{-# 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.DetectModerationLabels
-- 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 unsafe content in a specified JPEG or PNG format image. Use
-- @DetectModerationLabels@ to moderate images depending on your
-- requirements. For example, you might want to filter images that contain
-- nudity, but not images containing suggestive content.
--
-- To filter images, use the labels returned by @DetectModerationLabels@ to
-- determine which types of content are appropriate.
--
-- For information about moderation labels, see Detecting Unsafe Content in
-- the Amazon Rekognition Developer Guide.
--
-- You pass the input image 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 is not
-- supported. The image must be either a PNG or JPEG formatted file.
module Amazonka.Rekognition.DetectModerationLabels
  ( -- * Creating a Request
    DetectModerationLabels (..),
    newDetectModerationLabels,

    -- * Request Lenses
    detectModerationLabels_humanLoopConfig,
    detectModerationLabels_minConfidence,
    detectModerationLabels_image,

    -- * Destructuring the Response
    DetectModerationLabelsResponse (..),
    newDetectModerationLabelsResponse,

    -- * Response Lenses
    detectModerationLabelsResponse_humanLoopActivationOutput,
    detectModerationLabelsResponse_moderationLabels,
    detectModerationLabelsResponse_moderationModelVersion,
    detectModerationLabelsResponse_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:/ 'newDetectModerationLabels' smart constructor.
data DetectModerationLabels = DetectModerationLabels'
  { -- | Sets up the configuration for human evaluation, including the
    -- FlowDefinition the image will be sent to.
    humanLoopConfig :: Prelude.Maybe HumanLoopConfig,
    -- | Specifies the minimum confidence level for the labels to return. Amazon
    -- Rekognition doesn\'t return any labels with a confidence level lower
    -- than this specified value.
    --
    -- If you don\'t specify @MinConfidence@, the operation returns labels with
    -- confidence values greater than or equal to 50 percent.
    minConfidence :: Prelude.Maybe Prelude.Double,
    -- | 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 is not 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 'DetectModerationLabels' 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:
--
-- 'humanLoopConfig', 'detectModerationLabels_humanLoopConfig' - Sets up the configuration for human evaluation, including the
-- FlowDefinition the image will be sent to.
--
-- 'minConfidence', 'detectModerationLabels_minConfidence' - Specifies the minimum confidence level for the labels to return. Amazon
-- Rekognition doesn\'t return any labels with a confidence level lower
-- than this specified value.
--
-- If you don\'t specify @MinConfidence@, the operation returns labels with
-- confidence values greater than or equal to 50 percent.
--
-- 'image', 'detectModerationLabels_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 is not 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.
newDetectModerationLabels ::
  -- | 'image'
  Image ->
  DetectModerationLabels
newDetectModerationLabels pImage_ =
  DetectModerationLabels'
    { humanLoopConfig =
        Prelude.Nothing,
      minConfidence = Prelude.Nothing,
      image = pImage_
    }

-- | Sets up the configuration for human evaluation, including the
-- FlowDefinition the image will be sent to.
detectModerationLabels_humanLoopConfig :: Lens.Lens' DetectModerationLabels (Prelude.Maybe HumanLoopConfig)
detectModerationLabels_humanLoopConfig = Lens.lens (\DetectModerationLabels' {humanLoopConfig} -> humanLoopConfig) (\s@DetectModerationLabels' {} a -> s {humanLoopConfig = a} :: DetectModerationLabels)

-- | Specifies the minimum confidence level for the labels to return. Amazon
-- Rekognition doesn\'t return any labels with a confidence level lower
-- than this specified value.
--
-- If you don\'t specify @MinConfidence@, the operation returns labels with
-- confidence values greater than or equal to 50 percent.
detectModerationLabels_minConfidence :: Lens.Lens' DetectModerationLabels (Prelude.Maybe Prelude.Double)
detectModerationLabels_minConfidence = Lens.lens (\DetectModerationLabels' {minConfidence} -> minConfidence) (\s@DetectModerationLabels' {} a -> s {minConfidence = a} :: DetectModerationLabels)

-- | 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 is not 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.
detectModerationLabels_image :: Lens.Lens' DetectModerationLabels Image
detectModerationLabels_image = Lens.lens (\DetectModerationLabels' {image} -> image) (\s@DetectModerationLabels' {} a -> s {image = a} :: DetectModerationLabels)

instance Core.AWSRequest DetectModerationLabels where
  type
    AWSResponse DetectModerationLabels =
      DetectModerationLabelsResponse
  request overrides =
    Request.postJSON (overrides defaultService)
  response =
    Response.receiveJSON
      ( \s h x ->
          DetectModerationLabelsResponse'
            Prelude.<$> (x Data..?> "HumanLoopActivationOutput")
            Prelude.<*> ( x
                            Data..?> "ModerationLabels"
                            Core..!@ Prelude.mempty
                        )
            Prelude.<*> (x Data..?> "ModerationModelVersion")
            Prelude.<*> (Prelude.pure (Prelude.fromEnum s))
      )

instance Prelude.Hashable DetectModerationLabels where
  hashWithSalt _salt DetectModerationLabels' {..} =
    _salt
      `Prelude.hashWithSalt` humanLoopConfig
      `Prelude.hashWithSalt` minConfidence
      `Prelude.hashWithSalt` image

instance Prelude.NFData DetectModerationLabels where
  rnf DetectModerationLabels' {..} =
    Prelude.rnf humanLoopConfig
      `Prelude.seq` Prelude.rnf minConfidence
      `Prelude.seq` Prelude.rnf image

