diff --git a/.api-extractor.json b/.api-extractor.json
index e1f8299b..33a6658d 100644
--- a/.api-extractor.json
+++ b/.api-extractor.json
@@ -1,7 +1,7 @@
 {
   "$schema": "https://developer.microsoft.com/json-schemas/api-extractor/v7/api-extractor.schema.json",
   "mainEntryPointFilePath": "types/lib/src/human.d.ts",
-  "bundledPackages": ["@tensorflow/tfjs-core", "@tensorflow/tfjs-converter", "@tensorflow/tfjs-data", "@tensorflow/tfjs-layers"],
+  "bundledPackages": ["@tensorflow/tfjs-core", "@tensorflow/tfjs-converter"],
   "compiler": {
     "skipLibCheck": false
   },
diff --git a/.build.json b/.build.json
index 971b2f55..cab0f010 100644
--- a/.build.json
+++ b/.build.json
@@ -12,7 +12,7 @@
     "clean": ["clean"]
   },
   "clean": {
-    "locations": ["dist/*", "types/lib/*", "typedoc/*"]
+    "locations": ["dist/*", "types/*", "typedoc/*"]
   },
   "lint": {
     "locations": [ "*.json", "src/**/*.ts", "test/**/*.js", "demo/**/*.js" ],
@@ -24,8 +24,8 @@
   "serve": {
     "sslKey": "node_modules/@vladmandic/build/cert/https.key",
     "sslCrt": "node_modules/@vladmandic/build/cert/https.crt",
-    "httpPort": 10030,
-    "httpsPort": 10031,
+    "httpPort": 8000,
+    "httpsPort": 8001,
     "documentRoot": ".",
     "defaultFolder": "demo",
     "defaultFile": "index.html"
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 7a201178..7c4074fe 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,6 +1,6 @@
 # @vladmandic/human  
 
-  Version: **2.11.1**  
+  Version: **3.0.0**  
   Description: **Human: AI-powered 3D Face Detection & Rotation Tracking, Face Description & Recognition, Body Pose Tracking, 3D Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction, Gesture Recognition**  
   
   Author: **Vladimir Mandic <mandic00@live.com>**  
@@ -9,7 +9,10 @@
   
 ## Changelog
   
-### **HEAD -> main** 2022/10/09 mandic00@live.com
+### **HEAD -> main** 2022/10/13 mandic00@live.com
+
+
+### **release: 2.11.1** 2022/10/09 mandic00@live.com
 
 
 ### **2.11.1** 2022/10/09 mandic00@live.com
diff --git a/README.md b/README.md
index 204b2a8b..a24822b8 100644
--- a/README.md
+++ b/README.md
@@ -12,7 +12,8 @@
 **Body Pose Tracking, 3D Hand & Finger Tracking, Iris Analysis,**  
 **Age & Gender & Emotion Prediction, Gaze Tracking, Gesture Recognition, Body Segmentation**  
 
-JavaScript module using TensorFlow/JS Machine Learning library  
+<br>
+
 ## Highlights
 
 - Compatible with most server-side and client-side environments and frameworks  
@@ -239,7 +240,7 @@ Additionally, `HTMLVideoElement`, `HTMLMediaElement` can be a standard `<video>`
   e.g.: **HLS** (*HTTP Live Streaming*) using `hls.js` or **DASH** (*Dynamic Adaptive Streaming over HTTP*) using `dash.js`
 - **WebRTC** media track using built-in support  
 
-<br>
+<br><hr><br>
 
 ## Code Examples
 
@@ -375,6 +376,27 @@ drawResults(); // start draw loop
 
 And for even better results, you can run detection in a separate web worker thread
 
+<br><hr><br>
+
+## TypeDefs
+
+`Human` is written using TypeScript strong typing and ships with full **TypeDefs** for all classes defined by the library bundled in `types/human.d.ts` and enabled by default  
+
+*Note*: This does not include embedded `tfjs`  
+If you want to use embedded `tfjs` inside `Human` (`human.tf` namespace) and still full **typedefs**, add this code:
+
+```js
+import type * as tfjs from '@vladmandic/human/dist/tfjs.esm';
+...
+const tf = human.tf as typeof tfjs;
+```
+
+This is not enabled by default as `Human` does not ship with full **TFJS TypeDefs** due to size considerations  
+Enabling `tfjs` TypeDefs as above creates additional project (dev-only as only types are required) dependencies as defined in `@vladmandic/human/dist/tfjs.esm.d.ts`:
+
+    @tensorflow/tfjs-core, @tensorflow/tfjs-converter, @tensorflow/tfjs-backend-wasm, @tensorflow/tfjs-backend-webgl
+
+
 <br><hr><br>
 
 ## Default models
@@ -404,9 +426,9 @@ For more info, see [**Configuration Details**](https://github.com/vladmandic/hum
 
 <br><hr><br>
 
-`Human` library is written in `TypeScript` [4.8](https://www.typescriptlang.org/docs/handbook/intro.html)  
-Conforming to latest `JavaScript` [ECMAScript version 2022](https://262.ecma-international.org/) standard  
-Build target is `JavaScript` [EMCAScript version 2018](https://262.ecma-international.org/11.0/)  
+`Human` library is written in [TypeScript](https://www.typescriptlang.org/docs/handbook/intro.html) **4.8** using [TensorFlow/JS](https://www.tensorflow.org/js/) **4.0** and conforming to latest `JavaScript` [ECMAScript version 2022](https://262.ecma-international.org/) standard  
+
+Build target for distributables is `JavaScript` [EMCAScript version 2018](https://262.ecma-international.org/9.0/)  
 
 <br>
 
diff --git a/TODO.md b/TODO.md
index ed1d76e6..8c56cae4 100644
--- a/TODO.md
+++ b/TODO.md
@@ -2,6 +2,8 @@
 
 ## Work-in-Progress
 
+- `src/tfjs/tfjs.esm.d.ts`
+- `src/tfjs/long.d.ts`
 
 <hr><br>
 
diff --git a/build.js b/build.js
index db38a1e2..e735e21d 100644
--- a/build.js
+++ b/build.js
@@ -93,8 +93,8 @@ async function main() {
   const build = new Build();
   await build.run('production');
   // patch tfjs typedefs
-  log.state('Copy:', { input: 'tfjs/tfjs.esm.d.ts' });
-  copy('tfjs/tfjs.esm.d.ts', 'types/lib/dist/tfjs.esm.d.ts');
+  log.state('Copy:', { input: 'src/tfjs/tfjs.esm.d.ts', output: 'dist/tfjs.esm.d.ts' });
+  copy('src/tfjs/tfjs.esm.d.ts', 'dist/tfjs.esm.d.ts');
   // run api-extractor to create typedef rollup
   const extractorConfig = APIExtractor.ExtractorConfig.loadFileAndPrepare('.api-extractor.json');
   const extractorResult = APIExtractor.Extractor.invoke(extractorConfig, {
diff --git a/demo/faceid/index.js b/demo/faceid/index.js
index 2cd259dd..1630f8a6 100644
--- a/demo/faceid/index.js
+++ b/demo/faceid/index.js
@@ -4,6 +4,6 @@
   author: <https://github.com/vladmandic>'
 */
 
-import*as S from"../../dist/human.esm.js";var l,L="human",f="person",v=(...a)=>console.log("indexdb",...a);async function h(){return l?!0:new Promise(a=>{let n=indexedDB.open(L,1);n.onerror=o=>v("error:",o),n.onupgradeneeded=o=>{v("create:",o.target),l=o.target.result,l.createObjectStore(f,{keyPath:"id",autoIncrement:!0})},n.onsuccess=o=>{l=o.target.result,v("open:",l),a(!0)}})}async function C(){let a=[];return l||await h(),new Promise(n=>{let o=l.transaction([f],"readwrite").objectStore(f).openCursor(null,"next");o.onerror=i=>v("load error:",i),o.onsuccess=i=>{i.target.result?(a.push(i.target.result.value),i.target.result.continue()):n(a)}})}async function b(){return l||await h(),new Promise(a=>{let n=l.transaction([f],"readwrite").objectStore(f).count();n.onerror=o=>v("count error:",o),n.onsuccess=()=>a(n.result)})}async function x(a){l||await h();let n={name:a.name,descriptor:a.descriptor,image:a.image};l.transaction([f],"readwrite").objectStore(f).put(n),v("save:",n)}async function D(a){l||await h(),l.transaction([f],"readwrite").objectStore(f).delete(a.id),v("delete:",a)}var g={cacheSensitivity:0,modelBasePath:"../../models",filter:{equalization:!0},face:{enabled:!0,detector:{rotation:!0,return:!0,cropFactor:1.6,mask:!1},description:{enabled:!0},iris:{enabled:!0},emotion:{enabled:!1},antispoof:{enabled:!0},liveness:{enabled:!0}},body:{enabled:!1},hand:{enabled:!1},object:{enabled:!1},gesture:{enabled:!0}},B={order:2,multiplier:25,min:.2,max:.8},d={minConfidence:.6,minSize:224,maxTime:3e4,blinkMin:10,blinkMax:800,threshold:.5,mask:g.face.detector.mask,rotation:g.face.detector.rotation,cropFactor:g.face.detector.cropFactor,...B},e={faceCount:{status:!1,val:0},faceConfidence:{status:!1,val:0},facingCenter:{status:!1,val:0},lookingCenter:{status:!1,val:0},blinkDetected:{status:!1,val:0},faceSize:{status:!1,val:0},antispoofCheck:{status:!1,val:0},livenessCheck:{status:!1,val:0},age:{status:!1,val:0},gender:{status:!1,val:0},timeout:{status:!0,val:0},descriptor:{status:!1,val:0},elapsedMs:{status:void 0,val:0},detectFPS:{status:void 0,val:0},drawFPS:{status:void 0,val:0}},E=()=>e.faceCount.status&&e.faceSize.status&&e.blinkDetected.status&&e.facingCenter.status&&e.lookingCenter.status&&e.faceConfidence.status&&e.antispoofCheck.status&&e.livenessCheck.status&&e.descriptor.status&&e.age.status&&e.gender.status,c={face:null,record:null},u={start:0,end:0,time:0},s=new S.Human(g);s.env.perfadd=!1;s.draw.options.font='small-caps 18px "Lato"';s.draw.options.lineHeight=20;var t={video:document.getElementById("video"),canvas:document.getElementById("canvas"),log:document.getElementById("log"),fps:document.getElementById("fps"),match:document.getElementById("match"),name:document.getElementById("name"),save:document.getElementById("save"),delete:document.getElementById("delete"),retry:document.getElementById("retry"),source:document.getElementById("source"),ok:document.getElementById("ok")},y={detect:0,draw:0},I=0,r=(...a)=>{t.log.innerText+=a.join(" ")+`
-`,console.log(...a)};async function H(){let a={audio:!1,video:{facingMode:"user",resizeMode:"none",width:{ideal:document.body.clientWidth}}},n=await navigator.mediaDevices.getUserMedia(a),o=new Promise(i=>{t.video.onloadeddata=()=>i(!0)});t.video.srcObject=n,t.video.play(),await o,t.canvas.width=t.video.videoWidth,t.canvas.height=t.video.videoHeight,t.canvas.style.width="50%",t.canvas.style.height="50%",s.env.initial&&r("video:",t.video.videoWidth,t.video.videoHeight,"|",n.getVideoTracks()[0].label),t.canvas.onclick=()=>{t.video.paused?t.video.play():t.video.pause()}}async function T(){var a;if(!t.video.paused){(a=c.face)!=null&&a.tensor&&s.tf.dispose(c.face.tensor),await s.detect(t.video);let n=s.now();e.detectFPS.val=Math.round(1e4/(n-y.detect))/10,y.detect=n,requestAnimationFrame(T)}}function P(){let a=32;for(let[n,o]of Object.entries(e)){let i=document.getElementById(`ok-${n}`);i||(i=document.createElement("div"),i.id=`ok-${n}`,i.innerText=n,i.className="ok",i.style.top=`${a}px`,t.ok.appendChild(i)),typeof o.status=="boolean"&&(i.style.backgroundColor=o.status?"lightgreen":"lightcoral");let m=o.status?"ok":"fail";i.innerText=`${n}: ${o.val===0?m:o.val}`,a+=28}}async function R(){var o;let a=s.next(s.result);s.draw.canvas(t.video,t.canvas),await s.draw.all(t.canvas,a);let n=s.now();if(e.drawFPS.val=Math.round(1e4/(n-y.draw))/10,y.draw=n,e.faceCount.val=s.result.face.length,e.faceCount.status=e.faceCount.val===1,e.faceCount.status){let i=Object.values(s.result.gesture).map(m=>m.gesture);(i.includes("blink left eye")||i.includes("blink right eye"))&&(u.start=s.now()),u.start>0&&!i.includes("blink left eye")&&!i.includes("blink right eye")&&(u.end=s.now()),e.blinkDetected.status=e.blinkDetected.status||Math.abs(u.end-u.start)>d.blinkMin&&Math.abs(u.end-u.start)<d.blinkMax,e.blinkDetected.status&&u.time===0&&(u.time=Math.trunc(u.end-u.start)),e.facingCenter.status=i.includes("facing center"),e.lookingCenter.status=i.includes("looking center"),e.faceConfidence.val=s.result.face[0].faceScore||s.result.face[0].boxScore||0,e.faceConfidence.status=e.faceConfidence.val>=d.minConfidence,e.antispoofCheck.val=s.result.face[0].real||0,e.antispoofCheck.status=e.antispoofCheck.val>=d.minConfidence,e.livenessCheck.val=s.result.face[0].live||0,e.livenessCheck.status=e.livenessCheck.val>=d.minConfidence,e.faceSize.val=Math.min(s.result.face[0].box[2],s.result.face[0].box[3]),e.faceSize.status=e.faceSize.val>=d.minSize,e.descriptor.val=((o=s.result.face[0].embedding)==null?void 0:o.length)||0,e.descriptor.status=e.descriptor.val>0,e.age.val=s.result.face[0].age||0,e.age.status=e.age.val>0,e.gender.val=s.result.face[0].genderScore||0,e.gender.status=e.gender.val>=d.minConfidence}return e.timeout.status=e.elapsedMs.val<=d.maxTime,P(),E()||!e.timeout.status?(t.video.pause(),s.result.face[0]):(e.elapsedMs.val=Math.trunc(s.now()-I),new Promise(i=>{setTimeout(async()=>{await R(),i(s.result.face[0])},30)}))}async function z(){var a,n,o,i;if(t.name.value.length>0){let m=(a=t.canvas.getContext("2d"))==null?void 0:a.getImageData(0,0,t.canvas.width,t.canvas.height),p={id:0,name:t.name.value,descriptor:(n=c.face)==null?void 0:n.embedding,image:m};await x(p),r("saved face record:",p.name,"descriptor length:",(i=(o=c.face)==null?void 0:o.embedding)==null?void 0:i.length),r("known face records:",await b())}else r("invalid name")}async function j(){c.record&&c.record.id>0&&await D(c.record)}async function $(){var i,m,p,k;if(t.canvas.style.height="",(i=t.canvas.getContext("2d"))==null||i.clearRect(0,0,d.minSize,d.minSize),!((m=c==null?void 0:c.face)!=null&&m.tensor)||!((p=c==null?void 0:c.face)!=null&&p.embedding))return!1;if(console.log("face record:",c.face),r(`detected face: ${c.face.gender} ${c.face.age||0}y distance ${c.face.iris||0}cm/${Math.round(100*(c.face.iris||0)/2.54)/100}in`),s.tf.browser.toPixels(c.face.tensor,t.canvas),await b()===0)return r("face database is empty: nothing to compare face with"),document.body.style.background="black",t.delete.style.display="none",!1;let a=await C(),n=a.map(w=>w.descriptor).filter(w=>w.length>0),o=s.match(c.face.embedding,n,B);return c.record=a[o.index]||null,c.record&&(r(`best match: ${c.record.name} | id: ${c.record.id} | similarity: ${Math.round(1e3*o.similarity)/10}%`),t.name.value=c.record.name,t.source.style.display="",(k=t.source.getContext("2d"))==null||k.putImageData(c.record.image,0,0)),document.body.style.background=o.similarity>d.threshold?"darkgreen":"maroon",o.similarity>d.threshold}async function M(){var a,n;return e.faceCount.status=!1,e.faceConfidence.status=!1,e.facingCenter.status=!1,e.blinkDetected.status=!1,e.faceSize.status=!1,e.antispoofCheck.status=!1,e.livenessCheck.status=!1,e.age.status=!1,e.gender.status=!1,e.elapsedMs.val=0,t.match.style.display="none",t.retry.style.display="none",t.source.style.display="none",t.canvas.style.height="50%",document.body.style.background="black",await H(),await T(),I=s.now(),c.face=await R(),t.canvas.width=((a=c.face.tensor)==null?void 0:a.shape[1])||d.minSize,t.canvas.height=((n=c.face.tensor)==null?void 0:n.shape[0])||d.minSize,t.source.width=t.canvas.width,t.source.height=t.canvas.height,t.canvas.style.width="",t.match.style.display="flex",t.save.style.display="flex",t.delete.style.display="flex",t.retry.style.display="block",E()?$():(r("did not find valid face"),!1)}async function q(){var a,n;r("human version:",s.version,"| tfjs version:",s.tf.version["tfjs-core"]),r("options:",JSON.stringify(d).replace(/{|}|"|\[|\]/g,"").replace(/,/g," ")),r("initializing webcam..."),await H(),r("loading human models..."),await s.load(),r("initializing human..."),r("face embedding model:",g.face.description.enabled?"faceres":"",(a=g.face.mobilefacenet)!=null&&a.enabled?"mobilefacenet":"",(n=g.face.insightface)!=null&&n.enabled?"insightface":""),r("loading face database..."),r("known face records:",await b()),t.retry.addEventListener("click",M),t.save.addEventListener("click",z),t.delete.addEventListener("click",j),await s.warmup(),await M()}window.onload=q;
+import*as S from"../../dist/human.esm.js";var l,F="human",f="person",v=(...a)=>console.log("indexdb",...a);async function h(){return l?!0:new Promise(a=>{let n=indexedDB.open(F,1);n.onerror=o=>v("error:",o),n.onupgradeneeded=o=>{v("create:",o.target),l=o.target.result,l.createObjectStore(f,{keyPath:"id",autoIncrement:!0})},n.onsuccess=o=>{l=o.target.result,v("open:",l),a(!0)}})}async function C(){let a=[];return l||await h(),new Promise(n=>{let o=l.transaction([f],"readwrite").objectStore(f).openCursor(null,"next");o.onerror=i=>v("load error:",i),o.onsuccess=i=>{i.target.result?(a.push(i.target.result.value),i.target.result.continue()):n(a)}})}async function b(){return l||await h(),new Promise(a=>{let n=l.transaction([f],"readwrite").objectStore(f).count();n.onerror=o=>v("count error:",o),n.onsuccess=()=>a(n.result)})}async function x(a){l||await h();let n={name:a.name,descriptor:a.descriptor,image:a.image};l.transaction([f],"readwrite").objectStore(f).put(n),v("save:",n)}async function D(a){l||await h(),l.transaction([f],"readwrite").objectStore(f).delete(a.id),v("delete:",a)}var g={cacheSensitivity:0,modelBasePath:"../../models",filter:{equalization:!0},face:{enabled:!0,detector:{rotation:!0,return:!0,cropFactor:1.6,mask:!1},description:{enabled:!0},iris:{enabled:!0},emotion:{enabled:!1},antispoof:{enabled:!0},liveness:{enabled:!0}},body:{enabled:!1},hand:{enabled:!1},object:{enabled:!1},gesture:{enabled:!0}},B={order:2,multiplier:25,min:.2,max:.8},d={minConfidence:.6,minSize:224,maxTime:3e4,blinkMin:10,blinkMax:800,threshold:.5,mask:g.face.detector.mask,rotation:g.face.detector.rotation,cropFactor:g.face.detector.cropFactor,...B},e={faceCount:{status:!1,val:0},faceConfidence:{status:!1,val:0},facingCenter:{status:!1,val:0},lookingCenter:{status:!1,val:0},blinkDetected:{status:!1,val:0},faceSize:{status:!1,val:0},antispoofCheck:{status:!1,val:0},livenessCheck:{status:!1,val:0},age:{status:!1,val:0},gender:{status:!1,val:0},timeout:{status:!0,val:0},descriptor:{status:!1,val:0},elapsedMs:{status:void 0,val:0},detectFPS:{status:void 0,val:0},drawFPS:{status:void 0,val:0}},E=()=>e.faceCount.status&&e.faceSize.status&&e.blinkDetected.status&&e.facingCenter.status&&e.lookingCenter.status&&e.faceConfidence.status&&e.antispoofCheck.status&&e.livenessCheck.status&&e.descriptor.status&&e.age.status&&e.gender.status,c={face:null,record:null},u={start:0,end:0,time:0},s=new S.Human(g);s.env.perfadd=!1;s.draw.options.font='small-caps 18px "Lato"';s.draw.options.lineHeight=20;var t={video:document.getElementById("video"),canvas:document.getElementById("canvas"),log:document.getElementById("log"),fps:document.getElementById("fps"),match:document.getElementById("match"),name:document.getElementById("name"),save:document.getElementById("save"),delete:document.getElementById("delete"),retry:document.getElementById("retry"),source:document.getElementById("source"),ok:document.getElementById("ok")},y={detect:0,draw:0},I=0,r=(...a)=>{t.log.innerText+=a.join(" ")+`
+`,console.log(...a)};async function H(){let a={audio:!1,video:{facingMode:"user",resizeMode:"none",width:{ideal:document.body.clientWidth}}},n=await navigator.mediaDevices.getUserMedia(a),o=new Promise(i=>{t.video.onloadeddata=()=>i(!0)});t.video.srcObject=n,t.video.play(),await o,t.canvas.width=t.video.videoWidth,t.canvas.height=t.video.videoHeight,t.canvas.style.width="50%",t.canvas.style.height="50%",s.env.initial&&r("video:",t.video.videoWidth,t.video.videoHeight,"|",n.getVideoTracks()[0].label),t.canvas.onclick=()=>{t.video.paused?t.video.play():t.video.pause()}}async function T(){var a;if(!t.video.paused){(a=c.face)!=null&&a.tensor&&s.tf.dispose(c.face.tensor),await s.detect(t.video);let n=s.now();e.detectFPS.val=Math.round(1e4/(n-y.detect))/10,y.detect=n,requestAnimationFrame(T)}}function P(){let a=32;for(let[n,o]of Object.entries(e)){let i=document.getElementById(`ok-${n}`);i||(i=document.createElement("div"),i.id=`ok-${n}`,i.innerText=n,i.className="ok",i.style.top=`${a}px`,t.ok.appendChild(i)),typeof o.status=="boolean"&&(i.style.backgroundColor=o.status?"lightgreen":"lightcoral");let m=o.status?"ok":"fail";i.innerText=`${n}: ${o.val===0?m:o.val}`,a+=28}}async function R(){var o;let a=s.next(s.result);s.draw.canvas(t.video,t.canvas),await s.draw.all(t.canvas,a);let n=s.now();if(e.drawFPS.val=Math.round(1e4/(n-y.draw))/10,y.draw=n,e.faceCount.val=s.result.face.length,e.faceCount.status=e.faceCount.val===1,e.faceCount.status){let i=Object.values(s.result.gesture).map(m=>m.gesture);(i.includes("blink left eye")||i.includes("blink right eye"))&&(u.start=s.now()),u.start>0&&!i.includes("blink left eye")&&!i.includes("blink right eye")&&(u.end=s.now()),e.blinkDetected.status=e.blinkDetected.status||Math.abs(u.end-u.start)>d.blinkMin&&Math.abs(u.end-u.start)<d.blinkMax,e.blinkDetected.status&&u.time===0&&(u.time=Math.trunc(u.end-u.start)),e.facingCenter.status=i.includes("facing center"),e.lookingCenter.status=i.includes("looking center"),e.faceConfidence.val=s.result.face[0].faceScore||s.result.face[0].boxScore||0,e.faceConfidence.status=e.faceConfidence.val>=d.minConfidence,e.antispoofCheck.val=s.result.face[0].real||0,e.antispoofCheck.status=e.antispoofCheck.val>=d.minConfidence,e.livenessCheck.val=s.result.face[0].live||0,e.livenessCheck.status=e.livenessCheck.val>=d.minConfidence,e.faceSize.val=Math.min(s.result.face[0].box[2],s.result.face[0].box[3]),e.faceSize.status=e.faceSize.val>=d.minSize,e.descriptor.val=((o=s.result.face[0].embedding)==null?void 0:o.length)||0,e.descriptor.status=e.descriptor.val>0,e.age.val=s.result.face[0].age||0,e.age.status=e.age.val>0,e.gender.val=s.result.face[0].genderScore||0,e.gender.status=e.gender.val>=d.minConfidence}return e.timeout.status=e.elapsedMs.val<=d.maxTime,P(),E()||!e.timeout.status?(t.video.pause(),s.result.face[0]):(e.elapsedMs.val=Math.trunc(s.now()-I),new Promise(i=>{setTimeout(async()=>{await R(),i(s.result.face[0])},30)}))}async function z(){var a,n,o,i;if(t.name.value.length>0){let m=(a=t.canvas.getContext("2d"))==null?void 0:a.getImageData(0,0,t.canvas.width,t.canvas.height),p={id:0,name:t.name.value,descriptor:(n=c.face)==null?void 0:n.embedding,image:m};await x(p),r("saved face record:",p.name,"descriptor length:",(i=(o=c.face)==null?void 0:o.embedding)==null?void 0:i.length),r("known face records:",await b())}else r("invalid name")}async function j(){c.record&&c.record.id>0&&await D(c.record)}async function $(){var i,m,p,k;if(t.canvas.style.height="",(i=t.canvas.getContext("2d"))==null||i.clearRect(0,0,d.minSize,d.minSize),!((m=c==null?void 0:c.face)!=null&&m.tensor)||!((p=c==null?void 0:c.face)!=null&&p.embedding))return!1;if(console.log("face record:",c.face),r(`detected face: ${c.face.gender} ${c.face.age||0}y distance ${c.face.iris||0}cm/${Math.round(100*(c.face.iris||0)/2.54)/100}in`),await s.tf.browser.toPixels(c.face.tensor,t.canvas),await b()===0)return r("face database is empty: nothing to compare face with"),document.body.style.background="black",t.delete.style.display="none",!1;let a=await C(),n=a.map(w=>w.descriptor).filter(w=>w.length>0),o=s.match(c.face.embedding,n,B);return c.record=a[o.index]||null,c.record&&(r(`best match: ${c.record.name} | id: ${c.record.id} | similarity: ${Math.round(1e3*o.similarity)/10}%`),t.name.value=c.record.name,t.source.style.display="",(k=t.source.getContext("2d"))==null||k.putImageData(c.record.image,0,0)),document.body.style.background=o.similarity>d.threshold?"darkgreen":"maroon",o.similarity>d.threshold}async function M(){var a,n;return e.faceCount.status=!1,e.faceConfidence.status=!1,e.facingCenter.status=!1,e.blinkDetected.status=!1,e.faceSize.status=!1,e.antispoofCheck.status=!1,e.livenessCheck.status=!1,e.age.status=!1,e.gender.status=!1,e.elapsedMs.val=0,t.match.style.display="none",t.retry.style.display="none",t.source.style.display="none",t.canvas.style.height="50%",document.body.style.background="black",await H(),await T(),I=s.now(),c.face=await R(),t.canvas.width=((a=c.face.tensor)==null?void 0:a.shape[1])||d.minSize,t.canvas.height=((n=c.face.tensor)==null?void 0:n.shape[0])||d.minSize,t.source.width=t.canvas.width,t.source.height=t.canvas.height,t.canvas.style.width="",t.match.style.display="flex",t.save.style.display="flex",t.delete.style.display="flex",t.retry.style.display="block",E()?$():(r("did not find valid face"),!1)}async function q(){var a,n;r("human version:",s.version,"| tfjs version:",s.tf.version["tfjs-core"]),r("options:",JSON.stringify(d).replace(/{|}|"|\[|\]/g,"").replace(/,/g," ")),r("initializing webcam..."),await H(),r("loading human models..."),await s.load(),r("initializing human..."),r("face embedding model:",g.face.description.enabled?"faceres":"",(a=g.face.mobilefacenet)!=null&&a.enabled?"mobilefacenet":"",(n=g.face.insightface)!=null&&n.enabled?"insightface":""),r("loading face database..."),r("known face records:",await b()),t.retry.addEventListener("click",M),t.save.addEventListener("click",z),t.delete.addEventListener("click",j),await s.warmup(),await M()}window.onload=q;
 //# sourceMappingURL=index.js.map
diff --git a/demo/faceid/index.js.map b/demo/faceid/index.js.map
index ba7ac80d..37efd22e 100644
--- a/demo/faceid/index.js.map
+++ b/demo/faceid/index.js.map
@@ -1,7 +1,7 @@
 {
   "version": 3,
   "sources": ["index.ts", "indexdb.ts"],
-  "sourcesContent": ["/**\n * Human demo for browsers\n * @default Human Library\n * @summary <https://github.com/vladmandic/human>\n * @author <https://github.com/vladmandic>\n * @copyright <https://github.com/vladmandic>\n * @license MIT\n */\n\nimport * as H from '../../dist/human.esm.js'; // equivalent of @vladmandic/Human\nimport * as indexDb from './indexdb'; // methods to deal with indexdb\n\nconst humanConfig = { // user configuration for human, used to fine-tune behavior\n  cacheSensitivity: 0,\n  modelBasePath: '../../models',\n  filter: { equalization: true }, // lets run with histogram equilizer\n  face: {\n    enabled: true,\n    detector: { rotation: true, return: true, cropFactor: 1.6, mask: false }, // return tensor is used to get detected face image\n    description: { enabled: true }, // default model for face descriptor extraction is faceres\n    // mobilefacenet: { enabled: true, modelPath: 'https://vladmandic.github.io/human-models/models/mobilefacenet.json' }, // alternative model\n    // insightface: { enabled: true, modelPath: 'https://vladmandic.github.io/insightface/models/insightface-mobilenet-swish.json' }, // alternative model\n    iris: { enabled: true }, // needed to determine gaze direction\n    emotion: { enabled: false }, // not needed\n    antispoof: { enabled: true }, // enable optional antispoof module\n    liveness: { enabled: true }, // enable optional liveness module\n  },\n  body: { enabled: false },\n  hand: { enabled: false },\n  object: { enabled: false },\n  gesture: { enabled: true }, // parses face and iris gestures\n};\n\n// const matchOptions = { order: 2, multiplier: 1000, min: 0.0, max: 1.0 }; // for embedding model\nconst matchOptions = { order: 2, multiplier: 25, min: 0.2, max: 0.8 }; // for faceres model\n\nconst options = {\n  minConfidence: 0.6, // overal face confidence for box, face, gender, real, live\n  minSize: 224, // min input to face descriptor model before degradation\n  maxTime: 30000, // max time before giving up\n  blinkMin: 10, // minimum duration of a valid blink\n  blinkMax: 800, // maximum duration of a valid blink\n  threshold: 0.5, // minimum similarity\n  mask: humanConfig.face.detector.mask,\n  rotation: humanConfig.face.detector.rotation,\n  cropFactor: humanConfig.face.detector.cropFactor,\n  ...matchOptions,\n};\n\nconst ok: Record<string, { status: boolean | undefined, val: number }> = { // must meet all rules\n  faceCount: { status: false, val: 0 },\n  faceConfidence: { status: false, val: 0 },\n  facingCenter: { status: false, val: 0 },\n  lookingCenter: { status: false, val: 0 },\n  blinkDetected: { status: false, val: 0 },\n  faceSize: { status: false, val: 0 },\n  antispoofCheck: { status: false, val: 0 },\n  livenessCheck: { status: false, val: 0 },\n  age: { status: false, val: 0 },\n  gender: { status: false, val: 0 },\n  timeout: { status: true, val: 0 },\n  descriptor: { status: false, val: 0 },\n  elapsedMs: { status: undefined, val: 0 }, // total time while waiting for valid face\n  detectFPS: { status: undefined, val: 0 }, // mark detection fps performance\n  drawFPS: { status: undefined, val: 0 }, // mark redraw fps performance\n};\n\nconst allOk = () => ok.faceCount.status\n  && ok.faceSize.status\n  && ok.blinkDetected.status\n  && ok.facingCenter.status\n  && ok.lookingCenter.status\n  && ok.faceConfidence.status\n  && ok.antispoofCheck.status\n  && ok.livenessCheck.status\n  && ok.descriptor.status\n  && ok.age.status\n  && ok.gender.status;\n\nconst current: { face: H.FaceResult | null, record: indexDb.FaceRecord | null } = { face: null, record: null }; // current face record and matched database record\n\nconst blink = { // internal timers for blink start/end/duration\n  start: 0,\n  end: 0,\n  time: 0,\n};\n\n// let db: Array<{ name: string, source: string, embedding: number[] }> = []; // holds loaded face descriptor database\nconst human = new H.Human(humanConfig); // create instance of human with overrides from user configuration\n\nhuman.env.perfadd = false; // is performance data showing instant or total values\nhuman.draw.options.font = 'small-caps 18px \"Lato\"'; // set font used to draw labels when using draw methods\nhuman.draw.options.lineHeight = 20;\n\nconst dom = { // grab instances of dom objects so we dont have to look them up later\n  video: document.getElementById('video') as HTMLVideoElement,\n  canvas: document.getElementById('canvas') as HTMLCanvasElement,\n  log: document.getElementById('log') as HTMLPreElement,\n  fps: document.getElementById('fps') as HTMLPreElement,\n  match: document.getElementById('match') as HTMLDivElement,\n  name: document.getElementById('name') as HTMLInputElement,\n  save: document.getElementById('save') as HTMLSpanElement,\n  delete: document.getElementById('delete') as HTMLSpanElement,\n  retry: document.getElementById('retry') as HTMLDivElement,\n  source: document.getElementById('source') as HTMLCanvasElement,\n  ok: document.getElementById('ok') as HTMLDivElement,\n};\nconst timestamp = { detect: 0, draw: 0 }; // holds information used to calculate performance and possible memory leaks\nlet startTime = 0;\n\nconst log = (...msg) => { // helper method to output messages\n  dom.log.innerText += msg.join(' ') + '\\n';\n  console.log(...msg); // eslint-disable-line no-console\n};\n\nasync function webCam() { // initialize webcam\n  // @ts-ignore resizeMode is not yet defined in tslib\n  const cameraOptions: MediaStreamConstraints = { audio: false, video: { facingMode: 'user', resizeMode: 'none', width: { ideal: document.body.clientWidth } } };\n  const stream: MediaStream = await navigator.mediaDevices.getUserMedia(cameraOptions);\n  const ready = new Promise((resolve) => { dom.video.onloadeddata = () => resolve(true); });\n  dom.video.srcObject = stream;\n  void dom.video.play();\n  await ready;\n  dom.canvas.width = dom.video.videoWidth;\n  dom.canvas.height = dom.video.videoHeight;\n  dom.canvas.style.width = '50%';\n  dom.canvas.style.height = '50%';\n  if (human.env.initial) log('video:', dom.video.videoWidth, dom.video.videoHeight, '|', stream.getVideoTracks()[0].label);\n  dom.canvas.onclick = () => { // pause when clicked on screen and resume on next click\n    if (dom.video.paused) void dom.video.play();\n    else dom.video.pause();\n  };\n}\n\nasync function detectionLoop() { // main detection loop\n  if (!dom.video.paused) {\n    if (current.face?.tensor) human.tf.dispose(current.face.tensor); // dispose previous tensor\n    await human.detect(dom.video); // actual detection; were not capturing output in a local variable as it can also be reached via human.result\n    const now = human.now();\n    ok.detectFPS.val = Math.round(10000 / (now - timestamp.detect)) / 10;\n    timestamp.detect = now;\n    requestAnimationFrame(detectionLoop); // start new frame immediately\n  }\n}\n\nfunction drawValidationTests() {\n  let y = 32;\n  for (const [key, val] of Object.entries(ok)) {\n    let el = document.getElementById(`ok-${key}`);\n    if (!el) {\n      el = document.createElement('div');\n      el.id = `ok-${key}`;\n      el.innerText = key;\n      el.className = 'ok';\n      el.style.top = `${y}px`;\n      dom.ok.appendChild(el);\n    }\n    if (typeof val.status === 'boolean') el.style.backgroundColor = val.status ? 'lightgreen' : 'lightcoral';\n    const status = val.status ? 'ok' : 'fail';\n    el.innerText = `${key}: ${val.val === 0 ? status : val.val}`;\n    y += 28;\n  }\n}\n\nasync function validationLoop(): Promise<H.FaceResult> { // main screen refresh loop\n  const interpolated = human.next(human.result); // smoothen result using last-known results\n  human.draw.canvas(dom.video, dom.canvas); // draw canvas to screen\n  await human.draw.all(dom.canvas, interpolated); // draw labels, boxes, lines, etc.\n  const now = human.now();\n  ok.drawFPS.val = Math.round(10000 / (now - timestamp.draw)) / 10;\n  timestamp.draw = now;\n  ok.faceCount.val = human.result.face.length;\n  ok.faceCount.status = ok.faceCount.val === 1; // must be exactly detected face\n  if (ok.faceCount.status) { // skip the rest if no face\n    const gestures: string[] = Object.values(human.result.gesture).map((gesture: H.GestureResult) => gesture.gesture); // flatten all gestures\n    if (gestures.includes('blink left eye') || gestures.includes('blink right eye')) blink.start = human.now(); // blink starts when eyes get closed\n    if (blink.start > 0 && !gestures.includes('blink left eye') && !gestures.includes('blink right eye')) blink.end = human.now(); // if blink started how long until eyes are back open\n    ok.blinkDetected.status = ok.blinkDetected.status || (Math.abs(blink.end - blink.start) > options.blinkMin && Math.abs(blink.end - blink.start) < options.blinkMax);\n    if (ok.blinkDetected.status && blink.time === 0) blink.time = Math.trunc(blink.end - blink.start);\n    ok.facingCenter.status = gestures.includes('facing center');\n    ok.lookingCenter.status = gestures.includes('looking center'); // must face camera and look at camera\n    ok.faceConfidence.val = human.result.face[0].faceScore || human.result.face[0].boxScore || 0;\n    ok.faceConfidence.status = ok.faceConfidence.val >= options.minConfidence;\n    ok.antispoofCheck.val = human.result.face[0].real || 0;\n    ok.antispoofCheck.status = ok.antispoofCheck.val >= options.minConfidence;\n    ok.livenessCheck.val = human.result.face[0].live || 0;\n    ok.livenessCheck.status = ok.livenessCheck.val >= options.minConfidence;\n    ok.faceSize.val = Math.min(human.result.face[0].box[2], human.result.face[0].box[3]);\n    ok.faceSize.status = ok.faceSize.val >= options.minSize;\n    ok.descriptor.val = human.result.face[0].embedding?.length || 0;\n    ok.descriptor.status = ok.descriptor.val > 0;\n    ok.age.val = human.result.face[0].age || 0;\n    ok.age.status = ok.age.val > 0;\n    ok.gender.val = human.result.face[0].genderScore || 0;\n    ok.gender.status = ok.gender.val >= options.minConfidence;\n  }\n  // run again\n  ok.timeout.status = ok.elapsedMs.val <= options.maxTime;\n  drawValidationTests();\n  if (allOk() || !ok.timeout.status) { // all criteria met\n    dom.video.pause();\n    return human.result.face[0];\n  }\n  ok.elapsedMs.val = Math.trunc(human.now() - startTime);\n  return new Promise((resolve) => {\n    setTimeout(async () => {\n      await validationLoop(); // run validation loop until conditions are met\n      resolve(human.result.face[0]); // recursive promise resolve\n    }, 30); // use to slow down refresh from max refresh rate to target of 30 fps\n  });\n}\n\nasync function saveRecords() {\n  if (dom.name.value.length > 0) {\n    const image = dom.canvas.getContext('2d')?.getImageData(0, 0, dom.canvas.width, dom.canvas.height) as ImageData;\n    const rec = { id: 0, name: dom.name.value, descriptor: current.face?.embedding as number[], image };\n    await indexDb.save(rec);\n    log('saved face record:', rec.name, 'descriptor length:', current.face?.embedding?.length);\n    log('known face records:', await indexDb.count());\n  } else {\n    log('invalid name');\n  }\n}\n\nasync function deleteRecord() {\n  if (current.record && current.record.id > 0) {\n    await indexDb.remove(current.record);\n  }\n}\n\nasync function detectFace() {\n  dom.canvas.style.height = '';\n  dom.canvas.getContext('2d')?.clearRect(0, 0, options.minSize, options.minSize);\n  if (!current?.face?.tensor || !current?.face?.embedding) return false;\n  console.log('face record:', current.face); // eslint-disable-line no-console\n  log(`detected face: ${current.face.gender} ${current.face.age || 0}y distance ${current.face.iris || 0}cm/${Math.round(100 * (current.face.iris || 0) / 2.54) / 100}in`);\n  human.tf.browser.toPixels(current.face.tensor as unknown as H.TensorLike, dom.canvas);\n  if (await indexDb.count() === 0) {\n    log('face database is empty: nothing to compare face with');\n    document.body.style.background = 'black';\n    dom.delete.style.display = 'none';\n    return false;\n  }\n  const db = await indexDb.load();\n  const descriptors = db.map((rec) => rec.descriptor).filter((desc) => desc.length > 0);\n  const res = human.match(current.face.embedding, descriptors, matchOptions);\n  current.record = db[res.index] || null;\n  if (current.record) {\n    log(`best match: ${current.record.name} | id: ${current.record.id} | similarity: ${Math.round(1000 * res.similarity) / 10}%`);\n    dom.name.value = current.record.name;\n    dom.source.style.display = '';\n    dom.source.getContext('2d')?.putImageData(current.record.image, 0, 0);\n  }\n  document.body.style.background = res.similarity > options.threshold ? 'darkgreen' : 'maroon';\n  return res.similarity > options.threshold;\n}\n\nasync function main() { // main entry point\n  ok.faceCount.status = false;\n  ok.faceConfidence.status = false;\n  ok.facingCenter.status = false;\n  ok.blinkDetected.status = false;\n  ok.faceSize.status = false;\n  ok.antispoofCheck.status = false;\n  ok.livenessCheck.status = false;\n  ok.age.status = false;\n  ok.gender.status = false;\n  ok.elapsedMs.val = 0;\n  dom.match.style.display = 'none';\n  dom.retry.style.display = 'none';\n  dom.source.style.display = 'none';\n  dom.canvas.style.height = '50%';\n  document.body.style.background = 'black';\n  await webCam();\n  await detectionLoop(); // start detection loop\n  startTime = human.now();\n  current.face = await validationLoop(); // start validation loop\n  dom.canvas.width = current.face.tensor?.shape[1] || options.minSize;\n  dom.canvas.height = current.face.tensor?.shape[0] || options.minSize;\n  dom.source.width = dom.canvas.width;\n  dom.source.height = dom.canvas.height;\n  dom.canvas.style.width = '';\n  dom.match.style.display = 'flex';\n  dom.save.style.display = 'flex';\n  dom.delete.style.display = 'flex';\n  dom.retry.style.display = 'block';\n  if (!allOk()) { // is all criteria met?\n    log('did not find valid face');\n    return false;\n  }\n  return detectFace();\n}\n\nasync function init() {\n  log('human version:', human.version, '| tfjs version:', human.tf.version['tfjs-core']);\n  log('options:', JSON.stringify(options).replace(/{|}|\"|\\[|\\]/g, '').replace(/,/g, ' '));\n  log('initializing webcam...');\n  await webCam(); // start webcam\n  log('loading human models...');\n  await human.load(); // preload all models\n  log('initializing human...');\n  log('face embedding model:', humanConfig.face.description.enabled ? 'faceres' : '', humanConfig.face['mobilefacenet']?.enabled ? 'mobilefacenet' : '', humanConfig.face['insightface']?.enabled ? 'insightface' : '');\n  log('loading face database...');\n  log('known face records:', await indexDb.count());\n  dom.retry.addEventListener('click', main);\n  dom.save.addEventListener('click', saveRecords);\n  dom.delete.addEventListener('click', deleteRecord);\n  await human.warmup(); // warmup function to initialize backend for future faster detection\n  await main();\n}\n\nwindow.onload = init;\n", "let db: IDBDatabase; // instance of indexdb\n\nconst database = 'human';\nconst table = 'person';\n\nexport interface FaceRecord { id: number, name: string, descriptor: number[], image: ImageData }\n\nconst log = (...msg) => console.log('indexdb', ...msg); // eslint-disable-line no-console\n\nexport async function open() {\n  if (db) return true;\n  return new Promise((resolve) => {\n    const request: IDBOpenDBRequest = indexedDB.open(database, 1);\n    request.onerror = (evt) => log('error:', evt);\n    request.onupgradeneeded = (evt: IDBVersionChangeEvent) => { // create if doesnt exist\n      log('create:', evt.target);\n      db = (evt.target as IDBOpenDBRequest).result;\n      db.createObjectStore(table, { keyPath: 'id', autoIncrement: true });\n    };\n    request.onsuccess = (evt) => { // open\n      db = (evt.target as IDBOpenDBRequest).result;\n      log('open:', db);\n      resolve(true);\n    };\n  });\n}\n\nexport async function load(): Promise<FaceRecord[]> {\n  const faceDB: FaceRecord[] = [];\n  if (!db) await open(); // open or create if not already done\n  return new Promise((resolve) => {\n    const cursor: IDBRequest = db.transaction([table], 'readwrite').objectStore(table).openCursor(null, 'next');\n    cursor.onerror = (evt) => log('load error:', evt);\n    cursor.onsuccess = (evt) => {\n      if ((evt.target as IDBRequest).result) {\n        faceDB.push((evt.target as IDBRequest).result.value);\n        (evt.target as IDBRequest).result.continue();\n      } else {\n        resolve(faceDB);\n      }\n    };\n  });\n}\n\nexport async function count(): Promise<number> {\n  if (!db) await open(); // open or create if not already done\n  return new Promise((resolve) => {\n    const store: IDBRequest = db.transaction([table], 'readwrite').objectStore(table).count();\n    store.onerror = (evt) => log('count error:', evt);\n    store.onsuccess = () => resolve(store.result);\n  });\n}\n\nexport async function save(faceRecord: FaceRecord) {\n  if (!db) await open(); // open or create if not already done\n  const newRecord = { name: faceRecord.name, descriptor: faceRecord.descriptor, image: faceRecord.image }; // omit id as its autoincrement\n  db.transaction([table], 'readwrite').objectStore(table).put(newRecord);\n  log('save:', newRecord);\n}\n\nexport async function remove(faceRecord: FaceRecord) {\n  if (!db) await open(); // open or create if not already done\n  db.transaction([table], 'readwrite').objectStore(table).delete(faceRecord.id); // delete based on id\n  log('delete:', faceRecord);\n}\n"],
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+  "sourcesContent": ["/**\n * Human demo for browsers\n * @default Human Library\n * @summary <https://github.com/vladmandic/human>\n * @author <https://github.com/vladmandic>\n * @copyright <https://github.com/vladmandic>\n * @license MIT\n */\n\nimport * as H from '../../dist/human.esm.js'; // equivalent of @vladmandic/Human\nimport * as indexDb from './indexdb'; // methods to deal with indexdb\n\nconst humanConfig = { // user configuration for human, used to fine-tune behavior\n  cacheSensitivity: 0,\n  modelBasePath: '../../models',\n  filter: { equalization: true }, // lets run with histogram equilizer\n  face: {\n    enabled: true,\n    detector: { rotation: true, return: true, cropFactor: 1.6, mask: false }, // return tensor is used to get detected face image\n    description: { enabled: true }, // default model for face descriptor extraction is faceres\n    // mobilefacenet: { enabled: true, modelPath: 'https://vladmandic.github.io/human-models/models/mobilefacenet.json' }, // alternative model\n    // insightface: { enabled: true, modelPath: 'https://vladmandic.github.io/insightface/models/insightface-mobilenet-swish.json' }, // alternative model\n    iris: { enabled: true }, // needed to determine gaze direction\n    emotion: { enabled: false }, // not needed\n    antispoof: { enabled: true }, // enable optional antispoof module\n    liveness: { enabled: true }, // enable optional liveness module\n  },\n  body: { enabled: false },\n  hand: { enabled: false },\n  object: { enabled: false },\n  gesture: { enabled: true }, // parses face and iris gestures\n};\n\n// const matchOptions = { order: 2, multiplier: 1000, min: 0.0, max: 1.0 }; // for embedding model\nconst matchOptions = { order: 2, multiplier: 25, min: 0.2, max: 0.8 }; // for faceres model\n\nconst options = {\n  minConfidence: 0.6, // overal face confidence for box, face, gender, real, live\n  minSize: 224, // min input to face descriptor model before degradation\n  maxTime: 30000, // max time before giving up\n  blinkMin: 10, // minimum duration of a valid blink\n  blinkMax: 800, // maximum duration of a valid blink\n  threshold: 0.5, // minimum similarity\n  mask: humanConfig.face.detector.mask,\n  rotation: humanConfig.face.detector.rotation,\n  cropFactor: humanConfig.face.detector.cropFactor,\n  ...matchOptions,\n};\n\nconst ok: Record<string, { status: boolean | undefined, val: number }> = { // must meet all rules\n  faceCount: { status: false, val: 0 },\n  faceConfidence: { status: false, val: 0 },\n  facingCenter: { status: false, val: 0 },\n  lookingCenter: { status: false, val: 0 },\n  blinkDetected: { status: false, val: 0 },\n  faceSize: { status: false, val: 0 },\n  antispoofCheck: { status: false, val: 0 },\n  livenessCheck: { status: false, val: 0 },\n  age: { status: false, val: 0 },\n  gender: { status: false, val: 0 },\n  timeout: { status: true, val: 0 },\n  descriptor: { status: false, val: 0 },\n  elapsedMs: { status: undefined, val: 0 }, // total time while waiting for valid face\n  detectFPS: { status: undefined, val: 0 }, // mark detection fps performance\n  drawFPS: { status: undefined, val: 0 }, // mark redraw fps performance\n};\n\nconst allOk = () => ok.faceCount.status\n  && ok.faceSize.status\n  && ok.blinkDetected.status\n  && ok.facingCenter.status\n  && ok.lookingCenter.status\n  && ok.faceConfidence.status\n  && ok.antispoofCheck.status\n  && ok.livenessCheck.status\n  && ok.descriptor.status\n  && ok.age.status\n  && ok.gender.status;\n\nconst current: { face: H.FaceResult | null, record: indexDb.FaceRecord | null } = { face: null, record: null }; // current face record and matched database record\n\nconst blink = { // internal timers for blink start/end/duration\n  start: 0,\n  end: 0,\n  time: 0,\n};\n\n// let db: Array<{ name: string, source: string, embedding: number[] }> = []; // holds loaded face descriptor database\nconst human = new H.Human(humanConfig); // create instance of human with overrides from user configuration\n\nhuman.env.perfadd = false; // is performance data showing instant or total values\nhuman.draw.options.font = 'small-caps 18px \"Lato\"'; // set font used to draw labels when using draw methods\nhuman.draw.options.lineHeight = 20;\n\nconst dom = { // grab instances of dom objects so we dont have to look them up later\n  video: document.getElementById('video') as HTMLVideoElement,\n  canvas: document.getElementById('canvas') as HTMLCanvasElement,\n  log: document.getElementById('log') as HTMLPreElement,\n  fps: document.getElementById('fps') as HTMLPreElement,\n  match: document.getElementById('match') as HTMLDivElement,\n  name: document.getElementById('name') as HTMLInputElement,\n  save: document.getElementById('save') as HTMLSpanElement,\n  delete: document.getElementById('delete') as HTMLSpanElement,\n  retry: document.getElementById('retry') as HTMLDivElement,\n  source: document.getElementById('source') as HTMLCanvasElement,\n  ok: document.getElementById('ok') as HTMLDivElement,\n};\nconst timestamp = { detect: 0, draw: 0 }; // holds information used to calculate performance and possible memory leaks\nlet startTime = 0;\n\nconst log = (...msg) => { // helper method to output messages\n  dom.log.innerText += msg.join(' ') + '\\n';\n  console.log(...msg); // eslint-disable-line no-console\n};\n\nasync function webCam() { // initialize webcam\n  // @ts-ignore resizeMode is not yet defined in tslib\n  const cameraOptions: MediaStreamConstraints = { audio: false, video: { facingMode: 'user', resizeMode: 'none', width: { ideal: document.body.clientWidth } } };\n  const stream: MediaStream = await navigator.mediaDevices.getUserMedia(cameraOptions);\n  const ready = new Promise((resolve) => { dom.video.onloadeddata = () => resolve(true); });\n  dom.video.srcObject = stream;\n  void dom.video.play();\n  await ready;\n  dom.canvas.width = dom.video.videoWidth;\n  dom.canvas.height = dom.video.videoHeight;\n  dom.canvas.style.width = '50%';\n  dom.canvas.style.height = '50%';\n  if (human.env.initial) log('video:', dom.video.videoWidth, dom.video.videoHeight, '|', stream.getVideoTracks()[0].label);\n  dom.canvas.onclick = () => { // pause when clicked on screen and resume on next click\n    if (dom.video.paused) void dom.video.play();\n    else dom.video.pause();\n  };\n}\n\nasync function detectionLoop() { // main detection loop\n  if (!dom.video.paused) {\n    if (current.face?.tensor) human.tf.dispose(current.face.tensor); // dispose previous tensor\n    await human.detect(dom.video); // actual detection; were not capturing output in a local variable as it can also be reached via human.result\n    const now = human.now();\n    ok.detectFPS.val = Math.round(10000 / (now - timestamp.detect)) / 10;\n    timestamp.detect = now;\n    requestAnimationFrame(detectionLoop); // start new frame immediately\n  }\n}\n\nfunction drawValidationTests() {\n  let y = 32;\n  for (const [key, val] of Object.entries(ok)) {\n    let el = document.getElementById(`ok-${key}`);\n    if (!el) {\n      el = document.createElement('div');\n      el.id = `ok-${key}`;\n      el.innerText = key;\n      el.className = 'ok';\n      el.style.top = `${y}px`;\n      dom.ok.appendChild(el);\n    }\n    if (typeof val.status === 'boolean') el.style.backgroundColor = val.status ? 'lightgreen' : 'lightcoral';\n    const status = val.status ? 'ok' : 'fail';\n    el.innerText = `${key}: ${val.val === 0 ? status : val.val}`;\n    y += 28;\n  }\n}\n\nasync function validationLoop(): Promise<H.FaceResult> { // main screen refresh loop\n  const interpolated = human.next(human.result); // smoothen result using last-known results\n  human.draw.canvas(dom.video, dom.canvas); // draw canvas to screen\n  await human.draw.all(dom.canvas, interpolated); // draw labels, boxes, lines, etc.\n  const now = human.now();\n  ok.drawFPS.val = Math.round(10000 / (now - timestamp.draw)) / 10;\n  timestamp.draw = now;\n  ok.faceCount.val = human.result.face.length;\n  ok.faceCount.status = ok.faceCount.val === 1; // must be exactly detected face\n  if (ok.faceCount.status) { // skip the rest if no face\n    const gestures: string[] = Object.values(human.result.gesture).map((gesture: H.GestureResult) => gesture.gesture); // flatten all gestures\n    if (gestures.includes('blink left eye') || gestures.includes('blink right eye')) blink.start = human.now(); // blink starts when eyes get closed\n    if (blink.start > 0 && !gestures.includes('blink left eye') && !gestures.includes('blink right eye')) blink.end = human.now(); // if blink started how long until eyes are back open\n    ok.blinkDetected.status = ok.blinkDetected.status || (Math.abs(blink.end - blink.start) > options.blinkMin && Math.abs(blink.end - blink.start) < options.blinkMax);\n    if (ok.blinkDetected.status && blink.time === 0) blink.time = Math.trunc(blink.end - blink.start);\n    ok.facingCenter.status = gestures.includes('facing center');\n    ok.lookingCenter.status = gestures.includes('looking center'); // must face camera and look at camera\n    ok.faceConfidence.val = human.result.face[0].faceScore || human.result.face[0].boxScore || 0;\n    ok.faceConfidence.status = ok.faceConfidence.val >= options.minConfidence;\n    ok.antispoofCheck.val = human.result.face[0].real || 0;\n    ok.antispoofCheck.status = ok.antispoofCheck.val >= options.minConfidence;\n    ok.livenessCheck.val = human.result.face[0].live || 0;\n    ok.livenessCheck.status = ok.livenessCheck.val >= options.minConfidence;\n    ok.faceSize.val = Math.min(human.result.face[0].box[2], human.result.face[0].box[3]);\n    ok.faceSize.status = ok.faceSize.val >= options.minSize;\n    ok.descriptor.val = human.result.face[0].embedding?.length || 0;\n    ok.descriptor.status = ok.descriptor.val > 0;\n    ok.age.val = human.result.face[0].age || 0;\n    ok.age.status = ok.age.val > 0;\n    ok.gender.val = human.result.face[0].genderScore || 0;\n    ok.gender.status = ok.gender.val >= options.minConfidence;\n  }\n  // run again\n  ok.timeout.status = ok.elapsedMs.val <= options.maxTime;\n  drawValidationTests();\n  if (allOk() || !ok.timeout.status) { // all criteria met\n    dom.video.pause();\n    return human.result.face[0];\n  }\n  ok.elapsedMs.val = Math.trunc(human.now() - startTime);\n  return new Promise((resolve) => {\n    setTimeout(async () => {\n      await validationLoop(); // run validation loop until conditions are met\n      resolve(human.result.face[0]); // recursive promise resolve\n    }, 30); // use to slow down refresh from max refresh rate to target of 30 fps\n  });\n}\n\nasync function saveRecords() {\n  if (dom.name.value.length > 0) {\n    const image = dom.canvas.getContext('2d')?.getImageData(0, 0, dom.canvas.width, dom.canvas.height) as ImageData;\n    const rec = { id: 0, name: dom.name.value, descriptor: current.face?.embedding as number[], image };\n    await indexDb.save(rec);\n    log('saved face record:', rec.name, 'descriptor length:', current.face?.embedding?.length);\n    log('known face records:', await indexDb.count());\n  } else {\n    log('invalid name');\n  }\n}\n\nasync function deleteRecord() {\n  if (current.record && current.record.id > 0) {\n    await indexDb.remove(current.record);\n  }\n}\n\nasync function detectFace() {\n  dom.canvas.style.height = '';\n  dom.canvas.getContext('2d')?.clearRect(0, 0, options.minSize, options.minSize);\n  if (!current?.face?.tensor || !current?.face?.embedding) return false;\n  console.log('face record:', current.face); // eslint-disable-line no-console\n  log(`detected face: ${current.face.gender} ${current.face.age || 0}y distance ${current.face.iris || 0}cm/${Math.round(100 * (current.face.iris || 0) / 2.54) / 100}in`);\n  await human.tf.browser.toPixels(current.face.tensor, dom.canvas);\n  if (await indexDb.count() === 0) {\n    log('face database is empty: nothing to compare face with');\n    document.body.style.background = 'black';\n    dom.delete.style.display = 'none';\n    return false;\n  }\n  const db = await indexDb.load();\n  const descriptors = db.map((rec) => rec.descriptor).filter((desc) => desc.length > 0);\n  const res = human.match(current.face.embedding, descriptors, matchOptions);\n  current.record = db[res.index] || null;\n  if (current.record) {\n    log(`best match: ${current.record.name} | id: ${current.record.id} | similarity: ${Math.round(1000 * res.similarity) / 10}%`);\n    dom.name.value = current.record.name;\n    dom.source.style.display = '';\n    dom.source.getContext('2d')?.putImageData(current.record.image, 0, 0);\n  }\n  document.body.style.background = res.similarity > options.threshold ? 'darkgreen' : 'maroon';\n  return res.similarity > options.threshold;\n}\n\nasync function main() { // main entry point\n  ok.faceCount.status = false;\n  ok.faceConfidence.status = false;\n  ok.facingCenter.status = false;\n  ok.blinkDetected.status = false;\n  ok.faceSize.status = false;\n  ok.antispoofCheck.status = false;\n  ok.livenessCheck.status = false;\n  ok.age.status = false;\n  ok.gender.status = false;\n  ok.elapsedMs.val = 0;\n  dom.match.style.display = 'none';\n  dom.retry.style.display = 'none';\n  dom.source.style.display = 'none';\n  dom.canvas.style.height = '50%';\n  document.body.style.background = 'black';\n  await webCam();\n  await detectionLoop(); // start detection loop\n  startTime = human.now();\n  current.face = await validationLoop(); // start validation loop\n  dom.canvas.width = current.face.tensor?.shape[1] || options.minSize;\n  dom.canvas.height = current.face.tensor?.shape[0] || options.minSize;\n  dom.source.width = dom.canvas.width;\n  dom.source.height = dom.canvas.height;\n  dom.canvas.style.width = '';\n  dom.match.style.display = 'flex';\n  dom.save.style.display = 'flex';\n  dom.delete.style.display = 'flex';\n  dom.retry.style.display = 'block';\n  if (!allOk()) { // is all criteria met?\n    log('did not find valid face');\n    return false;\n  }\n  return detectFace();\n}\n\nasync function init() {\n  log('human version:', human.version, '| tfjs version:', human.tf.version['tfjs-core']);\n  log('options:', JSON.stringify(options).replace(/{|}|\"|\\[|\\]/g, '').replace(/,/g, ' '));\n  log('initializing webcam...');\n  await webCam(); // start webcam\n  log('loading human models...');\n  await human.load(); // preload all models\n  log('initializing human...');\n  log('face embedding model:', humanConfig.face.description.enabled ? 'faceres' : '', humanConfig.face['mobilefacenet']?.enabled ? 'mobilefacenet' : '', humanConfig.face['insightface']?.enabled ? 'insightface' : '');\n  log('loading face database...');\n  log('known face records:', await indexDb.count());\n  dom.retry.addEventListener('click', main);\n  dom.save.addEventListener('click', saveRecords);\n  dom.delete.addEventListener('click', deleteRecord);\n  await human.warmup(); // warmup function to initialize backend for future faster detection\n  await main();\n}\n\nwindow.onload = init;\n", "let db: IDBDatabase; // instance of indexdb\n\nconst database = 'human';\nconst table = 'person';\n\nexport interface FaceRecord { id: number, name: string, descriptor: number[], image: ImageData }\n\nconst log = (...msg) => console.log('indexdb', ...msg); // eslint-disable-line no-console\n\nexport async function open() {\n  if (db) return true;\n  return new Promise((resolve) => {\n    const request: IDBOpenDBRequest = indexedDB.open(database, 1);\n    request.onerror = (evt) => log('error:', evt);\n    request.onupgradeneeded = (evt: IDBVersionChangeEvent) => { // create if doesnt exist\n      log('create:', evt.target);\n      db = (evt.target as IDBOpenDBRequest).result;\n      db.createObjectStore(table, { keyPath: 'id', autoIncrement: true });\n    };\n    request.onsuccess = (evt) => { // open\n      db = (evt.target as IDBOpenDBRequest).result;\n      log('open:', db);\n      resolve(true);\n    };\n  });\n}\n\nexport async function load(): Promise<FaceRecord[]> {\n  const faceDB: FaceRecord[] = [];\n  if (!db) await open(); // open or create if not already done\n  return new Promise((resolve) => {\n    const cursor: IDBRequest = db.transaction([table], 'readwrite').objectStore(table).openCursor(null, 'next');\n    cursor.onerror = (evt) => log('load error:', evt);\n    cursor.onsuccess = (evt) => {\n      if ((evt.target as IDBRequest).result) {\n        faceDB.push((evt.target as IDBRequest).result.value);\n        (evt.target as IDBRequest).result.continue();\n      } else {\n        resolve(faceDB);\n      }\n    };\n  });\n}\n\nexport async function count(): Promise<number> {\n  if (!db) await open(); // open or create if not already done\n  return new Promise((resolve) => {\n    const store: IDBRequest = db.transaction([table], 'readwrite').objectStore(table).count();\n    store.onerror = (evt) => log('count error:', evt);\n    store.onsuccess = () => resolve(store.result);\n  });\n}\n\nexport async function save(faceRecord: FaceRecord) {\n  if (!db) await open(); // open or create if not already done\n  const newRecord = { name: faceRecord.name, descriptor: faceRecord.descriptor, image: faceRecord.image }; // omit id as its autoincrement\n  db.transaction([table], 'readwrite').objectStore(table).put(newRecord);\n  log('save:', newRecord);\n}\n\nexport async function remove(faceRecord: FaceRecord) {\n  if (!db) await open(); // open or create if not already done\n  db.transaction([table], 'readwrite').objectStore(table).delete(faceRecord.id); // delete based on id\n  log('delete:', faceRecord);\n}\n"],
+  "mappings": 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,EAAK,CACb,CAEA,OAAO,OAASC",
   "names": ["H", "db", "database", "table", "log", "msg", "open", "resolve", "request", "evt", "load", "faceDB", "cursor", "count", "store", "save", "faceRecord", "newRecord", "remove", "humanConfig", "matchOptions", "options", "ok", "allOk", "current", "blink", "human", "dom", "timestamp", "startTime", "log", "msg", "webCam", "cameraOptions", "stream", "ready", "resolve", "detectionLoop", "_a", "now", "drawValidationTests", "y", "key", "val", "el", "status", "validationLoop", "interpolated", "gestures", "gesture", "saveRecords", "_b", "_c", "_d", "image", "rec", "save", "count", "deleteRecord", "remove", "detectFace", "db", "load", "descriptors", "desc", "res", "main", "init"]
 }
diff --git a/demo/faceid/index.ts b/demo/faceid/index.ts
index b7507a23..7dd81425 100644
--- a/demo/faceid/index.ts
+++ b/demo/faceid/index.ts
@@ -234,7 +234,7 @@ async function detectFace() {
   if (!current?.face?.tensor || !current?.face?.embedding) return false;
   console.log('face record:', current.face); // eslint-disable-line no-console
   log(`detected face: ${current.face.gender} ${current.face.age || 0}y distance ${current.face.iris || 0}cm/${Math.round(100 * (current.face.iris || 0) / 2.54) / 100}in`);
-  human.tf.browser.toPixels(current.face.tensor as unknown as H.TensorLike, dom.canvas);
+  await human.tf.browser.toPixels(current.face.tensor, dom.canvas);
   if (await indexDb.count() === 0) {
     log('face database is empty: nothing to compare face with');
     document.body.style.background = 'black';
diff --git a/demo/typescript/index.js.map b/demo/typescript/index.js.map
index 2d6d226c..2c1e2c88 100644
--- a/demo/typescript/index.js.map
+++ b/demo/typescript/index.js.map
@@ -1,7 +1,7 @@
 {
   "version": 3,
   "sources": ["index.ts"],
-  "sourcesContent": ["/**\n * Human demo for browsers\n * @default Human Library\n * @summary <https://github.com/vladmandic/human>\n * @author <https://github.com/vladmandic>\n * @copyright <https://github.com/vladmandic>\n * @license MIT\n */\n\nimport * as H from '../../dist/human.esm.js'; // equivalent of @vladmandic/Human\n\nconst humanConfig: Partial<H.Config> = { // user configuration for human, used to fine-tune behavior\n  modelBasePath: '../../models',\n  filter: { enabled: true, equalization: false, flip: false },\n  face: { enabled: true, detector: { rotation: false }, mesh: { enabled: true }, attention: { enabled: false }, iris: { enabled: true }, description: { enabled: true }, emotion: { enabled: true } },\n  body: { enabled: true },\n  hand: { enabled: true },\n  object: { enabled: false },\n  segmentation: { enabled: false },\n  gesture: { enabled: true },\n};\n\nconst human = new H.Human(humanConfig); // create instance of human with overrides from user configuration\n\nhuman.env.perfadd = false; // is performance data showing instant or total values\nhuman.draw.options.font = 'small-caps 18px \"Lato\"'; // set font used to draw labels when using draw methods\nhuman.draw.options.lineHeight = 20;\n// human.draw.options.fillPolygons = true;\n\nconst dom = { // grab instances of dom objects so we dont have to look them up later\n  video: document.getElementById('video') as HTMLVideoElement,\n  canvas: document.getElementById('canvas') as HTMLCanvasElement,\n  log: document.getElementById('log') as HTMLPreElement,\n  fps: document.getElementById('status') as HTMLPreElement,\n  perf: document.getElementById('performance') as HTMLDivElement,\n};\nconst timestamp = { detect: 0, draw: 0, tensors: 0, start: 0 }; // holds information used to calculate performance and possible memory leaks\nconst fps = { detectFPS: 0, drawFPS: 0, frames: 0, averageMs: 0 }; // holds calculated fps information for both detect and screen refresh\n\nconst log = (...msg) => { // helper method to output messages\n  dom.log.innerText += msg.join(' ') + '\\n';\n  console.log(...msg); // eslint-disable-line no-console\n};\nconst status = (msg) => dom.fps.innerText = msg; // print status element\nconst perf = (msg) => dom.perf.innerText = 'tensors:' + (human.tf.memory().numTensors as number).toString() + ' | performance: ' + JSON.stringify(msg).replace(/\"|{|}/g, '').replace(/,/g, ' | '); // print performance element\n\nasync function detectionLoop() { // main detection loop\n  if (!dom.video.paused) {\n    if (timestamp.start === 0) timestamp.start = human.now();\n    // log('profiling data:', await human.profile(dom.video));\n    await human.detect(dom.video); // actual detection; were not capturing output in a local variable as it can also be reached via human.result\n    const tensors = human.tf.memory().numTensors; // check current tensor usage for memory leaks\n    if (tensors - timestamp.tensors !== 0) log('allocated tensors:', tensors - timestamp.tensors); // printed on start and each time there is a tensor leak\n    timestamp.tensors = tensors;\n    fps.detectFPS = Math.round(1000 * 1000 / (human.now() - timestamp.detect)) / 1000;\n    fps.frames++;\n    fps.averageMs = Math.round(1000 * (human.now() - timestamp.start) / fps.frames) / 1000;\n    if (fps.frames % 100 === 0 && !dom.video.paused) log('performance', { ...fps, tensors: timestamp.tensors });\n  }\n  timestamp.detect = human.now();\n  requestAnimationFrame(detectionLoop); // start new frame immediately\n}\n\nasync function drawLoop() { // main screen refresh loop\n  if (!dom.video.paused) {\n    const interpolated = human.next(human.result); // smoothen result using last-known results\n    if (human.config.filter.flip) human.draw.canvas(interpolated.canvas as HTMLCanvasElement, dom.canvas); // draw processed image to screen canvas\n    else human.draw.canvas(dom.video, dom.canvas); // draw original video to screen canvas // better than using procesed image as this loop happens faster than processing loop\n    await human.draw.all(dom.canvas, interpolated); // draw labels, boxes, lines, etc.\n    perf(interpolated.performance); // write performance data\n  }\n  const now = human.now();\n  fps.drawFPS = Math.round(1000 * 1000 / (now - timestamp.draw)) / 1000;\n  timestamp.draw = now;\n  status(dom.video.paused ? 'paused' : `fps: ${fps.detectFPS.toFixed(1).padStart(5, ' ')} detect | ${fps.drawFPS.toFixed(1).padStart(5, ' ')} draw`); // write status\n  setTimeout(drawLoop, 30); // use to slow down refresh from max refresh rate to target of 30 fps\n}\n\nasync function webCam() {\n  await human.webcam.start({ element: dom.video, crop: true }); // use human webcam helper methods and associate webcam stream with a dom element\n  dom.canvas.width = human.webcam.width;\n  dom.canvas.height = human.webcam.height;\n  dom.canvas.onclick = async () => { // pause when clicked on screen and resume on next click\n    if (human.webcam.paused) await human.webcam.play();\n    else human.webcam.pause();\n  };\n}\n\nasync function main() { // main entry point\n  log('human version:', human.version, '| tfjs version:', human.tf.version['tfjs-core']);\n  log('platform:', human.env.platform, '| agent:', human.env.agent);\n  status('loading...');\n  await human.load(); // preload all models\n  log('backend:', human.tf.getBackend(), '| available:', human.env.backends);\n  log('models stats:', human.getModelStats());\n  log('models loaded:', Object.values(human.models).filter((model) => model !== null).length);\n  status('initializing...');\n  await human.warmup(); // warmup function to initialize backend for future faster detection\n  await webCam(); // start webcam\n  await detectionLoop(); // start detection loop\n  await drawLoop(); // start draw loop\n}\n\nwindow.onload = main;\n"],
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+  "sourcesContent": ["/**\n * Human demo for browsers\n * @default Human Library\n * @summary <https://github.com/vladmandic/human>\n * @author <https://github.com/vladmandic>\n * @copyright <https://github.com/vladmandic>\n * @license MIT\n */\n\nimport * as H from '../../dist/human.esm.js'; // equivalent of @vladmandic/Human\n\nconst humanConfig: Partial<H.Config> = { // user configuration for human, used to fine-tune behavior\n  modelBasePath: '../../models',\n  filter: { enabled: true, equalization: false, flip: false },\n  face: { enabled: true, detector: { rotation: false }, mesh: { enabled: true }, attention: { enabled: false }, iris: { enabled: true }, description: { enabled: true }, emotion: { enabled: true } },\n  body: { enabled: true },\n  hand: { enabled: true },\n  object: { enabled: false },\n  segmentation: { enabled: false },\n  gesture: { enabled: true },\n};\n\nconst human = new H.Human(humanConfig); // create instance of human with overrides from user configuration\n\nhuman.env.perfadd = false; // is performance data showing instant or total values\nhuman.draw.options.font = 'small-caps 18px \"Lato\"'; // set font used to draw labels when using draw methods\nhuman.draw.options.lineHeight = 20;\n// human.draw.options.fillPolygons = true;\n\nconst dom = { // grab instances of dom objects so we dont have to look them up later\n  video: document.getElementById('video') as HTMLVideoElement,\n  canvas: document.getElementById('canvas') as HTMLCanvasElement,\n  log: document.getElementById('log') as HTMLPreElement,\n  fps: document.getElementById('status') as HTMLPreElement,\n  perf: document.getElementById('performance') as HTMLDivElement,\n};\nconst timestamp = { detect: 0, draw: 0, tensors: 0, start: 0 }; // holds information used to calculate performance and possible memory leaks\nconst fps = { detectFPS: 0, drawFPS: 0, frames: 0, averageMs: 0 }; // holds calculated fps information for both detect and screen refresh\n\nconst log = (...msg) => { // helper method to output messages\n  dom.log.innerText += msg.join(' ') + '\\n';\n  console.log(...msg); // eslint-disable-line no-console\n};\nconst status = (msg) => dom.fps.innerText = msg; // print status element\nconst perf = (msg) => dom.perf.innerText = 'tensors:' + human.tf.memory().numTensors.toString() + ' | performance: ' + JSON.stringify(msg).replace(/\"|{|}/g, '').replace(/,/g, ' | '); // print performance element\n\nasync function detectionLoop() { // main detection loop\n  if (!dom.video.paused) {\n    if (timestamp.start === 0) timestamp.start = human.now();\n    // log('profiling data:', await human.profile(dom.video));\n    await human.detect(dom.video); // actual detection; were not capturing output in a local variable as it can also be reached via human.result\n    const tensors = human.tf.memory().numTensors; // check current tensor usage for memory leaks\n    if (tensors - timestamp.tensors !== 0) log('allocated tensors:', tensors - timestamp.tensors); // printed on start and each time there is a tensor leak\n    timestamp.tensors = tensors;\n    fps.detectFPS = Math.round(1000 * 1000 / (human.now() - timestamp.detect)) / 1000;\n    fps.frames++;\n    fps.averageMs = Math.round(1000 * (human.now() - timestamp.start) / fps.frames) / 1000;\n    if (fps.frames % 100 === 0 && !dom.video.paused) log('performance', { ...fps, tensors: timestamp.tensors });\n  }\n  timestamp.detect = human.now();\n  requestAnimationFrame(detectionLoop); // start new frame immediately\n}\n\nasync function drawLoop() { // main screen refresh loop\n  if (!dom.video.paused) {\n    const interpolated = human.next(human.result); // smoothen result using last-known results\n    if (human.config.filter.flip) human.draw.canvas(interpolated.canvas as HTMLCanvasElement, dom.canvas); // draw processed image to screen canvas\n    else human.draw.canvas(dom.video, dom.canvas); // draw original video to screen canvas // better than using procesed image as this loop happens faster than processing loop\n    await human.draw.all(dom.canvas, interpolated); // draw labels, boxes, lines, etc.\n    perf(interpolated.performance); // write performance data\n  }\n  const now = human.now();\n  fps.drawFPS = Math.round(1000 * 1000 / (now - timestamp.draw)) / 1000;\n  timestamp.draw = now;\n  status(dom.video.paused ? 'paused' : `fps: ${fps.detectFPS.toFixed(1).padStart(5, ' ')} detect | ${fps.drawFPS.toFixed(1).padStart(5, ' ')} draw`); // write status\n  setTimeout(drawLoop, 30); // use to slow down refresh from max refresh rate to target of 30 fps\n}\n\nasync function webCam() {\n  await human.webcam.start({ element: dom.video, crop: true }); // use human webcam helper methods and associate webcam stream with a dom element\n  dom.canvas.width = human.webcam.width;\n  dom.canvas.height = human.webcam.height;\n  dom.canvas.onclick = async () => { // pause when clicked on screen and resume on next click\n    if (human.webcam.paused) await human.webcam.play();\n    else human.webcam.pause();\n  };\n}\n\nasync function main() { // main entry point\n  log('human version:', human.version, '| tfjs version:', human.tf.version['tfjs-core']);\n  log('platform:', human.env.platform, '| agent:', human.env.agent);\n  status('loading...');\n  await human.load(); // preload all models\n  log('backend:', human.tf.getBackend(), '| available:', human.env.backends);\n  log('models stats:', human.getModelStats());\n  log('models loaded:', Object.values(human.models).filter((model) => model !== null).length);\n  status('initializing...');\n  await human.warmup(); // warmup function to initialize backend for future faster detection\n  await webCam(); // start webcam\n  await detectionLoop(); // start detection loop\n  await drawLoop(); // start draw loop\n}\n\nwindow.onload = main;\n"],
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   "names": ["H", "humanConfig", "human", "dom", "timestamp", "fps", "log", "msg", "status", "perf", "detectionLoop", "tensors", "drawLoop", "interpolated", "now", "webCam", "main", "model"]
 }
diff --git a/demo/typescript/index.ts b/demo/typescript/index.ts
index d15bb071..922a6f5c 100644
--- a/demo/typescript/index.ts
+++ b/demo/typescript/index.ts
@@ -42,7 +42,7 @@ const log = (...msg) => { // helper method to output messages
   console.log(...msg); // eslint-disable-line no-console
 };
 const status = (msg) => dom.fps.innerText = msg; // print status element
-const perf = (msg) => dom.perf.innerText = 'tensors:' + (human.tf.memory().numTensors as number).toString() + ' | performance: ' + JSON.stringify(msg).replace(/"|{|}/g, '').replace(/,/g, ' | '); // print performance element
+const perf = (msg) => dom.perf.innerText = 'tensors:' + human.tf.memory().numTensors.toString() + ' | performance: ' + JSON.stringify(msg).replace(/"|{|}/g, '').replace(/,/g, ' | '); // print performance element
 
