diff --git a/CHANGELOG.md b/CHANGELOG.md
index 86682e07..15d1d0eb 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,7 +9,7 @@
   
 ## Changelog
   
-### **HEAD -> main** 2022/06/10 mandic00@live.com
+### **HEAD -> main** 2022/06/21 mandic00@live.com
 
 
 ### **release: 2.8.1** 2022/06/08 mandic00@live.com
diff --git a/demo/typescript/index.js.map b/demo/typescript/index.js.map
index faad7e91..16dcc14f 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 { Human, Config } from '../../dist/human.esm.js'; // equivalent of @vladmandic/Human\n\nconst humanConfig: Partial<Config> = { // user configuration for human, used to fine-tune behavior\n  // backend: 'webgpu' as const,\n  // wasmPath: 'https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@3.18.0/dist/',\n  // cacheSensitivity: 0,\n  async: true,\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  gesture: { enabled: true },\n};\n\nconst human = new 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('status') as HTMLPreElement,\n  perf: document.getElementById('performance') as HTMLDivElement,\n};\nconst timestamp = { detect: 0, draw: 0, tensors: 0 }; // holds information used to calculate performance and possible memory leaks\nconst fps = { detect: 0, draw: 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  // eslint-disable-next-line no-console\n  console.log(...msg);\n};\nconst status = (msg) => dom.fps.innerText = msg; // print status element\nconst perf = (msg) => dom.perf.innerText = 'tensors:' + human.tf.memory().numTensors + ' | performance: ' + JSON.stringify(msg).replace(/\"|{|}/g, '').replace(/,/g, ' | '); // print performance element\n\nasync function webCam() { // initialize webcam\n  status('starting webcam...');\n  // @ts-ignore resizeMode is not yet defined in tslib\n  const options: MediaStreamConstraints = { audio: false, video: { facingMode: 'user', resizeMode: 'none', width: { ideal: document.body.clientWidth }, height: { ideal: document.body.clientHeight } } };\n  const stream: MediaStream = await navigator.mediaDevices.getUserMedia(options);\n  const ready = new Promise((resolve) => { dom.video.onloadeddata = () => resolve(true); });\n  dom.video.srcObject = stream;\n  dom.video.play();\n  await ready;\n  dom.canvas.width = dom.video.videoWidth;\n  dom.canvas.height = dom.video.videoHeight;\n  const track: MediaStreamTrack = stream.getVideoTracks()[0];\n  const capabilities: MediaTrackCapabilities | string = track.getCapabilities ? track.getCapabilities() : '';\n  const settings: MediaTrackSettings | string = track.getSettings ? track.getSettings() : '';\n  const constraints: MediaTrackConstraints | string = track.getConstraints ? track.getConstraints() : '';\n  log('video:', dom.video.videoWidth, dom.video.videoHeight, track.label, { stream, track, settings, constraints, capabilities });\n  dom.canvas.onclick = () => { // pause when clicked on screen and resume on next click\n    if (dom.video.paused) dom.video.play();\n    else dom.video.pause();\n  };\n}\n\nasync function detectionLoop() { // main detection loop\n  if (!dom.video.paused) {\n    // console.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  }\n  const now = human.now();\n  fps.detect = 1000 / (now - timestamp.detect);\n  timestamp.detect = 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 = await human.next(human.result); // smoothen result using last-known results\n    if (human.config.filter.flip) await human.draw.canvas(interpolated.canvas as HTMLCanvasElement, dom.canvas); // draw processed image to screen canvas\n    else await 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.draw = 1000 / (now - timestamp.draw);\n  timestamp.draw = now;\n  status(dom.video.paused ? 'paused' : `fps: ${fps.detect.toFixed(1).padStart(5, ' ')} detect | ${fps.draw.toFixed(1).padStart(5, ' ')} draw`); // write status\n  // requestAnimationFrame(drawLoop); // refresh at screen refresh rate\n  setTimeout(drawLoop, 30); // use to slow down refresh from max refresh rate to target of 30 fps\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('loaded models:', 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"],
+  "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 { Human, Config } from '../../dist/human.esm.js'; // equivalent of @vladmandic/Human\n\nconst humanConfig: Partial<Config> = { // user configuration for human, used to fine-tune behavior\n  // backend: 'wasm' as const,\n  // wasmPath: 'https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@3.18.0/dist/',\n  // cacheSensitivity: 0,\n  async: true,\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  gesture: { enabled: true },\n};\n\nconst human = new 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('status') as HTMLPreElement,\n  perf: document.getElementById('performance') as HTMLDivElement,\n};\nconst timestamp = { detect: 0, draw: 0, tensors: 0 }; // holds information used to calculate performance and possible memory leaks\nconst fps = { detect: 0, draw: 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  // eslint-disable-next-line no-console\n  console.log(...msg);\n};\nconst status = (msg) => dom.fps.innerText = msg; // print status element\nconst perf = (msg) => dom.perf.innerText = 'tensors:' + human.tf.memory().numTensors + ' | performance: ' + JSON.stringify(msg).replace(/\"|{|}/g, '').replace(/,/g, ' | '); // print performance element\n\nasync function webCam() { // initialize webcam\n  status('starting webcam...');\n  // @ts-ignore resizeMode is not yet defined in tslib\n  const options: MediaStreamConstraints = { audio: false, video: { facingMode: 'user', resizeMode: 'none', width: { ideal: document.body.clientWidth }, height: { ideal: document.body.clientHeight } } };\n  const stream: MediaStream = await navigator.mediaDevices.getUserMedia(options);\n  const ready = new Promise((resolve) => { dom.video.onloadeddata = () => resolve(true); });\n  dom.video.srcObject = stream;\n  dom.video.play();\n  await ready;\n  dom.canvas.width = dom.video.videoWidth;\n  dom.canvas.height = dom.video.videoHeight;\n  const track: MediaStreamTrack = stream.getVideoTracks()[0];\n  const capabilities: MediaTrackCapabilities | string = track.getCapabilities ? track.getCapabilities() : '';\n  const settings: MediaTrackSettings | string = track.getSettings ? track.getSettings() : '';\n  const constraints: MediaTrackConstraints | string = track.getConstraints ? track.getConstraints() : '';\n  log('video:', dom.video.videoWidth, dom.video.videoHeight, track.label, { stream, track, settings, constraints, capabilities });\n  dom.canvas.onclick = () => { // pause when clicked on screen and resume on next click\n    if (dom.video.paused) dom.video.play();\n    else dom.video.pause();\n  };\n}\n\nasync function detectionLoop() { // main detection loop\n  if (!dom.video.paused) {\n    // console.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  }\n  const now = human.now();\n  fps.detect = 1000 / (now - timestamp.detect);\n  timestamp.detect = 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 = await human.next(human.result); // smoothen result using last-known results\n    if (human.config.filter.flip) await human.draw.canvas(interpolated.canvas as HTMLCanvasElement, dom.canvas); // draw processed image to screen canvas\n    else await 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.draw = 1000 / (now - timestamp.draw);\n  timestamp.draw = now;\n  status(dom.video.paused ? 'paused' : `fps: ${fps.detect.toFixed(1).padStart(5, ' ')} detect | ${fps.draw.toFixed(1).padStart(5, ' ')} draw`); // write status\n  // requestAnimationFrame(drawLoop); // refresh at screen refresh rate\n  setTimeout(drawLoop, 30); // use to slow down refresh from max refresh rate to target of 30 fps\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('loaded models:', 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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diff --git a/demo/typescript/index.ts b/demo/typescript/index.ts
index e0d27f04..978999b1 100644
--- a/demo/typescript/index.ts
+++ b/demo/typescript/index.ts
@@ -10,7 +10,7 @@
 import { Human, Config } from '../../dist/human.esm.js'; // equivalent of @vladmandic/Human
 
