diff --git a/CHANGELOG.md b/CHANGELOG.md
index df256aee..2b82938c 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,6 +1,6 @@
 # @vladmandic/human  
 
-  Version: **2.6.5**  
+  Version: **2.7.0**  
   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>**  
@@ -9,8 +9,9 @@
   
 ## Changelog
   
-### **HEAD -> main** 2022/04/05 mandic00@live.com
+### **HEAD -> main** 2022/04/10 mandic00@live.com
 
+- rebuild
 
 ### **2.6.5** 2022/04/01 mandic00@live.com
 
diff --git a/demo/typescript/index.html b/demo/typescript/index.html
index a74a14bc..47296bfb 100644
--- a/demo/typescript/index.html
+++ b/demo/typescript/index.html
@@ -25,6 +25,6 @@
     <video id="video" playsinline style="display: none"></video>
     <pre id="status" style="position: absolute; top: 12px; right: 20px; background-color: grey; padding: 8px; box-shadow: 2px 2px black"></pre>
     <pre id="log" style="padding: 8px"></pre>
-    <div id="performance" style="position: absolute; bottom: 0; width: 100%; padding: 8px; font-size: 0.8rem;"></div>
+    <div id="performance" style="position: absolute; bottom: 1rem; width: 100%; padding: 8px; font-size: 0.8rem;"></div>
   </body>
 </html>
diff --git a/demo/typescript/index.js b/demo/typescript/index.js
index 24d94078..d1025ce8 100644
--- a/demo/typescript/index.js
+++ b/demo/typescript/index.js
@@ -4,8 +4,8 @@
   author: <https://github.com/vladmandic>'
 */
 
-import{Human as p}from"../../dist/human.esm.js";var w={modelBasePath:"../../models",filter:{enabled:!0,equalization:!1},face:{enabled:!0,detector:{rotation:!1},mesh:{enabled:!0},iris:{enabled:!0},description:{enabled:!0},emotion:{enabled:!0}},body:{enabled:!0},hand:{enabled:!0},object:{enabled:!0},gesture:{enabled:!0}},t=new p(w);t.env.perfadd=!1;t.draw.options.font='small-caps 18px "Lato"';t.draw.options.lineHeight=20;var e={video:document.getElementById("video"),canvas:document.getElementById("canvas"),log:document.getElementById("log"),fps:document.getElementById("status"),perf:document.getElementById("performance")},i={detect:0,draw:0,tensors:0},d={detect:0,draw:0},s=(...a)=>{e.log.innerText+=a.join(" ")+`
-`,console.log(...a)},r=a=>e.fps.innerText=a,b=a=>e.perf.innerText="tensors:"+t.tf.memory().numTensors+" | performance: "+JSON.stringify(a).replace(/"|{|}/g,"").replace(/,/g," | ");async function h(){r("starting webcam...");let a={audio:!1,video:{facingMode:"user",resizeMode:"none",width:{ideal:document.body.clientWidth}}},n=await navigator.mediaDevices.getUserMedia(a),m=new Promise(f=>{e.video.onloadeddata=()=>f(!0)});e.video.srcObject=n,e.video.play(),await m,e.canvas.width=e.video.videoWidth,e.canvas.height=e.video.videoHeight;let o=n.getVideoTracks()[0],u=o.getCapabilities?o.getCapabilities():"",v=o.getSettings?o.getSettings():"",g=o.getConstraints?o.getConstraints():"";s("video:",e.video.videoWidth,e.video.videoHeight,o.label,{stream:n,track:o,settings:v,constraints:g,capabilities:u}),e.canvas.onclick=()=>{e.video.paused?e.video.play():e.video.pause()}}async function c(){if(!e.video.paused){await t.detect(e.video);let n=t.tf.memory().numTensors;n-i.tensors!==0&&s("allocated tensors:",n-i.tensors),i.tensors=n}let a=t.now();d.detect=1e3/(a-i.detect),i.detect=a,requestAnimationFrame(c)}async function l(){if(!e.video.paused){let n=await t.next(t.result);await t.draw.canvas(e.video,e.canvas),await t.draw.all(e.canvas,n),b(n.performance)}let a=t.now();d.draw=1e3/(a-i.draw),i.draw=a,r(e.video.paused?"paused":`fps: ${d.detect.toFixed(1).padStart(5," ")} detect | ${d.draw.toFixed(1).padStart(5," ")} draw`),setTimeout(l,30)}async function y(){s("human version:",t.version,"| tfjs version:",t.tf.version["tfjs-core"]),s("platform:",t.env.platform,"| agent:",t.env.agent),r("loading..."),await t.load(),s("backend:",t.tf.getBackend(),"| available:",t.env.backends),s("loaded models:",Object.values(t.models).filter(a=>a!==null).length),r("initializing..."),await t.warmup(),await h(),await c(),await l()}window.onload=y;
+import{Human as p}from"../../dist/human.esm.js";var w={modelBasePath:"../../models",filter:{enabled:!0,equalization:!1},cacheSensitivity:0,face:{enabled:!0,detector:{rotation:!1},mesh:{enabled:!0},attention:{enabled:!1},iris:{enabled:!0},description:{enabled:!0},emotion:{enabled:!0}},body:{enabled:!0},hand:{enabled:!0},object:{enabled:!0},gesture:{enabled:!0}},t=new p(w);t.env.perfadd=!1;t.draw.options.font='small-caps 18px "Lato"';t.draw.options.lineHeight=20;var e={video:document.getElementById("video"),canvas:document.getElementById("canvas"),log:document.getElementById("log"),fps:document.getElementById("status"),perf:document.getElementById("performance")},i={detect:0,draw:0,tensors:0},d={detect:0,draw:0},s=(...a)=>{e.log.innerText+=a.join(" ")+`
+`,console.log(...a)},r=a=>e.fps.innerText=a,b=a=>e.perf.innerText="tensors:"+t.tf.memory().numTensors+" | performance: "+JSON.stringify(a).replace(/"|{|}/g,"").replace(/,/g," | ");async function h(){r("starting webcam...");let a={audio:!1,video:{facingMode:"user",resizeMode:"none",width:{ideal:document.body.clientWidth}}},n=await navigator.mediaDevices.getUserMedia(a),m=new Promise(f=>{e.video.onloadeddata=()=>f(!0)});e.video.srcObject=n,e.video.play(),await m,e.canvas.width=e.video.videoWidth,e.canvas.height=e.video.videoHeight;let o=n.getVideoTracks()[0],v=o.getCapabilities?o.getCapabilities():"",u=o.getSettings?o.getSettings():"",g=o.getConstraints?o.getConstraints():"";s("video:",e.video.videoWidth,e.video.videoHeight,o.label,{stream:n,track:o,settings:u,constraints:g,capabilities:v}),e.canvas.onclick=()=>{e.video.paused?e.video.play():e.video.pause()}}async function c(){if(!e.video.paused){await t.detect(e.video);let n=t.tf.memory().numTensors;n-i.tensors!==0&&s("allocated tensors:",n-i.tensors),i.tensors=n}let a=t.now();d.detect=1e3/(a-i.detect),i.detect=a,requestAnimationFrame(c)}async function l(){if(!e.video.paused){let n=await t.next(t.result);await t.draw.canvas(e.video,e.canvas),await t.draw.all(e.canvas,n),b(n.performance)}let a=t.now();d.draw=1e3/(a-i.draw),i.draw=a,r(e.video.paused?"paused":`fps: ${d.detect.toFixed(1).padStart(5," ")} detect | ${d.draw.toFixed(1).padStart(5," ")} draw`),setTimeout(l,30)}async function y(){s("human version:",t.version,"| tfjs version:",t.tf.version["tfjs-core"]),s("platform:",t.env.platform,"| agent:",t.env.agent),r("loading..."),await t.load(),s("backend:",t.tf.getBackend(),"| available:",t.env.backends),s("loaded models:",Object.values(t.models).filter(a=>a!==null).length),r("initializing..."),await t.warmup(),await h(),await c(),await l()}window.onload=y;
 /**
  * Human demo for browsers
  * @default Human Library
diff --git a/demo/typescript/index.js.map b/demo/typescript/index.js.map
index 518c681f..3c244fca 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  // async: true,\n  modelBasePath: '../../models',\n  filter: { enabled: true, equalization: false },\n  face: { enabled: true, detector: { rotation: false }, mesh: { enabled: true }, iris: { enabled: true }, description: { enabled: true }, emotion: { enabled: true } },\n  body: { enabled: true },\n  hand: { enabled: true },\n  object: { enabled: true },\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 } } };\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    await 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    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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+  "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  // async: true,\n  modelBasePath: '../../models',\n  filter: { enabled: true, equalization: false },\n  cacheSensitivity: 0,\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: true },\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 } } };\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    await 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    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 25c77d9b..1e0a3406 100644
--- a/demo/typescript/index.ts
+++ b/demo/typescript/index.ts
@@ -14,7 +14,8 @@ const humanConfig: Partial<Config> = { // user configuration for human, used to
   // async: true,
   modelBasePath: '../../models',
   filter: { enabled: true, equalization: false },
-  face: { enabled: true, detector: { rotation: false }, mesh: { enabled: true }, iris: { enabled: true }, description: { enabled: true }, emotion: { enabled: true } },
+  cacheSensitivity: 0,
+  face: { enabled: true, detector: { rotation: false }, mesh: { enabled: true }, attention: { enabled: false }, iris: { enabled: true }, description: { enabled: true }, emotion: { enabled: true } },
   body: { enabled: true },
   hand: { enabled: true },
   object: { enabled: true },
diff --git a/models/facemesh-attention.bin b/models/facemesh-attention.bin
new file mode 100644