 async function detectionLoop() { // main detection loop
   if (!dom.video.paused) {
diff --git a/package.json b/package.json
index 6ed620a9..b65c4525 100644
--- a/package.json
+++ b/package.json
@@ -1,6 +1,6 @@
 {
   "name": "@vladmandic/human",
-  "version": "2.11.1",
+  "version": "3.0.0",
   "description": "Human: AI-powered 3D Face Detection & Rotation Tracking, Face Description & Recognition, Body Pose Tracking, 3D Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction, Gesture Recognition",
   "sideEffects": false,
   "main": "dist/human.node.js",
@@ -68,21 +68,21 @@
   "devDependencies": {
     "@html-eslint/eslint-plugin": "^0.15.0",
     "@html-eslint/parser": "^0.15.0",
-    "@microsoft/api-extractor": "^7.33.1",
-    "@tensorflow/tfjs": "^3.21.0",
-    "@tensorflow/tfjs-backend-cpu": "^3.21.0",
-    "@tensorflow/tfjs-backend-wasm": "^3.21.0",
-    "@tensorflow/tfjs-backend-webgl": "^3.21.0",
+    "@microsoft/api-extractor": "^7.33.2",
+    "@tensorflow/tfjs": "^4.0.0",
+    "@tensorflow/tfjs-backend-cpu": "^4.0.0",
+    "@tensorflow/tfjs-backend-wasm": "^4.0.0",
+    "@tensorflow/tfjs-backend-webgl": "^4.0.0",
     "@tensorflow/tfjs-backend-webgpu": "0.0.1-alpha.14",
-    "@tensorflow/tfjs-converter": "^3.21.0",
-    "@tensorflow/tfjs-core": "^3.21.0",
-    "@tensorflow/tfjs-data": "^3.21.0",
-    "@tensorflow/tfjs-layers": "^3.21.0",
-    "@tensorflow/tfjs-node": "^3.21.1",
-    "@tensorflow/tfjs-node-gpu": "^3.21.0",
+    "@tensorflow/tfjs-converter": "^4.0.0",
+    "@tensorflow/tfjs-core": "^4.0.0",
+    "@tensorflow/tfjs-data": "^4.0.0",
+    "@tensorflow/tfjs-layers": "^4.0.0",
+    "@tensorflow/tfjs-node": "^4.0.0",
+    "@tensorflow/tfjs-node-gpu": "^4.0.0",
     "@tensorflow/tfjs-tflite": "0.0.1-alpha.9",
     "@types/emscripten": "^1.39.6",
-    "@types/node": "^18.8.5",
+    "@types/node": "^18.11.0",
     "@types/offscreencanvas": "^2019.7.0",
     "@typescript-eslint/eslint-plugin": "^5.40.0",
     "@typescript-eslint/parser": "^5.40.0",
@@ -91,7 +91,7 @@
     "@vladmandic/tfjs": "github:vladmandic/tfjs",
     "@webgpu/types": "^0.1.22",
     "canvas": "^2.10.1",
-    "esbuild": "^0.15.10",
+    "esbuild": "^0.15.11",
     "eslint": "8.25.0",
     "eslint-config-airbnb-base": "^15.0.0",
     "eslint-plugin-html": "^7.1.0",
diff --git a/src/body/blazepose.ts b/src/body/blazepose.ts
index 52e9fe1e..12b2bccb 100644
--- a/src/body/blazepose.ts
+++ b/src/body/blazepose.ts
@@ -2,12 +2,12 @@
  * BlazePose model implementation
  */
 
-import * as tf from '../../dist/tfjs.esm.js';
+import * as tf from 'dist/tfjs.esm.js';
 import { loadModel } from '../tfjs/load';
 import { constants } from '../tfjs/constants';
 import { log, now } from '../util/util';
 import type { BodyKeypoint, BodyResult, BodyLandmark, Box, Point, BodyAnnotation } from '../result';
-import type { GraphModel, Tensor } from '../tfjs/types';
+import type { GraphModel, Tensor, Tensor4D } from '../tfjs/types';
 import type { Config } from '../config';
 import * as coords from './blazeposecoords';
 import * as detect from './blazeposedetector';
@@ -59,7 +59,7 @@ export async function load(config: Config): Promise<[GraphModel | null, GraphMod
   return [models.detector, models.landmarks];
 }
 
-function prepareImage(input: Tensor, size: number): Tensor {
+function prepareImage(input: Tensor4D, size: number): Tensor {
   const t: Record<string, Tensor> = {};
   if (!input?.shape?.[1] || !input?.shape?.[2]) return input;
   let final: Tensor;
@@ -82,10 +82,10 @@ function prepareImage(input: Tensor, size: number): Tensor {
       [0, 0], // dont touch rbg
     ];
     t.pad = tf.pad(t.cropped || input, padding); // use cropped box if it exists
-    t.resize = tf.image.resizeBilinear(t.pad, [size, size]);
+    t.resize = tf.image.resizeBilinear(t.pad as Tensor4D, [size, size]);
     final = tf.div(t.resize, constants.tf255);
   } else if (input.shape[1] !== size) { // if input needs resizing
-    t.resize = tf.image.resizeBilinear(t.cropped || input, [size, size]);
+    t.resize = tf.image.resizeBilinear(t.cropped as Tensor4D || input, [size, size]);
     final = tf.div(t.resize, constants.tf255);
   } else { // if input is already in a correct resolution just normalize it
     final = tf.div(t.cropped || input, constants.tf255);
@@ -142,7 +142,7 @@ async function detectLandmarks(input: Tensor, config: Config, outputSize: [numbe
   */
   if (!models.landmarks?.['executor']) return null;
   const t: Record<string, Tensor> = {};
-  [t.ld/* 1,195(39*5) */, t.segmentation/* 1,256,256,1 */, t.heatmap/* 1,64,64,39 */, t.world/* 1,117(39*3) */, t.poseflag/* 1,1 */] = models.landmarks?.execute(input, outputNodes.landmarks) as Tensor[]; // run model
+  [t.ld/* 1,195(39*5) */, t.segmentation/* 1,256,256,1 */, t.heatmap/* 1,64,64,39 */, t.world/* 1,117(39*3) */, t.poseflag/* 1,1 */] = models.landmarks?.execute(input, outputNodes.landmarks) as unknown as Tensor[]; // run model
   const poseScore = (await t.poseflag.data())[0];
   const points = await t.ld.data();
   const distances = await t.world.data();
@@ -207,7 +207,7 @@ async function detectBoxes(input: Tensor, config: Config, outputSize: [number, n
 }
 */
 
-export async function predict(input: Tensor, config: Config): Promise<BodyResult[]> {
+export async function predict(input: Tensor4D, config: Config): Promise<BodyResult[]> {
   const outputSize: [number, number] = [input.shape[2] || 0, input.shape[1] || 0];
   const skipTime = (config.body.skipTime || 0) > (now() - lastTime);
   const skipFrame = skipped < (config.body.skipFrames || 0);
diff --git a/src/body/blazeposedetector.ts b/src/body/blazeposedetector.ts
index efb28fc3..447d4ddd 100644
--- a/src/body/blazeposedetector.ts
+++ b/src/body/blazeposedetector.ts
@@ -1,4 +1,4 @@
-import * as tf from '../../dist/tfjs.esm.js';
+import * as tf from 'dist/tfjs.esm.js';
 import type { Tensor } from '../tfjs/types';
 import type { Box } from '../result';
 import type { Config } from '../config';
diff --git a/src/body/efficientpose.ts b/src/body/efficientpose.ts
index 5680b0d8..406a62b0 100644
--- a/src/body/efficientpose.ts
+++ b/src/body/efficientpose.ts
@@ -4,13 +4,13 @@
  * Based on: [**EfficientPose**](https://github.com/daniegr/EfficientPose)
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log, now } from '../util/util';
-import * as tf from '../../dist/tfjs.esm.js';
 import { loadModel } from '../tfjs/load';
 import * as coords from './efficientposecoords';
 import { constants } from '../tfjs/constants';
 import type { BodyResult, Point, BodyLandmark, BodyAnnotation } from '../result';
-import type { GraphModel, Tensor } from '../tfjs/types';
+import type { GraphModel, Tensor4D } from '../tfjs/types';
 import type { Config } from '../config';
 import { env } from '../util/env';
 
