import type { Rect as AppiumRect } from '@appium/types';
export interface Point {
    x: number;
    y: number;
}
export interface Region {
    left: number;
    top: number;
    width: number;
    height: number;
}
export interface Rect {
    x: number;
    y: number;
    width: number;
    height: number;
}
export type TemplateMatchingMethod = 'TM_CCOEFF' | 'TM_CCOEFF_NORMED' | 'TM_CCORR' | 'TM_CCORR_NORMED' | 'TM_SQDIFF' | 'TM_SQDIFF_NORMED';
export interface Match {
    score: number;
    x: number;
    y: number;
}
export interface MatchComputationResult {
    descriptor: any;
    keyPoints: any;
}
export type DetectorName = 'AKAZE' | 'AGAST' | 'BRISK' | 'FAST' | 'GFTT' | 'KAZE' | 'MSER' | 'ORB';
export type MatchFuncName = 'FlannBased' | 'BruteForce' | 'BruteForceL1' | 'BruteForceHamming' | 'BruteForceHammingLut' | 'BruteForceSL2';
export interface MatchingOptions {
    /**
     * One of possible OpenCV feature detector names from keys of the `AVAILABLE_DETECTORS` object.
     * Defaults to `'ORB'`. Some methods (FAST, AGAST, GFTT, SIFT, MSER) are not available in the
     * default OpenCV installation and have to be enabled manually before library compilation.
     */
    detectorName?: DetectorName;
    /**
     * The name of the matching function. Should be one of the keys of the `AVAILABLE_MATCHING_FUNCTIONS` object.
     * Defaults to `'BruteForce'`.
     */
    matchFunc?: MatchFuncName;
    /**
     * The maximum count of "good" matches (e.g. with minimal distances) or a function, which accepts
     * 3 arguments: the current distance, minimal distance, maximum distance and returns true or false
     * to include or exclude the match.
     */
    goodMatchesFactor?: number | ((distance: number, minDistance: number, maxDistance: number) => boolean);
    /**
     * Whether to return the resulting visualization as an image buffer (useful for debugging purposes).
     * Defaults to `false`.
     */
    visualize?: boolean;
}
export interface MatchingResult {
    count: number;
    totalCount: number;
    visualization?: Buffer | null;
    points1: Point[];
    rect1: Rect;
    points2: Point[];
    rect2: Rect;
}
export interface SimilarityOptions {
    /**
     * Whether to return the resulting visualization as an image buffer where difference regions are
     * highlighted with rectangles. Defaults to `false`.
     */
    visualize?: boolean;
    /**
     * The name of the template matching method. Acceptable values are: `TM_CCOEFF`, `TM_CCOEFF_NORMED` (default),
     * `TM_CCORR`, `TM_CCORR_NORMED`, `TM_SQDIFF`, `TM_SQDIFF_NORMED`. Defaults to `'TM_CCOEFF_NORMED'`.
     */
    method?: TemplateMatchingMethod;
}
export interface SimilarityResult {
    score: number;
    visualization?: Buffer | null;
}
export interface OccurrenceOptions {
    /**
     * Whether to return the resulting visualization as an image buffer where the matching region is
     * highlighted with a rectangle. If the multiple option is passed, all results are highlighted.
     * Defaults to `false`.
     */
    visualize?: boolean;
    /**
     * At what normalized threshold to reject a match. Defaults to `0.5`.
     */
    threshold?: number;
    /**
     * Whether to find multiple matches in the image. If `true` or a number, returns all matches above
     * the threshold. Defaults to `false`.
     */
    multiple?: boolean | number;
    /**
     * The pixel distance between matches we consider to be part of the same template match.
     * Defaults to `10`.
     */
    matchNeighbourThreshold?: number;
    /**
     * The name of the template matching method. Acceptable values are: `TM_CCOEFF`, `TM_CCOEFF_NORMED` (default),
     * `TM_CCORR`, `TM_CCORR_NORMED`, `TM_SQDIFF`, `TM_SQDIFF_NORMED`. Defaults to `'TM_CCOEFF_NORMED'`.
     */
    method?: TemplateMatchingMethod;
}
export interface OccurrenceResult {
    rect: AppiumRect;
    visualization?: Buffer | null;
    score: number;
    multiple?: OccurrenceResult[];
}
export interface OpenCVBindings {
    Mat: any;
    KeyPointVector: any;
    FeatureDetector: any;
    Scalar: new (...args: number[]) => any;
    Point: new (x: number, y: number) => any;
    DescriptorMatcher: new (matchFunc: string) => any;
    DMatchVector: new () => any;
    MatVector: new () => any;
    [key: string]: any;
}
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