index 00000000..82e7786b
Binary files /dev/null and b/models/facemesh-attention.bin differ
diff --git a/models/facemesh-attention.json b/models/facemesh-attention.json
new file mode 100644
index 00000000..27bf7f9f
--- /dev/null
+++ b/models/facemesh-attention.json
@@ -0,0 +1,1351 @@
+{
+  "format": "graph-model",
+  "generatedBy": "https://github.com/google/mediapipe",
+  "convertedBy": "https://github.com/vladmandic",
+  "signature":
+  {
+      "inputs":
+      {
+          "input_1": {"name":"input_1:0","dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"192"},{"size":"192"},{"size":"3"}]}}
+      },
+      "outputs":
+      {
+          "output_left_eye:0": {"name":"output_left_eye:0","dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"1"},{"size":"142"}]}},
+          "output_right_iris:0": {"name":"output_right_iris:0","dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"1"},{"size":"10"}]}},
+          "output_mesh_identity": {"name":"output_mesh_identity:0","dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"1"},{"size":"1404"}]}},
+          "output_left_iris:0": {"name":"output_left_iris:0","dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"1"},{"size":"10"}]}},
+          "conv_faceflag": {"name":"conv_faceflag:0","dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"1"},{"size":"1"}]}},
+          "output_lips": {"name":"output_lips:0","dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"1"},{"size":"160"}]}},
+          "output_right_eye:0": {"name":"output_right_eye:0","dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"1"},{"size":"142"}]}}
+      }
+  },
+  "modelTopology":
+  {
+      "node":
+      [
+          {"name":"Conv2D_94/filter","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"32"},{"size":"1"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"conv_faceflag/y","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"p_re_lu_45/Alpha_dequantize_prelu/Neg","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"32"}]}}}}},
+          {"name":"conv2d_45_1/y","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"32"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"p_re_lu_44/Alpha_dequantize_prelu/Neg","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"32"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"p_re_lu_43/Alpha_dequantize_prelu/Neg","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"128"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"conv2d_43_1/y","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"128"}]}}}}},
+          {"name":"p_re_lu_42/Alpha_dequantize_prelu/Neg","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"128"}]}}}}},
+          {"name":"conv2d_42_1/y","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"128"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"p_re_lu_41/Alpha_dequantize_prelu/Neg","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"128"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"conv2d_41_1/y","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"128"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"p_re_lu_40/Alpha_dequantize_prelu/Neg","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"128"}]}}}}},
+          {"name":"conv2d_40_1/y","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"128"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"p_re_lu_39/Alpha_dequantize_prelu/Neg","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"128"}]}}}}},
+          {"name":"conv2d_39_1/y","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"128"}]}}}}},
+          {"name":"depthwise_37/filter_in","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"128"},{"size":"1"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"Conv2D_45/filter","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"128"},{"size":"128"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"depthwise_42/filter_in","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"128"},{"size":"1"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"Conv2D_50/filter","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"128"},{"size":"128"}]}}}}},
+          {"name":"depthwise_47/filter_in","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"128"},{"size":"1"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"Conv2D_63/filter","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"128"},{"size":"128"}]}}}}},
+          {"name":"depthwise_52/filter_in","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"128"},{"size":"1"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"Conv2D_70/filter","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"128"},{"size":"128"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"depthwise_57/filter_in","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"128"},{"size":"1"}]}}}}},
+          {"name":"Conv2D_75/filter","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"128"},{"size":"128"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"Conv2D_80/filter","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"128"},{"size":"32"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"conv2d_44_1/y","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"32"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"depthwise_62/filter_in","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"32"},{"size":"1"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"Conv2D_85/filter","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"32"},{"size":"32"}]}}}}},
+          {"name":"Conv2D_90/filter","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"2"},{"size":"2"},{"size":"32"},{"size":"142"}]}}}}},
+          {"name":"conv_left_eye/y","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"142"}]}}}}},
+          {"name":"reshape_3_1/shape","op":"Const","attr":{"dtype":{"type":"DT_INT32"},"value":{"tensor":{"dtype":"DT_INT32","tensorShape":{"dim":[{"size":"3"}]}}}}},
+          {"name":"strided_slice_59/stack","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_INT32","tensorShape":{"dim":[{"size":"3"}]}}},"dtype":{"type":"DT_INT32"}}},
+          {"name":"strided_slice_59/stack_1","op":"Const","attr":{"dtype":{"type":"DT_INT32"},"value":{"tensor":{"dtype":"DT_INT32","tensorShape":{"dim":[{"size":"3"}]}}}}},
+          {"name":"strided_slice_59/stack_2","op":"Const","attr":{"dtype":{"type":"DT_INT32"},"value":{"tensor":{"dtype":"DT_INT32","tensorShape":{"dim":[{"size":"3"}]}}}}},
+          {"name":"strided_slice_60/stack","op":"Const","attr":{"dtype":{"type":"DT_INT32"},"value":{"tensor":{"dtype":"DT_INT32","tensorShape":{"dim":[{"size":"3"}]}}}}},
+          {"name":"strided_slice_60/stack_1","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_INT32","tensorShape":{"dim":[{"size":"3"}]}}},"dtype":{"type":"DT_INT32"}}},
+          {"name":"strided_slice_60/stack_2","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_INT32","tensorShape":{"dim":[{"size":"3"}]}}},"dtype":{"type":"DT_INT32"}}},
+          {"name":"Reshape_9/shape","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_INT32","tensorShape":{"dim":[{"size":"3"}]}}},"dtype":{"type":"DT_INT32"}}},
+          {"name":"output_left_eye/shape","op":"Const","attr":{"dtype":{"type":"DT_INT32"},"value":{"tensor":{"dtype":"DT_INT32","tensorShape":{"dim":[{"size":"4"}]}}}}},
+          {"name":"p_re_lu_52/Alpha_dequantize_prelu/Neg","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"32"}]}}}}},
+          {"name":"conv2d_52_1/y","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"32"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"p_re_lu_51/Alpha_dequantize_prelu/Neg","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"32"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"p_re_lu_50/Alpha_dequantize_prelu/Neg","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"128"}]}}}}},
+          {"name":"conv2d_50_1/y","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"128"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"p_re_lu_49/Alpha_dequantize_prelu/Neg","op":"Const","attr":{"dtype":{"type":"DT_FLOAT"},"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"128"}]}}}}},
+          {"name":"conv2d_49_1/y","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"128"}]}}},"dtype":{"type":"DT_FLOAT"}}},
+          {"name":"p_re_lu_48/Alpha_dequantize_prelu/Neg","op":"Const","attr":{"value":{"tensor":{"dtype":"DT_FLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"128"}]}}},"dtype":{"type":"DT_FLOAT"}}},
