rebuild all

CHANGELOG.md

@@ -9,8 +9,10 @@
   
 ## Changelog
   
-### **HEAD -> main** 2022/11/10 mandic00@live.com
+### **HEAD -> main** 2022/11/11 mandic00@live.com
 
+- include project files for types
+- architectural improvements
 - refresh dependencies
 - add named exports
 - add draw label templates

demo/typescript/index.js

@@ -4,98 +4,6 @@
   author: <https://github.com/vladmandic>'
 */
 
-
-// demo/typescript/index.ts
-import * as H from "../../dist/human.esm.js";
-var width = 1920;
-var humanConfig = {
-  modelBasePath: "../../models",
-  filter: { enabled: true, equalization: false, flip: false, width },
-  face: { enabled: true, detector: { rotation: true }, mesh: { enabled: true }, attention: { enabled: false }, iris: { enabled: true }, description: { enabled: true }, emotion: { enabled: true }, antispoof: { enabled: true }, liveness: { enabled: true } },
-  body: { enabled: true },
-  hand: { enabled: true },
-  object: { enabled: false },
-  segmentation: { enabled: false },
-  gesture: { enabled: true }
-};
-var human = new H.Human(humanConfig);
-human.env.perfadd = false;
-human.draw.options.font = 'small-caps 18px "Lato"';
-human.draw.options.lineHeight = 20;
-var dom = {
-  video: document.getElementById("video"),
-  canvas: document.getElementById("canvas"),
-  log: document.getElementById("log"),
-  fps: document.getElementById("status"),
-  perf: document.getElementById("performance")
-};
-var timestamp = { detect: 0, draw: 0, tensors: 0, start: 0 };
-var fps = { detectFPS: 0, drawFPS: 0, frames: 0, averageMs: 0 };
-var log = (...msg) => {
-  dom.log.innerText += msg.join(" ") + "\n";
-  console.log(...msg);
-};
-var status = (msg) => dom.fps.innerText = msg;
-var perf = (msg) => dom.perf.innerText = "tensors:" + human.tf.memory().numTensors.toString() + " | performance: " + JSON.stringify(msg).replace(/"|{|}/g, "").replace(/,/g, " | ");
-async function detectionLoop() {
-  if (!dom.video.paused) {
-    if (timestamp.start === 0)
-      timestamp.start = human.now();
-    await human.detect(dom.video);
-    const tensors = human.tf.memory().numTensors;
-    if (tensors - timestamp.tensors !== 0)
-      log("allocated tensors:", tensors - timestamp.tensors);
-    timestamp.tensors = tensors;
-    fps.detectFPS = Math.round(1e3 * 1e3 / (human.now() - timestamp.detect)) / 1e3;
-    fps.frames++;
-    fps.averageMs = Math.round(1e3 * (human.now() - timestamp.start) / fps.frames) / 1e3;
-    if (fps.frames % 100 === 0 && !dom.video.paused)
-      log("performance", { ...fps, tensors: timestamp.tensors });
-  }
-  timestamp.detect = human.now();
-  requestAnimationFrame(detectionLoop);
-}
-async function drawLoop() {
-  var _a, _b, _c;
-  if (!dom.video.paused) {
-    const interpolated = human.next(human.result);
-    const processed = await human.image(dom.video);
-    human.draw.canvas(processed.canvas, dom.canvas);
-    const opt = { bodyLabels: `person confidence [score] and ${(_c = (_b = (_a = human.result) == null ? void 0 : _a.body) == null ? void 0 : _b[0]) == null ? void 0 : _c.keypoints.length} keypoints` };
-    await human.draw.all(dom.canvas, interpolated, opt);
-    perf(interpolated.performance);
-  }
-  const now = human.now();
-  fps.drawFPS = Math.round(1e3 * 1e3 / (now - timestamp.draw)) / 1e3;
-  timestamp.draw = now;
-  status(dom.video.paused ? "paused" : `fps: ${fps.detectFPS.toFixed(1).padStart(5, " ")} detect | ${fps.drawFPS.toFixed(1).padStart(5, " ")} draw`);
-  setTimeout(drawLoop, 30);
-}
-async function webCam() {
-  await human.webcam.start({ element: dom.video, crop: true, width });
