/**
 * @license
 * Copyright 2019 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
import * as tf from '@tensorflow/tfjs';
export declare const IMAGE_SIZE = 224;
export declare const MODEL_BASE_URL = "https://tmstore.blob.core.windows.net/models";
/**
 * the metadata to describe the model's creation,
 * includes the labels associated with the classes
 * and versioning information from training.
 */
export interface Metadata {
    tfjsVersion: string;
    tmVersion?: string;
    packageVersion: string;
    packageName: string;
    modelName?: string;
    timeStamp?: string;
    labels: string[];
    userMetadata?: unknown;
    grayscale?: boolean;
    imageSize?: number;
}
export interface ModelOptions {
    version?: number;
    checkpointUrl?: string;
    alpha?: number;
    trainingLayer?: string;
    modelBaseUrl?: string;
}
/**
 * Receives a Metadata object and fills in the optional fields such as timeStamp
 * @param data a Metadata object
 */
export declare const fillMetadata: (data: Partial<Metadata>) => Metadata;
export declare type ClassifierInputSource = HTMLImageElement | HTMLCanvasElement | HTMLVideoElement | ImageBitmap;
/**
 * Computes the probabilities of the topK classes given logits by computing
 * softmax to get probabilities and then sorting the probabilities.
 * @param logits Tensor representing the logits from MobileNet.
 * @param topK The number of top predictions to show.
 */
export declare function getTopKClasses(labels: string[], logits: tf.Tensor<tf.Rank>, topK?: number): Promise<any[]>;
/**
 * load the base mobilenet model
 * @param modelOptions options determining what model to load
 */
export declare function loadTruncatedMobileNet(modelOptions?: ModelOptions): Promise<tf.Sequential>;