@@ -50,8 +50,8 @@ async function max2d(inputs, minScore): Promise<[number, number, number]> {
   return [0, 0, newScore];
 }
 
-export async function predict(image: Tensor, config: Config): Promise<BodyResult[]> {
-  if (!model?.['executor']) return [];
+export async function predict(image: Tensor4D, config: Config): Promise<BodyResult[]> {
+  if (!model?.['executor'] || !model?.inputs[0].shape) return [];
   const skipTime = (config.body.skipTime || 0) > (now() - lastTime);
   const skipFrame = skipped < (config.body.skipFrames || 0);
   if (config.skipAllowed && skipTime && skipFrame && Object.keys(cache.keypoints).length > 0) {
@@ -61,8 +61,7 @@ export async function predict(image: Tensor, config: Config): Promise<BodyResult
   skipped = 0;
   return new Promise(async (resolve) => {
     const tensor = tf.tidy(() => {
-      if (!model?.inputs[0].shape) return null;
-      const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);
+      const resize = tf.image.resizeBilinear(image, [model?.inputs[0].shape?.[2] || 0, model?.inputs[0].shape?.[1] || 0], false);
       const enhance = tf.mul(resize, constants.tf2);
       const norm = tf.sub(enhance, constants.tf1);
       return norm;
diff --git a/src/body/movenet.ts b/src/body/movenet.ts
index 26637702..aea787ba 100644
--- a/src/body/movenet.ts
+++ b/src/body/movenet.ts
@@ -4,9 +4,9 @@
  * Based on: [**MoveNet**](https://blog.tensorflow.org/2021/05/next-generation-pose-detection-with-movenet-and-tensorflowjs.html)
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log, now } from '../util/util';
 import * as box from '../util/box';
-import * as tf from '../../dist/tfjs.esm.js';
 import * as coords from './movenetcoords';
 import * as fix from './movenetfix';
 import { loadModel } from '../tfjs/load';
diff --git a/src/body/movenetfix.ts b/src/body/movenetfix.ts
index 43e9c716..0b82c44a 100644
--- a/src/body/movenetfix.ts
+++ b/src/body/movenetfix.ts
@@ -1,8 +1,8 @@
+import * as tf from 'dist/tfjs.esm.js';
 import type { BodyKeypoint, BodyResult } from '../result';
 import * as box from '../util/box';
 import * as coords from './movenetcoords';
-import * as tf from '../../dist/tfjs.esm.js';
-import type { Tensor } from '../tfjs/types';
+import type { Tensor, Tensor3D } from '../tfjs/types';
 
 const maxJitter = 0.005; // default allowed jitter is within 0.5%
 
@@ -83,7 +83,7 @@ export function padInput(input: Tensor, inputSize: number): Tensor {
     [0, 0], // dont touch rbg
   ];
   t.pad = tf.pad(input, cache.padding);
-  t.resize = tf.image.resizeBilinear(t.pad, [inputSize, inputSize]);
+  t.resize = tf.image.resizeBilinear(t.pad as Tensor3D, [inputSize, inputSize]);
   const final = tf.cast(t.resize, 'int32');
   Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));
   return final;
diff --git a/src/body/posenet.ts b/src/body/posenet.ts
index 166bceea..bdeac329 100644
--- a/src/body/posenet.ts
+++ b/src/body/posenet.ts
@@ -4,11 +4,11 @@
  * Based on: [**PoseNet**](https://medium.com/tensorflow/real-time-human-pose-estimation-in-the-browser-with-tensorflow-js-7dd0bc881cd5)
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log } from '../util/util';
-import * as tf from '../../dist/tfjs.esm.js';
 import { loadModel } from '../tfjs/load';
 import type { BodyResult, BodyLandmark, Box } from '../result';
-import type { Tensor, GraphModel } from '../tfjs/types';
+import type { Tensor, GraphModel, Tensor4D } from '../tfjs/types';
 import type { Config } from '../config';
 import { env } from '../util/env';
 import * as utils from './posenetutils';
@@ -155,7 +155,7 @@ export function decode(offsets, scores, displacementsFwd, displacementsBwd, maxD
   return poses;
 }
 
-export async function predict(input: Tensor, config: Config): Promise<BodyResult[]> {
+export async function predict(input: Tensor4D, config: Config): Promise<BodyResult[]> {
   /** posenet is mostly obsolete
    * caching is not implemented
    */
diff --git a/src/exports.ts b/src/exports.ts
index e83978d9..e499a9f6 100644
--- a/src/exports.ts
+++ b/src/exports.ts
@@ -6,8 +6,10 @@ export * from './config';
 /* Export results details */
 export * from './result';
 
-/* Explict reexport of main @tensorflow/tfjs types */
-export type { Tensor, TensorLike, GraphModel, Rank } from './tfjs/types';
+/**
+ * Explict reexport of main @tensorflow/tfjs types
+ */
+export type { Tensor, Tensor4D, GraphModel, Rank } from './tfjs/types';
 
 // re-export types
 export type { DrawOptions } from './draw/options';
diff --git a/src/face/antispoof.ts b/src/face/antispoof.ts
index aeb8c9ec..6deebfa9 100644
--- a/src/face/antispoof.ts
+++ b/src/face/antispoof.ts
@@ -2,10 +2,10 @@
  * Anti-spoofing model implementation
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log, now } from '../util/util';
 import type { Config } from '../config';
-import type { GraphModel, Tensor } from '../tfjs/types';
-import * as tf from '../../dist/tfjs.esm.js';
+import type { GraphModel, Tensor, Tensor4D } from '../tfjs/types';
 import { loadModel } from '../tfjs/load';
 import { env } from '../util/env';
 
@@ -22,7 +22,7 @@ export async function load(config: Config): Promise<GraphModel> {
   return model;
 }
 
-export async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<number> {
+export async function predict(image: Tensor4D, config: Config, idx: number, count: number): Promise<number> {
   if (!model || !model?.['executor']) return 0;
   const skipTime = (config.face.antispoof?.skipTime || 0) > (now() - lastTime);
   const skipFrame = skipped < (config.face.antispoof?.skipFrames || 0);
diff --git a/src/face/blazeface.ts b/src/face/blazeface.ts
index 88dc3cdf..2c08241e 100644
--- a/src/face/blazeface.ts
+++ b/src/face/blazeface.ts
@@ -3,13 +3,13 @@
  * See `facemesh.ts` for entry point
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log } from '../util/util';
-import * as tf from '../../dist/tfjs.esm.js';
 import * as util from './facemeshutil';
 import { loadModel } from '../tfjs/load';
 import { constants } from '../tfjs/constants';
 import type { Config } from '../config';
-import type { Tensor, GraphModel } from '../tfjs/types';
+import type { Tensor, GraphModel, Tensor1D, Tensor2D, Tensor4D } from '../tfjs/types';
 import { env } from '../util/env';
 import type { Point } from '../result';
 
@@ -35,6 +35,7 @@ export async function load(config: Config): Promise<GraphModel> {
 }
 
 function decodeBoxes(boxOutputs: Tensor) {
+  if (!anchors || !inputSizeT) return tf.zeros([0, 0]);
   const t: Record<string, Tensor> = {};
   t.boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);
   t.centers = tf.add(t.boxStarts, anchors);
@@ -46,12 +47,12 @@ function decodeBoxes(boxOutputs: Tensor) {
   t.ends = tf.add(t.centersNormalized, t.halfBoxSize);
   t.startNormalized = tf.mul(t.starts, inputSizeT);
   t.endNormalized = tf.mul(t.ends, inputSizeT);
-  const boxes = tf.concat2d([t.startNormalized, t.endNormalized], 1);
+  const boxes = tf.concat2d([t.startNormalized as Tensor2D, t.endNormalized as Tensor2D], 1);
   Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));
   return boxes;
 }
 
-export async function getBoxes(inputImage: Tensor, config: Config) {
+export async function getBoxes(inputImage: Tensor4D, config: Config) {
   // sanity check on input
   if ((!inputImage) || (inputImage['isDisposedInternal']) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return [];
   const t: Record<string, Tensor> = {};
@@ -64,7 +65,7 @@ export async function getBoxes(inputImage: Tensor, config: Config) {
     t.concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16
     t.concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16
     t.concat = tf.concat([t.concat512, t.concat384], 1);
-    t.batch = tf.squeeze(t.concat, 0);
+    t.batch = tf.squeeze(t.concat, [0]);
   } else if (Array.isArray(res)) { // new facemesh-detection tfhub model
     t.batch = tf.squeeze(res[0]);
   } else { // original blazeface tfhub model
@@ -75,7 +76,7 @@ export async function getBoxes(inputImage: Tensor, config: Config) {
   t.logits = tf.slice(t.batch, [0, 0], [-1, 1]);
   t.sigmoid = tf.sigmoid(t.logits);
   t.scores = tf.squeeze(t.sigmoid);
-  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes, t.scores, (config.face.detector?.maxDetected || 0), (config.face.detector?.iouThreshold || 0), (config.face.detector?.minConfidence || 0));
+  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes as Tensor2D, t.scores as Tensor1D, (config.face.detector?.maxDetected || 0), (config.face.detector?.iouThreshold || 0), (config.face.detector?.minConfidence || 0));
   const nms = await t.nms.array() as number[];
   const boxes: DetectBox[] = [];
   const scores = await t.scores.data();
diff --git a/src/face/face.ts b/src/face/face.ts
index f87c310b..bb8fbca2 100644
--- a/src/face/face.ts
+++ b/src/face/face.ts
@@ -3,9 +3,9 @@
  * Uses FaceMesh, Emotion and FaceRes models to create a unified pipeline
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log, now } from '../util/util';
 import { env } from '../util/env';
-import * as tf from '../../dist/tfjs.esm.js';
 import * as facemesh from './facemesh';
 import * as emotion from '../gear/emotion';
 import * as faceres from './faceres';
@@ -18,13 +18,13 @@ import * as ssrnetGender from '../gear/ssrnet-gender';
 import * as mobilefacenet from './mobilefacenet';
 import * as insightface from './insightface';
 import type { FaceResult, Emotion, Gender, Race } from '../result';
-import type { Tensor } from '../tfjs/types';
+import type { Tensor4D } from '../tfjs/types';
 import type { Human } from '../human';
 import { calculateFaceAngle } from './angles';
 
 interface DescRes { age: number, gender: Gender, genderScore: number, descriptor: number[], race?: { score: number, race: Race }[] }
 
-export const detectFace = async (instance: Human /* instance of human */, input: Tensor): Promise<FaceResult[]> => {
+export const detectFace = async (instance: Human /* instance of human */, input: Tensor4D): Promise<FaceResult[]> => {
   // run facemesh, includes blazeface and iris
   let timeStamp: number = now();
   let ageRes: { age: number } | Promise<{ age: number }> | null;
@@ -68,11 +68,11 @@ export const detectFace = async (instance: Human /* instance of human */, input:
     // run emotion, inherits face from blazeface
     instance.analyze('Start Emotion:');
     if (instance.config.async) {
-      emotionRes = instance.config.face.emotion?.enabled ? emotion.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : [];
+      emotionRes = instance.config.face.emotion?.enabled ? emotion.predict(faces[i].tensor as Tensor4D || tf.tensor([]), instance.config, i, faces.length) : [];
     } else {
       instance.state = 'run:emotion';
       timeStamp = now();
-      emotionRes = instance.config.face.emotion?.enabled ? await emotion.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : [];
+      emotionRes = instance.config.face.emotion?.enabled ? await emotion.predict(faces[i].tensor as Tensor4D || tf.tensor([]), instance.config, i, faces.length) : [];
       instance.performance.emotion = env.perfadd ? (instance.performance.emotion || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     instance.analyze('End Emotion:');
@@ -80,11 +80,11 @@ export const detectFace = async (instance: Human /* instance of human */, input:
     // run antispoof, inherits face from blazeface
     instance.analyze('Start AntiSpoof:');
     if (instance.config.async) {
-      antispoofRes = instance.config.face.antispoof?.enabled ? antispoof.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : 0;
+      antispoofRes = instance.config.face.antispoof?.enabled ? antispoof.predict(faces[i].tensor as Tensor4D || tf.tensor([]), instance.config, i, faces.length) : 0;
     } else {
       instance.state = 'run:antispoof';
       timeStamp = now();
-      antispoofRes = instance.config.face.antispoof?.enabled ? await antispoof.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : 0;
+      antispoofRes = instance.config.face.antispoof?.enabled ? await antispoof.predict(faces[i].tensor as Tensor4D || tf.tensor([]), instance.config, i, faces.length) : 0;
       instance.performance.antispoof = env.perfadd ? (instance.performance.antispoof || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     instance.analyze('End AntiSpoof:');
@@ -92,11 +92,11 @@ export const detectFace = async (instance: Human /* instance of human */, input:
     // run liveness, inherits face from blazeface
     instance.analyze('Start Liveness:');
     if (instance.config.async) {
-      livenessRes = instance.config.face.liveness?.enabled ? liveness.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : 0;
+      livenessRes = instance.config.face.liveness?.enabled ? liveness.predict(faces[i].tensor as Tensor4D || tf.tensor([]), instance.config, i, faces.length) : 0;
     } else {
       instance.state = 'run:liveness';
       timeStamp = now();
-      livenessRes = instance.config.face.liveness?.enabled ? await liveness.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : 0;
+      livenessRes = instance.config.face.liveness?.enabled ? await liveness.predict(faces[i].tensor as Tensor4D || tf.tensor([]), instance.config, i, faces.length) : 0;
       instance.performance.liveness = env.perfadd ? (instance.performance.antispoof || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     instance.analyze('End Liveness:');
@@ -104,11 +104,11 @@ export const detectFace = async (instance: Human /* instance of human */, input:
     // run gear, inherits face from blazeface
     instance.analyze('Start GEAR:');
     if (instance.config.async) {
-      gearRes = instance.config.face.gear?.enabled ? gear.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;
+      gearRes = instance.config.face.gear?.enabled ? gear.predict(faces[i].tensor as Tensor4D || tf.tensor([]), instance.config, i, faces.length) : null;
     } else {
       instance.state = 'run:gear';
       timeStamp = now();
-      gearRes = instance.config.face.gear?.enabled ? await gear.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;
+      gearRes = instance.config.face.gear?.enabled ? await gear.predict(faces[i].tensor as Tensor4D || tf.tensor([]), instance.config, i, faces.length) : null;
       instance.performance.gear = Math.trunc(now() - timeStamp);
     }
     instance.analyze('End GEAR:');
@@ -116,13 +116,13 @@ export const detectFace = async (instance: Human /* instance of human */, input:
     // run gear, inherits face from blazeface
     instance.analyze('Start SSRNet:');
     if (instance.config.async) {
-      ageRes = instance.config.face['ssrnet']?.enabled ? ssrnetAge.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;
-      genderRes = instance.config.face['ssrnet']?.enabled ? ssrnetGender.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;
+      ageRes = instance.config.face['ssrnet']?.enabled ? ssrnetAge.predict(faces[i].tensor as Tensor4D || tf.tensor([]), instance.config, i, faces.length) : null;
+      genderRes = instance.config.face['ssrnet']?.enabled ? ssrnetGender.predict(faces[i].tensor as Tensor4D || tf.tensor([]), instance.config, i, faces.length) : null;
     } else {
       instance.state = 'run:ssrnet';
       timeStamp = now();
-      ageRes = instance.config.face['ssrnet']?.enabled ? await ssrnetAge.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;
-      genderRes = instance.config.face['ssrnet']?.enabled ? await ssrnetGender.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;
+      ageRes = instance.config.face['ssrnet']?.enabled ? await ssrnetAge.predict(faces[i].tensor as Tensor4D || tf.tensor([]), instance.config, i, faces.length) : null;
+      genderRes = instance.config.face['ssrnet']?.enabled ? await ssrnetGender.predict(faces[i].tensor as Tensor4D || tf.tensor([]), instance.config, i, faces.length) : null;
       instance.performance.ssrnet = Math.trunc(now() - timeStamp);
     }
     instance.analyze('End SSRNet:');
@@ -130,11 +130,11 @@ export const detectFace = async (instance: Human /* instance of human */, input:
     // run mobilefacenet alternative, inherits face from blazeface
     instance.analyze('Start MobileFaceNet:');
     if (instance.config.async) {
-      mobilefacenetRes = instance.config.face['mobilefacenet']?.enabled ? mobilefacenet.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;
+      mobilefacenetRes = instance.config.face['mobilefacenet']?.enabled ? mobilefacenet.predict(faces[i].tensor as Tensor4D || tf.tensor([]), instance.config, i, faces.length) : null;
     } else {
       instance.state = 'run:mobilefacenet';
       timeStamp = now();
-      mobilefacenetRes = instance.config.face['mobilefacenet']?.enabled ? await mobilefacenet.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;
+      mobilefacenetRes = instance.config.face['mobilefacenet']?.enabled ? await mobilefacenet.predict(faces[i].tensor as Tensor4D || tf.tensor([]), instance.config, i, faces.length) : null;
       instance.performance.mobilefacenet = Math.trunc(now() - timeStamp);
     }
     instance.analyze('End MobileFaceNet:');
@@ -142,11 +142,11 @@ export const detectFace = async (instance: Human /* instance of human */, input:
     // run insightface alternative, inherits face from blazeface
     instance.analyze('Start InsightFace:');
     if (instance.config.async) {
-      insightfaceRes = instance.config.face['insightface']?.enabled ? insightface.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;
+      insightfaceRes = instance.config.face['insightface']?.enabled ? insightface.predict(faces[i].tensor as Tensor4D || tf.tensor([]), instance.config, i, faces.length) : null;
     } else {
       instance.state = 'run:mobilefacenet';
       timeStamp = now();
-      insightfaceRes = instance.config.face['insightface']?.enabled ? await insightface.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;
+      insightfaceRes = instance.config.face['insightface']?.enabled ? await insightface.predict(faces[i].tensor as Tensor4D || tf.tensor([]), instance.config, i, faces.length) : null;
       instance.performance.mobilefacenet = Math.trunc(now() - timeStamp);
     }
     instance.analyze('End InsightFace:');
@@ -154,11 +154,11 @@ export const detectFace = async (instance: Human /* instance of human */, input:
     // run faceres, inherits face from blazeface
     instance.analyze('Start Description:');
     if (instance.config.async) {
-      descRes = faceres.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length);
+      descRes = faceres.predict(faces[i].tensor as Tensor4D || tf.tensor([]), instance.config, i, faces.length);
     } else {
       instance.state = 'run:description';
       timeStamp = now();
-      descRes = await faceres.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length);
+      descRes = await faceres.predict(faces[i].tensor as Tensor4D || tf.tensor([]), instance.config, i, faces.length);
       instance.performance.description = env.perfadd ? (instance.performance.description || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     instance.analyze('End Description:');
@@ -207,7 +207,7 @@ export const detectFace = async (instance: Human /* instance of human */, input:
       : 0; // note: average human iris size is 11.7mm
 
     // optionally return tensor
-    const tensor = instance.config.face.detector?.return ? tf.squeeze(faces[i].tensor) : null;
+    const tensor = instance.config.face.detector?.return ? tf.squeeze(faces[i].tensor as Tensor4D) : null;
     // dispose original face tensor
     tf.dispose(faces[i].tensor);
     // delete temp face image
diff --git a/src/face/faceboxes.ts b/src/face/faceboxes.ts
index f7c7ccee..6d42f9f5 100644
--- a/src/face/faceboxes.ts
+++ b/src/face/faceboxes.ts
@@ -1,7 +1,7 @@
 // https://github.com/TropComplique/FaceBoxes-tensorflow
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log } from '../util/util';
-import * as tf from '../../dist/tfjs.esm.js';
 import { loadModel } from '../tfjs/load';
 import type { GraphModel, Tensor } from '../tfjs/types';
 import type { Config } from '../config';
@@ -29,14 +29,14 @@ export class FaceBoxes {
     const [scoresT, boxesT, numT] = await this.model.executeAsync(castT) as Tensor[];
     const scores = await scoresT.data();
     const squeezeT = tf.squeeze(boxesT);
-    const boxes = squeezeT.arraySync();
+    const boxes = squeezeT.arraySync() as number[][];
     scoresT.dispose();
     boxesT.dispose();
     squeezeT.dispose();
     numT.dispose();
     castT.dispose();
     resizeT.dispose();
-    for (const i in boxes) {
+    for (let i = 0; i < boxes.length; i++) {
       if (scores[i] && scores[i] > (this.config.face.detector?.minConfidence || 0.1)) {
         const crop = [boxes[i][0] / this.enlarge, boxes[i][1] / this.enlarge, boxes[i][2] * this.enlarge, boxes[i][3] * this.enlarge];
         const boxRaw: Box = [crop[1], crop[0], (crop[3]) - (crop[1]), (crop[2]) - (crop[0])];
diff --git a/src/face/facemesh.ts b/src/face/facemesh.ts
index 17fccd45..38e75865 100644
--- a/src/face/facemesh.ts
+++ b/src/face/facemesh.ts
@@ -7,9 +7,9 @@
  * - Eye Iris Details: [**MediaPipe Iris**](https://drive.google.com/file/d/1bsWbokp9AklH2ANjCfmjqEzzxO1CNbMu/view)
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log, now } from '../util/util';
 import { loadModel } from '../tfjs/load';
-import * as tf from '../../dist/tfjs.esm.js';
 import * as blazeface from './blazeface';
 import * as util from './facemeshutil';
 import * as coords from './facemeshcoords';
@@ -17,7 +17,7 @@ import * as iris from './iris';
 import * as attention from './attention';
 import { histogramEqualization } from '../image/enhance';
 import { env } from '../util/env';
-import type { GraphModel, Tensor } from '../tfjs/types';
+import type { GraphModel, Tensor, Tensor4D } from '../tfjs/types';
 import type { FaceResult, FaceLandmark, Point } from '../result';
 import type { Config } from '../config';
 
@@ -32,7 +32,7 @@ const cache = {
 let model: GraphModel | null = null;
 let inputSize = 0;
 
-export async function predict(input: Tensor, config: Config): Promise<FaceResult[]> {
+export async function predict(input: Tensor4D, config: Config): Promise<FaceResult[]> {
   if (!model?.['executor']) return [];
   // reset cached boxes
   const skipTime = (config.face.detector?.skipTime || 0) > (now() - cache.timestamp);
diff --git a/src/face/facemeshutil.ts b/src/face/facemeshutil.ts
index 90ac1ae8..6628ee61 100644
--- a/src/face/facemeshutil.ts
+++ b/src/face/facemeshutil.ts
@@ -3,7 +3,7 @@
  * See `facemesh.ts` for entry point
  */
 
-import * as tf from '../../dist/tfjs.esm.js';
+import * as tf from 'dist/tfjs.esm.js';
 import * as coords from './facemeshcoords';
 import { constants } from '../tfjs/constants';
 import type { Box, Point } from '../result';
@@ -175,7 +175,7 @@ export function correctFaceRotation(rotate, box, input, inputSize) {
     if (largeAngle) { // perform rotation only if angle is sufficiently high
       const center: Point = getBoxCenter(box);
       const centerRaw: Point = [center[0] / input.shape[2], center[1] / input.shape[1]];
-      const rotated = tf.image.rotateWithOffset(input, angle, 0, centerRaw);
+      const rotated = tf.image.rotateWithOffset(input, angle, 0, [centerRaw[0], centerRaw[1]]);
       rotationMatrix = buildRotationMatrix(-angle, center);
       face = cutAndResize(box, rotated, [inputSize, inputSize]);
       tf.dispose(rotated);
diff --git a/src/face/faceres.ts b/src/face/faceres.ts
index fe1ed588..9c8e8913 100644
--- a/src/face/faceres.ts
+++ b/src/face/faceres.ts
@@ -7,12 +7,12 @@
  * Based on: [**HSE-FaceRes**](https://github.com/HSE-asavchenko/HSE_FaceRec_tf)
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log, now } from '../util/util';
 import { env } from '../util/env';
-import * as tf from '../../dist/tfjs.esm.js';
 import { loadModel } from '../tfjs/load';
 import { constants } from '../tfjs/constants';
-import type { Tensor, GraphModel } from '../tfjs/types';
+import type { Tensor, GraphModel, Tensor4D, Tensor1D } from '../tfjs/types';
 import type { Config } from '../config';
 import type { Gender, Race } from '../result';
 
@@ -33,7 +33,7 @@ export async function load(config: Config): Promise<GraphModel> {
 }
 
 export function enhance(input): Tensor {
-  const tensor = (input.image || input.tensor || input) as Tensor; // input received from detector is already normalized to 0..1, input is also assumed to be straightened
+  const tensor = (input.image || input.tensor || input) as Tensor4D; // input received from detector is already normalized to 0..1, input is also assumed to be straightened
   if (!model?.inputs[0].shape) return tensor; // model has no shape so no point continuing
   const crop: Tensor = tf.image.resizeBilinear(tensor, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);
   const norm: Tensor = tf.mul(crop, constants.tf255);
@@ -58,7 +58,7 @@ export function enhance(input): Tensor {
   */
 }
 
-export async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<FaceRes> {
+export async function predict(image: Tensor4D, config: Config, idx: number, count: number): Promise<FaceRes> {
   const obj: FaceRes = {
     age: 0 as number,
     gender: 'unknown' as Gender,
@@ -86,7 +86,7 @@ export async function predict(image: Tensor, config: Config, idx: number, count:
         obj.gender = gender[0] <= 0.5 ? 'female' : 'male';
         obj.genderScore = Math.min(0.99, confidence);
       }
-      const argmax = tf.argMax(resT.find((t) => t.shape[1] === 100), 1);
+      const argmax = tf.argMax(resT.find((t) => t.shape[1] === 100) as Tensor1D, 1);
       const ageIdx: number = (await argmax.data())[0];
       tf.dispose(argmax);
       const ageT = resT.find((t) => t.shape[1] === 100) as Tensor;
diff --git a/src/face/insightface.ts b/src/face/insightface.ts
index 1a0bdb5a..3d5c577f 100644
--- a/src/face/insightface.ts
+++ b/src/face/insightface.ts
@@ -6,10 +6,10 @@
  * Alternative face embedding detection
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log, now } from '../util/util';
-import * as tf from '../../dist/tfjs.esm.js';
 import { loadModel } from '../tfjs/load';
-import type { Tensor, GraphModel } from '../tfjs/types';
+import type { Tensor, Tensor4D, GraphModel } from '../tfjs/types';
 import type { Config } from '../config';
 import { env } from '../util/env';
 
@@ -26,7 +26,7 @@ export async function load(config: Config): Promise<GraphModel> {
   return model;
 }
 
-export async function predict(input: Tensor, config: Config, idx, count): Promise<number[]> {
+export async function predict(input: Tensor4D, config: Config, idx, count): Promise<number[]> {
   if (!model?.['executor']) return [];
   const skipFrame = skipped < (config.face['insightface']?.skipFrames || 0);
   const skipTime = (config.face['insightface']?.skipTime || 0) > (now() - lastTime);
diff --git a/src/face/iris.ts b/src/face/iris.ts
index abc00fa2..d2117d81 100644
--- a/src/face/iris.ts
+++ b/src/face/iris.ts
@@ -1,6 +1,6 @@
+import * as tf from 'dist/tfjs.esm.js';
 import * as coords from './facemeshcoords';
 import * as util from './facemeshutil';
-import * as tf from '../../dist/tfjs.esm.js';
 import type { Tensor, GraphModel } from '../tfjs/types';
 import { env } from '../util/env';
 import { log } from '../util/util';
diff --git a/src/face/liveness.ts b/src/face/liveness.ts
index 94d154cf..29bb31e9 100644
--- a/src/face/liveness.ts
+++ b/src/face/liveness.ts
@@ -2,11 +2,11 @@
  * Anti-spoofing model implementation
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log, now } from '../util/util';
 import { loadModel } from '../tfjs/load';
 import type { Config } from '../config';
-import type { GraphModel, Tensor } from '../tfjs/types';
-import * as tf from '../../dist/tfjs.esm.js';
+import type { GraphModel, Tensor, Tensor4D } from '../tfjs/types';
 import { env } from '../util/env';
 
 let model: GraphModel | null;
@@ -22,7 +22,7 @@ export async function load(config: Config): Promise<GraphModel> {
   return model;
 }
 
-export async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<number> {
+export async function predict(image: Tensor4D, config: Config, idx: number, count: number): Promise<number> {
   if (!model?.['executor']) return 0;
   const skipTime = (config.face.liveness?.skipTime || 0) > (now() - lastTime);
   const skipFrame = skipped < (config.face.liveness?.skipFrames || 0);
diff --git a/src/face/mask.ts b/src/face/mask.ts
index 1d6e723d..e07a28cc 100644
--- a/src/face/mask.ts
+++ b/src/face/mask.ts
@@ -1,6 +1,6 @@
 import type { Tensor } from '../tfjs/types';
 import type { FaceResult } from '../result';
-import * as tf from '../../dist/tfjs.esm.js';
+// import * as tf from 'dist/tfjs.esm.js';
 import { meshAnnotations } from './facemeshcoords';
 
 const expandFact = 0.1;
@@ -36,6 +36,6 @@ export async function mask(face: FaceResult): Promise<Tensor | undefined> {
     }
   }
   const output = buffer.toTensor();
-  tf.dispose(buffer);
+  // tf.dispose(buffer);
   return output;
 }
diff --git a/src/face/mobilefacenet.ts b/src/face/mobilefacenet.ts
index d8a5dcfc..e569d4a5 100644
--- a/src/face/mobilefacenet.ts
+++ b/src/face/mobilefacenet.ts
@@ -6,10 +6,10 @@
  * Obsolete and replaced by `faceres` that performs age/gender/descriptor analysis
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log, now } from '../util/util';
-import * as tf from '../../dist/tfjs.esm.js';
 import { loadModel } from '../tfjs/load';
-import type { Tensor, GraphModel } from '../tfjs/types';
+import type { Tensor, Tensor4D, GraphModel } from '../tfjs/types';
 import type { Config } from '../config';
 import { env } from '../util/env';
 
@@ -44,7 +44,7 @@ const factor = 5;
 const contrast = merge.sub(mean).mul(factor).add(mean);
 */
 
-export async function predict(input: Tensor, config: Config, idx, count): Promise<number[]> {
+export async function predict(input: Tensor4D, config: Config, idx, count): Promise<number[]> {
   if (!model?.['executor']) return [];
   const skipFrame = skipped < (config.face['mobilefacenet']?.skipFrames || 0);
   const skipTime = (config.face['mobilefacenet']?.skipTime || 0) > (now() - lastTime);
diff --git a/src/gear/emotion.ts b/src/gear/emotion.ts
index 7fb8b152..9b1a4df2 100644
--- a/src/gear/emotion.ts
+++ b/src/gear/emotion.ts
@@ -4,11 +4,11 @@
  * [**Oarriaga**](https://github.com/oarriaga/face_classification)
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import type { Emotion } from '../result';
 import { log, now } from '../util/util';
 import type { Config } from '../config';
-import type { GraphModel, Tensor } from '../tfjs/types';
-import * as tf from '../../dist/tfjs.esm.js';
+import type { GraphModel, Tensor, Tensor4D } from '../tfjs/types';
 import { loadModel } from '../tfjs/load';
 import { env } from '../util/env';
 import { constants } from '../tfjs/constants';
@@ -27,7 +27,7 @@ export async function load(config: Config): Promise<GraphModel> {
   return model;
 }
 
-export async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<{ score: number, emotion: Emotion }[]> {
+export async function predict(image: Tensor4D, config: Config, idx: number, count: number): Promise<{ score: number, emotion: Emotion }[]> {
   if (!model) return [];
   const skipFrame = skipped < (config.face.emotion?.skipFrames || 0);
   const skipTime = (config.face.emotion?.skipTime || 0) > (now() - lastTime);
diff --git a/src/gear/gear.ts b/src/gear/gear.ts
index 9cacbba3..d87c78c9 100644
--- a/src/gear/gear.ts
+++ b/src/gear/gear.ts
@@ -4,12 +4,12 @@
  * Based on: [**GEAR Predictor**](https://github.com/Udolf15/GEAR-Predictor)
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log, now } from '../util/util';
-import * as tf from '../../dist/tfjs.esm.js';
 import { loadModel } from '../tfjs/load';
 import type { Gender, Race } from '../result';
 import type { Config } from '../config';
-import type { GraphModel, Tensor } from '../tfjs/types';
+import type { GraphModel, Tensor, Tensor4D } from '../tfjs/types';
 import { env } from '../util/env';
 
 export interface GearType { age: number, gender: Gender, genderScore: number, race: { score: number, race: Race }[] }
@@ -28,7 +28,7 @@ export async function load(config: Config) {
   return model;
 }
 
-export async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<GearType> {
+export async function predict(image: Tensor4D, config: Config, idx: number, count: number): Promise<GearType> {
   if (!model) return { age: 0, gender: 'unknown', genderScore: 0, race: [] };
   const skipFrame = skipped < (config.face.gear?.skipFrames || 0);
   const skipTime = (config.face.gear?.skipTime || 0) > (now() - lastTime);
diff --git a/src/gear/ssrnet-age.ts b/src/gear/ssrnet-age.ts
index 95621838..f9e9afcd 100644
--- a/src/gear/ssrnet-age.ts
+++ b/src/gear/ssrnet-age.ts
@@ -4,13 +4,13 @@
  * Based on: [**SSR-Net**](https://github.com/shamangary/SSR-Net)
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log, now } from '../util/util';
-import * as tf from '../../dist/tfjs.esm.js';
 import { loadModel } from '../tfjs/load';
 import { env } from '../util/env';
 import { constants } from '../tfjs/constants';
 import type { Config } from '../config';
-import type { GraphModel, Tensor } from '../tfjs/types';
+import type { GraphModel, Tensor, Tensor4D } from '../tfjs/types';
 
 let model: GraphModel | null;
 const last: { age: number }[] = [];
@@ -25,7 +25,7 @@ export async function load(config: Config) {
   return model;
 }
 
-export async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<{ age: number }> {
+export async function predict(image: Tensor4D, config: Config, idx: number, count: number): Promise<{ age: number }> {
   if (!model) return { age: 0 };
   const skipFrame = skipped < (config.face['ssrnet']?.skipFrames || 0);
   const skipTime = (config.face['ssrnet']?.skipTime || 0) > (now() - lastTime);
diff --git a/src/gear/ssrnet-gender.ts b/src/gear/ssrnet-gender.ts
index f91c6fb0..3a09d120 100644
--- a/src/gear/ssrnet-gender.ts
+++ b/src/gear/ssrnet-gender.ts
@@ -4,13 +4,13 @@
  * Based on: [**SSR-Net**](https://github.com/shamangary/SSR-Net)
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log, now } from '../util/util';
-import * as tf from '../../dist/tfjs.esm.js';
 import { loadModel } from '../tfjs/load';
 import { constants } from '../tfjs/constants';
 import type { Gender } from '../result';
 import type { Config } from '../config';
-import type { GraphModel, Tensor } from '../tfjs/types';
+import type { GraphModel, Tensor, Tensor4D } from '../tfjs/types';
 import { env } from '../util/env';
 
 let model: GraphModel | null;
@@ -29,7 +29,7 @@ export async function load(config: Config) {
   return model;
 }
 
-export async function predict(image: Tensor, config: Config, idx, count): Promise<{ gender: Gender, genderScore: number }> {
+export async function predict(image: Tensor4D, config: Config, idx, count): Promise<{ gender: Gender, genderScore: number }> {
   if (!model) return { gender: 'unknown', genderScore: 0 };
   const skipFrame = skipped < (config.face['ssrnet']?.skipFrames || 0);
   const skipTime = (config.face['ssrnet']?.skipTime || 0) > (now() - lastTime);
diff --git a/src/hand/handposedetector.ts b/src/hand/handposedetector.ts
index 43b4fc51..2523d529 100644
--- a/src/hand/handposedetector.ts
+++ b/src/hand/handposedetector.ts
@@ -3,11 +3,11 @@
  * See `handpose.ts` for entry point
  */
 
-import * as tf from '../../dist/tfjs.esm.js';
+import * as tf from 'dist/tfjs.esm.js';
 import * as util from './handposeutil';
 import * as anchors from './handposeanchors';
 import { constants } from '../tfjs/constants';
-import type { Tensor, GraphModel } from '../tfjs/types';
+import type { Tensor, Tensor1D, Tensor2D, Tensor4D, GraphModel } from '../tfjs/types';
 import type { Point } from '../result';
 import type { Config } from '../config';
 
@@ -39,22 +39,22 @@ export class HandDetector {
     t.startPoints = tf.mul(t.sub, this.inputSizeTensor);
     t.add = tf.add(t.boxCenterPoints, t.halfBoxSizes);
     t.endPoints = tf.mul(t.add, this.inputSizeTensor);
-    const res = tf.concat2d([t.startPoints, t.endPoints], 1);
+    const res = tf.concat2d([t.startPoints as Tensor2D, t.endPoints as Tensor2D], 1);
     Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));
     return res as Tensor;
   }
 
-  normalizeLandmarks(rawPalmLandmarks, index: number) {
+  normalizeLandmarks(rawPalmLandmarks, index: number): Tensor {
     const t: Record<string, Tensor> = {};
     t.reshape = tf.reshape(rawPalmLandmarks, [-1, 7, 2]);
     t.div = tf.div(t.reshape, this.inputSizeTensor);
     t.landmarks = tf.add(t.div, this.anchors[index] ? this.anchors[index] : 0);
     const res = tf.mul(t.landmarks, this.inputSizeTensor);
     Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));
-    return res as Tensor;
+    return res;
   }
 
-  async predict(input: Tensor, config: Config): Promise<{ startPoint: Point; endPoint: Point, palmLandmarks: Point[]; confidence: number }[]> {
+  async predict(input: Tensor4D, config: Config): Promise<{ startPoint: Point; endPoint: Point, palmLandmarks: Point[]; confidence: number }[]> {
     const t: Record<string, Tensor> = {};
     t.resize = tf.image.resizeBilinear(input, [this.inputSize, this.inputSize]);
     t.div = tf.div(t.resize, constants.tf127);
@@ -68,7 +68,7 @@ export class HandDetector {
     t.boxes = tf.slice(t.predictions, [0, 1], [-1, 4]);
     t.norm = this.normalizeBoxes(t.boxes);
     // box detection is flaky so we look for 3x boxes than we need results
-    t.nms = await tf.image.nonMaxSuppressionAsync(t.norm, t.scores, 3 * (config.hand?.maxDetected || 1), config.hand.iouThreshold, config.hand.minConfidence);
+    t.nms = await tf.image.nonMaxSuppressionAsync(t.norm as Tensor2D, t.scores as Tensor1D, 3 * (config.hand?.maxDetected || 1), config.hand.iouThreshold, config.hand.minConfidence);
     const nms = await t.nms.array() as number[];
     const hands: { startPoint: Point; endPoint: Point; palmLandmarks: Point[]; confidence: number }[] = [];
     for (const index of nms) {
diff --git a/src/hand/handposepipeline.ts b/src/hand/handposepipeline.ts
index 80f43500..2a5bc6b6 100644
--- a/src/hand/handposepipeline.ts
+++ b/src/hand/handposepipeline.ts
@@ -3,7 +3,7 @@
  * See `handpose.ts` for entry point
  */
 
-import * as tf from '../../dist/tfjs.esm.js';
+import * as tf from 'dist/tfjs.esm.js';
 import * as util from './handposeutil';
 import type * as detector from './handposedetector';
 import { constants } from '../tfjs/constants';
@@ -115,7 +115,7 @@ export class HandPipeline {
       if (config.hand.landmarks) {
         const angle = config.hand.rotation ? util.computeRotation(currentBox.palmLandmarks[palmLandmarksPalmBase], currentBox.palmLandmarks[palmLandmarksMiddleFingerBase]) : 0;
         const palmCenter = util.getBoxCenter(currentBox);
-        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];
+        const palmCenterNormalized: [number, number] = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];
         const rotatedImage = config.hand.rotation && env.kernels.includes('rotatewithoffset') ? tf.image.rotateWithOffset(image, angle, 0, palmCenterNormalized) : image.clone();
         const rotationMatrix = util.buildRotationMatrix(-angle, palmCenter);
         const newBox = useFreshBox ? this.getBoxForPalmLandmarks(currentBox.palmLandmarks, rotationMatrix) : currentBox;
diff --git a/src/hand/handposeutil.ts b/src/hand/handposeutil.ts
index d0c0bfd5..bfca72be 100644
--- a/src/hand/handposeutil.ts
+++ b/src/hand/handposeutil.ts
@@ -1,4 +1,4 @@
-import * as tf from '../../dist/tfjs.esm.js';
+import * as tf from 'dist/tfjs.esm.js';
 import type { Point } from '../result';
 
 export function getBoxSize(box) {
diff --git a/src/hand/handtrack.ts b/src/hand/handtrack.ts
index 1c12a877..16d7393a 100644
--- a/src/hand/handtrack.ts
+++ b/src/hand/handtrack.ts
@@ -6,12 +6,12 @@
  * - Hand Tracking: [**HandTracking**](https://github.com/victordibia/handtracking)
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log, now } from '../util/util';
 import * as box from '../util/box';
-import * as tf from '../../dist/tfjs.esm.js';
 import { loadModel } from '../tfjs/load';
 import type { HandResult, HandType, Box, Point } from '../result';
-import type { GraphModel, Tensor } from '../tfjs/types';
+import type { GraphModel, Tensor, Tensor1D, Tensor2D, Tensor4D } from '../tfjs/types';
 import type { Config } from '../config';
 import { env } from '../util/env';
 import * as fingerPose from './fingerpose';
@@ -100,7 +100,7 @@ export async function load(config: Config): Promise<[GraphModel | null, GraphMod
   return models;
 }
 
-async function detectHands(input: Tensor, config: Config): Promise<HandDetectResult[]> {
+async function detectHands(input: Tensor4D, config: Config): Promise<HandDetectResult[]> {
   const hands: HandDetectResult[] = [];
   if (!input || !models[0]) return hands;
   const t: Record<string, Tensor> = {};
@@ -121,7 +121,7 @@ async function detectHands(input: Tensor, config: Config): Promise<HandDetectRes
   t.max = tf.max(t.filtered, 1); // max overall score
   t.argmax = tf.argMax(t.filtered, 1); // class index of max overall score
   let id = 0;
-  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes, t.max, (config.hand.maxDetected || 0) + 1, config.hand.iouThreshold || 0, config.hand.minConfidence || 1);
+  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes as Tensor2D, t.max as Tensor1D, (config.hand.maxDetected || 0) + 1, config.hand.iouThreshold || 0, config.hand.minConfidence || 1);
   const nms = await t.nms.data();
   const scores = await t.max.data();
   const classNum = await t.argmax.data();
@@ -143,7 +143,7 @@ async function detectHands(input: Tensor, config: Config): Promise<HandDetectRes
   return hands;
 }
 
