import type { CanvasLike, ImageDataLike } from "./dither/dither";
export type ImageStyle = "photo" | "illustration" | "unknown";
export type ImageKind = "photo" | "lowContrastPhoto" | "highContrastPhoto" | "flatIllustration" | "lineArt" | "textOrUi" | "pixelArt" | "unknown";
export interface ImageStyleMetrics {
    sampleCount: number;
    uniqueColorRatio: number;
    topColorCoverage: number;
    paletteEntropy: number;
    flatRatio: number;
    softChangeRatio: number;
    strongEdgeRatio: number;
    edgeDensity: number;
    horizontalEdgeRatio: number;
    verticalEdgeRatio: number;
    lumaStdDev: number;
    lumaP05: number;
    lumaP95: number;
    lumaRange: number;
    saturationMean: number;
    saturationStdDev: number;
    darkRatio: number;
    lightRatio: number;
    grayRatio: number;
    highSaturationRatio: number;
    warmPaperRatio: number;
    redRatio: number;
    darkNeutralRatio: number;
    photoTileRatio: number;
    flatTileRatio: number;
    textTileRatio: number;
    gradientTileRatio: number;
    transparentRatio: number;
}
export interface ImageStyleClassification {
    style: ImageStyle;
    kind: ImageKind;
    kindScores: Record<ImageKind, number>;
    confidence: number;
    photoScore: number;
    metrics: ImageStyleMetrics;
}
export interface ClassifyImageStyleOptions {
    /**
     * Longest side of the internal sample grid. Larger values are slower but can
     * preserve more detail for tiny repeated patterns.
     */
    maxSampleDimension?: number;
    /** Pixels at or below this alpha value are ignored. */
    transparentAlphaThreshold?: number;
    /**
     * Decision threshold for `photoScore`. Raise it to classify ambiguous images
     * as illustrations more often, lower it to classify them as photos more often.
     */
    photoThreshold?: number;
}
/**
 * Heuristically classify image data as a photo or an illustration.
 *
 * This does not use ML. It looks for signals that usually separate photos from
 * illustrations: color diversity, soft tonal changes, flat-color regions, edge
 * density, and saturation/luminance variation.
 */
export declare function classifyImageStyle(image: ImageDataLike, options?: ClassifyImageStyleOptions): ImageStyleClassification;
export declare function classifyCanvasImageStyle(canvas: CanvasLike, options?: ClassifyImageStyleOptions): ImageStyleClassification;
export declare function isPhotoImage(image: ImageDataLike, options?: ClassifyImageStyleOptions): boolean;
export declare function isIllustrationImage(image: ImageDataLike, options?: ClassifyImageStyleOptions): boolean;