/**
 * Result interface definition for **Human** library
 *
 * Contains all possible detection results
 */

/** Face results
 * Combined results of face detector, face mesh, age, gender, emotion, embedding, iris models
 * Some values may be null if specific model is not enabled
 *
 * Array of individual results with one object per detected face
 * Each result has:
 * - id: face number
 * - confidence: overal detection confidence value
 * - boxConfidence: face box detection confidence value
 * - faceConfidence: face keypoints detection confidence value
 * - box: face bounding box as array of [x, y, width, height], normalized to image resolution
 * - boxRaw: face bounding box as array of [x, y, width, height], normalized to range 0..1
 * - mesh: face keypoints as array of [x, y, z] points of face mesh, normalized to image resolution
 * - meshRaw: face keypoints as array of [x, y, z] points of face mesh, normalized to range 0..1
 * - annotations: annotated face keypoints as array of annotated face mesh points
 * - age: age as value
 * - gender: gender as value
 * - genderConfidence: gender detection confidence as value
 * - emotion: emotions as array of possible emotions with their individual scores
 * - embedding: facial descriptor as array of numerical elements
 * - iris: iris distance from current viewpoint as distance value
 * - rotation: face rotiation that contains both angles and matrix used for 3d transformations
 *  - angle: face angle as object with values for roll, yaw and pitch angles
 *  - matrix: 3d transofrmation matrix as array of numeric values
 * - tensor: face tensor as Tensor object which contains detected face
 */
export interface Face {
  id: number
  confidence: number,
  boxConfidence: number,
  faceConfidence: number,
  box: [number, number, number, number],
  boxRaw: [number, number, number, number],
  mesh: Array<[number, number, number]>
  meshRaw: Array<[number, number, number]>
  annotations: Array<{ part: string, points: Array<[number, number, number]>[] }>,
  age: number,
  gender: string,
  genderConfidence: number,
  emotion: Array<{ score: number, emotion: string }>,
  embedding: Array<number>,
  iris: number,
  rotation: {
    angle: { roll: number, yaw: number, pitch: number },
    matrix: [number, number, number, number, number, number, number, number, number],
  }
  tensor: any,
}

/** Body results
 *
 * Array of individual results with one object per detected body
 * Each results has:
 * - id:body id number
 * - score: overall detection score
 * - box: bounding box: x, y, width, height normalized to input image resolution
 * - boxRaw: bounding box: x, y, width, height normalized to 0..1
 * - keypoints: array of keypoints
 *  - part: body part name
 *  - position: body part position with x,y,z coordinates
 *  - score: body part score value
 *  - presence: body part presence value
 */

export interface Body {
  id: number,
  score: number,
  box?: [x: number, y: number, width: number, height: number],
  boxRaw?: [x: number, y: number, width: number, height: number],
  keypoints: Array<{
    part: string,
    position: { x: number, y: number, z: number },
    score: number,
    presence?: number,
  }>
}

/** Hand results
 *
 * Array of individual results with one object per detected hand
 * Each result has:
 * - confidence as value
 * - box as array of [x, y, width, height], normalized to image resolution
 * - boxRaw as array of [x, y, width, height], normalized to range 0..1
 * - landmarks as array of [x, y, z] points of hand, normalized to image resolution
 * - annotations as array of annotated face landmark points
 */
export interface Hand {
  id: number,
  confidence: number,
  box: [number, number, number, number],
  boxRaw: [number, number, number, number],
  landmarks: Array<[number, number, number]>,
  // annotations: Array<{ part: string, points: Array<[number, number, number]> }>,
  // annotations: Annotations,
  annotations: Record<string, Array<{ part: string, points: Array<[number, number, number]> }>>,
}

/** Object results
*
* Array of individual results with one object per detected gesture
* Each result has:
* - score as value
* - label as detected class name
* - center as array of [x, y], normalized to image resolution
* - centerRaw as array of [x, y], normalized to range 0..1
* - box as array of [x, y, width, height], normalized to image resolution
* - boxRaw as array of [x, y, width, height], normalized to range 0..1
*/
export interface Item {
  score: number,
  strideSize?: number,
  class: number,
  label: string,
  center?: number[],
  centerRaw?: number[],
  box: number[],
  boxRaw: number[],
}

/** Gesture results
 *
 * Array of individual results with one object per detected gesture
 * Each result has:
 * - part: part name and number where gesture was detected: face, iris, body, hand
 * - gesture: gesture detected
 */
export type Gesture =
  { 'face': number, gesture: string }
  | { 'iris': number, gesture: string }
  | { 'body': number, gesture: string }
  | { 'hand': number, gesture: string }

export interface Result {
  /** {@link Face}: detection & analysis results */
  face: Array<Face>,
  /** {@link Body}: detection & analysis results */
  body: Array<Body>,
  /** {@link Hand}: detection & analysis results */
  hand: Array<Hand>,
  /** {@link Gesture}: detection & analysis results */
  gesture: Array<Gesture>,
  /** {@link Object}: detection & analysis results */
  object: Array<Item>
  performance: { any },
  canvas: OffscreenCanvas | HTMLCanvasElement,
  timestamp: number,
}