-async function detectFingers(input: Tensor, h: HandDetectResult, config: Config): Promise<HandResult> {
+async function detectFingers(input: Tensor4D, h: HandDetectResult, config: Config): Promise<HandResult> {
   const hand: HandResult = { // initial values inherited from hand detect
     id: h.id,
     score: Math.round(100 * h.score) / 100,
@@ -181,7 +181,7 @@ async function detectFingers(input: Tensor, h: HandDetectResult, config: Config)
   return hand;
 }
 
-export async function predict(input: Tensor, config: Config): Promise<HandResult[]> {
+export async function predict(input: Tensor4D, config: Config): Promise<HandResult[]> {
   if (!models[0]?.['executor'] || !models[1]?.['executor'] || !models[0].inputs[0].shape || !models[1].inputs[0].shape) return []; // something is wrong with the model
   outputSize = [input.shape[2] || 0, input.shape[1] || 0];
   skipped++; // increment skip frames
diff --git a/src/human.ts b/src/human.ts
index 44293a25..f21ea84d 100644
--- a/src/human.ts
+++ b/src/human.ts
@@ -8,12 +8,12 @@
  */
 
 // module imports
+import * as tf from 'dist/tfjs.esm.js';
 import { log, now, mergeDeep, validate } from './util/util';
 import { defaults } from './config';
 import { env, Env } from './util/env';
 import { WebCam } from './util/webcam';
 import { setModelLoadOptions } from './tfjs/load';
-import * as tf from '../dist/tfjs.esm.js';
 import * as app from '../package.json';
 import * as backend from './tfjs/backend';
 import * as draw from './draw/draw';
@@ -41,9 +41,11 @@ import * as selfie from './segmentation/selfie';
 import * as warmups from './warmup';
 
 // type definitions
-import type { Input, Tensor, DrawOptions, Config, Result, FaceResult, HandResult, BodyResult, ObjectResult, GestureResult, PersonResult, AnyCanvas } from './exports';
+import type { Input, DrawOptions, Config, Result, FaceResult, HandResult, BodyResult, ObjectResult, GestureResult, PersonResult, AnyCanvas } from './exports';
+import type { Tensor, Tensor4D } from './tfjs/types';
 // type exports
 export * from './exports';
+// tfjs re-export
 
 /** **Human** library main class
  *
@@ -324,6 +326,7 @@ export class Human {
       await tf.ready();
       if (this.env.browser) {
         if (this.config.debug) log('configuration:', this.config);
+        // @ts-ignore private property
         if (this.config.debug) log('tf flags:', this.tf.ENV.flags);
       }
     }
@@ -379,13 +382,15 @@ export class Human {
    * - actual detection object can be accessed via `human.result`
   */
   async profile(input: Input, userConfig?: Partial<Config>): Promise<{ kernel: string, time: number, perc: number }[]> {
+    // @ts-ignore profile wraps method return values
     const profile = await this.tf.profile(() => this.detect(input, userConfig));
     const kernels: Record<string, number> = {};
     let total = 0;
     for (const kernel of profile.kernels) { // sum kernel time values per kernel
-      if (kernels[kernel.name]) kernels[kernel.name] += kernel.kernelTimeMs;
-      else kernels[kernel.name] = kernel.kernelTimeMs;
-      total += kernel.kernelTimeMs;
+      const ms = Number(kernel.kernelTimeMs) || 0;
+      if (kernels[kernel.name]) kernels[kernel.name] += ms;
+      else kernels[kernel.name] = ms;
+      total += ms;
     }
     const kernelArr: { kernel: string, time: number, perc: number }[] = [];
     Object.entries(kernels).forEach((key) => kernelArr.push({ kernel: key[0], time: key[1] as unknown as number, perc: 0 })); // convert to array
@@ -434,7 +439,7 @@ export class Human {
 
       timeStamp = now();
       this.state = 'image';
-      const img = await image.process(input, this.config) as { canvas: AnyCanvas, tensor: Tensor };
+      const img = await image.process(input, this.config) as { canvas: AnyCanvas, tensor: Tensor4D };
       this.process = img;
       this.performance.inputProcess = this.env.perfadd ? (this.performance.inputProcess || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       this.analyze('Get Image:');
diff --git a/src/image/enhance.ts b/src/image/enhance.ts
index 34aeec47..97846907 100644
--- a/src/image/enhance.ts
+++ b/src/image/enhance.ts
@@ -2,7 +2,7 @@
  * Image enhancements
  */
 
-import * as tf from '../../dist/tfjs.esm.js';
+import * as tf from 'dist/tfjs.esm.js';
 import type { Tensor } from '../exports';
 
 export async function histogramEqualization(inputImage: Tensor): Promise<Tensor> {
@@ -18,7 +18,7 @@ export async function histogramEqualization(inputImage: Tensor): Promise<Tensor>
   const fact = [tf.div(maxValue, range[0]), tf.div(maxValue, range[1]), tf.div(maxValue, range[2])];
   const enh = [tf.mul(sub[0], fact[0]), tf.mul(sub[1], fact[1]), tf.mul(sub[2], fact[2])];
   const rgb = tf.stack([enh[0], enh[1], enh[2]], 2);
-  const reshape = tf.reshape(rgb, [1, squeeze.shape[0], squeeze.shape[1], 3]);
+  const reshape = tf.reshape(rgb, [1, squeeze.shape[0] || 0, squeeze.shape[1] || 0, 3]);
   tf.dispose([...channels, ...min, ...max, ...sub, ...range, ...fact, ...enh, rgb, squeeze]);
-  return reshape as Tensor; // output shape is [1, height, width, 3]
+  return reshape; // output shape is [1, height, width, 3]
 }
diff --git a/src/image/image.ts b/src/image/image.ts
index 681b0880..2236adae 100644
--- a/src/image/image.ts
+++ b/src/image/image.ts
@@ -2,9 +2,10 @@
  * Image Processing algorithm implementation
  */
 
-import * as tf from '../../dist/tfjs.esm.js';
+import * as tf from 'dist/tfjs.esm.js';
 import * as fxImage from './imagefx';
-import type { Input, AnyCanvas, Tensor, Config } from '../exports';
+import type { Input, AnyCanvas, Config } from '../exports';
+import type { Tensor, Tensor3D, Tensor4D } from '../tfjs/types';
 import { env } from '../util/env';
 import { log } from '../util/util';
 import * as enhance from './enhance';
@@ -64,7 +65,7 @@ export function copy(input: AnyCanvas, output?: AnyCanvas) {
 // process input image and return tensor
 // input can be tensor, imagedata, htmlimageelement, htmlvideoelement
 // input is resized and run through imagefx filter
-export async function process(input: Input, config: Config, getTensor: boolean = true): Promise<{ tensor: Tensor | null, canvas: AnyCanvas | null }> {
+export async function process(input: Input, config: Config, getTensor: boolean = true): Promise<{ tensor: Tensor4D | null, canvas: AnyCanvas | null }> {
   if (!input) {
     // throw new Error('input is missing');
     if (config.debug) log('input error: input is missing');
@@ -88,13 +89,13 @@ export async function process(input: Input, config: Config, getTensor: boolean =
   }
   if (input instanceof tf.Tensor) { // if input is tensor use as-is without filters but correct shape as needed
     let tensor: Tensor | null = null;
-    if ((input as Tensor)['isDisposedInternal']) throw new Error('input error: attempted to use tensor but it is disposed');
+    if (input['isDisposedInternal']) throw new Error('input error: attempted to use tensor but it is disposed');
     if (!(input as Tensor).shape) throw new Error('input error: attempted to use tensor without a shape');
     if ((input as Tensor).shape.length === 3) { // [height, width, 3 || 4]
       if ((input as Tensor).shape[2] === 3) { // [height, width, 3] so add batch
         tensor = tf.expandDims(input, 0);
       } else if ((input as Tensor).shape[2] === 4) { // [height, width, 4] so strip alpha and add batch
-        const rgb = tf.slice3d(input, [0, 0, 0], [-1, -1, 3]);
+        const rgb = tf.slice3d(input as Tensor3D, [0, 0, 0], [-1, -1, 3]);
         tensor = tf.expandDims(rgb, 0);
         tf.dispose(rgb);
       }
@@ -102,7 +103,7 @@ export async function process(input: Input, config: Config, getTensor: boolean =
       if ((input as Tensor).shape[3] === 3) { // [1, width, height, 3] just clone
         tensor = tf.clone(input);
       } else if ((input as Tensor).shape[3] === 4) { // [1, width, height, 4] so strip alpha
-        tensor = tf.slice4d(input, [0, 0, 0, 0], [-1, -1, -1, 3]);
+        tensor = tf.slice4d(input as Tensor4D, [0, 0, 0, 0], [-1, -1, -1, 3]);
       }
     }
     // at the end shape must be [1, height, width, 3]
@@ -112,7 +113,7 @@ export async function process(input: Input, config: Config, getTensor: boolean =
       tf.dispose(tensor);
       tensor = cast;
     }
-    return { tensor, canvas: (config.filter.return ? outCanvas : null) };
+    return { tensor: tensor as Tensor4D, canvas: (config.filter.return ? outCanvas : null) };
   }
   // check if resizing will be needed
   if (typeof input['readyState'] !== 'undefined' && (input as HTMLMediaElement).readyState <= 2) {
@@ -204,7 +205,7 @@ export async function process(input: Input, config: Config, getTensor: boolean =
   let depth = 3;
   if ((typeof ImageData !== 'undefined' && input instanceof ImageData) || ((input as ImageData).data && (input as ImageData).width && (input as ImageData).height)) { // if input is imagedata, just use it
     if (env.browser && tf.browser) {
-      pixels = tf.browser ? tf.browser.fromPixels(input) : null;
+      pixels = tf.browser ? tf.browser.fromPixels(input as ImageData) : null;
     } else {
       depth = (input as ImageData).data.length / (input as ImageData).height / (input as ImageData).width;
       // const arr = Uint8Array.from(input['data']);
@@ -215,10 +216,10 @@ export async function process(input: Input, config: Config, getTensor: boolean =
     if (!tmpCanvas || (outCanvas.width !== tmpCanvas.width) || (outCanvas.height !== tmpCanvas.height)) tmpCanvas = canvas(outCanvas.width, outCanvas.height); // init output canvas
     if (tf.browser && env.browser) {
       if (config.backend === 'webgl' || config.backend === 'humangl' || config.backend === 'webgpu') {
-        pixels = tf.browser.fromPixels(outCanvas); // safe to reuse since both backend and context are gl based
+        pixels = tf.browser.fromPixels(outCanvas as HTMLCanvasElement); // safe to reuse since both backend and context are gl based
       } else {
         tmpCanvas = copy(outCanvas); // cannot use output canvas as it already has gl context so we do a silly one more canvas
-        pixels = tf.browser.fromPixels(tmpCanvas);
+        pixels = tf.browser.fromPixels(tmpCanvas as HTMLCanvasElement);
       }
     } else {
       const tempCanvas = copy(outCanvas); // cannot use output canvas as it already has gl context so we do a silly one more canvas
@@ -238,7 +239,7 @@ export async function process(input: Input, config: Config, getTensor: boolean =
   const casted: Tensor = tf.cast(pixels, 'float32');
   const tensor: Tensor = config.filter.equalization ? await enhance.histogramEqualization(casted) : tf.expandDims(casted, 0);
   tf.dispose([pixels, casted]);
-  return { tensor, canvas: (config.filter.return ? outCanvas : null) };
+  return { tensor: tensor as Tensor4D, canvas: (config.filter.return ? outCanvas : null) };
 }
 
 /*
@@ -317,7 +318,7 @@ export async function compare(config: Partial<Config>, input1: Tensor, input2: T
     return 0;
   }
   t.input1 = tf.clone(input1);
-  t.input2 = (input1.shape[1] !== input2.shape[1] || input1.shape[2] !== input2.shape[2]) ? tf.image.resizeBilinear(input2, [input1.shape[1], input1.shape[2]]) : tf.clone(input2);
+  t.input2 = (input1.shape[1] !== input2.shape[1] || input1.shape[2] !== input2.shape[2]) ? tf.image.resizeBilinear(input2 as Tensor3D, [input1.shape[1], input1.shape[2]]) : tf.clone(input2);
   t.diff = tf.sub(t.input1, t.input2);
   t.squared = tf.mul(t.diff, t.diff);
   t.sum = tf.sum(t.squared);
diff --git a/src/object/centernet.ts b/src/object/centernet.ts
index 908ad58e..de98b798 100644
--- a/src/object/centernet.ts
+++ b/src/object/centernet.ts
@@ -4,12 +4,12 @@
  * Based on: [**NanoDet**](https://github.com/RangiLyu/nanodet)
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log, now } from '../util/util';
-import * as tf from '../../dist/tfjs.esm.js';
 import { loadModel } from '../tfjs/load';
 import { labels } from './labels';
 import type { ObjectResult, ObjectType, Box } from '../result';
-import type { GraphModel, Tensor } from '../tfjs/types';
+import type { GraphModel, Tensor, Tensor1D, Tensor2D, Tensor4D } from '../tfjs/types';
 import type { Config } from '../config';
 import { env } from '../util/env';
 
@@ -36,13 +36,13 @@ async function process(res: Tensor | null, outputShape: [number, number], config
   const results: ObjectResult[] = [];
   const detections = await res.array() as number[][][];
   t.squeeze = tf.squeeze(res);
-  const arr = tf.split(t.squeeze, 6, 1) as Tensor[]; // x1, y1, x2, y2, score, class
+  const arr = tf.split(t.squeeze, 6, 1); // x1, y1, x2, y2, score, class
   t.stack = tf.stack([arr[1], arr[0], arr[3], arr[2]], 1); // reorder dims as tf.nms expects y, x
   t.boxes = tf.squeeze(t.stack);
   t.scores = tf.squeeze(arr[4]);
   t.classes = tf.squeeze(arr[5]);
   tf.dispose([res, ...arr]);
-  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes, t.scores, config.object.maxDetected, config.object.iouThreshold, (config.object.minConfidence || 0));
+  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes as Tensor2D, t.scores as Tensor1D, config.object.maxDetected || 0, config.object.iouThreshold, (config.object.minConfidence || 0));
   const nms = await t.nms.data();
   let i = 0;
   for (const id of Array.from(nms)) {
@@ -72,7 +72,7 @@ async function process(res: Tensor | null, outputShape: [number, number], config
   return results;
 }
 
-export async function predict(input: Tensor, config: Config): Promise<ObjectResult[]> {
+export async function predict(input: Tensor4D, config: Config): Promise<ObjectResult[]> {
   if (!model?.['executor']) return [];
   const skipTime = (config.object.skipTime || 0) > (now() - lastTime);
   const skipFrame = skipped < (config.object.skipFrames || 0);
diff --git a/src/object/nanodet.ts b/src/object/nanodet.ts
index be418f04..d8863edf 100644
--- a/src/object/nanodet.ts
+++ b/src/object/nanodet.ts
@@ -4,13 +4,13 @@
  * Based on: [**MB3-CenterNet**](https://github.com/610265158/mobilenetv3_centernet)
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log, now } from '../util/util';
-import * as tf from '../../dist/tfjs.esm.js';
 import { loadModel } from '../tfjs/load';
 import { constants } from '../tfjs/constants';
 import { labels } from './labels';
 import type { ObjectResult, ObjectType, Box } from '../result';
-import type { GraphModel, Tensor } from '../tfjs/types';
+import type { GraphModel, Tensor, Tensor2D, Tensor4D } from '../tfjs/types';
 import type { Config } from '../config';
 import { env } from '../util/env';
 
@@ -39,14 +39,14 @@ async function process(res: Tensor[], outputShape: [number, number], config: Con
     // find scores, boxes, classes
     const baseSize = strideSize * 13; // 13x13=169, 26x26=676, 52x52=2704
     // find boxes and scores output depending on stride
-    const scoresT = tf.squeeze(res.find((a: Tensor) => (a.shape[1] === (baseSize ** 2) && (a.shape[2] || 0) === labels.length)));
+    const scoresT = tf.squeeze(res.find((a) => (a.shape[1] === (baseSize ** 2) && (a.shape[2] || 0) === labels.length)) as Tensor2D);
     const scores = await scoresT.array(); // optionally use exponential scores or just as-is
-    const featuresT = tf.squeeze(res.find((a: Tensor) => (a.shape[1] === (baseSize ** 2) && (a.shape[2] || 0) < labels.length)));
-    const boxesMaxT = featuresT.reshape([-1, 4, featuresT.shape[1] / 4]); // reshape [output] to [4, output / 4] where number is number of different features inside each stride
-    const boxIdxT = boxesMaxT.argMax(2); // what we need is indexes of features with highest scores, not values itself
+    const featuresT = tf.squeeze(res.find((a) => (a.shape[1] === (baseSize ** 2) && (a.shape[2] || 0) < labels.length)) as Tensor2D);
+    const boxesMaxT = tf.reshape(featuresT, [-1, 4, (featuresT.shape?.[1] || 0) / 4]); // reshape [output] to [4, output / 4] where number is number of different features inside each stride
+    const boxIdxT = tf.argMax(boxesMaxT, 2); // what we need is indexes of features with highest scores, not values itself
     const boxIdx = await boxIdxT.array(); // what we need is indexes of features with highest scores, not values itself
     for (let i = 0; i < scoresT.shape[0]; i++) { // total strides (x * y matrix)
-      for (let j = 0; j < scoresT.shape[1]; j++) { // one score for each class
+      for (let j = 0; j < (scoresT.shape?.[1] || 0); j++) { // one score for each class
         const score = scores[i][j]; // get score for current position
         if (score > (config.object.minConfidence || 0) && j !== 61) {
           const cx = (0.5 + Math.trunc(i % baseSize)) / baseSize; // center.x normalized to range 0..1
@@ -92,8 +92,8 @@ async function process(res: Tensor[], outputShape: [number, number], config: Con
   const nmsScores = results.map((a) => a.score);
   let nmsIdx: number[] = [];
   if (nmsBoxes && nmsBoxes.length > 0) {
-    const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxDetected, config.object.iouThreshold, config.object.minConfidence);
-    nmsIdx = await nms.data();
+    const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxDetected || 0, config.object.iouThreshold, config.object.minConfidence);
+    nmsIdx = Array.from(await nms.data());
     tf.dispose(nms);
   }
 
@@ -105,7 +105,7 @@ async function process(res: Tensor[], outputShape: [number, number], config: Con
   return results;
 }
 
-export async function predict(image: Tensor, config: Config): Promise<ObjectResult[]> {
+export async function predict(image: Tensor4D, config: Config): Promise<ObjectResult[]> {
   if (!model?.['executor']) return [];
   const skipTime = (config.object.skipTime || 0) > (now() - lastTime);
   const skipFrame = skipped < (config.object.skipFrames || 0);
diff --git a/src/segmentation/meet.ts b/src/segmentation/meet.ts
index 1a2e95ee..ff56a6b7 100644
--- a/src/segmentation/meet.ts
+++ b/src/segmentation/meet.ts
@@ -5,11 +5,11 @@
  * - [**MediaPipe Meet**](https://drive.google.com/file/d/1lnP1bRi9CSqQQXUHa13159vLELYDgDu0/preview)
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log } from '../util/util';
-import * as tf from '../../dist/tfjs.esm.js';
 import { loadModel } from '../tfjs/load';
 import { constants } from '../tfjs/constants';
-import type { GraphModel, Tensor } from '../tfjs/types';
+import type { GraphModel, Tensor, Tensor4D } from '../tfjs/types';
 import type { Config } from '../config';
 import { env } from '../util/env';
 
@@ -21,21 +21,21 @@ export async function load(config: Config): Promise<GraphModel> {
   return model;
 }
 
-export async function predict(input: Tensor, config: Config): Promise<Tensor | null> {
+export async function predict(input: Tensor4D, config: Config): Promise<Tensor | null> {
   if (!model) model = await load(config);
   if (!model?.['executor'] || !model?.inputs?.[0].shape) return null; // something is wrong with the model
   const t: Record<string, Tensor> = {};
   t.resize = tf.image.resizeBilinear(input, [model.inputs[0].shape ? model.inputs[0].shape[1] : 0, model.inputs[0].shape ? model.inputs[0].shape[2] : 0], false);
   t.norm = tf.div(t.resize, constants.tf255);
   t.res = model.execute(t.norm) as Tensor;
-  t.squeeze = tf.squeeze(t.res, 0);
+  t.squeeze = tf.squeeze(t.res, [0]);
   // t.softmax = tf.softmax(t.squeeze); // model meet has two channels for fg and bg
   [t.bgRaw, t.fgRaw] = tf.unstack(t.squeeze, 2);
   // t.bg = tf.softmax(t.bgRaw); // we can ignore bg channel
   t.fg = tf.softmax(t.fgRaw);
   t.mul = tf.mul(t.fg, constants.tf255);
   t.expand = tf.expandDims(t.mul, 2);
-  t.output = tf.image.resizeBilinear(t.expand, [input.shape[1], input.shape[2]]);
+  t.output = tf.image.resizeBilinear(t.expand as Tensor4D, [input.shape[1] || 0, input.shape[2] || 0]);
   let rgba: Tensor;
   switch (config.segmentation.mode || 'default') {
     case 'default':
diff --git a/src/segmentation/rvm.ts b/src/segmentation/rvm.ts
index b75891cd..c16db921 100644
--- a/src/segmentation/rvm.ts
+++ b/src/segmentation/rvm.ts
@@ -5,11 +5,11 @@
  * - [**Robust Video Matting**](https://github.com/PeterL1n/RobustVideoMatting)
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log } from '../util/util';
-import * as tf from '../../dist/tfjs.esm.js';
 import { loadModel } from '../tfjs/load';
 import { constants } from '../tfjs/constants';
-import type { GraphModel, Tensor } from '../tfjs/types';
+import type { GraphModel, Tensor, Tensor4D } from '../tfjs/types';
 import type { Config } from '../config';
 import { env } from '../util/env';
 
@@ -37,11 +37,11 @@ export async function load(config: Config): Promise<GraphModel> {
   return model;
 }
 
-const normalize = (r: Tensor) => tf.tidy(() => {
+const normalize = (r: Tensor): Tensor => tf.tidy(() => {
   const squeeze = tf.squeeze(r, ([0]));
   const mul = tf.mul(squeeze, constants.tf255);
   const cast = tf.cast(mul, 'int32');
-  return cast as Tensor;
+  return cast;
 });
 
 function getRGBA(fgr: Tensor | null, pha: Tensor | null): Tensor { // gets rgba // either fgr or pha must be present
@@ -68,13 +68,13 @@ function getState(state: Tensor): Tensor { // gets internal recurrent states
     r.add = tf.add(r.expand, 1);
     r.mul = tf.mul(r.add, 127.5);
     r.cast = tf.cast(r.mul, 'int32');
-    r.tile = tf.tile(r.cast, [1, 1, 3]) as Tensor;
-    r.alpha = tf.fill([r.tile.shape[0] || 0, r.tile.shape[1] || 0, 1], 255, 'int32');
-    return tf.concat([r.tile, r.alpha], -1) as Tensor;
+    r.tile = tf.tile(r.cast, [1, 1, 3]);
+    r.alpha = tf.fill([(r.tile as Tensor).shape[0] || 0, (r.tile as Tensor).shape[1] || 0, 1], 255, 'int32'); // eslint-disable-line @typescript-eslint/no-unnecessary-type-assertion
+    return tf.concat([r.tile, r.alpha], -1);
   });
 }
 
-export async function predict(input: Tensor, config: Config): Promise<Tensor | null> {
+export async function predict(input: Tensor4D, config: Config): Promise<Tensor | null> {
   if (!model) model = await load(config);
   if (!model?.['executor']) return null;
   // const expand = tf.expandDims(input, 0);
diff --git a/src/segmentation/selfie.ts b/src/segmentation/selfie.ts
index addd7e0f..726ca3c2 100644
--- a/src/segmentation/selfie.ts
+++ b/src/segmentation/selfie.ts
@@ -5,11 +5,11 @@
  * - [**MediaPipe Selfie**](https://drive.google.com/file/d/1dCfozqknMa068vVsO2j_1FgZkW_e3VWv/preview)
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log } from '../util/util';
-import * as tf from '../../dist/tfjs.esm.js';
 import { loadModel } from '../tfjs/load';
 import { constants } from '../tfjs/constants';
-import type { GraphModel, Tensor } from '../tfjs/types';
+import type { GraphModel, Tensor, Tensor4D } from '../tfjs/types';
 import type { Config } from '../config';
 import { env } from '../util/env';
 
@@ -21,15 +21,15 @@ export async function load(config: Config): Promise<GraphModel> {
   return model;
 }
 
-export async function predict(input: Tensor, config: Config): Promise<Tensor | null> {
+export async function predict(input: Tensor4D, config: Config): Promise<Tensor | null> {
   if (!model) model = await load(config);
   if (!model?.['executor'] || !model?.inputs?.[0].shape) return null; // something is wrong with the model
   const t: Record<string, Tensor> = {};
   t.resize = tf.image.resizeBilinear(input, [model.inputs[0].shape ? model.inputs[0].shape[1] : 0, model.inputs[0].shape ? model.inputs[0].shape[2] : 0], false);
   t.norm = tf.div(t.resize, constants.tf255);
   t.res = model.execute(t.norm) as Tensor;
-  t.squeeze = tf.squeeze(t.res, 0); // meet.shape:[1,256,256,1], selfie.shape:[1,144,256,2]
-  t.alpha = tf.image.resizeBilinear(t.squeeze, [input.shape[1], input.shape[2]]); // model selfie has a single channel that we can use directly
+  t.squeeze = tf.squeeze(t.res, [0]); // meet.shape:[1,256,256,1], selfie.shape:[1,144,256,2]
+  t.alpha = tf.image.resizeBilinear(t.squeeze as Tensor4D, [input.shape[1] || 0, input.shape[2] || 0]); // model selfie has a single channel that we can use directly
   t.mul = tf.mul(t.alpha, constants.tf255);
   let rgba: Tensor;
   switch (config.segmentation.mode || 'default') {
diff --git a/src/tfjs/backend.ts b/src/tfjs/backend.ts
index 8a9df51f..cdbc4356 100644
--- a/src/tfjs/backend.ts
+++ b/src/tfjs/backend.ts
@@ -1,11 +1,12 @@
 /** TFJS backend initialization and customization */
 
-import type { Human, Config } from '../human';
+import * as tf from 'dist/tfjs.esm.js';
+import type { Human, Config, BackendEnum } from '../human';
 import { log, now } from '../util/util';
 import { env } from '../util/env';
 import * as humangl from './humangl';
-import * as tf from '../../dist/tfjs.esm.js';
 import * as constants from './constants';
+import type { TensorInfo } from './types';
 
 function registerCustomOps(config: Config) {
   const newKernels: string[] = [];
@@ -23,7 +24,7 @@ function registerCustomOps(config: Config) {
     const kernelFloorMod = {
       kernelName: 'FloorMod',
       backendName: tf.getBackend(),
-      kernelFunc: (op) => tf.tidy(() => tf.add(tf.mul(tf.floorDiv(op.inputs.a / op.inputs.b), op.inputs.b), tf.mod(op.inputs.a, op.inputs.b))),
+      kernelFunc: (op) => tf.tidy(() => tf.add(tf.mul(tf.floorDiv(op.inputs.a, op.inputs.b), op.inputs.b), tf.mod(op.inputs.a, op.inputs.b))),
     };
     tf.registerKernel(kernelFloorMod);
     env.kernels.push('floormod');
@@ -55,9 +56,9 @@ function registerCustomOps(config: Config) {
       backendName: tf.getBackend(),
       kernelFunc: (op) => tf.tidy(() => {
         const backend = tf.getBackend();
-        tf.setBackend('cpu');
+        tf.setBackend('cpu'); // eslint-disable-line @typescript-eslint/no-floating-promises
         const t = tf.image.rotateWithOffset(op.inputs.image, op.attrs.radians, op.attrs.fillValue, op.attrs.center);
-        tf.setBackend(backend);
+        tf.setBackend(backend); // eslint-disable-line @typescript-eslint/no-floating-promises
         return t;
       }),
     };
@@ -105,7 +106,7 @@ export async function check(instance: Human, force = false) {
             instance.config.backend = 'webgl';
           } else {
             // @ts-ignore requestAdapterInfo is not in tslib
-            const adapterInfo = 'requestAdapterInfo' in adapter ? await (adapter as GPUAdapter).requestAdapterInfo() : undefined;
+            const adapterInfo = 'requestAdapterInfo' in adapter ? await adapter.requestAdapterInfo() : undefined;
             // if (adapter.features) adapter.features.forEach((feature) => log('webgpu features:', feature));
             log('webgpu adapter info:', adapterInfo);
           }
@@ -130,6 +131,7 @@ export async function check(instance: Human, force = false) {
 
       // customize wasm
       if (instance.config.backend === 'wasm') {
+        // @ts-ignore private property
         if (tf.env().flagRegistry.CANVAS2D_WILL_READ_FREQUENTLY) tf.env().set('CANVAS2D_WILL_READ_FREQUENTLY', true);
         if (instance.config.debug) log('wasm path:', instance.config.wasmPath);
         if (typeof tf.setWasmPaths !== 'undefined') tf.setWasmPaths(instance.config.wasmPath, instance.config.wasmPlatformFetch);
@@ -137,8 +139,8 @@ export async function check(instance: Human, force = false) {
         let mt = false;
         let simd = false;
         try {
-          mt = await tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');
-          simd = await tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');
+          mt = await tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT') as boolean;
+          simd = await tf.env().getAsync('WASM_HAS_SIMD_SUPPORT') as boolean;
           if (instance.config.debug) log(`wasm execution: ${simd ? 'simd' : 'no simd'} ${mt ? 'multithreaded' : 'singlethreaded'}`);
           if (instance.config.debug && !simd) log('warning: wasm simd support is not enabled');
         } catch {
@@ -153,12 +155,15 @@ export async function check(instance: Human, force = false) {
         log('error: cannot set backend:', instance.config.backend, err);
         return false;
       }
+      // @ts-ignore private property
       if (instance.config.debug) defaultFlags = JSON.parse(JSON.stringify(tf.env().flags));
     }
 
     // customize humangl
     if (tf.getBackend() === 'humangl' || tf.getBackend() === 'webgl') {
+      // @ts-ignore private property
       if (tf.env().flagRegistry.WEBGL_USE_SHAPES_UNIFORMS) tf.env().set('WEBGL_USE_SHAPES_UNIFORMS', true); // default=false <https://github.com/tensorflow/tfjs/issues/5205>
+      // @ts-ignore private property
       if (tf.env().flagRegistry.WEBGL_EXP_CONV) tf.env().set('WEBGL_EXP_CONV', true); // default=false <https://github.com/tensorflow/tfjs/issues/6678>
       // if (tf.env().flagRegistry['WEBGL_PACK_DEPTHWISECONV'])  tf.env().set('WEBGL_PACK_DEPTHWISECONV', false); // default=true <https://github.com/tensorflow/tfjs/pull/4909>
       // if (tf.env().flagRegistry.USE_SETTIMEOUTCUSTOM) tf.env().set('USE_SETTIMEOUTCUSTOM', true); // default=false <https://github.com/tensorflow/tfjs/issues/6687>
@@ -178,6 +183,7 @@ export async function check(instance: Human, force = false) {
     }
 
     if (instance.config.debug) {
+      // @ts-ignore private property
       const newFlags = tf.env().flags;
       const updatedFlags = {};
       for (const key of Object.keys(newFlags)) {
@@ -190,14 +196,14 @@ export async function check(instance: Human, force = false) {
     if (instance.config.flags && Object.keys(instance.config.flags).length > 0) {
       if (instance.config.debug) log('flags:', instance.config['flags']);
       for (const [key, val] of Object.entries(instance.config.flags)) {
-        tf.env().set(key, val);
+        tf.env().set(key, val as number | boolean);
       }
     }
 
     tf.enableProdMode();
     constants.init();
     instance.performance.initBackend = Math.trunc(now() - timeStamp);
-    instance.config.backend = tf.getBackend();
+    instance.config.backend = tf.getBackend() as BackendEnum;
     await env.updateBackend(); // update env on backend init
     registerCustomOps(instance.config);
     // await env.updateBackend(); // update env on backend init
@@ -213,11 +219,14 @@ export function fakeOps(kernelNames: string[], config) {
     const kernelConfig = {
       kernelName,
       backendName: config.backend,
-      kernelFunc: () => { if (config.debug) log('kernelFunc', kernelName, config.backend); },
+      kernelFunc: (param): TensorInfo => {
+        if (config.debug) log('kernelFunc', kernelName, config.backend, param);
+        return param?.inputs?.info as TensorInfo;
+      },
       // setupFunc: () => { if (config.debug) log('kernelFunc', kernelName, config.backend); },
       // disposeFunc: () => { if (config.debug) log('kernelFunc', kernelName, config.backend); },
     };
     tf.registerKernel(kernelConfig);
   }
-  env.kernels = tf.getKernelsForBackend(tf.getBackend()).map((kernel) => (kernel.kernelName as string).toLowerCase()); // re-scan registered ops
+  env.kernels = tf.getKernelsForBackend(tf.getBackend()).map((kernel) => kernel.kernelName.toLowerCase()); // re-scan registered ops
 }
diff --git a/src/tfjs/constants.ts b/src/tfjs/constants.ts
index 68957282..7aed8eeb 100644
--- a/src/tfjs/constants.ts
+++ b/src/tfjs/constants.ts
@@ -1,4 +1,4 @@
-import * as tf from '../../dist/tfjs.esm.js';
+import * as tf from 'dist/tfjs.esm.js';
 import type { Tensor } from './types';
 
 export const constants: Record<string, Tensor | number | number[]> = {
diff --git a/src/tfjs/humangl.ts b/src/tfjs/humangl.ts
index 31f04831..3a74d496 100644
--- a/src/tfjs/humangl.ts
+++ b/src/tfjs/humangl.ts
@@ -1,11 +1,12 @@
 /** TFJS custom backend registration */
 
+import * as tf from 'dist/tfjs.esm.js';
 import type { Human } from '../human';
 import { log } from '../util/util';
-import * as tf from '../../dist/tfjs.esm.js';
 import * as image from '../image/image';
 import * as models from '../models';
 import type { AnyCanvas } from '../exports';
+import type { MathBackendWebGL } from './types';
 // import { env } from '../env';
 
 export const config = {
@@ -120,13 +121,15 @@ export function register(instance: Human): void {
       return;
     }
     try {
+      // @ts-ignore private property
       if (tf.env().flagRegistry.WEBGL_VERSION) tf.env().set('WEBGL_VERSION', 2);
     } catch (err) {
       log('humangl error: cannot set WebGL backend flags:', err);
       return;
     }
     extensions();
-    const current = tf.backend().getGPGPUContext ? tf.backend().getGPGPUContext().gl : null;
+    const backend = tf.backend() as MathBackendWebGL;
+    const current = typeof backend['gpgpu'] !== 'undefined' ? backend.getGPGPUContext().gl : null;
     if (current) {
       if (instance.config.debug) log('humangl backend registered:', { webgl: current.getParameter(current.VERSION) as string, renderer: current.getParameter(current.RENDERER) as string });
     } else {
diff --git a/src/tfjs/load.ts b/src/tfjs/load.ts
index db477cb0..4ee2640d 100644
--- a/src/tfjs/load.ts
+++ b/src/tfjs/load.ts
@@ -1,5 +1,5 @@
+import * as tf from 'dist/tfjs.esm.js';
 import { log, join } from '../util/util';
-import * as tf from '../../dist/tfjs.esm.js';
 import type { GraphModel } from './types';
 import type { Config } from '../config';
 import * as modelsDefs from '../../models/models.json';
diff --git a/src/tfjs/long.d.ts b/src/tfjs/long.d.ts
new file mode 100644
index 00000000..52b2b859
--- /dev/null
+++ b/src/tfjs/long.d.ts
@@ -0,0 +1,391 @@
+/* eslint-disable no-use-before-define */
+// Type definitions for long.js 4.0.0
+// Project: https://github.com/dcodeIO/long.js
+// Definitions by: Peter Kooijmans <https://github.com/peterkooijmans>
+// Definitions: https://github.com/DefinitelyTyped/DefinitelyTyped
+// Definitions by: Denis Cappellin <https://github.com/cappellin>
+
+export = Long;
+export as namespace Long;
+
+declare const Long: Long.LongConstructor;
+type Long = Long.Long;
+declare namespace Long {
+  interface LongConstructor {
+    /**
+     * Constructs a 64 bit two's-complement integer, given its low and high 32 bit values as signed integers. See the from* functions below for more convenient ways of constructing Longs.
+     */
+    new(low: number, high?: number, unsigned?: boolean): Long;
+    prototype: Long;
+    /**
+     * Maximum unsigned value.
+     */
+    MAX_UNSIGNED_VALUE: Long;
+
+    /**
+     * Maximum signed value.
+     */
+    MAX_VALUE: Long;
+
+    /**
+     * Minimum signed value.
+     */
+    MIN_VALUE: Long;
+
+    /**
+     * Signed negative one.
+     */
+    NEG_ONE: Long;
+
+    /**
+     * Signed one.
+     */
+    ONE: Long;
+
+    /**
+     * Unsigned one.
+     */
+    UONE: Long;
+
+    /**
+     * Unsigned zero.
+     */
+    UZERO: Long;
+
+    /**
+     * Signed zero
+     */
+    ZERO: Long;
+
+    /**
+     * Returns a Long representing the 64 bit integer that comes by concatenating the given low and high bits. Each is assumed to use 32 bits.
+     */
+    fromBits(lowBits:number, highBits:number, unsigned?:boolean): Long;
+
+    /**
+     * Returns a Long representing the given 32 bit integer value.
+     */
+    fromInt(value: number, unsigned?: boolean): Long;
+
+    /**
+     * Returns a Long representing the given value, provided that it is a finite number. Otherwise, zero is returned.
+     */
+    fromNumber(value: number, unsigned?: boolean): Long;
+
+    /**
+     * Returns a Long representation of the given string, written using the specified radix.
+     */
+    fromString(str: string, unsigned?: boolean | number, radix?: number): Long;
+
+    /**
+     * Creates a Long from its byte representation.
+     */
+    fromBytes(bytes: number[], unsigned?: boolean, le?: boolean): Long;
+
+    /**
+     * Creates a Long from its little endian byte representation.
+     */
+    fromBytesLE(bytes: number[], unsigned?: boolean): Long;
+
+    /**
+     * Creates a Long from its little endian byte representation.
+     */
+    fromBytesBE(bytes: number[], unsigned?: boolean): Long;
+
+    /**
+     * Tests if the specified object is a Long.
+     */
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    isLong(obj: any): obj is Long;
+
+    /**
+     * Converts the specified value to a Long.
+     */
+    fromValue(val: Long | number | string | {low: number, high: number, unsigned: boolean}): Long;
+  }
+  interface Long
+  {
+    /**
+     * The high 32 bits as a signed value.
+     */
+    high: number;
+
+    /**
+     * The low 32 bits as a signed value.
+     */
+    low: number;
+
+    /**
+     * Whether unsigned or not.
+     */
+    unsigned: boolean;
+
+    /**
+     * Returns the sum of this and the specified Long.
+     */
+    add(addend: number | Long | string): Long;
+
+    /**
+     * Returns the bitwise AND of this Long and the specified.
+     */
+    and(other: Long | number | string): Long;
+
+    /**
+     * Compares this Long's value with the specified's.
+     */
+    compare(other: Long | number | string): number;
+
+    /**
+     * Compares this Long's value with the specified's.
+     */
+    comp(other: Long | number | string): number;
+
+    /**
+     * Returns this Long divided by the specified.
+     */
+    divide(divisor: Long | number | string): Long;
+
+    /**
+     * Returns this Long divided by the specified.
+     */
+    div(divisor: Long | number | string): Long;
+
+    /**
+     * Tests if this Long's value equals the specified's.
+     */
+    equals(other: Long | number | string): boolean;
+
+    /**
+     * Tests if this Long's value equals the specified's.
+     */
+    eq(other: Long | number | string): boolean;
+
+    /**
+     * Gets the high 32 bits as a signed integer.
+     */
+    getHighBits(): number;
+
+    /**
+     * Gets the high 32 bits as an unsigned integer.
+     */
+    getHighBitsUnsigned(): number;
+
+    /**
+     * Gets the low 32 bits as a signed integer.
+     */
+    getLowBits(): number;
+
+    /**
+     * Gets the low 32 bits as an unsigned integer.
+     */
+    getLowBitsUnsigned(): number;
+
+    /**
+     * Gets the number of bits needed to represent the absolute value of this Long.
+     */
+    getNumBitsAbs(): number;
+
+    /**
+     * Tests if this Long's value is greater than the specified's.
+     */
+    greaterThan(other: Long | number | string): boolean;
+
+    /**
+     * Tests if this Long's value is greater than the specified's.
+     */
+    gt(other: Long | number | string): boolean;
+
+    /**
+     * Tests if this Long's value is greater than or equal the specified's.
+     */
+    greaterThanOrEqual(other: Long | number | string): boolean;
+
+    /**
+     * Tests if this Long's value is greater than or equal the specified's.
+     */
+    gte(other: Long | number | string): boolean;
+
+    /**
+     * Tests if this Long's value is even.
+     */
+    isEven(): boolean;
+
+    /**
+     * Tests if this Long's value is negative.
+     */
+    isNegative(): boolean;
+
+    /**
+     * Tests if this Long's value is odd.
+     */
+    isOdd(): boolean;
+
+    /**
+     * Tests if this Long's value is positive.
+     */
+    isPositive(): boolean;
+
+    /**
+     * Tests if this Long's value equals zero.
+     */
+    isZero(): boolean;
+
+    /**
+     * Tests if this Long's value is less than the specified's.
+     */
+    lessThan(other: Long | number | string): boolean;
+
+    /**
+     * Tests if this Long's value is less than the specified's.
+     */
+    lt(other: Long | number | string): boolean;
+
+    /**
+     * Tests if this Long's value is less than or equal the specified's.
+     */
+    lessThanOrEqual(other: Long | number | string): boolean;
+
+    /**
+     * Tests if this Long's value is less than or equal the specified's.
+     */
+    lte(other: Long | number | string): boolean;
+
+    /**
+     * Returns this Long modulo the specified.
+     */
+    modulo(other: Long | number | string): Long;
+
+    /**
+     * Returns this Long modulo the specified.
+     */
+    mod(other: Long | number | string): Long;
+
+    /**
+     * Returns the product of this and the specified Long.
+     */
+    multiply(multiplier: Long | number | string): Long;
+
+    /**
+     * Returns the product of this and the specified Long.
+     */
+    mul(multiplier: Long | number | string): Long;
+
+    /**
+     * Negates this Long's value.
+     */
+    negate(): Long;
+
+    /**
+     * Negates this Long's value.
+     */
+    neg(): Long;
+
+    /**
+     * Returns the bitwise NOT of this Long.
+     */
+    not(): Long;
+
+    /**
+     * Tests if this Long's value differs from the specified's.
+     */
+    notEquals(other: Long | number | string): boolean;
+
+    /**
+     * Tests if this Long's value differs from the specified's.
+     */
+    neq(other: Long | number | string): boolean;
+
+    /**
+     * Returns the bitwise OR of this Long and the specified.
+     */
+    or(other: Long | number | string): Long;
+
+    /**
+     * Returns this Long with bits shifted to the left by the given amount.
+     */
+    shiftLeft(numBits: number | Long): Long;
+
+    /**
+     * Returns this Long with bits shifted to the left by the given amount.
+     */
+    shl(numBits: number | Long): Long;
+
+    /**
+     * Returns this Long with bits arithmetically shifted to the right by the given amount.
+     */
+    shiftRight(numBits: number | Long): Long;
+
+    /**
+     * Returns this Long with bits arithmetically shifted to the right by the given amount.
+     */
+    shr(numBits: number | Long): Long;
+
+    /**
+     * Returns this Long with bits logically shifted to the right by the given amount.
+     */
+    shiftRightUnsigned(numBits: number | Long): Long;
+
+    /**
+     * Returns this Long with bits logically shifted to the right by the given amount.
+     */
+    shru(numBits: number | Long): Long;
+
+    /**
+     * Returns the difference of this and the specified Long.
+     */
+    subtract(subtrahend: number | Long | string): Long;
+
+    /**
+     * Returns the difference of this and the specified Long.
+     */
+    sub(subtrahend: number | Long |string): Long;
+
+    /**
+     * Converts the Long to a 32 bit integer, assuming it is a 32 bit integer.
+     */
+    toInt(): number;
+
+    /**
+     * Converts the Long to a the nearest floating-point representation of this value (double, 53 bit mantissa).
+     */
+    toNumber(): number;
+
+    /**
+     * Converts this Long to its byte representation.
+     */
+
+    toBytes(le?: boolean): number[];
+
+    /**
+     * Converts this Long to its little endian byte representation.
+     */
+
+    toBytesLE(): number[];
+
+    /**
+     * Converts this Long to its big endian byte representation.
+     */
+
+    toBytesBE(): number[];
+
+    /**
+     * Converts this Long to signed.
+     */
+    toSigned(): Long;
+
+    /**
+     * Converts the Long to a string written in the specified radix.
+     */
+    toString(radix?: number): string;
+
+    /**
+     * Converts this Long to unsigned.
+     */
+    toUnsigned(): Long;
+
+    /**
+     * Returns the bitwise XOR of this Long and the given one.
+     */
+    xor(other: Long | number | string): Long;
+  }
+}
diff --git a/src/tfjs/tfjs.esm.d.ts b/src/tfjs/tfjs.esm.d.ts
index 9a0eb9c2..1bd2f216 100644
--- a/src/tfjs/tfjs.esm.d.ts
+++ b/src/tfjs/tfjs.esm.d.ts
@@ -12,9 +12,8 @@ export declare const version: {
 
 export * from '@tensorflow/tfjs-core';
 export * from '@tensorflow/tfjs-converter';
-export * from '@tensorflow/tfjs-data';
-export * from '@tensorflow/tfjs-layers';
-export * from '@tensorflow/tfjs-backend-cpu';
+// export * from '@tensorflow/tfjs-data';
+// export * from '@tensorflow/tfjs-layers';
+// export * from '@tensorflow/tfjs-backend-cpu';
 export * from '@tensorflow/tfjs-backend-wasm';
 export * from '@tensorflow/tfjs-backend-webgl';
-export {};
diff --git a/src/tfjs/types.ts b/src/tfjs/types.ts
index 7ad33ea6..e96de15f 100644
--- a/src/tfjs/types.ts
+++ b/src/tfjs/types.ts
@@ -1,18 +1,25 @@
-/** TFJS common types exports */
+/* eslint-disable import/no-extraneous-dependencies */
 
