time based caching

README.md

@@ -60,6 +60,7 @@ Check out [**Live Demo**](https://vladmandic.github.io/human/demo/index.html) ap
 - [**Usage & Functions**](https://github.com/vladmandic/human/wiki/Usage)
 - [**Configuration Details**](https://github.com/vladmandic/human/wiki/Configuration)
 - [**Output Details**](https://github.com/vladmandic/human/wiki/Outputs)
+- [**Caching & Smoothing**](https://github.com/vladmandic/human/wiki/Caching)
 - [**Face Recognition & Face Description**](https://github.com/vladmandic/human/wiki/Embedding)
 - [**Gesture Recognition**](https://github.com/vladmandic/human/wiki/Gesture)
 - [**Common Issues**](https://github.com/vladmandic/human/wiki/Issues)

TODO.md

@@ -2,16 +2,14 @@
 
 ## Work in Progress
 
-- `skipTime`: testing, documentation
-
 <br>
 
 ### Exploring
 
-- Optical Flow: <https://docs.opencv.org/3.3.1/db/d7f/tutorial_js_lucas_kanade.html>
-- TFLite Models: <https://js.tensorflow.org/api_tflite/0.0.1-alpha.4/>
-- Histogram Equalization: Regular, Adaptive, Contrast Limited
 - Switch to custom `tfjs` for main `human` ESM bundle
+- Optical Flow: <https://docs.opencv.org/3.3.1/db/d7f/tutorial_js_lucas_kanade.html>
+- Histogram Equalization: Regular, Adaptive, Contrast Limited
+- TFLite Models: <https://js.tensorflow.org/api_tflite/0.0.1-alpha.4/>
 - Body segmentation: `robust-video-matting`
 
 #### WebGPU
@@ -55,6 +53,7 @@ Object detection using CenterNet or NanoDet models is not working when using WAS
 ## Pending Release
 
 - Update to TFJS 3.10.0
+- Time based caching
 - Multiple bug fixes
 - Utility class `human.env`
 - Add `skipTime` in addition to `skipFrames`

demo/index.js

@@ -1016,6 +1016,7 @@ async function main() {
 
   // create instance of human
   human = new Human(userConfig);
+  human.env.perfadd = true;
 
   log('human version:', human.version);
   // we've merged human defaults with user config and now lets store it back so it can be accessed by methods such as menu

dist/human.esm-nobundle.js

@@ -115,8 +115,8 @@ var config = {
   debug: true,
   async: true,
   warmup: "full",
-  cacheSensitivity: 0.75,
-  skipFrame: false,
+  cacheSensitivity: 0.7,
+  skipAllowed: false,
   filter: {
     enabled: true,
     width: 0,
@@ -146,8 +146,8 @@ var config = {
       modelPath: "blazeface.json",
       rotation: true,
       maxDetected: 1,
-      skipFrames: 11,
-      skipTime: 2e3,
+      skipFrames: 99,
+      skipTime: 2500,
       minConfidence: 0.2,
       iouThreshold: 0.1,
       return: false
@@ -163,21 +163,21 @@ var config = {
     emotion: {
       enabled: true,
       minConfidence: 0.1,
-      skipFrames: 12,
-      skipTime: 2e3,
+      skipFrames: 99,
+      skipTime: 1500,
       modelPath: "emotion.json"
     },
     description: {
       enabled: true,
       modelPath: "faceres.json",
-      skipFrames: 13,
-      skipTime: 2e3,
+      skipFrames: 99,
+      skipTime: 3e3,
       minConfidence: 0.1
     },
     antispoof: {
       enabled: false,
-      skipFrames: 14,
-      skipTime: 2e3,
+      skipFrames: 99,
+      skipTime: 4e3,
       modelPath: "antispoof.json"
     }
   },
@@ -190,12 +190,12 @@ var config = {
     maxDetected: -1,
     minConfidence: 0.3,
     skipFrames: 1,
-    skipTime: 2e3
+    skipTime: 200
   },
   hand: {
     enabled: true,
     rotation: true,
-    skipFrames: 2,
+    skipFrames: 99,
     skipTime: 2e3,
     minConfidence: 0.5,
     iouThreshold: 0.2,
@@ -214,8 +214,8 @@ var config = {
     minConfidence: 0.2,
     iouThreshold: 0.4,
     maxDetected: 10,
-    skipFrames: 15,
-    skipTime: 2e3
+    skipFrames: 99,
+    skipTime: 1e3
   },
   segmentation: {
     enabled: false,
@@ -1181,6 +1181,7 @@ var Env = class {
     __publicField(this, "filter");
     __publicField(this, "tfjs");
     __publicField(this, "offscreen");
+    __publicField(this, "perfadd", false);
     __publicField(this, "wasm", {
       supported: void 0,
       backend: void 0,
@@ -1304,7 +1305,7 @@ var model2;
 var cached = [];
 var skipped2 = Number.MAX_SAFE_INTEGER;
 var lastCount = 0;
-var last = 0;
+var lastTime = 0;
 async function load2(config3) {
   var _a, _b;
   if (env.initial)
@@ -1323,7 +1324,9 @@ async function predict(image25, config3, idx, count2) {
   var _a, _b;
   if (!model2)
     return null;
-  if (skipped2 < (((_a = config3.face.antispoof) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.antispoof) == null ? void 0 : _b.skipTime) || 0) <= now() - last && config3.skipFrame && lastCount === count2 && cached[idx]) {
+  const skipTime = (((_a = config3.face.antispoof) == null ? void 0 : _a.skipTime) || 0) > now() - lastTime;
+  const skipFrame = skipped2 < (((_b = config3.face.antispoof) == null ? void 0 : _b.skipFrames) || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && lastCount === count2 && cached[idx]) {
     skipped2++;
     return cached[idx];
   }
@@ -1334,7 +1337,7 @@ async function predict(image25, config3, idx, count2) {
     const num = (await res.data())[0];
     cached[idx] = Math.round(100 * num) / 100;
     lastCount = count2;
-    last = now();
+    lastTime = now();
     tfjs_esm_exports.dispose([resize, res]);
     resolve(cached[idx]);
   });
@@ -4910,7 +4913,7 @@ var skipped3 = Number.MAX_SAFE_INTEGER;
 var outputNodes;
 var cache = null;
 var padding = [[0, 0], [0, 0], [0, 0], [0, 0]];
-var last2 = 0;
+var lastTime2 = 0;
 async function loadDetect(config3) {
   var _a, _b, _c;
   if (env3.initial)
@@ -5027,11 +5030,13 @@ async function detectParts(input, config3, outputSize2) {
 }
 async function predict2(input, config3) {
   const outputSize2 = [input.shape[2] || 0, input.shape[1] || 0];
-  if (skipped3 < (config3.body.skipFrames || 0) && (config3.body.skipTime || 0) <= now() - last2 && config3.skipFrame && cache !== null) {
+  const skipTime = (config3.body.skipTime || 0) > now() - lastTime2;
+  const skipFrame = skipped3 < (config3.body.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && cache !== null) {
     skipped3++;
   } else {
     cache = await detectParts(input, config3, outputSize2);
-    last2 = now();
+    lastTime2 = now();
     skipped3 = 0;
   }
   if (cache)
@@ -5126,8 +5131,8 @@ var labels = [
 // src/object/centernet.ts
 var model4;
 var inputSize3 = 0;
-var last3 = [];
-var lastTime = 0;
+var last = [];
+var lastTime3 = 0;
 var skipped4 = Number.MAX_SAFE_INTEGER;
 async function load4(config3) {
   if (env.initial)
@@ -5192,21 +5197,23 @@ async function process3(res, outputShape, config3) {
   return results;
 }
 async function predict3(input, config3) {
-  if (skipped4 < (config3.object.skipFrames || 0) && (config3.object.skipTime || 0) <= now() - lastTime && config3.skipFrame && last3.length > 0) {
+  const skipTime = (config3.object.skipTime || 0) > now() - lastTime3;
+  const skipFrame = skipped4 < (config3.object.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && last.length > 0) {
     skipped4++;
-    return last3;
+    return last;
   }
   skipped4 = 0;
   if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
-    return last3;
+    return last;
   return new Promise(async (resolve) => {
     const outputSize2 = [input.shape[2], input.shape[1]];
     const resize = tfjs_esm_exports.image.resizeBilinear(input, [inputSize3, inputSize3]);
     const objectT = config3.object.enabled ? model4 == null ? void 0 : model4.execute(resize, ["tower_0/detections"]) : null;
-    lastTime = now();
+    lastTime3 = now();
     tfjs_esm_exports.dispose(resize);
     const obj = await process3(objectT, outputSize2, config3);
-    last3 = obj;
+    last = obj;
     resolve(obj);
   });
 }
@@ -5246,7 +5253,7 @@ var connected2 = {
 
 // src/body/efficientpose.ts
 var model5;
-var last4 = 0;
+var lastTime4 = 0;
 var cache2 = { id: 0, keypoints: [], box: [0, 0, 0, 0], boxRaw: [0, 0, 0, 0], score: 0, annotations: {} };
 var skipped5 = Number.MAX_SAFE_INTEGER;
 async function load5(config3) {
@@ -5278,14 +5285,15 @@ function max2d(inputs, minScore) {
   });
 }
 async function predict4(image25, config3) {
-  var _a;
-  if (skipped5 < (((_a = config3.body) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && Object.keys(cache2.keypoints).length > 0 && (config3.body.skipTime || 0) <= now() - last4) {
+  const skipTime = (config3.body.skipTime || 0) > now() - lastTime4;
+  const skipFrame = skipped5 < (config3.body.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && Object.keys(cache2.keypoints).length > 0) {
     skipped5++;
     return [cache2];
   }
   skipped5 = 0;
   return new Promise(async (resolve) => {
-    var _a2;
+    var _a;
     const tensor3 = tfjs_esm_exports.tidy(() => {
       if (!(model5 == null ? void 0 : model5.inputs[0].shape))
         return null;
@@ -5297,7 +5305,7 @@ async function predict4(image25, config3) {
     let resT;
     if (config3.body.enabled)
       resT = await (model5 == null ? void 0 : model5.predict(tensor3));
-    last4 = now();
+    lastTime4 = now();
     tfjs_esm_exports.dispose(tensor3);
     if (resT) {
       cache2.keypoints.length = 0;
@@ -5307,7 +5315,7 @@ async function predict4(image25, config3) {
       tfjs_esm_exports.dispose(squeeze8);
       for (let id = 0; id < stack3.length; id++) {
         const [x2, y2, partScore] = max2d(stack3[id], config3.body.minConfidence);
-        if (partScore > (((_a2 = config3.body) == null ? void 0 : _a2.minConfidence) || 0)) {
+        if (partScore > (((_a = config3.body) == null ? void 0 : _a.minConfidence) || 0)) {
           cache2.keypoints.push({
             score: Math.round(100 * partScore) / 100,
             part: kpt2[id],
@@ -5358,9 +5366,9 @@ async function predict4(image25, config3) {
 // src/gear/emotion.ts
 var annotations = ["angry", "disgust", "fear", "happy", "sad", "surprise", "neutral"];
 var model6;
-var last5 = [];
+var last2 = [];
 var lastCount2 = 0;
-var lastTime2 = 0;
+var lastTime5 = 0;
 var skipped6 = Number.MAX_SAFE_INTEGER;
 var rgb = [0.2989, 0.587, 0.114];
 async function load6(config3) {
@@ -5381,9 +5389,11 @@ async function predict5(image25, config3, idx, count2) {
   var _a, _b;
   if (!model6)
     return null;
-  if (skipped6 < (((_a = config3.face.emotion) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.emotion) == null ? void 0 : _b.skipTime) || 0) <= now() - lastTime2 && config3.skipFrame && lastCount2 === count2 && last5[idx] && last5[idx].length > 0) {
+  const skipFrame = skipped6 < (((_a = config3.face.emotion) == null ? void 0 : _a.skipFrames) || 0);
+  const skipTime = (((_b = config3.face.emotion) == null ? void 0 : _b.skipTime) || 0) > now() - lastTime5;
+  if (config3.skipAllowed && skipTime && skipFrame && lastCount2 === count2 && last2[idx] && last2[idx].length > 0) {
     skipped6++;
-    return last5[idx];
+    return last2[idx];
   }
   skipped6 = 0;
   return new Promise(async (resolve) => {
@@ -5406,7 +5416,7 @@ async function predict5(image25, config3, idx, count2) {
       const normalize = tfjs_esm_exports.tidy(() => tfjs_esm_exports.mul(tfjs_esm_exports.sub(grayscale, 0.5), 2));
       tfjs_esm_exports.dispose(grayscale);
       const emotionT = await (model6 == null ? void 0 : model6.predict(normalize));
-      lastTime2 = now();
+      lastTime5 = now();
       const data = await emotionT.data();
       tfjs_esm_exports.dispose(emotionT);
       for (let i = 0; i < data.length; i++) {
@@ -5416,7 +5426,7 @@ async function predict5(image25, config3, idx, count2) {
       obj.sort((a, b) => b.score - a.score);
       tfjs_esm_exports.dispose(normalize);
     }
-    last5[idx] = obj;
+    last2[idx] = obj;
     lastCount2 = count2;
     resolve(obj);
   });
@@ -5559,13 +5569,15 @@ var boxCache = [];
 var model8 = null;
 var inputSize5 = 0;
 var skipped7 = Number.MAX_SAFE_INTEGER;
-var lastTime3 = 0;
+var lastTime6 = 0;
 var detectedFaces = 0;
 async function predict6(input, config3) {
-  var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m;
-  if (!config3.skipFrame || (detectedFaces !== ((_a = config3.face.detector) == null ? void 0 : _a.maxDetected) || !((_b = config3.face.mesh) == null ? void 0 : _b.enabled)) && (skipped7 > (((_c = config3.face.detector) == null ? void 0 : _c.skipFrames) || 0) && (((_d = config3.face.description) == null ? void 0 : _d.skipTime) || 0) <= now() - lastTime3)) {
+  var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k;
+  const skipTime = (((_a = config3.face.detector) == null ? void 0 : _a.skipTime) || 0) > now() - lastTime6;
+  const skipFrame = skipped7 < (((_b = config3.face.detector) == null ? void 0 : _b.skipFrames) || 0);
+  if (!config3.skipAllowed || !skipTime || !skipFrame || detectedFaces === 0) {
     const newBoxes2 = await getBoxes(input, config3);
-    lastTime3 = now();
+    lastTime6 = now();
     boxCache = [];
     for (const possible of newBoxes2.boxes) {
       const startPoint = await possible.box.startPoint.data();
@@ -5601,16 +5613,16 @@ async function predict6(input, config3) {
       faceScore: 0,
       annotations: {}
     };
-    if (((_e = config3.face.detector) == null ? void 0 : _e.rotation) && ((_f = config3.face.mesh) == null ? void 0 : _f.enabled) && env.kernels.includes("rotatewithoffset")) {
+    if (((_c = config3.face.detector) == null ? void 0 : _c.rotation) && ((_d = config3.face.mesh) == null ? void 0 : _d.enabled) && env.kernels.includes("rotatewithoffset")) {
       [angle, rotationMatrix, face5.tensor] = correctFaceRotation(box4, input, inputSize5);
     } else {
       rotationMatrix = IDENTITY_MATRIX;
-      const cut = cutBoxFromImageAndResize({ startPoint: box4.startPoint, endPoint: box4.endPoint }, input, ((_g = config3.face.mesh) == null ? void 0 : _g.enabled) ? [inputSize5, inputSize5] : [size(), size()]);
+      const cut = cutBoxFromImageAndResize({ startPoint: box4.startPoint, endPoint: box4.endPoint }, input, ((_e = config3.face.mesh) == null ? void 0 : _e.enabled) ? [inputSize5, inputSize5] : [size(), size()]);
       face5.tensor = tfjs_esm_exports.div(cut, 255);
       tfjs_esm_exports.dispose(cut);
     }
     face5.boxScore = Math.round(100 * box4.confidence) / 100;
-    if (!((_h = config3.face.mesh) == null ? void 0 : _h.enabled)) {
+    if (!((_f = config3.face.mesh) == null ? void 0 : _f.enabled)) {
       face5.box = getClampedBox(box4, input);
       face5.boxRaw = getRawBox(box4, input);
       face5.score = Math.round(100 * box4.confidence || 0) / 100;
@@ -5633,17 +5645,17 @@ async function predict6(input, config3) {
       let rawCoords = await coordsReshaped.array();
       tfjs_esm_exports.dispose(contourCoords);
       tfjs_esm_exports.dispose(coordsReshaped);
-      if (faceConfidence < (((_i = config3.face.detector) == null ? void 0 : _i.minConfidence) || 1)) {
+      if (faceConfidence < (((_g = config3.face.detector) == null ? void 0 : _g.minConfidence) || 1)) {
         box4.confidence = faceConfidence;
       } else {
-        if ((_j = config3.face.iris) == null ? void 0 : _j.enabled)
+        if ((_h = config3.face.iris) == null ? void 0 : _h.enabled)
           rawCoords = await augmentIris(rawCoords, face5.tensor, config3, inputSize5);
         face5.mesh = transformRawCoords(rawCoords, box4, angle, rotationMatrix, inputSize5);
         face5.meshRaw = face5.mesh.map((pt) => [pt[0] / (input.shape[2] || 0), pt[1] / (input.shape[1] || 0), (pt[2] || 0) / inputSize5]);
         box4 = { ...enlargeBox(calculateLandmarksBoundingBox(face5.mesh), 1.5), confidence: box4.confidence };
         for (const key of Object.keys(meshAnnotations))
           face5.annotations[key] = meshAnnotations[key].map((index) => face5.mesh[index]);
-        if (((_k = config3.face.detector) == null ? void 0 : _k.rotation) && config3.face.mesh.enabled && ((_l = config3.face.description) == null ? void 0 : _l.enabled) && env.kernels.includes("rotatewithoffset")) {
+        if (((_i = config3.face.detector) == null ? void 0 : _i.rotation) && config3.face.mesh.enabled && ((_j = config3.face.description) == null ? void 0 : _j.enabled) && env.kernels.includes("rotatewithoffset")) {
           tfjs_esm_exports.dispose(face5.tensor);
           [angle, rotationMatrix, face5.tensor] = correctFaceRotation(box4, input, inputSize5);
         }
@@ -5657,7 +5669,7 @@ async function predict6(input, config3) {
     faces.push(face5);
     newBoxes.push(box4);
   }
-  if ((_m = config3.face.mesh) == null ? void 0 : _m.enabled)
+  if ((_k = config3.face.mesh) == null ? void 0 : _k.enabled)
     boxCache = newBoxes.filter((a) => {
       var _a2;
       return a.confidence > (((_a2 = config3.face.detector) == null ? void 0 : _a2.minConfidence) || 0);
@@ -5687,8 +5699,8 @@ var uvmap = UV468;
 
