add loaded property to model stats and mark models not loaded correctly.

Signed-off-by: Vladimir Mandic <mandic00@live.com>

demo/typescript/index.js

@@ -4,6 +4,105 @@
   author: <https://github.com/vladmandic>'
 */
 
-import*as m from"../../dist/human.esm.js";var v=1920,b={debug:!0,backend:"webgl",modelBasePath:"https://vladmandic.github.io/human-models/models/",filter:{enabled:!0,equalization:!1,flip:!1},face:{enabled:!0,detector:{rotation:!1},mesh:{enabled:!0},attention:{enabled:!1},iris:{enabled:!0},description:{enabled:!0},emotion:{enabled:!0},antispoof:{enabled:!0},liveness:{enabled:!0}},body:{enabled:!1},hand:{enabled:!1},object:{enabled:!1},segmentation:{enabled:!1},gesture:{enabled:!0}},e=new m.Human(b);e.env.perfadd=!1;e.draw.options.font='small-caps 18px "Lato"';e.draw.options.lineHeight=20;e.draw.options.drawPoints=!0;var a={video:document.getElementById("video"),canvas:document.getElementById("canvas"),log:document.getElementById("log"),fps:document.getElementById("status"),perf:document.getElementById("performance")},n={detect:0,draw:0,tensors:0,start:0},s={detectFPS:0,drawFPS:0,frames:0,averageMs:0},o=(...t)=>{a.log.innerText+=t.join(" ")+`
+
-`,console.log(...t)},i=t=>a.fps.innerText=t,g=t=>a.perf.innerText="tensors:"+e.tf.memory().numTensors.toString()+" | performance: "+JSON.stringify(t).replace(/"|{|}/g,"").replace(/,/g," | ");async function f(){if(!a.video.paused){n.start===0&&(n.start=e.now()),await e.detect(a.video);let t=e.tf.memory().numTensors;t-n.tensors!==0&&o("allocated tensors:",t-n.tensors),n.tensors=t,s.detectFPS=Math.round(1e3*1e3/(e.now()-n.detect))/1e3,s.frames++,s.averageMs=Math.round(1e3*(e.now()-n.start)/s.frames)/1e3,s.frames%100===0&&!a.video.paused&&o("performance",{...s,tensors:n.tensors})}n.detect=e.now(),requestAnimationFrame(f)}async function u(){var d,r,c;if(!a.video.paused){let l=e.next(e.result),w=await e.image(a.video);e.draw.canvas(w.canvas,a.canvas);let p={bodyLabels:`person confidence [score] and ${(c=(r=(d=e.result)==null?void 0:d.body)==null?void 0:r[0])==null?void 0:c.keypoints.length} keypoints`};await e.draw.all(a.canvas,l,p),g(l.performance)}let t=e.now();s.drawFPS=Math.round(1e3*1e3/(t-n.draw))/1e3,n.draw=t,i(a.video.paused?"paused":`fps: ${s.detectFPS.toFixed(1).padStart(5," ")} detect | ${s.drawFPS.toFixed(1).padStart(5," ")} draw`),setTimeout(u,30)}async function h(){let d=(await e.webcam.enumerate())[0].deviceId,r=await e.webcam.start({element:a.video,crop:!1,width:v,id:d});o(r),a.canvas.width=e.webcam.width,a.canvas.height=e.webcam.height,a.canvas.onclick=async()=>{e.webcam.paused?await e.webcam.play():e.webcam.pause()}}async function y(){o("human version:",e.version,"| tfjs version:",e.tf.version["tfjs-core"]),o("platform:",e.env.platform,"| agent:",e.env.agent),i("loading..."),await e.load(),o("backend:",e.tf.getBackend(),"| available:",e.env.backends),o("models stats:",e.models.stats()),o("models loaded:",e.models.loaded()),o("environment",e.env),i("initializing..."),await e.warmup(),await h(),await f(),await u()}window.onload=y;
+// demo/typescript/index.ts
+import * as H from "../../dist/human.esm.js";
+var width = 1920;
+var humanConfig = {
+  // user configuration for human, used to fine-tune behavior
+  debug: true,
+  backend: "webgl",
+  // cacheSensitivity: 0,
+  // cacheModels: false,
+  // warmup: 'none',
+  // modelBasePath: '../../models',
+  modelBasePath: "https://vladmandic.github.io/human-models/models/",
+  filter: { enabled: true, equalization: false, flip: false },
+  face: { enabled: true, detector: { rotation: false }, mesh: { enabled: true }, attention: { enabled: false }, iris: { enabled: true }, description: { enabled: true }, emotion: { enabled: true }, antispoof: { enabled: true }, liveness: { enabled: true } },