 /**
- * TensorFlow Tensor type
+ * TensorFlow
  * @external
  */
-export type { Tensor, TensorLike, Rank } from '@tensorflow/tfjs-core/dist/index'; // eslint-disable-line import/no-extraneous-dependencies
+export type { version_core } from '@tensorflow/tfjs-core'; // eslint-disable-line camelcase
+export type { image, browser, io } from '@tensorflow/tfjs-core';
+export type { clone, sum, transpose, addN, softmax, tile, cast, unstack, pad, div, split, squeeze, add, mul, sub, stack, sigmoid, argMax, reshape, max, mod, min, floorDiv } from '@tensorflow/tfjs-core';
+export type { slice, slice3d, slice4d, concat, concat2d, expandDims } from '@tensorflow/tfjs-core';
+export type { fill, scalar, tensor2d, zeros, tensor, dispose, tensor1d, tidy, ready, getBackend, registerKernel, engine, env, setBackend, enableProdMode, getKernelsForBackend, findBackend, registerBackend, backend } from '@tensorflow/tfjs-core';
+export type { Tensor, Tensor1D, Tensor2D, Tensor3D, Tensor4D, TensorLike, TensorInfo, DataType, Rank, TensorContainer, TensorContainerObject } from '@tensorflow/tfjs-core';
+export type { loadGraphModel, GraphModel } from '@tensorflow/tfjs-converter';
+export type { setWasmPaths } from '@tensorflow/tfjs-backend-wasm';
+export type { setWebGLContext, GPGPUContext, MathBackendWebGL } from '@tensorflow/tfjs-backend-webgl';
 
-/**
- * TensorFlow GraphModel type
- * @external
- */
-export type { GraphModel } from '@tensorflow/tfjs-converter/dist/index'; // eslint-disable-line import/no-extraneous-dependencies
-
-/** Tensorflow Long type
- * @external long
- */
-// export type { Long } from 'long';
+export declare const version: {
+  'tfjs-core': string;
+  'tfjs-backend-cpu': string;
+  'tfjs-backend-webgl': string;
+  'tfjs-data': string;
+  'tfjs-layers': string;
+  'tfjs-converter': string;
+  tfjs: string;
+};
diff --git a/src/util/env.ts b/src/util/env.ts
index f7940fac..7cc0d402 100644
--- a/src/util/env.ts
+++ b/src/util/env.ts
@@ -1,5 +1,6 @@
-import * as tf from '../../dist/tfjs.esm.js';
+import * as tf from 'dist/tfjs.esm.js';
 import * as image from '../image/image';
+import type { MathBackendWebGL } from '../tfjs/types';
 
 /** Env class that holds detected capabilities */
 export class Env {
@@ -124,14 +125,14 @@ export class Env {
     // analyze backends
     this.backends = Object.keys(tf.engine().registryFactory);
     this.tensorflow = {
-      version: (tf.backend().binding ? tf.backend().binding.TF_Version : undefined),
-      gpu: (tf.backend().binding ? tf.backend().binding.isUsingGpuDevice() : undefined),
+      version: (tf.backend()['binding'] ? tf.backend()['binding'].TF_Version : undefined),
+      gpu: (tf.backend()['binding'] ? tf.backend()['binding'].isUsingGpuDevice() : undefined),
     };
     this.wasm.supported = typeof WebAssembly !== 'undefined';
     this.wasm.backend = this.backends.includes('wasm');
     if (this.wasm.supported && this.wasm.backend && tf.getBackend() === 'wasm') {
-      this.wasm.simd = tf.env().get('WASM_HAS_SIMD_SUPPORT');
-      this.wasm.multithread = tf.env().get('WASM_HAS_MULTITHREAD_SUPPORT');
+      this.wasm.simd = tf.env().get('WASM_HAS_SIMD_SUPPORT') as boolean;
+      this.wasm.multithread = tf.env().get('WASM_HAS_MULTITHREAD_SUPPORT') as boolean;
     }
     const c = image.canvas(100, 100);
     const ctx = c ? c.getContext('webgl2') : undefined; // causes too many gl contexts
@@ -139,7 +140,8 @@ export class Env {
     this.webgl.supported = typeof ctx !== 'undefined';
     this.webgl.backend = this.backends.includes('webgl');
     if (this.webgl.supported && this.webgl.backend && (tf.getBackend() === 'webgl' || tf.getBackend() === 'humangl')) {
-      const gl = tf.backend().gpgpu !== 'undefined' ? await tf.backend().getGPGPUContext().gl : null;
+      const backend = tf.backend() as MathBackendWebGL;
+      const gl = typeof backend['gpgpu'] !== 'undefined' ? backend.getGPGPUContext().gl : null;
       if (gl) {
         this.webgl.version = gl.getParameter(gl.VERSION);
         this.webgl.renderer = gl.getParameter(gl.RENDERER);
@@ -156,7 +158,7 @@ export class Env {
       this.webgpu.supported = false;
     }
     try {
-      this.kernels = tf.getKernelsForBackend(tf.getBackend()).map((kernel) => (kernel.kernelName as string).toLowerCase());
+      this.kernels = tf.getKernelsForBackend(tf.getBackend()).map((kernel) => kernel.kernelName.toLowerCase());
     } catch { /**/ }
   }
 
diff --git a/src/warmup.ts b/src/warmup.ts
index d8115824..ccb9525d 100644
--- a/src/warmup.ts
+++ b/src/warmup.ts
@@ -2,16 +2,16 @@
  * Warmup algorithm that uses embedded images to exercise loaded models for faster future inference
  */
 
+import * as tf from 'dist/tfjs.esm.js';
 import { log, now, mergeDeep } from './util/util';
 import * as sample from './sample';
-import * as tf from '../dist/tfjs.esm.js';
 import * as image from './image/image';
 import * as backend from './tfjs/backend';
 import { env } from './util/env';
 import type { Config } from './config';
 import type { Result } from './result';
 import { Human, models } from './human';
-import type { Tensor } from './exports';
+import type { Tensor, DataType, MathBackendWebGL } from './tfjs/types';
 
 async function warmupBitmap(instance: Human): Promise<Result | undefined> {
   const b64toBlob = (base64: string, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());
@@ -110,10 +110,11 @@ async function runInference(instance: Human) {
 