 const humanConfig: Partial<Config> = { // user configuration for human, used to fine-tune behavior
-  // backend: 'webgpu' as const,
+  // backend: 'wasm' as const,
   // wasmPath: 'https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@3.18.0/dist/',
   // cacheSensitivity: 0,
   async: true,
diff --git a/src/face/faceboxes.ts b/src/face/faceboxes.ts
index cf84b56d..d3377933 100644
--- a/src/face/faceboxes.ts
+++ b/src/face/faceboxes.ts
@@ -2,6 +2,7 @@
 
 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';
 
@@ -56,7 +57,7 @@ export class FaceBoxes {
 }
 
 export async function load(config) {
-  const model = await tf.loadGraphModel(config.face.detector.modelPath);
+  const model = await loadModel(config.face.detector?.modelPath);
   if (config.debug) log(`load model: ${config.face.detector.modelPath.match(/\/(.*)\./)[1]}`);
   const faceboxes = new FaceBoxes(model, config);
   if (config.face.mesh.enabled && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\/(.*)\./)[1]}`);
diff --git a/src/human.ts b/src/human.ts
index d8224aea..d8a6dd02 100644
--- a/src/human.ts
+++ b/src/human.ts
@@ -329,6 +329,9 @@ export class Human {
     return interpolate.calc(result, this.config) as Result;
   }
 
