :: Text

    The ID of an existing collection to which you want to add the faces that are detected in the input images.

  • 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 base64-encoded image bytes isn't supported.

    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

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Eq IndexFaces Source # 
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Read IndexFaces Source # 
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Show IndexFaces Source # 
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Generic IndexFaces Source # 
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Associated Types

type Rep IndexFaces :: Type -> Type #

NFData IndexFaces Source # 
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Methods

rnf :: IndexFaces -> () #

Hashable IndexFaces Source # 
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ToJSON IndexFaces Source # 
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AWSRequest IndexFaces Source # 
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Associated Types

type AWSResponse IndexFaces #

ToHeaders IndexFaces Source # 
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Methods

toHeaders :: IndexFaces -> [Header] #

ToPath IndexFaces Source # 
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ToQuery IndexFaces Source # 
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type Rep IndexFaces Source # 
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type Rep IndexFaces = D1 ('MetaData "IndexFaces" "Amazonka.Rekognition.IndexFaces" "libZSservicesZSamazonka-rekognitionZSamazonka-rekognition" 'False) (C1 ('MetaCons "IndexFaces'" 'PrefixI 'True) ((S1 ('MetaSel ('Just "externalImageId") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :*: (S1 ('MetaSel ('Just "qualityFilter") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe QualityFilter)) :*: S1 ('MetaSel ('Just "maxFaces") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Natural)))) :*: (S1 ('MetaSel ('Just "detectionAttributes") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe [Attribute])) :*: (S1 ('MetaSel ('Just "collectionId") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Text) :*: S1 ('MetaSel ('Just "image") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Image)))))
type AWSResponse IndexFaces Source # 
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Defined in Amazonka.Rekognition.IndexFaces

newIndexFaces Source #

Create a value of IndexFaces 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:externalImageId:IndexFaces', indexFaces_externalImageId - The ID you want to assign to all the faces detected in the image.

$sel:qualityFilter:IndexFaces', indexFaces_qualityFilter - A filter that specifies a quality bar for how much filtering is done to identify faces. Filtered faces aren't indexed. If you specify AUTO, Amazon Rekognition chooses the quality bar. If you specify LOW, MEDIUM, or HIGH, filtering removes all faces that don’t meet the chosen quality bar. The default value is AUTO. The quality bar is based on a variety of common use cases. Low-quality detections can occur for a number of reasons. Some examples are an object that's misidentified as a face, a face that's too blurry, or a face with a pose that's too extreme to use. If you specify NONE, no filtering is performed.

To use quality filtering, the collection you are using must be associated with version 3 of the face model or higher.

$sel:maxFaces:IndexFaces', indexFaces_maxFaces - The maximum number of faces to index. The value of MaxFaces must be greater than or equal to 1. IndexFaces returns no more than 100 detected faces in an image, even if you specify a larger value for MaxFaces.

If IndexFaces detects more faces than the value of MaxFaces, the faces with the lowest quality are filtered out first. If there are still more faces than the value of MaxFaces, the faces with the smallest bounding boxes are filtered out (up to the number that's needed to satisfy the value of MaxFaces). Information about the unindexed faces is available in the UnindexedFaces array.

The faces that are returned by IndexFaces are sorted by the largest face bounding box size to the smallest size, in descending order.

MaxFaces can be used with a collection associated with any version of the face model.

$sel:detectionAttributes:IndexFaces', indexFaces_detectionAttributes - An array of facial attributes that you want to be returned. This can be the default list of attributes or all attributes. If you don't specify a value for Attributes or if you specify ["DEFAULT"], the API returns the following subset of facial attributes: BoundingBox, Confidence, Pose, Quality, and Landmarks. If you provide ["ALL"], all facial attributes are returned, but the operation takes longer to complete.

If you provide both, ["ALL", "DEFAULT"], the service uses a logical AND operator to determine which attributes to return (in this case, all attributes).

$sel:collectionId:IndexFaces', indexFaces_collectionId - The ID of an existing collection to which you want to add the faces that are detected in the input images.

$sel:image:IndexFaces', indexFaces_image - The input image as base64-encoded bytes or an S3 object. If you use the AWS CLI to call Amazon Rekognition operations, passing base64-encoded image bytes isn't supported.