+  body: { enabled: false },
+  hand: { enabled: false },
+  object: { enabled: false },
+  segmentation: { enabled: false },
+  gesture: { enabled: true }
+};
+var human = new H.Human(humanConfig);
+human.env.perfadd = false;
+human.draw.options.font = 'small-caps 18px "Lato"';
+human.draw.options.lineHeight = 20;
+human.draw.options.drawPoints = true;
+var dom = {
+  // grab instances of dom objects so we dont have to look them up later
+  video: document.getElementById("video"),
+  canvas: document.getElementById("canvas"),
+  log: document.getElementById("log"),
+  fps: document.getElementById("status"),
+  perf: document.getElementById("performance")
+};
+var timestamp = { detect: 0, draw: 0, tensors: 0, start: 0 };
+var fps = { detectFPS: 0, drawFPS: 0, frames: 0, averageMs: 0 };
+var log = (...msg) => {
+  dom.log.innerText += msg.join(" ") + "\n";
+  console.log(...msg);
+};
+var status = (msg) => dom.fps.innerText = msg;
+var perf = (msg) => dom.perf.innerText = "tensors:" + human.tf.memory().numTensors.toString() + " | performance: " + JSON.stringify(msg).replace(/"|{|}/g, "").replace(/,/g, " | ");
+async function detectionLoop() {
+  if (!dom.video.paused) {
+    if (timestamp.start === 0) timestamp.start = human.now();
+    await human.detect(dom.video);
+    const tensors = human.tf.memory().numTensors;
+    if (tensors - timestamp.tensors !== 0) log("allocated tensors:", tensors - timestamp.tensors);
+    timestamp.tensors = tensors;
+    fps.detectFPS = Math.round(1e3 * 1e3 / (human.now() - timestamp.detect)) / 1e3;
+    fps.frames++;
+    fps.averageMs = Math.round(1e3 * (human.now() - timestamp.start) / fps.frames) / 1e3;
+    if (fps.frames % 100 === 0 && !dom.video.paused) log("performance", { ...fps, tensors: timestamp.tensors });
+  }
+  timestamp.detect = human.now();
+  requestAnimationFrame(detectionLoop);
+}
+async function drawLoop() {
+  var _a, _b, _c;
+  if (!dom.video.paused) {
+    const interpolated = human.next(human.result);
+    const processed = await human.image(dom.video);
+    human.draw.canvas(processed.canvas, dom.canvas);
+    const opt = { bodyLabels: `person confidence [score] and ${(_c = (_b = (_a = human.result) == null ? void 0 : _a.body) == null ? void 0 : _b[0]) == null ? void 0 : _c.keypoints.length} keypoints` };
+    await human.draw.all(dom.canvas, interpolated, opt);
+    perf(interpolated.performance);
+  }
+  const now = human.now();
+  fps.drawFPS = Math.round(1e3 * 1e3 / (now - timestamp.draw)) / 1e3;
+  timestamp.draw = now;
+  status(dom.video.paused ? "paused" : `fps: ${fps.detectFPS.toFixed(1).padStart(5, " ")} detect | ${fps.drawFPS.toFixed(1).padStart(5, " ")} draw`);
+  setTimeout(drawLoop, 30);
+}
+async function webCam() {
+  const devices = await human.webcam.enumerate();
+  const id = devices[0].deviceId;
+  const webcamStatus = await human.webcam.start({ element: dom.video, crop: false, width, id });
+  log(webcamStatus);
+  dom.canvas.width = human.webcam.width;
+  dom.canvas.height = human.webcam.height;
+  dom.canvas.onclick = async () => {
+    if (human.webcam.paused) await human.webcam.play();
+    else human.webcam.pause();
+  };
+}
+async function main() {
+  log("human version:", human.version, "| tfjs version:", human.tf.version["tfjs-core"]);
+  log("platform:", human.env.platform, "| agent:", human.env.agent);
+  status("loading...");
+  await human.load();
+  log("backend:", human.tf.getBackend(), "| available:", human.env.backends);
+  log("models stats:", human.models.stats());
+  log("models loaded:", human.models.loaded());
+  log("environment", human.env);
+  status("initializing...");
+  await human.warmup();
+  await webCam();
+  await detectionLoop();
+  await drawLoop();
+}
+window.onload = main;
 //# sourceMappingURL=index.js.map

