import * as tf from '@tensorflow/tfjs-node';
import { DecodeSegmentArgs } from './common';
import { ImageInput } from '../tensorflow/node';
export * from './common';
export type DetectSegmentArgs = {
    model: tf.InferenceModel;
    /** used for image resize when necessary, auto inferred from model shape */
    input_shape?: {
        width: number;
        height: number;
    };
} & Omit<DecodeSegmentArgs, 'output_boxes' | 'output_masks'> & ImageInput;
/**
 * boxes features:
 *   - x, y, width, height
 *   - highest confidence, class_index
 *   - mask coefficients for each channel
 *
 * mask features:
 * - [height, width, channel]: 0 for background, 1 for object
 *
 * The x, y, width, height are in pixel unit, NOT normalized in the range of [0, 1].
 * The the pixel units are scaled to the input_shape.
 *
 * The confidence are already normalized between 0 to 1.
 */
export declare function detectSegment(args: DetectSegmentArgs): Promise<import("./common").SegmentResult>;
/**
 * Sync version of `detectSegment`.
 */
export declare function detectSegmentSync(args: DetectSegmentArgs): import("./common").SegmentResult;