import type { Image } from '../../Image.ts';
import type { Point } from '../../index_full.ts';

import { getEigenvaluesForScore } from './getEigenvaluesForScore.js';

export interface GetShiTomasiScoreOptions {
  qualityLevel?: number;
  /**
   * Size of the window to compute the Harris score.
   * Should be an odd number so that the window can be centered on the corner.
   * @default `7`
   */
  windowSize?: number;
}

/**
 * Get the Shi-Tomasi score of a corner. The idea is similar to Harris score, but it removes constant to calculate the score and just takes the minimum from two eigenvalues.
 * We distinguish 3 cases:
 * - the score is highly negative: you have an edge
 * - the absolute value of the score is small: the region is flat
 * - the score is highly positive: you have a corner.
 * @param image - Image to which the corner belongs. It must be a greyscale image with only one channel.
 * @param origin - Center of the window, where the corner should be.
 * @param options  - Get Shi-Tomasi score options.
 * @returns The Shi-Tomasi score.
 */
export function getShiTomasiScore(
  image: Image,
  origin: Point,
  options: GetShiTomasiScoreOptions = {},
): number {
  const { windowSize = 7 } = options;

  const eigenValues = getEigenvaluesForScore(image, origin, windowSize);
  return Math.min(eigenValues[0], eigenValues[1]);
}