 // src/face/faceres.ts
 var model9;
-var last6 = [];
-var lastTime4 = 0;
+var last3 = [];
+var lastTime7 = 0;
 var lastCount3 = 0;
 var skipped8 = Number.MAX_SAFE_INTEGER;
 async function load9(config3) {
@@ -5724,9 +5736,11 @@ async function predict7(image25, config3, idx, count2) {
   var _a, _b, _c, _d;
   if (!model9)
     return null;
-  if (skipped8 < (((_a = config3.face.description) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.description) == null ? void 0 : _b.skipTime) || 0) <= now() - lastTime4 && config3.skipFrame && lastCount3 === count2 && ((_c = last6[idx]) == null ? void 0 : _c.age) && ((_d = last6[idx]) == null ? void 0 : _d.age) > 0) {
+  const skipFrame = skipped8 < (((_a = config3.face.description) == null ? void 0 : _a.skipFrames) || 0);
+  const skipTime = (((_b = config3.face.description) == null ? void 0 : _b.skipTime) || 0) > now() - lastTime7;
+  if (config3.skipAllowed && skipFrame && skipTime && lastCount3 === count2 && ((_c = last3[idx]) == null ? void 0 : _c.age) && ((_d = last3[idx]) == null ? void 0 : _d.age) > 0) {
     skipped8++;
-    return last6[idx];
+    return last3[idx];
   }
   skipped8 = 0;
   return new Promise(async (resolve) => {
@@ -5740,7 +5754,7 @@ async function predict7(image25, config3, idx, count2) {
     if ((_a2 = config3.face.description) == null ? void 0 : _a2.enabled) {
       const enhanced = enhance(image25);
       const resT = await (model9 == null ? void 0 : model9.predict(enhanced));
-      lastTime4 = now();
+      lastTime7 = now();
       tfjs_esm_exports.dispose(enhanced);
       const genderT = await resT.find((t) => t.shape[1] === 1);
       const gender = await genderT.data();
@@ -5760,7 +5774,7 @@ async function predict7(image25, config3, idx, count2) {
       obj.descriptor = Array.from(descriptor);
       resT.forEach((t) => tfjs_esm_exports.dispose(t));
     }
-    last6[idx] = obj;
+    last3[idx] = obj;
     lastCount3 = count2;
     resolve(obj);
   });
@@ -8907,7 +8921,7 @@ var handBoxEnlargeFactor = 1.65;
 var palmLandmarkIds = [0, 5, 9, 13, 17, 1, 2];
 var palmLandmarksPalmBase = 0;
 var palmLandmarksMiddleFingerBase = 2;
-var lastTime5 = 0;
+var lastTime8 = 0;
 var HandPipeline = class {
   constructor(handDetector, handPoseModel2) {
     __publicField(this, "handDetector");
@@ -8920,7 +8934,7 @@ var HandPipeline = class {
     this.handPoseModel = handPoseModel2;
     this.inputSize = this.handPoseModel && this.handPoseModel.inputs[0].shape ? this.handPoseModel.inputs[0].shape[2] : 0;
     this.storedBoxes = [];
-    this.skipped = 0;
+    this.skipped = Number.MAX_SAFE_INTEGER;
     this.detectedHands = 0;
   }
   calculateLandmarksBoundingBox(landmarks) {
@@ -8972,11 +8986,13 @@ var HandPipeline = class {
   async estimateHands(image25, config3) {
     let useFreshBox = false;
     let boxes;
-    if (this.skipped === 0 || this.skipped > config3.hand.skipFrames && (config3.hand.skipTime || 0) <= now() - lastTime5 || !config3.hand.landmarks || !config3.skipFrame) {
+    const skipTime = (config3.hand.skipTime || 0) > now() - lastTime8;
+    const skipFrame = this.skipped < (config3.hand.skipFrames || 0);
+    if (config3.skipAllowed && skipTime && skipFrame) {
       boxes = await this.handDetector.estimateHandBounds(image25, config3);
       this.skipped = 0;
     }
-    if (config3.skipFrame)
+    if (config3.skipAllowed)
       this.skipped++;
     if (boxes && boxes.length > 0 && (boxes.length !== this.detectedHands && this.detectedHands !== config3.hand.maxDetected || !config3.hand.landmarks)) {
       this.detectedHands = 0;
@@ -9001,7 +9017,7 @@ var HandPipeline = class {
         tfjs_esm_exports.dispose(croppedInput);
         tfjs_esm_exports.dispose(rotatedImage);
         const [confidenceT, keypoints] = await this.handPoseModel.predict(handImage);
-        lastTime5 = now();
+        lastTime8 = now();
         tfjs_esm_exports.dispose(handImage);
         const confidence = (await confidenceT.data())[0];
         tfjs_esm_exports.dispose(confidenceT);
@@ -9569,8 +9585,8 @@ var faceIndex = 4;
 var boxExpandFact = 1.6;
 var maxDetectorResolution = 512;
 var detectorExpandFact = 1.4;
-var skipped9 = 0;
-var lastTime6 = 0;
+var skipped9 = Number.MAX_SAFE_INTEGER;
+var lastTime9 = 0;
 var outputSize = [0, 0];
 var cache3 = {
   boxes: [],
@@ -9710,17 +9726,21 @@ async function predict9(input, config3) {
     return [];
   outputSize = [input.shape[2] || 0, input.shape[1] || 0];
   skipped9++;
-  if (config3.skipFrame && skipped9 <= (config3.hand.skipFrames || 0) && (config3.hand.skipTime || 0) <= now() - lastTime6) {
+  const skipTime = (config3.hand.skipTime || 0) > now() - lastTime9;
+  const skipFrame = skipped9 < (config3.hand.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame) {
     return cache3.hands;
   }
   return new Promise(async (resolve) => {
-    if (config3.skipFrame && cache3.hands.length === config3.hand.maxDetected) {
+    const skipTimeExtended = 3 * (config3.hand.skipTime || 0) > now() - lastTime9;
+    const skipFrameExtended = skipped9 < 3 * (config3.hand.skipFrames || 0);
+    if (config3.skipAllowed && cache3.hands.length === config3.hand.maxDetected) {
       cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
-    } else if (config3.skipFrame && skipped9 < 3 * (config3.hand.skipFrames || 0) && (config3.hand.skipTime || 0) <= 3 * (now() - lastTime6) && cache3.hands.length > 0) {
+    } else if (config3.skipAllowed && skipTimeExtended && skipFrameExtended && cache3.hands.length > 0) {
       cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
     } else {
       cache3.boxes = await detectHands(input, config3);
-      lastTime6 = now();
+      lastTime9 = now();
       cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
       skipped9 = 0;
     }
@@ -10015,10 +10035,12 @@ async function parseMultiPose(res, config3, image25, inputBox) {
 async function predict10(input, config3) {
   if (!model10 || !(model10 == null ? void 0 : model10.inputs[0].shape))
     return [];
-  if (!config3.skipFrame)
+  if (!config3.skipAllowed)
     cache5.boxes.length = 0;
   skipped10++;
-  if (config3.skipFrame && (skipped10 <= (config3.body.skipFrames || 0) && (config3.body.skipTime || 0) <= now() - cache5.last)) {
+  const skipTime = (config3.body.skipTime || 0) > now() - cache5.last;
+  const skipFrame = skipped10 < (config3.body.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame) {
     return cache5.bodies;
   }
   return new Promise(async (resolve) => {
@@ -10040,8 +10062,8 @@ async function predict10(input, config3) {
 
 // src/object/nanodet.ts
 var model11;
-var last7 = [];
-var lastTime7 = 0;
+var last4 = [];
+var lastTime10 = 0;
 var skipped11 = Number.MAX_SAFE_INTEGER;
 var scaleBox = 2.5;
 async function load12(config3) {
@@ -10121,13 +10143,15 @@ async function process4(res, inputSize8, outputShape, config3) {
   return results;
 }
 async function predict11(image25, config3) {
-  if (skipped11 < (config3.object.skipFrames || 0) && (config3.object.skipTime || 0) <= now() - lastTime7 && config3.skipFrame && last7.length > 0) {
+  const skipTime = (config3.object.skipTime || 0) > now() - lastTime10;
+  const skipFrame = skipped11 < (config3.object.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && last4.length > 0) {
     skipped11++;
-    return last7;
+    return last4;
   }
   skipped11 = 0;
   if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
-    return last7;
+    return last4;
   return new Promise(async (resolve) => {
     const outputSize2 = [image25.shape[2], image25.shape[1]];
     const resize = tfjs_esm_exports.image.resizeBilinear(image25, [model11.inputSize, model11.inputSize], false);
@@ -10138,10 +10162,10 @@ async function predict11(image25, config3) {
     let objectT;
     if (config3.object.enabled)
       objectT = await model11.predict(transpose);
-    lastTime7 = now();
+    lastTime10 = now();
     tfjs_esm_exports.dispose(transpose);
     const obj = await process4(objectT, model11.inputSize, outputSize2, config3);
-    last7 = obj;
+    last4 = obj;
     resolve(obj);
   });
 }
@@ -11336,7 +11360,7 @@ async function canvas2(input, output) {
 async function all(inCanvas2, result, drawOptions) {
   if (!result || !result.performance || !result || !inCanvas2)
     return null;
-  const timestamp = now();
+  const timeStamp = now();
   const localOptions = mergeDeep(options2, drawOptions);
   const promise = Promise.all([
     face(inCanvas2, result.face, localOptions),
@@ -11345,7 +11369,7 @@ async function all(inCanvas2, result, drawOptions) {
     object(inCanvas2, result.object, localOptions),
     gesture(inCanvas2, result.gesture, localOptions)
   ]);
-  result.performance.draw = Math.trunc(now() - timestamp);
+  result.performance.draw = env.perfadd ? (result.performance.draw || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
   return promise;
 }
 