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":"float32"}},{"name":"depthwise_17/filter_in","shape":[3,3,32,1],"dtype":"float32","quantization":{"dtype":"float16","original_dtype":"float32"}},{"name":"Conv2D_20/filter","shape":[1,1,32,32],"dtype":"float32","quantization":{"dtype":"float16","original_dtype":"float32"}},{"name":"conv2d_19_1/y","shape":[32],"dtype":"float32","quantization":{"dtype":"float16","original_dtype":"float32"}},{"name":"Conv2D_21/filter","shape":[3,3,32,1404],"dtype":"float32","quantization":{"dtype":"float16","original_dtype":"float32"}},{"name":"output_mesh/y","shape":[1404],"dtype":"float32","quantization":{"dtype":"float16","original_dtype":"float32"}},{"name":"reshape_5/shape","shape":[3],"dtype":"int32"},{"name":"multiply_by_constant_4/y","shape":[1],"dtype":"float32","quantization":{"dtype":"float16","original_dtype":"float32"}},{"name":"strided_slice_10/stack","shape":[3],"dtype":"int32"},{"name":"strided_slice_10/stack_1","shape":[3],"dtype":"int32"},{"name":"strided_slice_10/stack_2","shape":[3],"dtype":"int32"},{"name":"strided_slice_11/stack","shape":[3],"dtype":"int32"},{"name":"strided_slice_11/stack_1","shape":[3],"dtype":"int32"},{"name":"strided_slice_11/stack_2","shape":[3],"dtype":"int32"},{"name":"norm_2/Sum/reduction_indices","shape":[1],"dtype":"int32"},{"name":"Const_8","shape":[2,2],"dtype":"float32","quantization":{"dtype":"float16","original_dtype":"float32"}},{"name":"concat_6/axis","shape":[],"dtype":"int32"},{"name":"Min_2/reduction_indices","shape":[],"dtype":"int32"},{"name":"strided_slice_14/stack","shape":[3],"dtype":"int32"},{"name":"strided_slice_14/stack_1","shape":[3],"dtype":"int32"},{"name":"strided_slice_14/stack_2","shape":[3],"dtype":"int32"},{"name":"Mul_17/y","shape":[],"dtype":"float32","quantization":{"dtype":"float16","original_dtype":"float32"}},{"name":"concat_7/axis","shape":[],"dtype":"int32"},{"name":"transpose_5/perm","shape":[3],"dtype":"int32"},{"name":"Tile_2","shape":[1,2,4],"dtype":"float32","quantization":{"dtype":"float16","original_dtype":"float32"}},{"name":"concat_8/axis","shape":[],"dtype":"int32"},{"name":"multiply_by_constant_5/y","shape":[1,4,4],"dtype":"float32","quantization":{"dtype":"float16","original_dtype":"float32"}},{"name":"strided_slice_66/stack","shape":[3],"dtype":"int32"},{"name":"strided_slice_66/stack_1","shape":[3],"dtype":"int32"},{"name":"strided_slice_66/stack_2","shape":[3],"dtype":"int32"},{"name":"Reshape_12/shape","shape":[3],"dtype":"int32"},{"name":"output_right_iris/shape","shape":[4],"dtype":"int32"}]
+      }
+  ]
+}
\ No newline at end of file
diff --git a/package.json b/package.json
index cf945e6d..07d7d345 100644
--- a/package.json
+++ b/package.json
@@ -1,6 +1,6 @@
 {
   "name": "@vladmandic/human",
-  "version": "2.6.5",
+  "version": "2.7.0",
   "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",
@@ -86,7 +86,7 @@
     "rimraf": "^3.0.2",
     "seedrandom": "^3.0.5",
     "tslib": "^2.3.1",
-    "typedoc": "0.22.14",
+    "typedoc": "0.22.15",
     "typescript": "4.6.3"
   }
 }
diff --git a/src/config.ts b/src/config.ts
index d1a004e4..f2626d99 100644
--- a/src/config.ts
+++ b/src/config.ts
@@ -40,6 +40,9 @@ export interface FaceMeshConfig extends GenericConfig {}
 /** Iris part of face configuration */
 export interface FaceIrisConfig extends GenericConfig {}
 
+/** Attention part of face configuration */
+export interface FaceAttentionConfig extends GenericConfig {}
+
 /** Description or face embedding part of face configuration
  * - also used by age and gender detection
  */
@@ -64,6 +67,7 @@ export interface FaceLivenessConfig extends GenericConfig {}
 export interface FaceConfig extends GenericConfig {
   detector: Partial<FaceDetectorConfig>,
   mesh: Partial<FaceMeshConfig>,
+  attention: Partial<FaceAttentionConfig>,
   iris: Partial<FaceIrisConfig>,
   description: Partial<FaceDescriptionConfig>,
   emotion: Partial<FaceEmotionConfig>,
@@ -349,6 +353,10 @@ const config: Config = {
       enabled: true,
       modelPath: 'facemesh.json',
     },
+    attention: {
+      enabled: false,
+      modelPath: 'facemesh-attention.json',
+    },
     iris: {
       enabled: true,
       modelPath: 'iris.json',
diff --git a/src/draw/body.ts b/src/draw/body.ts
new file mode 100644
index 00000000..6ff6d342
--- /dev/null
+++ b/src/draw/body.ts
@@ -0,0 +1,51 @@
+import { mergeDeep } from '../util/util';
+import { getCanvasContext, rect, point, curves, colorDepth } from './primitives';
+import { options } from './options';
+import type { BodyResult } from '../result';
+import type { AnyCanvas, DrawOptions } from '../exports';
+
+/** draw detected bodies */
+export async function body(inCanvas: AnyCanvas, result: Array<BodyResult>, drawOptions?: Partial<DrawOptions>) {
+  const localOptions = mergeDeep(options, drawOptions);
+  if (!result || !inCanvas) return;
+  const ctx = getCanvasContext(inCanvas);
+  if (!ctx) return;
+  ctx.lineJoin = 'round';
+  for (let i = 0; i < result.length; i++) {
+    ctx.strokeStyle = localOptions.color;
+    ctx.fillStyle = localOptions.color;
+    ctx.lineWidth = localOptions.lineWidth;
+    ctx.font = localOptions.font;
+    if (localOptions.drawBoxes && result[i].box && result[i].box?.length === 4) {
+      rect(ctx, result[i].box[0], result[i].box[1], result[i].box[2], result[i].box[3], localOptions);
+      if (localOptions.drawLabels) {
+        if (localOptions.shadowColor && localOptions.shadowColor !== '') {
+          ctx.fillStyle = localOptions.shadowColor;
+          ctx.fillText(`body ${100 * result[i].score}%`, result[i].box[0] + 3, 1 + result[i].box[1] + localOptions.lineHeight, result[i].box[2]);
+        }
+        ctx.fillStyle = localOptions.labelColor;
+        ctx.fillText(`body ${100 * result[i].score}%`, result[i].box[0] + 2, 0 + result[i].box[1] + localOptions.lineHeight, result[i].box[2]);
+      }
+    }
+    if (localOptions.drawPoints && result[i].keypoints) {
+      for (let pt = 0; pt < result[i].keypoints.length; pt++) {
+        if (!result[i].keypoints[pt].score || (result[i].keypoints[pt].score === 0)) continue;
+        ctx.fillStyle = localOptions.useDepth && result[i].keypoints[pt].position[2] ? colorDepth(result[i].keypoints[pt].position[2] || 0) : localOptions.color;
+        point(ctx, result[i].keypoints[pt].position[0], result[i].keypoints[pt].position[1], 0, localOptions);
+      }
+    }
+    if (localOptions.drawLabels && result[i].keypoints) {
+      ctx.font = localOptions.font;
+      for (const pt of result[i].keypoints) {
+        if (!pt.score || (pt.score === 0)) continue;
+        ctx.fillStyle = localOptions.useDepth && pt.position[2] ? colorDepth(pt.position[2]) : localOptions.color;
+        ctx.fillText(`${pt.part} ${Math.trunc(100 * pt.score)}%`, pt.position[0] + 4, pt.position[1] + 4);
+      }
+    }
+    if (localOptions.drawPolygons && result[i].keypoints && result[i].annotations) {
+      for (const part of Object.values(result[i].annotations)) {
+        for (const connected of part) curves(ctx, connected, localOptions);
+      }
+    }
+  }
+}
diff --git a/src/draw/draw.ts b/src/draw/draw.ts
new file mode 100644
index 00000000..5b519999
--- /dev/null
+++ b/src/draw/draw.ts
@@ -0,0 +1,78 @@
+/**
+ * Module that implements helper draw functions, exposed as human.draw
+ */
+
+import { mergeDeep, now } from '../util/util';
+import { env } from '../util/env';
+import { getCanvasContext, rect } from './primitives';
+import { options } from './options';
+import { face } from './face';
+import { body } from './body';
+import { hand } from './hand';
+import { object } from './object';
+import { gesture } from './gesture';
+import type { Result, PersonResult } from '../result';
+import type { AnyCanvas, DrawOptions } from '../exports';
+
+let drawTime = 0;
+
+export { options } from './options';
+export { face } from './face';
+export { body } from './body';
+export { hand } from './hand';
+export { object } from './object';
+export { gesture } from './gesture';
+
+/** draw combined person results instead of individual detection result objects */
+export async function person(inCanvas: AnyCanvas, result: Array<PersonResult>, drawOptions?: Partial<DrawOptions>) {
+  const localOptions = mergeDeep(options, drawOptions);
+  if (!result || !inCanvas) return;
+  const ctx = getCanvasContext(inCanvas);
+  if (!ctx) return;
+  ctx.lineJoin = 'round';
+  ctx.font = localOptions.font;
+
+  for (let i = 0; i < result.length; i++) {
+    if (localOptions.drawBoxes) {
+      ctx.strokeStyle = localOptions.color;
+      ctx.fillStyle = localOptions.color;
+      rect(ctx, result[i].box[0], result[i].box[1], result[i].box[2], result[i].box[3], localOptions);
+      if (localOptions.drawLabels) {
+        const label = `person #${i}`;
+        if (localOptions.shadowColor && localOptions.shadowColor !== '') {
+          ctx.fillStyle = localOptions.shadowColor;
+          ctx.fillText(label, result[i].box[0] + 3, 1 + result[i].box[1] + localOptions.lineHeight, result[i].box[2]);
