human/src/config.ts

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/* eslint-disable indent */
/* eslint-disable no-multi-spaces */
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/** Generic config type inherited by all module types */
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export interface GenericConfig {
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/** @property is module enabled? */
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enabled: boolean,
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/** @property path to model json file */
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modelPath: string,
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/** @property how many max frames to go without re-running model if cached results are acceptable */
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skipFrames: number,
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/** @property how many max miliseconds to go without re-running model if cached results are acceptable */
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skipTime: number,
}
/** Dectector part of face configuration */
export interface FaceDetectorConfig extends GenericConfig {
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/** @property is face rotation correction performed after detecting face? */
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rotation: boolean,
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/** @property maximum number of detected faces */
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maxDetected: number,
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/** @property minimum confidence for a detected face before results are discarded */
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minConfidence: number,
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/** @property minimum overlap between two detected faces before one is discarded */
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iouThreshold: number,
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/** @property should face detection return face tensor to be used in some other extenrnal model? */
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return: boolean,
}
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/** Mesh part of face configuration */
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export interface FaceMeshConfig extends GenericConfig {}
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/** Iris part of face configuration */
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export interface FaceIrisConfig extends GenericConfig {}
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/** Description or face embedding part of face configuration
* - also used by age and gender detection
*/
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export interface FaceDescriptionConfig extends GenericConfig {
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/** @property minimum confidence for a detected face before results are discarded */
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minConfidence: number,
}
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/** Emotion part of face configuration */
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export interface FaceEmotionConfig extends GenericConfig {
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/** @property minimum confidence for a detected face before results are discarded */
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minConfidence: number,
}
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/** Anti-spoofing part of face configuration */
export interface FaceAntiSpoofConfig extends GenericConfig {}
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/** Configures all face-specific options: face detection, mesh analysis, age, gender, emotion detection and face description */
export interface FaceConfig extends GenericConfig {
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detector: Partial<FaceDetectorConfig>,
mesh: Partial<FaceMeshConfig>,
iris: Partial<FaceIrisConfig>,
description: Partial<FaceDescriptionConfig>,
emotion: Partial<FaceEmotionConfig>,
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antispoof: Partial<FaceAntiSpoofConfig>,
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}
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/** Configures all body detection specific options */
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export interface BodyConfig extends GenericConfig {
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/** @property maximum numboer of detected bodies */
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maxDetected: number,
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/** @property minimum confidence for a detected body before results are discarded */
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minConfidence: number,
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detector?: {
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/** @property path to optional body detector model json file */
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modelPath: string
},
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}
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/** Configures all hand detection specific options */
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export interface HandConfig extends GenericConfig {
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/** @property should hand rotation correction be performed after hand detection? */
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rotation: boolean,
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/** @property minimum confidence for a detected hand before results are discarded */
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minConfidence: number,
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/** @property minimum overlap between two detected hands before one is discarded */
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iouThreshold: number,
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/** @property maximum number of detected hands */
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maxDetected: number,
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/** @property should hand landmarks be detected or just return detected hand box */
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landmarks: boolean,
detector: {
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/** @property path to hand detector model json */
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modelPath?: string,
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},
skeleton: {
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/** @property path to hand skeleton model json */
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modelPath?: string,
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},
}
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/** Configures all object detection specific options */
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export interface ObjectConfig extends GenericConfig {
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/** @property minimum confidence for a detected objects before results are discarded */
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minConfidence: number,
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/** @property minimum overlap between two detected objects before one is discarded */
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iouThreshold: number,