dist/human.esm.js

@@ -536,6 +536,7 @@ var AG = (r15, e, t10, o) => {
 };
 var zp = (r15, e, t10) => (t10 = r15 != null ? _G(RG(r15)) : {}, AG(e || !r15 || !r15.__esModule ? QC(t10, "default", { value: r15, enumerable: true }) : t10, r15));
 var U0 = Kt((ple, W0) => {
+  "use strict";
   W0.exports = kt;
   var ko = null;
   try {
@@ -826,10 +827,13 @@ var U0 = Kt((ple, W0) => {
   };
 });
 var Ek = Kt(() => {
+  "use strict";
 });
 var $k = Kt(() => {
+  "use strict";
 });
 var o1 = Kt((r1, Ww) => {
+  "use strict";
   (function(r15, e, t10) {
     function o(i) {
       var p = this, u = a();
@@ -869,6 +873,7 @@ var o1 = Kt((r1, Ww) => {
   })(r1, typeof Ww == "object" && Ww, typeof define == "function" && define);
 });
 var s1 = Kt((n1, Uw) => {
+  "use strict";
   (function(r15, e, t10) {
     function o(a) {
       var i = this, p = "";
@@ -900,6 +905,7 @@ var s1 = Kt((n1, Uw) => {
   })(n1, typeof Uw == "object" && Uw, typeof define == "function" && define);
 });
 var i1 = Kt((a1, Gw) => {
+  "use strict";
   (function(r15, e, t10) {
     function o(a) {
       var i = this, p = "";
@@ -931,6 +937,7 @@ var i1 = Kt((a1, Gw) => {
   })(a1, typeof Gw == "object" && Gw, typeof define == "function" && define);
 });
 var p1 = Kt((u1, Hw) => {
+  "use strict";
   (function(r15, e, t10) {
     function o(a) {
       var i = this;
@@ -971,6 +978,7 @@ var p1 = Kt((u1, Hw) => {
   })(u1, typeof Hw == "object" && Hw, typeof define == "function" && define);
 });
 var l1 = Kt((c1, Kw) => {
+  "use strict";
   (function(r15, e, t10) {
     function o(a) {
       var i = this;
@@ -1009,6 +1017,7 @@ var l1 = Kt((c1, Kw) => {
   })(c1, typeof Kw == "object" && Kw, typeof define == "function" && define);
 });
 var d1 = Kt((m1, qw) => {
+  "use strict";
   (function(r15, e, t10) {
     function o(a) {
       var i = this, p = "";
@@ -1040,8 +1049,10 @@ var d1 = Kt((m1, qw) => {
   })(m1, typeof qw == "object" && qw, typeof define == "function" && define);
 });
 var f1 = Kt(() => {
+  "use strict";
 });
 var g1 = Kt((h1, Md) => {
+  "use strict";
   (function(r15, e, t10) {
     var o = 256, n = 6, s = 52, a = "random", i = t10.pow(o, n), p = t10.pow(2, s), u = p * 2, c = o - 1, l;
     function m(C, S, k) {
@@ -1110,6 +1121,7 @@ var g1 = Kt((h1, Md) => {
   })(typeof self != "undefined" ? self : h1, [], Math);
 });
 var jw = Kt((s1e, x1) => {
+  "use strict";
   var Dq = o1(), Aq = s1(), Fq = i1(), Pq = p1(), Oq = l1(), Mq = d1(), Ku = g1();
   Ku.alea = Dq;
   Ku.xor128 = Aq;
@@ -1120,16 +1132,22 @@ var jw = Kt((s1e, x1) => {
   x1.exports = Ku;
 });
 var Vv = Kt(() => {
+  "use strict";
 });
 var Wv = Kt(() => {
+  "use strict";
 });
 var LB = Kt(() => {
+  "use strict";
 });
 var BB = Kt(() => {
+  "use strict";
 });
 var zB = Kt(() => {
+  "use strict";
 });
 var VB = Kt((Wg, Gv) => {
+  "use strict";
   var Uv = (() => {
     var r15 = typeof document != "undefined" && document.currentScript ? document.currentScript.src : void 0;
     return typeof __filename != "undefined" && (r15 = r15 || __filename), function(e) {
@@ -2088,10 +2106,12 @@ var VB = Kt((Wg, Gv) => {
   }) : typeof Wg == "object" && (Wg.WasmBackendModuleThreadedSimd = Uv);
 });
 var UB = Kt((e3t, WB) => {
+  "use strict";