@@ -11470,7 +11494,7 @@ var detectFace = async (parent, input) => {
   parent.state = "run:face";
   timeStamp = now();
   const faces = await predict6(input, parent.config);
-  parent.performance.face = Math.trunc(now() - timeStamp);
+  parent.performance.face = env.perfadd ? (parent.performance.face || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
   if (!input.shape || input.shape.length !== 4)
     return [];
   if (!faces)
@@ -11489,7 +11513,7 @@ var detectFace = async (parent, input) => {
       parent.state = "run:emotion";
       timeStamp = now();
       emotionRes = parent.config.face.emotion.enabled ? await predict5(faces[i].tensor || tfjs_esm_exports.tensor([]), parent.config, i, faces.length) : null;
-      parent.performance.emotion = Math.trunc(now() - timeStamp);
+      parent.performance.emotion = env.perfadd ? (parent.performance.emotion || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     parent.analyze("End Emotion:");
     parent.analyze("Start AntiSpoof:");
@@ -11499,7 +11523,7 @@ var detectFace = async (parent, input) => {
       parent.state = "run:antispoof";
       timeStamp = now();
       antispoofRes = parent.config.face.antispoof.enabled ? await predict(faces[i].tensor || tfjs_esm_exports.tensor([]), parent.config, i, faces.length) : null;
-      parent.performance.antispoof = Math.trunc(now() - timeStamp);
+      parent.performance.antispoof = env.perfadd ? (parent.performance.antispoof || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     parent.analyze("End AntiSpoof:");
     parent.analyze("Start Description:");
@@ -11509,7 +11533,7 @@ var detectFace = async (parent, input) => {
       parent.state = "run:description";
       timeStamp = now();
       descRes = parent.config.face.description.enabled ? await predict7(faces[i].tensor || tfjs_esm_exports.tensor([]), parent.config, i, faces.length) : null;
-      parent.performance.embedding = Math.trunc(now() - timeStamp);
+      parent.performance.embedding = env.perfadd ? (parent.performance.embedding || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     parent.analyze("End Description:");
     if (parent.config.async) {
@@ -12827,7 +12851,7 @@ var Human = class {
     const count2 = Object.values(this.models).filter((model14) => model14).length;
     if (userConfig)
       this.config = mergeDeep(this.config, userConfig);
-    if (env.initial) {
+    if (this.env.initial) {
       if (this.config.debug)
         log(`version: ${this.version}`);
       if (this.config.debug)
@@ -12843,9 +12867,9 @@ var Human = class {
       }
     }
     await load15(this);
-    if (env.initial && this.config.debug)
+    if (this.env.initial && this.config.debug)
       log("tf engine state:", this.tf.engine().state.numBytes, "bytes", this.tf.engine().state.numTensors, "tensors");
-    env.initial = false;
+    this.env.initial = false;
     const loaded = Object.values(this.models).filter((model14) => model14).length;
     if (loaded !== count2) {
       await validate2(this);
@@ -12853,7 +12877,7 @@ var Human = class {
     }
     const current = Math.trunc(now() - timeStamp);
     if (current > (this.performance.load || 0))
-      this.performance.load = current;
+      this.performance.load = this.env.perfadd ? (this.performance.load || 0) + current : current;
   }
   next(result = this.result) {
     return calc2(result, this.config);
@@ -12867,7 +12891,6 @@ var Human = class {
       var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q, _r, _s, _t, _u, _v;
       this.state = "config";
       let timeStamp;
-      let elapsedTime;
       this.config = mergeDeep(this.config, userConfig);
       this.state = "check";
       const error = __privateGet(this, _sanity).call(this, input);
@@ -12882,7 +12905,7 @@ var Human = class {
       this.state = "image";
       const img = process2(input, this.config);
       this.process = img;
-      this.performance.image = Math.trunc(now() - timeStamp);
+      this.performance.image = this.env.perfadd ? (this.performance.image || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       this.analyze("Get Image:");
       if (!img.tensor) {
         if (this.config.debug)
@@ -12892,15 +12915,15 @@ var Human = class {
       }
       this.emit("image");
       timeStamp = now();
-      this.config.skipFrame = await skip(this.config, img.tensor);
+      this.config.skipAllowed = await skip(this.config, img.tensor);
       if (!this.performance.frames)
         this.performance.frames = 0;
       if (!this.performance.cached)
         this.performance.cached = 0;
       this.performance.frames++;
-      if (this.config.skipFrame)
+      if (this.config.skipAllowed)
         this.performance.cached++;
-      this.performance.changed = Math.trunc(now() - timeStamp);
+      this.performance.changed = this.env.perfadd ? (this.performance.changed || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       this.analyze("Check Changed:");
       let faceRes = [];
       let bodyRes = [];
@@ -12914,9 +12937,7 @@ var Human = class {
       } else {
         timeStamp = now();
         faceRes = this.config.face.enabled ? await detectFace(this, img.tensor) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0)
-          this.performance.face = elapsedTime;
+        this.performance.face = this.env.perfadd ? (this.performance.face || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       if (this.config.async && (this.config.body.maxDetected === -1 || this.config.hand.maxDetected === -1))
         faceRes = await faceRes;
@@ -12944,9 +12965,7 @@ var Human = class {
           bodyRes = this.config.body.enabled ? await predict4(img.tensor, bodyConfig) : [];
         else if ((_h = this.config.body.modelPath) == null ? void 0 : _h.includes("movenet"))
           bodyRes = this.config.body.enabled ? await predict10(img.tensor, bodyConfig) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0)
-          this.performance.body = elapsedTime;
+        this.performance.body = this.env.perfadd ? (this.performance.body || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       this.analyze("End Body:");
       this.analyze("Start Hand:");
@@ -12965,9 +12984,7 @@ var Human = class {
           handRes = this.config.hand.enabled ? await predict8(img.tensor, handConfig) : [];
         else if ((_p = (_o = this.config.hand.detector) == null ? void 0 : _o.modelPath) == null ? void 0 : _p.includes("handtrack"))
           handRes = this.config.hand.enabled ? await predict9(img.tensor, handConfig) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0)
-          this.performance.hand = elapsedTime;
+        this.performance.hand = this.env.perfadd ? (this.performance.hand || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       this.analyze("End Hand:");
       this.analyze("Start Object:");
@@ -12985,9 +13002,7 @@ var Human = class {
           objectRes = this.config.object.enabled ? await predict11(img.tensor, this.config) : [];
         else if ((_t = this.config.object.modelPath) == null ? void 0 : _t.includes("centernet"))
           objectRes = this.config.object.enabled ? await predict3(img.tensor, this.config) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0)
-          this.performance.object = elapsedTime;
+        this.performance.object = this.env.perfadd ? (this.performance.object || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       this.analyze("End Object:");
       this.state = "detect:await";
@@ -12999,7 +13014,7 @@ var Human = class {
         timeStamp = now();
         gestureRes = [...face2(faceRes), ...body2(bodyRes), ...hand2(handRes), ...iris3(faceRes)];
         if (!this.config.async)
-          this.performance.gesture = Math.trunc(now() - timeStamp);
+          this.performance.gesture = this.env.perfadd ? (this.performance.gesture || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
         else if (this.performance.gesture)
           delete this.performance.gesture;
       }

dist/human.esm.js

@@ -104,8 +104,8 @@ var config = {
   debug: true,
   async: true,
   warmup: "full",
-  cacheSensitivity: 0.75,
-  skipFrame: false,
+  cacheSensitivity: 0.7,
+  skipAllowed: false,
   filter: {
     enabled: true,
     width: 0,
@@ -135,8 +135,8 @@ var config = {
       modelPath: "blazeface.json",
       rotation: true,
       maxDetected: 1,
-      skipFrames: 11,
-      skipTime: 2e3,
+      skipFrames: 99,
+      skipTime: 2500,
       minConfidence: 0.2,
       iouThreshold: 0.1,
       return: false
@@ -152,21 +152,21 @@ var config = {
     emotion: {
       enabled: true,
       minConfidence: 0.1,
-      skipFrames: 12,
-      skipTime: 2e3,
+      skipFrames: 99,
+      skipTime: 1500,
       modelPath: "emotion.json"
     },
     description: {
       enabled: true,
       modelPath: "faceres.json",
-      skipFrames: 13,
-      skipTime: 2e3,
+      skipFrames: 99,
+      skipTime: 3e3,
       minConfidence: 0.1
     },
     antispoof: {
       enabled: false,
-      skipFrames: 14,
-      skipTime: 2e3,
+      skipFrames: 99,
+      skipTime: 4e3,
       modelPath: "antispoof.json"
     }
   },
@@ -179,12 +179,12 @@ var config = {
     maxDetected: -1,
     minConfidence: 0.3,
     skipFrames: 1,
-    skipTime: 2e3
+    skipTime: 200
   },
   hand: {
     enabled: true,
     rotation: true,
-    skipFrames: 2,
+    skipFrames: 99,
     skipTime: 2e3,
     minConfidence: 0.5,
     iouThreshold: 0.2,
@@ -203,8 +203,8 @@ var config = {
     minConfidence: 0.2,
     iouThreshold: 0.4,
     maxDetected: 10,
-    skipFrames: 15,
-    skipTime: 2e3
+    skipFrames: 99,
+    skipTime: 1e3
   },
   segmentation: {
     enabled: false,
@@ -34798,6 +34798,7 @@ var Env = class {
     __publicField(this, "filter");
     __publicField(this, "tfjs");
     __publicField(this, "offscreen");
+    __publicField(this, "perfadd", false);
     __publicField(this, "wasm", {
       supported: void 0,
       backend: void 0,
@@ -34921,7 +34922,7 @@ var model2;
 var cached = [];
 var skipped2 = Number.MAX_SAFE_INTEGER;
 var lastCount = 0;
-var last = 0;
+var lastTime = 0;
 async function load2(config3) {
   var _a2, _b;
   if (env.initial)
@@ -34940,7 +34941,9 @@ async function predict(image6, config3, idx, count2) {
   var _a2, _b;
   if (!model2)
     return null;
-  if (skipped2 < (((_a2 = config3.face.antispoof) == null ? void 0 : _a2.skipFrames) || 0) && (((_b = config3.face.antispoof) == null ? void 0 : _b.skipTime) || 0) <= now() - last && config3.skipFrame && lastCount === count2 && cached[idx]) {
+  const skipTime = (((_a2 = config3.face.antispoof) == null ? void 0 : _a2.skipTime) || 0) > now() - lastTime;
+  const skipFrame = skipped2 < (((_b = config3.face.antispoof) == null ? void 0 : _b.skipFrames) || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && lastCount === count2 && cached[idx]) {
     skipped2++;
     return cached[idx];
   }
@@ -34951,7 +34954,7 @@ async function predict(image6, config3, idx, count2) {
     const num = (await res.data())[0];
     cached[idx] = Math.round(100 * num) / 100;
     lastCount = count2;
-    last = now();
+    lastTime = now();
     De([resize, res]);
     resolve(cached[idx]);
   });
@@ -38527,7 +38530,7 @@ var skipped3 = Number.MAX_SAFE_INTEGER;
 var outputNodes;
 var cache = null;
 var padding = [[0, 0], [0, 0], [0, 0], [0, 0]];
-var last2 = 0;
+var lastTime2 = 0;
 async function loadDetect(config3) {
   var _a2, _b, _c2;
   if (env2.initial)
@@ -38644,11 +38647,13 @@ async function detectParts(input, config3, outputSize2) {
 }
 async function predict2(input, config3) {
   const outputSize2 = [input.shape[2] || 0, input.shape[1] || 0];
-  if (skipped3 < (config3.body.skipFrames || 0) && (config3.body.skipTime || 0) <= now() - last2 && config3.skipFrame && cache !== null) {
+  const skipTime = (config3.body.skipTime || 0) > now() - lastTime2;
+  const skipFrame = skipped3 < (config3.body.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && cache !== null) {
     skipped3++;
   } else {
     cache = await detectParts(input, config3, outputSize2);
-    last2 = now();
+    lastTime2 = now();
     skipped3 = 0;
   }
   if (cache)
@@ -38743,8 +38748,8 @@ var labels = [
 // src/object/centernet.ts
 var model4;
 var inputSize3 = 0;
-var last3 = [];
-var lastTime = 0;
+var last = [];
+var lastTime3 = 0;
 var skipped4 = Number.MAX_SAFE_INTEGER;
 async function load4(config3) {
   if (env.initial)
@@ -38809,21 +38814,23 @@ async function process3(res, outputShape, config3) {
   return results;
 }
 async function predict3(input, config3) {
-  if (skipped4 < (config3.object.skipFrames || 0) && (config3.object.skipTime || 0) <= now() - lastTime && config3.skipFrame && last3.length > 0) {
+  const skipTime = (config3.object.skipTime || 0) > now() - lastTime3;
+  const skipFrame = skipped4 < (config3.object.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && last.length > 0) {
     skipped4++;
-    return last3;
+    return last;
   }
   skipped4 = 0;
   if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
-    return last3;
+    return last;
   return new Promise(async (resolve) => {
     const outputSize2 = [input.shape[2], input.shape[1]];
     const resize = Cn.resizeBilinear(input, [inputSize3, inputSize3]);
     const objectT = config3.object.enabled ? model4 == null ? void 0 : model4.execute(resize, ["tower_0/detections"]) : null;
-    lastTime = now();
+    lastTime3 = now();
     De(resize);
     const obj = await process3(objectT, outputSize2, config3);
-    last3 = obj;
+    last = obj;
     resolve(obj);
   });
 }
@@ -38863,7 +38870,7 @@ var connected2 = {
 