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/** @property maximum number of detected objects */
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maxDetected: number,
}
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/** Configures all body segmentation module
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* removes background from input containing person
* if segmentation is enabled it will run as preprocessing task before any other model
* alternatively leave it disabled and use it on-demand using human.segmentation method which can
* remove background or replace it with user-provided background
*/
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export interface SegmentationConfig extends GenericConfig {
/** @property blur segmentation output by <number> pixels for more realistic image */
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blur: number,
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}
/** Run input through image filters before inference
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* - available only in Browser environments
* - image filters run with near-zero latency as they are executed on the GPU using WebGL
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*/
export interface FilterConfig {
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/** @property are image filters enabled? */
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enabled: boolean,
/** Resize input width
* - if both width and height are set to 0, there is no resizing
* - if just one is set, second one is scaled automatically
* - if both are set, values are used as-is
*/
width: number,
/** Resize input height
* - if both width and height are set to 0, there is no resizing
* - if just one is set, second one is scaled automatically
* - if both are set, values are used as-is
*/
height: number,
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/** @property return processed canvas imagedata in result */
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return: boolean,
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/** @property flip input as mirror image */
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flip: boolean,
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/** @property range: -1 (darken) to 1 (lighten) */
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brightness: number,
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/** @property range: -1 (reduce contrast) to 1 (increase contrast) */
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contrast: number,
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/** @property range: 0 (no sharpening) to 1 (maximum sharpening) */
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sharpness: number,
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/** @property range: 0 (no blur) to N (blur radius in pixels) */
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blur: number
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/** @property range: -1 (reduce saturation) to 1 (increase saturation) */
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saturation: number,
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/** @property range: 0 (no change) to 360 (hue rotation in degrees) */
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hue: number,
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/** @property image negative */
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negative: boolean,
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/** @property image sepia colors */
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sepia: boolean,
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/** @property image vintage colors */
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vintage: boolean,
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/** @property image kodachrome colors */
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kodachrome: boolean,
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/** @property image technicolor colors */
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technicolor: boolean,
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/** @property image polaroid camera effect */
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polaroid: boolean,
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/** @property range: 0 (no pixelate) to N (number of pixels to pixelate) */
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pixelate: number,
}
/** Controlls gesture detection */
export interface GestureConfig {
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/** @property is gesture detection enabled? */
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enabled: boolean,
}
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/**
* Configuration interface definition for **Human** library
*
* Contains all configurable parameters
* @typedef Config
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*
* Defaults: [config](https://github.com/vladmandic/human/blob/main/src/config.ts#L292)
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*/
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export interface Config {
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/** Backend used for TFJS operations
* Valid build-in backends are:
* - Browser: `cpu`, `wasm`, `webgl`, `humangl`
* - NodeJS: `cpu`, `wasm`, `tensorflow`
*
* Experimental:
* - Browser: `webgpu` - requires custom build of `tfjs-backend-webgpu`
*
* Defaults: `humangl` for browser and `tensorflow` for nodejs
*/
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backend: '' | 'cpu' | 'wasm' | 'webgl' | 'humangl' | 'tensorflow' | 'webgpu',
// backend: string;
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/** Path to *.wasm files if backend is set to `wasm`
* - if not set, auto-detects to link to CDN `jsdelivr` when running in browser
*/
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wasmPath: string,
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/** Print debug statements to console */
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debug: boolean,
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/** Perform model loading and inference concurrently or sequentially */
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async: boolean,
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/** What to use for `human.warmup()`
* - warmup pre-initializes all models for faster inference but can take significant time on startup
*/
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warmup: 'none' | 'face' | 'full' | 'body',
// warmup: string;
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/** Base model path (typically starting with file://, http:// or https://) for all models
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* - individual modelPath values are relative to this path
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*/
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modelBasePath: string,
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/** Cache sensitivity
* - values 0..1 where 0.01 means reset cache if input changed more than 1%
* - set to 0 to disable caching
*/
cacheSensitivity: number;
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/** Internal Variable */
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skipAllowed: boolean;
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/** {@link FilterConfig} */
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filter: Partial<FilterConfig>,
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/** {@link GestureConfig} */