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

indexFaces_externalImageId :: Lens' IndexFaces (Maybe Text) Source #

The ID you want to assign to all the faces detected in the image.

indexFaces_qualityFilter :: Lens' IndexFaces (Maybe QualityFilter) Source #

A filter that specifies a quality bar for how much filtering is done to identify faces. Filtered faces aren't indexed. If you specify AUTO, Amazon Rekognition chooses the quality bar. If you specify LOW, MEDIUM, or HIGH, filtering removes all faces that don’t meet the chosen quality bar. The default value is AUTO. The quality bar is based on a variety of common use cases. Low-quality detections can occur for a number of reasons. Some examples are an object that's misidentified as a face, a face that's too blurry, or a face with a pose that's too extreme to use. If you specify NONE, no filtering is performed.

To use quality filtering, the collection you are using must be associated with version 3 of the face model or higher.

indexFaces_maxFaces :: Lens' IndexFaces (Maybe Natural) Source #

The maximum number of faces to index. The value of MaxFaces must be greater than or equal to 1. IndexFaces returns no more than 100 detected faces in an image, even if you specify a larger value for MaxFaces.

If IndexFaces detects more faces than the value of MaxFaces, the faces with the lowest quality are filtered out first. If there are still more faces than the value of MaxFaces, the faces with the smallest bounding boxes are filtered out (up to the number that's needed to satisfy the value of MaxFaces). Information about the unindexed faces is available in the UnindexedFaces array.

The faces that are returned by IndexFaces are sorted by the largest face bounding box size to the smallest size, in descending order.

MaxFaces can be used with a collection associated with any version of the face model.

indexFaces_detectionAttributes :: Lens' IndexFaces (Maybe [Attribute]) Source #

An array of facial attributes that you want to be returned. This can be the default list of attributes or all attributes. If you don't specify a value for Attributes or if you specify ["DEFAULT"], the API returns the following subset of facial attributes: BoundingBox, Confidence, Pose, Quality, and Landmarks. If you provide ["ALL"], all facial attributes are returned, but the operation takes longer to complete.

If you provide both, ["ALL", "DEFAULT"], the service uses a logical AND operator to determine which attributes to return (in this case, all attributes).

indexFaces_collectionId :: Lens' IndexFaces Text Source #

The ID of an existing collection to which you want to add the faces that are detected in the input images.

indexFaces_image :: Lens' IndexFaces 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 base64-encoded image bytes isn't supported.

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 IndexFacesResponse Source #

See: newIndexFacesResponse smart constructor.

Constructors

IndexFacesResponse' 

Fields

  • faceModelVersion :: Maybe Text

    The version number of the face detection model that's associated with the input collection (CollectionId).

  • faceRecords :: Maybe [FaceRecord]

    An array of faces detected and added to the collection. For more information, see Searching Faces in a Collection in the Amazon Rekognition Developer Guide.

  • orientationCorrection :: Maybe OrientationCorrection

    If your collection is associated with a face detection model that's later than version 3.0, the value of OrientationCorrection is always null and no orientation information is returned.

    If your collection is associated with a face detection model that's version 3.0 or earlier, the following applies:

    • 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. The value of OrientationCorrection is null.
    • If the image doesn't contain orientation information in its Exif metadata, Amazon Rekognition returns an estimated orientation (ROTATE_0, ROTATE_90, ROTATE_180, ROTATE_270). Amazon Rekognition doesn’t perform image correction for images. The bounding box coordinates aren't translated and represent the object locations before the image is rotated.

    Bounding box information is returned in the FaceRecords array. You can get the version of the face detection model by calling DescribeCollection.

  • unindexedFaces :: Maybe [UnindexedFace]

    An array of faces that were detected in the image but weren't indexed. They weren't indexed because the quality filter identified them as low quality, or the MaxFaces request parameter filtered them out. To use the quality filter, you specify the QualityFilter request parameter.

  • httpStatus :: Int

    The response's http status code.