 /** Runs pre-compile on all loaded models */
 export async function runCompile(instance: Human) {
+  // @ts-ignore private property
   if (!tf.env().flagRegistry.ENGINE_COMPILE_ONLY) return; // tfjs does not support compile-only inference
   const backendType = tf.getBackend();
-  const webGLBackend = tf.backend();
-  if ((backendType !== 'webgl' && backendType !== 'humangl') || !webGLBackend?.checkCompileCompletion) {
+  const webGLBackend = tf.backend() as MathBackendWebGL;
+  if ((backendType !== 'webgl' && backendType !== 'humangl') || !webGLBackend?.['checkCompileCompletion']) {
     // log('compile pass: skip');
     return;
   }
@@ -122,7 +123,7 @@ export async function runCompile(instance: Human) {
   const compiledModels: string[] = [];
   for (const [modelName, model] of Object.entries(instance.models).filter(([key, val]) => (key !== null && val !== null))) {
     const shape = (model.inputs?.[0]?.shape) ? [...model.inputs[0].shape] : [1, 64, 64, 3];
-    const dtype: string = (model.inputs?.[0]?.dtype) ? model.inputs[0].dtype : 'float32';
+    const dtype: DataType = (model.inputs?.[0]?.dtype) ? model.inputs[0].dtype : 'float32';
     for (let dim = 0; dim < shape.length; dim++) {
       if (shape[dim] === -1) shape[dim] = dim === 0 ? 1 : 64; // override batch number and any dynamic dimensions
     }
diff --git a/test/build.log b/test/build.log
index f1817448..99fcb380 100644
--- a/test/build.log
+++ b/test/build.log
@@ -1,40 +1,40 @@
-2022-10-13 09:27:05 DATA:  Build {"name":"@vladmandic/human","version":"2.11.1"} 
-2022-10-13 09:27:05 INFO:  Application: {"name":"@vladmandic/human","version":"2.11.1"} 
-2022-10-13 09:27:05 INFO:  Environment: {"profile":"production","config":".build.json","package":"package.json","tsconfig":true,"eslintrc":true,"git":true} 
-2022-10-13 09:27:05 INFO:  Toolchain: {"build":"0.7.14","esbuild":"0.15.10","typescript":"4.8.4","typedoc":"0.23.16","eslint":"8.25.0"} 
-2022-10-13 09:27:05 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]} 
-2022-10-13 09:27:05 STATE: Clean: {"locations":["dist/*","types/lib/*","typedoc/*"]} 
-2022-10-13 09:27:05 STATE: Compile: {"name":"tfjs/nodejs/cpu","format":"cjs","platform":"node","input":"tfjs/tf-node.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":159,"outputBytes":608} 
-2022-10-13 09:27:05 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":78,"inputBytes":669029,"outputBytes":315176} 
-2022-10-13 09:27:05 STATE: Compile: {"name":"tfjs/nodejs/gpu","format":"cjs","platform":"node","input":"tfjs/tf-node-gpu.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":167,"outputBytes":612} 
-2022-10-13 09:27:05 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":78,"inputBytes":669033,"outputBytes":315180} 
-2022-10-13 09:27:05 STATE: Compile: {"name":"tfjs/nodejs/wasm","format":"cjs","platform":"node","input":"tfjs/tf-node-wasm.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":206,"outputBytes":664} 
-2022-10-13 09:27:05 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":78,"inputBytes":669085,"outputBytes":315230} 
-2022-10-13 09:27:05 STATE: Compile: {"name":"tfjs/browser/version","format":"esm","platform":"browser","input":"tfjs/tf-version.ts","output":"dist/tfjs.version.js","files":1,"inputBytes":1125,"outputBytes":358} 
-2022-10-13 09:27:05 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":1088,"outputBytes":583} 
-2022-10-13 09:27:05 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":78,"inputBytes":669004,"outputBytes":313912} 
-2022-10-13 09:27:05 STATE: Compile: {"name":"tfjs/browser/esm/custom","format":"esm","platform":"browser","input":"tfjs/tf-custom.ts","output":"dist/tfjs.esm.js","files":11,"inputBytes":1265,"outputBytes":2814441} 
-2022-10-13 09:27:05 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":78,"inputBytes":3482862,"outputBytes":1693611} 
-2022-10-13 09:27:05 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":78,"inputBytes":3482862,"outputBytes":3111620} 
-2022-10-13 09:27:10 STATE: Typings: {"input":"src/human.ts","output":"types/lib","files":15} 
-2022-10-13 09:27:12 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":76,"generated":true} 
-2022-10-13 09:27:12 STATE: Compile: {"name":"demo/typescript","format":"esm","platform":"browser","input":"demo/typescript/index.ts","output":"demo/typescript/index.js","files":1,"inputBytes":5684,"outputBytes":2632} 
-2022-10-13 09:27:12 STATE: Compile: {"name":"demo/faceid","format":"esm","platform":"browser","input":"demo/faceid/index.ts","output":"demo/faceid/index.js","files":2,"inputBytes":17155,"outputBytes":9175} 
-2022-10-13 09:27:23 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":114,"errors":0,"warnings":0} 
-2022-10-13 09:27:23 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"} 
-2022-10-13 09:27:23 STATE: Copy: {"input":"tfjs/tfjs.esm.d.ts"} 
-2022-10-13 09:27:23 INFO:  Done... 
-2022-10-13 09:27:24 STATE: API-Extractor: {"succeeeded":true,"errors":0,"warnings":197} 
-2022-10-13 09:27:24 STATE: Filter: {"input":"types/human.d.ts"} 
-2022-10-13 09:27:24 STATE: Link: {"input":"types/human.d.ts"} 
-2022-10-13 09:27:24 INFO:  Analyze models: {"folders":8,"result":"models/models.json"} 
-2022-10-13 09:27:24 STATE: Models {"folder":"./models","models":12} 
-2022-10-13 09:27:24 STATE: Models {"folder":"../human-models/models","models":43} 
-2022-10-13 09:27:24 STATE: Models {"folder":"../blazepose/model/","models":4} 
-2022-10-13 09:27:24 STATE: Models {"folder":"../anti-spoofing/model","models":1} 
-2022-10-13 09:27:24 STATE: Models {"folder":"../efficientpose/models","models":3} 
-2022-10-13 09:27:24 STATE: Models {"folder":"../insightface/models","models":5} 
-2022-10-13 09:27:24 STATE: Models {"folder":"../movenet/models","models":3} 
-2022-10-13 09:27:24 STATE: Models {"folder":"../nanodet/models","models":4} 
-2022-10-13 09:27:24 STATE: Models: {"count":58,"totalSize":386543911} 
-2022-10-13 09:27:24 INFO:  Human Build complete... {"logFile":"test/build.log"} 
+2022-10-16 20:28:16 DATA:  Build {"name":"@vladmandic/human","version":"3.0.0"} 
+2022-10-16 20:28:16 INFO:  Application: {"name":"@vladmandic/human","version":"3.0.0"} 
+2022-10-16 20:28:16 INFO:  Environment: {"profile":"production","config":".build.json","package":"package.json","tsconfig":true,"eslintrc":true,"git":true} 
+2022-10-16 20:28:16 INFO:  Toolchain: {"build":"0.7.14","esbuild":"0.15.11","typescript":"4.8.4","typedoc":"0.23.16","eslint":"8.25.0"} 
+2022-10-16 20:28:16 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]} 
+2022-10-16 20:28:16 STATE: Clean: {"locations":["dist/*","types/*","typedoc/*"]} 
+2022-10-16 20:28:16 STATE: Compile: {"name":"tfjs/nodejs/cpu","format":"cjs","platform":"node","input":"tfjs/tf-node.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":159,"outputBytes":608} 
+2022-10-16 20:28:16 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":78,"inputBytes":671035,"outputBytes":315423} 
+2022-10-16 20:28:16 STATE: Compile: {"name":"tfjs/nodejs/gpu","format":"cjs","platform":"node","input":"tfjs/tf-node-gpu.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":167,"outputBytes":612} 
+2022-10-16 20:28:16 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":78,"inputBytes":671039,"outputBytes":315427} 
+2022-10-16 20:28:16 STATE: Compile: {"name":"tfjs/nodejs/wasm","format":"cjs","platform":"node","input":"tfjs/tf-node-wasm.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":206,"outputBytes":664} 
+2022-10-16 20:28:16 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":78,"inputBytes":671091,"outputBytes":315477} 
+2022-10-16 20:28:16 STATE: Compile: {"name":"tfjs/browser/version","format":"esm","platform":"browser","input":"tfjs/tf-version.ts","output":"dist/tfjs.version.js","files":1,"inputBytes":1125,"outputBytes":351} 
+2022-10-16 20:28:16 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":1081,"outputBytes":576} 
+2022-10-16 20:28:16 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":78,"inputBytes":671003,"outputBytes":314166} 
+2022-10-16 20:28:17 STATE: Compile: {"name":"tfjs/browser/esm/custom","format":"esm","platform":"browser","input":"tfjs/tf-custom.ts","output":"dist/tfjs.esm.js","files":11,"inputBytes":1354,"outputBytes":2868616} 
+2022-10-16 20:28:17 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":78,"inputBytes":3539043,"outputBytes":1717157} 
+2022-10-16 20:28:17 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":78,"inputBytes":3539043,"outputBytes":3175031} 
+2022-10-16 20:28:27 STATE: Typings: {"input":"src/human.ts","output":"types/lib","files":15} 
+2022-10-16 20:28:29 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":76,"generated":true} 
+2022-10-16 20:28:29 STATE: Compile: {"name":"demo/typescript","format":"esm","platform":"browser","input":"demo/typescript/index.ts","output":"demo/typescript/index.js","files":1,"inputBytes":5672,"outputBytes":2632} 
+2022-10-16 20:28:29 STATE: Compile: {"name":"demo/faceid","format":"esm","platform":"browser","input":"demo/faceid/index.ts","output":"demo/faceid/index.js","files":2,"inputBytes":17134,"outputBytes":9181} 
+2022-10-16 20:28:39 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":115,"errors":0,"warnings":0} 
+2022-10-16 20:28:39 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"} 
+2022-10-16 20:28:39 STATE: Copy: {"input":"src/tfjs/tfjs.esm.d.ts","output":"dist/tfjs.esm.d.ts"} 
+2022-10-16 20:28:39 INFO:  Done... 
+2022-10-16 20:28:39 STATE: API-Extractor: {"succeeeded":true,"errors":0,"warnings":195} 
+2022-10-16 20:28:39 STATE: Filter: {"input":"types/human.d.ts"} 
+2022-10-16 20:28:39 STATE: Link: {"input":"types/human.d.ts"} 
+2022-10-16 20:28:39 INFO:  Analyze models: {"folders":8,"result":"models/models.json"} 
+2022-10-16 20:28:39 STATE: Models {"folder":"./models","models":12} 
+2022-10-16 20:28:39 STATE: Models {"folder":"../human-models/models","models":43} 
+2022-10-16 20:28:39 STATE: Models {"folder":"../blazepose/model/","models":4} 
+2022-10-16 20:28:39 STATE: Models {"folder":"../anti-spoofing/model","models":1} 
+2022-10-16 20:28:39 STATE: Models {"folder":"../efficientpose/models","models":3} 
+2022-10-16 20:28:39 STATE: Models {"folder":"../insightface/models","models":5} 
+2022-10-16 20:28:39 STATE: Models {"folder":"../movenet/models","models":3} 
+2022-10-16 20:28:39 STATE: Models {"folder":"../nanodet/models","models":4} 
+2022-10-16 20:28:40 STATE: Models: {"count":58,"totalSize":386543911} 
+2022-10-16 20:28:40 INFO:  Human Build complete... {"logFile":"test/build.log"} 
diff --git a/test/test.log b/test/test.log
index 6e2ac25a..1ab4e80b 100644
--- a/test/test.log
+++ b/test/test.log
@@ -1,1002 +1,703 @@
-2022-10-13 09:27:28 INFO:  @vladmandic/human version 2.11.1 
-2022-10-13 09:27:28 INFO:  User: vlado Platform: linux Arch: x64 Node: v18.10.0 
-2022-10-13 09:27:28 INFO:  demos: [{"cmd":"../demo/nodejs/node.js","args":[]},{"cmd":"../demo/nodejs/node-simple.js","args":[]},{"cmd":"../demo/nodejs/node-fetch.js","args":[]},{"cmd":"../demo/nodejs/node-event.js","args":["samples/in/ai-body.jpg"]},{"cmd":"../demo/nodejs/node-similarity.js","args":["samples/in/ai-face.jpg","samples/in/ai-upper.jpg"]},{"cmd":"../demo/nodejs/node-canvas.js","args":["samples/in/ai-body.jpg","samples/out/ai-body.jpg"]},{"cmd":"../demo/nodejs/process-folder.js","args":["samples"]},{"cmd":"../demo/multithread/node-multiprocess.js","args":[]},{"cmd":"../demo/facematch/node-match.js","args":[]}] 
-2022-10-13 09:27:28 INFO:  {"cmd":"../demo/nodejs/node.js","args":[]} start 
-2022-10-13 09:27:29 INFO:  {"cmd":"../demo/nodejs/node-simple.js","args":[]} start 
-2022-10-13 09:27:30 INFO:  {"cmd":"../demo/nodejs/node-fetch.js","args":[]} start 
-2022-10-13 09:27:32 INFO:  {"cmd":"../demo/nodejs/node-event.js","args":["samples/in/ai-body.jpg"]} start 
-2022-10-13 09:27:33 INFO:  {"cmd":"../demo/nodejs/node-similarity.js","args":["samples/in/ai-face.jpg","samples/in/ai-upper.jpg"]} start 
-2022-10-13 09:27:34 INFO:  {"cmd":"../demo/nodejs/node-canvas.js","args":["samples/in/ai-body.jpg","samples/out/ai-body.jpg"]} start 
-2022-10-13 09:27:35 INFO:  {"cmd":"../demo/nodejs/process-folder.js","args":["samples"]} start 
-2022-10-13 09:27:37 INFO:  {"cmd":"../demo/multithread/node-multiprocess.js","args":[]} start 
-2022-10-13 09:27:50 INFO:  {"cmd":"../demo/facematch/node-match.js","args":[]} start 
-2022-10-13 09:27:52 INFO:  tests: ["test-node-load.js","test-node-gear.js","test-backend-node.js","test-backend-node-gpu.js","test-backend-node-wasm.js"] 
-2022-10-13 09:27:52 INFO:  
-2022-10-13 09:27:52 INFO:  test-node-load.js start 
-2022-10-13 09:27:52 INFO:  test-node-load.js load start {"human":"2.11.1","tf":"3.21.0","progress":0} 
-2022-10-13 09:27:52 DATA:  test-node-load.js load interval {"elapsed":1,"progress":0} 
-2022-10-13 09:27:52 DATA:  test-node-load.js load interval {"elapsed":11,"progress":0} 
-2022-10-13 09:27:52 DATA:  test-node-load.js load interval {"elapsed":22,"progress":0.05339166087267679} 
-2022-10-13 09:27:52 DATA:  test-node-load.js load interval {"elapsed":33,"progress":0.2135162934143239} 
-2022-10-13 09:27:52 DATA:  test-node-load.js load interval {"elapsed":61,"progress":0.3299591712723044} 
-2022-10-13 09:27:52 DATA:  test-node-load.js load interval {"elapsed":85,"progress":0.5125946867158943} 
-2022-10-13 09:27:52 DATA:  test-node-load.js load interval {"elapsed":98,"progress":0.7259096583739463} 
-2022-10-13 09:27:52 STATE: test-node-load.js passed {"progress":1} 
-2022-10-13 09:27:52 INFO:  test-node-load.js load final {"progress":1} 
-2022-10-13 09:27:53 DATA:  test-node-load.js load interval {"elapsed":504,"progress":1} 
-2022-10-13 09:27:53 INFO:  
-2022-10-13 09:27:53 INFO:  test-node-gear.js start 
-2022-10-13 09:27:53 DATA:  test-node-gear.js input: ["samples/in/ai-face.jpg"] 
-2022-10-13 09:27:54 STATE: test-node-gear.js passed: gear faceres samples/in/ai-face.jpg 
-2022-10-13 09:27:54 DATA:  test-node-gear.js results {"face":0,"model":"faceres","image":"samples/in/ai-face.jpg","age":23.5,"gender":"female","genderScore":0.92} 
-2022-10-13 09:27:54 STATE: test-node-gear.js passed: gear gear samples/in/ai-face.jpg 
-2022-10-13 09:27:54 DATA:  test-node-gear.js results {"face":0,"model":"gear","image":"samples/in/ai-face.jpg","age":23.3,"gender":"female","genderScore":0.51,"race":[{"score":0.93,"race":"white"}]} 
-2022-10-13 09:27:54 STATE: test-node-gear.js passed: gear ssrnet samples/in/ai-face.jpg 
-2022-10-13 09:27:54 DATA:  test-node-gear.js results {"face":0,"model":"ssrnet","image":"samples/in/ai-face.jpg","age":23.4,"gender":"female","genderScore":0.99} 
-2022-10-13 09:27:54 INFO:  
-2022-10-13 09:27:54 INFO:  test-backend-node.js start 
-2022-10-13 09:27:55 INFO:  test-backend-node.js test: configuration validation 
-2022-10-13 09:27:55 STATE: test-backend-node.js passed: configuration default validation [] 
-2022-10-13 09:27:55 STATE: test-backend-node.js passed: configuration invalid validation [{"reason":"unknown property","where":"config.invalid = true"}] 
-2022-10-13 09:27:55 INFO:  test-backend-node.js test: model load 
-2022-10-13 09:27:55 STATE: test-backend-node.js passed: models loaded 25 11 [{"name":"ssrnetage","loaded":false,"url":null},{"name":"gear","loaded":false,"url":null},{"name":"blazeposedetect","loaded":false,"url":null},{"name":"blazepose","loaded":false,"url":null},{"name":"centernet","loaded":true,"url":"file://models/mb3-centernet.json"},{"name":"efficientpose","loaded":false,"url":null},{"name":"mobilefacenet","loaded":false,"url":null},{"name":"insightface","loaded":false,"url":null},{"name":"emotion","loaded":true,"url":"file://models/emotion.json"},{"name":"facedetect","loaded":true,"url":"file://models/blazeface.json"},{"name":"faceiris","loaded":true,"url":"file://models/iris.json"},{"name":"facemesh","loaded":true,"url":"file://models/facemesh.json"},{"name":"faceres","loaded":true,"url":"file://models/faceres.json"},{"name":"ssrnetgender","loaded":false,"url":null},{"name":"handpose","loaded":false,"url":null},{"name":"handskeleton","loaded":true,"url":"file://models/handlandmark-full.json"},{"name":"handtrack","loaded":true,"url":"file://models/handtrack.json"},{"name":"liveness","loaded":true,"url":"file://models/liveness.json"},{"name":"meet","loaded":false,"url":null},{"name":"movenet","loaded":true,"url":"file://models/movenet-lightning.json"},{"name":"nanodet","loaded":false,"url":null},{"name":"posenet","loaded":false,"url":null},{"name":"selfie","loaded":false,"url":null},{"name":"rvm","loaded":false,"url":null},{"name":"antispoof","loaded":true,"url":"file://models/antispoof.json"}] 
-2022-10-13 09:27:55 INFO:  test-backend-node.js memory: {"memory":{"unreliable":true,"numTensors":1785,"numDataBuffers":1785,"numBytes":63247332}} 
-2022-10-13 09:27:55 INFO:  test-backend-node.js state: {"state":{"registeredVariables":{},"nextTapeNodeId":0,"numBytes":63247332,"numTensors":1785,"numStringTensors":0,"numDataBuffers":1785,"gradientDepth":0,"kernelDepth":0,"scopeStack":[],"numDataMovesStack":[],"nextScopeId":0,"tensorInfo":{},"profiling":false,"activeProfile":{"newBytes":0,"newTensors":0,"peakBytes":0,"kernels":[],"result":null,"kernelNames":[]}}} 
-2022-10-13 09:27:55 INFO:  test-backend-node.js test: warmup 
-2022-10-13 09:27:55 STATE: test-backend-node.js passed: create human 
-2022-10-13 09:27:55 INFO:  test-backend-node.js human version: 2.11.1 
-2022-10-13 09:27:55 INFO:  test-backend-node.js platform: linux x64 agent: NodeJS v18.10.0 
-2022-10-13 09:27:55 INFO:  test-backend-node.js tfjs version: 3.21.0 
-2022-10-13 09:27:55 INFO:  test-backend-node.js env: {"browser":false,"node":true,"platform":"linux x64","agent":"NodeJS v18.10.0","backends":["cpu","tensorflow"],"initial":false,"tfjs":{"version":"3.21.0"},"offscreen":false,"perfadd":false,"tensorflow":{"version":"2.9.1","gpu":false},"wasm":{"supported":true,"backend":false},"webgl":{"supported":false,"backend":false},"webgpu":{"supported":false,"backend":false},"cpu":{"flags":[]},"kernels":169} 
-2022-10-13 09:27:55 STATE: test-backend-node.js passed: set backend: tensorflow 
-2022-10-13 09:27:55 STATE: test-backend-node.js tensors 1785 
-2022-10-13 09:27:55 STATE: test-backend-node.js passed: load models 
-2022-10-13 09:27:55 STATE: test-backend-node.js  result: defined models: 25 loaded models: 11 
-2022-10-13 09:27:55 STATE: test-backend-node.js passed: warmup: none default 
-2022-10-13 09:27:55 DATA:  test-backend-node.js  result: face: 0 body: 0 hand: 0 gesture: 0 object: 0 person: 0 {} {} {} 
-2022-10-13 09:27:55 DATA:  test-backend-node.js  result: performance: load: null total: null 
-2022-10-13 09:27:55 STATE: test-backend-node.js passed: warmup none result match 
-2022-10-13 09:27:55 STATE: test-backend-node.js event: image 
-2022-10-13 09:27:55 STATE: test-backend-node.js event: detect 
-2022-10-13 09:27:55 STATE: test-backend-node.js event: warmup 
-2022-10-13 09:27:55 STATE: test-backend-node.js passed: warmup: face default 
-2022-10-13 09:27:55 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.42,"keypoints":4} 
-2022-10-13 09:27:55 DATA:  test-backend-node.js  result: performance: load: null total: 474 
-2022-10-13 09:27:55 STATE: test-backend-node.js passed: warmup face result match 
-2022-10-13 09:27:55 STATE: test-backend-node.js event: image 
-2022-10-13 09:27:56 STATE: test-backend-node.js event: detect 
-2022-10-13 09:27:56 STATE: test-backend-node.js event: warmup 
-2022-10-13 09:27:56 STATE: test-backend-node.js passed: warmup: body default 
-2022-10-13 09:27:56 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-10-13 09:27:56 DATA:  test-backend-node.js  result: performance: load: null total: 367 
-2022-10-13 09:27:56 STATE: test-backend-node.js passed: warmup body result match 
-2022-10-13 09:27:56 STATE: test-backend-node.js details: {"face":{"boxScore":0.92,"faceScore":1,"age":23.7,"gender":"female","genderScore":0.97},"emotion":[{"score":0.63,"emotion":"angry"},{"score":0.22,"emotion":"fear"}],"body":{"score":0.92,"keypoints":17},"hand":{"boxScore":0.52,"fingerScore":0.73,"keypoints":21},"gestures":[{"face":0,"gesture":"facing right"},{"face":0,"gesture":"mouth 10% open"},{"hand":0,"gesture":"pinky forward"},{"hand":0,"gesture":"palm up"},{"hand":0,"gesture":"open palm"},{"iris":0,"gesture":"looking left"},{"iris":0,"gesture":"looking up"}]} 
-2022-10-13 09:27:56 INFO:  test-backend-node.js test: details verification 
-2022-10-13 09:27:56 STATE: test-backend-node.js start default 
-2022-10-13 09:27:56 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-10-13 09:27:56 STATE: test-backend-node.js event: image 
-2022-10-13 09:27:56 STATE: test-backend-node.js event: detect 
-2022-10-13 09:27:56 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg default 
-2022-10-13 09:27:56 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-10-13 09:27:56 DATA:  test-backend-node.js  result: performance: load: null total: 338 
-2022-10-13 09:27:56 STATE: test-backend-node.js passed: details face length 1 
-2022-10-13 09:27:56 STATE: test-backend-node.js passed: details face score 1 0.93 1 
-2022-10-13 09:27:56 STATE: test-backend-node.js passed: details face age/gender 23.7 female 0.97 85.47 
-2022-10-13 09:27:56 STATE: test-backend-node.js passed: details face arrays 4 478 1024 
-2022-10-13 09:27:56 STATE: test-backend-node.js passed: details face emotion 2 {"score":0.59,"emotion":"angry"} 
-2022-10-13 09:27:56 STATE: test-backend-node.js passed: details face anti-spoofing 0.79 
-2022-10-13 09:27:56 STATE: test-backend-node.js passed: details face liveness 0.83 
-2022-10-13 09:27:56 STATE: test-backend-node.js passed: details body length 1 
-2022-10-13 09:27:56 STATE: test-backend-node.js passed: details body 0.92 17 6 
-2022-10-13 09:27:56 STATE: test-backend-node.js passed: details hand length 1 
-2022-10-13 09:27:56 STATE: test-backend-node.js passed: details hand 0.51 0.73 point 
-2022-10-13 09:27:56 STATE: test-backend-node.js passed: details hand arrays 21 5 7 
-2022-10-13 09:27:56 STATE: test-backend-node.js passed: details gesture length 7 
-2022-10-13 09:27:56 STATE: test-backend-node.js passed: details gesture first {"face":0,"gesture":"facing right"} 
-2022-10-13 09:27:56 STATE: test-backend-node.js passed: details object length 1 
-2022-10-13 09:27:56 STATE: test-backend-node.js passed: details object 0.72 person 
-2022-10-13 09:27:56 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1371996928} 
-2022-10-13 09:27:56 STATE: test-backend-node.js event: image 
-2022-10-13 09:27:57 STATE: test-backend-node.js event: detect 
-2022-10-13 09:27:57 STATE: test-backend-node.js passed: tensor shape: [1,1200,1200,4] dtype: float32 
-2022-10-13 09:27:57 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1200,1200,4] {"checksum":1371996928} 
-2022-10-13 09:27:57 STATE: test-backend-node.js event: image 
-2022-10-13 09:27:57 STATE: test-backend-node.js event: detect 
-2022-10-13 09:27:57 STATE: test-backend-node.js passed: tensor shape: [1200,1200,4] dtype: float32 
-2022-10-13 09:27:57 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-10-13 09:27:57 STATE: test-backend-node.js event: image 
-2022-10-13 09:27:58 STATE: test-backend-node.js event: detect 
-2022-10-13 09:27:58 STATE: test-backend-node.js passed: tensor shape: [1,1200,1200,3] dtype: float32 
-2022-10-13 09:27:58 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1200,1200,3] {"checksum":1004796864} 
-2022-10-13 09:27:58 STATE: test-backend-node.js event: image 
-2022-10-13 09:27:58 STATE: test-backend-node.js event: detect 
-2022-10-13 09:27:58 STATE: test-backend-node.js passed: tensor shape: [1200,1200,3] dtype: float32 
-2022-10-13 09:27:58 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1371996871} 
-2022-10-13 09:27:58 STATE: test-backend-node.js event: image 
-2022-10-13 09:27:59 STATE: test-backend-node.js event: detect 
-2022-10-13 09:27:59 STATE: test-backend-node.js passed: tensor shape: [1,1200,1200,4] dtype: int32 
-2022-10-13 09:27:59 INFO:  test-backend-node.js test default 
-2022-10-13 09:27:59 STATE: test-backend-node.js start async 
-2022-10-13 09:27:59 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-10-13 09:27:59 STATE: test-backend-node.js event: image 
-2022-10-13 09:27:59 STATE: test-backend-node.js event: detect 
-2022-10-13 09:27:59 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg async 
-2022-10-13 09:27:59 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-10-13 09:27:59 DATA:  test-backend-node.js  result: performance: load: null total: 313 
-2022-10-13 09:27:59 STATE: test-backend-node.js passed: default result face match 1 female 0.97 
-2022-10-13 09:27:59 INFO:  test-backend-node.js test sync 
-2022-10-13 09:27:59 STATE: test-backend-node.js start sync 
-2022-10-13 09:27:59 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-10-13 09:27:59 STATE: test-backend-node.js event: image 
-2022-10-13 09:28:00 STATE: test-backend-node.js event: detect 
-2022-10-13 09:28:00 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg sync 
-2022-10-13 09:28:00 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:00 DATA:  test-backend-node.js  result: performance: load: null total: 305 
-2022-10-13 09:28:00 STATE: test-backend-node.js passed: default sync 1 female 0.97 
-2022-10-13 09:28:00 INFO:  test-backend-node.js test: image process 
-2022-10-13 09:28:00 STATE: test-backend-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-10-13 09:28:00 STATE: test-backend-node.js passed: image input null [1,256,256,3] 
-2022-10-13 09:28:00 INFO:  test-backend-node.js test: image null 
-2022-10-13 09:28:00 STATE: test-backend-node.js passed: invalid input could not convert input to tensor 
-2022-10-13 09:28:00 INFO:  test-backend-node.js test face similarity 
-2022-10-13 09:28:00 STATE: test-backend-node.js start face similarity 
-2022-10-13 09:28:00 STATE: test-backend-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-10-13 09:28:00 STATE: test-backend-node.js event: image 
-2022-10-13 09:28:00 STATE: test-backend-node.js event: detect 
-2022-10-13 09:28:00 STATE: test-backend-node.js passed: detect: samples/in/ai-face.jpg face similarity 
-2022-10-13 09:28:00 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 6 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":3} 
-2022-10-13 09:28:00 DATA:  test-backend-node.js  result: performance: load: null total: 315 
-2022-10-13 09:28:00 STATE: test-backend-node.js start face similarity 
-2022-10-13 09:28:00 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-10-13 09:28:00 STATE: test-backend-node.js event: image 
-2022-10-13 09:28:01 STATE: test-backend-node.js event: detect 
-2022-10-13 09:28:01 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg face similarity 
-2022-10-13 09:28:01 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:01 DATA:  test-backend-node.js  result: performance: load: null total: 305 
-2022-10-13 09:28:01 STATE: test-backend-node.js start face similarity 
-2022-10-13 09:28:01 STATE: test-backend-node.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289024} 
-2022-10-13 09:28:01 STATE: test-backend-node.js event: image 
-2022-10-13 09:28:01 STATE: test-backend-node.js event: detect 
-2022-10-13 09:28:01 STATE: test-backend-node.js passed: detect: samples/in/ai-upper.jpg face similarity 
-2022-10-13 09:28:01 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 0 gesture: 4 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":7} 
-2022-10-13 09:28:01 DATA:  test-backend-node.js  result: performance: load: null total: 281 
-2022-10-13 09:28:01 STATE: test-backend-node.js passed: face descriptor 
-2022-10-13 09:28:01 STATE: test-backend-node.js passed: face similarity {"similarity":[1,0.44727441595492046,0.556793560189727],"descriptors":[1024,1024,1024]} 
-2022-10-13 09:28:01 INFO:  test-backend-node.js test object 
-2022-10-13 09:28:01 STATE: test-backend-node.js start object 
-2022-10-13 09:28:01 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-10-13 09:28:01 STATE: test-backend-node.js event: image 
-2022-10-13 09:28:01 STATE: test-backend-node.js event: detect 
-2022-10-13 09:28:01 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg object 
-2022-10-13 09:28:01 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:01 DATA:  test-backend-node.js  result: performance: load: null total: 325 
-2022-10-13 09:28:01 STATE: test-backend-node.js passed: centernet 
-2022-10-13 09:28:01 STATE: test-backend-node.js start object 
-2022-10-13 09:28:03 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-10-13 09:28:03 STATE: test-backend-node.js event: image 
-2022-10-13 09:28:03 STATE: test-backend-node.js event: detect 
-2022-10-13 09:28:03 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg object 
-2022-10-13 09:28:03 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 3 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.86,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:03 DATA:  test-backend-node.js  result: performance: load: null total: 308 
-2022-10-13 09:28:03 STATE: test-backend-node.js passed: nanodet 
-2022-10-13 09:28:03 INFO:  test-backend-node.js test sensitive 
-2022-10-13 09:28:03 STATE: test-backend-node.js start sensitive 
-2022-10-13 09:28:03 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-10-13 09:28:03 STATE: test-backend-node.js event: image 
-2022-10-13 09:28:03 STATE: test-backend-node.js event: detect 
-2022-10-13 09:28:03 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg sensitive 
-2022-10-13 09:28:03 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 0 person: 1 {"score":1,"age":23.7,"gender":"female"} {} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:03 DATA:  test-backend-node.js  result: performance: load: null total: 263 
-2022-10-13 09:28:03 STATE: test-backend-node.js passed: sensitive result match 
-2022-10-13 09:28:03 STATE: test-backend-node.js passed: sensitive face result match 
-2022-10-13 09:28:03 STATE: test-backend-node.js passed: sensitive face emotion result [{"score":0.59,"emotion":"angry"},{"score":0.29,"emotion":"fear"}] 
-2022-10-13 09:28:03 STATE: test-backend-node.js passed: sensitive body result match 
-2022-10-13 09:28:03 STATE: test-backend-node.js passed: sensitive hand result match 
-2022-10-13 09:28:03 INFO:  test-backend-node.js test body 
-2022-10-13 09:28:03 STATE: test-backend-node.js start blazepose 
-2022-10-13 09:28:06 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-10-13 09:28:06 STATE: test-backend-node.js event: image 
-2022-10-13 09:28:06 STATE: test-backend-node.js event: detect 
-2022-10-13 09:28:06 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg blazepose 
-2022-10-13 09:28:06 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 0 person: 1 {"score":1,"age":23.7,"gender":"female"} {} {"score":0.99,"keypoints":39} 
-2022-10-13 09:28:06 DATA:  test-backend-node.js  result: performance: load: null total: 354 
-2022-10-13 09:28:06 STATE: test-backend-node.js passed: blazepose 
-2022-10-13 09:28:06 STATE: test-backend-node.js start efficientpose 
-2022-10-13 09:28:07 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-10-13 09:28:07 STATE: test-backend-node.js event: image 
-2022-10-13 09:28:07 STATE: test-backend-node.js event: detect 
-2022-10-13 09:28:07 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg efficientpose 
-2022-10-13 09:28:07 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 0 person: 1 {"score":1,"age":23.7,"gender":"female"} {} {"score":0.75,"keypoints":13} 
-2022-10-13 09:28:07 DATA:  test-backend-node.js  result: performance: load: null total: 319 
-2022-10-13 09:28:07 STATE: test-backend-node.js passed: efficientpose 
-2022-10-13 09:28:07 STATE: test-backend-node.js start posenet 
-2022-10-13 09:28:08 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-10-13 09:28:08 STATE: test-backend-node.js event: image 
-2022-10-13 09:28:08 STATE: test-backend-node.js event: detect 
-2022-10-13 09:28:08 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg posenet 
-2022-10-13 09:28:08 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 0 person: 1 {"score":1,"age":23.7,"gender":"female"} {} {"score":0.96,"keypoints":16} 
-2022-10-13 09:28:08 DATA:  test-backend-node.js  result: performance: load: null total: 259 
-2022-10-13 09:28:08 STATE: test-backend-node.js passed: posenet 
-2022-10-13 09:28:08 STATE: test-backend-node.js start movenet 
-2022-10-13 09:28:08 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-10-13 09:28:08 STATE: test-backend-node.js event: image 
-2022-10-13 09:28:08 STATE: test-backend-node.js event: detect 
-2022-10-13 09:28:08 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg movenet 
-2022-10-13 09:28:08 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 0 person: 1 {"score":1,"age":23.7,"gender":"female"} {} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:08 DATA:  test-backend-node.js  result: performance: load: null total: 267 
-2022-10-13 09:28:08 STATE: test-backend-node.js passed: movenet 
-2022-10-13 09:28:08 INFO:  test-backend-node.js test face matching 
-2022-10-13 09:28:08 STATE: test-backend-node.js passed: face database 40 
-2022-10-13 09:28:08 STATE: test-backend-node.js passed: face match {"first":{"index":4,"similarity":0.7827852251220577}} {"second":{"index":4,"similarity":0.5002052057057577}} {"third":{"index":4,"similarity":0.5401588464054732}} 
-2022-10-13 09:28:08 INFO:  test-backend-node.js test face similarity alternative 
-2022-10-13 09:28:08 STATE: test-backend-node.js start face embeddings 
-2022-10-13 09:28:09 STATE: test-backend-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-10-13 09:28:09 STATE: test-backend-node.js event: image 
-2022-10-13 09:28:09 STATE: test-backend-node.js event: detect 
-2022-10-13 09:28:09 STATE: test-backend-node.js passed: detect: samples/in/ai-face.jpg face embeddings 
-2022-10-13 09:28:09 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 2 gesture: 8 object: 0 person: 1 {"score":1,"age":23.5,"gender":"female"} {} {"score":0.47,"keypoints":3} 
-2022-10-13 09:28:09 DATA:  test-backend-node.js  result: performance: load: null total: 295 
-2022-10-13 09:28:09 STATE: test-backend-node.js passed: mobilefacenet {"embedding":192} 
-2022-10-13 09:28:09 STATE: test-backend-node.js start face embeddings 
-2022-10-13 09:28:10 STATE: test-backend-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-10-13 09:28:10 STATE: test-backend-node.js event: image 
-2022-10-13 09:28:10 STATE: test-backend-node.js event: detect 
-2022-10-13 09:28:10 STATE: test-backend-node.js passed: detect: samples/in/ai-face.jpg face embeddings 
-2022-10-13 09:28:10 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 2 gesture: 8 object: 0 person: 1 {"score":1,"age":23.5,"gender":"female"} {} {"score":0.47,"keypoints":3} 
-2022-10-13 09:28:10 DATA:  test-backend-node.js  result: performance: load: null total: 315 
-2022-10-13 09:28:10 STATE: test-backend-node.js passed: insightface {"embedding":512} 
-2022-10-13 09:28:10 INFO:  test-backend-node.js test face attention 
-2022-10-13 09:28:10 STATE: test-backend-node.js start face attention 
-2022-10-13 09:28:11 STATE: test-backend-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-10-13 09:28:11 STATE: test-backend-node.js event: image 
-2022-10-13 09:28:11 STATE: test-backend-node.js event: detect 
-2022-10-13 09:28:11 STATE: test-backend-node.js passed: detect: samples/in/ai-face.jpg face attention 
-2022-10-13 09:28:11 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 2 gesture: 8 object: 0 person: 1 {"score":1,"age":23.5,"gender":"female"} {} {"score":0.47,"keypoints":3} 
-2022-10-13 09:28:11 DATA:  test-backend-node.js  result: performance: load: null total: 299 
-2022-10-13 09:28:11 STATE: test-backend-node.js passed: face attention 
-2022-10-13 09:28:11 INFO:  test-backend-node.js test detectors 
-2022-10-13 09:28:11 STATE: test-backend-node.js start detectors 
-2022-10-13 09:28:11 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-10-13 09:28:11 STATE: test-backend-node.js event: image 
-2022-10-13 09:28:11 STATE: test-backend-node.js event: detect 
-2022-10-13 09:28:11 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg detectors 
-2022-10-13 09:28:11 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 0 person: 1 {"score":0.93,"gender":"unknown"} {} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:11 DATA:  test-backend-node.js  result: performance: load: null total: 177 
-2022-10-13 09:28:11 STATE: test-backend-node.js passed: detector result face match 
-2022-10-13 09:28:11 STATE: test-backend-node.js passed: detector result hand match 
-2022-10-13 09:28:11 INFO:  test-backend-node.js test: multi-instance 
-2022-10-13 09:28:11 STATE: test-backend-node.js start multi instance 
-2022-10-13 09:28:11 STATE: test-backend-node.js event: image 
-2022-10-13 09:28:11 STATE: test-backend-node.js event: detect 
-2022-10-13 09:28:11 STATE: test-backend-node.js passed: detect: random multi instance 
-2022-10-13 09:28:11 DATA:  test-backend-node.js  result: face: 0 body: 1 hand: 0 gesture: 0 object: 0 person: 0 {} {} {"score":0,"keypoints":0} 
-2022-10-13 09:28:11 DATA:  test-backend-node.js  result: performance: load: null total: 134 
-2022-10-13 09:28:11 INFO:  test-backend-node.js test: first instance 
-2022-10-13 09:28:11 STATE: test-backend-node.js start multi instance 
-2022-10-13 09:28:11 STATE: test-backend-node.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289024} 
-2022-10-13 09:28:12 STATE: test-backend-node.js passed: detect: samples/in/ai-upper.jpg multi instance 
-2022-10-13 09:28:12 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 0 person: 1 {"score":0.96,"gender":"unknown"} {} {"score":0.75,"keypoints":7} 
-2022-10-13 09:28:12 DATA:  test-backend-node.js  result: performance: load: null total: 157 
-2022-10-13 09:28:12 INFO:  test-backend-node.js test: second instance 
-2022-10-13 09:28:12 STATE: test-backend-node.js start multi instance 
-2022-10-13 09:28:12 STATE: test-backend-node.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289024} 
-2022-10-13 09:28:12 STATE: test-backend-node.js passed: detect: samples/in/ai-upper.jpg multi instance 
-2022-10-13 09:28:12 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 0 person: 1 {"score":0.96,"gender":"unknown"} {} {"score":0.75,"keypoints":7} 
-2022-10-13 09:28:12 DATA:  test-backend-node.js  result: performance: load: null total: 141 
-2022-10-13 09:28:12 INFO:  test-backend-node.js test: concurrent 
-2022-10-13 09:28:12 STATE: test-backend-node.js start concurrent 
-2022-10-13 09:28:12 STATE: test-backend-node.js start concurrent 
-2022-10-13 09:28:12 STATE: test-backend-node.js start concurrent 
-2022-10-13 09:28:12 STATE: test-backend-node.js start concurrent 
-2022-10-13 09:28:12 STATE: test-backend-node.js start concurrent 
-2022-10-13 09:28:12 STATE: test-backend-node.js start concurrent 
-2022-10-13 09:28:12 STATE: test-backend-node.js start concurrent 
-2022-10-13 09:28:12 STATE: test-backend-node.js start concurrent 
-2022-10-13 09:28:12 STATE: test-backend-node.js start concurrent 
-2022-10-13 09:28:12 STATE: test-backend-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-10-13 09:28:12 STATE: test-backend-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-10-13 09:28:12 STATE: test-backend-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-10-13 09:28:12 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-10-13 09:28:12 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-10-13 09:28:12 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-10-13 09:28:12 STATE: test-backend-node.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289024} 
-2022-10-13 09:28:13 STATE: test-backend-node.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289024} 
-2022-10-13 09:28:13 STATE: test-backend-node.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289024} 
-2022-10-13 09:28:13 STATE: test-backend-node.js event: image 
-2022-10-13 09:28:13 STATE: test-backend-node.js event: image 
-2022-10-13 09:28:13 STATE: test-backend-node.js event: image 
-2022-10-13 09:28:14 STATE: test-backend-node.js event: detect 
-2022-10-13 09:28:14 STATE: test-backend-node.js passed: detect: samples/in/ai-upper.jpg concurrent 
-2022-10-13 09:28:14 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 0 person: 1 {"score":0.96,"gender":"unknown"} {} {"score":0.75,"keypoints":7} 
-2022-10-13 09:28:14 DATA:  test-backend-node.js  result: performance: load: null total: 1432 
-2022-10-13 09:28:14 STATE: test-backend-node.js passed: detect: samples/in/ai-upper.jpg concurrent 
-2022-10-13 09:28:14 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 0 person: 1 {"score":0.96,"gender":"unknown"} {} {"score":0.75,"keypoints":7} 
-2022-10-13 09:28:14 DATA:  test-backend-node.js  result: performance: load: null total: 1432 
-2022-10-13 09:28:14 STATE: test-backend-node.js passed: detect: samples/in/ai-upper.jpg concurrent 
-2022-10-13 09:28:14 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 0 person: 1 {"score":0.96,"gender":"unknown"} {} {"score":0.75,"keypoints":7} 
-2022-10-13 09:28:14 DATA:  test-backend-node.js  result: performance: load: null total: 1432 
-2022-10-13 09:28:14 STATE: test-backend-node.js event: detect 
-2022-10-13 09:28:14 STATE: test-backend-node.js event: detect 
-2022-10-13 09:28:14 STATE: test-backend-node.js passed: detect: samples/in/ai-face.jpg concurrent 
-2022-10-13 09:28:14 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 0 person: 1 {"score":0.91,"gender":"unknown"} {} {"score":0.47,"keypoints":3} 
-2022-10-13 09:28:14 DATA:  test-backend-node.js  result: performance: load: null total: 1432 
-2022-10-13 09:28:14 STATE: test-backend-node.js passed: detect: samples/in/ai-face.jpg concurrent 
-2022-10-13 09:28:14 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 0 person: 1 {"score":0.91,"gender":"unknown"} {} {"score":0.47,"keypoints":3} 
-2022-10-13 09:28:14 DATA:  test-backend-node.js  result: performance: load: null total: 1432 
-2022-10-13 09:28:14 STATE: test-backend-node.js passed: detect: samples/in/ai-face.jpg concurrent 
-2022-10-13 09:28:14 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 0 person: 1 {"score":0.91,"gender":"unknown"} {} {"score":0.47,"keypoints":3} 
-2022-10-13 09:28:14 DATA:  test-backend-node.js  result: performance: load: null total: 1432 
-2022-10-13 09:28:14 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg concurrent 
-2022-10-13 09:28:14 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 0 person: 1 {"score":0.93,"gender":"unknown"} {} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:14 DATA:  test-backend-node.js  result: performance: load: null total: 1432 
-2022-10-13 09:28:14 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg concurrent 
-2022-10-13 09:28:14 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 0 person: 1 {"score":0.93,"gender":"unknown"} {} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:14 DATA:  test-backend-node.js  result: performance: load: null total: 1432 
-2022-10-13 09:28:14 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg concurrent 
-2022-10-13 09:28:14 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 0 person: 1 {"score":0.93,"gender":"unknown"} {} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:14 DATA:  test-backend-node.js  result: performance: load: null total: 1432 
-2022-10-13 09:28:14 INFO:  test-backend-node.js test: monkey-patch 
-2022-10-13 09:28:14 STATE: test-backend-node.js event: image 
-2022-10-13 09:28:14 STATE: test-backend-node.js event: detect 
-2022-10-13 09:28:14 STATE: test-backend-node.js passed: monkey patch 
-2022-10-13 09:28:15 STATE: test-backend-node.js passed: segmentation [262144] 
-2022-10-13 09:28:15 STATE: test-backend-node.js passeed: equal usage 
-2022-10-13 09:28:15 INFO:  test-backend-node.js test: input compare 
-2022-10-13 09:28:15 STATE: test-backend-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-10-13 09:28:15 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-10-13 09:28:15 STATE: test-backend-node.js passed: image compare 0 23.275441687091504 
-2022-10-13 09:28:15 INFO:  test-backend-node.js events: {"image":29,"detect":29,"warmup":2} 
-2022-10-13 09:28:15 INFO:  test-backend-node.js tensors 4441 
-2022-10-13 09:28:15 INFO:  test-backend-node.js test complete: 20449 ms 
-2022-10-13 09:28:15 INFO:  
-2022-10-13 09:28:15 INFO:  test-backend-node-gpu.js start 
-2022-10-13 09:28:16 INFO:  test-backend-node-gpu.js test: configuration validation 
-2022-10-13 09:28:16 STATE: test-backend-node-gpu.js passed: configuration default validation [] 
-2022-10-13 09:28:16 STATE: test-backend-node-gpu.js passed: configuration invalid validation [{"reason":"unknown property","where":"config.invalid = true"}] 
-2022-10-13 09:28:16 INFO:  test-backend-node-gpu.js test: model load 
-2022-10-13 09:28:16 STATE: test-backend-node-gpu.js passed: models loaded 25 11 [{"name":"ssrnetage","loaded":false,"url":null},{"name":"gear","loaded":false,"url":null},{"name":"blazeposedetect","loaded":false,"url":null},{"name":"blazepose","loaded":false,"url":null},{"name":"centernet","loaded":true,"url":"file://models/mb3-centernet.json"},{"name":"efficientpose","loaded":false,"url":null},{"name":"mobilefacenet","loaded":false,"url":null},{"name":"insightface","loaded":false,"url":null},{"name":"emotion","loaded":true,"url":"file://models/emotion.json"},{"name":"facedetect","loaded":true,"url":"file://models/blazeface.json"},{"name":"faceiris","loaded":true,"url":"file://models/iris.json"},{"name":"facemesh","loaded":true,"url":"file://models/facemesh.json"},{"name":"faceres","loaded":true,"url":"file://models/faceres.json"},{"name":"ssrnetgender","loaded":false,"url":null},{"name":"handpose","loaded":false,"url":null},{"name":"handskeleton","loaded":true,"url":"file://models/handlandmark-full.json"},{"name":"handtrack","loaded":true,"url":"file://models/handtrack.json"},{"name":"liveness","loaded":true,"url":"file://models/liveness.json"},{"name":"meet","loaded":false,"url":null},{"name":"movenet","loaded":true,"url":"file://models/movenet-lightning.json"},{"name":"nanodet","loaded":false,"url":null},{"name":"posenet","loaded":false,"url":null},{"name":"selfie","loaded":false,"url":null},{"name":"rvm","loaded":false,"url":null},{"name":"antispoof","loaded":true,"url":"file://models/antispoof.json"}] 
-2022-10-13 09:28:16 INFO:  test-backend-node-gpu.js memory: {"memory":{"unreliable":true,"numTensors":1785,"numDataBuffers":1785,"numBytes":63247332}} 
-2022-10-13 09:28:16 INFO:  test-backend-node-gpu.js state: {"state":{"registeredVariables":{},"nextTapeNodeId":0,"numBytes":63247332,"numTensors":1785,"numStringTensors":0,"numDataBuffers":1785,"gradientDepth":0,"kernelDepth":0,"scopeStack":[],"numDataMovesStack":[],"nextScopeId":0,"tensorInfo":{},"profiling":false,"activeProfile":{"newBytes":0,"newTensors":0,"peakBytes":0,"kernels":[],"result":null,"kernelNames":[]}}} 
-2022-10-13 09:28:16 INFO:  test-backend-node-gpu.js test: warmup 
-2022-10-13 09:28:16 STATE: test-backend-node-gpu.js passed: create human 
-2022-10-13 09:28:16 INFO:  test-backend-node-gpu.js human version: 2.11.1 
-2022-10-13 09:28:16 INFO:  test-backend-node-gpu.js platform: linux x64 agent: NodeJS v18.10.0 
-2022-10-13 09:28:16 INFO:  test-backend-node-gpu.js tfjs version: 3.21.0 
-2022-10-13 09:28:16 INFO:  test-backend-node-gpu.js env: {"browser":false,"node":true,"platform":"linux x64","agent":"NodeJS v18.10.0","backends":["cpu","tensorflow"],"initial":false,"tfjs":{"version":"3.21.0"},"offscreen":false,"perfadd":false,"tensorflow":{"version":"2.9.1","gpu":true},"wasm":{"supported":true,"backend":false},"webgl":{"supported":false,"backend":false},"webgpu":{"supported":false,"backend":false},"cpu":{"flags":[]},"kernels":169} 
-2022-10-13 09:28:16 STATE: test-backend-node-gpu.js passed: set backend: tensorflow 
-2022-10-13 09:28:16 STATE: test-backend-node-gpu.js tensors 1785 
-2022-10-13 09:28:16 STATE: test-backend-node-gpu.js passed: load models 
-2022-10-13 09:28:16 STATE: test-backend-node-gpu.js  result: defined models: 25 loaded models: 11 
-2022-10-13 09:28:16 STATE: test-backend-node-gpu.js passed: warmup: none default 
-2022-10-13 09:28:16 DATA:  test-backend-node-gpu.js  result: face: 0 body: 0 hand: 0 gesture: 0 object: 0 person: 0 {} {} {} 
-2022-10-13 09:28:16 DATA:  test-backend-node-gpu.js  result: performance: load: null total: null 
-2022-10-13 09:28:16 STATE: test-backend-node-gpu.js passed: warmup none result match 
-2022-10-13 09:28:17 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:21 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:21 STATE: test-backend-node-gpu.js event: warmup 
-2022-10-13 09:28:21 STATE: test-backend-node-gpu.js passed: warmup: face default 
-2022-10-13 09:28:21 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.42,"keypoints":4} 
-2022-10-13 09:28:21 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 4648 
-2022-10-13 09:28:21 STATE: test-backend-node-gpu.js passed: warmup face result match 
-2022-10-13 09:28:21 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js event: warmup 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: warmup: body default 
-2022-10-13 09:28:22 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:22 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 194 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: warmup body result match 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js details: {"face":{"boxScore":0.92,"faceScore":1,"age":23.7,"gender":"female","genderScore":0.97},"emotion":[{"score":0.63,"emotion":"angry"},{"score":0.22,"emotion":"fear"}],"body":{"score":0.92,"keypoints":17},"hand":{"boxScore":0.52,"fingerScore":0.73,"keypoints":21},"gestures":[{"face":0,"gesture":"facing right"},{"face":0,"gesture":"mouth 10% open"},{"hand":0,"gesture":"pinky forward"},{"hand":0,"gesture":"palm up"},{"hand":0,"gesture":"open palm"},{"iris":0,"gesture":"looking left"},{"iris":0,"gesture":"looking up"}]} 
-2022-10-13 09:28:22 INFO:  test-backend-node-gpu.js test: details verification 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js start default 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
-2022-10-13 09:28:22 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:22 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 183 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: details face length 1 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: details face score 1 0.93 1 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: details face age/gender 23.7 female 0.97 85.47 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: details face arrays 4 478 1024 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: details face emotion 2 {"score":0.59,"emotion":"angry"} 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: details face anti-spoofing 0.79 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: details face liveness 0.83 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: details body length 1 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: details body 0.92 17 6 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: details hand length 1 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: details hand 0.51 0.73 point 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: details hand arrays 21 5 7 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: details gesture length 7 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: details gesture first {"face":0,"gesture":"facing right"} 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: details object length 1 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: details object 0.72 person 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1371996928} 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:22 STATE: test-backend-node-gpu.js passed: tensor shape: [1,1200,1200,4] dtype: float32 
-2022-10-13 09:28:23 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1200,1200,4] {"checksum":1371996928} 
-2022-10-13 09:28:23 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:23 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:23 STATE: test-backend-node-gpu.js passed: tensor shape: [1200,1200,4] dtype: float32 
-2022-10-13 09:28:23 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-10-13 09:28:23 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:23 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:23 STATE: test-backend-node-gpu.js passed: tensor shape: [1,1200,1200,3] dtype: float32 
-2022-10-13 09:28:23 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1200,1200,3] {"checksum":1004796928} 
-2022-10-13 09:28:23 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:24 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:24 STATE: test-backend-node-gpu.js passed: tensor shape: [1200,1200,3] dtype: float32 
-2022-10-13 09:28:24 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1371996871} 
-2022-10-13 09:28:24 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:24 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:24 STATE: test-backend-node-gpu.js passed: tensor shape: [1,1200,1200,4] dtype: int32 
-2022-10-13 09:28:24 INFO:  test-backend-node-gpu.js test default 
-2022-10-13 09:28:24 STATE: test-backend-node-gpu.js start async 
-2022-10-13 09:28:24 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-10-13 09:28:24 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:24 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:24 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-body.jpg async 
-2022-10-13 09:28:24 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:24 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 175 
-2022-10-13 09:28:24 STATE: test-backend-node-gpu.js passed: default result face match 1 female 0.97 
-2022-10-13 09:28:24 INFO:  test-backend-node-gpu.js test sync 
-2022-10-13 09:28:24 STATE: test-backend-node-gpu.js start sync 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-body.jpg sync 
-2022-10-13 09:28:25 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:25 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 202 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js passed: default sync 1 female 0.97 
-2022-10-13 09:28:25 INFO:  test-backend-node-gpu.js test: image process 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js passed: image input null [1,256,256,3] 
-2022-10-13 09:28:25 INFO:  test-backend-node-gpu.js test: image null 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js passed: invalid input could not convert input to tensor 
-2022-10-13 09:28:25 INFO:  test-backend-node-gpu.js test face similarity 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js start face similarity 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-face.jpg face similarity 
-2022-10-13 09:28:25 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 6 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":3} 
-2022-10-13 09:28:25 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 201 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js start face similarity 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-body.jpg face similarity 
-2022-10-13 09:28:25 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:25 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 170 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js start face similarity 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289056} 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-upper.jpg face similarity 
-2022-10-13 09:28:25 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 0 gesture: 4 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":7} 
-2022-10-13 09:28:25 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 131 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js passed: face descriptor 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js passed: face similarity {"similarity":[1,0.4475002983522097,0.5570879556505012],"descriptors":[1024,1024,1024]} 
-2022-10-13 09:28:25 INFO:  test-backend-node-gpu.js test object 
-2022-10-13 09:28:25 STATE: test-backend-node-gpu.js start object 
-2022-10-13 09:28:26 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-10-13 09:28:26 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:26 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:26 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-body.jpg object 
-2022-10-13 09:28:26 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:26 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 158 
-2022-10-13 09:28:26 STATE: test-backend-node-gpu.js passed: centernet 
-2022-10-13 09:28:26 STATE: test-backend-node-gpu.js start object 
