import type { MetadataBearer as __MetadataBearer } from "@smithy/types"; import type { DetectLabelsRequest, DetectLabelsResponse } from "../models/models_0"; /** * @public */ export type { __MetadataBearer }; /** * @public * * The input for {@link DetectLabelsCommand}. */ export interface DetectLabelsCommandInput extends DetectLabelsRequest { } /** * @public * * The output of {@link DetectLabelsCommand}. */ export interface DetectLabelsCommandOutput extends DetectLabelsResponse, __MetadataBearer { } declare const DetectLabelsCommand_base: { new (input: DetectLabelsCommandInput): import("@smithy/core/client").CommandImpl; new (input: DetectLabelsCommandInput): import("@smithy/core/client").CommandImpl; getEndpointParameterInstructions(): import("@smithy/types").EndpointParameterInstructions; }; /** *

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.

*

When getting labels, 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. These arguments are only valid when supplying GENERAL_LABELS as a * feature type.

*

* 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:

* *

The API returns the following information regarding the image, as part of the * ImageProperties structure:

* *

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.

* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript * import { RekognitionClient, DetectLabelsCommand } from "@aws-sdk/client-rekognition"; // ES Modules import * // const { RekognitionClient, DetectLabelsCommand } = require("@aws-sdk/client-rekognition"); // CommonJS import * // import type { RekognitionClientConfig } from "@aws-sdk/client-rekognition"; * const config = {}; // type is RekognitionClientConfig * const client = new RekognitionClient(config); * const input = { // DetectLabelsRequest * Image: { // Image * Bytes: new Uint8Array(), // e.g. Buffer.from("") or new TextEncoder().encode("") * S3Object: { // S3Object * Bucket: "STRING_VALUE", * Name: "STRING_VALUE", * Version: "STRING_VALUE", * }, * }, * MaxLabels: Number("int"), * MinConfidence: Number("float"), * Features: [ // DetectLabelsFeatureList * "GENERAL_LABELS" || "IMAGE_PROPERTIES", * ], * Settings: { // DetectLabelsSettings * GeneralLabels: { // GeneralLabelsSettings * LabelInclusionFilters: [ // GeneralLabelsFilterList * "STRING_VALUE", * ], * LabelExclusionFilters: [ * "STRING_VALUE", * ], * LabelCategoryInclusionFilters: [ * "STRING_VALUE", * ], * LabelCategoryExclusionFilters: [ * "STRING_VALUE", * ], * }, * ImageProperties: { // DetectLabelsImagePropertiesSettings * MaxDominantColors: Number("int"), * }, * }, * }; * const command = new DetectLabelsCommand(input); * const response = await client.send(command); * // { // DetectLabelsResponse * // Labels: [ // Labels * // { // Label * // Name: "STRING_VALUE", * // Confidence: Number("float"), * // Instances: [ // Instances * // { // Instance * // BoundingBox: { // BoundingBox * // Width: Number("float"), * // Height: Number("float"), * // Left: Number("float"), * // Top: Number("float"), * // }, * // Confidence: Number("float"), * // DominantColors: [ // DominantColors * // { // DominantColor * // Red: Number("int"), * // Blue: Number("int"), * // Green: Number("int"), * // HexCode: "STRING_VALUE", * // CSSColor: "STRING_VALUE", * // SimplifiedColor: "STRING_VALUE", * // PixelPercent: Number("float"), * // }, * // ], * // }, * // ], * // Parents: [ // Parents * // { // Parent * // Name: "STRING_VALUE", * // }, * // ], * // Aliases: [ // LabelAliases * // { // LabelAlias * // Name: "STRING_VALUE", * // }, * // ], * // Categories: [ // LabelCategories * // { // LabelCategory * // Name: "STRING_VALUE", * // }, * // ], * // }, * // ], * // OrientationCorrection: "ROTATE_0" || "ROTATE_90" || "ROTATE_180" || "ROTATE_270", * // LabelModelVersion: "STRING_VALUE", * // ImageProperties: { // DetectLabelsImageProperties * // Quality: { // DetectLabelsImageQuality * // Brightness: Number("float"), * // Sharpness: Number("float"), * // Contrast: Number("float"), * // }, * // DominantColors: [ * // { * // Red: Number("int"), * // Blue: Number("int"), * // Green: Number("int"), * // HexCode: "STRING_VALUE", * // CSSColor: "STRING_VALUE", * // SimplifiedColor: "STRING_VALUE", * // PixelPercent: Number("float"), * // }, * // ], * // Foreground: { // DetectLabelsImageForeground * // Quality: { * // Brightness: Number("float"), * // Sharpness: Number("float"), * // Contrast: Number("float"), * // }, * // DominantColors: "", * // }, * // Background: { // DetectLabelsImageBackground * // Quality: { * // Brightness: Number("float"), * // Sharpness: Number("float"), * // Contrast: Number("float"), * // }, * // DominantColors: "", * // }, * // }, * // }; * * ``` * * @param DetectLabelsCommandInput - {@link DetectLabelsCommandInput} * @returns {@link DetectLabelsCommandOutput} * @see {@link DetectLabelsCommandInput} for command's `input` shape. * @see {@link DetectLabelsCommandOutput} for command's `response` shape. * @see {@link RekognitionClientResolvedConfig | config} for RekognitionClient's `config` shape. * * @throws {@link AccessDeniedException} (client fault) *

You are not authorized to perform the action.

* * @throws {@link ImageTooLargeException} (client fault) *

The input image size exceeds the allowed limit. If you are calling * DetectProtectiveEquipment, the image size or resolution exceeds the allowed limit. For more * information, see Guidelines and quotas in Amazon Rekognition in the Amazon Rekognition Developer Guide. *

* * @throws {@link InternalServerError} (server fault) *

Amazon Rekognition experienced a service issue. Try your call again.

* * @throws {@link InvalidImageFormatException} (client fault) *

The provided image format is not supported.

* * @throws {@link InvalidParameterException} (client fault) *

Input parameter violated a constraint. Validate your parameter before calling the API * operation again.

* * @throws {@link InvalidS3ObjectException} (client fault) *

Amazon Rekognition is unable to access the S3 object specified in the request.

* * @throws {@link ProvisionedThroughputExceededException} (client fault) *

The number of requests exceeded your throughput limit. If you want to increase this * limit, contact Amazon Rekognition.

* * @throws {@link ThrottlingException} (server fault) *

Amazon Rekognition is temporarily unable to process the request. Try your call again.

* * @throws {@link RekognitionServiceException} *

Base exception class for all service exceptions from Rekognition service.

* * * @example To detect labels * ```javascript * // This operation detects labels in the supplied image * const input = { * Image: { * S3Object: { * Bucket: "mybucket", * Name: "myphoto" * } * }, * MaxLabels: 123, * MinConfidence: 70 * }; * const command = new DetectLabelsCommand(input); * const response = await client.send(command); * /* response is * { * Labels: [ * { * Confidence: 99.25072479248047, * Name: "People" * }, * { * Confidence: 99.25074005126953, * Name: "Person" * } * ] * } * *\/ * ``` * * @public */ export declare class DetectLabelsCommand extends DetectLabelsCommand_base { /** @internal type navigation helper, not in runtime. */ protected static __types: { api: { input: DetectLabelsRequest; output: DetectLabelsResponse; }; sdk: { input: DetectLabelsCommandInput; output: DetectLabelsCommandOutput; }; }; }