import type { MetadataBearer as __MetadataBearer } from "@smithy/types";
import type { StartSegmentDetectionRequest, StartSegmentDetectionResponse } from "../models/models_0";
/**
 * @public
 */
export type { __MetadataBearer };
/**
 * @public
 *
 * The input for {@link StartSegmentDetectionCommand}.
 */
export interface StartSegmentDetectionCommandInput extends StartSegmentDetectionRequest {
}
/**
 * @public
 *
 * The output of {@link StartSegmentDetectionCommand}.
 */
export interface StartSegmentDetectionCommandOutput extends StartSegmentDetectionResponse, __MetadataBearer {
}
declare const StartSegmentDetectionCommand_base: {
    new (input: StartSegmentDetectionCommandInput): import("@smithy/core/client").CommandImpl<StartSegmentDetectionCommandInput, StartSegmentDetectionCommandOutput, import("..").RekognitionClientResolvedConfig, import("..").ServiceInputTypes, import("..").ServiceOutputTypes>;
    new (input: StartSegmentDetectionCommandInput): import("@smithy/core/client").CommandImpl<StartSegmentDetectionCommandInput, StartSegmentDetectionCommandOutput, import("..").RekognitionClientResolvedConfig, import("..").ServiceInputTypes, import("..").ServiceOutputTypes>;
    getEndpointParameterInstructions(): import("@smithy/types").EndpointParameterInstructions;
};
/**
 * <p>Starts asynchronous detection of segment detection in a stored video.</p>
 *          <p>Amazon Rekognition Video can detect segments in a video stored in an Amazon S3 bucket. Use <a>Video</a> to specify the bucket name and
 *       the filename of the video. <code>StartSegmentDetection</code> returns a job identifier (<code>JobId</code>) which you use to get
 *       the results of the operation. When segment detection is finished, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic
 *       that you specify in <code>NotificationChannel</code>.</p>
 *          <p>You can use the <code>Filters</code> (<a>StartSegmentDetectionFilters</a>)
 *       input parameter to specify the minimum detection confidence returned in the response.
 *       Within <code>Filters</code>, use <code>ShotFilter</code> (<a>StartShotDetectionFilter</a>)
 *       to filter detected shots. Use  <code>TechnicalCueFilter</code> (<a>StartTechnicalCueDetectionFilter</a>)
 *       to filter technical cues. </p>
 *          <p>To get the results of the segment detection operation, first check that the status value published to the Amazon SNS
 *       topic is <code>SUCCEEDED</code>. if so, call <a>GetSegmentDetection</a> and pass the job identifier (<code>JobId</code>)
 *       from the initial call to <code>StartSegmentDetection</code>. </p>
 *          <p>For more information, see Detecting video segments in stored video in the Amazon Rekognition Developer Guide.</p>
 * @example
 * Use a bare-bones client and the command you need to make an API call.
 * ```javascript
 * import { RekognitionClient, StartSegmentDetectionCommand } from "@aws-sdk/client-rekognition"; // ES Modules import
 * // const { RekognitionClient, StartSegmentDetectionCommand } = 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 = { // StartSegmentDetectionRequest
 *   Video: { // Video
 *     S3Object: { // S3Object
 *       Bucket: "STRING_VALUE",
 *       Name: "STRING_VALUE",
 *       Version: "STRING_VALUE",
 *     },
 *   },
 *   ClientRequestToken: "STRING_VALUE",
 *   NotificationChannel: { // NotificationChannel
 *     SNSTopicArn: "STRING_VALUE", // required
 *     RoleArn: "STRING_VALUE", // required
 *   },
 *   JobTag: "STRING_VALUE",
 *   Filters: { // StartSegmentDetectionFilters
 *     TechnicalCueFilter: { // StartTechnicalCueDetectionFilter
 *       MinSegmentConfidence: Number("float"),
 *       BlackFrame: { // BlackFrame
 *         MaxPixelThreshold: Number("float"),
 *         MinCoveragePercentage: Number("float"),
 *       },
 *     },
 *     ShotFilter: { // StartShotDetectionFilter
 *       MinSegmentConfidence: Number("float"),
 *     },
 *   },
 *   SegmentTypes: [ // SegmentTypes // required
 *     "TECHNICAL_CUE" || "SHOT",
 *   ],
 * };
 * const command = new StartSegmentDetectionCommand(input);
 * const response = await client.send(command);
 * // { // StartSegmentDetectionResponse
 * //   JobId: "STRING_VALUE",
 * // };
 *
 * ```
 *
 * @param StartSegmentDetectionCommandInput - {@link StartSegmentDetectionCommandInput}
 * @returns {@link StartSegmentDetectionCommandOutput}
 * @see {@link StartSegmentDetectionCommandInput} for command's `input` shape.
 * @see {@link StartSegmentDetectionCommandOutput} for command's `response` shape.
 * @see {@link RekognitionClientResolvedConfig | config} for RekognitionClient's `config` shape.
 *
 * @throws {@link AccessDeniedException} (client fault)
 *  <p>You are not authorized to perform the action.</p>
 *
 * @throws {@link IdempotentParameterMismatchException} (client fault)
 *  <p>A <code>ClientRequestToken</code> input parameter was reused with an operation, but at least one of the other input
 *         parameters is different from the previous call to the operation.</p>
 *
 * @throws {@link InternalServerError} (server fault)
 *  <p>Amazon Rekognition experienced a service issue. Try your call again.</p>
 *
 * @throws {@link InvalidParameterException} (client fault)
 *  <p>Input parameter violated a constraint. Validate your parameter before calling the API
 *       operation again.</p>
 *
 * @throws {@link InvalidS3ObjectException} (client fault)
 *  <p>Amazon Rekognition is unable to access the S3 object specified in the request.</p>
 *
 * @throws {@link LimitExceededException} (client fault)
 *  <p>An Amazon Rekognition service limit was exceeded. For example, if you start too many jobs
 *             concurrently, subsequent calls to start operations (ex:
 *             <code>StartLabelDetection</code>) will raise a <code>LimitExceededException</code>
 *             exception (HTTP status code: 400) until the number of concurrently running jobs is below
 *             the Amazon Rekognition service limit. </p>
 *
 * @throws {@link ProvisionedThroughputExceededException} (client fault)
 *  <p>The number of requests exceeded your throughput limit. If you want to increase this
 *       limit, contact Amazon Rekognition.</p>
 *
 * @throws {@link ThrottlingException} (server fault)
 *  <p>Amazon Rekognition is temporarily unable to process the request. Try your call again.</p>
 *
 * @throws {@link VideoTooLargeException} (client fault)
 *  <p>The file size or duration of the supplied media is too large. The maximum file size is 10GB.
 *         The maximum duration is 6 hours. </p>
 *
 * @throws {@link RekognitionServiceException}
 * <p>Base exception class for all service exceptions from Rekognition service.</p>
 *
 *
 * @public
 */
export declare class StartSegmentDetectionCommand extends StartSegmentDetectionCommand_base {
    /** @internal type navigation helper, not in runtime. */
    protected static __types: {
        api: {
            input: StartSegmentDetectionRequest;
            output: StartSegmentDetectionResponse;
        };
        sdk: {
            input: StartSegmentDetectionCommandInput;
            output: StartSegmentDetectionCommandOutput;
        };
    };
}