updated node-multiprocess demo

demo/node-multiprocess-worker.js

@@ -30,10 +30,10 @@ async function detect(img) {
   const tensor = await image(img);
   const result = await faceapi
     .detectAllFaces(tensor, optionsSSDMobileNet)
-    .withFaceLandmarks()
-    .withFaceExpressions()
-    .withFaceDescriptors()
-    .withAgeAndGender();
+    .withFaceLandmarks();
+    // .withFaceExpressions()
+    // .withFaceDescriptors()
+    // .withAgeAndGender();
   process.send({ image: img, detected: result }); // send results back to main
   process.send({ ready: true }); // send signal back to main that this worker is now idle and ready for next image
   tensor.dispose();

demo/node-multiprocess.js

@@ -8,7 +8,7 @@ const child_process = require('child_process');
 // note that main process import faceapi or tfjs at all
 
 const imgPathRoot = './demo'; // modify to include your sample images
-const numWorkers = 2; // how many workers will be started
+const numWorkers = 4; // how many workers will be started
 const workers = []; // this holds worker processes
 const images = []; // this holds queue of enumerated images
 const t = []; // timers
@@ -33,7 +33,7 @@ function waitCompletion() {
   if (activeWorkers > 0) setImmediate(() => waitCompletion());
   else {
     t[1] = process.hrtime.bigint();
-    log.info('Processed', numImages, 'images in', Math.trunc(parseInt(t[1] - t[0]) / 1000 / 1000), 'ms');
+    log.info('Processed:', numImages, 'images in', 'total:', Math.trunc(parseInt(t[1] - t[0]) / 1000000), 'ms', 'working:', Math.trunc(parseInt(t[1] - t[2]) / 1000000), 'ms', 'average:', Math.trunc(parseInt(t[1] - t[2]) / numImages / 1000000), 'ms');
   }
 }