mirror of https://github.com/vladmandic/human
402 lines
17 KiB
TypeScript
402 lines
17 KiB
TypeScript
/* eslint-disable indent */
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/* eslint-disable no-multi-spaces */
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export interface FaceDetectorConfig {
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modelPath: string,
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rotation: boolean,
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maxDetected: number,
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skipFrames: number,
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minConfidence: number,
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iouThreshold: number,
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return: boolean,
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}
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export interface FaceMeshConfig {
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enabled: boolean,
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modelPath: string,
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}
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export interface FaceIrisConfig {
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enabled: boolean,
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modelPath: string,
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}
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export interface FaceDescriptionConfig {
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enabled: boolean,
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modelPath: string,
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skipFrames: number,
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minConfidence: number,
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}
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export interface FaceEmotionConfig {
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enabled: boolean,
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minConfidence: number,
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skipFrames: number,
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modelPath: string,
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}
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/** Controlls and configures all face-specific options:
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* - face detection, face mesh detection, age, gender, emotion detection and face description
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* Parameters:
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* - enabled: true/false
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* - modelPath: path for each of face models
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* - minConfidence: threshold for discarding a prediction
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* - iouThreshold: ammount of overlap between two detected objects before one object is removed
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* - maxDetected: maximum number of faces detected in the input, should be set to the minimum number for performance
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* - rotation: use calculated rotated face image or just box with rotation as-is, false means higher performance, but incorrect mesh mapping on higher face angles
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* - return: return extracted face as tensor for futher user processing, in which case user is reponsible for manually disposing the tensor
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*/
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export interface FaceConfig {
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enabled: boolean,
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detector: Partial<FaceDetectorConfig>,
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mesh: Partial<FaceMeshConfig>,
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iris: Partial<FaceIrisConfig>,
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description: Partial<FaceDescriptionConfig>,
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emotion: Partial<FaceEmotionConfig>,
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}
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/** Controlls and configures all body detection specific options
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* - enabled: true/false
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* - modelPath: body pose model, can be absolute path or relative to modelBasePath
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* - minConfidence: threshold for discarding a prediction
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* - maxDetected: maximum number of people detected in the input, should be set to the minimum number for performance
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*/
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export interface BodyConfig {
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enabled: boolean,
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modelPath: string,
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maxDetected: number,
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minConfidence: number,
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skipFrames: number,
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}
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/** Controlls and configures all hand detection specific options
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* - enabled: true/false
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* - landmarks: detect hand landmarks or just hand boundary box
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* - modelPath: paths for hand detector and hand skeleton models, can be absolute path or relative to modelBasePath
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* - minConfidence: threshold for discarding a prediction
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* - iouThreshold: ammount of overlap between two detected objects before one object is removed
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* - maxDetected: maximum number of hands detected in the input, should be set to the minimum number for performance
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* - rotation: use best-guess rotated hand image or just box with rotation as-is, false means higher performance, but incorrect finger mapping if hand is inverted
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*/
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export interface HandConfig {
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enabled: boolean,
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rotation: boolean,
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skipFrames: number,
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minConfidence: number,
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iouThreshold: number,
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maxDetected: number,
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landmarks: boolean,
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detector: {
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modelPath?: string,
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},
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skeleton: {
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modelPath?: string,
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},
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}
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/** Controlls and configures all object detection specific options
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* - enabled: true/false
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* - modelPath: object detection model, can be absolute path or relative to modelBasePath
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* - minConfidence: minimum score that detection must have to return as valid object
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* - iouThreshold: ammount of overlap between two detected objects before one object is removed
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* - maxDetected: maximum number of detections to return
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*/
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export interface ObjectConfig {
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enabled: boolean,
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modelPath: string,
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minConfidence: number,
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iouThreshold: number,
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maxDetected: number,
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skipFrames: number,
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}
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/** Controlls and configures all body segmentation module
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* removes background from input containing person
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* if segmentation is enabled it will run as preprocessing task before any other model
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* alternatively leave it disabled and use it on-demand using human.segmentation method which can
