import * as tf from '@tensorflow/tfjs';
import { io } from '@tensorflow/tfjs-core';
import LearningInterface from './base';
declare class LearningMobilenet implements LearningInterface {
    model: tf.LayersModel | null;
    epochs: number;
    batchSize: number;
    learningRate: number;
    validateRate: number;
    isRunning: boolean;
    isReady: boolean;
    isTrainedDone: boolean;
    limitSize: number;
    mobilenetModule: tf.LayersModel | null;
    imageExamples: Float32Array[][];
    classNumber: string[];
    readonly MOBILE_NET_INPUT_WIDTH = 224;
    readonly MOBILE_NET_INPUT_HEIGHT = 224;
    readonly MOBILE_NET_INPUT_CHANNEL = 3;
    readonly IMAGE_NORMALIZATION_FACTOR = 255;
    constructor({ epochs, batchSize, limitSize, learningRate, validateRate, }?: {
        epochs?: number;
        batchSize?: number;
        limitSize?: number;
        learningRate?: number;
        validateRate?: number;
    });
    onProgress: (progress: number) => void;
    onLoss: (loss: number) => void;
    onEvents: (logs: any) => void;
    onTrainBegin: (log: any) => void;
    onTrainEnd: (log: any) => void;
    onEpochEnd: (epoch: number, logs: any) => void;
    load({ jsonURL, labels }: {
        jsonURL: string;
        labels: Array<string>;
    }): Promise<void>;
    private registerClassNumber;
    private _convertToTfDataset;
    addData(label: string, data: any): Promise<void>;
    init(): Promise<void>;
    private setupBackend;
    private checkWasmSupport;
    train(): Promise<tf.History>;
    infer(data: any): Promise<Map<string, number>>;
    saveModel(handlerOrURL: io.IOHandler | string, config?: io.SaveConfig): Promise<void>;
    running(): boolean;
    ready(): boolean;
    private _createModel;
}
export default LearningMobilenet;