-2022-10-13 09:28:27 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-10-13 09:28:27 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:28 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:28 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-body.jpg object 
-2022-10-13 09:28:28 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 3 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.86,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:28 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 805 
-2022-10-13 09:28:28 STATE: test-backend-node-gpu.js passed: nanodet 
-2022-10-13 09:28:28 INFO:  test-backend-node-gpu.js test sensitive 
-2022-10-13 09:28:28 STATE: test-backend-node-gpu.js start sensitive 
-2022-10-13 09:28:28 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-10-13 09:28:28 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:28 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:28 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-body.jpg sensitive 
-2022-10-13 09:28:28 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 0 person: 1 {"score":1,"age":23.7,"gender":"female"} {} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:28 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 138 
-2022-10-13 09:28:28 STATE: test-backend-node-gpu.js passed: sensitive result match 
-2022-10-13 09:28:28 STATE: test-backend-node-gpu.js passed: sensitive face result match 
-2022-10-13 09:28:28 STATE: test-backend-node-gpu.js passed: sensitive face emotion result [{"score":0.59,"emotion":"angry"},{"score":0.29,"emotion":"fear"}] 
-2022-10-13 09:28:28 STATE: test-backend-node-gpu.js passed: sensitive body result match 
-2022-10-13 09:28:28 STATE: test-backend-node-gpu.js passed: sensitive hand result match 
-2022-10-13 09:28:28 INFO:  test-backend-node-gpu.js test body 
-2022-10-13 09:28:28 STATE: test-backend-node-gpu.js start blazepose 
-2022-10-13 09:28:30 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-10-13 09:28:30 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:30 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:30 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-body.jpg blazepose 
-2022-10-13 09:28:30 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 0 person: 1 {"score":1,"age":23.7,"gender":"female"} {} {"score":0.99,"keypoints":39} 
-2022-10-13 09:28:30 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 334 
-2022-10-13 09:28:30 STATE: test-backend-node-gpu.js passed: blazepose 
-2022-10-13 09:28:30 STATE: test-backend-node-gpu.js start efficientpose 
-2022-10-13 09:28:30 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-10-13 09:28:30 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:32 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:32 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-body.jpg efficientpose 
-2022-10-13 09:28:32 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 0 person: 1 {"score":1,"age":23.7,"gender":"female"} {} {"score":0.75,"keypoints":13} 
-2022-10-13 09:28:32 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 1203 
-2022-10-13 09:28:32 STATE: test-backend-node-gpu.js passed: efficientpose 
-2022-10-13 09:28:32 STATE: test-backend-node-gpu.js start posenet 
-2022-10-13 09:28:32 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-10-13 09:28:32 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:32 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:32 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-body.jpg posenet 
-2022-10-13 09:28:32 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 0 person: 1 {"score":1,"age":23.7,"gender":"female"} {} {"score":0.96,"keypoints":16} 
-2022-10-13 09:28:32 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 172 
-2022-10-13 09:28:32 STATE: test-backend-node-gpu.js passed: posenet 
-2022-10-13 09:28:32 STATE: test-backend-node-gpu.js start movenet 
-2022-10-13 09:28:33 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-10-13 09:28:33 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:33 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:33 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-body.jpg movenet 
-2022-10-13 09:28:33 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 0 person: 1 {"score":1,"age":23.7,"gender":"female"} {} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:33 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 177 
-2022-10-13 09:28:33 STATE: test-backend-node-gpu.js passed: movenet 
-2022-10-13 09:28:33 INFO:  test-backend-node-gpu.js test face matching 
-2022-10-13 09:28:33 STATE: test-backend-node-gpu.js passed: face database 40 
-2022-10-13 09:28:33 STATE: test-backend-node-gpu.js passed: face match {"first":{"index":4,"similarity":0.7829338043932047}} {"second":{"index":4,"similarity":0.5002928781584631}} {"third":{"index":4,"similarity":0.5402934771672516}} 
-2022-10-13 09:28:33 INFO:  test-backend-node-gpu.js test face similarity alternative 
-2022-10-13 09:28:33 STATE: test-backend-node-gpu.js start face embeddings 
-2022-10-13 09:28:33 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-10-13 09:28:33 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:33 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:33 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-face.jpg face embeddings 
-2022-10-13 09:28:33 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 2 gesture: 8 object: 0 person: 1 {"score":1,"age":23.5,"gender":"female"} {} {"score":0.47,"keypoints":3} 
-2022-10-13 09:28:33 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 259 
-2022-10-13 09:28:33 STATE: test-backend-node-gpu.js passed: mobilefacenet {"embedding":192} 
-2022-10-13 09:28:33 STATE: test-backend-node-gpu.js start face embeddings 
-2022-10-13 09:28:34 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-10-13 09:28:34 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:34 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:34 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-face.jpg face embeddings 
-2022-10-13 09:28:34 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 2 gesture: 8 object: 0 person: 1 {"score":1,"age":23.5,"gender":"female"} {} {"score":0.47,"keypoints":3} 
-2022-10-13 09:28:34 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 268 
-2022-10-13 09:28:34 STATE: test-backend-node-gpu.js passed: insightface {"embedding":512} 
-2022-10-13 09:28:34 INFO:  test-backend-node-gpu.js test face attention 
-2022-10-13 09:28:34 STATE: test-backend-node-gpu.js start face attention 
-2022-10-13 09:28:34 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-10-13 09:28:34 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:35 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:35 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-face.jpg face attention 
-2022-10-13 09:28:35 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 2 gesture: 8 object: 0 person: 1 {"score":1,"age":23.5,"gender":"female"} {} {"score":0.47,"keypoints":3} 
-2022-10-13 09:28:35 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 440 
-2022-10-13 09:28:35 STATE: test-backend-node-gpu.js passed: face attention 
-2022-10-13 09:28:35 INFO:  test-backend-node-gpu.js test detectors 
-2022-10-13 09:28:35 STATE: test-backend-node-gpu.js start detectors 
-2022-10-13 09:28:35 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-10-13 09:28:35 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:35 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:35 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-body.jpg detectors 
-2022-10-13 09:28:35 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 0 person: 1 {"score":0.93,"gender":"unknown"} {} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:35 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 112 
-2022-10-13 09:28:35 STATE: test-backend-node-gpu.js passed: detector result face match 
-2022-10-13 09:28:35 STATE: test-backend-node-gpu.js passed: detector result hand match 
-2022-10-13 09:28:35 INFO:  test-backend-node-gpu.js test: multi-instance 
-2022-10-13 09:28:35 STATE: test-backend-node-gpu.js start multi instance 
-2022-10-13 09:28:35 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:35 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:35 STATE: test-backend-node-gpu.js passed: detect: random multi instance 
-2022-10-13 09:28:35 DATA:  test-backend-node-gpu.js  result: face: 0 body: 1 hand: 0 gesture: 0 object: 0 person: 0 {} {} {"score":0,"keypoints":0} 
-2022-10-13 09:28:35 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 51 
-2022-10-13 09:28:35 INFO:  test-backend-node-gpu.js test: first instance 
-2022-10-13 09:28:35 STATE: test-backend-node-gpu.js start multi instance 
-2022-10-13 09:28:35 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289056} 
-2022-10-13 09:28:35 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-upper.jpg multi instance 
-2022-10-13 09:28:35 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 0 person: 1 {"score":0.96,"gender":"unknown"} {} {"score":0.75,"keypoints":7} 
-2022-10-13 09:28:35 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 79 
-2022-10-13 09:28:35 INFO:  test-backend-node-gpu.js test: second instance 
-2022-10-13 09:28:35 STATE: test-backend-node-gpu.js start multi instance 
-2022-10-13 09:28:36 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289056} 
-2022-10-13 09:28:36 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-upper.jpg multi instance 
-2022-10-13 09:28:36 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 0 person: 1 {"score":0.96,"gender":"unknown"} {} {"score":0.75,"keypoints":7} 
-2022-10-13 09:28:36 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 71 
-2022-10-13 09:28:36 INFO:  test-backend-node-gpu.js test: concurrent 
-2022-10-13 09:28:36 STATE: test-backend-node-gpu.js start concurrent 
-2022-10-13 09:28:36 STATE: test-backend-node-gpu.js start concurrent 
-2022-10-13 09:28:36 STATE: test-backend-node-gpu.js start concurrent 
-2022-10-13 09:28:36 STATE: test-backend-node-gpu.js start concurrent 
-2022-10-13 09:28:36 STATE: test-backend-node-gpu.js start concurrent 
-2022-10-13 09:28:36 STATE: test-backend-node-gpu.js start concurrent 
-2022-10-13 09:28:36 STATE: test-backend-node-gpu.js start concurrent 
-2022-10-13 09:28:36 STATE: test-backend-node-gpu.js start concurrent 
-2022-10-13 09:28:36 STATE: test-backend-node-gpu.js start concurrent 
-2022-10-13 09:28:36 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-10-13 09:28:36 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-10-13 09:28:36 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-10-13 09:28:36 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-10-13 09:28:36 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-10-13 09:28:36 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-10-13 09:28:36 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289056} 
-2022-10-13 09:28:37 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289056} 
-2022-10-13 09:28:37 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289056} 
-2022-10-13 09:28:37 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:37 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:37 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:37 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:37 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-upper.jpg concurrent 
-2022-10-13 09:28:37 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 0 person: 1 {"score":0.96,"gender":"unknown"} {} {"score":0.75,"keypoints":7} 
-2022-10-13 09:28:37 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 658 
-2022-10-13 09:28:37 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-upper.jpg concurrent 
-2022-10-13 09:28:37 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 0 person: 1 {"score":0.96,"gender":"unknown"} {} {"score":0.75,"keypoints":7} 
-2022-10-13 09:28:37 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 658 
-2022-10-13 09:28:37 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-upper.jpg concurrent 
-2022-10-13 09:28:37 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 0 person: 1 {"score":0.96,"gender":"unknown"} {} {"score":0.75,"keypoints":7} 
-2022-10-13 09:28:37 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 658 
-2022-10-13 09:28:37 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:37 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:37 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-face.jpg concurrent 
-2022-10-13 09:28:37 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 0 person: 1 {"score":0.91,"gender":"unknown"} {} {"score":0.47,"keypoints":3} 
-2022-10-13 09:28:37 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 659 
-2022-10-13 09:28:37 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-face.jpg concurrent 
-2022-10-13 09:28:37 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 0 person: 1 {"score":0.91,"gender":"unknown"} {} {"score":0.47,"keypoints":3} 
-2022-10-13 09:28:37 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 659 
-2022-10-13 09:28:37 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-face.jpg concurrent 
-2022-10-13 09:28:37 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 0 person: 1 {"score":0.91,"gender":"unknown"} {} {"score":0.47,"keypoints":3} 
-2022-10-13 09:28:37 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 658 
-2022-10-13 09:28:37 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-body.jpg concurrent 
-2022-10-13 09:28:37 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 0 person: 1 {"score":0.93,"gender":"unknown"} {} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:37 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 659 
-2022-10-13 09:28:37 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-body.jpg concurrent 
-2022-10-13 09:28:37 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 0 person: 1 {"score":0.93,"gender":"unknown"} {} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:37 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 659 
-2022-10-13 09:28:37 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-body.jpg concurrent 
-2022-10-13 09:28:37 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 0 person: 1 {"score":0.93,"gender":"unknown"} {} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:37 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 658 
-2022-10-13 09:28:37 INFO:  test-backend-node-gpu.js test: monkey-patch 
-2022-10-13 09:28:37 STATE: test-backend-node-gpu.js event: image 
-2022-10-13 09:28:37 STATE: test-backend-node-gpu.js event: detect 
-2022-10-13 09:28:37 STATE: test-backend-node-gpu.js passed: monkey patch 
-2022-10-13 09:28:38 STATE: test-backend-node-gpu.js passed: segmentation [262144] 
-2022-10-13 09:28:38 STATE: test-backend-node-gpu.js passeed: equal usage 
-2022-10-13 09:28:38 INFO:  test-backend-node-gpu.js test: input compare 
-2022-10-13 09:28:38 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-10-13 09:28:38 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-10-13 09:28:38 STATE: test-backend-node-gpu.js passed: image compare 0 23.275441687091504 
-2022-10-13 09:28:38 INFO:  test-backend-node-gpu.js events: {"image":29,"detect":29,"warmup":2} 
-2022-10-13 09:28:38 INFO:  test-backend-node-gpu.js tensors 4441 
-2022-10-13 09:28:38 INFO:  test-backend-node-gpu.js test complete: 22272 ms 
-2022-10-13 09:28:40 INFO:  
-2022-10-13 09:28:40 INFO:  test-backend-node-wasm.js start 
-2022-10-13 09:28:40 DATA:  test-backend-node-wasm.js stdout: 2022-10-13 09:28:40 INFO:  { supported: true, backend: true, simd: true, multithread: false } https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@3.21.0/dist/ 
-2022-10-13 09:28:40 STATE: test-backend-node-wasm.js passed: model server: https://vladmandic.github.io/human-models/models/ 
-2022-10-13 09:28:40 INFO:  test-backend-node-wasm.js test: configuration validation 
-2022-10-13 09:28:40 STATE: test-backend-node-wasm.js passed: configuration default validation [] 
-2022-10-13 09:28:40 STATE: test-backend-node-wasm.js passed: configuration invalid validation [{"reason":"unknown property","where":"config.invalid = true"}] 
-2022-10-13 09:28:40 INFO:  test-backend-node-wasm.js test: model load 
-2022-10-13 09:28:42 STATE: test-backend-node-wasm.js passed: models loaded 25 11 [{"name":"ssrnetage","loaded":false,"url":null},{"name":"gear","loaded":false,"url":null},{"name":"blazeposedetect","loaded":false,"url":null},{"name":"blazepose","loaded":false,"url":null},{"name":"centernet","loaded":true,"url":"https://vladmandic.github.io/human-models/models/mb3-centernet.json"},{"name":"efficientpose","loaded":false,"url":null},{"name":"mobilefacenet","loaded":false,"url":null},{"name":"insightface","loaded":false,"url":null},{"name":"emotion","loaded":true,"url":"https://vladmandic.github.io/human-models/models/emotion.json"},{"name":"facedetect","loaded":true,"url":"https://vladmandic.github.io/human-models/models/blazeface.json"},{"name":"faceiris","loaded":true,"url":"https://vladmandic.github.io/human-models/models/iris.json"},{"name":"facemesh","loaded":true,"url":"https://vladmandic.github.io/human-models/models/facemesh.json"},{"name":"faceres","loaded":true,"url":"https://vladmandic.github.io/human-models/models/faceres.json"},{"name":"ssrnetgender","loaded":false,"url":null},{"name":"handpose","loaded":false,"url":null},{"name":"handskeleton","loaded":true,"url":"https://vladmandic.github.io/human-models/models/handlandmark-full.json"},{"name":"handtrack","loaded":true,"url":"https://vladmandic.github.io/human-models/models/handtrack.json"},{"name":"liveness","loaded":true,"url":"https://vladmandic.github.io/human-models/models/liveness.json"},{"name":"meet","loaded":false,"url":null},{"name":"movenet","loaded":true,"url":"https://vladmandic.github.io/human-models/models/movenet-lightning.json"},{"name":"nanodet","loaded":false,"url":null},{"name":"posenet","loaded":false,"url":null},{"name":"selfie","loaded":false,"url":null},{"name":"rvm","loaded":false,"url":null},{"name":"antispoof","loaded":true,"url":"https://vladmandic.github.io/human-models/models/antispoof.json"}] 
-2022-10-13 09:28:42 INFO:  test-backend-node-wasm.js memory: {"memory":{"unreliable":false,"numTensors":1785,"numDataBuffers":1785,"numBytes":63247332}} 
-2022-10-13 09:28:42 INFO:  test-backend-node-wasm.js state: {"state":{"registeredVariables":{},"nextTapeNodeId":0,"numBytes":63247332,"numTensors":1785,"numStringTensors":0,"numDataBuffers":1785,"gradientDepth":0,"kernelDepth":0,"scopeStack":[],"numDataMovesStack":[],"nextScopeId":0,"tensorInfo":{},"profiling":false,"activeProfile":{"newBytes":0,"newTensors":0,"peakBytes":0,"kernels":[],"result":null,"kernelNames":[]}}} 
-2022-10-13 09:28:42 INFO:  test-backend-node-wasm.js test: warmup 
-2022-10-13 09:28:42 STATE: test-backend-node-wasm.js passed: create human 
-2022-10-13 09:28:42 INFO:  test-backend-node-wasm.js human version: 2.11.1 
-2022-10-13 09:28:42 INFO:  test-backend-node-wasm.js platform: linux x64 agent: NodeJS v18.10.0 
-2022-10-13 09:28:42 INFO:  test-backend-node-wasm.js tfjs version: 3.21.0 
-2022-10-13 09:28:42 INFO:  test-backend-node-wasm.js env: {"browser":false,"node":true,"platform":"linux x64","agent":"NodeJS v18.10.0","backends":["cpu","wasm"],"initial":false,"tfjs":{"version":"3.21.0"},"offscreen":false,"perfadd":false,"tensorflow":{},"wasm":{"supported":true,"backend":true,"simd":true,"multithread":false},"webgl":{"supported":false,"backend":false},"webgpu":{"supported":false,"backend":false},"cpu":{"flags":[]},"kernels":126} 
-2022-10-13 09:28:42 STATE: test-backend-node-wasm.js passed: set backend: wasm 
-2022-10-13 09:28:42 STATE: test-backend-node-wasm.js tensors 1785 
-2022-10-13 09:28:42 STATE: test-backend-node-wasm.js passed: load models 
-2022-10-13 09:28:42 STATE: test-backend-node-wasm.js  result: defined models: 25 loaded models: 11 
-2022-10-13 09:28:42 STATE: test-backend-node-wasm.js passed: warmup: none default 
-2022-10-13 09:28:42 DATA:  test-backend-node-wasm.js  result: face: 0 body: 0 hand: 0 gesture: 0 object: 0 person: 0 {} {} {} 
-2022-10-13 09:28:42 DATA:  test-backend-node-wasm.js  result: performance: load: null total: null 
-2022-10-13 09:28:42 STATE: test-backend-node-wasm.js passed: warmup none result match 
-2022-10-13 09:28:42 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:28:43 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:28:43 STATE: test-backend-node-wasm.js event: warmup 
-2022-10-13 09:28:43 STATE: test-backend-node-wasm.js passed: warmup: face default 
-2022-10-13 09:28:43 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 6 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":3} 
-2022-10-13 09:28:43 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 577 
-2022-10-13 09:28:43 STATE: test-backend-node-wasm.js passed: warmup face result match 
-2022-10-13 09:28:43 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:28:43 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:28:43 STATE: test-backend-node-wasm.js event: warmup 
-2022-10-13 09:28:43 STATE: test-backend-node-wasm.js passed: warmup: body default 
-2022-10-13 09:28:43 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:43 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 453 
-2022-10-13 09:28:43 STATE: test-backend-node-wasm.js passed: warmup body result match 
-2022-10-13 09:28:43 STATE: test-backend-node-wasm.js details: {"face":{"boxScore":0.93,"faceScore":1,"age":23.7,"gender":"female","genderScore":0.97},"emotion":[{"score":0.59,"emotion":"angry"},{"score":0.29,"emotion":"fear"}],"body":{"score":0.92,"keypoints":17},"hand":{"boxScore":0.51,"fingerScore":0.73,"keypoints":21},"gestures":[{"face":0,"gesture":"facing right"},{"face":0,"gesture":"mouth 21% open"},{"hand":0,"gesture":"pinky forward"},{"hand":0,"gesture":"palm up"},{"hand":0,"gesture":"open palm"},{"iris":0,"gesture":"looking left"},{"iris":0,"gesture":"looking up"}]} 
-2022-10-13 09:28:43 INFO:  test-backend-node-wasm.js test: details verification 
-2022-10-13 09:28:43 STATE: test-backend-node-wasm.js start default 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
-2022-10-13 09:28:44 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:44 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 372 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js passed: details face length 1 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js passed: details face score 1 0.93 1 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js passed: details face age/gender 23.7 female 0.97 85.47 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js passed: details face arrays 4 478 1024 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js passed: details face emotion 2 {"score":0.59,"emotion":"angry"} 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js passed: details face anti-spoofing 0.79 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js passed: details face liveness 0.83 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js passed: details body length 1 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js passed: details body 0.92 17 6 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js passed: details hand length 1 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js passed: details hand 0.51 0.73 point 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js passed: details hand arrays 21 5 7 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js passed: details gesture length 7 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js passed: details gesture first {"face":0,"gesture":"facing right"} 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js passed: details object length 1 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js passed: details object 0.72 person 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1413675264} 
-2022-10-13 09:28:44 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:28:45 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:28:45 STATE: test-backend-node-wasm.js passed: tensor shape: [1,1200,1200,4] dtype: float32 
-2022-10-13 09:28:45 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1200,1200,4] {"checksum":1413675264} 
-2022-10-13 09:28:45 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:28:45 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:28:45 STATE: test-backend-node-wasm.js passed: tensor shape: [1200,1200,4] dtype: float32 
-2022-10-13 09:28:46 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-10-13 09:28:46 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:28:46 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:28:46 STATE: test-backend-node-wasm.js passed: tensor shape: [1,1200,1200,3] dtype: float32 
-2022-10-13 09:28:46 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1200,1200,3] {"checksum":1038921856} 
-2022-10-13 09:28:46 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:28:47 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:28:47 STATE: test-backend-node-wasm.js passed: tensor shape: [1200,1200,3] dtype: float32 
-2022-10-13 09:28:47 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1371996871} 
-2022-10-13 09:28:47 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:28:47 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:28:47 STATE: test-backend-node-wasm.js passed: tensor shape: [1,1200,1200,4] dtype: int32 
-2022-10-13 09:28:47 INFO:  test-backend-node-wasm.js test default 
-2022-10-13 09:28:47 STATE: test-backend-node-wasm.js start async 
-2022-10-13 09:28:47 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-10-13 09:28:47 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:28:48 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:28:48 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg async 
-2022-10-13 09:28:48 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 8 object: 1 person: 1 {"score":1,"age":29.6,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:48 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 339 
-2022-10-13 09:28:48 STATE: test-backend-node-wasm.js passed: default result face match 1 female 0.97 
-2022-10-13 09:28:48 INFO:  test-backend-node-wasm.js test sync 
-2022-10-13 09:28:48 STATE: test-backend-node-wasm.js start sync 
-2022-10-13 09:28:48 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-10-13 09:28:48 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:28:48 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:28:48 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg sync 
-2022-10-13 09:28:48 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 8 object: 1 person: 1 {"score":1,"age":29.6,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:48 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 343 
-2022-10-13 09:28:48 STATE: test-backend-node-wasm.js passed: default sync 1 female 0.97 
-2022-10-13 09:28:48 INFO:  test-backend-node-wasm.js test: image process 
-2022-10-13 09:28:48 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
-2022-10-13 09:28:48 STATE: test-backend-node-wasm.js passed: image input null [1,256,256,3] 
-2022-10-13 09:28:48 INFO:  test-backend-node-wasm.js test: image null 
-2022-10-13 09:28:48 STATE: test-backend-node-wasm.js passed: invalid input could not convert input to tensor 
-2022-10-13 09:28:48 INFO:  test-backend-node-wasm.js test face similarity 
-2022-10-13 09:28:48 STATE: test-backend-node-wasm.js start face similarity 
-2022-10-13 09:28:48 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
-2022-10-13 09:28:48 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:28:49 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:28:49 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-face.jpg face similarity 
-2022-10-13 09:28:49 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 6 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":3} 
-2022-10-13 09:28:49 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 303 
-2022-10-13 09:28:49 STATE: test-backend-node-wasm.js start face similarity 
-2022-10-13 09:28:49 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-10-13 09:28:49 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:28:49 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:28:49 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg face similarity 
-2022-10-13 09:28:49 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 8 object: 1 person: 1 {"score":1,"age":29.6,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:49 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 327 
-2022-10-13 09:28:49 STATE: test-backend-node-wasm.js start face similarity 
-2022-10-13 09:28:49 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151155104} 
-2022-10-13 09:28:49 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:28:50 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:28:50 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-upper.jpg face similarity 
-2022-10-13 09:28:50 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 0 gesture: 4 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":7} 
-2022-10-13 09:28:50 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 310 
-2022-10-13 09:28:50 STATE: test-backend-node-wasm.js passed: face descriptor 
-2022-10-13 09:28:50 STATE: test-backend-node-wasm.js passed: face similarity {"similarity":[1,0.5266119940661309,0.4858842904087851],"descriptors":[1024,1024,1024]} 
-2022-10-13 09:28:50 INFO:  test-backend-node-wasm.js test object 
-2022-10-13 09:28:50 STATE: test-backend-node-wasm.js start object 
-2022-10-13 09:28:50 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-10-13 09:28:50 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:28:50 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:28:50 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg object 
-2022-10-13 09:28:50 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 8 object: 1 person: 1 {"score":1,"age":29.6,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:50 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 324 
-2022-10-13 09:28:50 STATE: test-backend-node-wasm.js passed: centernet 
-2022-10-13 09:28:50 STATE: test-backend-node-wasm.js start object 
-2022-10-13 09:28:51 WARN:  test-backend-node-wasm.js missing kernel ops {"title":"object","model":"nanodet","url":"https://vladmandic.github.io/human-models/models/nanodet.json","missing":["sparsetodense"],"backkend":"wasm"} 
-2022-10-13 09:28:51 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-10-13 09:28:51 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:28:52 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:28:52 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg object 
-2022-10-13 09:28:52 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 8 object: 0 person: 1 {"score":1,"age":29.6,"gender":"female"} {} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:52 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 241 
-2022-10-13 09:28:52 ERROR: test-backend-node-wasm.js failed: nanodet [] 
-2022-10-13 09:28:52 INFO:  test-backend-node-wasm.js test sensitive 
-2022-10-13 09:28:52 STATE: test-backend-node-wasm.js start sensitive 
-2022-10-13 09:28:52 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-10-13 09:28:52 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:28:52 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:28:52 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg sensitive 
-2022-10-13 09:28:52 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 2 gesture: 10 object: 0 person: 1 {"score":1,"age":29.6,"gender":"female"} {} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:52 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 280 
-2022-10-13 09:28:52 STATE: test-backend-node-wasm.js passed: sensitive result match 
-2022-10-13 09:28:52 STATE: test-backend-node-wasm.js passed: sensitive face result match 
-2022-10-13 09:28:52 STATE: test-backend-node-wasm.js passed: sensitive face emotion result [{"score":0.46,"emotion":"neutral"},{"score":0.24,"emotion":"fear"},{"score":0.17,"emotion":"sad"}] 
-2022-10-13 09:28:52 STATE: test-backend-node-wasm.js passed: sensitive body result match 
-2022-10-13 09:28:52 STATE: test-backend-node-wasm.js passed: sensitive hand result match 
-2022-10-13 09:28:52 INFO:  test-backend-node-wasm.js test body 
-2022-10-13 09:28:52 STATE: test-backend-node-wasm.js start blazepose 
-2022-10-13 09:28:55 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-10-13 09:28:55 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:28:55 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:28:55 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg blazepose 
-2022-10-13 09:28:55 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 2 gesture: 10 object: 0 person: 1 {"score":1,"age":29.6,"gender":"female"} {} {"score":0.99,"keypoints":39} 
-2022-10-13 09:28:55 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 408 
-2022-10-13 09:28:55 STATE: test-backend-node-wasm.js passed: blazepose 
-2022-10-13 09:28:55 STATE: test-backend-node-wasm.js start efficientpose 
-2022-10-13 09:28:56 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-10-13 09:28:56 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:28:57 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:28:57 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg efficientpose 
-2022-10-13 09:28:57 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 2 gesture: 10 object: 0 person: 1 {"score":1,"age":29.6,"gender":"female"} {} {"score":0.75,"keypoints":13} 
-2022-10-13 09:28:57 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 653 
-2022-10-13 09:28:57 STATE: test-backend-node-wasm.js passed: efficientpose 
-2022-10-13 09:28:57 STATE: test-backend-node-wasm.js start posenet 
-2022-10-13 09:28:57 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-10-13 09:28:57 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:28:58 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:28:58 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg posenet 
-2022-10-13 09:28:58 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 2 gesture: 10 object: 0 person: 1 {"score":1,"age":29.6,"gender":"female"} {} {"score":0.96,"keypoints":16} 
-2022-10-13 09:28:58 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 297 
-2022-10-13 09:28:58 STATE: test-backend-node-wasm.js passed: posenet 
-2022-10-13 09:28:58 STATE: test-backend-node-wasm.js start movenet 
-2022-10-13 09:28:58 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-10-13 09:28:58 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:28:58 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:28:58 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg movenet 
-2022-10-13 09:28:58 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 2 gesture: 10 object: 0 person: 1 {"score":1,"age":29.6,"gender":"female"} {} {"score":0.92,"keypoints":17} 
-2022-10-13 09:28:58 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 240 
-2022-10-13 09:28:58 STATE: test-backend-node-wasm.js passed: movenet 
-2022-10-13 09:28:58 INFO:  test-backend-node-wasm.js test face matching 
-2022-10-13 09:28:58 STATE: test-backend-node-wasm.js passed: face database 40 
-2022-10-13 09:28:58 STATE: test-backend-node-wasm.js passed: face match {"first":{"index":4,"similarity":0.7827852754786533}} {"second":{"index":4,"similarity":0.5660821189104794}} {"third":{"index":4,"similarity":0.45074189882665594}} 
-2022-10-13 09:28:58 INFO:  test-backend-node-wasm.js test face similarity alternative 
-2022-10-13 09:28:58 STATE: test-backend-node-wasm.js start face embeddings 
-2022-10-13 09:28:59 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
-2022-10-13 09:28:59 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:28:59 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:28:59 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-face.jpg face embeddings 
-2022-10-13 09:28:59 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 2 gesture: 8 object: 0 person: 1 {"score":1,"age":23.5,"gender":"female"} {} {"score":0.47,"keypoints":3} 
-2022-10-13 09:28:59 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 243 
-2022-10-13 09:28:59 STATE: test-backend-node-wasm.js passed: mobilefacenet {"embedding":192} 
-2022-10-13 09:28:59 STATE: test-backend-node-wasm.js start face embeddings 
-2022-10-13 09:29:00 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
-2022-10-13 09:29:00 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:29:00 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:29:00 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-face.jpg face embeddings 
-2022-10-13 09:29:00 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 2 gesture: 8 object: 0 person: 1 {"score":1,"age":23.5,"gender":"female"} {} {"score":0.47,"keypoints":3} 
-2022-10-13 09:29:00 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 307 
-2022-10-13 09:29:00 STATE: test-backend-node-wasm.js passed: insightface {"embedding":512} 
-2022-10-13 09:29:00 INFO:  test-backend-node-wasm.js test face attention 
-2022-10-13 09:29:00 STATE: test-backend-node-wasm.js start face attention 
-2022-10-13 09:29:01 WARN:  test-backend-node-wasm.js missing kernel ops {"title":"face attention","model":"facemesh","url":"https://vladmandic.github.io/human-models/models/facemesh-attention.json","missing":["atan2"],"backkend":"wasm"} 
-2022-10-13 09:29:01 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
-2022-10-13 09:29:01 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:29:01 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:29:01 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-face.jpg face attention 
-2022-10-13 09:29:01 DATA:  test-backend-node-wasm.js  result: face: 0 body: 1 hand: 1 gesture: 2 object: 0 person: 0 {} {} {"score":0.47,"keypoints":3} 
-2022-10-13 09:29:01 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 124 
-2022-10-13 09:29:01 ERROR: test-backend-node-wasm.js failed: face attention {"annotations":0} 
-2022-10-13 09:29:01 INFO:  test-backend-node-wasm.js test detectors 
-2022-10-13 09:29:01 STATE: test-backend-node-wasm.js start detectors 
-2022-10-13 09:29:01 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-10-13 09:29:01 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:29:01 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:29:01 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg detectors 
-2022-10-13 09:29:01 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 0 person: 1 {"score":0.93,"gender":"unknown"} {} {"score":0.92,"keypoints":17} 
-2022-10-13 09:29:01 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 129 
-2022-10-13 09:29:01 STATE: test-backend-node-wasm.js passed: detector result face match 
-2022-10-13 09:29:01 STATE: test-backend-node-wasm.js passed: detector result hand match 
-2022-10-13 09:29:01 INFO:  test-backend-node-wasm.js test: multi-instance 
-2022-10-13 09:29:01 STATE: test-backend-node-wasm.js start multi instance 
-2022-10-13 09:29:01 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:29:01 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:29:01 STATE: test-backend-node-wasm.js passed: detect: random multi instance 
-2022-10-13 09:29:01 DATA:  test-backend-node-wasm.js  result: face: 0 body: 1 hand: 0 gesture: 0 object: 0 person: 0 {} {} {"score":0,"keypoints":0} 
-2022-10-13 09:29:01 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 102 
-2022-10-13 09:29:01 INFO:  test-backend-node-wasm.js test: first instance 
-2022-10-13 09:29:01 STATE: test-backend-node-wasm.js start multi instance 
-2022-10-13 09:29:01 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151155104} 
-2022-10-13 09:29:02 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-upper.jpg multi instance 
-2022-10-13 09:29:02 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 0 person: 1 {"score":0.96,"gender":"unknown"} {} {"score":0.75,"keypoints":7} 
-2022-10-13 09:29:02 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 116 
-2022-10-13 09:29:02 INFO:  test-backend-node-wasm.js test: second instance 
-2022-10-13 09:29:02 STATE: test-backend-node-wasm.js start multi instance 
-2022-10-13 09:29:02 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151155104} 
-2022-10-13 09:29:02 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-upper.jpg multi instance 
-2022-10-13 09:29:02 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 0 person: 1 {"score":0.96,"gender":"unknown"} {} {"score":0.75,"keypoints":7} 
-2022-10-13 09:29:02 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 115 
-2022-10-13 09:29:02 INFO:  test-backend-node-wasm.js test: concurrent 
-2022-10-13 09:29:02 STATE: test-backend-node-wasm.js start concurrent 
-2022-10-13 09:29:02 STATE: test-backend-node-wasm.js start concurrent 
-2022-10-13 09:29:02 STATE: test-backend-node-wasm.js start concurrent 
-2022-10-13 09:29:02 STATE: test-backend-node-wasm.js start concurrent 
-2022-10-13 09:29:02 STATE: test-backend-node-wasm.js start concurrent 
-2022-10-13 09:29:02 STATE: test-backend-node-wasm.js start concurrent 
-2022-10-13 09:29:02 STATE: test-backend-node-wasm.js start concurrent 
-2022-10-13 09:29:02 STATE: test-backend-node-wasm.js start concurrent 
-2022-10-13 09:29:02 STATE: test-backend-node-wasm.js start concurrent 
-2022-10-13 09:29:02 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
-2022-10-13 09:29:02 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
-2022-10-13 09:29:02 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
-2022-10-13 09:29:02 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-10-13 09:29:02 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-10-13 09:29:03 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-10-13 09:29:03 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151155104} 
-2022-10-13 09:29:03 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151155104} 
-2022-10-13 09:29:03 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151155104} 
-2022-10-13 09:29:03 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:29:03 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:29:03 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:29:04 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:29:04 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-upper.jpg concurrent 
-2022-10-13 09:29:04 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 0 person: 1 {"score":0.96,"gender":"unknown"} {} {"score":0.75,"keypoints":7} 
-2022-10-13 09:29:04 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 994 
-2022-10-13 09:29:04 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-upper.jpg concurrent 
-2022-10-13 09:29:04 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 0 person: 1 {"score":0.96,"gender":"unknown"} {} {"score":0.75,"keypoints":7} 
-2022-10-13 09:29:04 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 995 
-2022-10-13 09:29:04 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-upper.jpg concurrent 
-2022-10-13 09:29:04 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 0 person: 1 {"score":0.96,"gender":"unknown"} {} {"score":0.75,"keypoints":7} 
-2022-10-13 09:29:04 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 994 
-2022-10-13 09:29:04 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:29:04 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:29:04 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-face.jpg concurrent 
-2022-10-13 09:29:04 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 0 person: 1 {"score":0.91,"gender":"unknown"} {} {"score":0.47,"keypoints":3} 
-2022-10-13 09:29:04 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 995 
-2022-10-13 09:29:04 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-face.jpg concurrent 
-2022-10-13 09:29:04 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 0 person: 1 {"score":0.91,"gender":"unknown"} {} {"score":0.47,"keypoints":3} 
-2022-10-13 09:29:04 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 995 
-2022-10-13 09:29:04 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-face.jpg concurrent 
-2022-10-13 09:29:04 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 0 person: 1 {"score":0.91,"gender":"unknown"} {} {"score":0.47,"keypoints":3} 
-2022-10-13 09:29:04 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 995 
-2022-10-13 09:29:04 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg concurrent 
-2022-10-13 09:29:04 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 0 person: 1 {"score":0.93,"gender":"unknown"} {} {"score":0.92,"keypoints":17} 
-2022-10-13 09:29:04 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 995 
-2022-10-13 09:29:04 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg concurrent 
-2022-10-13 09:29:04 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 0 person: 1 {"score":0.93,"gender":"unknown"} {} {"score":0.92,"keypoints":17} 
-2022-10-13 09:29:04 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 995 
-2022-10-13 09:29:04 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg concurrent 
-2022-10-13 09:29:04 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 0 person: 1 {"score":0.93,"gender":"unknown"} {} {"score":0.92,"keypoints":17} 
-2022-10-13 09:29:04 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 995 
-2022-10-13 09:29:04 INFO:  test-backend-node-wasm.js test: monkey-patch 
-2022-10-13 09:29:04 STATE: test-backend-node-wasm.js event: image 
-2022-10-13 09:29:04 STATE: test-backend-node-wasm.js event: detect 
-2022-10-13 09:29:04 STATE: test-backend-node-wasm.js passed: monkey patch 
-2022-10-13 09:29:04 STATE: test-backend-node-wasm.js passed: segmentation [262144] 
-2022-10-13 09:29:04 STATE: test-backend-node-wasm.js passeed: equal usage 
-2022-10-13 09:29:04 INFO:  test-backend-node-wasm.js test: input compare 
-2022-10-13 09:29:04 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
-2022-10-13 09:29:05 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-10-13 09:29:05 STATE: test-backend-node-wasm.js passed: image compare 0 23.280073018790848 
-2022-10-13 09:29:05 INFO:  test-backend-node-wasm.js events: {"image":29,"detect":29,"warmup":2} 
-2022-10-13 09:29:05 INFO:  test-backend-node-wasm.js tensors 4443 
-2022-10-13 09:29:05 INFO:  test-backend-node-wasm.js test complete: 24675 ms 
-2022-10-13 09:29:05 STATE: all tests complete 
-2022-10-13 09:29:05 INFO:    status {"test":"../demo/nodejs/node.js","passed":1,"failed":0} 
-2022-10-13 09:29:05 INFO:    status {"test":"../demo/nodejs/node-simple.js","passed":1,"failed":0} 
-2022-10-13 09:29:05 INFO:    status {"test":"../demo/nodejs/node-fetch.js","passed":1,"failed":0} 
-2022-10-13 09:29:05 INFO:    status {"test":"../demo/nodejs/node-event.js","passed":1,"failed":0} 
-2022-10-13 09:29:05 INFO:    status {"test":"../demo/nodejs/node-similarity.js","passed":1,"failed":0} 
-2022-10-13 09:29:05 INFO:    status {"test":"../demo/nodejs/node-canvas.js","passed":1,"failed":0} 
-2022-10-13 09:29:05 INFO:    status {"test":"../demo/nodejs/process-folder.js","passed":1,"failed":0} 
-2022-10-13 09:29:05 INFO:    status {"test":"../demo/multithread/node-multiprocess.js","passed":1,"failed":0} 
-2022-10-13 09:29:05 INFO:    status {"test":"../demo/facematch/node-match.js","passed":1,"failed":0} 
-2022-10-13 09:29:05 INFO:    status {"test":"test-node-load.js","passed":1,"failed":0} 
-2022-10-13 09:29:05 INFO:    status {"test":"test-node-gear.js","passed":3,"failed":0} 
-2022-10-13 09:29:05 INFO:    status {"test":"test-backend-node.js","passed":125,"failed":0} 
-2022-10-13 09:29:05 INFO:    status {"test":"test-backend-node-gpu.js","passed":125,"failed":0} 
-2022-10-13 09:29:05 INFO:    status {"test":"test-backend-node-wasm.js","passed":124,"failed":2} 
-2022-10-13 09:29:05 INFO:  failures {"count":2} 
-2022-10-13 09:29:05 WARN:    failed {"test":"test-backend-node-wasm.js","message":["error",["failed: nanodet",[]]]} 
-2022-10-13 09:29:05 WARN:    failed {"test":"test-backend-node-wasm.js","message":["error",["failed: face attention",{"annotations":0}]]} 
+2022-10-14 10:55:26 INFO:  @vladmandic/human version 2.11.1 
+2022-10-14 10:55:26 INFO:  User: vlado Platform: linux Arch: x64 Node: v18.10.0 
+2022-10-14 10:55:26 INFO:  demos: [{"cmd":"../demo/nodejs/node.js","args":[]},{"cmd":"../demo/nodejs/node-simple.js","args":[]},{"cmd":"../demo/nodejs/node-fetch.js","args":[]},{"cmd":"../demo/nodejs/node-event.js","args":["samples/in/ai-body.jpg"]},{"cmd":"../demo/nodejs/node-similarity.js","args":["samples/in/ai-face.jpg","samples/in/ai-upper.jpg"]},{"cmd":"../demo/nodejs/node-canvas.js","args":["samples/in/ai-body.jpg","samples/out/ai-body.jpg"]},{"cmd":"../demo/nodejs/process-folder.js","args":["samples"]},{"cmd":"../demo/multithread/node-multiprocess.js","args":[]},{"cmd":"../demo/facematch/node-match.js","args":[]}] 
+2022-10-14 10:55:26 INFO:  {"cmd":"../demo/nodejs/node.js","args":[]} start 
+2022-10-14 10:55:27 INFO:  {"cmd":"../demo/nodejs/node-simple.js","args":[]} start 
+2022-10-14 10:55:28 INFO:  {"cmd":"../demo/nodejs/node-fetch.js","args":[]} start 
+2022-10-14 10:55:31 INFO:  {"cmd":"../demo/nodejs/node-event.js","args":["samples/in/ai-body.jpg"]} start 
+2022-10-14 10:55:32 INFO:  {"cmd":"../demo/nodejs/node-similarity.js","args":["samples/in/ai-face.jpg","samples/in/ai-upper.jpg"]} start 
+2022-10-14 10:55:32 INFO:  {"cmd":"../demo/nodejs/node-canvas.js","args":["samples/in/ai-body.jpg","samples/out/ai-body.jpg"]} start 
+2022-10-14 10:55:33 INFO:  {"cmd":"../demo/nodejs/process-folder.js","args":["samples"]} start 
+2022-10-14 10:55:37 INFO:  {"cmd":"../demo/multithread/node-multiprocess.js","args":[]} start 
+2022-10-14 10:55:49 INFO:  {"cmd":"../demo/facematch/node-match.js","args":[]} start 
+2022-10-14 10:55:51 INFO:  tests: ["test-node-load.js","test-node-gear.js","test-backend-node.js","test-backend-node-gpu.js","test-backend-node-wasm.js"] 
+2022-10-14 10:55:51 INFO:  
+2022-10-14 10:55:51 INFO:  test-node-load.js start 
+2022-10-14 10:55:51 INFO:  test-node-load.js load start {"human":"2.11.1","tf":"4.0.0","progress":0} 
+2022-10-14 10:55:51 DATA:  test-node-load.js load interval {"elapsed":0,"progress":0} 
+2022-10-14 10:55:51 DATA:  test-node-load.js load interval {"elapsed":10,"progress":0} 
+2022-10-14 10:55:51 DATA:  test-node-load.js load interval {"elapsed":23,"progress":0.02116619810068672} 
+2022-10-14 10:55:51 DATA:  test-node-load.js load interval {"elapsed":35,"progress":0.2135162934143239} 
+2022-10-14 10:55:51 DATA:  test-node-load.js load interval {"elapsed":46,"progress":0.3961518088579138} 
+2022-10-14 10:55:51 DATA:  test-node-load.js load interval {"elapsed":69,"progress":0.5125946867158943} 
+2022-10-14 10:55:51 DATA:  test-node-load.js load interval {"elapsed":88,"progress":0.7259096583739463} 
+2022-10-14 10:55:51 STATE: test-node-load.js passed {"progress":1} 
+2022-10-14 10:55:51 INFO:  test-node-load.js load final {"progress":1} 
+2022-10-14 10:55:52 DATA:  test-node-load.js load interval {"elapsed":474,"progress":1} 
+2022-10-14 10:55:52 INFO:  
+2022-10-14 10:55:52 INFO:  test-node-gear.js start 
+2022-10-14 10:55:52 DATA:  test-node-gear.js input: ["samples/in/ai-face.jpg"] 
+2022-10-14 10:55:53 STATE: test-node-gear.js passed: gear faceres samples/in/ai-face.jpg 
+2022-10-14 10:55:53 DATA:  test-node-gear.js results {"face":0,"model":"faceres","image":"samples/in/ai-face.jpg","age":23.5,"gender":"female","genderScore":0.92} 
+2022-10-14 10:55:53 STATE: test-node-gear.js passed: gear gear samples/in/ai-face.jpg 
+2022-10-14 10:55:53 DATA:  test-node-gear.js results {"face":0,"model":"gear","image":"samples/in/ai-face.jpg","age":23.3,"gender":"female","genderScore":0.51,"race":[{"score":0.93,"race":"white"}]} 
+2022-10-14 10:55:53 STATE: test-node-gear.js passed: gear ssrnet samples/in/ai-face.jpg 
+2022-10-14 10:55:53 DATA:  test-node-gear.js results {"face":0,"model":"ssrnet","image":"samples/in/ai-face.jpg","age":23.4,"gender":"female","genderScore":0.99} 
+2022-10-14 10:55:53 INFO:  
+2022-10-14 10:55:53 INFO:  test-backend-node.js start 
+2022-10-14 10:55:53 INFO:  test-backend-node.js test: configuration validation 
+2022-10-14 10:55:53 STATE: test-backend-node.js passed: configuration default validation [] 
+2022-10-14 10:55:53 STATE: test-backend-node.js passed: configuration invalid validation [{"reason":"unknown property","where":"config.invalid = true"}] 
+2022-10-14 10:55:53 INFO:  test-backend-node.js test: model load 
+2022-10-14 10:55:54 STATE: test-backend-node.js passed: models loaded 25 11 [{"name":"ssrnetage","loaded":false,"url":null},{"name":"gear","loaded":false,"url":null},{"name":"blazeposedetect","loaded":false,"url":null},{"name":"blazepose","loaded":false,"url":null},{"name":"centernet","loaded":true,"url":"file://models/mb3-centernet.json"},{"name":"efficientpose","loaded":false,"url":null},{"name":"mobilefacenet","loaded":false,"url":null},{"name":"insightface","loaded":false,"url":null},{"name":"emotion","loaded":true,"url":"file://models/emotion.json"},{"name":"facedetect","loaded":true,"url":"file://models/blazeface.json"},{"name":"faceiris","loaded":true,"url":"file://models/iris.json"},{"name":"facemesh","loaded":true,"url":"file://models/facemesh.json"},{"name":"faceres","loaded":true,"url":"file://models/faceres.json"},{"name":"ssrnetgender","loaded":false,"url":null},{"name":"handpose","loaded":false,"url":null},{"name":"handskeleton","loaded":true,"url":"file://models/handlandmark-full.json"},{"name":"handtrack","loaded":true,"url":"file://models/handtrack.json"},{"name":"liveness","loaded":true,"url":"file://models/liveness.json"},{"name":"meet","loaded":false,"url":null},{"name":"movenet","loaded":true,"url":"file://models/movenet-lightning.json"},{"name":"nanodet","loaded":false,"url":null},{"name":"posenet","loaded":false,"url":null},{"name":"selfie","loaded":false,"url":null},{"name":"rvm","loaded":false,"url":null},{"name":"antispoof","loaded":true,"url":"file://models/antispoof.json"}] 
+2022-10-14 10:55:54 INFO:  test-backend-node.js memory: {"memory":{"unreliable":true,"numTensors":1785,"numDataBuffers":1785,"numBytes":63247332}} 
+2022-10-14 10:55:54 INFO:  test-backend-node.js state: {"state":{"registeredVariables":{},"nextTapeNodeId":0,"numBytes":63247332,"numTensors":1785,"numStringTensors":0,"numDataBuffers":1785,"gradientDepth":0,"kernelDepth":0,"scopeStack":[],"numDataMovesStack":[],"nextScopeId":0,"tensorInfo":{},"profiling":false,"activeProfile":{"newBytes":0,"newTensors":0,"peakBytes":0,"kernels":[],"result":null,"kernelNames":[]}}} 
+2022-10-14 10:55:54 INFO:  test-backend-node.js test: warmup 
+2022-10-14 10:55:54 STATE: test-backend-node.js passed: create human 
+2022-10-14 10:55:54 INFO:  test-backend-node.js human version: 2.11.1 
+2022-10-14 10:55:54 INFO:  test-backend-node.js platform: linux x64 agent: NodeJS v18.10.0 
+2022-10-14 10:55:54 INFO:  test-backend-node.js tfjs version: 4.0.0 
+2022-10-14 10:55:54 INFO:  test-backend-node.js env: {"browser":false,"node":true,"platform":"linux x64","agent":"NodeJS v18.10.0","backends":["cpu","tensorflow"],"initial":false,"tfjs":{"version":"4.0.0"},"offscreen":false,"perfadd":false,"tensorflow":{"version":"2.9.1","gpu":false},"wasm":{"supported":true,"backend":false},"webgl":{"supported":false,"backend":false},"webgpu":{"supported":false,"backend":false},"cpu":{"flags":[]},"kernels":169} 
+2022-10-14 10:55:54 STATE: test-backend-node.js passed: set backend: tensorflow 
+2022-10-14 10:55:54 STATE: test-backend-node.js tensors 1785 
+2022-10-14 10:55:54 STATE: test-backend-node.js passed: load models 
+2022-10-14 10:55:54 STATE: test-backend-node.js  result: defined models: 25 loaded models: 11 
+2022-10-14 10:55:54 STATE: test-backend-node.js passed: warmup: none default 
+2022-10-14 10:55:54 DATA:  test-backend-node.js  result: face: 0 body: 0 hand: 0 gesture: 0 object: 0 person: 0 {} {} {} 
+2022-10-14 10:55:54 DATA:  test-backend-node.js  result: performance: load: null total: null 
+2022-10-14 10:55:54 STATE: test-backend-node.js passed: warmup none result match 
+2022-10-14 10:55:54 STATE: test-backend-node.js event: image 
+2022-10-14 10:55:54 STATE: test-backend-node.js event: detect 
+2022-10-14 10:55:54 STATE: test-backend-node.js event: warmup 
+2022-10-14 10:55:54 STATE: test-backend-node.js passed: warmup: face default 
+2022-10-14 10:55:54 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.42,"keypoints":4} 
+2022-10-14 10:55:54 DATA:  test-backend-node.js  result: performance: load: null total: 510 
+2022-10-14 10:55:54 STATE: test-backend-node.js passed: warmup face result match 
+2022-10-14 10:55:54 STATE: test-backend-node.js event: image 
+2022-10-14 10:55:54 STATE: test-backend-node.js event: detect 
+2022-10-14 10:55:54 STATE: test-backend-node.js event: warmup 