+        }
+        ctx.fillStyle = localOptions.labelColor;
+        ctx.fillText(label, result[i].box[0] + 2, 0 + result[i].box[1] + localOptions.lineHeight, result[i].box[2]);
+      }
+      ctx.stroke();
+    }
+  }
+}
+
+/** draw processed canvas */
+export async function canvas(input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas) {
+  if (!input || !output) return;
+  const ctx = getCanvasContext(output);
+  if (!ctx) return;
+  ctx.drawImage(input, 0, 0);
+}
+
+/** meta-function that performs draw for: canvas, face, body, hand */
+export async function all(inCanvas: AnyCanvas, result: Result, drawOptions?: Partial<DrawOptions>) {
+  if (!result || !result.performance || !result || !inCanvas) return null;
+  const timeStamp = now();
+  const localOptions = mergeDeep(options, drawOptions);
+  const promise = Promise.all([
+    face(inCanvas, result.face, localOptions),
+    body(inCanvas, result.body, localOptions),
+    hand(inCanvas, result.hand, localOptions),
+    object(inCanvas, result.object, localOptions),
+    gesture(inCanvas, result.gesture, localOptions), // gestures do not have buffering
+    // person(inCanvas, result.persons, localOptions); // already included above
+  ]);
+  drawTime = env.perfadd ? drawTime + Math.round(now() - timeStamp) : Math.round(now() - timeStamp);
+  result.performance.draw = drawTime;
+  return promise;
+}
diff --git a/src/draw/face.ts b/src/draw/face.ts
new file mode 100644
index 00000000..00277a83
--- /dev/null
+++ b/src/draw/face.ts
@@ -0,0 +1,134 @@
+import { TRI468 as triangulation } from '../face/facemeshcoords';
+import { mergeDeep } from '../util/util';
+import { getCanvasContext, rad2deg, rect, point, lines, arrow } from './primitives';
+import { options } from './options';
+import type { FaceResult } from '../result';
+import type { AnyCanvas, DrawOptions } from '../exports';
+
+/** draw detected faces */
+export async function face(inCanvas: AnyCanvas, result: Array<FaceResult>, drawOptions?: Partial<DrawOptions>) {
+  const localOptions = mergeDeep(options, drawOptions);
+  if (!result || !inCanvas) return;
+  const ctx = getCanvasContext(inCanvas);
+  if (!ctx) return;
+  for (const f of result) {
+    ctx.font = localOptions.font;
+    ctx.strokeStyle = localOptions.color;
+    ctx.fillStyle = localOptions.color;
+    if (localOptions.drawBoxes) rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3], localOptions);
+    if (localOptions.drawLabels) {
+      // silly hack since fillText does not suport new line
+      const labels:string[] = [];
+      labels.push(`face: ${Math.trunc(100 * f.score)}%`);
+      if (f.genderScore) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderScore)}%`);
+      if (f.age) labels.push(`age: ${f.age || ''}`);
+      if (f.iris) labels.push(`distance: ${f.iris}`);
+      if (f.real) labels.push(`real: ${Math.trunc(100 * f.real)}%`);
+      if (f.live) labels.push(`live: ${Math.trunc(100 * f.live)}%`);
+      if (f.emotion && f.emotion.length > 0) {
+        const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);
+        if (emotion.length > 3) emotion.length = 3;
+        labels.push(emotion.join(' '));
+      }
+      if (f.rotation && f.rotation.angle && f.rotation.gaze) {
+        if (f.rotation.angle.roll) labels.push(`roll: ${rad2deg(f.rotation.angle.roll)}° yaw:${rad2deg(f.rotation.angle.yaw)}° pitch:${rad2deg(f.rotation.angle.pitch)}°`);
+        if (f.rotation.gaze.bearing) labels.push(`gaze: ${rad2deg(f.rotation.gaze.bearing)}°`);
+      }
+      if (labels.length === 0) labels.push('face');
+      ctx.fillStyle = localOptions.color;
+      for (let i = labels.length - 1; i >= 0; i--) {
+        const x = Math.max(f.box[0], 0);
+        const y = i * localOptions.lineHeight + f.box[1];
+        if (localOptions.shadowColor && localOptions.shadowColor !== '') {
+          ctx.fillStyle = localOptions.shadowColor;
+          ctx.fillText(labels[i], x + 5, y + 16);
+        }
+        ctx.fillStyle = localOptions.labelColor;
+        ctx.fillText(labels[i], x + 4, y + 15);
+      }
+    }
+    // ctx.lineWidth = localOptions.lineWidth;
+    ctx.lineWidth = 2;
+    if (f.mesh && f.mesh.length > 0) {
+      if (localOptions.drawPoints) {
+        const length = Math.max(468, f.mesh.length);
+        for (let i = 0; i < length; i++) point(ctx, f.mesh[i][0], f.mesh[i][1], f.mesh[i][2], localOptions);
+      }
+      if (localOptions.drawAttention && f.mesh.length > 468) {
+        for (let i = 468; i < f.mesh.length; i++) point(ctx, f.mesh[i][0], f.mesh[i][1], -255, localOptions);
+      }
+      if (localOptions.drawPolygons) {
+        if (f.mesh.length > 450) {
+          for (let i = 0; i < triangulation.length / 3; i++) {
+            const points = [
+              triangulation[i * 3 + 0],
+              triangulation[i * 3 + 1],
+              triangulation[i * 3 + 2],
+            ].map((index) => f.mesh[index]);
+            lines(ctx, points, localOptions);
+          }
+        }
+        // iris: array[center, left, top, right, bottom]
+        if (f.annotations && f.annotations['leftEyeIris'] && f.annotations['leftEyeIris'][0]) {
+          ctx.strokeStyle = localOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : localOptions.color;
+          ctx.beginPath();
+          const sizeX = Math.abs(f.annotations['leftEyeIris'][3][0] - f.annotations['leftEyeIris'][1][0]) / 2;
+          const sizeY = Math.abs(f.annotations['leftEyeIris'][4][1] - f.annotations['leftEyeIris'][2][1]) / 2;
+          ctx.ellipse(f.annotations['leftEyeIris'][0][0], f.annotations['leftEyeIris'][0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);
+          ctx.stroke();
+          if (localOptions.fillPolygons) {
+            ctx.fillStyle = localOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : localOptions.color;
+            ctx.fill();
+          }
+        }
+        if (f.annotations && f.annotations['rightEyeIris'] && f.annotations['rightEyeIris'][0]) {
+          ctx.strokeStyle = localOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : localOptions.color;
+          ctx.beginPath();
+          const sizeX = Math.abs(f.annotations['rightEyeIris'][3][0] - f.annotations['rightEyeIris'][1][0]) / 2;
+          const sizeY = Math.abs(f.annotations['rightEyeIris'][4][1] - f.annotations['rightEyeIris'][2][1]) / 2;
+          ctx.ellipse(f.annotations['rightEyeIris'][0][0], f.annotations['rightEyeIris'][0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);
+          ctx.stroke();
+          if (localOptions.fillPolygons) {
+            ctx.fillStyle = localOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : localOptions.color;
+            ctx.fill();
+          }
+        }
+        if (localOptions.drawGaze && f.rotation?.angle && typeof Path2D !== 'undefined') {
+          ctx.strokeStyle = 'pink';
+          const valX = (f.box[0] + f.box[2] / 2) - (f.box[3] * rad2deg(f.rotation.angle.yaw) / 90);
+          const valY = (f.box[1] + f.box[3] / 2) + (f.box[2] * rad2deg(f.rotation.angle.pitch) / 90);
+          const pathV = new Path2D(`
+            M ${f.box[0] + f.box[2] / 2} ${f.box[1]}
+            C
+              ${valX} ${f.box[1]},
+              ${valX} ${f.box[1] + f.box[3]},
+              ${f.box[0] + f.box[2] / 2} ${f.box[1] + f.box[3]}
+          `);
+          const pathH = new Path2D(`
+            M ${f.box[0]} ${f.box[1] + f.box[3] / 2}
+            C 
+              ${f.box[0]} ${valY},
+              ${f.box[0] + f.box[2]} ${valY},
+              ${f.box[0] + f.box[2]} ${f.box[1] + f.box[3] / 2}
+          `);
+          ctx.stroke(pathH);
+          ctx.stroke(pathV);
+        }
+        if (localOptions.drawGaze && f.rotation?.gaze?.strength && f.rotation?.gaze?.bearing && f.annotations['leftEyeIris'] && f.annotations['rightEyeIris'] && f.annotations['leftEyeIris'][0] && f.annotations['rightEyeIris'][0]) {
+          ctx.strokeStyle = 'pink';
+          ctx.fillStyle = 'pink';
+          const leftGaze = [
+            f.annotations['leftEyeIris'][0][0] + (Math.sin(f.rotation.gaze.bearing) * f.rotation.gaze.strength * f.box[3]),
+            f.annotations['leftEyeIris'][0][1] + (Math.cos(f.rotation.gaze.bearing) * f.rotation.gaze.strength * f.box[2]),
+          ];
+          arrow(ctx, [f.annotations['leftEyeIris'][0][0], f.annotations['leftEyeIris'][0][1]], [leftGaze[0], leftGaze[1]], 4);
+          const rightGaze = [
+            f.annotations['rightEyeIris'][0][0] + (Math.sin(f.rotation.gaze.bearing) * f.rotation.gaze.strength * f.box[3]),
+            f.annotations['rightEyeIris'][0][1] + (Math.cos(f.rotation.gaze.bearing) * f.rotation.gaze.strength * f.box[2]),
+          ];
