mirror of https://github.com/vladmandic/human
181 lines
10 KiB
JavaScript
181 lines
10 KiB
JavaScript
/* eslint-disable indent */
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/* eslint-disable no-multi-spaces */
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export default {
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backend: 'webgl', // select tfjs backend to use
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// can be 'webgl', 'wasm', 'cpu', or 'humangl' which is a custom version of webgl
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// leave as empty string to continue using default backend
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// when backend is set outside of Human library
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wasmPath: '../assets/', // path for wasm binaries
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// only used for backend: wasm
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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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// this disables per-model performance data but
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// slightly increases performance
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// cannot be used if profiling is enabled
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profile: false, // enable tfjs profiling
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// this has significant performance impact
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// only enable for debugging purposes
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// currently only implemented for age,gender,emotion models
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deallocate: false, // aggresively deallocate gpu memory after each usage
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// only valid for webgl backend and only during first call
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// cannot be changed unless library is reloaded
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// this has significant performance impact
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// only enable on low-memory devices
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scoped: false, // enable scoped runs
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// some models *may* have memory leaks,
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// this wrapps everything in a local scope at a cost of performance
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// typically not needed
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videoOptimized: true, // perform additional optimizations when input is video,
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// must be disabled for images
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// basically this skips object box boundary detection for every n frames
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// while maintaining in-box detection since objects cannot move that fast
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warmup: 'face', // 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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filter: {
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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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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 simple gesture recognition
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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: '../models/blazeface-back.json', // can be 'blazeface-front', 'blazeface-back' or 'faceboxes'
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// 'blazeface-front' is blazeface model optimized for large faces such as front-facing camera
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// 'blazeface-back' is blazeface model optimized for smaller and/or distanct faces
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// 'faceboxes' is alternative model to 'blazeface'
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inputSize: 256, // fixed value: 128 for front and 256 for 'back'
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rotation: false, // 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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maxFaces: 10, // 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: 11, // how many frames to go without re-running the face bounding box detector
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// only used for video inputs
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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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skipInitial: false, // if previous detection resulted in no faces detected,
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// should skipFrames be reset immediately
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minConfidence: 0.1, // threshold for discarding a prediction
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iouThreshold: 0.1, // threshold for deciding whether boxes overlap too much in
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// non-maximum suppression (0.1 means drop if overlap 10%)
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scoreThreshold: 0.1, // threshold for deciding when to remove boxes based on score
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// in non-maximum suppression,
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// this is applied on detection objects only and before minConfidence
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},
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mesh: {
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enabled: true,
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modelPath: '../models/facemesh.json',
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inputSize: 192, // fixed value
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returnRawData: false, // in addition to standard mesh and box values, return raw normalized values as well
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},
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iris: {
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enabled: true,
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modelPath: '../models/iris.json',
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inputSize: 64, // fixed value
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},
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age: {
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enabled: true,
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modelPath: '../models/age-ssrnet-imdb.json',
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inputSize: 64, // fixed value
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skipFrames: 31, // how many frames to go without re-running the detector
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// only used for video inputs
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},
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gender: {
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enabled: true,
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minConfidence: 0.1, // threshold for discarding a prediction
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modelPath: '../models/gender.json', // can be 'gender' or 'gender-ssrnet-imdb'
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inputSize: 64, // fixed value
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skipFrames: 41, // how many frames to go without re-running the detector
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// only used for video inputs
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},
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emotion: {
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enabled: true,
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inputSize: 64, // fixed value
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minConfidence: 0.1, // threshold for discarding a prediction
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skipFrames: 21, // how many frames to go without re-running the detector
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modelPath: '../models/emotion.json',
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},
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embedding: {
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enabled: false,
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inputSize: 112, // fixed value
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modelPath: '../models/mobilefacenet.json',
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},
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},
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body: {
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enabled: true,
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modelPath: '../models/posenet.json', // can be 'posenet' or 'blazepose'
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inputSize: 257, // fixed value, 257 for posenet and 256 for blazepose
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maxDetections: 10, // 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 blazepose only detects single pose
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scoreThreshold: 0.5, // threshold for deciding when to remove boxes based on score
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// in non-maximum suppression
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// only valid for posenet as blazepose only detects single pose
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nmsRadius: 20, // radius for deciding points are too close in non-maximum suppression
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// only valid for posenet as blazepose only detects single pose
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modelType: 'posenet-mobilenet', // can be 'posenet-mobilenet', 'posenet-resnet', 'blazepose'
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},
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hand: {
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enabled: true,
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rotation: false, // 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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inputSize: 256, // fixed value
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skipFrames: 12, // how many frames to go without re-running the hand bounding box detector
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// only used for video inputs
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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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skipInitial: false, // if previous detection resulted in no faces detected,
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// should skipFrames be reset immediately
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minConfidence: 0.1, // threshold for discarding a prediction
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iouThreshold: 0.1, // threshold for deciding whether boxes overlap too much
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// in non-maximum suppression
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scoreThreshold: 0.5, // threshold for deciding when to remove boxes based on
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// score in non-maximum suppression
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maxHands: 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: '../models/handdetect.json',
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},
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skeleton: {
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modelPath: '../models/handskeleton.json',
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},
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},
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};
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