-  dom.canvas.width = human.webcam.width;
-  dom.canvas.height = human.webcam.height;
-  dom.canvas.onclick = async () => {
-    if (human.webcam.paused)
-      await human.webcam.play();
-    else
-      human.webcam.pause();
-  };
-}
-async function main() {
-  log("human version:", human.version, "| tfjs version:", human.tf.version["tfjs-core"]);
-  log("platform:", human.env.platform, "| agent:", human.env.agent);
-  status("loading...");
-  await human.load();
-  log("backend:", human.tf.getBackend(), "| available:", human.env.backends);
-  log("models stats:", human.getModelStats());
-  log("models loaded:", Object.values(human.models).filter((model) => model !== null).length);
-  log("environment", human.env);
-  status("initializing...");
-  await human.warmup();
-  await webCam();
-  await detectionLoop();
-  await drawLoop();
-}
-window.onload = main;
+import*as m from"../../dist/human.esm.js";var f=1920,g={modelBasePath:"../../models",filter:{enabled:!0,equalization:!1,flip:!1,width:f},face:{enabled:!0,detector:{rotation:!0},mesh:{enabled:!0},attention:{enabled:!1},iris:{enabled:!0},description:{enabled:!0},emotion:{enabled:!0},antispoof:{enabled:!0},liveness:{enabled:!0}},body:{enabled:!0},hand:{enabled:!0},object:{enabled:!1},segmentation:{enabled:!1},gesture:{enabled:!0}},e=new m.Human(g);e.env.perfadd=!1;e.draw.options.font='small-caps 18px "Lato"';e.draw.options.lineHeight=20;var a={video:document.getElementById("video"),canvas:document.getElementById("canvas"),log:document.getElementById("log"),fps:document.getElementById("status"),perf:document.getElementById("performance")},n={detect:0,draw:0,tensors:0,start:0},o={detectFPS:0,drawFPS:0,frames:0,averageMs:0},s=(...t)=>{a.log.innerText+=t.join(" ")+`
+`,console.log(...t)},r=t=>a.fps.innerText=t,b=t=>a.perf.innerText="tensors:"+e.tf.memory().numTensors.toString()+" | performance: "+JSON.stringify(t).replace(/"|{|}/g,"").replace(/,/g," | ");async function u(){if(!a.video.paused){n.start===0&&(n.start=e.now()),await e.detect(a.video);let t=e.tf.memory().numTensors;t-n.tensors!==0&&s("allocated tensors:",t-n.tensors),n.tensors=t,o.detectFPS=Math.round(1e3*1e3/(e.now()-n.detect))/1e3,o.frames++,o.averageMs=Math.round(1e3*(e.now()-n.start)/o.frames)/1e3,o.frames%100===0&&!a.video.paused&&s("performance",{...o,tensors:n.tensors})}n.detect=e.now(),requestAnimationFrame(u)}async function p(){var d,i,l;if(!a.video.paused){let c=e.next(e.result),w=await e.image(a.video);e.draw.canvas(w.canvas,a.canvas);let v={bodyLabels:`person confidence [score] and ${(l=(i=(d=e.result)==null?void 0:d.body)==null?void 0:i[0])==null?void 0:l.keypoints.length} keypoints`};await e.draw.all(a.canvas,c,v),b(c.performance)}let t=e.now();o.drawFPS=Math.round(1e3*1e3/(t-n.draw))/1e3,n.draw=t,r(a.video.paused?"paused":`fps: ${o.detectFPS.toFixed(1).padStart(5," ")} detect | ${o.drawFPS.toFixed(1).padStart(5," ")} draw`),setTimeout(p,30)}async function h(){await e.webcam.start({element:a.video,crop:!0,width:f}),a.canvas.width=e.webcam.width,a.canvas.height=e.webcam.height,a.canvas.onclick=async()=>{e.webcam.paused?await e.webcam.play():e.webcam.pause()}}async function y(){s("human version:",e.version,"| tfjs version:",e.tf.version["tfjs-core"]),s("platform:",e.env.platform,"| agent:",e.env.agent),r("loading..."),await e.load(),s("backend:",e.tf.getBackend(),"| available:",e.env.backends),s("models stats:",e.getModelStats()),s("models loaded:",Object.values(e.models).filter(t=>t!==null).length),s("environment",e.env),r("initializing..."),await e.warmup(),await h(),await u(),await p()}window.onload=y;
 //# sourceMappingURL=index.js.map