+          arrow(ctx, [f.annotations['rightEyeIris'][0][0], f.annotations['rightEyeIris'][0][1]], [rightGaze[0], rightGaze[1]], 4);
+        }
+      }
+    }
+  }
+}
diff --git a/src/draw/gesture.ts b/src/draw/gesture.ts
new file mode 100644
index 00000000..a7dc7682
--- /dev/null
+++ b/src/draw/gesture.ts
@@ -0,0 +1,34 @@
+import { mergeDeep } from '../util/util';
+import { getCanvasContext } from './primitives';
+import { options } from './options';
+import type { GestureResult } from '../result';
+import type { AnyCanvas, DrawOptions } from '../exports';
+
+/** draw detected gestures */
+export async function gesture(inCanvas: AnyCanvas, result: Array<GestureResult>, drawOptions?: Partial<DrawOptions>) {
+  const localOptions = mergeDeep(options, drawOptions);
+  if (!result || !inCanvas) return;
+  if (localOptions.drawGestures) {
+    const ctx = getCanvasContext(inCanvas);
+    if (!ctx) return;
+    ctx.font = localOptions.font;
+    ctx.fillStyle = localOptions.color;
+    let i = 1;
+    for (let j = 0; j < result.length; j++) {
+      let where: unknown[] = []; // what&where is a record
+      let what: unknown[] = []; // what&where is a record
+      [where, what] = Object.entries(result[j]);
+      if ((what.length > 1) && ((what[1] as string).length > 0)) {
+        const who = where[1] as number > 0 ? `#${where[1]}` : '';
+        const label = `${where[0]} ${who}: ${what[1]}`;
+        if (localOptions.shadowColor && localOptions.shadowColor !== '') {
+          ctx.fillStyle = localOptions.shadowColor;
+          ctx.fillText(label, 8, 2 + (i * localOptions.lineHeight));
+        }
+        ctx.fillStyle = localOptions.labelColor;
+        ctx.fillText(label, 6, 0 + (i * localOptions.lineHeight));
+        i += 1;
+      }
+    }
+  }
+}
diff --git a/src/draw/hand.ts b/src/draw/hand.ts
new file mode 100644
index 00000000..50474443
--- /dev/null
+++ b/src/draw/hand.ts
@@ -0,0 +1,74 @@
+import { mergeDeep } from '../util/util';
+import { getCanvasContext, rect, point, colorDepth } from './primitives';
+import { options } from './options';
+import type { HandResult } from '../result';
+import type { AnyCanvas, DrawOptions, Point } from '../exports';
+
+/** draw detected hands */
+export async function hand(inCanvas: AnyCanvas, result: Array<HandResult>, drawOptions?: Partial<DrawOptions>) {
+  const localOptions = mergeDeep(options, drawOptions);
+  if (!result || !inCanvas) return;
+  const ctx = getCanvasContext(inCanvas);
+  if (!ctx) return;
+  ctx.lineJoin = 'round';
+  ctx.font = localOptions.font;
+  for (const h of result) {
+    if (localOptions.drawBoxes) {
+      ctx.strokeStyle = localOptions.color;
+      ctx.fillStyle = localOptions.color;
+      rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3], localOptions);
+      if (localOptions.drawLabels) {
+        if (localOptions.shadowColor && localOptions.shadowColor !== '') {
+          ctx.fillStyle = localOptions.shadowColor;
+          ctx.fillText(`hand:${Math.trunc(100 * h.score)}%`, h.box[0] + 3, 1 + h.box[1] + localOptions.lineHeight, h.box[2]); // can use h.label
+        }
+        ctx.fillStyle = localOptions.labelColor;
+        ctx.fillText(`hand:${Math.trunc(100 * h.score)}%`, h.box[0] + 2, 0 + h.box[1] + localOptions.lineHeight, h.box[2]); // can use h.label
+      }
+      ctx.stroke();
+    }
+    if (localOptions.drawPoints) {
+      if (h.keypoints && h.keypoints.length > 0) {
+        for (const pt of h.keypoints) {
+          ctx.fillStyle = localOptions.useDepth ? colorDepth(pt[2] || 0) : localOptions.color;
+          point(ctx, pt[0], pt[1], 0, localOptions);
+        }
+      }
+    }
+    if (localOptions.drawLabels && h.annotations) {
+      const addHandLabel = (part: Array<Point>, title: string) => {
+        if (!part || part.length === 0 || !part[0]) return;
+        const z = part[part.length - 1][2] || 0;
+        ctx.fillStyle = localOptions.useDepth ? colorDepth(z) : localOptions.color;
+        ctx.fillText(title, part[part.length - 1][0] + 4, part[part.length - 1][1] + 4);
+      };
+      ctx.font = localOptions.font;
+      addHandLabel(h.annotations['index'], 'index');
+      addHandLabel(h.annotations['middle'], 'middle');
+      addHandLabel(h.annotations['ring'], 'ring');
+      addHandLabel(h.annotations['pinky'], 'pinky');
+      addHandLabel(h.annotations['thumb'], 'thumb');
+      addHandLabel(h.annotations['palm'], 'palm');
+    }
+    if (localOptions.drawPolygons && h.annotations) {
+      const addHandLine = (part: Array<Point>) => {
+        if (!part || part.length === 0 || !part[0]) return;
+        for (let i = 0; i < part.length; i++) {
+          ctx.beginPath();
+          const z = part[i][2] || 0;
+          ctx.strokeStyle = localOptions.useDepth ? colorDepth(i * z) : localOptions.color;
+          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);
+          ctx.lineTo(part[i][0], part[i][1]);
+          ctx.stroke();
+        }
+      };
+      ctx.lineWidth = localOptions.lineWidth;
+      addHandLine(h.annotations['index']);
+      addHandLine(h.annotations['middle']);
+      addHandLine(h.annotations['ring']);
+      addHandLine(h.annotations['pinky']);
+      addHandLine(h.annotations['thumb']);
+      // addPart(h.annotations.palm);
+    }
+  }
+}
diff --git a/src/draw/object.ts b/src/draw/object.ts
new file mode 100644
index 00000000..8664e083
--- /dev/null
+++ b/src/draw/object.ts
@@ -0,0 +1,32 @@
+import { mergeDeep } from '../util/util';
+import { getCanvasContext, rect } from './primitives';
+import { options } from './options';
+import type { ObjectResult } from '../result';
+import type { AnyCanvas, DrawOptions } from '../exports';
+
+/** draw detected objects */
+export async function object(inCanvas: AnyCanvas, result: Array<ObjectResult>, drawOptions?: Partial<DrawOptions>) {
+  const localOptions = mergeDeep(options, drawOptions);
+  if (!result || !inCanvas) return;
+  const ctx = getCanvasContext(inCanvas);
+  if (!ctx) return;
+  ctx.lineJoin = 'round';
+  ctx.font = localOptions.font;
+  for (const h of result) {
+    if (localOptions.drawBoxes) {
+      ctx.strokeStyle = localOptions.color;
+      ctx.fillStyle = localOptions.color;
+      rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3], localOptions);
+      if (localOptions.drawLabels) {
+        const label = `${h.label} ${Math.round(100 * h.score)}%`;
+        if (localOptions.shadowColor && localOptions.shadowColor !== '') {
+          ctx.fillStyle = localOptions.shadowColor;
+          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + localOptions.lineHeight, h.box[2]);
+        }
+        ctx.fillStyle = localOptions.labelColor;
+        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + localOptions.lineHeight, h.box[2]);
+      }
+      ctx.stroke();
+    }
+  }
+}
diff --git a/src/draw/options.ts b/src/draw/options.ts
new file mode 100644
index 00000000..79cde324
--- /dev/null
+++ b/src/draw/options.ts
@@ -0,0 +1,66 @@
+/** Draw Options
+ * - Accessed via `human.draw.options` or provided per each draw method as the drawOptions optional parameter
+ */
+export type DrawOptions = {
+  /** draw line color */
+  color: string,
+  /** alpha value used for lines */
+  alpha: number,
+  /** label color */
+  labelColor: string,
+  /** label shadow color */
+  shadowColor: string,
+  /** label font */
+  font: string,
+  /** line spacing between labels */
+  lineHeight: number,
+  /** line width for drawn lines */
+  lineWidth: number,
+  /** size of drawn points */
+  pointSize: number,
+  /** draw rounded boxes by n pixels */
+  roundRect: number,
+  /** should points be drawn? */
+  drawPoints: boolean,
+  /** should labels be drawn? */
+  drawLabels: boolean,
+  /** should face attention keypoints be highlighted */
+  drawAttention: boolean;
+  /** should detected gestures be drawn? */
+  drawGestures: boolean,
+  /** should draw boxes around detection results? */
+  drawBoxes: boolean,
+  /** should draw polygons from detection points? */
+  drawPolygons: boolean,
+  /** should draw gaze arrows? */
+  drawGaze: boolean,
+  /** should fill polygons? */
+  fillPolygons: boolean,
+  /** use z-coordinate when available */
+  useDepth: boolean,
+  /** should lines be curved? */
+  useCurves: boolean,
+}
+
+/** currently set draw options {@link DrawOptions} */
+export const options: DrawOptions = {
+  color: <string>'rgba(173, 216, 230, 0.6)', // 'lightblue' with light alpha channel
+  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel
+  shadowColor: <string>'black',
+  alpha: 0.5,
+  font: <string>'small-caps 16px "Segoe UI"',
+  lineHeight: <number>18,
+  lineWidth: <number>4,
+  pointSize: <number>2,
+  roundRect: <number>8,
+  drawPoints: <boolean>false,
