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/ *
Human library
homepage : < https : //github.com/vladmandic/human>
author : < https : //github.com/vladmandic>'
* /
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var f5 = Object . defineProperty ; var kA = Object . getOwnPropertyDescriptor ; var WA = Object . getOwnPropertyNames ; var IA = Object . prototype . hasOwnProperty ; var NA = e => f5 ( e , "__esModule" , { value : ! 0 } ) ; var ue = ( e , A ) => { NA ( e ) ; for ( var t in A ) f5 ( e , t , { get : A [ t ] , enumerable : ! 0 } ) } , b = ( e , A , t ) => { if ( A && typeof A == "object" || typeof A == "function" ) for ( let r of WA ( A ) ) ! IA . call ( e , r ) && r !== "default" && f5 ( e , r , { get : ( ) => A [ r ] , enumerable : ! ( t = kA ( A , r ) ) || t . enumerable } ) ; return e } ; var pe = ( e , A , t ) => { if ( ! A . has ( e ) ) throw TypeError ( "Cannot " + t ) } ; var G = ( e , A , t ) => ( pe ( e , A , "read from private field" ) , t ? t . call ( e ) : A . get ( e ) ) , e0 = ( e , A , t ) => { if ( A . has ( e ) ) throw TypeError ( "Cannot add the same private member more than once" ) ; A instanceof WeakSet ? A . add ( e ) : A . set ( e , t ) } , n0 = ( e , A , t , r ) => ( pe ( e , A , "write to private field" ) , r ? r . call ( e , t ) : A . set ( e , t ) , t ) ; function Z ( e , A ) { let t = e . endsWith ( "/" ) ? "" : "/" , o = A . startsWith ( "." ) || A . startsWith ( "/" ) || A . startsWith ( "http:" ) || A . startsWith ( "https:" ) || A . startsWith ( "file:" ) ? ` ${ A } ` : ` ${ e } ${ t } ${ A } ` ; if ( ! o . toLocaleLowerCase ( ) . includes ( ".json" ) ) throw new Error ( ` Human: ModelPath Error: ${ o } Expecting JSON file ` ) ; return o } function M ( ... e ) { let A = new Date , t = ` ${ A . getHours ( ) . toString ( ) . padStart ( 2 , "0" ) } : ${ A . getMinutes ( ) . toString ( ) . padStart ( 2 , "0" ) } : ${ A . getSeconds ( ) . toString ( ) . padStart ( 2 , "0" ) } . ${ A . getMilliseconds ( ) . toString ( ) . padStart ( 3 , "0" ) } ` ; e && console . log ( t , "Human:" , ... e ) } var L = ( ) => typeof performance != "undefined" ? performance . now ( ) : parseInt ( ( Number ( process . hrtime . bigint ( ) ) / 1e3 / 1e3 ) . toString ( ) ) ; function U ( ... e ) { let A = t => t && typeof t == "object" ; return e . reduce ( ( t , r ) => ( Object . keys ( r || { } ) . forEach ( o => { let a = t [ o ] , i = r [ o ] ; Array . isArray ( a ) && Array . isArray ( i ) ? t [ o ] = a . concat ( ... i ) : A ( a ) && A ( i ) ? t [ o ] = U ( a , i ) : t [ o ] = i } ) , t ) , { } ) } var m5 = { backend : "webgl" , modelBasePath : "../models/" , wasmPath : "" , debug : ! 0 , async : ! 0 , warmup : "full" , cacheSensitivity : . 75 , skipFrame : ! 1 , filter : { enabled : ! 0 , width : 0 , height : 0 , flip : ! 1 , return : ! 0 , brightness : 0 , contrast : 0 , sharpness : 0 , blur : 0 , saturation : 0 , hue : 0 , negative : ! 1 , sepia : ! 1 , vintage : ! 1 , kodachrome : ! 1 , technicolor : ! 1 , polaroid : ! 1 , pixelate : 0 } , gesture : { enabled : ! 0 } , face : { enabled : ! 0 , detector : { modelPath : "blazeface.json" , rotation : ! 0 , maxDetected : 15 , skipFrames : 15 , minConfidence : . 2 , iouThreshold : . 1 , return : ! 1 } , mesh : { enabled : ! 0 , modelPath : "facemesh.json" } , iris : { enabled : ! 0 , modelPath : "iris.json" } , description : { enabled : ! 0 , modelPath : "faceres.json" , skipFrames : 11 , minConfidence : . 1 } , emotion : { enabled : ! 0 , minConfidence : . 1 , skipFrames : 17 , modelPath : "emotion.json" } } , body : { enabled : ! 0 , modelPath : "movenet-lightning.json" , maxDetected : 1 , minConfidence : . 