 // src/body/efficientpose.ts
 var model5;
-var last4 = 0;
+var lastTime4 = 0;
 var cache2 = { id: 0, keypoints: [], box: [0, 0, 0, 0], boxRaw: [0, 0, 0, 0], score: 0, annotations: {} };
 var skipped5 = Number.MAX_SAFE_INTEGER;
 async function load5(config3) {
@@ -38895,14 +38902,15 @@ function max2d(inputs, minScore) {
   });
 }
 async function predict4(image6, config3) {
-  var _a2;
-  if (skipped5 < (((_a2 = config3.body) == null ? void 0 : _a2.skipFrames) || 0) && config3.skipFrame && Object.keys(cache2.keypoints).length > 0 && (config3.body.skipTime || 0) <= now() - last4) {
+  const skipTime = (config3.body.skipTime || 0) > now() - lastTime4;
+  const skipFrame = skipped5 < (config3.body.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && Object.keys(cache2.keypoints).length > 0) {
     skipped5++;
     return [cache2];
   }
   skipped5 = 0;
   return new Promise(async (resolve) => {
-    var _a3;
+    var _a2;
     const tensor = V(() => {
       if (!(model5 == null ? void 0 : model5.inputs[0].shape))
         return null;
@@ -38914,7 +38922,7 @@ async function predict4(image6, config3) {
     let resT;
     if (config3.body.enabled)
       resT = await (model5 == null ? void 0 : model5.predict(tensor));
-    last4 = now();
+    lastTime4 = now();
     De(tensor);
     if (resT) {
       cache2.keypoints.length = 0;
@@ -38924,7 +38932,7 @@ async function predict4(image6, config3) {
       De(squeeze);
       for (let id2 = 0; id2 < stack.length; id2++) {
         const [x7, y7, partScore] = max2d(stack[id2], config3.body.minConfidence);
-        if (partScore > (((_a3 = config3.body) == null ? void 0 : _a3.minConfidence) || 0)) {
+        if (partScore > (((_a2 = config3.body) == null ? void 0 : _a2.minConfidence) || 0)) {
           cache2.keypoints.push({
             score: Math.round(100 * partScore) / 100,
             part: kpt2[id2],
@@ -38975,9 +38983,9 @@ async function predict4(image6, config3) {
 // src/gear/emotion.ts
 var annotations = ["angry", "disgust", "fear", "happy", "sad", "surprise", "neutral"];
 var model6;
-var last5 = [];
+var last2 = [];
 var lastCount2 = 0;
-var lastTime2 = 0;
+var lastTime5 = 0;
 var skipped6 = Number.MAX_SAFE_INTEGER;
 var rgb = [0.2989, 0.587, 0.114];
 async function load6(config3) {
@@ -38998,9 +39006,11 @@ async function predict5(image6, config3, idx, count2) {
   var _a2, _b;
   if (!model6)
     return null;
-  if (skipped6 < (((_a2 = config3.face.emotion) == null ? void 0 : _a2.skipFrames) || 0) && (((_b = config3.face.emotion) == null ? void 0 : _b.skipTime) || 0) <= now() - lastTime2 && config3.skipFrame && lastCount2 === count2 && last5[idx] && last5[idx].length > 0) {
+  const skipFrame = skipped6 < (((_a2 = config3.face.emotion) == null ? void 0 : _a2.skipFrames) || 0);
+  const skipTime = (((_b = config3.face.emotion) == null ? void 0 : _b.skipTime) || 0) > now() - lastTime5;
+  if (config3.skipAllowed && skipTime && skipFrame && lastCount2 === count2 && last2[idx] && last2[idx].length > 0) {
     skipped6++;
-    return last5[idx];
+    return last2[idx];
   }
   skipped6 = 0;
   return new Promise(async (resolve) => {
@@ -39023,7 +39033,7 @@ async function predict5(image6, config3, idx, count2) {
       const normalize = V(() => O(le(grayscale, 0.5), 2));
       De(grayscale);
       const emotionT = await (model6 == null ? void 0 : model6.predict(normalize));
-      lastTime2 = now();
+      lastTime5 = now();
       const data = await emotionT.data();
       De(emotionT);
       for (let i = 0; i < data.length; i++) {
@@ -39033,7 +39043,7 @@ async function predict5(image6, config3, idx, count2) {
       obj.sort((a, b10) => b10.score - a.score);
       De(normalize);
     }
-    last5[idx] = obj;
+    last2[idx] = obj;
     lastCount2 = count2;
     resolve(obj);
   });
@@ -39176,13 +39186,15 @@ var boxCache = [];
 var model8 = null;
 var inputSize5 = 0;
 var skipped7 = Number.MAX_SAFE_INTEGER;
-var lastTime3 = 0;
+var lastTime6 = 0;
 var detectedFaces = 0;
 async function predict6(input, config3) {
-  var _a2, _b, _c2, _d2, _e, _f2, _g, _h2, _i2, _j2, _k2, _l2, _m2;
-  if (!config3.skipFrame || (detectedFaces !== ((_a2 = config3.face.detector) == null ? void 0 : _a2.maxDetected) || !((_b = config3.face.mesh) == null ? void 0 : _b.enabled)) && (skipped7 > (((_c2 = config3.face.detector) == null ? void 0 : _c2.skipFrames) || 0) && (((_d2 = config3.face.description) == null ? void 0 : _d2.skipTime) || 0) <= now() - lastTime3)) {
+  var _a2, _b, _c2, _d2, _e, _f2, _g, _h2, _i2, _j2, _k2;
+  const skipTime = (((_a2 = config3.face.detector) == null ? void 0 : _a2.skipTime) || 0) > now() - lastTime6;
+  const skipFrame = skipped7 < (((_b = config3.face.detector) == null ? void 0 : _b.skipFrames) || 0);
+  if (!config3.skipAllowed || !skipTime || !skipFrame || detectedFaces === 0) {
     const newBoxes2 = await getBoxes(input, config3);
-    lastTime3 = now();
+    lastTime6 = now();
     boxCache = [];
     for (const possible of newBoxes2.boxes) {
       const startPoint = await possible.box.startPoint.data();
@@ -39218,16 +39230,16 @@ async function predict6(input, config3) {
       faceScore: 0,
       annotations: {}
     };
-    if (((_e = config3.face.detector) == null ? void 0 : _e.rotation) && ((_f2 = config3.face.mesh) == null ? void 0 : _f2.enabled) && env.kernels.includes("rotatewithoffset")) {
+    if (((_c2 = config3.face.detector) == null ? void 0 : _c2.rotation) && ((_d2 = config3.face.mesh) == null ? void 0 : _d2.enabled) && env.kernels.includes("rotatewithoffset")) {
       [angle, rotationMatrix, face5.tensor] = correctFaceRotation(box4, input, inputSize5);
     } else {
       rotationMatrix = IDENTITY_MATRIX;
-      const cut = cutBoxFromImageAndResize({ startPoint: box4.startPoint, endPoint: box4.endPoint }, input, ((_g = config3.face.mesh) == null ? void 0 : _g.enabled) ? [inputSize5, inputSize5] : [size(), size()]);
+      const cut = cutBoxFromImageAndResize({ startPoint: box4.startPoint, endPoint: box4.endPoint }, input, ((_e = config3.face.mesh) == null ? void 0 : _e.enabled) ? [inputSize5, inputSize5] : [size(), size()]);
       face5.tensor = ce(cut, 255);
       De(cut);
     }
     face5.boxScore = Math.round(100 * box4.confidence) / 100;
-    if (!((_h2 = config3.face.mesh) == null ? void 0 : _h2.enabled)) {
+    if (!((_f2 = config3.face.mesh) == null ? void 0 : _f2.enabled)) {
       face5.box = getClampedBox(box4, input);
       face5.boxRaw = getRawBox(box4, input);
       face5.score = Math.round(100 * box4.confidence || 0) / 100;
@@ -39250,17 +39262,17 @@ async function predict6(input, config3) {
       let rawCoords = await coordsReshaped.array();
       De(contourCoords);
       De(coordsReshaped);
-      if (faceConfidence < (((_i2 = config3.face.detector) == null ? void 0 : _i2.minConfidence) || 1)) {
+      if (faceConfidence < (((_g = config3.face.detector) == null ? void 0 : _g.minConfidence) || 1)) {
         box4.confidence = faceConfidence;
       } else {
-        if ((_j2 = config3.face.iris) == null ? void 0 : _j2.enabled)
+        if ((_h2 = config3.face.iris) == null ? void 0 : _h2.enabled)
           rawCoords = await augmentIris(rawCoords, face5.tensor, config3, inputSize5);
         face5.mesh = transformRawCoords(rawCoords, box4, angle, rotationMatrix, inputSize5);
         face5.meshRaw = face5.mesh.map((pt) => [pt[0] / (input.shape[2] || 0), pt[1] / (input.shape[1] || 0), (pt[2] || 0) / inputSize5]);
         box4 = { ...enlargeBox(calculateLandmarksBoundingBox(face5.mesh), 1.5), confidence: box4.confidence };
         for (const key of Object.keys(meshAnnotations))
           face5.annotations[key] = meshAnnotations[key].map((index) => face5.mesh[index]);
-        if (((_k2 = config3.face.detector) == null ? void 0 : _k2.rotation) && config3.face.mesh.enabled && ((_l2 = config3.face.description) == null ? void 0 : _l2.enabled) && env.kernels.includes("rotatewithoffset")) {
+        if (((_i2 = config3.face.detector) == null ? void 0 : _i2.rotation) && config3.face.mesh.enabled && ((_j2 = config3.face.description) == null ? void 0 : _j2.enabled) && env.kernels.includes("rotatewithoffset")) {
           De(face5.tensor);
           [angle, rotationMatrix, face5.tensor] = correctFaceRotation(box4, input, inputSize5);
         }
@@ -39274,7 +39286,7 @@ async function predict6(input, config3) {
     faces.push(face5);
     newBoxes.push(box4);
   }
-  if ((_m2 = config3.face.mesh) == null ? void 0 : _m2.enabled)
+  if ((_k2 = config3.face.mesh) == null ? void 0 : _k2.enabled)
     boxCache = newBoxes.filter((a) => {
       var _a3;
       return a.confidence > (((_a3 = config3.face.detector) == null ? void 0 : _a3.minConfidence) || 0);
@@ -39304,8 +39316,8 @@ var uvmap = UV468;
 
 // src/face/faceres.ts
 var model9;
-var last6 = [];
-var lastTime4 = 0;
+var last3 = [];
+var lastTime7 = 0;
 var lastCount3 = 0;
 var skipped8 = Number.MAX_SAFE_INTEGER;
 async function load9(config3) {
@@ -39341,9 +39353,11 @@ async function predict7(image6, config3, idx, count2) {
   var _a2, _b, _c2, _d2;
   if (!model9)
     return null;
-  if (skipped8 < (((_a2 = config3.face.description) == null ? void 0 : _a2.skipFrames) || 0) && (((_b = config3.face.description) == null ? void 0 : _b.skipTime) || 0) <= now() - lastTime4 && config3.skipFrame && lastCount3 === count2 && ((_c2 = last6[idx]) == null ? void 0 : _c2.age) && ((_d2 = last6[idx]) == null ? void 0 : _d2.age) > 0) {
+  const skipFrame = skipped8 < (((_a2 = config3.face.description) == null ? void 0 : _a2.skipFrames) || 0);
+  const skipTime = (((_b = config3.face.description) == null ? void 0 : _b.skipTime) || 0) > now() - lastTime7;
+  if (config3.skipAllowed && skipFrame && skipTime && lastCount3 === count2 && ((_c2 = last3[idx]) == null ? void 0 : _c2.age) && ((_d2 = last3[idx]) == null ? void 0 : _d2.age) > 0) {
     skipped8++;
-    return last6[idx];
+    return last3[idx];
   }
   skipped8 = 0;
   return new Promise(async (resolve) => {
@@ -39357,7 +39371,7 @@ async function predict7(image6, config3, idx, count2) {
     if ((_a3 = config3.face.description) == null ? void 0 : _a3.enabled) {
       const enhanced = enhance(image6);
       const resT = await (model9 == null ? void 0 : model9.predict(enhanced));
-      lastTime4 = now();
+      lastTime7 = now();
       De(enhanced);
       const genderT = await resT.find((t) => t.shape[1] === 1);
       const gender = await genderT.data();
@@ -39377,7 +39391,7 @@ async function predict7(image6, config3, idx, count2) {
       obj.descriptor = Array.from(descriptor);
       resT.forEach((t) => De(t));
     }
-    last6[idx] = obj;
+    last3[idx] = obj;
     lastCount3 = count2;
     resolve(obj);
   });
@@ -42524,7 +42538,7 @@ var handBoxEnlargeFactor = 1.65;
 var palmLandmarkIds = [0, 5, 9, 13, 17, 1, 2];
 var palmLandmarksPalmBase = 0;
 var palmLandmarksMiddleFingerBase = 2;
-var lastTime5 = 0;
+var lastTime8 = 0;
 var HandPipeline = class {
   constructor(handDetector, handPoseModel2) {
     __publicField(this, "handDetector");
@@ -42537,7 +42551,7 @@ var HandPipeline = class {
     this.handPoseModel = handPoseModel2;
     this.inputSize = this.handPoseModel && this.handPoseModel.inputs[0].shape ? this.handPoseModel.inputs[0].shape[2] : 0;
     this.storedBoxes = [];
-    this.skipped = 0;
+    this.skipped = Number.MAX_SAFE_INTEGER;
     this.detectedHands = 0;
   }
   calculateLandmarksBoundingBox(landmarks) {
@@ -42589,11 +42603,13 @@ var HandPipeline = class {
   async estimateHands(image6, config3) {
     let useFreshBox = false;
     let boxes;
-    if (this.skipped === 0 || this.skipped > config3.hand.skipFrames && (config3.hand.skipTime || 0) <= now() - lastTime5 || !config3.hand.landmarks || !config3.skipFrame) {
+    const skipTime = (config3.hand.skipTime || 0) > now() - lastTime8;
+    const skipFrame = this.skipped < (config3.hand.skipFrames || 0);
+    if (config3.skipAllowed && skipTime && skipFrame) {
       boxes = await this.handDetector.estimateHandBounds(image6, config3);
       this.skipped = 0;
     }
-    if (config3.skipFrame)
+    if (config3.skipAllowed)
       this.skipped++;
     if (boxes && boxes.length > 0 && (boxes.length !== this.detectedHands && this.detectedHands !== config3.hand.maxDetected || !config3.hand.landmarks)) {
       this.detectedHands = 0;
@@ -42618,7 +42634,7 @@ var HandPipeline = class {
         De(croppedInput);
         De(rotatedImage);
         const [confidenceT, keypoints] = await this.handPoseModel.predict(handImage);
-        lastTime5 = now();
+        lastTime8 = now();
         De(handImage);
         const confidence = (await confidenceT.data())[0];
         De(confidenceT);
@@ -43186,8 +43202,8 @@ var faceIndex = 4;
 var boxExpandFact = 1.6;
 var maxDetectorResolution = 512;
 var detectorExpandFact = 1.4;
-var skipped9 = 0;
-var lastTime6 = 0;
+var skipped9 = Number.MAX_SAFE_INTEGER;
+var lastTime9 = 0;
 var outputSize = [0, 0];
 var cache3 = {
   boxes: [],
@@ -43327,17 +43343,21 @@ async function predict9(input, config3) {
     return [];
   outputSize = [input.shape[2] || 0, input.shape[1] || 0];
   skipped9++;
-  if (config3.skipFrame && skipped9 <= (config3.hand.skipFrames || 0) && (config3.hand.skipTime || 0) <= now() - lastTime6) {
+  const skipTime = (config3.hand.skipTime || 0) > now() - lastTime9;
+  const skipFrame = skipped9 < (config3.hand.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame) {
     return cache3.hands;
   }
   return new Promise(async (resolve) => {
-    if (config3.skipFrame && cache3.hands.length === config3.hand.maxDetected) {
+    const skipTimeExtended = 3 * (config3.hand.skipTime || 0) > now() - lastTime9;
+    const skipFrameExtended = skipped9 < 3 * (config3.hand.skipFrames || 0);
+    if (config3.skipAllowed && cache3.hands.length === config3.hand.maxDetected) {
       cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
-    } else if (config3.skipFrame && skipped9 < 3 * (config3.hand.skipFrames || 0) && (config3.hand.skipTime || 0) <= 3 * (now() - lastTime6) && cache3.hands.length > 0) {
+    } else if (config3.skipAllowed && skipTimeExtended && skipFrameExtended && cache3.hands.length > 0) {
       cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
     } else {
       cache3.boxes = await detectHands(input, config3);
-      lastTime6 = now();
+      lastTime9 = now();
       cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
       skipped9 = 0;
     }
@@ -43632,10 +43652,12 @@ async function parseMultiPose(res, config3, image6, inputBox) {
 async function predict10(input, config3) {
   if (!model10 || !(model10 == null ? void 0 : model10.inputs[0].shape))
     return [];
-  if (!config3.skipFrame)
+  if (!config3.skipAllowed)
     cache5.boxes.length = 0;
   skipped10++;
-  if (config3.skipFrame && (skipped10 <= (config3.body.skipFrames || 0) && (config3.body.skipTime || 0) <= now() - cache5.last)) {
+  const skipTime = (config3.body.skipTime || 0) > now() - cache5.last;
+  const skipFrame = skipped10 < (config3.body.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame) {
     return cache5.bodies;
   }
   return new Promise(async (resolve) => {
@@ -43657,8 +43679,8 @@ async function predict10(input, config3) {
 
