/// <reference types="node" />
/// <reference types="node" />
import { EventEmitter } from "tsee";
import { LinuxImpulseRunner, ModelInformation, RunnerClassifyResponseSuccess, RunnerHelloResponseModelParameters } from "./linux-impulse-runner";
import sharp, { FitEnum } from 'sharp';
import { ICamera } from "../sensors/icamera";
import * as models from "../../sdk/studio/sdk/model/models";
export declare const FitMethodMap: {
    [key: string]: keyof FitEnum;
};
export declare const FitMethodStudioMap: Record<Exclude<RunnerHelloResponseModelParameters["image_resize_mode"], undefined>, models.ImageInputResizeMode>;
export declare class ImageClassifier extends EventEmitter<{
    result: (result: RunnerClassifyResponseSuccess, timeMs: number, imgAsJpeg: Buffer) => void;
    profileSnapshotHandlerBegin: (filename: string) => void;
    profileSnapshotHandlerEnd: (filename: string) => void;
    profileFeaturesBegin: (filename: string) => void;
    profileFeaturesEnd: (filename: string) => void;
    profileClassifyBegin: (filename: string) => void;
    profileClassifyEnd: (filename: string, timingCpp: RunnerClassifyResponseSuccess['timing']) => void;
    profileEmitResultBegin: (filename: string) => void;
    profileEmitResultEnd: (filename: string) => void;
}> {
    private _runner;
    private _camera;
    private _stopped;
    private _runningInference;
    private _model;
    private _verbose;
    /**
     * Classifies realtime image data from a camera
     * @param runner An initialized impulse runner instance
     * @param camera An initialized ICamera instance
     */
    constructor(runner: LinuxImpulseRunner, camera: ICamera, opts?: {
        verbose?: boolean;
    });
    /**
     * Start the image classifier
     */
    start(): Promise<void>;
    resume(): void;
    pause(): void;
    /**
     * Stop the classifier
     */
    stop(): Promise<void>;
    setImageParameters(params: {
        image_width?: number;
        image_height?: number;
        image_channels?: number;
    }): Promise<void>;
    getRunner(): LinuxImpulseRunner;
    static resizeImage(model: ModelInformation, data: Buffer, metadata?: sharp.Metadata): Promise<{
        img: sharp.Sharp;
        features: number[];
        originalWidth: number;
        originalHeight: number;
        newWidth: number;
        newHeight: number;
    }>;
    static rgbBufferToFeatures(data: Buffer): number[];
    private classify;
}