+  /** get model loading/loaded stats */
+  getModelStats = () => models.getModelStats();
+
   /** Warmup method pre-initializes all configured models for faster inference
    * - can take significant time on startup
    * - only used for `webgl` and `humangl` backends
diff --git a/src/models.ts b/src/models.ts
index 922122be..ce497569 100644
--- a/src/models.ts
+++ b/src/models.ts
@@ -24,6 +24,7 @@ import * as movenet from './body/movenet';
 import * as nanodet from './object/nanodet';
 import * as posenet from './body/posenet';
 import * as segmentation from './segmentation/segmentation';
+import { modelStats } from './tfjs/load';
 import type { GraphModel } from './tfjs/types';
 import type { Human } from './human';
 
@@ -58,6 +59,16 @@ export class Models {
   antispoof: null | GraphModel | Promise<GraphModel> = null;
 }
 
+export const getModelStats = () => {
+  let sizeManifest = 0;
+  let sizeWeights = 0;
+  for (const m of Object.values(modelStats)) {
+    sizeManifest += m.manifest;
+    sizeWeights += m.weights;
+  }
+  return { sizeManifest, sizeWeights, numModels: Object.values(modelStats).length };
+};
+
 export function reset(instance: Human): void {
   // if (instance.config.debug) log('resetting loaded models');
   for (const model of Object.keys(instance.models)) instance.models[model as keyof Models] = null;
@@ -67,8 +78,12 @@ export function reset(instance: Human): void {
 export async function load(instance: Human): Promise<void> {
   if (env.initial) reset(instance);
   if (instance.config.hand.enabled) { // handpose model is a combo that must be loaded as a whole
-    if (!instance.models.handpose && instance.config.hand.detector?.modelPath?.includes('handdetect')) [instance.models.handpose, instance.models.handskeleton] = await handpose.load(instance.config);
-    if (!instance.models.handskeleton && instance.config.hand.landmarks && instance.config.hand.detector?.modelPath?.includes('handdetect')) [instance.models.handpose, instance.models.handskeleton] = await handpose.load(instance.config);
+    if (!instance.models.handpose && instance.config.hand.detector?.modelPath?.includes('handdetect')) {
+      [instance.models.handpose, instance.models.handskeleton] = await handpose.load(instance.config);
+    }
+    if (!instance.models.handskeleton && instance.config.hand.landmarks && instance.config.hand.detector?.modelPath?.includes('handdetect')) {
+      [instance.models.handpose, instance.models.handskeleton] = await handpose.load(instance.config);
+    }
   }
   if (instance.config.body.enabled && !instance.models.blazepose && instance.config.body?.modelPath?.includes('blazepose')) instance.models.blazepose = blazepose.loadPose(instance.config);
   // @ts-ignore optional model
@@ -99,7 +114,9 @@ export async function load(instance: Human): Promise<void> {
 
   // models are loaded in parallel asynchronously so lets wait until they are actually loaded
   for await (const model of Object.keys(instance.models)) {
-    if (instance.models[model as keyof Models] && typeof instance.models[model as keyof Models] !== 'undefined') instance.models[model as keyof Models] = await instance.models[model as keyof Models];
+    if (instance.models[model as keyof Models] && typeof instance.models[model as keyof Models] !== 'undefined') {
+      instance.models[model as keyof Models] = await instance.models[model as keyof Models];
+    }
   }
 }
 
diff --git a/src/tfjs/load.ts b/src/tfjs/load.ts
index 751c6826..94a79ed0 100644
--- a/src/tfjs/load.ts
+++ b/src/tfjs/load.ts
@@ -10,6 +10,15 @@ const options = {
   modelBasePath: '',
 };
 