+  drawLabels: <boolean>true,
+  drawBoxes: <boolean>true,
+  drawAttention: <boolean>true,
+  drawGestures: <boolean>true,
+  drawPolygons: <boolean>true,
+  drawGaze: <boolean>true,
+  fillPolygons: <boolean>false,
+  useDepth: <boolean>true,
+  useCurves: <boolean>false,
+};
diff --git a/src/draw/primitives.ts b/src/draw/primitives.ts
new file mode 100644
index 00000000..a6bf282d
--- /dev/null
+++ b/src/draw/primitives.ts
@@ -0,0 +1,115 @@
+import { log } from '../util/util';
+import type { AnyCanvas } from '../exports';
+import type { Point } from '../result';
+import { options, DrawOptions } from './options';
+
+export const getCanvasContext = (input: AnyCanvas) => {
+  if (!input) log('draw error: invalid canvas');
+  else if (!input.getContext) log('draw error: canvas context not defined');
+  else {
+    const ctx = input.getContext('2d');
+    if (!ctx) log('draw error: cannot get canvas context');
+    else return ctx;
+  }
+  return null;
+};
+
+export const rad2deg = (theta: number) => Math.round((theta * 180) / Math.PI);
+export const colorDepth = (z: number, rgb: [boolean, boolean, boolean] = [true, true, false]): string => {
+  const r = rgb[0] ? 127 + Math.trunc(3 * z) : 255;
+  const g = rgb[1] ? 127 - Math.trunc(3 * z) : 255;
+  const b = rgb[2] ? 127 - Math.trunc(3 * z) : 255;
+  return `rgba(${r}, ${g}, ${b}, ${options.alpha})`;
+};
+
+export function point(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, x: number, y: number, z: number | undefined, localOptions: DrawOptions) {
+  z = z || 0;
+  ctx.fillStyle = localOptions.useDepth && z ? colorDepth(z, z === -255 ? [true, false, true] : [true, false, false]) : localOptions.color;
+  ctx.beginPath();
+  ctx.arc(x, y, localOptions.pointSize, 0, 2 * Math.PI);
+  ctx.fill();
+}
+
+export function rect(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, x: number, y: number, width: number, height: number, localOptions: DrawOptions) {
+  ctx.beginPath();
+  ctx.lineWidth = localOptions.lineWidth;
+  if (localOptions.useCurves) {
+    const cx = (x + x + width) / 2;
+    const cy = (y + y + height) / 2;
+    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);
+  } else {
+    ctx.moveTo(x + localOptions.roundRect, y);
+    ctx.lineTo(x + width - localOptions.roundRect, y);
+    ctx.quadraticCurveTo(x + width, y, x + width, y + localOptions.roundRect);
+    ctx.lineTo(x + width, y + height - localOptions.roundRect);
+    ctx.quadraticCurveTo(x + width, y + height, x + width - localOptions.roundRect, y + height);
+    ctx.lineTo(x + localOptions.roundRect, y + height);
+    ctx.quadraticCurveTo(x, y + height, x, y + height - localOptions.roundRect);
+    ctx.lineTo(x, y + localOptions.roundRect);
+    ctx.quadraticCurveTo(x, y, x + localOptions.roundRect, y);
+    ctx.closePath();
+  }
+  ctx.stroke();
+}
+
+export function lines(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, points: Point[], localOptions: DrawOptions) {
+  if (points.length < 2) return;
+  ctx.beginPath();
+  ctx.moveTo(points[0][0], points[0][1]);
+  for (const pt of points) {
+    const z = pt[2] || 0;
+    ctx.strokeStyle = localOptions.useDepth && z !== 0 ? colorDepth(z) : localOptions.color;
+    ctx.fillStyle = localOptions.useDepth && z !== 0 ? colorDepth(z) : localOptions.color;
+    ctx.lineTo(pt[0], Math.round(pt[1]));
+  }
+  ctx.stroke();
+  if (localOptions.fillPolygons) {
+    ctx.closePath();
+    ctx.fill();
+  }
+}
+
+export function curves(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, points: Point[], localOptions: DrawOptions) {
+  if (points.length < 2) return;
+  ctx.lineWidth = localOptions.lineWidth;
+  if (!localOptions.useCurves || points.length <= 2) {
+    lines(ctx, points, localOptions);
+    return;
+  }
+  ctx.moveTo(points[0][0], points[0][1]);
+  for (let i = 0; i < points.length - 2; i++) {
+    const xc = (points[i][0] + points[i + 1][0]) / 2;
+    const yc = (points[i][1] + points[i + 1][1]) / 2;
+    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);
+  }
+  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);
+  ctx.stroke();
+  if (localOptions.fillPolygons) {
+    ctx.closePath();
+    ctx.fill();
+  }
+}
+
+export function arrow(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, from: Point, to: Point, radius = 5) {
+  let angle;
+  let x;
+  let y;
+  ctx.beginPath();
+  ctx.moveTo(from[0], from[1]);
+  ctx.lineTo(to[0], to[1]);
+  angle = Math.atan2(to[1] - from[1], to[0] - from[0]);
+  x = radius * Math.cos(angle) + to[0];
+  y = radius * Math.sin(angle) + to[1];
+  ctx.moveTo(x, y);
+  angle += (1.0 / 3.0) * (2 * Math.PI);
+  x = radius * Math.cos(angle) + to[0];
+  y = radius * Math.sin(angle) + to[1];
+  ctx.lineTo(x, y);
+  angle += (1.0 / 3.0) * (2 * Math.PI);
+  x = radius * Math.cos(angle) + to[0];
+  y = radius * Math.sin(angle) + to[1];
+  ctx.lineTo(x, y);
+  ctx.closePath();
+  ctx.stroke();
+  ctx.fill();
+}
diff --git a/src/exports.ts b/src/exports.ts
index 725624b0..2c242b52 100644
--- a/src/exports.ts
+++ b/src/exports.ts
@@ -9,7 +9,7 @@ export * from './result';
 /* Explict reexport of main @tensorflow/tfjs types */
 export type { Tensor, TensorLike, GraphModel, Rank } from './tfjs/types';
 
-export type { DrawOptions } from './util/draw';
+export type { DrawOptions } from './draw/options';
 export type { Descriptor } from './face/match';
 export type { Box, Point } from './result';
 export type { Models } from './models';
diff --git a/src/face/attention.ts b/src/face/attention.ts
new file mode 100644
index 00000000..1654388a
--- /dev/null
+++ b/src/face/attention.ts
@@ -0,0 +1,19 @@
+import type { Tensor } from '../tfjs/types';
+
+export async function augment(rawCoords, results: Tensor[]) {
+  const t: Record<string, Float32Array> = {
+    eyeL: results[0].dataSync() as Float32Array, // 71 x 2d // output_left_eye
+    eyeR: results[6].dataSync() as Float32Array, // 71 x 2d // output_right_eye
+    irisL: results[3].dataSync() as Float32Array, // 5 x 2d // output_left_iris
+    irisR: results[1].dataSync() as Float32Array, // 5 x 2d // output_right_iris
+    lips: results[5].dataSync() as Float32Array, // 80 x 2d // output_lips
+    // flag: results[4], // already processed in parent // conv_faceflag
+    // mesh: results[2], // already have it in rawCoords // output_mesh_identity
+  };
+  for (let i = 0; i < t.lips.length / 2; i++) rawCoords.push([t.lips[2 * i + 0], t.lips[2 * i + 1], 0]);
+  for (let i = 0; i < t.eyeL.length / 2; i++) rawCoords.push([t.eyeL[2 * i + 0], t.eyeL[2 * i + 1], 0]);
+  for (let i = 0; i < t.eyeR.length / 2; i++) rawCoords.push([t.eyeR[2 * i + 0], t.eyeR[2 * i + 1], 0]);
+  for (let i = 0; i < t.irisL.length / 2; i++) rawCoords.push([t.irisL[2 * i + 0], t.irisL[2 * i + 1], 0]);
+  for (let i = 0; i < t.irisR.length / 2; i++) rawCoords.push([t.irisR[2 * i + 0], t.irisR[2 * i + 1], 0]);
+  return rawCoords;
+}
diff --git a/src/face/blazeface.ts b/src/face/blazeface.ts
index 871a4538..88426cc3 100644
--- a/src/face/blazeface.ts
+++ b/src/face/blazeface.ts
@@ -14,7 +14,7 @@ import { env } from '../util/env';
 import type { Point } from '../result';
 
 const keypointsCount = 6;
-const faceBoxScaleFactor = 1.2;
+const faceBoxScaleFactor = 1.4;
 let model: GraphModel | null;
 let anchors: Tensor | null = null;
 let inputSize = 0;
diff --git a/src/face/facemesh.ts b/src/face/facemesh.ts
index 07fd63d9..2dbb8670 100644
--- a/src/face/facemesh.ts
+++ b/src/face/facemesh.ts
@@ -14,6 +14,7 @@ import * as blazeface from './blazeface';
 import * as util from './facemeshutil';
 import * as coords from './facemeshcoords';
 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';
@@ -78,20 +79,27 @@ export async function predict(input: Tensor, config: Config): Promise<FaceResult
         ((box.startPoint[1] + box.endPoint[1])) / 2 + ((box.endPoint[1] + box.startPoint[1]) * pt[1] / blazeface.size()),
       ]);
       face.meshRaw = face.mesh.map((pt) => [pt[0] / (input.shape[2] || 0), pt[1] / (input.shape[1] || 0), (pt[2] || 0) / inputSize]);
-      for (const key of Object.keys(coords.blazeFaceLandmarks)) face.annotations[key] = [face.mesh[coords.blazeFaceLandmarks[key] as number]]; // add annotations
+      for (const key of Object.keys(coords.blazeFaceLandmarks)) {
+        face.annotations[key] = [face.mesh[coords.blazeFaceLandmarks[key] as number]]; // add annotations
+      }
     } else if (!model) { // mesh enabled, but not loaded
       if (config.debug) log('face mesh detection requested, but model is not loaded');
     } else { // mesh enabled
-      const [contours, confidence, contourCoords] = model.execute(face.tensor as Tensor) as Array<Tensor>; // first returned tensor represents facial contours which are already included in the coordinates.
