Class Human

Human* library main class

All methods and properties are available only as members of Human class

Configuration object definition: Config
Results object definition: Result
Possible inputs: Input

Param: userConfig

Config

Returns

instance of Human

Index

Constructors

constructor

new Human(userConfig?: Partial<Config>): Human
Constructor for Human library that is futher used for all operations
Parameters
- OptionaluserConfig: Partial<Config>
  user configuration object Config
Returns Human
- Defined in src/human.ts:135

Properties

config

config: Config

Current configuration

Defaults: config

draw

draw: draw = draw

Draw helper classes that can draw detected objects on canvas using specified draw

canvas: draws input to canvas
options: are global settings for all draw operations, can be overriden for each draw method DrawOptions
face, body, hand, gesture, object, person: draws detected results as overlays on canvas

env

env: Env = env

Object containing environment information used for diagnostics

events

events: undefined | EventTarget

Container for events dispatched by Human Possible events:

create: triggered when Human object is instantiated
load: triggered when models are loaded (explicitly or on-demand)
image: triggered when input image is processed
result: triggered when detection is complete
warmup: triggered when warmup is complete
error: triggered on some errors

faceTriangulation

faceTriangulation: number[]

Reference face triangualtion array of 468 points, used for triangle references between points

faceUVMap

faceUVMap: [number, number][]

Refernce UV map of 468 values, used for 3D mapping of the face mesh

match

match: match = match

Face Matching

similarity: compare two face descriptors and return similarity index
distance: compare two face descriptors and return raw calculated differences
find: compare face descriptor to array of face descriptors and return best match

performance

performance: Record<string, number>

Performance object that contains values for all recently performed operations

process

process: { canvas: null | AnyCanvas; tensor: null | Tensor<Rank> }

currenty processed image tensor and canvas

result

result: Result

Last known result of detect run

Can be accessed anytime after initial detection

state

state: string

Current state of Human library

Can be polled to determine operations that are currently executed
Progresses through: 'config', 'check', 'backend', 'load', 'run:', 'idle'

tf

tf: any

Instance of TensorFlow/JS used by Human

Can be embedded or externally provided TFJS API

version

version: string

Current version of Human library in semver format

webcam

webcam: WebCam = ...

WebCam helper methods

Methods

analyze

analyze(...msg: string[]): void
internal function to measure tensor leaks
Parameters
- ...msg: string[]
Returns void
- Defined in src/human.ts:182

compare

compare(firstImageTensor: Tensor, secondImageTensor: Tensor): Promise<number>
Compare two input tensors for pixel similarity
- use human.image to process any valid input and get a tensor that can be used for compare
- when passing manually generated tensors:
- both input tensors must be in format [1, height, width, 3]
- if resolution of tensors does not match, second tensor will be resized to match resolution of the first tensor
- return value is pixel similarity score normalized by input resolution and rgb channels
Parameters
- firstImageTensor: Tensor
- secondImageTensor: Tensor
Returns Promise<number>
- Defined in src/human.ts:261

detect

detect(input: Input, userConfig?: Partial<Config>): Promise<Result>
Main detection method
- Analyze configuration: Config
- Pre-process input: Input
- Run inference for all configured models
- Process and return result: Result
Parameters
- input: Input
  Input
- OptionaluserConfig: Partial<Config>
  Config
Returns Promise<Result>
result - Result
- Defined in src/human.ts:379

emit

emit(event: string): void
emit event
Parameters
- event: string
Returns void
- Defined in src/human.ts:315

image

image(
input: Input,
getTensor?: boolean,
): Promise<{ canvas: null | AnyCanvas; tensor: null | Tensor4D }>
Process input as return canvas and tensor
Parameters
- input: Input
  any input Input
- getTensor: boolean = false
  should image processing also return tensor or just canvas Returns object with tensor and canvas
Returns Promise<{ canvas: null | AnyCanvas; tensor: null | Tensor4D }>
- Defined in src/human.ts:231

init

init(): Promise<void>
Explicit backend initialization
- Normally done implicitly during initial load phase
- Call to explictly register and initialize TFJS backend without any other operations
- Use when changing backend during runtime
Returns Promise<void>
- Defined in src/human.ts:270

