// Code generated by smithy-go-codegen DO NOT EDIT.

package rekognition

import (
	"context"
	awsmiddleware "github.com/aws/aws-sdk-go-v2/aws/middleware"
	"github.com/aws/aws-sdk-go-v2/aws/signer/v4"
	"github.com/aws/aws-sdk-go-v2/service/rekognition/types"
	"github.com/aws/smithy-go/middleware"
	smithyhttp "github.com/aws/smithy-go/transport/http"
)

// 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 (https://docs.aws.amazon.com/rekognition/latest/dg/labels-detect-labels-image.html)
// . 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 about
// 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 doesn't return any
// data. This operation requires permissions to perform the
// rekognition:DetectLabels action.
func (c *Client) DetectLabels(ctx context.Context, params *DetectLabelsInput, optFns ...func(*Options)) (*DetectLabelsOutput, error) {
	if params == nil {
		params = &DetectLabelsInput{}
	}

	result, metadata, err := c.invokeOperation(ctx, "DetectLabels", params, optFns, c.addOperationDetectLabelsMiddlewares)
	if err != nil {
		return nil, err
	}

	out := result.(*DetectLabelsOutput)
	out.ResultMetadata = metadata
	return out, nil
}

type DetectLabelsInput struct {

	// 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.
	//
	// This member is required.
	Image *types.Image

	// 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.
	Features []types.DetectLabelsFeatureName

	// Maximum number of labels you want the service to return in the response. The
	// service returns the specified number of highest confidence labels.
	MaxLabels *int32

	// 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.
	MinConfidence *float32

	// 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 Detecting labels (https://docs.aws.amazon.com/rekognition/latest/dg/labels.html)
	// .
	Settings *types.DetectLabelsSettings

	noSmithyDocumentSerde
}

type DetectLabelsOutput struct {

	// Information about the properties of the input image, such as brightness,
	// sharpness, contrast, and dominant colors.
	ImageProperties *types.DetectLabelsImageProperties

	// Version number of the label detection model that was used to detect labels.
	LabelModelVersion *string

	// An array of labels for the real-world objects detected.
	Labels []types.Label

	// 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.
	OrientationCorrection types.OrientationCorrection

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata

	noSmithyDocumentSerde
}

func (c *Client) addOperationDetectLabelsMiddlewares(stack *middleware.Stack, options Options) (err error) {
	err = stack.Serialize.Add(&awsAwsjson11_serializeOpDetectLabels{}, middleware.After)
	if err != nil {
		return err
	}
	err = stack.Deserialize.Add(&awsAwsjson11_deserializeOpDetectLabels{}, middleware.After)
	if err != nil {
		return err
	}
	if err = addSetLoggerMiddleware(stack, options); err != nil {
		return err
	}
	if err = awsmiddleware.AddClientRequestIDMiddleware(stack); err != nil {
		return err
	}
	if err = smithyhttp.AddComputeContentLengthMiddleware(stack); err != nil {
		return err
	}
	if err = addResolveEndpointMiddleware(stack, options); err != nil {
		return err
	}
	if err = v4.AddComputePayloadSHA256Middleware(stack); err != nil {
		return err
	}
	if err = addRetryMiddlewares(stack, options); err != nil {
		return err
	}
	if err = addHTTPSignerV4Middleware(stack, options); err != nil {
		return err
	}
	if err = awsmiddleware.AddRawResponseToMetadata(stack); err != nil {
		return err
	}
	if err = awsmiddleware.AddRecordResponseTiming(stack); err != nil {
		return err
	}
	if err = addClientUserAgent(stack, options); err != nil {
		return err
	}
	if err = smithyhttp.AddErrorCloseResponseBodyMiddleware(stack); err != nil {
		return err
	}
	if err = smithyhttp.AddCloseResponseBodyMiddleware(stack); err != nil {
		return err
	}
	if err = addOpDetectLabelsValidationMiddleware(stack); err != nil {
		return err
	}
	if err = stack.Initialize.Add(newServiceMetadataMiddleware_opDetectLabels(options.Region), middleware.Before); err != nil {
		return err
	}
	if err = awsmiddleware.AddRecursionDetection(stack); err != nil {
		return err
	}
	if err = addRequestIDRetrieverMiddleware(stack); err != nil {
		return err
	}
	if err = addResponseErrorMiddleware(stack); err != nil {
		return err
	}
	if err = addRequestResponseLogging(stack, options); err != nil {
		return err
	}
	return nil
}

func newServiceMetadataMiddleware_opDetectLabels(region string) *awsmiddleware.RegisterServiceMetadata {
	return &awsmiddleware.RegisterServiceMetadata{
		Region:        region,
		ServiceID:     ServiceID,
		SigningName:   "rekognition",
		OperationName: "DetectLabels",
	}
}