+      const results = model.execute(face.tensor as Tensor) as Array<Tensor>;
+      const confidence = results.find((t) => t.shape[t.shape.length - 1] === 1) as Tensor;
+      const contourCoords = results.find((t) => t.shape[t.shape.length - 1] === 1404) as Tensor;
       const faceConfidence = await confidence.data();
       face.faceScore = Math.round(100 * faceConfidence[0]) / 100;
       const coordsReshaped = tf.reshape(contourCoords, [-1, 3]);
       let rawCoords = await coordsReshaped.array();
-      tf.dispose([contourCoords, coordsReshaped, confidence, contours]);
       if (face.faceScore < (config.face.detector?.minConfidence || 1)) { // low confidence in detected mesh
         box.confidence = face.faceScore; // reset confidence of cached box
       } else {
-        if (config.face.iris?.enabled) rawCoords = await iris.augmentIris(rawCoords, face.tensor, config, inputSize); // augment results with iris
+        if (config.face.attention?.enabled) {
+          rawCoords = await attention.augment(rawCoords, results); // augment iris results using attention model results
+        } else if (config.face.iris?.enabled) {
+          rawCoords = await iris.augmentIris(rawCoords, face.tensor, config, inputSize); // run iris model and augment results
+        }
         face.mesh = util.transformRawCoords(rawCoords, box, angle, rotationMatrix, inputSize); // get processed mesh
         face.meshRaw = face.mesh.map((pt) => [pt[0] / (input.shape[2] || 0), pt[1] / (input.shape[1] || 0), (pt[2] || 0) / inputSize]);
         for (const key of Object.keys(coords.meshAnnotations)) face.annotations[key] = coords.meshAnnotations[key].map((index) => face.mesh[index]); // add annotations
@@ -101,6 +109,7 @@ export async function predict(input: Tensor, config: Config): Promise<FaceResult
         face.boxRaw = util.getRawBox(calculatedBox, input);
         newCache.push(calculatedBox);
       }
+      tf.dispose([...results, coordsReshaped]);
     }
     if (face.score > (config.face.detector?.minConfidence || 1)) faces.push(face);
     else tf.dispose(face.tensor);
@@ -111,8 +120,12 @@ export async function predict(input: Tensor, config: Config): Promise<FaceResult
 
 export async function load(config: Config): Promise<GraphModel> {
   if (env.initial) model = null;
-  if (!model) model = await loadModel(config.face.mesh?.modelPath);
-  else if (config.debug) log('cached model:', model['modelUrl']);
+  if (!model) {
+    if (config.face.attention?.enabled) model = await loadModel(config.face.attention?.modelPath);
+    else model = await loadModel(config.face.mesh?.modelPath);
+  } else if (config.debug) {
+    log('cached model:', model['modelUrl']);
+  }
   inputSize = model.inputs[0].shape ? model.inputs[0].shape[2] : 0;
   return model;
 }
diff --git a/src/face/iris.ts b/src/face/iris.ts
index fde0a910..02ea2015 100644
--- a/src/face/iris.ts
+++ b/src/face/iris.ts
@@ -129,7 +129,7 @@ export async function augmentIris(rawCoords, face, config, meshSize) {
   const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);
   const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);
   const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);
-  const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize);
+  const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize, false);
   const leftToRightEyeDepthDifference = getLeftToRightEyeDepthDifference(rawCoords);
   if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.
     replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', null);
diff --git a/src/human.ts b/src/human.ts
index 0e7b938b..b0a4bc90 100644
--- a/src/human.ts
+++ b/src/human.ts
@@ -17,7 +17,7 @@ import * as app from '../package.json';
 import * as backend from './tfjs/backend';
 import * as blazepose from './body/blazepose';
 import * as centernet from './object/centernet';
-import * as draw from './util/draw';
+import * as draw from './draw/draw';
 import * as efficientpose from './body/efficientpose';
 import * as face from './face/face';
 import * as facemesh from './face/facemesh';
diff --git a/src/image/image.ts b/src/image/image.ts
index ad1473e4..54e2409c 100644
--- a/src/image/image.ts
+++ b/src/image/image.ts
@@ -159,25 +159,29 @@ export async function process(input: Input, config: Config, getTensor: boolean =
       env.filter = !!fx;
       if (!fx || !fx.add) {
         if (config.debug) log('input process error: cannot initialize filters');
-        return { tensor: null, canvas: inCanvas };
+        env.webgl.supported = false;
+        config.filter.enabled = false;
+        copy(inCanvas, outCanvas); // filter failed to initialize
+        // return { tensor: null, canvas: inCanvas };
+      } else {
+        fx.reset();
+        if (config.filter.brightness !== 0) fx.add('brightness', config.filter.brightness);
+        if (config.filter.contrast !== 0) fx.add('contrast', config.filter.contrast);
+        if (config.filter.sharpness !== 0) fx.add('sharpen', config.filter.sharpness);
+        if (config.filter.blur !== 0) fx.add('blur', config.filter.blur);
+        if (config.filter.saturation !== 0) fx.add('saturation', config.filter.saturation);
+        if (config.filter.hue !== 0) fx.add('hue', config.filter.hue);
+        if (config.filter.negative) fx.add('negative');
+        if (config.filter.sepia) fx.add('sepia');
+        if (config.filter.vintage) fx.add('brownie');
+        if (config.filter.sepia) fx.add('sepia');
+        if (config.filter.kodachrome) fx.add('kodachrome');
+        if (config.filter.technicolor) fx.add('technicolor');
+        if (config.filter.polaroid) fx.add('polaroid');
+        if (config.filter.pixelate !== 0) fx.add('pixelate', config.filter.pixelate);
+        if (fx.get() > 0) outCanvas = fx.apply(inCanvas);
+        else outCanvas = fx.draw(inCanvas);
       }
-      fx.reset();
-      if (config.filter.brightness !== 0) fx.add('brightness', config.filter.brightness);
-      if (config.filter.contrast !== 0) fx.add('contrast', config.filter.contrast);
-      if (config.filter.sharpness !== 0) fx.add('sharpen', config.filter.sharpness);
-      if (config.filter.blur !== 0) fx.add('blur', config.filter.blur);
-      if (config.filter.saturation !== 0) fx.add('saturation', config.filter.saturation);
-      if (config.filter.hue !== 0) fx.add('hue', config.filter.hue);
-      if (config.filter.negative) fx.add('negative');
-      if (config.filter.sepia) fx.add('sepia');
-      if (config.filter.vintage) fx.add('brownie');
-      if (config.filter.sepia) fx.add('sepia');
-      if (config.filter.kodachrome) fx.add('kodachrome');
-      if (config.filter.technicolor) fx.add('technicolor');
-      if (config.filter.polaroid) fx.add('polaroid');
-      if (config.filter.pixelate !== 0) fx.add('pixelate', config.filter.pixelate);
-      if (fx.get() > 0) outCanvas = fx.apply(inCanvas);
-      else outCanvas = fx.draw(inCanvas);
     } else {
       copy(inCanvas, outCanvas); // if no filters applied, output canvas is input canvas
       if (fx) fx = null;
diff --git a/src/image/imagefx.ts b/src/image/imagefx.ts
index dd57eefc..0db4ba2b 100644
--- a/src/image/imagefx.ts
+++ b/src/image/imagefx.ts
@@ -84,12 +84,12 @@ export function GLImageFilter() {
   const shaderProgramCache = { }; // key is the shader program source, value is the compiled program
   const DRAW = { INTERMEDIATE: 1 };
   const gl = fxcanvas.getContext('webgl') as WebGLRenderingContext;
-  // @ts-ignore used for sanity checks outside of imagefx
-  this.gl = gl;
   if (!gl) {
     log('filter: cannot get webgl context');
     return;
   }
+  // @ts-ignore used for sanity checks outside of imagefx
+  this.gl = gl;
 
   function resize(width, height) {
