Result interface definition for Human library

Contains all possible detection results

### Hierarchy

- Result

## Index

### Properties

- body
- canvas
- face
- gesture
- hand
- object
- performance

## Properties

### body

body: { id: number; part: string; position: { x: number; y: number; z: number }; presence: number; score: number }[]

Body results

Array of individual results with one object per detected body Each results has:

- body id number
- body part name
- part position with x,y,z coordinates
- body part score value
- body part presence value

### canvas

canvas: HTMLCanvasElement | OffscreenCanvas

### face

face: { age: number; annotations: { part: string; points: [number, number, number][][] }[]; box: [number, number, number, number]; boxConfidence: number; boxRaw: [number, number, number, number]; confidence: number; embedding: number[]; emotion: { emotion: string; score: number }[]; faceConfidence: number; gender: string; genderConfidence: number; iris: number; mesh: [number, number, number][]; meshRaw: [number, number, number][]; rotation: { angle: { pitch: number; roll: number; yaw: number }; matrix: [number, number, number, number, number, number, number, number, number][] }; tensor: any }[]

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:

- overal detection confidence value
- box detection confidence value
- mesh detection confidence 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
- mesh as array of [x, y, z] points of face mesh, normalized to image resolution
- meshRaw as array of [x, y, z] points of face mesh, normalized to range 0..1
- annotations as array of annotated face mesh points
- age as value
- gender as value
- genderConfidence as value
- emotion as array of possible emotions with their individual scores
- iris as distance value
- angle as object with values for roll, yaw and pitch angles
- tensor as Tensor object which contains detected face

### gesture

gesture: ({ face: number; gesture: string } | { gesture: string; iris: number } | { body: number; gesture: string } | { gesture: string; hand: 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

### hand

hand: { annotations: { part: string; points: [number, number, number][][] }[]; box: [number, number, number, number]; boxRaw: [number, number, number, number]; confidence: number; landmarks: [number, number, 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

### object

object: { box: number[]; boxRaw: number[]; center: number[]; centerRaw: number[]; class: number; label: string; score: number; strideSize: 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

### performance

performance: { any: any }

#### Type declaration

- ##### any: any