{-# LANGUAGE DeriveGeneric #-}
{-# LANGUAGE DuplicateRecordFields #-}
{-# LANGUAGE NamedFieldPuns #-}
{-# LANGUAGE OverloadedStrings #-}
{-# LANGUAGE RecordWildCards #-}
{-# LANGUAGE StrictData #-}
{-# LANGUAGE TypeFamilies #-}
{-# LANGUAGE NoImplicitPrelude #-}
{-# OPTIONS_GHC -fno-warn-unused-binds #-}
{-# OPTIONS_GHC -fno-warn-unused-imports #-}
{-# OPTIONS_GHC -fno-warn-unused-matches #-}

-- Derived from AWS service descriptions, licensed under Apache 2.0.

-- |
-- Module      : Amazonka.Rekognition.IndexFaces
-- Copyright   : (c) 2013-2023 Brendan Hay
-- License     : Mozilla Public License, v. 2.0.
-- Maintainer  : Brendan Hay
-- Stability   : auto-generated
-- Portability : non-portable (GHC extensions)
--
-- 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.
module Amazonka.Rekognition.IndexFaces
  ( -- * Creating a Request
    IndexFaces (..),
    newIndexFaces,

    -- * Request Lenses
    indexFaces_detectionAttributes,
    indexFaces_externalImageId,
    indexFaces_maxFaces,
    indexFaces_qualityFilter,
    indexFaces_collectionId,
    indexFaces_image,

    -- * Destructuring the Response
    IndexFacesResponse (..),
    newIndexFacesResponse,

    -- * Response Lenses
    indexFacesResponse_faceModelVersion,
    indexFacesResponse_faceRecords,
    indexFacesResponse_orientationCorrection,
    indexFacesResponse_unindexedFaces,
    indexFacesResponse_httpStatus,
  )
where

import qualified Amazonka.Core as Core
import qualified Amazonka.Core.Lens.Internal as Lens
import qualified Amazonka.Data as Data
import qualified Amazonka.Prelude as Prelude
import Amazonka.Rekognition.Types
import qualified Amazonka.Request as Request
import qualified Amazonka.Response as Response

-- | /See:/ 'newIndexFaces' smart constructor.
data IndexFaces = IndexFaces'
  { -- | 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).
    detectionAttributes :: Prelude.Maybe [Attribute],
    -- | The ID you want to assign to all the faces detected in the image.
    externalImageId :: Prelude.Maybe Prelude.Text,
    -- | 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.
    maxFaces :: Prelude.Maybe Prelude.Natural,
    -- | 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.
    qualityFilter :: Prelude.Maybe QualityFilter,
    -- | The ID of an existing collection to which you want to add the faces that
    -- are detected in the input images.
    collectionId :: Prelude.Text,
    -- | 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.
    image :: Image
  }
  deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic)

-- |
-- Create a value of 'IndexFaces' with all optional fields omitted.
--
-- Use <https://hackage.haskell.org/package/generic-lens generic-lens> or <https://hackage.haskell.org/package/optics optics> to modify other optional fields.
--
-- The following record fields are available, with the corresponding lenses provided
-- for backwards compatibility:
--
-- 'detectionAttributes', '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).
--
-- 'externalImageId', 'indexFaces_externalImageId' - The ID you want to assign to all the faces detected in the image.
--
-- 'maxFaces', '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.
--
-- 'qualityFilter', '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.
--
-- 'collectionId', 'indexFaces_collectionId' - The ID of an existing collection to which you want to add the faces that
-- are detected in the input images.
--
-- 'image', '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.
newIndexFaces ::
  -- | 'collectionId'
  Prelude.Text ->
  -- | 'image'
  Image ->
  IndexFaces
newIndexFaces pCollectionId_ pImage_ =
  IndexFaces'
    { detectionAttributes = Prelude.Nothing,
      externalImageId = Prelude.Nothing,
      maxFaces = Prelude.Nothing,
      qualityFilter = Prelude.Nothing,
      collectionId = pCollectionId_,
      image = pImage_
    }

-- | 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_detectionAttributes :: Lens.Lens' IndexFaces (Prelude.Maybe [Attribute])
indexFaces_detectionAttributes = Lens.lens (\IndexFaces' {detectionAttributes} -> detectionAttributes) (\s@IndexFaces' {} a -> s {detectionAttributes = a} :: IndexFaces) Prelude.. Lens.mapping Lens.coerced