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* remove background or replace it with user-provided background
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*
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* - enabled: true/false
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* - modelPath: object detection model, can be absolute path or relative to modelBasePath
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*/
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export interface SegmentationConfig {
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enabled: boolean,
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modelPath: string,
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}
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/** Run input through image filters before inference
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* - image filters run with near-zero latency as they are executed on the GPU
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*/
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export interface FilterConfig {
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enabled: boolean,
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/** Resize input width
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* - if both width and height are set to 0, there is no resizing
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* - if just one is set, second one is scaled automatically
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* - if both are set, values are used as-is
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*/
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width: number,
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/** Resize input height
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* - if both width and height are set to 0, there is no resizing
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* - if just one is set, second one is scaled automatically
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* - if both are set, values are used as-is
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*/
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height: number,
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/** Return processed canvas imagedata in result */
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return: boolean,
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/** Flip input as mirror image */
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flip: boolean,
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/** Range: -1 (darken) to 1 (lighten) */
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brightness: number,
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/** Range: -1 (reduce contrast) to 1 (increase contrast) */
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contrast: number,
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/** Range: 0 (no sharpening) to 1 (maximum sharpening) */
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sharpness: number,
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/** Range: 0 (no blur) to N (blur radius in pixels) */
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blur: number
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/** Range: -1 (reduce saturation) to 1 (increase saturation) */
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saturation: number,
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/** Range: 0 (no change) to 360 (hue rotation in degrees) */
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hue: number,
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/** Image negative */
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negative: boolean,
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/** Image sepia colors */
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sepia: boolean,
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/** Image vintage colors */
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vintage: boolean,
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/** Image kodachrome colors */
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kodachrome: boolean,
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/** Image technicolor colors */
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technicolor: boolean,
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/** Image polaroid camera effect */
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polaroid: boolean,
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/** Range: 0 (no pixelate) to N (number of pixels to pixelate) */
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pixelate: number,
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}
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/** Controlls gesture detection */
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export interface GestureConfig {
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enabled: boolean,
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}
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/**
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* Configuration interface definition for **Human** library
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*
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* Contains all configurable parameters
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* @typedef Config
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*/
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export interface Config {
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/** Backend used for TFJS operations */
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// backend: '' | 'cpu' | 'wasm' | 'webgl' | 'humangl' | 'tensorflow' | 'webgpu' | null,
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backend: string;
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/** Path to *.wasm files if backend is set to `wasm` */
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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()`
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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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*/
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// warmup: 'none' | 'face' | 'full' | 'body' | string,
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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
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* - values 0..1 where 0.01 means reset cache if input changed more than 1%
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* - set to 0 to disable caching
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*/
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cacheSensitivity: number;
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/** Cache sensitivity
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* - values 0..1 where 0.01 means reset cache if input changed more than 1%
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* - set to 0 to disable caching
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*/
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skipFrame: boolean;
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/** Run input through image filters before inference
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* - image filters run with near-zero latency as they are executed on the GPU
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*/
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filter: Partial<FilterConfig>,
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// type definition end
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gesture: Partial<GestureConfig>;
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face: Partial<FaceConfig>,
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body: Partial<BodyConfig>,
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hand: Partial<HandConfig>,
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object: Partial<ObjectConfig>,
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segmentation: Partial<SegmentationConfig>,
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}
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/**
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* [Default values](https://github.com/vladmandic/human/blob/main/src/config.ts#L244) for {@Config}
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*
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*/
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const config: Config = {
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backend: 'humangl', // select tfjs backend to use, leave empty to use default backend
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// can be 'webgl', 'wasm', 'cpu', or 'humangl' which is a custom version of webgl
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modelBasePath: '../models/', // base path for all models
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wasmPath: '', // path for wasm binaries, only used for backend: wasm
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// 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
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// significant time on startup
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// only used for `webgl` and `humangl` backends
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cacheSensitivity: 0.75, // cache sensitivity