2 , skipFrames : 1 } , hand : { enabled : ! 0 , rotation : ! 0 , skipFrames : 18 , minConfidence : . 8 , iouThreshold : . 2 , maxDetected : 1 , landmarks : ! 0 , detector : { modelPath : "handdetect.json" } , skeleton : { modelPath : "handskeleton.json" } } , object : { enabled : ! 1 , modelPath : "mb3-centernet.json" , minConfidence : . 2 , iouThreshold : . 4 , maxDetected : 10 , skipFrames : 19 } , segmentation : { enabled : ! 1 , modelPath : "selfie.json" } } ; function be ( ) { let e = "" , A = "" ; if ( typeof navigator != "undefined" ) { let t = navigator . userAgent . match ( /\(([^()]+)\)/g ) ; if ( t && t [ 0 ] ) { let r = t [ 0 ] . match ( /\(([^()]+)\)/g ) ; e = r && r [ 0 ] ? r [ 0 ] . replace ( /\(|\)/g , "" ) : "" , A = navigator . userAgent . replace ( t [ 0 ] , "" ) , e [ 1 ] && ( A = A . replace ( t [ 1 ] , "" ) ) , A = A . replace ( / /g , " " ) } } else typeof process != "undefined" && ( e = ` ${ process . platform } ${ process . arch } ` , A = ` NodeJS ${ process . version } ` ) ; return { platform : e , agent : A } } var n = { } ; ue ( n , { data : ( ) => qA , version : ( ) => GA } ) ; b ( n , qt ) ; b ( n , Gt ) ; b ( n , Ut ) ; b ( n , Bt ) ; b ( n , Dt ) ; b ( n , Yt ) ; import { version as OA } from "@tensorflow/tfjs/package.json" ; import { version as LA } from "@tensorflow/tfjs-core/package.json" ; import { version as HA } from "@tensorflow/tfjs-data/package.json" ; import { version as VA } from "@tensorflow/tfjs-layers/package.json" ; import { version as ZA } from "@tensorflow/tfjs-converter/package.json" ; import { version as FA } from "@tensorflow/tfjs-backend-cpu/package.json" ; import { version as XA } from "@tensorflow/tfjs-backend-webgl/package.json" ; import { version as CA } from "@tensorflow/tfjs-backend-wasm/package.json" ; import * as qt from "@tensorflow/tfjs-core/dist/index.js" ; import * as Gt from "@tensorflow/tfjs-layers/dist/index.js" ; import * as Ut from "@tensorflow/tfjs-converter/dist/index.js" ; import * as qA from " @ tensorflow / tfjs - data / dist / index
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` ),g.FRAGMENT_IDENTITY=["precision highp float;","varying vec2 vUv;","uniform sampler2D texture;","void main(void) {","gl_FragColor = texture2D(texture, vUv);","}"].join( `
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` )}var A5=2048,R,F,q;function g0(e,A){let t;if(!e)throw new Error("Human: Input is missing");if(!(e instanceof n.Tensor)&&!(typeof Image!="undefined"&&e instanceof Image)&&!(typeof ImageData!="undefined"&&e instanceof ImageData)&&!(typeof ImageBitmap!="undefined"&&e instanceof ImageBitmap)&&!(typeof HTMLImageElement!="undefined"&&e instanceof HTMLImageElement)&&!(typeof HTMLMediaElement!="undefined"&&e instanceof HTMLMediaElement)&&!(typeof HTMLVideoElement!="undefined"&&e instanceof HTMLVideoElement)&&!(typeof HTMLCanvasElement!="undefined"&&e instanceof HTMLCanvasElement)&&!(typeof OffscreenCanvas!="undefined"&&e instanceof OffscreenCanvas))throw new Error("Human: Input type is not recognized");if(e instanceof n.Tensor)if(e.shape&&e.shape.length===4&&e.shape[0]===1&&e.shape[3]===3)t=n.clone(e);else throw new Error( ` Human : Input tensor shape must be [ 1 , height , width , 3 ] and instead was $ { e . shape } ` );else{let o=e.naturalWidth||e.videoWidth||e.width||e.shape&&e.shape[1]>0,a=e.naturalHeight||e.videoHeight||e.height||e.shape&&e.shape[2]>0;if(!o||!a)return{tensor:null,canvas:R};let i=o,s=a;if(i>A5&&(i=A5,s=i*a/o),s>A5&&(s=A5,i=s*o/a),A.filter.width>0?i=A.filter.width:A.filter.height>0&&(i=o*(A.filter.height/a)),A.filter.height>0?s=A.filter.height:A.filter.width>0&&(s=a*(A.filter.width/o)),!i||!s)throw new Error("Human: Input cannot determine dimension");(!R||(R==null?void 0:R.width)!