     if (width === fxcanvas.width && height === fxcanvas.height) return; // Same width/height? Nothing to do here
diff --git a/test/build.log b/test/build.log
index af65cb75..989ad2f8 100644
--- a/test/build.log
+++ b/test/build.log
@@ -1,24 +1,24 @@
-2022-04-10 10:11:37 INFO:  Application: {"name":"@vladmandic/human","version":"2.6.5"} 
-2022-04-10 10:11:37 INFO:  Environment: {"profile":"production","config":".build.json","package":"package.json","tsconfig":true,"eslintrc":true,"git":true} 
-2022-04-10 10:11:37 INFO:  Toolchain: {"build":"0.7.2","esbuild":"0.14.34","typescript":"4.6.3","typedoc":"0.22.14","eslint":"8.13.0"} 
-2022-04-10 10:11:37 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]} 
-2022-04-10 10:11:37 STATE: Clean: {"locations":["dist/*","types/lib/*","typedoc/*"]} 
-2022-04-10 10:11:37 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":595} 
-2022-04-10 10:11:37 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":64,"inputBytes":564552,"outputBytes":293314} 
-2022-04-10 10:11:37 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":599} 
-2022-04-10 10:11:37 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":64,"inputBytes":564556,"outputBytes":293318} 
-2022-04-10 10:11:37 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":651} 
-2022-04-10 10:11:37 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":64,"inputBytes":564608,"outputBytes":293368} 
-2022-04-10 10:11:37 STATE: Compile: {"name":"tfjs/browser/version","format":"esm","platform":"browser","input":"tfjs/tf-version.ts","output":"dist/tfjs.version.js","files":1,"inputBytes":1063,"outputBytes":394} 
-2022-04-10 10:11:37 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":1068,"outputBytes":615} 
-2022-04-10 10:11:37 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":64,"inputBytes":564572,"outputBytes":292273} 
-2022-04-10 10:11:37 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":1344714} 
-2022-04-10 10:11:37 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":64,"inputBytes":1908671,"outputBytes":1636003} 
-2022-04-10 10:11:37 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":64,"inputBytes":1908671,"outputBytes":2113825} 
-2022-04-10 10:11:43 STATE: Typings: {"input":"src/human.ts","output":"types/lib","files":112} 
-2022-04-10 10:11:45 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":72,"generated":true} 
-2022-04-10 10:11:45 STATE: Compile: {"name":"demo/typescript","format":"esm","platform":"browser","input":"demo/typescript/index.ts","output":"demo/typescript/index.js","files":1,"inputBytes":5862,"outputBytes":2915} 
-2022-04-10 10:11:45 STATE: Compile: {"name":"demo/faceid","format":"esm","platform":"browser","input":"demo/faceid/index.ts","output":"demo/faceid/index.js","files":2,"inputBytes":15174,"outputBytes":7820} 
-2022-04-10 10:11:54 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":96,"errors":0,"warnings":0} 
-2022-04-10 10:11:54 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"} 
-2022-04-10 10:11:54 INFO:  Done... 
+2022-04-11 11:43:57 INFO:  Application: {"name":"@vladmandic/human","version":"2.7.0"} 
+2022-04-11 11:43:57 INFO:  Environment: {"profile":"production","config":".build.json","package":"package.json","tsconfig":true,"eslintrc":true,"git":true} 
+2022-04-11 11:43:57 INFO:  Toolchain: {"build":"0.7.2","esbuild":"0.14.34","typescript":"4.6.3","typedoc":"0.22.15","eslint":"8.13.0"} 
+2022-04-11 11:43:57 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]} 
+2022-04-11 11:43:57 STATE: Clean: {"locations":["dist/*","types/lib/*","typedoc/*"]} 
+2022-04-11 11:43:57 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":595} 
+2022-04-11 11:43:57 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":72,"inputBytes":568981,"outputBytes":294190} 
+2022-04-11 11:43:57 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":599} 
+2022-04-11 11:43:57 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":72,"inputBytes":568985,"outputBytes":294194} 
+2022-04-11 11:43:57 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":651} 
+2022-04-11 11:43:57 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":72,"inputBytes":569037,"outputBytes":294244} 
+2022-04-11 11:43:57 STATE: Compile: {"name":"tfjs/browser/version","format":"esm","platform":"browser","input":"tfjs/tf-version.ts","output":"dist/tfjs.version.js","files":1,"inputBytes":1063,"outputBytes":394} 
+2022-04-11 11:43:57 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":1068,"outputBytes":615} 
+2022-04-11 11:43:57 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":72,"inputBytes":569001,"outputBytes":293151} 
+2022-04-11 11:43:57 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":1344714} 
+2022-04-11 11:43:57 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":72,"inputBytes":1913100,"outputBytes":1636880} 
+2022-04-11 11:43:58 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":72,"inputBytes":1913100,"outputBytes":2115805} 
+2022-04-11 11:44:03 STATE: Typings: {"input":"src/human.ts","output":"types/lib","files":114} 
+2022-04-11 11:44:05 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":73,"generated":true} 
+2022-04-11 11:44:05 STATE: Compile: {"name":"demo/typescript","format":"esm","platform":"browser","input":"demo/typescript/index.ts","output":"demo/typescript/index.js","files":1,"inputBytes":5916,"outputBytes":2957} 
+2022-04-11 11:44:05 STATE: Compile: {"name":"demo/faceid","format":"esm","platform":"browser","input":"demo/faceid/index.ts","output":"demo/faceid/index.js","files":2,"inputBytes":15174,"outputBytes":7820} 
+2022-04-11 11:44:13 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":104,"errors":0,"warnings":0} 
+2022-04-11 11:44:13 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"} 
+2022-04-11 11:44:13 INFO:  Done... 
diff --git a/types/human.d.ts b/types/human.d.ts
index 16b4ccaa..d965b941 100644
--- a/types/human.d.ts
+++ b/types/human.d.ts
@@ -334,16 +334,15 @@ declare function distance(descriptor1: Descriptor, descriptor2: Descriptor, opti
 
 declare namespace draw {
     export {
-        gesture,
+        person,
+        canvas,
+        all,
+        options,
         face,
         body,
         hand,
         object,
-        person,
-        canvas,
-        all,
-        DrawOptions,
-        options
+        gesture
     }
 }
 export { draw }
@@ -354,6 +353,8 @@ export { draw }
 export declare type DrawOptions = {
     /** draw line color */
     color: string;
+    /** alpha value used for lines */
+    alpha: number;
     /** label color */
     labelColor: string;
     /** label shadow color */
@@ -372,6 +373,8 @@ export declare type DrawOptions = {
     drawPoints: boolean;
     /** should labels be drawn? */
     drawLabels: boolean;
+    /** should face attention keypoints be highlighted */
+    drawAttention: boolean;
     /** should detected gestures be drawn? */
     drawGestures: boolean;
     /** should draw boxes around detection results? */
@@ -499,10 +502,15 @@ declare function face(inCanvas: AnyCanvas, result: Array<FaceResult>, drawOption
 export declare interface FaceAntiSpoofConfig extends GenericConfig {
 }
 
+/** Attention part of face configuration */
+export declare interface FaceAttentionConfig extends GenericConfig {
+}
+
 /** Configures all face-specific options: face detection, mesh analysis, age, gender, emotion detection and face description */
 export declare interface FaceConfig extends GenericConfig {
     detector: Partial<FaceDetectorConfig>;
     mesh: Partial<FaceMeshConfig>;
+    attention: Partial<FaceAttentionConfig>;
     iris: Partial<FaceIrisConfig>;
     description: Partial<FaceDescriptionConfig>;
     emotion: Partial<FaceEmotionConfig>;