{-# LANGUAGE DeriveGeneric #-}
{-# LANGUAGE DuplicateRecordFields #-}
{-# LANGUAGE NamedFieldPuns #-}
{-# LANGUAGE OverloadedStrings #-}
{-# LANGUAGE RecordWildCards #-}
{-# LANGUAGE StrictData #-}
{-# LANGUAGE NoImplicitPrelude #-}
{-# 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.Types.Gender
-- Copyright   : (c) 2013-2023 Brendan Hay
-- License     : Mozilla Public License, v. 2.0.
-- Maintainer  : Brendan Hay
-- Stability   : auto-generated
-- Portability : non-portable (GHC extensions)
module Amazonka.Rekognition.Types.Gender 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.GenderType

-- | The predicted gender of a detected face.
--
-- Amazon Rekognition makes gender binary (male\/female) predictions based
-- on the physical appearance of a face in a particular image. This kind of
-- prediction is not designed to categorize a person’s gender identity, and
-- you shouldn\'t use Amazon Rekognition to make such a determination. For
-- example, a male actor wearing a long-haired wig and earrings for a role
-- might be predicted as female.
--
-- Using Amazon Rekognition to make gender binary predictions is best
-- suited for use cases where aggregate gender distribution statistics need
-- to be analyzed without identifying specific users. For example, the
-- percentage of female users compared to male users on a social media
-- platform.
--
-- We don\'t recommend using gender binary predictions to make decisions
-- that impact an individual\'s rights, privacy, or access to services.
--
-- /See:/ 'newGender' smart constructor.
data Gender = Gender'
  { -- | Level of confidence in the prediction.
    Gender -> Maybe Double
confidence :: Prelude.Maybe Prelude.Double,
    -- | The predicted gender of the face.
    Gender -> Maybe GenderType
value :: Prelude.Maybe GenderType
  }
  deriving (Gender -> Gender -> Bool
forall a. (a -> a -> Bool) -> (a -> a -> Bool) -> Eq a
/= :: Gender -> Gender -> Bool
$c/= :: Gender -> Gender -> Bool
== :: Gender -> Gender -> Bool
$c== :: Gender -> Gender -> Bool
Prelude.Eq, ReadPrec [Gender]
ReadPrec Gender
Int -> ReadS Gender
ReadS [Gender]
forall a.
(Int -> ReadS a)
-> ReadS [a] -> ReadPrec a -> ReadPrec [a] -> Read a
readListPrec :: ReadPrec [Gender]
$creadListPrec :: ReadPrec [Gender]
readPrec :: ReadPrec Gender
$creadPrec :: ReadPrec Gender
readList :: ReadS [Gender]
$creadList :: ReadS [Gender]
readsPrec :: Int -> ReadS Gender
$creadsPrec :: Int -> ReadS Gender
Prelude.Read, Int -> Gender -> ShowS
[Gender] -> ShowS
Gender -> String
forall a.
(Int -> a -> ShowS) -> (a -> String) -> ([a] -> ShowS) -> Show a
showList :: [Gender] -> ShowS
$cshowList :: [Gender] -> ShowS
show :: Gender -> String
$cshow :: Gender -> String
showsPrec :: Int -> Gender -> ShowS
$cshowsPrec :: Int -> Gender -> ShowS
Prelude.Show, forall x. Rep Gender x -> Gender
forall x. Gender -> Rep Gender x
forall a.
(forall x. a -> Rep a x) -> (forall x. Rep a x -> a) -> Generic a
$cto :: forall x. Rep Gender x -> Gender
$cfrom :: forall x. Gender -> Rep Gender x
Prelude.Generic)

-- |
-- Create a value of 'Gender' 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:
--
-- 'confidence', 'gender_confidence' - Level of confidence in the prediction.
--
-- 'value', 'gender_value' - The predicted gender of the face.
newGender ::
  Gender
newGender :: Gender
newGender =
  Gender'
    { $sel:confidence:Gender' :: Maybe Double
confidence = forall a. Maybe a
Prelude.Nothing,
      $sel:value:Gender' :: Maybe GenderType
value = forall a. Maybe a
Prelude.Nothing
    }

-- | Level of confidence in the prediction.
gender_confidence :: Lens.Lens' Gender (Prelude.Maybe Prelude.Double)
gender_confidence :: Lens' Gender (Maybe Double)
gender_confidence = forall s a b t. (s -> a) -> (s -> b -> t) -> Lens s t a b
Lens.lens (\Gender' {Maybe Double
confidence :: Maybe Double
$sel:confidence:Gender' :: Gender -> Maybe Double
confidence} -> Maybe Double
confidence) (\s :: Gender
s@Gender' {} Maybe Double
a -> Gender
s {$sel:confidence:Gender' :: Maybe Double
confidence = Maybe Double
a} :: Gender)

-- | The predicted gender of the face.
gender_value :: Lens.Lens' Gender (Prelude.Maybe GenderType)
gender_value :: Lens' Gender (Maybe GenderType)
gender_value = forall s a b t. (s -> a) -> (s -> b -> t) -> Lens s t a b
Lens.lens (\Gender' {Maybe GenderType
value :: Maybe GenderType
$sel:value:Gender' :: Gender -> Maybe GenderType
value} -> Maybe GenderType
value) (\s :: Gender
s@Gender' {} Maybe GenderType
a -> Gender
s {$sel:value:Gender' :: Maybe GenderType
value = Maybe GenderType
a} :: Gender)

instance Data.FromJSON Gender where
  parseJSON :: Value -> Parser Gender
parseJSON =
    forall a. String -> (Object -> Parser a) -> Value -> Parser a
Data.withObject
      String
"Gender"
      ( \Object
x ->
          Maybe Double -> Maybe GenderType -> Gender
Gender'
            forall (f :: * -> *) a b. Functor f => (a -> b) -> f a -> f b
Prelude.<$> (Object
x forall a. FromJSON a => Object -> Key -> Parser (Maybe a)
Data..:? Key
"Confidence")
            forall (f :: * -> *) a b. Applicative f => f (a -> b) -> f a -> f b
Prelude.<*> (Object
x forall a. FromJSON a => Object -> Key -> Parser (Maybe a)
Data..:? Key
"Value")
      )

instance Prelude.Hashable Gender where
  hashWithSalt :: Int -> Gender -> Int
hashWithSalt Int
_salt Gender' {Maybe Double
Maybe GenderType
value :: Maybe GenderType
confidence :: Maybe Double
$sel:value:Gender' :: Gender -> Maybe GenderType
$sel:confidence:Gender' :: Gender -> Maybe Double
..} =
    Int
_salt
      forall a. Hashable a => Int -> a -> Int
`Prelude.hashWithSalt` Maybe Double
confidence
      forall a. Hashable a => Int -> a -> Int
`Prelude.hashWithSalt` Maybe GenderType
value

instance Prelude.NFData Gender where
  rnf :: Gender -> ()
rnf Gender' {Maybe Double
Maybe GenderType
value :: Maybe GenderType
confidence :: Maybe Double
$sel:value:Gender' :: Gender -> Maybe GenderType
$sel:confidence:Gender' :: Gender -> Maybe Double
..} =
    forall a. NFData a => a -> ()
Prelude.rnf Maybe Double
confidence
      seq :: forall a b. a -> b -> b
`Prelude.seq` forall a. NFData a => a -> ()
Prelude.rnf Maybe GenderType
value