 // src/object/nanodet.ts
 var model11;
-var last7 = [];
-var lastTime7 = 0;
+var last4 = [];
+var lastTime10 = 0;
 var skipped11 = Number.MAX_SAFE_INTEGER;
 var scaleBox = 2.5;
 async function load12(config3) {
@@ -43738,13 +43760,15 @@ async function process4(res, inputSize8, outputShape, config3) {
   return results;
 }
 async function predict11(image6, config3) {
-  if (skipped11 < (config3.object.skipFrames || 0) && (config3.object.skipTime || 0) <= now() - lastTime7 && config3.skipFrame && last7.length > 0) {
+  const skipTime = (config3.object.skipTime || 0) > now() - lastTime10;
+  const skipFrame = skipped11 < (config3.object.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && last4.length > 0) {
     skipped11++;
-    return last7;
+    return last4;
   }
   skipped11 = 0;
   if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
-    return last7;
+    return last4;
   return new Promise(async (resolve) => {
     const outputSize2 = [image6.shape[2], image6.shape[1]];
     const resize = Cn.resizeBilinear(image6, [model11.inputSize, model11.inputSize], false);
@@ -43755,10 +43779,10 @@ async function predict11(image6, config3) {
     let objectT;
     if (config3.object.enabled)
       objectT = await model11.predict(transpose);
-    lastTime7 = now();
+    lastTime10 = now();
     De(transpose);
     const obj = await process4(objectT, model11.inputSize, outputSize2, config3);
-    last7 = obj;
+    last4 = obj;
     resolve(obj);
   });
 }
@@ -44953,7 +44977,7 @@ async function canvas2(input, output) {
 async function all(inCanvas2, result, drawOptions) {
   if (!result || !result.performance || !result || !inCanvas2)
     return null;
-  const timestamp = now();
+  const timeStamp = now();
   const localOptions = mergeDeep(options2, drawOptions);
   const promise = Promise.all([
     face(inCanvas2, result.face, localOptions),
@@ -44962,7 +44986,7 @@ async function all(inCanvas2, result, drawOptions) {
     object(inCanvas2, result.object, localOptions),
     gesture(inCanvas2, result.gesture, localOptions)
   ]);
-  result.performance.draw = Math.trunc(now() - timestamp);
+  result.performance.draw = env.perfadd ? (result.performance.draw || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
   return promise;
 }
 
@@ -45087,7 +45111,7 @@ var detectFace = async (parent, input) => {
   parent.state = "run:face";
   timeStamp = now();
   const faces = await predict6(input, parent.config);
-  parent.performance.face = Math.trunc(now() - timeStamp);
+  parent.performance.face = env.perfadd ? (parent.performance.face || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
   if (!input.shape || input.shape.length !== 4)
     return [];
   if (!faces)
@@ -45106,7 +45130,7 @@ var detectFace = async (parent, input) => {
       parent.state = "run:emotion";
       timeStamp = now();
       emotionRes = parent.config.face.emotion.enabled ? await predict5(faces[i].tensor || Dr([]), parent.config, i, faces.length) : null;
-      parent.performance.emotion = Math.trunc(now() - timeStamp);
+      parent.performance.emotion = env.perfadd ? (parent.performance.emotion || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     parent.analyze("End Emotion:");
     parent.analyze("Start AntiSpoof:");
@@ -45116,7 +45140,7 @@ var detectFace = async (parent, input) => {
       parent.state = "run:antispoof";
       timeStamp = now();
       antispoofRes = parent.config.face.antispoof.enabled ? await predict(faces[i].tensor || Dr([]), parent.config, i, faces.length) : null;
-      parent.performance.antispoof = Math.trunc(now() - timeStamp);
+      parent.performance.antispoof = env.perfadd ? (parent.performance.antispoof || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     parent.analyze("End AntiSpoof:");
     parent.analyze("Start Description:");
@@ -45126,7 +45150,7 @@ var detectFace = async (parent, input) => {
       parent.state = "run:description";
       timeStamp = now();
       descRes = parent.config.face.description.enabled ? await predict7(faces[i].tensor || Dr([]), parent.config, i, faces.length) : null;
-      parent.performance.embedding = Math.trunc(now() - timeStamp);
+      parent.performance.embedding = env.perfadd ? (parent.performance.embedding || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     parent.analyze("End Description:");
     if (parent.config.async) {
@@ -46444,7 +46468,7 @@ var Human = class {
     const count2 = Object.values(this.models).filter((model14) => model14).length;
     if (userConfig)
       this.config = mergeDeep(this.config, userConfig);
-    if (env.initial) {
+    if (this.env.initial) {
       if (this.config.debug)
         log(`version: ${this.version}`);
       if (this.config.debug)
@@ -46460,9 +46484,9 @@ var Human = class {
       }
     }
     await load15(this);
-    if (env.initial && this.config.debug)
+    if (this.env.initial && this.config.debug)
       log("tf engine state:", this.tf.engine().state.numBytes, "bytes", this.tf.engine().state.numTensors, "tensors");
-    env.initial = false;
+    this.env.initial = false;
     const loaded = Object.values(this.models).filter((model14) => model14).length;
     if (loaded !== count2) {
       await validate2(this);
@@ -46470,7 +46494,7 @@ var Human = class {
     }
     const current = Math.trunc(now() - timeStamp);
     if (current > (this.performance.load || 0))
-      this.performance.load = current;
+      this.performance.load = this.env.perfadd ? (this.performance.load || 0) + current : current;
   }
   next(result = this.result) {
     return calc2(result, this.config);
@@ -46484,7 +46508,6 @@ var Human = class {
       var _a2, _b, _c2, _d2, _e, _f2, _g, _h2, _i2, _j2, _k2, _l2, _m2, _n2, _o2, _p2, _q2, _r, _s2, _t2, _u2, _v2;
       this.state = "config";
       let timeStamp;
-      let elapsedTime;
       this.config = mergeDeep(this.config, userConfig);
       this.state = "check";
       const error = __privateGet(this, _sanity).call(this, input);
@@ -46499,7 +46522,7 @@ var Human = class {
       this.state = "image";
       const img = process2(input, this.config);
       this.process = img;
-      this.performance.image = Math.trunc(now() - timeStamp);
+      this.performance.image = this.env.perfadd ? (this.performance.image || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       this.analyze("Get Image:");
       if (!img.tensor) {
         if (this.config.debug)
@@ -46509,15 +46532,15 @@ var Human = class {
       }
       this.emit("image");
       timeStamp = now();
-      this.config.skipFrame = await skip(this.config, img.tensor);
+      this.config.skipAllowed = await skip(this.config, img.tensor);
       if (!this.performance.frames)
         this.performance.frames = 0;
       if (!this.performance.cached)
         this.performance.cached = 0;
       this.performance.frames++;
-      if (this.config.skipFrame)
+      if (this.config.skipAllowed)
         this.performance.cached++;
-      this.performance.changed = Math.trunc(now() - timeStamp);
+      this.performance.changed = this.env.perfadd ? (this.performance.changed || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       this.analyze("Check Changed:");
       let faceRes = [];
       let bodyRes = [];
@@ -46531,9 +46554,7 @@ var Human = class {
       } else {
         timeStamp = now();
         faceRes = this.config.face.enabled ? await detectFace(this, img.tensor) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0)
-          this.performance.face = elapsedTime;
+        this.performance.face = this.env.perfadd ? (this.performance.face || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       if (this.config.async && (this.config.body.maxDetected === -1 || this.config.hand.maxDetected === -1))
         faceRes = await faceRes;
@@ -46561,9 +46582,7 @@ var Human = class {
           bodyRes = this.config.body.enabled ? await predict4(img.tensor, bodyConfig) : [];
         else if ((_h2 = this.config.body.modelPath) == null ? void 0 : _h2.includes("movenet"))
           bodyRes = this.config.body.enabled ? await predict10(img.tensor, bodyConfig) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0)
-          this.performance.body = elapsedTime;
+        this.performance.body = this.env.perfadd ? (this.performance.body || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       this.analyze("End Body:");
       this.analyze("Start Hand:");
@@ -46582,9 +46601,7 @@ var Human = class {
           handRes = this.config.hand.enabled ? await predict8(img.tensor, handConfig) : [];
         else if ((_p2 = (_o2 = this.config.hand.detector) == null ? void 0 : _o2.modelPath) == null ? void 0 : _p2.includes("handtrack"))
           handRes = this.config.hand.enabled ? await predict9(img.tensor, handConfig) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0)
-          this.performance.hand = elapsedTime;
+        this.performance.hand = this.env.perfadd ? (this.performance.hand || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       this.analyze("End Hand:");
       this.analyze("Start Object:");
@@ -46602,9 +46619,7 @@ var Human = class {
           objectRes = this.config.object.enabled ? await predict11(img.tensor, this.config) : [];
         else if ((_t2 = this.config.object.modelPath) == null ? void 0 : _t2.includes("centernet"))
           objectRes = this.config.object.enabled ? await predict3(img.tensor, this.config) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0)
-          this.performance.object = elapsedTime;
+        this.performance.object = this.env.perfadd ? (this.performance.object || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       this.analyze("End Object:");
       this.state = "detect:await";
@@ -46616,7 +46631,7 @@ var Human = class {
         timeStamp = now();
         gestureRes = [...face2(faceRes), ...body2(bodyRes), ...hand2(handRes), ...iris3(faceRes)];
         if (!this.config.async)
-          this.performance.gesture = Math.trunc(now() - timeStamp);
+          this.performance.gesture = this.env.perfadd ? (this.performance.gesture || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
         else if (this.performance.gesture)
           delete this.performance.gesture;
       }

dist/human.node-gpu.js

@@ -152,8 +152,8 @@ var config = {
   debug: true,
   async: true,
   warmup: "full",
-  cacheSensitivity: 0.75,
-  skipFrame: false,
+  cacheSensitivity: 0.7,
+  skipAllowed: false,
   filter: {
     enabled: true,
     width: 0,
@@ -183,8 +183,8 @@ var config = {
       modelPath: "blazeface.json",
       rotation: true,
       maxDetected: 1,
-      skipFrames: 11,
-      skipTime: 2e3,
+      skipFrames: 99,
+      skipTime: 2500,
       minConfidence: 0.2,
       iouThreshold: 0.1,
       return: false
@@ -200,21 +200,21 @@ var config = {
     emotion: {
       enabled: true,
       minConfidence: 0.1,
-      skipFrames: 12,
-      skipTime: 2e3,
+      skipFrames: 99,
+      skipTime: 1500,
       modelPath: "emotion.json"
     },
     description: {
       enabled: true,
       modelPath: "faceres.json",
-      skipFrames: 13,
-      skipTime: 2e3,
+      skipFrames: 99,
+      skipTime: 3e3,
       minConfidence: 0.1
     },
     antispoof: {
       enabled: false,
-      skipFrames: 14,
-      skipTime: 2e3,
+      skipFrames: 99,
+      skipTime: 4e3,
       modelPath: "antispoof.json"
     }
   },
@@ -227,12 +227,12 @@ var config = {
     maxDetected: -1,
     minConfidence: 0.3,
     skipFrames: 1,
-    skipTime: 2e3
+    skipTime: 200
   },
   hand: {
     enabled: true,
     rotation: true,
-    skipFrames: 2,
+    skipFrames: 99,
     skipTime: 2e3,
     minConfidence: 0.5,
     iouThreshold: 0.2,
@@ -251,8 +251,8 @@ var config = {
     minConfidence: 0.2,
     iouThreshold: 0.4,
     maxDetected: 10,
-    skipFrames: 15,
-    skipTime: 2e3
+    skipFrames: 99,
+    skipTime: 1e3
   },
   segmentation: {
     enabled: false,
@@ -1190,6 +1190,7 @@ var Env = class {
     __publicField(this, "filter");
     __publicField(this, "tfjs");
     __publicField(this, "offscreen");
+    __publicField(this, "perfadd", false);
     __publicField(this, "wasm", {
       supported: void 0,
       backend: void 0,
@@ -1321,7 +1322,7 @@ var model2;
 var cached = [];
 var skipped2 = Number.MAX_SAFE_INTEGER;
 var lastCount = 0;
-var last = 0;
+var lastTime = 0;
 async function load2(config3) {
   var _a, _b;
   if (env.initial)
@@ -1340,7 +1341,9 @@ async function predict(image25, config3, idx, count2) {
   var _a, _b;
   if (!model2)
     return null;
-  if (skipped2 < (((_a = config3.face.antispoof) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.antispoof) == null ? void 0 : _b.skipTime) || 0) <= now() - last && config3.skipFrame && lastCount === count2 && cached[idx]) {
+  const skipTime = (((_a = config3.face.antispoof) == null ? void 0 : _a.skipTime) || 0) > now() - lastTime;
+  const skipFrame = skipped2 < (((_b = config3.face.antispoof) == null ? void 0 : _b.skipFrames) || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && lastCount === count2 && cached[idx]) {
     skipped2++;
     return cached[idx];
   }
@@ -1351,7 +1354,7 @@ async function predict(image25, config3, idx, count2) {
     const num = (await res.data())[0];
     cached[idx] = Math.round(100 * num) / 100;
     lastCount = count2;
-    last = now();
+    lastTime = now();
     tf4.dispose([resize, res]);
     resolve(cached[idx]);
   });
@@ -4936,7 +4939,7 @@ var skipped3 = Number.MAX_SAFE_INTEGER;
 var outputNodes;
 var cache = null;
 var padding = [[0, 0], [0, 0], [0, 0], [0, 0]];
-var last2 = 0;
+var lastTime2 = 0;
 async function loadDetect(config3) {
   var _a, _b, _c;
   if (env3.initial)
@@ -5053,11 +5056,13 @@ async function detectParts(input, config3, outputSize2) {
 }
 async function predict2(input, config3) {
   const outputSize2 = [input.shape[2] || 0, input.shape[1] || 0];
-  if (skipped3 < (config3.body.skipFrames || 0) && (config3.body.skipTime || 0) <= now() - last2 && config3.skipFrame && cache !== null) {
+  const skipTime = (config3.body.skipTime || 0) > now() - lastTime2;
+  const skipFrame = skipped3 < (config3.body.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && cache !== null) {
     skipped3++;
   } else {
     cache = await detectParts(input, config3, outputSize2);
-    last2 = now();
+    lastTime2 = now();
     skipped3 = 0;
   }
   if (cache)
@@ -5155,8 +5160,8 @@ var labels = [
 // src/object/centernet.ts
 var model4;
 var inputSize3 = 0;
-var last3 = [];
-var lastTime = 0;
+var last = [];
+var lastTime3 = 0;
 var skipped4 = Number.MAX_SAFE_INTEGER;
 async function load4(config3) {
   if (env.initial)
@@ -5221,21 +5226,23 @@ async function process3(res, outputShape, config3) {
   return results;
 }
 async function predict3(input, config3) {
-  if (skipped4 < (config3.object.skipFrames || 0) && (config3.object.skipTime || 0) <= now() - lastTime && config3.skipFrame && last3.length > 0) {
+  const skipTime = (config3.object.skipTime || 0) > now() - lastTime3;
+  const skipFrame = skipped4 < (config3.object.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && last.length > 0) {
     skipped4++;
-    return last3;
+    return last;
   }
   skipped4 = 0;
   if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
-    return last3;
+    return last;
   return new Promise(async (resolve) => {
     const outputSize2 = [input.shape[2], input.shape[1]];
     const resize = tf8.image.resizeBilinear(input, [inputSize3, inputSize3]);
     const objectT = config3.object.enabled ? model4 == null ? void 0 : model4.execute(resize, ["tower_0/detections"]) : null;
-    lastTime = now();
+    lastTime3 = now();
     tf8.dispose(resize);
     const obj = await process3(objectT, outputSize2, config3);
-    last3 = obj;
+    last = obj;
     resolve(obj);
   });
 }
@@ -5278,7 +5285,7 @@ var connected2 = {
 
