human/src/result.ts

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/**
* Type definitions for Human results
*/
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import { Tensor } from '../dist/tfjs.esm.js';
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/** 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
*
* Each result has:
* - id: face id number
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* - 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
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* - iris: iris distance from current viewpoint as distance value in centimeters for a typical camera
* field of view of 88 degrees. value should be adjusted manually as needed
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* - 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
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* - gaze: gaze direction as object with values for agngle in radians and strengthss
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* - 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],
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gaze: { angle: number, strength: number },
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}
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tensor: typeof Tensor,
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}
/** Body results
*
* Each results has:
* - id: body id number
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* - 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],
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keypoints: Array<{
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part: string,
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position: { x: number, y: number, z?: number },
positionRaw?: { x: number, y: number, z?: number },
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score: number,
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presence?: number,
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}>
}
/** Hand results
*
* Each result has:
* - id: hand id number
* - confidence: detection confidence score as value
* - box: bounding box: x, y, width, height normalized to input image resolution
* - boxRaw: bounding box: x, y, width, height normalized to 0..1
* - landmarks: landmarks as array of [x, y, z] points of hand, normalized to image resolution
* - annotations: annotated landmarks for each hand part
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*/
export interface Hand {
id: number,
confidence: number,
box: [number, number, number, number],
boxRaw: [number, number, number, number],
landmarks: number[],
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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:
* - id: object id number
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* - score as value
* - label as detected class name
* - box: bounding box: x, y, width, height normalized to input image resolution
* - boxRaw: bounding box: x, y, width, height normalized to 0..1
* - center: optional center point as array of [x, y], normalized to image resolution
* - centerRaw: optional center point as array of [x, y], normalized to range 0..1
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*/
export interface Item {
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id: number,
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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 }
/** Person getter
*
* Each result has:
* - id: person id
* - face: face object
* - body: body object
* - hands: array of hand objects
* - gestures: array of gestures
* - box: bounding box: x, y, width, height normalized to input image resolution
* - boxRaw: bounding box: x, y, width, height normalized to 0..1
*/
export interface Person {
id: number,
face: Face,
body: Body | null,
hands: { left: Hand | null, right: Hand | null },
gestures: Array<Gesture>,
box: [number, number, number, number],
boxRaw?: [number, number, number, number],
}
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/**
* Result interface definition for **Human** library
*
* Contains all possible detection results
*/
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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>
/** global performance object with timing values for each operation */
readonly performance: Record<string, unknown>,
/** optional processed canvas that can be used to draw input on screen */
readonly canvas?: OffscreenCanvas | HTMLCanvasElement,
/** timestamp of detection representing the milliseconds elapsed since the UNIX epoch */
readonly timestamp: number,
/** getter property that returns unified persons object */
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persons: Array<Person>,
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}