==i||(R==null?void 0:R.height)!==s)&&(R=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(i,s):document.createElement("canvas"),(R==null?void 0:R.width)!==i&&(R.width=i),(R==null?void 0:R.height)!==s&&(R.height=s));let y=R.getContext("2d");if(e instanceof ImageData?y.putImageData(e,0,0):A.filter.flip&&typeof y.translate!="undefined"?(y.translate(o,0),y.scale(-1,1),y.drawImage(e,0,0,o,a,0,0,R==null?void 0:R.width,R==null?void 0:R.height),y.setTransform(1,0,0,1,0,0)):y.drawImage(e,0,0,o,a,0,0,R==null?void 0:R.width,R==null?void 0:R.height),A.filter.enabled){if((!q||!F||R.width!==F.width||(R==null?void 0:R.height)!==(F==null?void 0:F.height))&&(F=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(R==null?void 0:R.width,R==null?void 0:R.height):document.createElement("canvas"),(F==null?void 0:F.width)!==(R==null?void 0:R.width)&&(F.width=R==null?void 0:R.width),(F==null?void 0:F.height)!==(R==null?void 0:R.height)&&(F.height=R==null?void 0:R.height),q=n.ENV.flags.IS_BROWSER?new hA({canvas:F}):null),!q)return{tensor:null,canvas:R};q.reset(),q.addFilter("brightness",A.filter.brightness),A.filter.contrast!==0&&q.addFilter("contrast",A.filter.contrast),A.filter.sharpness!==0&&q.addFilter("sharpen",A.filter.sharpness),A.filter.blur!==0&&q.addFilter("blur",A.filter.blur),A.filter.saturation!==0&&q.addFilter("saturation",A.filter.saturation),A.filter.hue!==0&&q.addFilter("hue",A.filter.hue),A.filter.negative&&q.addFilter("negative"),A.filter.sepia&&q.addFilter("sepia"),A.filter.vintage&&q.addFilter("brownie"),A.filter.sepia&&q.addFilter("sepia"),A.filter.kodachrome&&q.addFilter("kodachrome"),A.filter.technicolor&&q.addFilter("technicolor"),A.filter.polaroid&&q.addFilter("polaroid"),A.filter.pixelate!==0&&q.addFilter("pixelate",A.filter.pixelate),q.apply(R)}else F=R,q&&(q=null);if(!t){let x;if(F.data){let l=[F.height,F.width,3];x=n.tensor3d(F.data,l,"int32")}else if(F instanceof ImageData)x=n.browser?n.browser.fromPixels(F):null;else if(A.backend==="webgl"||A.backend==="humangl"){let l=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(i,s):document.createElement("canvas");l.width=i,l.height=s;let c=l.getContext("2d");c==null||c.drawImage(F,0,0),x=n.browser?n.browser.fromPixels(l):null}else{let l=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(i,s):document.createElement("canvas");l.width=i,l.height=s;let c=l.getContext("2d");c==null||c.drawImage(F,0,0);let d=c==null?void 0:c.getImageData(0,0,i,s);x=n.browser?n.browser.fromPixels(d):null}if(x){let l=n.cast(x,"float32");t=n.expandDims(l,0),n.dispose(x),n.dispose(l)}}}let r=A.filter.return?F:null;return{tensor:t,canvas:r}}var t0,ye=!1;async function t5(e){return t0?e.debug&&M("cached m
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2020-12-12 16:15:51 +01:00
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2 Q == ` ;var he="2.1.5";var R0,Z0,F0,M0,T0,w0,s5,X0,a5,i5,x5,y5,l5=class{constructor(A){e0(this,R0,void 0);e0(this,Z0,void 0);e0(this,F0,void 0);e0(this,M0,void 0);e0(this,T0,void 0);e0(this,w0,void 0);this.analyze=(...A)=>{if(!G(this,Z0))return;let t=this.tf.engine().state.numTensors,r=G(this,R0);n0(this,R0,t);let o=t-r;o!==0&&M(...A,o)};e0(this,s5,A=>{if(!G(this,F0))return null;if(!A)return"input is not defined";if(this.tf.ENV.flags.IS_NODE&&!(A instanceof n.Tensor))return"input must be a tensor";try{this.tf.getBackend()}catch(t){return"backend not loaded"}return null});e0(this,X0,async(A=!1)=>{var t;if(this.config.backend&&this.config.backend.length>0&&A||this.tf.getBackend()!