 // src/body/efficientpose.ts
 var model5;
-var last4 = 0;
+var lastTime4 = 0;
 var cache2 = { id: 0, keypoints: [], box: [0, 0, 0, 0], boxRaw: [0, 0, 0, 0], score: 0, annotations: {} };
 var skipped5 = Number.MAX_SAFE_INTEGER;
 async function load5(config3) {
@@ -5310,14 +5317,15 @@ function max2d(inputs, minScore) {
   });
 }
 async function predict4(image25, config3) {
-  var _a;
-  if (skipped5 < (((_a = config3.body) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && Object.keys(cache2.keypoints).length > 0 && (config3.body.skipTime || 0) <= now() - last4) {
+  const skipTime = (config3.body.skipTime || 0) > now() - lastTime4;
+  const skipFrame = skipped5 < (config3.body.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && Object.keys(cache2.keypoints).length > 0) {
     skipped5++;
     return [cache2];
   }
   skipped5 = 0;
   return new Promise(async (resolve) => {
-    var _a2;
+    var _a;
     const tensor3 = tf9.tidy(() => {
       if (!(model5 == null ? void 0 : model5.inputs[0].shape))
         return null;
@@ -5329,7 +5337,7 @@ async function predict4(image25, config3) {
     let resT;
     if (config3.body.enabled)
       resT = await (model5 == null ? void 0 : model5.predict(tensor3));
-    last4 = now();
+    lastTime4 = now();
     tf9.dispose(tensor3);
     if (resT) {
       cache2.keypoints.length = 0;
@@ -5339,7 +5347,7 @@ async function predict4(image25, config3) {
       tf9.dispose(squeeze8);
       for (let id = 0; id < stack3.length; id++) {
         const [x2, y2, partScore] = max2d(stack3[id], config3.body.minConfidence);
-        if (partScore > (((_a2 = config3.body) == null ? void 0 : _a2.minConfidence) || 0)) {
+        if (partScore > (((_a = config3.body) == null ? void 0 : _a.minConfidence) || 0)) {
           cache2.keypoints.push({
             score: Math.round(100 * partScore) / 100,
             part: kpt2[id],
@@ -5391,9 +5399,9 @@ async function predict4(image25, config3) {
 var tf10 = __toModule(require_tfjs_esm());
 var annotations = ["angry", "disgust", "fear", "happy", "sad", "surprise", "neutral"];
 var model6;
-var last5 = [];
+var last2 = [];
 var lastCount2 = 0;
-var lastTime2 = 0;
+var lastTime5 = 0;
 var skipped6 = Number.MAX_SAFE_INTEGER;
 var rgb = [0.2989, 0.587, 0.114];
 async function load6(config3) {
@@ -5414,9 +5422,11 @@ async function predict5(image25, config3, idx, count2) {
   var _a, _b;
   if (!model6)
     return null;
-  if (skipped6 < (((_a = config3.face.emotion) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.emotion) == null ? void 0 : _b.skipTime) || 0) <= now() - lastTime2 && config3.skipFrame && lastCount2 === count2 && last5[idx] && last5[idx].length > 0) {
+  const skipFrame = skipped6 < (((_a = config3.face.emotion) == null ? void 0 : _a.skipFrames) || 0);
+  const skipTime = (((_b = config3.face.emotion) == null ? void 0 : _b.skipTime) || 0) > now() - lastTime5;
+  if (config3.skipAllowed && skipTime && skipFrame && lastCount2 === count2 && last2[idx] && last2[idx].length > 0) {
     skipped6++;
-    return last5[idx];
+    return last2[idx];
   }
   skipped6 = 0;
   return new Promise(async (resolve) => {
@@ -5439,7 +5449,7 @@ async function predict5(image25, config3, idx, count2) {
       const normalize = tf10.tidy(() => tf10.mul(tf10.sub(grayscale, 0.5), 2));
       tf10.dispose(grayscale);
       const emotionT = await (model6 == null ? void 0 : model6.predict(normalize));
-      lastTime2 = now();
+      lastTime5 = now();
       const data = await emotionT.data();
       tf10.dispose(emotionT);
       for (let i = 0; i < data.length; i++) {
@@ -5449,7 +5459,7 @@ async function predict5(image25, config3, idx, count2) {
       obj.sort((a, b) => b.score - a.score);
       tf10.dispose(normalize);
     }
-    last5[idx] = obj;
+    last2[idx] = obj;
     lastCount2 = count2;
     resolve(obj);
   });
@@ -5596,13 +5606,15 @@ var boxCache = [];
 var model8 = null;
 var inputSize5 = 0;
 var skipped7 = Number.MAX_SAFE_INTEGER;
-var lastTime3 = 0;
+var lastTime6 = 0;
 var detectedFaces = 0;
 async function predict6(input, config3) {
-  var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m;
-  if (!config3.skipFrame || (detectedFaces !== ((_a = config3.face.detector) == null ? void 0 : _a.maxDetected) || !((_b = config3.face.mesh) == null ? void 0 : _b.enabled)) && (skipped7 > (((_c = config3.face.detector) == null ? void 0 : _c.skipFrames) || 0) && (((_d = config3.face.description) == null ? void 0 : _d.skipTime) || 0) <= now() - lastTime3)) {
+  var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k;
+  const skipTime = (((_a = config3.face.detector) == null ? void 0 : _a.skipTime) || 0) > now() - lastTime6;
+  const skipFrame = skipped7 < (((_b = config3.face.detector) == null ? void 0 : _b.skipFrames) || 0);
+  if (!config3.skipAllowed || !skipTime || !skipFrame || detectedFaces === 0) {
     const newBoxes2 = await getBoxes(input, config3);
-    lastTime3 = now();
+    lastTime6 = now();
     boxCache = [];
     for (const possible of newBoxes2.boxes) {
       const startPoint = await possible.box.startPoint.data();
@@ -5638,16 +5650,16 @@ async function predict6(input, config3) {
       faceScore: 0,
       annotations: {}
     };
-    if (((_e = config3.face.detector) == null ? void 0 : _e.rotation) && ((_f = config3.face.mesh) == null ? void 0 : _f.enabled) && env.kernels.includes("rotatewithoffset")) {
+    if (((_c = config3.face.detector) == null ? void 0 : _c.rotation) && ((_d = config3.face.mesh) == null ? void 0 : _d.enabled) && env.kernels.includes("rotatewithoffset")) {
       [angle, rotationMatrix, face5.tensor] = correctFaceRotation(box4, input, inputSize5);
     } else {
       rotationMatrix = IDENTITY_MATRIX;
-      const cut = cutBoxFromImageAndResize({ startPoint: box4.startPoint, endPoint: box4.endPoint }, input, ((_g = config3.face.mesh) == null ? void 0 : _g.enabled) ? [inputSize5, inputSize5] : [size(), size()]);
+      const cut = cutBoxFromImageAndResize({ startPoint: box4.startPoint, endPoint: box4.endPoint }, input, ((_e = config3.face.mesh) == null ? void 0 : _e.enabled) ? [inputSize5, inputSize5] : [size(), size()]);
       face5.tensor = tf12.div(cut, 255);
       tf12.dispose(cut);
     }
     face5.boxScore = Math.round(100 * box4.confidence) / 100;
-    if (!((_h = config3.face.mesh) == null ? void 0 : _h.enabled)) {
+    if (!((_f = config3.face.mesh) == null ? void 0 : _f.enabled)) {
       face5.box = getClampedBox(box4, input);
       face5.boxRaw = getRawBox(box4, input);
       face5.score = Math.round(100 * box4.confidence || 0) / 100;
@@ -5670,17 +5682,17 @@ async function predict6(input, config3) {
       let rawCoords = await coordsReshaped.array();
       tf12.dispose(contourCoords);
       tf12.dispose(coordsReshaped);
-      if (faceConfidence < (((_i = config3.face.detector) == null ? void 0 : _i.minConfidence) || 1)) {
+      if (faceConfidence < (((_g = config3.face.detector) == null ? void 0 : _g.minConfidence) || 1)) {
         box4.confidence = faceConfidence;
       } else {
-        if ((_j = config3.face.iris) == null ? void 0 : _j.enabled)
+        if ((_h = config3.face.iris) == null ? void 0 : _h.enabled)
           rawCoords = await augmentIris(rawCoords, face5.tensor, config3, inputSize5);
         face5.mesh = transformRawCoords(rawCoords, box4, angle, rotationMatrix, inputSize5);
         face5.meshRaw = face5.mesh.map((pt) => [pt[0] / (input.shape[2] || 0), pt[1] / (input.shape[1] || 0), (pt[2] || 0) / inputSize5]);
         box4 = { ...enlargeBox(calculateLandmarksBoundingBox(face5.mesh), 1.5), confidence: box4.confidence };
         for (const key of Object.keys(meshAnnotations))
           face5.annotations[key] = meshAnnotations[key].map((index) => face5.mesh[index]);
-        if (((_k = config3.face.detector) == null ? void 0 : _k.rotation) && config3.face.mesh.enabled && ((_l = config3.face.description) == null ? void 0 : _l.enabled) && env.kernels.includes("rotatewithoffset")) {
+        if (((_i = config3.face.detector) == null ? void 0 : _i.rotation) && config3.face.mesh.enabled && ((_j = config3.face.description) == null ? void 0 : _j.enabled) && env.kernels.includes("rotatewithoffset")) {
           tf12.dispose(face5.tensor);
           [angle, rotationMatrix, face5.tensor] = correctFaceRotation(box4, input, inputSize5);
         }
@@ -5694,7 +5706,7 @@ async function predict6(input, config3) {
     faces.push(face5);
     newBoxes.push(box4);
   }
-  if ((_m = config3.face.mesh) == null ? void 0 : _m.enabled)
+  if ((_k = config3.face.mesh) == null ? void 0 : _k.enabled)
     boxCache = newBoxes.filter((a) => {
       var _a2;
       return a.confidence > (((_a2 = config3.face.detector) == null ? void 0 : _a2.minConfidence) || 0);
@@ -5725,8 +5737,8 @@ var uvmap = UV468;
 // src/face/faceres.ts
 var tf13 = __toModule(require_tfjs_esm());
 var model9;
-var last6 = [];
-var lastTime4 = 0;
+var last3 = [];
+var lastTime7 = 0;
 var lastCount3 = 0;
 var skipped8 = Number.MAX_SAFE_INTEGER;
 async function load9(config3) {
@@ -5762,9 +5774,11 @@ async function predict7(image25, config3, idx, count2) {
   var _a, _b, _c, _d;
   if (!model9)
     return null;
-  if (skipped8 < (((_a = config3.face.description) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.description) == null ? void 0 : _b.skipTime) || 0) <= now() - lastTime4 && config3.skipFrame && lastCount3 === count2 && ((_c = last6[idx]) == null ? void 0 : _c.age) && ((_d = last6[idx]) == null ? void 0 : _d.age) > 0) {
+  const skipFrame = skipped8 < (((_a = config3.face.description) == null ? void 0 : _a.skipFrames) || 0);
+  const skipTime = (((_b = config3.face.description) == null ? void 0 : _b.skipTime) || 0) > now() - lastTime7;
+  if (config3.skipAllowed && skipFrame && skipTime && lastCount3 === count2 && ((_c = last3[idx]) == null ? void 0 : _c.age) && ((_d = last3[idx]) == null ? void 0 : _d.age) > 0) {
     skipped8++;
-    return last6[idx];
+    return last3[idx];
   }
   skipped8 = 0;
   return new Promise(async (resolve) => {
@@ -5778,7 +5792,7 @@ async function predict7(image25, config3, idx, count2) {
     if ((_a2 = config3.face.description) == null ? void 0 : _a2.enabled) {
       const enhanced = enhance(image25);
       const resT = await (model9 == null ? void 0 : model9.predict(enhanced));
-      lastTime4 = now();
+      lastTime7 = now();
       tf13.dispose(enhanced);
       const genderT = await resT.find((t) => t.shape[1] === 1);
       const gender = await genderT.data();
@@ -5798,7 +5812,7 @@ async function predict7(image25, config3, idx, count2) {
       obj.descriptor = Array.from(descriptor);
       resT.forEach((t) => tf13.dispose(t));
     }
-    last6[idx] = obj;
+    last3[idx] = obj;
     lastCount3 = count2;
     resolve(obj);
   });
@@ -8953,7 +8967,7 @@ var handBoxEnlargeFactor = 1.65;
 var palmLandmarkIds = [0, 5, 9, 13, 17, 1, 2];
 var palmLandmarksPalmBase = 0;
 var palmLandmarksMiddleFingerBase = 2;
-var lastTime5 = 0;
+var lastTime8 = 0;
 var HandPipeline = class {
   constructor(handDetector, handPoseModel2) {
     __publicField(this, "handDetector");
@@ -8966,7 +8980,7 @@ var HandPipeline = class {
     this.handPoseModel = handPoseModel2;
     this.inputSize = this.handPoseModel && this.handPoseModel.inputs[0].shape ? this.handPoseModel.inputs[0].shape[2] : 0;
     this.storedBoxes = [];
-    this.skipped = 0;
+    this.skipped = Number.MAX_SAFE_INTEGER;
     this.detectedHands = 0;
   }
   calculateLandmarksBoundingBox(landmarks) {
@@ -9018,11 +9032,13 @@ var HandPipeline = class {
   async estimateHands(image25, config3) {
     let useFreshBox = false;
     let boxes;
-    if (this.skipped === 0 || this.skipped > config3.hand.skipFrames && (config3.hand.skipTime || 0) <= now() - lastTime5 || !config3.hand.landmarks || !config3.skipFrame) {
+    const skipTime = (config3.hand.skipTime || 0) > now() - lastTime8;
+    const skipFrame = this.skipped < (config3.hand.skipFrames || 0);
+    if (config3.skipAllowed && skipTime && skipFrame) {
       boxes = await this.handDetector.estimateHandBounds(image25, config3);
       this.skipped = 0;
     }
-    if (config3.skipFrame)
+    if (config3.skipAllowed)
       this.skipped++;
     if (boxes && boxes.length > 0 && (boxes.length !== this.detectedHands && this.detectedHands !== config3.hand.maxDetected || !config3.hand.landmarks)) {
       this.detectedHands = 0;
@@ -9047,7 +9063,7 @@ var HandPipeline = class {
         tf16.dispose(croppedInput);
         tf16.dispose(rotatedImage);
         const [confidenceT, keypoints] = await this.handPoseModel.predict(handImage);
-        lastTime5 = now();
+        lastTime8 = now();
         tf16.dispose(handImage);
         const confidence = (await confidenceT.data())[0];
         tf16.dispose(confidenceT);
@@ -9616,8 +9632,8 @@ var faceIndex = 4;
 var boxExpandFact = 1.6;
 var maxDetectorResolution = 512;
 var detectorExpandFact = 1.4;
-var skipped9 = 0;
-var lastTime6 = 0;
+var skipped9 = Number.MAX_SAFE_INTEGER;
+var lastTime9 = 0;
 var outputSize = [0, 0];
 var cache3 = {
   boxes: [],
@@ -9757,17 +9773,21 @@ async function predict9(input, config3) {
     return [];
   outputSize = [input.shape[2] || 0, input.shape[1] || 0];
   skipped9++;
-  if (config3.skipFrame && skipped9 <= (config3.hand.skipFrames || 0) && (config3.hand.skipTime || 0) <= now() - lastTime6) {
+  const skipTime = (config3.hand.skipTime || 0) > now() - lastTime9;
+  const skipFrame = skipped9 < (config3.hand.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame) {
     return cache3.hands;
   }
   return new Promise(async (resolve) => {
-    if (config3.skipFrame && cache3.hands.length === config3.hand.maxDetected) {
+    const skipTimeExtended = 3 * (config3.hand.skipTime || 0) > now() - lastTime9;
+    const skipFrameExtended = skipped9 < 3 * (config3.hand.skipFrames || 0);
+    if (config3.skipAllowed && cache3.hands.length === config3.hand.maxDetected) {
       cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
-    } else if (config3.skipFrame && skipped9 < 3 * (config3.hand.skipFrames || 0) && (config3.hand.skipTime || 0) <= 3 * (now() - lastTime6) && cache3.hands.length > 0) {
+    } else if (config3.skipAllowed && skipTimeExtended && skipFrameExtended && cache3.hands.length > 0) {
       cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
     } else {
       cache3.boxes = await detectHands(input, config3);
-      lastTime6 = now();
+      lastTime9 = now();
       cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
       skipped9 = 0;
     }
@@ -10066,10 +10086,12 @@ async function parseMultiPose(res, config3, image25, inputBox) {
 async function predict10(input, config3) {
   if (!model10 || !(model10 == null ? void 0 : model10.inputs[0].shape))
     return [];
-  if (!config3.skipFrame)
+  if (!config3.skipAllowed)
     cache5.boxes.length = 0;
   skipped10++;
-  if (config3.skipFrame && (skipped10 <= (config3.body.skipFrames || 0) && (config3.body.skipTime || 0) <= now() - cache5.last)) {
+  const skipTime = (config3.body.skipTime || 0) > now() - cache5.last;
+  const skipFrame = skipped10 < (config3.body.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame) {
     return cache5.bodies;
   }
   return new Promise(async (resolve) => {
@@ -10092,8 +10114,8 @@ async function predict10(input, config3) {
 // src/object/nanodet.ts
 var tf21 = __toModule(require_tfjs_esm());
 var model11;
-var last7 = [];
-var lastTime7 = 0;
+var last4 = [];
+var lastTime10 = 0;
 var skipped11 = Number.MAX_SAFE_INTEGER;
 var scaleBox = 2.5;
 async function load12(config3) {
@@ -10173,13 +10195,15 @@ async function process4(res, inputSize8, outputShape, config3) {
   return results;
 }
 async function predict11(image25, config3) {
-  if (skipped11 < (config3.object.skipFrames || 0) && (config3.object.skipTime || 0) <= now() - lastTime7 && config3.skipFrame && last7.length > 0) {
+  const skipTime = (config3.object.skipTime || 0) > now() - lastTime10;
+  const skipFrame = skipped11 < (config3.object.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && last4.length > 0) {
     skipped11++;
-    return last7;
+    return last4;
   }
   skipped11 = 0;
   if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
-    return last7;
+    return last4;
   return new Promise(async (resolve) => {
     const outputSize2 = [image25.shape[2], image25.shape[1]];
     const resize = tf21.image.resizeBilinear(image25, [model11.inputSize, model11.inputSize], false);
@@ -10190,10 +10214,10 @@ async function predict11(image25, config3) {
     let objectT;
     if (config3.object.enabled)
       objectT = await model11.predict(transpose);
-    lastTime7 = now();
+    lastTime10 = now();
     tf21.dispose(transpose);
     const obj = await process4(objectT, model11.inputSize, outputSize2, config3);
-    last7 = obj;
+    last4 = obj;
     resolve(obj);
   });
 }
@@ -11393,7 +11417,7 @@ async function canvas2(input, output) {
 async function all(inCanvas2, result, drawOptions) {
   if (!result || !result.performance || !result || !inCanvas2)
     return null;
-  const timestamp = now();
+  const timeStamp = now();
   const localOptions = mergeDeep(options2, drawOptions);
   const promise = Promise.all([
     face(inCanvas2, result.face, localOptions),
@@ -11402,7 +11426,7 @@ async function all(inCanvas2, result, drawOptions) {
     object(inCanvas2, result.object, localOptions),
     gesture(inCanvas2, result.gesture, localOptions)
   ]);
-  result.performance.draw = Math.trunc(now() - timestamp);
+  result.performance.draw = env.perfadd ? (result.performance.draw || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
   return promise;
 }
 