Instances

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Eq IndexFacesResponse Source # 
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Read IndexFacesResponse Source # 
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Show IndexFacesResponse Source # 
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Generic IndexFacesResponse Source # 
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type Rep IndexFacesResponse :: Type -> Type #

NFData IndexFacesResponse Source # 
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Methods

rnf :: IndexFacesResponse -> () #

type Rep IndexFacesResponse Source # 
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type Rep IndexFacesResponse = D1 ('MetaData "IndexFacesResponse" "Amazonka.Rekognition.IndexFaces" "libZSservicesZSamazonka-rekognitionZSamazonka-rekognition" 'False) (C1 ('MetaCons "IndexFacesResponse'" 'PrefixI 'True) ((S1 ('MetaSel ('Just "faceModelVersion") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :*: S1 ('MetaSel ('Just "faceRecords") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe [FaceRecord]))) :*: (S1 ('MetaSel ('Just "orientationCorrection") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe OrientationCorrection)) :*: (S1 ('MetaSel ('Just "unindexedFaces") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe [UnindexedFace])) :*: S1 ('MetaSel ('Just "httpStatus") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Int)))))

newIndexFacesResponse Source #

Create a value of IndexFacesResponse 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:faceModelVersion:IndexFacesResponse', indexFacesResponse_faceModelVersion - The version number of the face detection model that's associated with the input collection (CollectionId).

$sel:faceRecords:IndexFacesResponse', indexFacesResponse_faceRecords - An array of faces detected and added to the collection. For more information, see Searching Faces in a Collection in the Amazon Rekognition Developer Guide.

$sel:orientationCorrection:IndexFacesResponse', indexFacesResponse_orientationCorrection - If your collection is associated with a face detection model that's later than version 3.0, the value of OrientationCorrection is always null and no orientation information is returned.

If your collection is associated with a face detection model that's version 3.0 or earlier, the following applies:

  • 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. The value of OrientationCorrection is null.
  • If the image doesn't contain orientation information in its Exif metadata, Amazon Rekognition returns an estimated orientation (ROTATE_0, ROTATE_90, ROTATE_180, ROTATE_270). Amazon Rekognition doesn’t perform image correction for images. The bounding box coordinates aren't translated and represent the object locations before the image is rotated.

Bounding box information is returned in the FaceRecords array. You can get the version of the face detection model by calling DescribeCollection.

$sel:unindexedFaces:IndexFacesResponse', indexFacesResponse_unindexedFaces - An array of faces that were detected in the image but weren't indexed. They weren't indexed because the quality filter identified them as low quality, or the MaxFaces request parameter filtered them out. To use the quality filter, you specify the QualityFilter request parameter.

$sel:httpStatus:IndexFacesResponse', indexFacesResponse_httpStatus - The response's http status code.

Response Lenses

indexFacesResponse_faceModelVersion :: Lens' IndexFacesResponse (Maybe Text) Source #

The version number of the face detection model that's associated with the input collection (CollectionId).

indexFacesResponse_faceRecords :: Lens' IndexFacesResponse (Maybe [FaceRecord]) Source #

An array of faces detected and added to the collection. For more information, see Searching Faces in a Collection in the Amazon Rekognition Developer Guide.

indexFacesResponse_orientationCorrection :: Lens' IndexFacesResponse (Maybe OrientationCorrection) Source #

If your collection is associated with a face detection model that's later than version 3.0, the value of OrientationCorrection is always null and no orientation information is returned.

If your collection is associated with a face detection model that's version 3.0 or earlier, the following applies:

  • 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. The value of OrientationCorrection is null.
  • If the image doesn't contain orientation information in its Exif metadata, Amazon Rekognition returns an estimated orientation (ROTATE_0, ROTATE_90, ROTATE_180, ROTATE_270). Amazon Rekognition doesn’t perform image correction for images. The bounding box coordinates aren't translated and represent the object locations before the image is rotated.

Bounding box information is returned in the FaceRecords array. You can get the version of the face detection model by calling DescribeCollection.

indexFacesResponse_unindexedFaces :: Lens' IndexFacesResponse (Maybe [UnindexedFace]) Source #

An array of faces that were detected in the image but weren't indexed. They weren't indexed because the quality filter identified them as low quality, or the MaxFaces request parameter filtered them out. To use the quality filter, you specify the QualityFilter request parameter.