==this.config.backend){let r=L();if(this.state="backend",this.config.backend&&this.config.backend.length>0){if(typeof window=="undefined"&&typeof WorkerGlobalScope!="undefined"&&this.config.debug&&M("running inside web worker"),this.tf.ENV.flags.IS_BROWSER&&this.config.backend==="tensorflow"&&(M("override: backend set to tensorflow while running in browser"),this.config.backend="humangl"),this.tf.ENV.flags.IS_NODE&&(this.config.backend==="webgl"||this.config.backend==="humangl")&&(M("override: backend set to webgl while running in nodejs"),this.config.backend="tensorflow"),this.tf.ENV.flags.IS_BROWSER&&this.config.backend==="webgpu")if(typeof navigator=="undefined"||typeof navigator.gpu=="undefined")M("override: backend set to webgpu but browser does not support webgpu"),this.config.backend="humangl";else{let a=await navigator.gpu.requestAdapter();this.config.debug&&M("enumerated webgpu adapter:",a)}this.config.backend==="humangl"&&ge();let o=Object.keys(this.tf.engine().registryFactory);if(this.config.debug&&M("available backends:",o),o.includes(this.config.backend)||(M( ` error : backend $ { this . config . backend } not found in registry ` ),this.config.backend=this.tf.ENV.flags.IS_NODE?"tensorflow":"humangl",M( ` override : using backend $ { this . config . backend } instead ` )),this.config.debug&&M("setting backend:",this.config.backend),this.config.backend==="wasm"){if(this.config.debug&&M("wasm path:",this.config.wasmPath),typeof((t=this.tf)==null?void 0:t.setWasmPaths)!="undefined")this.tf.setWasmPaths(this.config.wasmPath);else throw new Error("Human: WASM backend is not loaded");let a=await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT"),i=await this.tf.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");this.config.debug&&M( ` wasm execution : $ { a ? "SIMD" : "no SIMD" } $ { i ? "multithreaded" : "singlethreaded" } ` ),this.config.debug&&!a&&M("warning: wasm simd support is not enabled")}try{await this.tf.setBackend(this.config.backend)}catch(a){M("error: cannot set backend:",this.config.backend,a)}}if(this.tf.getBackend()==="webgl"||this.tf.getBackend()==="humangl"){this.tf.ENV.set("CHECK_COMPUTATION_FOR_ERRORS",!1),this.tf.ENV.set("WEBGL_CPU_FORWARD",!0),this.tf.ENV.set("WEBGL_PACK_DEPTHWISECONV",!0),this.tf.ENV.set("WEBGL_USE_SHAPES_UNIFORMS",!0),typeof this.config.deallocate!="undefined"&&this.config.deallocate&&(M("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",!0),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",0));let o=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&M( ` gl version : $ { o . getParameter ( o . VERSION ) } renderer : $ { o . getParameter ( o . RENDERER ) } ` )}this.tf.enableProdMode(),await this.tf.ready(),this.performance.backend=Math.trunc(L()-r)}});this.next=A=>jA(A||this.result);e0(this,a5,async A=>{if(this.config.cacheSensitivity===0)return!1;let t=32;if(!A.shape[1]||!A.shape[2])return!1;let r=n.image.resizeBilinear(A,[Math.trunc(A.shape[1]/t),Math.trunc(A.shape[2]/t)]),o=await r.data(),a=0;for(let y=0;y<o.length/3;y++)a+=o[3*y+2];r.dispose();let i=100*(Math.max(a,G(this,T0))/Math.min(a,G(this,T0))-1);n0(this,T0,a);let s=i<Math.max(this.config.cacheSensitivity,G(this,w0));return n0(this,w0,i>10*this.config.cacheSensitivity?0:i),s});e0(this,i5,async()=>{let A=(o,a="application/octet-stream")=>fetch( ` data : $ { a } ; base64 , $ { o } ` ).then(i=>i.blob()),t,r;switch(this.config.warmup){case"face":t=await A(o5);break;case"full":t=await A(r5);break;default:t=null}if(t){let o=await
2020-10-15 14:16:34 +02:00
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