@@ -11530,7 +11554,7 @@ var detectFace = async (parent, input) => {
   parent.state = "run:face";
   timeStamp = now();
   const faces = await predict6(input, parent.config);
-  parent.performance.face = Math.trunc(now() - timeStamp);
+  parent.performance.face = env.perfadd ? (parent.performance.face || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
   if (!input.shape || input.shape.length !== 4)
     return [];
   if (!faces)
@@ -11549,7 +11573,7 @@ var detectFace = async (parent, input) => {
       parent.state = "run:emotion";
       timeStamp = now();
       emotionRes = parent.config.face.emotion.enabled ? await predict5(faces[i].tensor || tf26.tensor([]), parent.config, i, faces.length) : null;
-      parent.performance.emotion = Math.trunc(now() - timeStamp);
+      parent.performance.emotion = env.perfadd ? (parent.performance.emotion || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     parent.analyze("End Emotion:");
     parent.analyze("Start AntiSpoof:");
@@ -11559,7 +11583,7 @@ var detectFace = async (parent, input) => {
       parent.state = "run:antispoof";
       timeStamp = now();
       antispoofRes = parent.config.face.antispoof.enabled ? await predict(faces[i].tensor || tf26.tensor([]), parent.config, i, faces.length) : null;
-      parent.performance.antispoof = Math.trunc(now() - timeStamp);
+      parent.performance.antispoof = env.perfadd ? (parent.performance.antispoof || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     parent.analyze("End AntiSpoof:");
     parent.analyze("Start Description:");
@@ -11569,7 +11593,7 @@ var detectFace = async (parent, input) => {
       parent.state = "run:description";
       timeStamp = now();
       descRes = parent.config.face.description.enabled ? await predict7(faces[i].tensor || tf26.tensor([]), parent.config, i, faces.length) : null;
-      parent.performance.embedding = Math.trunc(now() - timeStamp);
+      parent.performance.embedding = env.perfadd ? (parent.performance.embedding || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     parent.analyze("End Description:");
     if (parent.config.async) {
@@ -12888,7 +12912,7 @@ var Human = class {
     const count2 = Object.values(this.models).filter((model14) => model14).length;
     if (userConfig)
       this.config = mergeDeep(this.config, userConfig);
-    if (env.initial) {
+    if (this.env.initial) {
       if (this.config.debug)
         log(`version: ${this.version}`);
       if (this.config.debug)
@@ -12904,9 +12928,9 @@ var Human = class {
       }
     }
     await load15(this);
-    if (env.initial && this.config.debug)
+    if (this.env.initial && this.config.debug)
       log("tf engine state:", this.tf.engine().state.numBytes, "bytes", this.tf.engine().state.numTensors, "tensors");
-    env.initial = false;
+    this.env.initial = false;
     const loaded = Object.values(this.models).filter((model14) => model14).length;
     if (loaded !== count2) {
       await validate2(this);
@@ -12914,7 +12938,7 @@ var Human = class {
     }
     const current = Math.trunc(now() - timeStamp);
     if (current > (this.performance.load || 0))
-      this.performance.load = current;
+      this.performance.load = this.env.perfadd ? (this.performance.load || 0) + current : current;
   }
   next(result = this.result) {
     return calc2(result, this.config);
@@ -12928,7 +12952,6 @@ var Human = class {
       var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q, _r, _s, _t, _u, _v;
       this.state = "config";
       let timeStamp;
-      let elapsedTime;
       this.config = mergeDeep(this.config, userConfig);
       this.state = "check";
       const error = __privateGet(this, _sanity).call(this, input);
@@ -12943,7 +12966,7 @@ var Human = class {
       this.state = "image";
       const img = process2(input, this.config);
       this.process = img;
-      this.performance.image = Math.trunc(now() - timeStamp);
+      this.performance.image = this.env.perfadd ? (this.performance.image || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       this.analyze("Get Image:");
       if (!img.tensor) {
         if (this.config.debug)
@@ -12953,15 +12976,15 @@ var Human = class {
       }
       this.emit("image");
       timeStamp = now();
-      this.config.skipFrame = await skip(this.config, img.tensor);
+      this.config.skipAllowed = await skip(this.config, img.tensor);
       if (!this.performance.frames)
         this.performance.frames = 0;
       if (!this.performance.cached)
         this.performance.cached = 0;
       this.performance.frames++;
-      if (this.config.skipFrame)
+      if (this.config.skipAllowed)
         this.performance.cached++;
-      this.performance.changed = Math.trunc(now() - timeStamp);
+      this.performance.changed = this.env.perfadd ? (this.performance.changed || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       this.analyze("Check Changed:");
       let faceRes = [];
       let bodyRes = [];
@@ -12975,9 +12998,7 @@ var Human = class {
       } else {
         timeStamp = now();
         faceRes = this.config.face.enabled ? await detectFace(this, img.tensor) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0)
-          this.performance.face = elapsedTime;
+        this.performance.face = this.env.perfadd ? (this.performance.face || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       if (this.config.async && (this.config.body.maxDetected === -1 || this.config.hand.maxDetected === -1))
         faceRes = await faceRes;
@@ -13005,9 +13026,7 @@ var Human = class {
           bodyRes = this.config.body.enabled ? await predict4(img.tensor, bodyConfig) : [];
         else if ((_h = this.config.body.modelPath) == null ? void 0 : _h.includes("movenet"))
           bodyRes = this.config.body.enabled ? await predict10(img.tensor, bodyConfig) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0)
-          this.performance.body = elapsedTime;
+        this.performance.body = this.env.perfadd ? (this.performance.body || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       this.analyze("End Body:");
       this.analyze("Start Hand:");
@@ -13026,9 +13045,7 @@ var Human = class {
           handRes = this.config.hand.enabled ? await predict8(img.tensor, handConfig) : [];
         else if ((_p = (_o = this.config.hand.detector) == null ? void 0 : _o.modelPath) == null ? void 0 : _p.includes("handtrack"))
           handRes = this.config.hand.enabled ? await predict9(img.tensor, handConfig) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0)
-          this.performance.hand = elapsedTime;
+        this.performance.hand = this.env.perfadd ? (this.performance.hand || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       this.analyze("End Hand:");
       this.analyze("Start Object:");
@@ -13046,9 +13063,7 @@ var Human = class {
           objectRes = this.config.object.enabled ? await predict11(img.tensor, this.config) : [];
         else if ((_t = this.config.object.modelPath) == null ? void 0 : _t.includes("centernet"))
           objectRes = this.config.object.enabled ? await predict3(img.tensor, this.config) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0)
-          this.performance.object = elapsedTime;
+        this.performance.object = this.env.perfadd ? (this.performance.object || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       this.analyze("End Object:");
       this.state = "detect:await";
@@ -13060,7 +13075,7 @@ var Human = class {
         timeStamp = now();
         gestureRes = [...face2(faceRes), ...body2(bodyRes), ...hand2(handRes), ...iris3(faceRes)];
         if (!this.config.async)
-          this.performance.gesture = Math.trunc(now() - timeStamp);
+          this.performance.gesture = this.env.perfadd ? (this.performance.gesture || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
         else if (this.performance.gesture)
           delete this.performance.gesture;
       }

