import { Tensor } from 'onnxruntime-node';
import type { InferenceSession } from 'onnxruntime-node';
import sharp from 'sharp';
export declare class BackgroundRemover {
    session: InferenceSession;
    mean: number[];
    std: number[];
    /**
     * Initalize the base parameters of the target model
     * @param {InferenceSession} session - onnxruntime inference session
     * @param {Array<number>} mean - Mean values for normalization [R, G, B]
     * @param {Array<number>} std - Standard deviation values [R, G, B]
     */
    constructor(session: InferenceSession, mean: number[], std: number[]);
    /**
     * Normalize an image for model input
     * @param {sharp.Sharp} image - Image buffer or path
     * @returns {Tensor} - Input tensor for ONNX model
     */
    normalize(image: sharp.Sharp): Promise<Tensor>;
    /**
     * Make the output masks for the input image using the inner session.
     * @param {sharp.Sharp} image - The input image
     * @returns {Promise<sharp.Sharp>} - Masked image
     */
    mask(image: sharp.Sharp): Promise<sharp.Sharp>;
}
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