/**
 * @license
 * Copyright 2021 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 deeplab from '@tensorflow-models/deeplab';
import { TaskModelLoader } from '../../task_model';
import { Runtime, Task, TFJSModelCommonLoadingOption } from '../common';
import { ImageSegmentationResult, ImageSegmenter } from './common';
declare type DeeplabNS = typeof deeplab;
/** Loading options. */
export interface DeeplabTFJSLoadingOptions extends TFJSModelCommonLoadingOption, deeplab.ModelConfig {
    /** The backend to use to run TFJS models. Default to 'webgl'. */
    backend: 'cpu' | 'webgl';
}
/** Inference options. */
export interface DeeplabTFJSInferenceOptions extends deeplab.PredictionConfig {
}
/** Loader for deeplab TFJS model. */
export declare class DeeplapTFJSLoader extends TaskModelLoader<DeeplabNS, DeeplabTFJSLoadingOptions, DeeplabTFJS> {
    readonly metadata: {
        name: string;
        description: string;
        resourceUrls: {
            'github': string;
        };
        runtime: Runtime;
        version: string;
        supportedTasks: Task[];
    };
    readonly packageUrls: string[][];
    readonly sourceModelGlobalNamespace = "deeplab";
    protected transformSourceModel(sourceModelGlobal: DeeplabNS, loadingOptions?: DeeplabTFJSLoadingOptions): Promise<DeeplabTFJS>;
}
/**
 * Pre-trained TFJS depelab model.
 *
 * Usage:
 *
 * ```js
 * // Load the model with options (optional).
 * //
 * // By default, it uses base='pascal' and quantizationBytes=2 with webgl
 * // backend. You can change them in the options parameter of the `load`
 * // function (see below for docs).
 * const model = await tfTask.ImageSegmentation.Deeplab.TFJS.load();
 *
 * // Run inference on an image with options (optional).
 * const img = document.querySelector('img');
 * const result = await model.predict(img);
 * console.log(result);
 *
 * // Clean up.
 * model.cleanUp();
 * ```
 *
 * Refer to `tfTask.ImageSegmenter` for the `predict` and `cleanUp` method.
 *
 * @docextratypes [
 *   {description: 'Options for `load`', symbol: 'DeeplabTFJSLoadingOptions'},
 *   {description: 'Options for `predict`', symbol:
 * 'DeeplabTFJSInferenceOptions'}
 * ]
 *
 * @doc {heading: 'Image Segmentation', subheading: 'Models'}
 */
export declare class DeeplabTFJS extends ImageSegmenter<DeeplabTFJSInferenceOptions> {
    private deeplabModel?;
    private loadingOptions?;
    constructor(deeplabModel?: deeplab.SemanticSegmentation, loadingOptions?: DeeplabTFJSLoadingOptions);
    predict(img: ImageData | HTMLImageElement | HTMLCanvasElement | HTMLVideoElement, infereceOptions?: DeeplabTFJSInferenceOptions): Promise<ImageSegmentationResult>;
    cleanUp(): void;
}
export declare const deeplabTfjsLoader: DeeplapTFJSLoader;
export {};