   WB.exports.wasmWorkerContents = `"use strict";var Module={};var ENVIRONMENT_IS_NODE=typeof process=="object"&&typeof process.versions=="object"&&typeof process.versions.node=="string";if(ENVIRONMENT_IS_NODE){var nodeWorkerThreads=require("worker_threads");var parentPort=nodeWorkerThreads.parentPort;parentPort.on("message",data=>onmessage({data:data}));var fs=require("fs");Object.assign(global,{self:global,require:require,Module:Module,location:{href:__filename},Worker:nodeWorkerThreads.Worker,importScripts:function(f){(0,eval)(fs.readFileSync(f,"utf8")+"//# sourceURL="+f)},postMessage:function(msg){parentPort.postMessage(msg)},performance:global.performance||{now:function(){return Date.now()}}})}var initializedJS=false;var pendingNotifiedProxyingQueues=[];function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(" ");if(ENVIRONMENT_IS_NODE){fs.writeSync(2,text+"
 ");return}console.error(text)}function threadAlert(){var text=Array.prototype.slice.call(arguments).join(" ");postMessage({cmd:"alert",text:text,threadId:Module["_pthread_self"]()})}var err=threadPrintErr;self.alert=threadAlert;Module["instantiateWasm"]=(info,receiveInstance)=>{var instance=new WebAssembly.Instance(Module["wasmModule"],info);receiveInstance(instance);Module["wasmModule"]=null;return instance.exports};self.onunhandledrejection=e=>{throw e.reason??e};self.startWorker=instance=>{Module=instance;postMessage({"cmd":"loaded"})};self.onmessage=e=>{try{if(e.data.cmd==="load"){Module["wasmModule"]=e.data.wasmModule;for(const handler of e.data.handlers){Module[handler]=function(){postMessage({cmd:"callHandler",handler:handler,args:[...arguments]})}}Module["wasmMemory"]=e.data.wasmMemory;Module["buffer"]=Module["wasmMemory"].buffer;Module["ENVIRONMENT_IS_PTHREAD"]=true;if(typeof e.data.urlOrBlob=="string"){importScripts(e.data.urlOrBlob)}else{var objectUrl=URL.createObjectURL(e.data.urlOrBlob);importScripts(objectUrl);URL.revokeObjectURL(objectUrl)}WasmBackendModuleThreadedSimd(Module)}else if(e.data.cmd==="run"){Module["__emscripten_thread_init"](e.data.pthread_ptr,0,0,1);Module["establishStackSpace"]();Module["PThread"].receiveObjectTransfer(e.data);Module["PThread"].threadInitTLS();if(!initializedJS){pendingNotifiedProxyingQueues.forEach(queue=>{Module["executeNotifiedProxyingQueue"](queue)});pendingNotifiedProxyingQueues=[];initializedJS=true}try{Module["invokeEntryPoint"](e.data.start_routine,e.data.arg)}catch(ex){if(ex!="unwind"){if(ex instanceof Module["ExitStatus"]){if(Module["keepRuntimeAlive"]()){}else{Module["__emscripten_thread_exit"](ex.status)}}else{throw ex}}}}else if(e.data.cmd==="cancel"){if(Module["_pthread_self"]()){Module["__emscripten_thread_exit"](-1)}}else if(e.data.target==="setimmediate"){}else if(e.data.cmd==="processProxyingQueue"){if(initializedJS){Module["executeNotifiedProxyingQueue"](e.data.queue)}else{pendingNotifiedProxyingQueues.push(e.data.queue)}}else if(e.data.cmd){err("worker.js received unknown command "+e.data.cmd);err(e.data)}}catch(ex){if(Module["__emscripten_thread_crashed"]){Module["__emscripten_thread_crashed"]()}throw ex}};`;
 });
 var GB = Kt((Ug, Kv) => {
+  "use strict";
   var Hv = (() => {
     var r15 = typeof document != "undefined" && document.currentScript ? document.currentScript.src : void 0;
     return typeof __filename != "undefined" && (r15 = r15 || __filename), function(e) {
@@ -33502,7 +33522,7 @@ function setModelLoadOptions(config3) {
   options.modelBasePath = config3.modelBasePath;
 }
 async function loadModel(modelPath) {
-  var _a, _b, _c2, _d2;
+  var _a, _b, _c2, _d2, _e, _f2;
   let modelUrl = join(options.modelBasePath, modelPath || "");