load

load(userConfig?: Partial<Config>): Promise<void>
Load method preloads all configured models on-demand
- Not explicitly required as any required model is load implicitly on it's first run
Parameters
- OptionaluserConfig: Partial<Config>
  Config
Returns Promise<void>
- Defined in src/human.ts:286

next(result?: Result): Result
Runs interpolation using last known result and returns smoothened result Interpolation is based on time since last known result so can be called independently
Parameters
- result: Result = ...
  Result optional use specific result set to run interpolation on
Returns Result
result - Result
- Defined in src/human.ts:325

now

now(): number
Utility wrapper for performance.now()

Returns number
- Defined in src/human.ts:221

profile

profile(
input: Input,
userConfig?: Partial<Config>,
): Promise<{ kernel: string; perc: number; time: number }[]>
Run detect with tensorflow profiling
- result object will contain total exeuction time information for top-20 kernels
- actual detection object can be accessed via human.result
Parameters
- input: Input
- OptionaluserConfig: Partial<Config>
Returns Promise<{ kernel: string; perc: number; time: number }[]>
- Defined in src/human.ts:347

reset

reset(): void
Reset configuration to default values

Returns void
- Defined in src/human.ts:205

segmentation

segmentation(
input: Input,
userConfig?: Partial<Config>,
): Promise<null | Tensor<Rank>>
Segmentation method takes any input and returns RGBA tensor Note: Segmentation is not triggered as part of detect process
Parameters
- input: Input
  Input Returns tensor which contains image data in RGBA format
- OptionaluserConfig: Partial<Config>
Returns Promise<null | Tensor<Rank>>
- Defined in src/human.ts:241

sleep

sleep(ms: number): Promise<void>
Helper function
Parameters
- ms: number
  sleep time in miliseconds
Returns Promise<void>
- Defined in src/human.ts:543

validate

validate(
userConfig?: Partial<Config>,
): { expected?: string; reason: string; where: string }[]
Validate current configuration schema
Parameters
- OptionaluserConfig: Partial<Config>
Returns { expected?: string; reason: string; where: string }[]
- Defined in src/human.ts:214

video

video(element: HTMLVideoElement, run?: boolean, delay?: number): Promise<void>
Continously detect video frames
Parameters
- element: HTMLVideoElement
  HTMLVideoElement input
- run: boolean = true
  boolean run continously or stop if already running, default true
- delay: number = 0
  number delay detection between frames for number of miliseconds, default 0
Returns Promise<void>
- Defined in src/human.ts:554

warmup

warmup(userConfig?: Partial<Config>): Promise<undefined | Result>
Warmup method pre-initializes all configured models for faster inference
- can take significant time on startup
- only used for webgl and humangl backends
Parameters
- OptionaluserConfig: Partial<Config>
  Config
Returns Promise<undefined | Result>
result - Result
- Defined in src/human.ts:335

Class Human

Param: userConfig

Returns

Index

Constructors

Properties

Methods

Constructors

constructor

Parameters

Returns Human

Properties

config

draw

env

events

faceTriangulation

faceUVMap

match

performance

process

result

state

tf

version

webcam

Methods

analyze

Parameters

Returns void

compare

Parameters

Returns Promise<number>

detect

Parameters

Returns Promise<Result>

emit

Parameters

Returns void

image

Parameters

Returns Promise<{ canvas: null | AnyCanvas; tensor: null | Tensor4D }>

init

Returns Promise<void>

load

Parameters

Returns Promise<void>

next

Parameters

Returns Result

now

Returns number

profile

Parameters

Returns Promise<{ kernel: string; perc: number; time: number }[]>

reset

Returns void

segmentation

Parameters

Returns Promise<null | Tensor<Rank>>

sleep

Parameters

Returns Promise<void>

validate

Parameters

Returns { expected?: string; reason: string; where: string }[]

video

Parameters

Returns Promise<void>

warmup

Parameters

Returns Promise<undefined | Result>

Settings

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