+type ModelStats = {
+  name: string,
+  cached: boolean,
+  manifest: number,
+  weights: number,
+}
+
+export const modelStats: Record<string, ModelStats> = {};
+
 async function httpHandler(url, init?): Promise<Response | null> {
   if (options.debug) log('load model fetch:', url, init);
   return fetch(url, init);
@@ -25,26 +34,35 @@ export async function loadModel(modelPath: string | undefined): Promise<GraphMod
   let modelUrl = join(options.modelBasePath, modelPath || '');
   if (!modelUrl.toLowerCase().endsWith('.json')) modelUrl += '.json';
   const modelPathSegments = modelUrl.split('/');
-  const cachedModelName = 'indexeddb://' + modelPathSegments[modelPathSegments.length - 1].replace('.json', ''); // generate short model name for cache
+  const shortModelName = modelPathSegments[modelPathSegments.length - 1].replace('.json', '');
+  const cachedModelName = 'indexeddb://' + shortModelName; // generate short model name for cache
+  modelStats[shortModelName] = {
+    name: shortModelName,
+    manifest: 0,
+    weights: 0,
+    cached: false,
+  };
   const cachedModels = await tf.io.listModels(); // list all models already in cache
-  const modelCached = options.cacheModels && Object.keys(cachedModels).includes(cachedModelName); // is model found in cache
+  modelStats[shortModelName].cached = options.cacheModels && Object.keys(cachedModels).includes(cachedModelName); // is model found in cache
   const tfLoadOptions = typeof fetch === 'undefined' ? {} : { fetchFunc: (url, init?) => httpHandler(url, init) };
-  const model: GraphModel = new tf.GraphModel(modelCached ? cachedModelName : modelUrl, tfLoadOptions) as unknown as GraphModel; // create model prototype and decide if load from cache or from original modelurl
+  const model: GraphModel = new tf.GraphModel(modelStats[shortModelName].cached ? cachedModelName : modelUrl, tfLoadOptions) as unknown as GraphModel; // create model prototype and decide if load from cache or from original modelurl
   let loaded = false;
   try {
     // @ts-ignore private function
     model.findIOHandler(); // decide how to actually load a model
-    // @ts-ignore private property
-    if (options.debug) log('model load handler:', model.handler);
+    if (options.debug) log('model load handler:', model['handler']);
     // @ts-ignore private property
     const artifacts = await model.handler.load(); // load manifest
+    modelStats[shortModelName].manifest = artifacts?.weightData?.byteLength || 0;
     model.loadSync(artifacts); // load weights
-    if (options.verbose) log('load model:', model['modelUrl']);
+    // @ts-ignore private property
+    modelStats[shortModelName].weights = model?.artifacts?.weightData?.byteLength || 0;
+    if (options.verbose) log('load model:', model['modelUrl'], { bytes: modelStats[shortModelName].weights });
     loaded = true;
   } catch (err) {
     log('error loading model:', modelUrl, err);
   }
-  if (loaded && options.cacheModels && !modelCached) { // save model to cache
+  if (loaded && options.cacheModels && !modelStats[shortModelName].cached) { // save model to cache
     try {
       const saveResult = await model.save(cachedModelName);
       log('model saved:', cachedModelName, saveResult);
diff --git a/test/build.log b/test/build.log
index e45cb8a0..3a63a854 100644
--- a/test/build.log
+++ b/test/build.log
@@ -1,24 +1,24 @@
-2022-06-21 13:20:54 INFO:  Application: {"name":"@vladmandic/human","version":"2.8.1"} 
-2022-06-21 13:20:54 INFO:  Environment: {"profile":"production","config":".build.json","package":"package.json","tsconfig":true,"eslintrc":true,"git":true} 
-2022-06-21 13:20:54 INFO:  Toolchain: {"build":"0.7.3","esbuild":"0.14.47","typescript":"4.7.4","typedoc":"0.22.17","eslint":"8.18.0"} 
-2022-06-21 13:20:54 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]} 
-2022-06-21 13:20:54 STATE: Clean: {"locations":["dist/*","types/lib/*","typedoc/*"]} 
-2022-06-21 13:20:54 STATE: Compile: {"name":"tfjs/nodejs/cpu","format":"cjs","platform":"node","input":"tfjs/tf-node.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":102,"outputBytes":608} 
-2022-06-21 13:20:54 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":73,"inputBytes":642839,"outputBytes":300711} 
-2022-06-21 13:20:54 STATE: Compile: {"name":"tfjs/nodejs/gpu","format":"cjs","platform":"node","input":"tfjs/tf-node-gpu.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":110,"outputBytes":612} 
-2022-06-21 13:20:54 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":73,"inputBytes":642843,"outputBytes":300715} 
-2022-06-21 13:20:54 STATE: Compile: {"name":"tfjs/nodejs/wasm","format":"cjs","platform":"node","input":"tfjs/tf-node-wasm.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":149,"outputBytes":664} 
-2022-06-21 13:20:54 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":73,"inputBytes":642895,"outputBytes":300765} 