   if (!modelUrl.toLowerCase().endsWith(".json")) modelUrl += ".json";
   const modelPathSegments = modelUrl.includes("/") ? modelUrl.split("/") : modelUrl.split("\\");
@@ -33510,6 +33530,7 @@ async function loadModel(modelPath) {
   const cachedModelName = "indexeddb://" + shortModelName;
   modelStats[shortModelName] = {
     name: shortModelName,
+    loaded: false,
     sizeFromManifest: 0,
     sizeLoadedWeights: 0,
     sizeDesired: models_exports[shortModelName],
@@ -33527,7 +33548,7 @@ async function loadModel(modelPath) {
   modelStats[shortModelName].url = modelStats[shortModelName].inCache ? cachedModelName : modelUrl;
   const tfLoadOptions = typeof fetch === "undefined" ? {} : { fetchFunc: (url, init4) => httpHandler(url, init4) };
   let model23 = new Bl(modelStats[shortModelName].url, tfLoadOptions);
-  let loaded = false;
+  modelStats[shortModelName].loaded = false;
   try {
     model23.findIOHandler();
     if (options.debug) log("model load handler:", model23["handler"]);
@@ -33539,13 +33560,13 @@ async function loadModel(modelPath) {
     modelStats[shortModelName].sizeFromManifest = ((_b = artifacts == null ? void 0 : artifacts.weightData) == null ? void 0 : _b.byteLength) || 0;
     if (artifacts) model23.loadSync(artifacts);
     else model23 = await M8(modelStats[shortModelName].inCache ? cachedModelName : modelUrl, tfLoadOptions);
-    modelStats[shortModelName].sizeLoadedWeights = ((_d2 = (_c2 = model23.artifacts) == null ? void 0 : _c2.weightData) == null ? void 0 : _d2.byteLength) || 0;
+    modelStats[shortModelName].sizeLoadedWeights = ((_d2 = (_c2 = model23.artifacts) == null ? void 0 : _c2.weightData) == null ? void 0 : _d2.byteLength) || ((_f2 = (_e = model23.artifacts) == null ? void 0 : _e.weightData) == null ? void 0 : _f2[0].byteLength) || 0;
     if (options.verbose) log("load:", { model: shortModelName, url: model23["modelUrl"], bytes: modelStats[shortModelName].sizeLoadedWeights });
-    loaded = true;
+    modelStats[shortModelName].loaded = true;
   } catch (err) {
     log("error loading model:", modelUrl, err);
   }
-  if (loaded && options.cacheModels && options.cacheSupported && !modelStats[shortModelName].inCache) {
+  if (modelStats[shortModelName].loaded && options.cacheModels && options.cacheSupported && !modelStats[shortModelName].inCache) {
     try {
       const saveResult = await model23.save(cachedModelName);
       if (options.debug) log("model saved:", cachedModelName, saveResult);
@@ -45381,13 +45402,13 @@ var Models = class {
     let totalSizeWeights = 0;
     let totalSizeLoading = 0;
     for (const m of Object.values(modelStats)) {
-      totalSizeFromManifest += m.sizeFromManifest;
+      totalSizeFromManifest += Number.isNaN(+m.sizeFromManifest) ? 0 : m.sizeFromManifest;
-      totalSizeWeights += m.sizeLoadedWeights;
+      totalSizeWeights += Number.isNaN(+m.sizeLoadedWeights) ? 0 : m.sizeLoadedWeights;
-      totalSizeLoading += m.sizeDesired;
+      totalSizeLoading += Number.isNaN(+m.sizeDesired) ? 0 : m.sizeDesired;
     }
     const percentageLoaded = totalSizeLoading > 0 ? totalSizeWeights / totalSizeLoading : 0;
     return {
-      numLoadedModels: Object.values(modelStats).length,
+      numLoadedModels: Object.values(modelStats).filter((m) => m == null ? void 0 : m.loaded).length,
       numDefinedModels: Object.keys(this.models).length,
       percentageLoaded,
       totalSizeFromManifest,