-- | The ID you want to assign to all the faces detected in the image.
indexFaces_externalImageId :: Lens.Lens' IndexFaces (Prelude.Maybe Prelude.Text)
indexFaces_externalImageId = Lens.lens (\IndexFaces' {externalImageId} -> externalImageId) (\s@IndexFaces' {} a -> s {externalImageId = a} :: IndexFaces)

-- | 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_maxFaces :: Lens.Lens' IndexFaces (Prelude.Maybe Prelude.Natural)
indexFaces_maxFaces = Lens.lens (\IndexFaces' {maxFaces} -> maxFaces) (\s@IndexFaces' {} a -> s {maxFaces = a} :: IndexFaces)

-- | 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_qualityFilter :: Lens.Lens' IndexFaces (Prelude.Maybe QualityFilter)
indexFaces_qualityFilter = Lens.lens (\IndexFaces' {qualityFilter} -> qualityFilter) (\s@IndexFaces' {} a -> s {qualityFilter = a} :: IndexFaces)

-- | The ID of an existing collection to which you want to add the faces that
-- are detected in the input images.
indexFaces_collectionId :: Lens.Lens' IndexFaces Prelude.Text
indexFaces_collectionId = Lens.lens (\IndexFaces' {collectionId} -> collectionId) (\s@IndexFaces' {} a -> s {collectionId = a} :: IndexFaces)

-- | 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.
indexFaces_image :: Lens.Lens' IndexFaces Image
indexFaces_image = Lens.lens (\IndexFaces' {image} -> image) (\s@IndexFaces' {} a -> s {image = a} :: IndexFaces)

instance Core.AWSRequest IndexFaces where
  type AWSResponse IndexFaces = IndexFacesResponse
  request overrides =
    Request.postJSON (overrides defaultService)
  response =
    Response.receiveJSON
      ( \s h x ->
          IndexFacesResponse'
            Prelude.<$> (x Data..?> "FaceModelVersion")
            Prelude.<*> (x Data..?> "FaceRecords" Core..!@ Prelude.mempty)
            Prelude.<*> (x Data..?> "OrientationCorrection")
            Prelude.<*> (x Data..?> "UnindexedFaces" Core..!@ Prelude.mempty)
            Prelude.<*> (Prelude.pure (Prelude.fromEnum s))
      )

instance Prelude.Hashable IndexFaces where
  hashWithSalt _salt IndexFaces' {..} =
    _salt
      `Prelude.hashWithSalt` detectionAttributes
      `Prelude.hashWithSalt` externalImageId
      `Prelude.hashWithSalt` maxFaces
      `Prelude.hashWithSalt` qualityFilter
      `Prelude.hashWithSalt` collectionId
      `Prelude.hashWithSalt` image

instance Prelude.NFData IndexFaces where
  rnf IndexFaces' {..} =
    Prelude.rnf detectionAttributes
      `Prelude.seq` Prelude.rnf externalImageId
      `Prelude.seq` Prelude.rnf maxFaces
      `Prelude.seq` Prelude.rnf qualityFilter
      `Prelude.seq` Prelude.rnf collectionId
      `Prelude.seq` Prelude.rnf image

instance Data.ToHeaders IndexFaces where
  toHeaders =
    Prelude.const
      ( Prelude.mconcat
          [ "X-Amz-Target"
              Data.=# ( "RekognitionService.IndexFaces" ::
                          Prelude.ByteString
                      ),
            "Content-Type"
              Data.=# ( "application/x-amz-json-1.1" ::
                          Prelude.ByteString
                      )
          ]
      )

instance Data.ToJSON IndexFaces where
  toJSON IndexFaces' {..} =
    Data.object
      ( Prelude.catMaybes
          [ ("DetectionAttributes" Data..=)
              Prelude.<$> detectionAttributes,
            ("ExternalImageId" Data..=)
              Prelude.<$> externalImageId,
            ("MaxFaces" Data..=) Prelude.<$> maxFaces,
            ("QualityFilter" Data..=) Prelude.<$> qualityFilter,
            Prelude.Just ("CollectionId" Data..= collectionId),
            Prelude.Just ("Image" Data..= image)
          ]
      )

instance Data.ToPath IndexFaces where
  toPath = Prelude.const "/"