-2022-06-21 13:20:54 STATE: Compile: {"name":"tfjs/browser/version","format":"esm","platform":"browser","input":"tfjs/tf-version.ts","output":"dist/tfjs.version.js","files":1,"inputBytes":1069,"outputBytes":371} 
-2022-06-21 13:20:54 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":1045,"outputBytes":596} 
-2022-06-21 13:20:54 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":73,"inputBytes":642827,"outputBytes":299608} 
-2022-06-21 13:20:55 STATE: Compile: {"name":"tfjs/browser/esm/custom","format":"esm","platform":"browser","input":"tfjs/tf-custom.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":110,"outputBytes":1353541} 
-2022-06-21 13:20:55 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":73,"inputBytes":1995772,"outputBytes":1652210} 
-2022-06-21 13:20:55 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":73,"inputBytes":1995772,"outputBytes":2139073} 
-2022-06-21 13:21:07 STATE: Typings: {"input":"src/human.ts","output":"types/lib","files":116} 
-2022-06-21 13:21:13 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":73,"generated":true} 
-2022-06-21 13:21:13 STATE: Compile: {"name":"demo/typescript","format":"esm","platform":"browser","input":"demo/typescript/index.ts","output":"demo/typescript/index.js","files":1,"inputBytes":6326,"outputBytes":3070} 
-2022-06-21 13:21:13 STATE: Compile: {"name":"demo/faceid","format":"esm","platform":"browser","input":"demo/faceid/index.ts","output":"demo/faceid/index.js","files":2,"inputBytes":15174,"outputBytes":7833} 
-2022-06-21 13:22:08 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":106,"errors":0,"warnings":0} 
-2022-06-21 13:22:08 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"} 
-2022-06-21 13:22:08 INFO:  Done... 
+2022-07-02 03:34:20 INFO:  Application: {"name":"@vladmandic/human","version":"2.8.1"} 
+2022-07-02 03:34:20 INFO:  Environment: {"profile":"production","config":".build.json","package":"package.json","tsconfig":true,"eslintrc":true,"git":true} 
+2022-07-02 03:34:20 INFO:  Toolchain: {"build":"0.7.3","esbuild":"0.14.47","typescript":"4.7.4","typedoc":"0.22.17","eslint":"8.18.0"} 
+2022-07-02 03:34:20 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]} 
+2022-07-02 03:34:20 STATE: Clean: {"locations":["dist/*","types/lib/*","typedoc/*"]} 
+2022-07-02 03:34:20 STATE: Compile: {"name":"tfjs/nodejs/cpu","format":"cjs","platform":"node","input":"tfjs/tf-node.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":102,"outputBytes":608} 
+2022-07-02 03:34:21 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":73,"inputBytes":643891,"outputBytes":301229} 
+2022-07-02 03:34:21 STATE: Compile: {"name":"tfjs/nodejs/gpu","format":"cjs","platform":"node","input":"tfjs/tf-node-gpu.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":110,"outputBytes":612} 
+2022-07-02 03:34:21 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":73,"inputBytes":643895,"outputBytes":301233} 
+2022-07-02 03:34:21 STATE: Compile: {"name":"tfjs/nodejs/wasm","format":"cjs","platform":"node","input":"tfjs/tf-node-wasm.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":149,"outputBytes":664} 
+2022-07-02 03:34:21 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":73,"inputBytes":643947,"outputBytes":301283} 
+2022-07-02 03:34:21 STATE: Compile: {"name":"tfjs/browser/version","format":"esm","platform":"browser","input":"tfjs/tf-version.ts","output":"dist/tfjs.version.js","files":1,"inputBytes":1069,"outputBytes":371} 
+2022-07-02 03:34:21 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":1045,"outputBytes":596} 
+2022-07-02 03:34:21 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":73,"inputBytes":643879,"outputBytes":300126} 
+2022-07-02 03:34:21 STATE: Compile: {"name":"tfjs/browser/esm/custom","format":"esm","platform":"browser","input":"tfjs/tf-custom.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":110,"outputBytes":1353541} 
+2022-07-02 03:34:21 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":73,"inputBytes":1996824,"outputBytes":1652733} 
+2022-07-02 03:34:21 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":73,"inputBytes":1996824,"outputBytes":2140101} 
+2022-07-02 03:34:36 STATE: Typings: {"input":"src/human.ts","output":"types/lib","files":116} 
+2022-07-02 03:34:44 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":73,"generated":true} 
+2022-07-02 03:34:44 STATE: Compile: {"name":"demo/typescript","format":"esm","platform":"browser","input":"demo/typescript/index.ts","output":"demo/typescript/index.js","files":1,"inputBytes":6324,"outputBytes":3070} 
+2022-07-02 03:34:44 STATE: Compile: {"name":"demo/faceid","format":"esm","platform":"browser","input":"demo/faceid/index.ts","output":"demo/faceid/index.js","files":2,"inputBytes":15174,"outputBytes":7833} 
+2022-07-02 03:35:04 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":106,"errors":0,"warnings":0} 
+2022-07-02 03:35:05 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"} 
+2022-07-02 03:35:05 INFO:  Done...