dist/tfjs.version.js

@@ -4,4 +4,37 @@
   author: <https://github.com/vladmandic>'
 */
 
-var e="4.21.0";var s="4.21.0";var t="4.21.0";var n="4.21.0";var r="4.21.0";var i="4.21.0";var h={tfjs:e,"tfjs-core":e,"tfjs-converter":s,"tfjs-backend-cpu":t,"tfjs-backend-webgl":n,"tfjs-backend-wasm":r,"tfjs-backend-webgpu":i};export{h as version};
+
+// node_modules/.pnpm/@tensorflow+tfjs-core@4.21.0/node_modules/@tensorflow/tfjs-core/package.json
+var version = "4.21.0";
+
+// node_modules/.pnpm/@tensorflow+tfjs-converter@4.21.0_@tensorflow+tfjs-core@4.21.0/node_modules/@tensorflow/tfjs-converter/package.json
+var version2 = "4.21.0";
+
+// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@4.21.0_@tensorflow+tfjs-core@4.21.0/node_modules/@tensorflow/tfjs-backend-cpu/package.json
+var version3 = "4.21.0";
+
+// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@4.21.0_@tensorflow+tfjs-core@4.21.0/node_modules/@tensorflow/tfjs-backend-webgl/package.json
+var version4 = "4.21.0";
+
+// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@4.21.0_@tensorflow+tfjs-core@4.21.0/node_modules/@tensorflow/tfjs-backend-wasm/package.json
+var version5 = "4.21.0";
+
+// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@4.21.0_@tensorflow+tfjs-core@4.21.0/node_modules/@tensorflow/tfjs-backend-webgpu/package.json
+var version6 = "4.21.0";
+
+// tfjs/tf-version.ts
+var version7 = {
+  tfjs: version,
+  "tfjs-core": version,
+  // 'tfjs-data': tfjsDataVersion,
+  // 'tfjs-layers': tfjsLayersVersion,
+  "tfjs-converter": version2,
+  "tfjs-backend-cpu": version3,
+  "tfjs-backend-webgl": version4,
+  "tfjs-backend-wasm": version5,
+  "tfjs-backend-webgpu": version6
+};
+export {
+  version7 as version
+};