+2022-10-14 10:55:54 STATE: test-backend-node.js passed: warmup: body default 
+2022-10-14 10:55:54 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-10-14 10:55:54 DATA:  test-backend-node.js  result: performance: load: null total: 355 
+2022-10-14 10:55:54 STATE: test-backend-node.js passed: warmup body result match 
+2022-10-14 10:55:54 STATE: test-backend-node.js details: {"face":{"boxScore":0.92,"faceScore":1,"age":23.7,"gender":"female","genderScore":0.97},"emotion":[{"score":0.63,"emotion":"angry"},{"score":0.22,"emotion":"fear"}],"body":{"score":0.92,"keypoints":17},"hand":{"boxScore":0.52,"fingerScore":0.73,"keypoints":21},"gestures":[{"face":0,"gesture":"facing right"},{"face":0,"gesture":"mouth 10% open"},{"hand":0,"gesture":"pinky forward"},{"hand":0,"gesture":"palm up"},{"hand":0,"gesture":"open palm"},{"iris":0,"gesture":"looking left"},{"iris":0,"gesture":"looking up"}]} 
+2022-10-14 10:55:54 INFO:  test-backend-node.js test: details verification 
+2022-10-14 10:55:54 STATE: test-backend-node.js start default 
+2022-10-14 10:55:55 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
+2022-10-14 10:55:55 STATE: test-backend-node.js event: image 
+2022-10-14 10:55:55 STATE: test-backend-node.js event: detect 
+2022-10-14 10:55:55 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg default 
+2022-10-14 10:55:55 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-10-14 10:55:55 DATA:  test-backend-node.js  result: performance: load: null total: 323 
+2022-10-14 10:55:55 STATE: test-backend-node.js passed: details face length 1 
+2022-10-14 10:55:55 STATE: test-backend-node.js passed: details face score 1 0.93 1 
+2022-10-14 10:55:55 STATE: test-backend-node.js passed: details face age/gender 23.7 female 0.97 85.47 
+2022-10-14 10:55:55 STATE: test-backend-node.js passed: details face arrays 4 478 1024 
+2022-10-14 10:55:55 STATE: test-backend-node.js passed: details face emotion 2 {"score":0.59,"emotion":"angry"} 
+2022-10-14 10:55:55 STATE: test-backend-node.js passed: details face anti-spoofing 0.79 
+2022-10-14 10:55:55 STATE: test-backend-node.js passed: details face liveness 0.83 
+2022-10-14 10:55:55 STATE: test-backend-node.js passed: details body length 1 
+2022-10-14 10:55:55 STATE: test-backend-node.js passed: details body 0.92 17 6 
+2022-10-14 10:55:55 STATE: test-backend-node.js passed: details hand length 1 
+2022-10-14 10:55:55 STATE: test-backend-node.js passed: details hand 0.51 0.73 point 
+2022-10-14 10:55:55 STATE: test-backend-node.js passed: details hand arrays 21 5 7 
+2022-10-14 10:55:55 STATE: test-backend-node.js passed: details gesture length 7 
+2022-10-14 10:55:55 STATE: test-backend-node.js passed: details gesture first {"face":0,"gesture":"facing right"} 
+2022-10-14 10:55:55 STATE: test-backend-node.js passed: details object length 1 
+2022-10-14 10:55:55 STATE: test-backend-node.js passed: details object 0.72 person 
+2022-10-14 10:55:55 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1371996928} 
+2022-10-14 10:55:55 STATE: test-backend-node.js event: image 
+2022-10-14 10:55:56 STATE: test-backend-node.js event: detect 
+2022-10-14 10:55:56 STATE: test-backend-node.js passed: tensor shape: [1,1200,1200,4] dtype: float32 
+2022-10-14 10:55:56 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1200,1200,4] {"checksum":1371996928} 
+2022-10-14 10:55:56 STATE: test-backend-node.js event: image 
+2022-10-14 10:55:56 STATE: test-backend-node.js event: detect 
+2022-10-14 10:55:56 STATE: test-backend-node.js passed: tensor shape: [1200,1200,4] dtype: float32 
+2022-10-14 10:55:56 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
+2022-10-14 10:55:56 STATE: test-backend-node.js event: image 
+2022-10-14 10:55:57 STATE: test-backend-node.js event: detect 
+2022-10-14 10:55:57 STATE: test-backend-node.js passed: tensor shape: [1,1200,1200,3] dtype: float32 
+2022-10-14 10:55:57 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1200,1200,3] {"checksum":1004796864} 
+2022-10-14 10:55:57 STATE: test-backend-node.js event: image 
+2022-10-14 10:55:57 STATE: test-backend-node.js event: detect 
+2022-10-14 10:55:57 STATE: test-backend-node.js passed: tensor shape: [1200,1200,3] dtype: float32 
+2022-10-14 10:55:57 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1371996871} 
+2022-10-14 10:55:57 STATE: test-backend-node.js event: image 
+2022-10-14 10:55:57 STATE: test-backend-node.js event: detect 
+2022-10-14 10:55:57 STATE: test-backend-node.js passed: tensor shape: [1,1200,1200,4] dtype: int32 
+2022-10-14 10:55:57 INFO:  test-backend-node.js test default 
+2022-10-14 10:55:57 STATE: test-backend-node.js start async 
+2022-10-14 10:55:58 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
+2022-10-14 10:55:58 STATE: test-backend-node.js event: image 
+2022-10-14 10:55:58 STATE: test-backend-node.js event: detect 
+2022-10-14 10:55:58 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg async 
+2022-10-14 10:55:58 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-10-14 10:55:58 DATA:  test-backend-node.js  result: performance: load: null total: 312 
+2022-10-14 10:55:58 STATE: test-backend-node.js passed: default result face match 1 female 0.97 
+2022-10-14 10:55:58 INFO:  test-backend-node.js test sync 
+2022-10-14 10:55:58 STATE: test-backend-node.js start sync 
+2022-10-14 10:55:58 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
+2022-10-14 10:55:58 STATE: test-backend-node.js event: image 
+2022-10-14 10:55:58 STATE: test-backend-node.js event: detect 
+2022-10-14 10:55:58 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg sync 
+2022-10-14 10:55:58 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-10-14 10:55:58 DATA:  test-backend-node.js  result: performance: load: null total: 295 
+2022-10-14 10:55:58 STATE: test-backend-node.js passed: default sync 1 female 0.97 
+2022-10-14 10:55:58 INFO:  test-backend-node.js test: image process 
+2022-10-14 10:55:58 STATE: test-backend-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
+2022-10-14 10:55:58 STATE: test-backend-node.js passed: image input null [1,256,256,3] 
+2022-10-14 10:55:58 INFO:  test-backend-node.js test: image null 
+2022-10-14 10:55:58 STATE: test-backend-node.js passed: invalid input could not convert input to tensor 
+2022-10-14 10:55:58 INFO:  test-backend-node.js test face similarity 
+2022-10-14 10:55:58 STATE: test-backend-node.js start face similarity 
+2022-10-14 10:55:58 STATE: test-backend-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
+2022-10-14 10:55:58 STATE: test-backend-node.js event: image 
+2022-10-14 10:55:59 STATE: test-backend-node.js event: detect 
+2022-10-14 10:55:59 STATE: test-backend-node.js passed: detect: samples/in/ai-face.jpg face similarity 
+2022-10-14 10:55:59 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 6 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":3} 
+2022-10-14 10:55:59 DATA:  test-backend-node.js  result: performance: load: null total: 294 
+2022-10-14 10:55:59 STATE: test-backend-node.js start face similarity 
+2022-10-14 10:55:59 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
+2022-10-14 10:55:59 STATE: test-backend-node.js event: image 
+2022-10-14 10:55:59 STATE: test-backend-node.js event: detect 
+2022-10-14 10:55:59 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg face similarity 
+2022-10-14 10:55:59 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-10-14 10:55:59 DATA:  test-backend-node.js  result: performance: load: null total: 310 
+2022-10-14 10:55:59 STATE: test-backend-node.js start face similarity 
+2022-10-14 10:55:59 STATE: test-backend-node.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289024} 
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+2022-10-14 10:56:00 STATE: test-backend-node.js event: detect 
+2022-10-14 10:56:00 STATE: test-backend-node.js passed: detect: samples/in/ai-upper.jpg face similarity 
+2022-10-14 10:56:00 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 0 gesture: 4 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":7} 
+2022-10-14 10:56:00 DATA:  test-backend-node.js  result: performance: load: null total: 293 
+2022-10-14 10:56:00 STATE: test-backend-node.js passed: face descriptor 
+2022-10-14 10:56:00 STATE: test-backend-node.js passed: face similarity {"similarity":[1,0.44727441595492046,0.556793560189727],"descriptors":[1024,1024,1024]} 
+2022-10-14 10:56:00 INFO:  test-backend-node.js test object 
+2022-10-14 10:56:00 STATE: test-backend-node.js start object 
+2022-10-14 10:56:00 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
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+2022-10-14 10:56:00 STATE: test-backend-node.js event: detect 
+2022-10-14 10:56:00 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg object 
+2022-10-14 10:56:00 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-10-14 10:56:00 DATA:  test-backend-node.js  result: performance: load: null total: 316 
+2022-10-14 10:56:00 STATE: test-backend-node.js passed: centernet 
+2022-10-14 10:56:00 STATE: test-backend-node.js start object 
+2022-10-14 10:56:01 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
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+2022-10-14 10:56:02 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg object 
+2022-10-14 10:56:02 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 3 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.86,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-10-14 10:56:02 DATA:  test-backend-node.js  result: performance: load: null total: 318 
+2022-10-14 10:56:02 STATE: test-backend-node.js passed: nanodet 
+2022-10-14 10:56:02 INFO:  test-backend-node.js test sensitive 
+2022-10-14 10:56:02 STATE: test-backend-node.js start sensitive 
+2022-10-14 10:56:02 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
+2022-10-14 10:56:02 STATE: test-backend-node.js event: image 
+2022-10-14 10:56:02 STATE: test-backend-node.js event: detect 
+2022-10-14 10:56:02 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg sensitive 
+2022-10-14 10:56:02 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 0 person: 1 {"score":1,"age":23.7,"gender":"female"} {} {"score":0.92,"keypoints":17} 
+2022-10-14 10:56:02 DATA:  test-backend-node.js  result: performance: load: null total: 263 
+2022-10-14 10:56:02 STATE: test-backend-node.js passed: sensitive result match 
+2022-10-14 10:56:02 STATE: test-backend-node.js passed: sensitive face result match 
+2022-10-14 10:56:02 STATE: test-backend-node.js passed: sensitive face emotion result [{"score":0.59,"emotion":"angry"},{"score":0.29,"emotion":"fear"}] 
+2022-10-14 10:56:02 STATE: test-backend-node.js passed: sensitive body result match 
+2022-10-14 10:56:02 STATE: test-backend-node.js passed: sensitive hand result match 
+2022-10-14 10:56:02 INFO:  test-backend-node.js test body 
+2022-10-14 10:56:02 STATE: test-backend-node.js start blazepose 
+2022-10-14 10:56:04 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
+2022-10-14 10:56:04 STATE: test-backend-node.js event: image 
+2022-10-14 10:56:04 STATE: test-backend-node.js event: detect 
+2022-10-14 10:56:04 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg blazepose 
+2022-10-14 10:56:04 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 0 person: 1 {"score":1,"age":23.7,"gender":"female"} {} {"score":0.99,"keypoints":39} 
+2022-10-14 10:56:04 DATA:  test-backend-node.js  result: performance: load: null total: 337 
+2022-10-14 10:56:04 STATE: test-backend-node.js passed: blazepose 
+2022-10-14 10:56:04 STATE: test-backend-node.js start efficientpose 
+2022-10-14 10:56:05 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
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+2022-10-14 10:56:06 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg efficientpose 
+2022-10-14 10:56:06 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 0 person: 1 {"score":1,"age":23.7,"gender":"female"} {} {"score":0.75,"keypoints":13} 
+2022-10-14 10:56:06 DATA:  test-backend-node.js  result: performance: load: null total: 310 
+2022-10-14 10:56:06 STATE: test-backend-node.js passed: efficientpose 
+2022-10-14 10:56:06 STATE: test-backend-node.js start posenet 
+2022-10-14 10:56:06 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
+2022-10-14 10:56:06 STATE: test-backend-node.js event: image 
+2022-10-14 10:56:06 STATE: test-backend-node.js event: detect 
+2022-10-14 10:56:06 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg posenet 
+2022-10-14 10:56:06 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 0 person: 1 {"score":1,"age":23.7,"gender":"female"} {} {"score":0.96,"keypoints":16} 
+2022-10-14 10:56:06 DATA:  test-backend-node.js  result: performance: load: null total: 259 
+2022-10-14 10:56:06 STATE: test-backend-node.js passed: posenet 
+2022-10-14 10:56:06 STATE: test-backend-node.js start movenet 
+2022-10-14 10:56:07 STATE: test-backend-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
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+2022-10-14 10:56:07 STATE: test-backend-node.js event: detect 
+2022-10-14 10:56:07 STATE: test-backend-node.js passed: detect: samples/in/ai-body.jpg movenet 
+2022-10-14 10:56:07 DATA:  test-backend-node.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 0 person: 1 {"score":1,"age":23.7,"gender":"female"} {} {"score":0.92,"keypoints":17} 
+2022-10-14 10:56:07 DATA:  test-backend-node.js  result: performance: load: null total: 259 
+2022-10-14 10:56:07 STATE: test-backend-node.js passed: movenet 
+2022-10-14 10:56:07 INFO:  test-backend-node.js test face matching 
+2022-10-14 10:56:07 STATE: test-backend-node.js passed: face database 40 
+2022-10-14 10:56:07 STATE: test-backend-node.js passed: face match {"first":{"index":4,"similarity":0.7827852251220577}} {"second":{"index":4,"similarity":0.5002052057057577}} {"third":{"index":4,"similarity":0.5401588464054732}} 
+2022-10-14 10:56:07 INFO:  test-backend-node.js test face similarity alternative 
+2022-10-14 10:56:07 STATE: test-backend-node.js start face embeddings 
+2022-10-14 10:56:07 STATE: test-backend-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
+2022-10-14 10:56:07 STATE: test-backend-node.js event: image 
+2022-10-14 10:56:07 ERROR: test-backend-node.js uncaughtException getImage samples/in/ai-face.jpg {} 
+2022-10-14 10:56:07 WARN:  test-backend-node.js stderr: /home/vlado/dev/human/test/test-node-main.js:16 
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+2022-10-14 10:56:07 WARN:  test-backend-node.js stderr:   ^ 
+2022-10-14 10:56:07 WARN:  test-backend-node.js stderr: Error: TypeError: Cannot read properties of undefined (reading 'img_inputs') 
+2022-10-14 10:56:07 WARN:  test-backend-node.js stderr:     at process.<anonymous> (/home/vlado/dev/human/test/test-node-main.js:16:9) 
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+2022-10-14 10:56:07 WARN:  test-backend-node.js stderr:     at process._fatalException (node:internal/process/execution:149:25) 
+2022-10-14 10:56:07 WARN:  test-backend-node.js stderr:     at processPromiseRejections (node:internal/process/promises:261:11) 
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+2022-10-14 10:56:07 WARN:  test-backend-node.js stderr: Thrown at: 
+2022-10-14 10:56:07 WARN:  test-backend-node.js stderr:     at /home/vlado/dev/human/test/test-node-main.js:16:9 
+2022-10-14 10:56:07 WARN:  test-backend-node.js stderr:     at emit (node:events:513:28) 
+2022-10-14 10:56:07 WARN:  test-backend-node.js stderr:     at node:internal/process/execution:149:25 
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+2022-10-14 10:56:07 INFO:  
+2022-10-14 10:56:07 INFO:  test-backend-node-gpu.js start 
+2022-10-14 10:56:08 INFO:  test-backend-node-gpu.js test: configuration validation 
+2022-10-14 10:56:08 STATE: test-backend-node-gpu.js passed: configuration default validation [] 
+2022-10-14 10:56:08 STATE: test-backend-node-gpu.js passed: configuration invalid validation [{"reason":"unknown property","where":"config.invalid = true"}] 
+2022-10-14 10:56:08 INFO:  test-backend-node-gpu.js test: model load 
+2022-10-14 10:56:09 STATE: test-backend-node-gpu.js passed: models loaded 25 11 [{"name":"ssrnetage","loaded":false,"url":null},{"name":"gear","loaded":false,"url":null},{"name":"blazeposedetect","loaded":false,"url":null},{"name":"blazepose","loaded":false,"url":null},{"name":"centernet","loaded":true,"url":"file://models/mb3-centernet.json"},{"name":"efficientpose","loaded":false,"url":null},{"name":"mobilefacenet","loaded":false,"url":null},{"name":"insightface","loaded":false,"url":null},{"name":"emotion","loaded":true,"url":"file://models/emotion.json"},{"name":"facedetect","loaded":true,"url":"file://models/blazeface.json"},{"name":"faceiris","loaded":true,"url":"file://models/iris.json"},{"name":"facemesh","loaded":true,"url":"file://models/facemesh.json"},{"name":"faceres","loaded":true,"url":"file://models/faceres.json"},{"name":"ssrnetgender","loaded":false,"url":null},{"name":"handpose","loaded":false,"url":null},{"name":"handskeleton","loaded":true,"url":"file://models/handlandmark-full.json"},{"name":"handtrack","loaded":true,"url":"file://models/handtrack.json"},{"name":"liveness","loaded":true,"url":"file://models/liveness.json"},{"name":"meet","loaded":false,"url":null},{"name":"movenet","loaded":true,"url":"file://models/movenet-lightning.json"},{"name":"nanodet","loaded":false,"url":null},{"name":"posenet","loaded":false,"url":null},{"name":"selfie","loaded":false,"url":null},{"name":"rvm","loaded":false,"url":null},{"name":"antispoof","loaded":true,"url":"file://models/antispoof.json"}] 
+2022-10-14 10:56:09 INFO:  test-backend-node-gpu.js memory: {"memory":{"unreliable":true,"numTensors":1785,"numDataBuffers":1785,"numBytes":63247332}} 
+2022-10-14 10:56:09 INFO:  test-backend-node-gpu.js state: {"state":{"registeredVariables":{},"nextTapeNodeId":0,"numBytes":63247332,"numTensors":1785,"numStringTensors":0,"numDataBuffers":1785,"gradientDepth":0,"kernelDepth":0,"scopeStack":[],"numDataMovesStack":[],"nextScopeId":0,"tensorInfo":{},"profiling":false,"activeProfile":{"newBytes":0,"newTensors":0,"peakBytes":0,"kernels":[],"result":null,"kernelNames":[]}}} 
+2022-10-14 10:56:09 INFO:  test-backend-node-gpu.js test: warmup 
+2022-10-14 10:56:09 STATE: test-backend-node-gpu.js passed: create human 
+2022-10-14 10:56:09 INFO:  test-backend-node-gpu.js human version: 2.11.1 
+2022-10-14 10:56:09 INFO:  test-backend-node-gpu.js platform: linux x64 agent: NodeJS v18.10.0 
+2022-10-14 10:56:09 INFO:  test-backend-node-gpu.js tfjs version: 4.0.0 
+2022-10-14 10:56:09 INFO:  test-backend-node-gpu.js env: {"browser":false,"node":true,"platform":"linux x64","agent":"NodeJS v18.10.0","backends":["cpu","tensorflow"],"initial":false,"tfjs":{"version":"4.0.0"},"offscreen":false,"perfadd":false,"tensorflow":{"version":"2.9.1","gpu":true},"wasm":{"supported":true,"backend":false},"webgl":{"supported":false,"backend":false},"webgpu":{"supported":false,"backend":false},"cpu":{"flags":[]},"kernels":169} 
+2022-10-14 10:56:09 STATE: test-backend-node-gpu.js passed: set backend: tensorflow 
+2022-10-14 10:56:09 STATE: test-backend-node-gpu.js tensors 1785 
+2022-10-14 10:56:09 STATE: test-backend-node-gpu.js passed: load models 
+2022-10-14 10:56:09 STATE: test-backend-node-gpu.js  result: defined models: 25 loaded models: 11 
+2022-10-14 10:56:09 STATE: test-backend-node-gpu.js passed: warmup: none default 
+2022-10-14 10:56:09 DATA:  test-backend-node-gpu.js  result: face: 0 body: 0 hand: 0 gesture: 0 object: 0 person: 0 {} {} {} 
+2022-10-14 10:56:09 DATA:  test-backend-node-gpu.js  result: performance: load: null total: null 
+2022-10-14 10:56:09 STATE: test-backend-node-gpu.js passed: warmup none result match 
+2022-10-14 10:56:09 STATE: test-backend-node-gpu.js event: image 
+2022-10-14 10:56:13 STATE: test-backend-node-gpu.js event: detect 
+2022-10-14 10:56:13 STATE: test-backend-node-gpu.js event: warmup 
+2022-10-14 10:56:13 STATE: test-backend-node-gpu.js passed: warmup: face default 
+2022-10-14 10:56:13 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.42,"keypoints":4} 
+2022-10-14 10:56:13 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 4116 
+2022-10-14 10:56:13 STATE: test-backend-node-gpu.js passed: warmup face result match 
+2022-10-14 10:56:13 STATE: test-backend-node-gpu.js event: image 
+2022-10-14 10:56:13 STATE: test-backend-node-gpu.js event: detect 
+2022-10-14 10:56:13 STATE: test-backend-node-gpu.js event: warmup 
+2022-10-14 10:56:13 STATE: test-backend-node-gpu.js passed: warmup: body default 
+2022-10-14 10:56:13 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-10-14 10:56:13 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 173 
+2022-10-14 10:56:13 STATE: test-backend-node-gpu.js passed: warmup body result match 
+2022-10-14 10:56:13 STATE: test-backend-node-gpu.js details: {"face":{"boxScore":0.92,"faceScore":1,"age":23.7,"gender":"female","genderScore":0.97},"emotion":[{"score":0.63,"emotion":"angry"},{"score":0.22,"emotion":"fear"}],"body":{"score":0.92,"keypoints":17},"hand":{"boxScore":0.52,"fingerScore":0.73,"keypoints":21},"gestures":[{"face":0,"gesture":"facing right"},{"face":0,"gesture":"mouth 10% open"},{"hand":0,"gesture":"pinky forward"},{"hand":0,"gesture":"palm up"},{"hand":0,"gesture":"open palm"},{"iris":0,"gesture":"looking left"},{"iris":0,"gesture":"looking up"}]} 
+2022-10-14 10:56:13 INFO:  test-backend-node-gpu.js test: details verification 
+2022-10-14 10:56:13 STATE: test-backend-node-gpu.js start default 
+2022-10-14 10:56:13 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
+2022-10-14 10:56:13 STATE: test-backend-node-gpu.js event: image 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js event: detect 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
+2022-10-14 10:56:14 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-10-14 10:56:14 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 195 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js passed: details face length 1 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js passed: details face score 1 0.93 1 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js passed: details face age/gender 23.7 female 0.97 85.47 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js passed: details face arrays 4 478 1024 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js passed: details face emotion 2 {"score":0.59,"emotion":"angry"} 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js passed: details face anti-spoofing 0.79 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js passed: details face liveness 0.83 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js passed: details body length 1 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js passed: details body 0.92 17 6 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js passed: details hand length 1 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js passed: details hand 0.51 0.73 point 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js passed: details hand arrays 21 5 7 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js passed: details gesture length 7 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js passed: details gesture first {"face":0,"gesture":"facing right"} 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js passed: details object length 1 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js passed: details object 0.72 person 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1371996928} 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js event: image 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js event: detect 
+2022-10-14 10:56:14 STATE: test-backend-node-gpu.js passed: tensor shape: [1,1200,1200,4] dtype: float32 
+2022-10-14 10:56:15 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1200,1200,4] {"checksum":1371996928} 
+2022-10-14 10:56:15 STATE: test-backend-node-gpu.js event: image 
+2022-10-14 10:56:15 STATE: test-backend-node-gpu.js event: detect 
+2022-10-14 10:56:15 STATE: test-backend-node-gpu.js passed: tensor shape: [1200,1200,4] dtype: float32 
+2022-10-14 10:56:16 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
+2022-10-14 10:56:16 STATE: test-backend-node-gpu.js event: image 
+2022-10-14 10:56:16 STATE: test-backend-node-gpu.js event: detect 
+2022-10-14 10:56:16 STATE: test-backend-node-gpu.js passed: tensor shape: [1,1200,1200,3] dtype: float32 
+2022-10-14 10:56:16 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1200,1200,3] {"checksum":1004796928} 
+2022-10-14 10:56:16 STATE: test-backend-node-gpu.js event: image 
+2022-10-14 10:56:16 STATE: test-backend-node-gpu.js event: detect 
+2022-10-14 10:56:16 STATE: test-backend-node-gpu.js passed: tensor shape: [1200,1200,3] dtype: float32 
+2022-10-14 10:56:16 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1371996871} 
+2022-10-14 10:56:16 STATE: test-backend-node-gpu.js event: image 
+2022-10-14 10:56:17 STATE: test-backend-node-gpu.js event: detect 
+2022-10-14 10:56:17 STATE: test-backend-node-gpu.js passed: tensor shape: [1,1200,1200,4] dtype: int32 
+2022-10-14 10:56:17 INFO:  test-backend-node-gpu.js test default 
+2022-10-14 10:56:17 STATE: test-backend-node-gpu.js start async 
+2022-10-14 10:56:17 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
+2022-10-14 10:56:17 STATE: test-backend-node-gpu.js event: image 
+2022-10-14 10:56:17 STATE: test-backend-node-gpu.js event: detect 
+2022-10-14 10:56:17 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-body.jpg async 
+2022-10-14 10:56:17 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-10-14 10:56:17 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 142 
+2022-10-14 10:56:17 STATE: test-backend-node-gpu.js passed: default result face match 1 female 0.97 
+2022-10-14 10:56:17 INFO:  test-backend-node-gpu.js test sync 
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+2022-10-14 10:56:17 STATE: test-backend-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
+2022-10-14 10:56:17 STATE: test-backend-node-gpu.js event: image 
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+2022-10-14 10:56:17 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-body.jpg sync 
+2022-10-14 10:56:17 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-10-14 10:56:17 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 185 
+2022-10-14 10:56:17 STATE: test-backend-node-gpu.js passed: default sync 1 female 0.97 
+2022-10-14 10:56:17 INFO:  test-backend-node-gpu.js test: image process 
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+2022-10-14 10:56:17 STATE: test-backend-node-gpu.js passed: image input null [1,256,256,3] 
+2022-10-14 10:56:17 INFO:  test-backend-node-gpu.js test: image null 
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+2022-10-14 10:56:18 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-face.jpg face similarity 
+2022-10-14 10:56:18 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 6 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":3} 
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+2022-10-14 10:56:18 STATE: test-backend-node-gpu.js start face similarity 
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+2022-10-14 10:56:18 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
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+2022-10-14 10:56:18 STATE: test-backend-node-gpu.js start face similarity 
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+2022-10-14 10:56:18 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-upper.jpg face similarity 
+2022-10-14 10:56:18 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 0 gesture: 4 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":7} 
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+2022-10-14 10:56:19 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
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+2022-10-14 10:56:20 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 3 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.86,"class":"person"} {"score":0.92,"keypoints":17} 
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+2022-10-14 10:56:20 STATE: test-backend-node-gpu.js start sensitive 
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+2022-10-14 10:56:20 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 0 person: 1 {"score":1,"age":23.7,"gender":"female"} {} {"score":0.92,"keypoints":17} 
+2022-10-14 10:56:20 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 120 
+2022-10-14 10:56:20 STATE: test-backend-node-gpu.js passed: sensitive result match 
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+2022-10-14 10:56:22 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-body.jpg blazepose 
+2022-10-14 10:56:22 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 0 person: 1 {"score":1,"age":23.7,"gender":"female"} {} {"score":0.99,"keypoints":39} 
+2022-10-14 10:56:22 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 262 
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+2022-10-14 10:56:22 STATE: test-backend-node-gpu.js start efficientpose 
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+2022-10-14 10:56:24 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-body.jpg efficientpose 
+2022-10-14 10:56:24 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 0 person: 1 {"score":1,"age":23.7,"gender":"female"} {} {"score":0.75,"keypoints":13} 
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+2022-10-14 10:56:24 STATE: test-backend-node-gpu.js passed: efficientpose 
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+2022-10-14 10:56:24 STATE: test-backend-node-gpu.js passed: detect: samples/in/ai-body.jpg posenet 
+2022-10-14 10:56:24 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 0 person: 1 {"score":1,"age":23.7,"gender":"female"} {} {"score":0.96,"keypoints":16} 
+2022-10-14 10:56:24 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 128 
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+2022-10-14 10:56:25 DATA:  test-backend-node-gpu.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 0 person: 1 {"score":1,"age":23.7,"gender":"female"} {} {"score":0.92,"keypoints":17} 
+2022-10-14 10:56:25 DATA:  test-backend-node-gpu.js  result: performance: load: null total: 111 
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+2022-10-14 10:56:25 STATE: test-backend-node-gpu.js passed: face database 40 
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+2022-10-14 10:56:25 INFO:  test-backend-node-gpu.js test face similarity alternative 
+2022-10-14 10:56:25 STATE: test-backend-node-gpu.js start face embeddings 
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+2022-10-14 10:56:25 STATE: test-backend-node-gpu.js event: image 
+2022-10-14 10:56:25 ERROR: test-backend-node-gpu.js uncaughtException getImage samples/in/ai-face.jpg {} 
+2022-10-14 10:56:25 WARN:  test-backend-node-gpu.js stderr: /home/vlado/dev/human/test/test-node-main.js:16 
+2022-10-14 10:56:25 WARN:  test-backend-node-gpu.js stderr:   throw new Error(err); 
+2022-10-14 10:56:25 WARN:  test-backend-node-gpu.js stderr:   ^ 
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+2022-10-14 10:56:25 WARN:  test-backend-node-gpu.js stderr:     at process.<anonymous> (/home/vlado/dev/human/test/test-node-main.js:16:9) 
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+2022-10-14 10:56:25 WARN:  test-backend-node-gpu.js stderr:     at process._fatalException (node:internal/process/execution:149:25) 
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+2022-10-14 10:56:25 WARN:  test-backend-node-gpu.js stderr: Thrown at: 
+2022-10-14 10:56:25 WARN:  test-backend-node-gpu.js stderr:     at /home/vlado/dev/human/test/test-node-main.js:16:9 
+2022-10-14 10:56:25 WARN:  test-backend-node-gpu.js stderr:     at emit (node:events:513:28) 
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+2022-10-14 10:56:26 INFO:  
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+2022-10-14 10:56:27 STATE: test-backend-node-wasm.js passed: model server: https://vladmandic.github.io/human-models/models/ 
+2022-10-14 10:56:27 INFO:  test-backend-node-wasm.js test: configuration validation 
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+2022-10-14 10:56:27 STATE: test-backend-node-wasm.js passed: configuration invalid validation [{"reason":"unknown property","where":"config.invalid = true"}] 
+2022-10-14 10:56:27 INFO:  test-backend-node-wasm.js test: model load 
+2022-10-14 10:56:31 STATE: test-backend-node-wasm.js passed: models loaded 25 11 [{"name":"ssrnetage","loaded":false,"url":null},{"name":"gear","loaded":false,"url":null},{"name":"blazeposedetect","loaded":false,"url":null},{"name":"blazepose","loaded":false,"url":null},{"name":"centernet","loaded":true,"url":"https://vladmandic.github.io/human-models/models/mb3-centernet.json"},{"name":"efficientpose","loaded":false,"url":null},{"name":"mobilefacenet","loaded":false,"url":null},{"name":"insightface","loaded":false,"url":null},{"name":"emotion","loaded":true,"url":"https://vladmandic.github.io/human-models/models/emotion.json"},{"name":"facedetect","loaded":true,"url":"https://vladmandic.github.io/human-models/models/blazeface.json"},{"name":"faceiris","loaded":true,"url":"https://vladmandic.github.io/human-models/models/iris.json"},{"name":"facemesh","loaded":true,"url":"https://vladmandic.github.io/human-models/models/facemesh.json"},{"name":"faceres","loaded":true,"url":"https://vladmandic.github.io/human-models/models/faceres.json"},{"name":"ssrnetgender","loaded":false,"url":null},{"name":"handpose","loaded":false,"url":null},{"name":"handskeleton","loaded":true,"url":"https://vladmandic.github.io/human-models/models/handlandmark-full.json"},{"name":"handtrack","loaded":true,"url":"https://vladmandic.github.io/human-models/models/handtrack.json"},{"name":"liveness","loaded":true,"url":"https://vladmandic.github.io/human-models/models/liveness.json"},{"name":"meet","loaded":false,"url":null},{"name":"movenet","loaded":true,"url":"https://vladmandic.github.io/human-models/models/movenet-lightning.json"},{"name":"nanodet","loaded":false,"url":null},{"name":"posenet","loaded":false,"url":null},{"name":"selfie","loaded":false,"url":null},{"name":"rvm","loaded":false,"url":null},{"name":"antispoof","loaded":true,"url":"https://vladmandic.github.io/human-models/models/antispoof.json"}] 
+2022-10-14 10:56:31 INFO:  test-backend-node-wasm.js memory: {"memory":{"unreliable":false,"numTensors":1785,"numDataBuffers":1785,"numBytes":63247332}} 
+2022-10-14 10:56:31 INFO:  test-backend-node-wasm.js state: {"state":{"registeredVariables":{},"nextTapeNodeId":0,"numBytes":63247332,"numTensors":1785,"numStringTensors":0,"numDataBuffers":1785,"gradientDepth":0,"kernelDepth":0,"scopeStack":[],"numDataMovesStack":[],"nextScopeId":0,"tensorInfo":{},"profiling":false,"activeProfile":{"newBytes":0,"newTensors":0,"peakBytes":0,"kernels":[],"result":null,"kernelNames":[]}}} 
+2022-10-14 10:56:31 INFO:  test-backend-node-wasm.js test: warmup 
+2022-10-14 10:56:31 STATE: test-backend-node-wasm.js passed: create human 
+2022-10-14 10:56:31 INFO:  test-backend-node-wasm.js human version: 2.11.1 
+2022-10-14 10:56:31 INFO:  test-backend-node-wasm.js platform: linux x64 agent: NodeJS v18.10.0 
+2022-10-14 10:56:31 INFO:  test-backend-node-wasm.js tfjs version: 4.0.0 
+2022-10-14 10:56:31 INFO:  test-backend-node-wasm.js env: {"browser":false,"node":true,"platform":"linux x64","agent":"NodeJS v18.10.0","backends":["cpu","wasm"],"initial":false,"tfjs":{"version":"4.0.0"},"offscreen":false,"perfadd":false,"tensorflow":{},"wasm":{"supported":true,"backend":true,"simd":true,"multithread":false},"webgl":{"supported":false,"backend":false},"webgpu":{"supported":false,"backend":false},"cpu":{"flags":[]},"kernels":126} 
+2022-10-14 10:56:31 STATE: test-backend-node-wasm.js passed: set backend: wasm 
+2022-10-14 10:56:31 STATE: test-backend-node-wasm.js tensors 1785 
+2022-10-14 10:56:31 STATE: test-backend-node-wasm.js passed: load models 
+2022-10-14 10:56:31 STATE: test-backend-node-wasm.js  result: defined models: 25 loaded models: 11 
+2022-10-14 10:56:31 STATE: test-backend-node-wasm.js passed: warmup: none default 
+2022-10-14 10:56:31 DATA:  test-backend-node-wasm.js  result: face: 0 body: 0 hand: 0 gesture: 0 object: 0 person: 0 {} {} {} 
+2022-10-14 10:56:31 DATA:  test-backend-node-wasm.js  result: performance: load: null total: null 
+2022-10-14 10:56:31 STATE: test-backend-node-wasm.js passed: warmup none result match 
+2022-10-14 10:56:31 STATE: test-backend-node-wasm.js event: image 
+2022-10-14 10:56:31 STATE: test-backend-node-wasm.js event: detect 
+2022-10-14 10:56:31 STATE: test-backend-node-wasm.js event: warmup 
+2022-10-14 10:56:31 STATE: test-backend-node-wasm.js passed: warmup: face default 
+2022-10-14 10:56:31 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 6 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":3} 
+2022-10-14 10:56:31 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 553 
+2022-10-14 10:56:31 STATE: test-backend-node-wasm.js passed: warmup face result match 
+2022-10-14 10:56:31 STATE: test-backend-node-wasm.js event: image 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js event: detect 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js event: warmup 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js passed: warmup: body default 
+2022-10-14 10:56:32 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-10-14 10:56:32 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 357 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js passed: warmup body result match 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js details: {"face":{"boxScore":0.93,"faceScore":1,"age":23.7,"gender":"female","genderScore":0.97},"emotion":[{"score":0.59,"emotion":"angry"},{"score":0.29,"emotion":"fear"}],"body":{"score":0.92,"keypoints":17},"hand":{"boxScore":0.51,"fingerScore":0.73,"keypoints":21},"gestures":[{"face":0,"gesture":"facing right"},{"face":0,"gesture":"mouth 21% open"},{"hand":0,"gesture":"pinky forward"},{"hand":0,"gesture":"palm up"},{"hand":0,"gesture":"open palm"},{"iris":0,"gesture":"looking left"},{"iris":0,"gesture":"looking up"}]} 
+2022-10-14 10:56:32 INFO:  test-backend-node-wasm.js test: details verification 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js start default 
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+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js event: image 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js event: detect 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
+2022-10-14 10:56:32 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-10-14 10:56:32 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 313 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js passed: details face length 1 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js passed: details face score 1 0.93 1 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js passed: details face age/gender 23.7 female 0.97 85.47 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js passed: details face arrays 4 478 1024 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js passed: details face emotion 2 {"score":0.59,"emotion":"angry"} 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js passed: details face anti-spoofing 0.79 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js passed: details face liveness 0.83 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js passed: details body length 1 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js passed: details body 0.92 17 6 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js passed: details hand length 1 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js passed: details hand 0.51 0.73 point 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js passed: details hand arrays 21 5 7 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js passed: details gesture length 7 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js passed: details gesture first {"face":0,"gesture":"facing right"} 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js passed: details object length 1 
+2022-10-14 10:56:32 STATE: test-backend-node-wasm.js passed: details object 0.72 person 
+2022-10-14 10:56:33 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1413675264} 
+2022-10-14 10:56:33 STATE: test-backend-node-wasm.js event: image 
+2022-10-14 10:56:33 STATE: test-backend-node-wasm.js event: detect 
+2022-10-14 10:56:33 STATE: test-backend-node-wasm.js passed: tensor shape: [1,1200,1200,4] dtype: float32 
+2022-10-14 10:56:33 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1200,1200,4] {"checksum":1413675264} 
+2022-10-14 10:56:33 STATE: test-backend-node-wasm.js event: image 
+2022-10-14 10:56:33 STATE: test-backend-node-wasm.js event: detect 
+2022-10-14 10:56:33 STATE: test-backend-node-wasm.js passed: tensor shape: [1200,1200,4] dtype: float32 
+2022-10-14 10:56:34 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-10-14 10:56:34 STATE: test-backend-node-wasm.js event: image 
+2022-10-14 10:56:34 STATE: test-backend-node-wasm.js event: detect 
+2022-10-14 10:56:34 STATE: test-backend-node-wasm.js passed: tensor shape: [1,1200,1200,3] dtype: float32 
+2022-10-14 10:56:34 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1200,1200,3] {"checksum":1038921856} 
+2022-10-14 10:56:34 STATE: test-backend-node-wasm.js event: image 
+2022-10-14 10:56:35 STATE: test-backend-node-wasm.js event: detect 
+2022-10-14 10:56:35 STATE: test-backend-node-wasm.js passed: tensor shape: [1200,1200,3] dtype: float32 
+2022-10-14 10:56:35 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1371996871} 
+2022-10-14 10:56:35 STATE: test-backend-node-wasm.js event: image 
+2022-10-14 10:56:35 STATE: test-backend-node-wasm.js event: detect 
+2022-10-14 10:56:35 STATE: test-backend-node-wasm.js passed: tensor shape: [1,1200,1200,4] dtype: int32 
+2022-10-14 10:56:35 INFO:  test-backend-node-wasm.js test default 
+2022-10-14 10:56:35 STATE: test-backend-node-wasm.js start async 
+2022-10-14 10:56:35 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-10-14 10:56:35 STATE: test-backend-node-wasm.js event: image 
+2022-10-14 10:56:36 STATE: test-backend-node-wasm.js event: detect 
+2022-10-14 10:56:36 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg async 
+2022-10-14 10:56:36 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 8 object: 1 person: 1 {"score":1,"age":29.6,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-10-14 10:56:36 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 328 
+2022-10-14 10:56:36 STATE: test-backend-node-wasm.js passed: default result face match 1 female 0.97 
+2022-10-14 10:56:36 INFO:  test-backend-node-wasm.js test sync 
+2022-10-14 10:56:36 STATE: test-backend-node-wasm.js start sync 
+2022-10-14 10:56:36 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-10-14 10:56:36 STATE: test-backend-node-wasm.js event: image 
+2022-10-14 10:56:36 STATE: test-backend-node-wasm.js event: detect 
+2022-10-14 10:56:36 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg sync 
+2022-10-14 10:56:36 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 8 object: 1 person: 1 {"score":1,"age":29.6,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-10-14 10:56:36 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 378 
+2022-10-14 10:56:36 STATE: test-backend-node-wasm.js passed: default sync 1 female 0.97 
+2022-10-14 10:56:36 INFO:  test-backend-node-wasm.js test: image process 
+2022-10-14 10:56:36 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
+2022-10-14 10:56:36 STATE: test-backend-node-wasm.js passed: image input null [1,256,256,3] 
+2022-10-14 10:56:36 INFO:  test-backend-node-wasm.js test: image null 
+2022-10-14 10:56:36 STATE: test-backend-node-wasm.js passed: invalid input could not convert input to tensor 
+2022-10-14 10:56:36 INFO:  test-backend-node-wasm.js test face similarity 
+2022-10-14 10:56:36 STATE: test-backend-node-wasm.js start face similarity 
+2022-10-14 10:56:36 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
+2022-10-14 10:56:36 STATE: test-backend-node-wasm.js event: image 
+2022-10-14 10:56:37 STATE: test-backend-node-wasm.js event: detect 
+2022-10-14 10:56:37 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-face.jpg face similarity 
+2022-10-14 10:56:37 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 6 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":3} 
+2022-10-14 10:56:37 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 307 
+2022-10-14 10:56:37 STATE: test-backend-node-wasm.js start face similarity 
+2022-10-14 10:56:37 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-10-14 10:56:37 STATE: test-backend-node-wasm.js event: image 
+2022-10-14 10:56:37 STATE: test-backend-node-wasm.js event: detect 
+2022-10-14 10:56:37 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg face similarity 
+2022-10-14 10:56:37 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 8 object: 1 person: 1 {"score":1,"age":29.6,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-10-14 10:56:37 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 335 
+2022-10-14 10:56:37 STATE: test-backend-node-wasm.js start face similarity 
+2022-10-14 10:56:37 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151155104} 
+2022-10-14 10:56:37 STATE: test-backend-node-wasm.js event: image 
+2022-10-14 10:56:38 STATE: test-backend-node-wasm.js event: detect 
+2022-10-14 10:56:38 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-upper.jpg face similarity 
+2022-10-14 10:56:38 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 0 gesture: 4 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":7} 
+2022-10-14 10:56:38 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 286 
+2022-10-14 10:56:38 STATE: test-backend-node-wasm.js passed: face descriptor 
+2022-10-14 10:56:38 STATE: test-backend-node-wasm.js passed: face similarity {"similarity":[1,0.5266119940661309,0.4858842904087851],"descriptors":[1024,1024,1024]} 
+2022-10-14 10:56:38 INFO:  test-backend-node-wasm.js test object 
+2022-10-14 10:56:38 STATE: test-backend-node-wasm.js start object 
+2022-10-14 10:56:38 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-10-14 10:56:38 STATE: test-backend-node-wasm.js event: image 
+2022-10-14 10:56:38 STATE: test-backend-node-wasm.js event: detect 
+2022-10-14 10:56:38 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg object 
+2022-10-14 10:56:38 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 8 object: 1 person: 1 {"score":1,"age":29.6,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-10-14 10:56:38 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 309 
+2022-10-14 10:56:38 STATE: test-backend-node-wasm.js passed: centernet 
+2022-10-14 10:56:38 STATE: test-backend-node-wasm.js start object 
+2022-10-14 10:56:39 WARN:  test-backend-node-wasm.js missing kernel ops {"title":"object","model":"nanodet","url":"https://vladmandic.github.io/human-models/models/nanodet.json","missing":["sparsetodense"],"backkend":"wasm"} 
+2022-10-14 10:56:39 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-10-14 10:56:39 STATE: test-backend-node-wasm.js event: image 
+2022-10-14 10:56:39 STATE: test-backend-node-wasm.js event: detect 
+2022-10-14 10:56:39 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg object 
+2022-10-14 10:56:39 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 8 object: 0 person: 1 {"score":1,"age":29.6,"gender":"female"} {} {"score":0.92,"keypoints":17} 
+2022-10-14 10:56:39 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 223 
+2022-10-14 10:56:39 ERROR: test-backend-node-wasm.js failed: nanodet [] 
+2022-10-14 10:56:39 INFO:  test-backend-node-wasm.js test sensitive 
+2022-10-14 10:56:39 STATE: test-backend-node-wasm.js start sensitive 
+2022-10-14 10:56:40 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-10-14 10:56:40 STATE: test-backend-node-wasm.js event: image 
+2022-10-14 10:56:40 STATE: test-backend-node-wasm.js event: detect 
+2022-10-14 10:56:40 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg sensitive 
+2022-10-14 10:56:40 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 2 gesture: 10 object: 0 person: 1 {"score":1,"age":29.6,"gender":"female"} {} {"score":0.92,"keypoints":17} 
+2022-10-14 10:56:40 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 306 
+2022-10-14 10:56:40 STATE: test-backend-node-wasm.js passed: sensitive result match 
+2022-10-14 10:56:40 STATE: test-backend-node-wasm.js passed: sensitive face result match 
+2022-10-14 10:56:40 STATE: test-backend-node-wasm.js passed: sensitive face emotion result [{"score":0.46,"emotion":"neutral"},{"score":0.24,"emotion":"fear"},{"score":0.17,"emotion":"sad"}] 
+2022-10-14 10:56:40 STATE: test-backend-node-wasm.js passed: sensitive body result match 
+2022-10-14 10:56:40 STATE: test-backend-node-wasm.js passed: sensitive hand result match 
+2022-10-14 10:56:40 INFO:  test-backend-node-wasm.js test body 
+2022-10-14 10:56:40 STATE: test-backend-node-wasm.js start blazepose 
+2022-10-14 10:56:42 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-10-14 10:56:42 STATE: test-backend-node-wasm.js event: image 
+2022-10-14 10:56:42 STATE: test-backend-node-wasm.js event: detect 
+2022-10-14 10:56:42 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg blazepose 
+2022-10-14 10:56:42 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 2 gesture: 10 object: 0 person: 1 {"score":1,"age":29.6,"gender":"female"} {} {"score":0.99,"keypoints":39} 
+2022-10-14 10:56:42 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 387 
+2022-10-14 10:56:42 STATE: test-backend-node-wasm.js passed: blazepose 
+2022-10-14 10:56:42 STATE: test-backend-node-wasm.js start efficientpose 
+2022-10-14 10:56:43 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-10-14 10:56:43 STATE: test-backend-node-wasm.js event: image 
+2022-10-14 10:56:44 STATE: test-backend-node-wasm.js event: detect 
+2022-10-14 10:56:44 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg efficientpose 
+2022-10-14 10:56:44 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 2 gesture: 10 object: 0 person: 1 {"score":1,"age":29.6,"gender":"female"} {} {"score":0.75,"keypoints":13} 
+2022-10-14 10:56:44 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 683 
+2022-10-14 10:56:44 STATE: test-backend-node-wasm.js passed: efficientpose 
+2022-10-14 10:56:44 STATE: test-backend-node-wasm.js start posenet 
+2022-10-14 10:56:44 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-10-14 10:56:44 STATE: test-backend-node-wasm.js event: image 
+2022-10-14 10:56:45 STATE: test-backend-node-wasm.js event: detect 
+2022-10-14 10:56:45 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg posenet 
+2022-10-14 10:56:45 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 2 gesture: 10 object: 0 person: 1 {"score":1,"age":29.6,"gender":"female"} {} {"score":0.96,"keypoints":16} 
+2022-10-14 10:56:45 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 310 
+2022-10-14 10:56:45 STATE: test-backend-node-wasm.js passed: posenet 
+2022-10-14 10:56:45 STATE: test-backend-node-wasm.js start movenet 
+2022-10-14 10:56:45 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-10-14 10:56:45 STATE: test-backend-node-wasm.js event: image 
+2022-10-14 10:56:45 STATE: test-backend-node-wasm.js event: detect 
+2022-10-14 10:56:45 STATE: test-backend-node-wasm.js passed: detect: samples/in/ai-body.jpg movenet 
+2022-10-14 10:56:45 DATA:  test-backend-node-wasm.js  result: face: 1 body: 1 hand: 2 gesture: 10 object: 0 person: 1 {"score":1,"age":29.6,"gender":"female"} {} {"score":0.92,"keypoints":17} 
+2022-10-14 10:56:45 DATA:  test-backend-node-wasm.js  result: performance: load: null total: 261 
+2022-10-14 10:56:45 STATE: test-backend-node-wasm.js passed: movenet 
+2022-10-14 10:56:45 INFO:  test-backend-node-wasm.js test face matching 
+2022-10-14 10:56:45 STATE: test-backend-node-wasm.js passed: face database 40 
+2022-10-14 10:56:45 STATE: test-backend-node-wasm.js passed: face match {"first":{"index":4,"similarity":0.7827852754786533}} {"second":{"index":4,"similarity":0.5660821189104794}} {"third":{"index":4,"similarity":0.45074189882665594}} 
+2022-10-14 10:56:45 INFO:  test-backend-node-wasm.js test face similarity alternative 
+2022-10-14 10:56:45 STATE: test-backend-node-wasm.js start face embeddings 
+2022-10-14 10:56:46 STATE: test-backend-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
+2022-10-14 10:56:46 STATE: test-backend-node-wasm.js event: image 
+2022-10-14 10:56:46 ERROR: test-backend-node-wasm.js uncaughtException getImage samples/in/ai-face.jpg {} 
+2022-10-14 10:56:46 WARN:  test-backend-node-wasm.js stderr: /home/vlado/dev/human/test/test-node-main.js:16 
+2022-10-14 10:56:46 WARN:  test-backend-node-wasm.js stderr:   throw new Error(err); 
+2022-10-14 10:56:46 WARN:  test-backend-node-wasm.js stderr:   ^ 
+2022-10-14 10:56:46 WARN:  test-backend-node-wasm.js stderr: Error: TypeError: Cannot read properties of undefined (reading 'img_inputs') 
+2022-10-14 10:56:46 WARN:  test-backend-node-wasm.js stderr:     at process.<anonymous> (/home/vlado/dev/human/test/test-node-main.js:16:9) 
+2022-10-14 10:56:46 WARN:  test-backend-node-wasm.js stderr:     at process.emit (node:events:525:35) 
+2022-10-14 10:56:46 WARN:  test-backend-node-wasm.js stderr:     at process._fatalException (node:internal/process/execution:149:25) 
+2022-10-14 10:56:46 WARN:  test-backend-node-wasm.js stderr:     at processPromiseRejections (node:internal/process/promises:261:11) 
+2022-10-14 10:56:46 WARN:  test-backend-node-wasm.js stderr:     at process.processTicksAndRejections (node:internal/process/task_queues:96:32) 
+2022-10-14 10:56:46 WARN:  test-backend-node-wasm.js stderr: Thrown at: 
+2022-10-14 10:56:46 WARN:  test-backend-node-wasm.js stderr:     at /home/vlado/dev/human/test/test-node-main.js:16:9 
+2022-10-14 10:56:46 WARN:  test-backend-node-wasm.js stderr:     at emit (node:events:525:35) 
+2022-10-14 10:56:46 WARN:  test-backend-node-wasm.js stderr:     at node:internal/process/execution:149:25 
+2022-10-14 10:56:46 WARN:  test-backend-node-wasm.js stderr:     at processPromiseRejections (node:internal/process/promises:261:11) 
+2022-10-14 10:56:46 WARN:  test-backend-node-wasm.js stderr:     at processTicksAndRejections (node:internal/process/task_queues:96:32) 
+2022-10-14 10:56:46 WARN:  test-backend-node-wasm.js stderr: Node.js v18.10.0 
+2022-10-14 10:56:46 STATE: all tests complete 
+2022-10-14 10:56:46 INFO:    status {"test":"../demo/nodejs/node.js","passed":1,"failed":0} 
+2022-10-14 10:56:46 INFO:    status {"test":"../demo/nodejs/node-simple.js","passed":1,"failed":0} 
+2022-10-14 10:56:46 INFO:    status {"test":"../demo/nodejs/node-fetch.js","passed":1,"failed":0} 
+2022-10-14 10:56:46 INFO:    status {"test":"../demo/nodejs/node-event.js","passed":1,"failed":0} 
+2022-10-14 10:56:46 INFO:    status {"test":"../demo/nodejs/node-similarity.js","passed":1,"failed":0} 
+2022-10-14 10:56:46 INFO:    status {"test":"../demo/nodejs/node-canvas.js","passed":1,"failed":0} 
+2022-10-14 10:56:46 INFO:    status {"test":"../demo/nodejs/process-folder.js","passed":1,"failed":0} 
+2022-10-14 10:56:46 INFO:    status {"test":"../demo/multithread/node-multiprocess.js","passed":1,"failed":0} 
+2022-10-14 10:56:46 INFO:    status {"test":"../demo/facematch/node-match.js","passed":1,"failed":0} 
+2022-10-14 10:56:46 INFO:    status {"test":"test-node-load.js","passed":1,"failed":0} 
+2022-10-14 10:56:46 INFO:    status {"test":"test-node-gear.js","passed":3,"failed":0} 
+2022-10-14 10:56:46 INFO:    status {"test":"test-backend-node.js","passed":85,"failed":"critical"} 
+2022-10-14 10:56:46 INFO:    status {"test":"test-backend-node-gpu.js","passed":85,"failed":"critical"} 
+2022-10-14 10:56:46 INFO:    status {"test":"test-backend-node-wasm.js","passed":85,"failed":"critical"} 
+2022-10-14 10:56:46 INFO:  failures {"count":1} 
+2022-10-14 10:56:46 WARN:    failed {"test":"test-backend-node-wasm.js","message":["error",["failed: nanodet",[]]]} 
diff --git a/tsconfig.json b/tsconfig.json
index bbde1847..cb10ffbc 100644
--- a/tsconfig.json
+++ b/tsconfig.json
@@ -54,6 +54,7 @@
   "exclude": ["node_modules/", "types/", "dist/**/*.js"],
   "include": ["src", "tfjs/*.ts", "types/human.d.ts", "test/**/*.ts", "demo/**/*.ts"],
   "typedocOptions": {
-    "externalPattern": ["node_modules/", "tfjs/"]
+    "excludeExternals": true,
+    "externalPattern": ["**/node_modules/**", "tfjs/"]
   }
 }