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// values 0..1 where 0.01 means reset cache if input changed more than 1%
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// set to 0 to disable caching
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skipFrame: false, // internal & dynamic
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filter: { // run input through image filters before inference
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// 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
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height: 0, // resize input height
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// if both width and height are set to 0, there is no resizing
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// if just one is set, second one is scaled automatically
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// 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
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brightness: 0, // range: -1 (darken) to 1 (lighten)
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contrast: 0, // range: -1 (reduce contrast) to 1 (increase contrast)
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sharpness: 0, // range: 0 (no sharpening) to 1 (maximum sharpening)
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blur: 0, // range: 0 (no blur) to N (blur radius in pixels)
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saturation: 0, // range: -1 (reduce saturation) to 1 (increase saturation)
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hue: 0, // range: 0 (no change) to 360 (hue rotation in degrees)
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negative: false, // image negative
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sepia: false, // image sepia colors
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vintage: false, // image vintage colors
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kodachrome: false, // image kodachrome colors
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technicolor: false, // image technicolor colors
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polaroid: false, // image polaroid camera effect
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pixelate: 0, // range: 0 (no pixelate) to N (number of pixels to pixelate)
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},
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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:
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// detector, mesh, iris, age, gender, emotion
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// (note: module is not loaded until it is required)
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detector: {
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modelPath: 'blazeface.json', // detector model, can be absolute path or relative to modelBasePath
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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: 15, // 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: 15, // how many max frames 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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// e.g., if model is running st 25 FPS, we can re-use existing bounding
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// box for updated face analysis as the head probably hasn't moved much
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// in short time (10 * 1/25 = 0.25 sec)
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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: {
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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: {
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enabled: true,
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modelPath: 'iris.json', // face iris model
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// can be either absolute path or relative to modelBasePath
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},
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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
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// can be either absolute path or relative to modelBasePath
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skipFrames: 11, // 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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minConfidence: 0.1, // threshold for discarding a prediction
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},
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emotion: {
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enabled: true,
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minConfidence: 0.1, // threshold for discarding a prediction
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skipFrames: 17, // 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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modelPath: 'emotion.json', // face emotion model, can be absolute path or relative to modelBasePath
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},
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},
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body: {
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enabled: true,
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modelPath: 'movenet-lightning.json', // body model, can be absolute path or relative to modelBasePath
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// can be 'posenet', 'blazepose', 'efficientpose', 'movenet-lightning', 'movenet-thunder'
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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 as other models detects single pose
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minConfidence: 0.2, // 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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},
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hand: {
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enabled: true,
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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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skipFrames: 18, // how many max frames to go without re-running the hand bounding box detector
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// only used when cacheSensitivity is not zero
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// e.g., if model is running st 25 FPS, we can re-use existing bounding
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// box for updated hand skeleton analysis as the hand probably
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// hasn't moved much in short time (10 * 1/25 = 0.25 sec)
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minConfidence: 0.8, // threshold for discarding a prediction
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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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landmarks: true, // detect hand landmarks or just hand boundary box
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detector: {
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modelPath: 'handdetect.json', // hand detector model, can be absolute path or relative to modelBasePath
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},
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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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},
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},
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object: {
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enabled: false,
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modelPath: 'mb3-centernet.json', // experimental: object detection model, can be absolute path or relative to modelBasePath
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// can be 'mb3-centernet' or 'nanodet'
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minConfidence: 0.2, // threshold for discarding a prediction
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iouThreshold: 0.4, // ammount of overlap between two detected objects before one object is removed
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maxDetected: 10, // maximum number of objects detected in the input
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skipFrames: 19, // 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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},
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segmentation: {
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enabled: false, // controlls and configures all body segmentation module
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// removes background from input containing person
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// if segmentation is enabled it will run as preprocessing task before any other model
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// alternatively leave it disabled and use it on-demand using human.segmentation method which can
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// 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
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// can be 'selfie' or 'meet'
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},
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};
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export { config as defaults };
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