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gesture: Partial<GestureConfig>;
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/** {@link FaceConfig} */
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face: Partial<FaceConfig>,
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/** {@link BodyConfig} */
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body: Partial<BodyConfig>,
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/** {@link HandConfig} */
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hand: Partial<HandConfig>,
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/** {@link ObjectConfig} */
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object: Partial<ObjectConfig>,
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/** {@link SegmentationConfig} */
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segmentation: Partial<SegmentationConfig>,
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}
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/** - [See all default Config values...](https://github.com/vladmandic/human/blob/main/src/config.ts#L250) */
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const config: Config = {
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backend: '', // select tfjs backend to use, leave empty to use default backend
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// for browser environments: 'webgl', 'wasm', 'cpu', or 'humangl' (which is a custom version of webgl)
// for nodejs environments: 'tensorflow', 'wasm', 'cpu'
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// default set to `humangl` for browsers and `tensorflow` for nodejs
modelBasePath: '', // base path for all models
// default set to `../models/` for browsers and `file://models/` for nodejs
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wasmPath: '', // path for wasm binaries, only used for backend: wasm
// default set to download from jsdeliv during Human class instantiation
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debug: true, // print additional status messages to console
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async: true, // execute enabled models in parallel
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warmup: 'full', // what to use for human.warmup(), can be 'none', 'face', 'full'
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// warmup pre-initializes all models for faster inference but can take
// significant time on startup
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// only used for `webgl` and `humangl` backends
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cacheSensitivity: 0.70, // cache sensitivity
// values 0..1 where 0.01 means reset cache if input changed more than 1%
// set to 0 to disable caching
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skipAllowed: false, // internal & dynamic
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filter: { // run input through image filters before inference
// image filters run with near-zero latency as they are executed on the GPU
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enabled: true, // enable image pre-processing filters
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width: 0, // resize input width
height: 0, // resize input height
// if both width and height are set to 0, there is no resizing
// if just one is set, second one is scaled automatically
// if both are set, values are used as-is
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flip: false, // flip input as mirror image
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return: true, // return processed canvas imagedata in result
brightness: 0, // range: -1 (darken) to 1 (lighten)
contrast: 0, // range: -1 (reduce contrast) to 1 (increase contrast)
sharpness: 0, // range: 0 (no sharpening) to 1 (maximum sharpening)
blur: 0, // range: 0 (no blur) to N (blur radius in pixels)
saturation: 0, // range: -1 (reduce saturation) to 1 (increase saturation)
hue: 0, // range: 0 (no change) to 360 (hue rotation in degrees)
negative: false, // image negative
sepia: false, // image sepia colors
vintage: false, // image vintage colors
kodachrome: false, // image kodachrome colors
technicolor: false, // image technicolor colors
polaroid: false, // image polaroid camera effect
pixelate: 0, // range: 0 (no pixelate) to N (number of pixels to pixelate)
},
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gesture: {
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enabled: true, // enable gesture recognition based on model results
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},
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face: {
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enabled: true, // controls if specified modul is enabled
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// face.enabled is required for all face models:
// detector, mesh, iris, age, gender, emotion
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// (note: module is not loaded until it is required)
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detector: {
modelPath: 'blazeface.json', // detector model, can be absolute path or relative to modelBasePath
rotation: true, // use best-guess rotated face image or just box with rotation as-is
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// false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees
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// this parameter is not valid in nodejs
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maxDetected: 1, // maximum number of faces detected in the input
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// should be set to the minimum number for performance
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skipFrames: 99, // how many max frames to go without re-running the face bounding box detector
// only used when cacheSensitivity is not zero
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skipTime: 2500, // how many ms to go without re-running the face bounding box detector
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// only used when cacheSensitivity is not zero
minConfidence: 0.2, // threshold for discarding a prediction
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iouThreshold: 0.1, // ammount of overlap between two detected objects before one object is removed
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return: false, // return extracted face as tensor
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// in which case user is reponsible for disposing the tensor
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},
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mesh: {
enabled: true,
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modelPath: 'facemesh.json', // facemesh model, can be absolute path or relative to modelBasePath
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},
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iris: {
enabled: true,
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modelPath: 'iris.json', // face iris model
// can be either absolute path or relative to modelBasePath
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},
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emotion: {
enabled: true,
minConfidence: 0.1, // threshold for discarding a prediction
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skipFrames: 99, // how max many frames to go without re-running the detector
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// only used when cacheSensitivity is not zero