src/models.ts

@@ -100,13 +100,13 @@ export class Models {
     let totalSizeWeights = 0;
     let totalSizeLoading = 0;
     for (const m of Object.values(modelStats)) {
-      totalSizeFromManifest += m.sizeFromManifest;
+      totalSizeFromManifest += Number.isNaN(+m.sizeFromManifest) ? 0 : m.sizeFromManifest;
-      totalSizeWeights += m.sizeLoadedWeights;
+      totalSizeWeights += Number.isNaN(+m.sizeLoadedWeights) ? 0 : m.sizeLoadedWeights;
-      totalSizeLoading += m.sizeDesired;
+      totalSizeLoading += Number.isNaN(+m.sizeDesired) ? 0 : m.sizeDesired;
     }
     const percentageLoaded = totalSizeLoading > 0 ? totalSizeWeights / totalSizeLoading : 0;
     return {
-      numLoadedModels: Object.values(modelStats).length,
+      numLoadedModels: Object.values(modelStats).filter((m) => m?.loaded).length,
       numDefinedModels: Object.keys(this.models).length,
       percentageLoaded,
       totalSizeFromManifest,

src/tfjs/load.ts

@@ -14,6 +14,7 @@ const options = {
 
 export interface ModelInfo {
   name: string,
+  loaded: boolean,
   inCache: boolean,
   sizeDesired: number,
   sizeFromManifest: number,
@@ -42,6 +43,7 @@ export async function loadModel(modelPath: string | undefined): Promise<GraphMod
   const cachedModelName = 'indexeddb://' + shortModelName; // generate short model name for cache
   modelStats[shortModelName] = {
     name: shortModelName,
+    loaded: false,
     sizeFromManifest: 0,
     sizeLoadedWeights: 0,
     sizeDesired: modelsDefs[shortModelName],
@@ -59,7 +61,7 @@ export async function loadModel(modelPath: string | undefined): Promise<GraphMod
   modelStats[shortModelName].url = modelStats[shortModelName].inCache ? cachedModelName : modelUrl;
   const tfLoadOptions = typeof fetch === 'undefined' ? {} : { fetchFunc: (url: string, init?: RequestInit) => httpHandler(url, init) };
   let model: GraphModel = new tf.GraphModel(modelStats[shortModelName].url, tfLoadOptions) as unknown as GraphModel; // create model prototype and decide if load from cache or from original modelurl
-  let loaded = false;
+  modelStats[shortModelName].loaded = false;
   try {
     // @ts-ignore private function
     model.findIOHandler(); // decide how to actually load a model
@@ -74,13 +76,13 @@ export async function loadModel(modelPath: string | undefined): Promise<GraphMod
     if (artifacts) model.loadSync(artifacts); // load weights
     else model = await tf.loadGraphModel(modelStats[shortModelName].inCache ? cachedModelName : modelUrl, tfLoadOptions) as unknown as GraphModel;
     // @ts-ignore private property
-    modelStats[shortModelName].sizeLoadedWeights = model.artifacts?.weightData?.byteLength || 0;
+    modelStats[shortModelName].sizeLoadedWeights = model.artifacts?.weightData?.byteLength || model.artifacts?.weightData?.[0].byteLength || 0;
     if (options.verbose) log('load:', { model: shortModelName, url: model['modelUrl'], bytes: modelStats[shortModelName].sizeLoadedWeights });
-    loaded = true;
+    modelStats[shortModelName].loaded = true;
   } catch (err) {
     log('error loading model:', modelUrl, err);
   }
-  if (loaded && options.cacheModels && options.cacheSupported && !modelStats[shortModelName].inCache) { // save model to cache
+  if (modelStats[shortModelName].loaded && options.cacheModels && options.cacheSupported && !modelStats[shortModelName].inCache) { // save model to cache
     try {
       const saveResult = await model.save(cachedModelName);
       if (options.debug) log('model saved:', cachedModelName, saveResult);