instance Data.ToQuery IndexFaces where
  toQuery = Prelude.const Prelude.mempty

-- | /See:/ 'newIndexFacesResponse' smart constructor.
data IndexFacesResponse = IndexFacesResponse'
  { -- | The version number of the face detection model that\'s associated with
    -- the input collection (@CollectionId@).
    faceModelVersion :: Prelude.Maybe Prelude.Text,
    -- | 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.
    faceRecords :: Prelude.Maybe [FaceRecord],
    -- | 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.
    orientationCorrection :: Prelude.Maybe OrientationCorrection,
    -- | 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.
    unindexedFaces :: Prelude.Maybe [UnindexedFace],
    -- | The response's http status code.
    httpStatus :: Prelude.Int
  }
  deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic)

-- |
-- Create a value of 'IndexFacesResponse' with all optional fields omitted.
--
-- Use <https://hackage.haskell.org/package/generic-lens generic-lens> or <https://hackage.haskell.org/package/optics optics> to modify other optional fields.
--
-- The following record fields are available, with the corresponding lenses provided
-- for backwards compatibility:
--
-- 'faceModelVersion', 'indexFacesResponse_faceModelVersion' - The version number of the face detection model that\'s associated with
-- the input collection (@CollectionId@).
--
-- 'faceRecords', '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.
--
-- 'orientationCorrection', '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.
--
-- 'unindexedFaces', '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.
--
-- 'httpStatus', 'indexFacesResponse_httpStatus' - The response's http status code.
newIndexFacesResponse ::
  -- | 'httpStatus'
  Prelude.Int ->
  IndexFacesResponse
newIndexFacesResponse pHttpStatus_ =
  IndexFacesResponse'
    { faceModelVersion =
        Prelude.Nothing,
      faceRecords = Prelude.Nothing,
      orientationCorrection = Prelude.Nothing,
      unindexedFaces = Prelude.Nothing,
      httpStatus = pHttpStatus_
    }

-- | The version number of the face detection model that\'s associated with
-- the input collection (@CollectionId@).
indexFacesResponse_faceModelVersion :: Lens.Lens' IndexFacesResponse (Prelude.Maybe Prelude.Text)
indexFacesResponse_faceModelVersion = Lens.lens (\IndexFacesResponse' {faceModelVersion} -> faceModelVersion) (\s@IndexFacesResponse' {} a -> s {faceModelVersion = a} :: IndexFacesResponse)

-- | 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_faceRecords :: Lens.Lens' IndexFacesResponse (Prelude.Maybe [FaceRecord])
indexFacesResponse_faceRecords = Lens.lens (\IndexFacesResponse' {faceRecords} -> faceRecords) (\s@IndexFacesResponse' {} a -> s {faceRecords = a} :: IndexFacesResponse) Prelude.. Lens.mapping Lens.coerced

-- | 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_orientationCorrection :: Lens.Lens' IndexFacesResponse (Prelude.Maybe OrientationCorrection)
indexFacesResponse_orientationCorrection = Lens.lens (\IndexFacesResponse' {orientationCorrection} -> orientationCorrection) (\s@IndexFacesResponse' {} a -> s {orientationCorrection = a} :: IndexFacesResponse)

-- | 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.
indexFacesResponse_unindexedFaces :: Lens.Lens' IndexFacesResponse (Prelude.Maybe [UnindexedFace])
indexFacesResponse_unindexedFaces = Lens.lens (\IndexFacesResponse' {unindexedFaces} -> unindexedFaces) (\s@IndexFacesResponse' {} a -> s {unindexedFaces = a} :: IndexFacesResponse) Prelude.. Lens.mapping Lens.coerced

-- | The response's http status code.
indexFacesResponse_httpStatus :: Lens.Lens' IndexFacesResponse Prelude.Int
indexFacesResponse_httpStatus = Lens.lens (\IndexFacesResponse' {httpStatus} -> httpStatus) (\s@IndexFacesResponse' {} a -> s {httpStatus = a} :: IndexFacesResponse)

instance Prelude.NFData IndexFacesResponse where
  rnf IndexFacesResponse' {..} =
    Prelude.rnf faceModelVersion
      `Prelude.seq` Prelude.rnf faceRecords
      `Prelude.seq` Prelude.rnf orientationCorrection
      `Prelude.seq` Prelude.rnf unindexedFaces
      `Prelude.seq` Prelude.rnf httpStatus