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skipTime: 1500, // how many ms to go without re-running the face bounding box detector
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// only used when cacheSensitivity is not zero
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modelPath: 'emotion.json', // face emotion model, can be absolute path or relative to modelBasePath
},
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description: {
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enabled: true, // to improve accuracy of face description extraction it is
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// recommended to enable detector.rotation and mesh.enabled
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modelPath: 'faceres.json', // face description model
// can be either absolute path or relative to modelBasePath
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skipFrames: 99, // how many max frames to go without re-running the detector
// only used when cacheSensitivity is not zero
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skipTime: 3000, // how many ms to go without re-running the face bounding box detector
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// only used when cacheSensitivity is not zero
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minConfidence: 0.1, // threshold for discarding a prediction
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},
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antispoof: {
enabled: false,
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skipFrames: 99, // how max many frames to go without re-running the detector
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// only used when cacheSensitivity is not zero
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skipTime: 4000, // how many ms to go without re-running the face bounding box detector
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// only used when cacheSensitivity is not zero
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modelPath: 'antispoof.json', // face description model
// can be either absolute path or relative to modelBasePath
},
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},
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body: {
enabled: true,
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modelPath: 'movenet-lightning.json', // body model, can be absolute path or relative to modelBasePath
// can be 'posenet', 'blazepose', 'efficientpose', 'movenet-lightning', 'movenet-thunder'
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detector: {
modelPath: '', // optional body detector
},
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maxDetected: -1, // maximum number of people detected in the input
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// should be set to the minimum number for performance
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// only valid for posenet and movenet-multipose as other models detects single pose
// set to -1 to autodetect based on number of detected faces
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minConfidence: 0.3, // threshold for discarding a prediction
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skipFrames: 1, // how many max frames to go without re-running the detector
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// only used when cacheSensitivity is not zero
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skipTime: 200, // how many ms to go without re-running the face bounding box detector
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// only used when cacheSensitivity is not zero
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},
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hand: {
enabled: true,
rotation: true, // use best-guess rotated hand image or just box with rotation as-is
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// false means higher performance, but incorrect finger mapping if hand is inverted
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// only valid for `handdetect` variation
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skipFrames: 99, // how many max frames to go without re-running the hand bounding box detector
// only used when cacheSensitivity is not zero
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skipTime: 2000, // how many ms to go without re-running the face bounding box detector
// only used when cacheSensitivity is not zero
minConfidence: 0.50, // threshold for discarding a prediction
iouThreshold: 0.2, // ammount of overlap between two detected objects before one object is removed
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maxDetected: -1, // maximum number of hands detected in the input
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// should be set to the minimum number for performance
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// set to -1 to autodetect based on number of detected faces
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landmarks: true, // detect hand landmarks or just hand boundary box
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detector: {
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modelPath: 'handtrack.json', // hand detector model, can be absolute path or relative to modelBasePath
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// can be 'handdetect' or 'handtrack'
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},
skeleton: {
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modelPath: 'handskeleton.json', // hand skeleton model, can be absolute path or relative to modelBasePath
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},
},
object: {
enabled: false,
modelPath: 'mb3-centernet.json', // experimental: object detection model, can be absolute path or relative to modelBasePath
// can be 'mb3-centernet' or 'nanodet'
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minConfidence: 0.2, // threshold for discarding a prediction
iouThreshold: 0.4, // ammount of overlap between two detected objects before one object is removed
maxDetected: 10, // maximum number of objects detected in the input
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skipFrames: 99, // how many max frames to go without re-running the detector
// only used when cacheSensitivity is not zero
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skipTime: 1000, // how many ms to go without re-running object detector
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// only used when cacheSensitivity is not zero
},
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segmentation: {
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enabled: false, // controlls and configures all body segmentation module
// removes background from input containing person
// if segmentation is enabled it will run as preprocessing task before any other model
// alternatively leave it disabled and use it on-demand using human.segmentation method which can
// remove background or replace it with user-provided background
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modelPath: 'selfie.json', // experimental: object detection model, can be absolute path or relative to modelBasePath
// can be 'selfie' or 'meet'
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blur: 8, // blur segmentation output by n pixels for more realistic image
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},
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};
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export { config as defaults };