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

instance Data.ToJSON DetectModerationLabels where
  toJSON DetectModerationLabels' {..} =
    Data.object
      ( Prelude.catMaybes
          [ ("HumanLoopConfig" Data..=)
              Prelude.<$> humanLoopConfig,
            ("MinConfidence" Data..=) Prelude.<$> minConfidence,
            Prelude.Just ("Image" Data..= image)
          ]
      )

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

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

-- | /See:/ 'newDetectModerationLabelsResponse' smart constructor.
data DetectModerationLabelsResponse = DetectModerationLabelsResponse'
  { -- | Shows the results of the human in the loop evaluation.
    humanLoopActivationOutput :: Prelude.Maybe HumanLoopActivationOutput,
    -- | Array of detected Moderation labels and the time, in milliseconds from
    -- the start of the video, they were detected.
    moderationLabels :: Prelude.Maybe [ModerationLabel],
    -- | Version number of the moderation detection model that was used to detect
    -- unsafe content.
    moderationModelVersion :: Prelude.Maybe Prelude.Text,
    -- | The response's http status code.
    httpStatus :: Prelude.Int
  }
  deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic)

-- |
-- Create a value of 'DetectModerationLabelsResponse' 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:
--
-- 'humanLoopActivationOutput', 'detectModerationLabelsResponse_humanLoopActivationOutput' - Shows the results of the human in the loop evaluation.
--
-- 'moderationLabels', 'detectModerationLabelsResponse_moderationLabels' - Array of detected Moderation labels and the time, in milliseconds from
-- the start of the video, they were detected.
--
-- 'moderationModelVersion', 'detectModerationLabelsResponse_moderationModelVersion' - Version number of the moderation detection model that was used to detect
-- unsafe content.
--
-- 'httpStatus', 'detectModerationLabelsResponse_httpStatus' - The response's http status code.
newDetectModerationLabelsResponse ::
  -- | 'httpStatus'
  Prelude.Int ->
  DetectModerationLabelsResponse
newDetectModerationLabelsResponse pHttpStatus_ =
  DetectModerationLabelsResponse'
    { humanLoopActivationOutput =
        Prelude.Nothing,
      moderationLabels = Prelude.Nothing,
      moderationModelVersion = Prelude.Nothing,
      httpStatus = pHttpStatus_
    }

-- | Shows the results of the human in the loop evaluation.
detectModerationLabelsResponse_humanLoopActivationOutput :: Lens.Lens' DetectModerationLabelsResponse (Prelude.Maybe HumanLoopActivationOutput)
detectModerationLabelsResponse_humanLoopActivationOutput = Lens.lens (\DetectModerationLabelsResponse' {humanLoopActivationOutput} -> humanLoopActivationOutput) (\s@DetectModerationLabelsResponse' {} a -> s {humanLoopActivationOutput = a} :: DetectModerationLabelsResponse)

-- | Array of detected Moderation labels and the time, in milliseconds from
-- the start of the video, they were detected.
detectModerationLabelsResponse_moderationLabels :: Lens.Lens' DetectModerationLabelsResponse (Prelude.Maybe [ModerationLabel])
detectModerationLabelsResponse_moderationLabels = Lens.lens (\DetectModerationLabelsResponse' {moderationLabels} -> moderationLabels) (\s@DetectModerationLabelsResponse' {} a -> s {moderationLabels = a} :: DetectModerationLabelsResponse) Prelude.. Lens.mapping Lens.coerced

-- | Version number of the moderation detection model that was used to detect
-- unsafe content.
detectModerationLabelsResponse_moderationModelVersion :: Lens.Lens' DetectModerationLabelsResponse (Prelude.Maybe Prelude.Text)
detectModerationLabelsResponse_moderationModelVersion = Lens.lens (\DetectModerationLabelsResponse' {moderationModelVersion} -> moderationModelVersion) (\s@DetectModerationLabelsResponse' {} a -> s {moderationModelVersion = a} :: DetectModerationLabelsResponse)

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

instance
  Prelude.NFData
    DetectModerationLabelsResponse
  where
  rnf DetectModerationLabelsResponse' {..} =
    Prelude.rnf humanLoopActivationOutput
      `Prelude.seq` Prelude.rnf moderationLabels
      `Prelude.seq` Prelude.rnf moderationModelVersion
      `Prelude.seq` Prelude.rnf httpStatus