dist/human.node-wasm.js

@@ -153,8 +153,8 @@ var config = {
   debug: true,
   async: true,
   warmup: "full",
-  cacheSensitivity: 0.75,
-  skipFrame: false,
+  cacheSensitivity: 0.7,
+  skipAllowed: false,
   filter: {
     enabled: true,
     width: 0,
@@ -184,8 +184,8 @@ var config = {
       modelPath: "blazeface.json",
       rotation: true,
       maxDetected: 1,
-      skipFrames: 11,
-      skipTime: 2e3,
+      skipFrames: 99,
+      skipTime: 2500,
       minConfidence: 0.2,
       iouThreshold: 0.1,
       return: false
@@ -201,21 +201,21 @@ var config = {
     emotion: {
       enabled: true,
       minConfidence: 0.1,
-      skipFrames: 12,
-      skipTime: 2e3,
+      skipFrames: 99,
+      skipTime: 1500,
       modelPath: "emotion.json"
     },
     description: {
       enabled: true,
       modelPath: "faceres.json",
-      skipFrames: 13,
-      skipTime: 2e3,
+      skipFrames: 99,
+      skipTime: 3e3,
       minConfidence: 0.1
     },
     antispoof: {
       enabled: false,
-      skipFrames: 14,
-      skipTime: 2e3,
+      skipFrames: 99,
+      skipTime: 4e3,
       modelPath: "antispoof.json"
     }
   },
@@ -228,12 +228,12 @@ var config = {
     maxDetected: -1,
     minConfidence: 0.3,
     skipFrames: 1,
-    skipTime: 2e3
+    skipTime: 200
   },
   hand: {
     enabled: true,
     rotation: true,
-    skipFrames: 2,
+    skipFrames: 99,
     skipTime: 2e3,
     minConfidence: 0.5,
     iouThreshold: 0.2,
@@ -252,8 +252,8 @@ var config = {
     minConfidence: 0.2,
     iouThreshold: 0.4,
     maxDetected: 10,
-    skipFrames: 15,
-    skipTime: 2e3
+    skipFrames: 99,
+    skipTime: 1e3
   },
   segmentation: {
     enabled: false,
@@ -1191,6 +1191,7 @@ var Env = class {
     __publicField(this, "filter");
     __publicField(this, "tfjs");
     __publicField(this, "offscreen");
+    __publicField(this, "perfadd", false);
     __publicField(this, "wasm", {
       supported: void 0,
       backend: void 0,
@@ -1322,7 +1323,7 @@ var model2;
 var cached = [];
 var skipped2 = Number.MAX_SAFE_INTEGER;
 var lastCount = 0;
-var last = 0;
+var lastTime = 0;
 async function load2(config3) {
   var _a, _b;
   if (env.initial)
@@ -1341,7 +1342,9 @@ async function predict(image25, config3, idx, count2) {
   var _a, _b;
   if (!model2)
     return null;
-  if (skipped2 < (((_a = config3.face.antispoof) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.antispoof) == null ? void 0 : _b.skipTime) || 0) <= now() - last && config3.skipFrame && lastCount === count2 && cached[idx]) {
+  const skipTime = (((_a = config3.face.antispoof) == null ? void 0 : _a.skipTime) || 0) > now() - lastTime;
+  const skipFrame = skipped2 < (((_b = config3.face.antispoof) == null ? void 0 : _b.skipFrames) || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && lastCount === count2 && cached[idx]) {
     skipped2++;
     return cached[idx];
   }
@@ -1352,7 +1355,7 @@ async function predict(image25, config3, idx, count2) {
     const num = (await res.data())[0];
     cached[idx] = Math.round(100 * num) / 100;
     lastCount = count2;
-    last = now();
+    lastTime = now();
     tf4.dispose([resize, res]);
     resolve(cached[idx]);
   });
@@ -4937,7 +4940,7 @@ var skipped3 = Number.MAX_SAFE_INTEGER;
 var outputNodes;
 var cache = null;
 var padding = [[0, 0], [0, 0], [0, 0], [0, 0]];
-var last2 = 0;
+var lastTime2 = 0;
 async function loadDetect(config3) {
   var _a, _b, _c;
   if (env3.initial)
@@ -5054,11 +5057,13 @@ async function detectParts(input, config3, outputSize2) {
 }
 async function predict2(input, config3) {
   const outputSize2 = [input.shape[2] || 0, input.shape[1] || 0];
-  if (skipped3 < (config3.body.skipFrames || 0) && (config3.body.skipTime || 0) <= now() - last2 && config3.skipFrame && cache !== null) {
+  const skipTime = (config3.body.skipTime || 0) > now() - lastTime2;
+  const skipFrame = skipped3 < (config3.body.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && cache !== null) {
     skipped3++;
   } else {
     cache = await detectParts(input, config3, outputSize2);
-    last2 = now();
+    lastTime2 = now();
     skipped3 = 0;
   }
   if (cache)
@@ -5156,8 +5161,8 @@ var labels = [
 // src/object/centernet.ts
 var model4;
 var inputSize3 = 0;
-var last3 = [];
-var lastTime = 0;
+var last = [];
+var lastTime3 = 0;
 var skipped4 = Number.MAX_SAFE_INTEGER;
 async function load4(config3) {
   if (env.initial)
@@ -5222,21 +5227,23 @@ async function process3(res, outputShape, config3) {
   return results;
 }
 async function predict3(input, config3) {
-  if (skipped4 < (config3.object.skipFrames || 0) && (config3.object.skipTime || 0) <= now() - lastTime && config3.skipFrame && last3.length > 0) {
+  const skipTime = (config3.object.skipTime || 0) > now() - lastTime3;
+  const skipFrame = skipped4 < (config3.object.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && last.length > 0) {
     skipped4++;
-    return last3;
+    return last;
   }
   skipped4 = 0;
   if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
-    return last3;
+    return last;
   return new Promise(async (resolve) => {
     const outputSize2 = [input.shape[2], input.shape[1]];
     const resize = tf8.image.resizeBilinear(input, [inputSize3, inputSize3]);
     const objectT = config3.object.enabled ? model4 == null ? void 0 : model4.execute(resize, ["tower_0/detections"]) : null;
-    lastTime = now();
+    lastTime3 = now();
     tf8.dispose(resize);
     const obj = await process3(objectT, outputSize2, config3);
-    last3 = obj;
+    last = obj;
     resolve(obj);
   });
 }
@@ -5279,7 +5286,7 @@ var connected2 = {
 
 // src/body/efficientpose.ts
 var model5;
-var last4 = 0;
+var lastTime4 = 0;
 var cache2 = { id: 0, keypoints: [], box: [0, 0, 0, 0], boxRaw: [0, 0, 0, 0], score: 0, annotations: {} };
 var skipped5 = Number.MAX_SAFE_INTEGER;
 async function load5(config3) {
@@ -5311,14 +5318,15 @@ function max2d(inputs, minScore) {
   });
 }
 async function predict4(image25, config3) {
-  var _a;
-  if (skipped5 < (((_a = config3.body) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && Object.keys(cache2.keypoints).length > 0 && (config3.body.skipTime || 0) <= now() - last4) {
+  const skipTime = (config3.body.skipTime || 0) > now() - lastTime4;
+  const skipFrame = skipped5 < (config3.body.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && Object.keys(cache2.keypoints).length > 0) {
     skipped5++;
     return [cache2];
   }
   skipped5 = 0;
   return new Promise(async (resolve) => {
-    var _a2;
+    var _a;
     const tensor3 = tf9.tidy(() => {
       if (!(model5 == null ? void 0 : model5.inputs[0].shape))
         return null;
@@ -5330,7 +5338,7 @@ async function predict4(image25, config3) {
     let resT;
     if (config3.body.enabled)
       resT = await (model5 == null ? void 0 : model5.predict(tensor3));
-    last4 = now();
+    lastTime4 = now();
     tf9.dispose(tensor3);
     if (resT) {
       cache2.keypoints.length = 0;
@@ -5340,7 +5348,7 @@ async function predict4(image25, config3) {
       tf9.dispose(squeeze8);
       for (let id = 0; id < stack3.length; id++) {
         const [x2, y2, partScore] = max2d(stack3[id], config3.body.minConfidence);
-        if (partScore > (((_a2 = config3.body) == null ? void 0 : _a2.minConfidence) || 0)) {
+        if (partScore > (((_a = config3.body) == null ? void 0 : _a.minConfidence) || 0)) {
           cache2.keypoints.push({
             score: Math.round(100 * partScore) / 100,
             part: kpt2[id],
@@ -5392,9 +5400,9 @@ async function predict4(image25, config3) {
 var tf10 = __toModule(require_tfjs_esm());
 var annotations = ["angry", "disgust", "fear", "happy", "sad", "surprise", "neutral"];
 var model6;
-var last5 = [];
+var last2 = [];
 var lastCount2 = 0;
-var lastTime2 = 0;
+var lastTime5 = 0;
 var skipped6 = Number.MAX_SAFE_INTEGER;
 var rgb = [0.2989, 0.587, 0.114];
 async function load6(config3) {
@@ -5415,9 +5423,11 @@ async function predict5(image25, config3, idx, count2) {
   var _a, _b;
   if (!model6)
     return null;
-  if (skipped6 < (((_a = config3.face.emotion) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.emotion) == null ? void 0 : _b.skipTime) || 0) <= now() - lastTime2 && config3.skipFrame && lastCount2 === count2 && last5[idx] && last5[idx].length > 0) {
+  const skipFrame = skipped6 < (((_a = config3.face.emotion) == null ? void 0 : _a.skipFrames) || 0);
+  const skipTime = (((_b = config3.face.emotion) == null ? void 0 : _b.skipTime) || 0) > now() - lastTime5;
+  if (config3.skipAllowed && skipTime && skipFrame && lastCount2 === count2 && last2[idx] && last2[idx].length > 0) {
     skipped6++;
-    return last5[idx];
+    return last2[idx];
   }
   skipped6 = 0;
   return new Promise(async (resolve) => {
@@ -5440,7 +5450,7 @@ async function predict5(image25, config3, idx, count2) {
       const normalize = tf10.tidy(() => tf10.mul(tf10.sub(grayscale, 0.5), 2));
       tf10.dispose(grayscale);
       const emotionT = await (model6 == null ? void 0 : model6.predict(normalize));
-      lastTime2 = now();
+      lastTime5 = now();
       const data = await emotionT.data();
       tf10.dispose(emotionT);
       for (let i = 0; i < data.length; i++) {
@@ -5450,7 +5460,7 @@ async function predict5(image25, config3, idx, count2) {
       obj.sort((a, b) => b.score - a.score);
       tf10.dispose(normalize);
     }
-    last5[idx] = obj;
+    last2[idx] = obj;
     lastCount2 = count2;
     resolve(obj);
   });
@@ -5597,13 +5607,15 @@ var boxCache = [];
 var model8 = null;
 var inputSize5 = 0;
 var skipped7 = Number.MAX_SAFE_INTEGER;
-var lastTime3 = 0;
+var lastTime6 = 0;
 var detectedFaces = 0;
 async function predict6(input, config3) {
-  var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m;
-  if (!config3.skipFrame || (detectedFaces !== ((_a = config3.face.detector) == null ? void 0 : _a.maxDetected) || !((_b = config3.face.mesh) == null ? void 0 : _b.enabled)) && (skipped7 > (((_c = config3.face.detector) == null ? void 0 : _c.skipFrames) || 0) && (((_d = config3.face.description) == null ? void 0 : _d.skipTime) || 0) <= now() - lastTime3)) {
+  var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k;
+  const skipTime = (((_a = config3.face.detector) == null ? void 0 : _a.skipTime) || 0) > now() - lastTime6;
+  const skipFrame = skipped7 < (((_b = config3.face.detector) == null ? void 0 : _b.skipFrames) || 0);
+  if (!config3.skipAllowed || !skipTime || !skipFrame || detectedFaces === 0) {
     const newBoxes2 = await getBoxes(input, config3);
-    lastTime3 = now();
+    lastTime6 = now();
     boxCache = [];
     for (const possible of newBoxes2.boxes) {
       const startPoint = await possible.box.startPoint.data();
@@ -5639,16 +5651,16 @@ async function predict6(input, config3) {
       faceScore: 0,
       annotations: {}
     };
-    if (((_e = config3.face.detector) == null ? void 0 : _e.rotation) && ((_f = config3.face.mesh) == null ? void 0 : _f.enabled) && env.kernels.includes("rotatewithoffset")) {
+    if (((_c = config3.face.detector) == null ? void 0 : _c.rotation) && ((_d = config3.face.mesh) == null ? void 0 : _d.enabled) && env.kernels.includes("rotatewithoffset")) {
       [angle, rotationMatrix, face5.tensor] = correctFaceRotation(box4, input, inputSize5);
     } else {
       rotationMatrix = IDENTITY_MATRIX;
-      const cut = cutBoxFromImageAndResize({ startPoint: box4.startPoint, endPoint: box4.endPoint }, input, ((_g = config3.face.mesh) == null ? void 0 : _g.enabled) ? [inputSize5, inputSize5] : [size(), size()]);
+      const cut = cutBoxFromImageAndResize({ startPoint: box4.startPoint, endPoint: box4.endPoint }, input, ((_e = config3.face.mesh) == null ? void 0 : _e.enabled) ? [inputSize5, inputSize5] : [size(), size()]);
       face5.tensor = tf12.div(cut, 255);
       tf12.dispose(cut);
     }
     face5.boxScore = Math.round(100 * box4.confidence) / 100;
-    if (!((_h = config3.face.mesh) == null ? void 0 : _h.enabled)) {
+    if (!((_f = config3.face.mesh) == null ? void 0 : _f.enabled)) {
       face5.box = getClampedBox(box4, input);
       face5.boxRaw = getRawBox(box4, input);
       face5.score = Math.round(100 * box4.confidence || 0) / 100;
@@ -5671,17 +5683,17 @@ async function predict6(input, config3) {
       let rawCoords = await coordsReshaped.array();
       tf12.dispose(contourCoords);
       tf12.dispose(coordsReshaped);
-      if (faceConfidence < (((_i = config3.face.detector) == null ? void 0 : _i.minConfidence) || 1)) {
+      if (faceConfidence < (((_g = config3.face.detector) == null ? void 0 : _g.minConfidence) || 1)) {
         box4.confidence = faceConfidence;
       } else {
-        if ((_j = config3.face.iris) == null ? void 0 : _j.enabled)
+        if ((_h = config3.face.iris) == null ? void 0 : _h.enabled)
           rawCoords = await augmentIris(rawCoords, face5.tensor, config3, inputSize5);
         face5.mesh = transformRawCoords(rawCoords, box4, angle, rotationMatrix, inputSize5);
         face5.meshRaw = face5.mesh.map((pt) => [pt[0] / (input.shape[2] || 0), pt[1] / (input.shape[1] || 0), (pt[2] || 0) / inputSize5]);
         box4 = { ...enlargeBox(calculateLandmarksBoundingBox(face5.mesh), 1.5), confidence: box4.confidence };
         for (const key of Object.keys(meshAnnotations))
           face5.annotations[key] = meshAnnotations[key].map((index) => face5.mesh[index]);
-        if (((_k = config3.face.detector) == null ? void 0 : _k.rotation) && config3.face.mesh.enabled && ((_l = config3.face.description) == null ? void 0 : _l.enabled) && env.kernels.includes("rotatewithoffset")) {
+        if (((_i = config3.face.detector) == null ? void 0 : _i.rotation) && config3.face.mesh.enabled && ((_j = config3.face.description) == null ? void 0 : _j.enabled) && env.kernels.includes("rotatewithoffset")) {
           tf12.dispose(face5.tensor);
           [angle, rotationMatrix, face5.tensor] = correctFaceRotation(box4, input, inputSize5);
         }
@@ -5695,7 +5707,7 @@ async function predict6(input, config3) {
     faces.push(face5);
     newBoxes.push(box4);
   }
-  if ((_m = config3.face.mesh) == null ? void 0 : _m.enabled)
+  if ((_k = config3.face.mesh) == null ? void 0 : _k.enabled)
     boxCache = newBoxes.filter((a) => {
       var _a2;
       return a.confidence > (((_a2 = config3.face.detector) == null ? void 0 : _a2.minConfidence) || 0);
@@ -5726,8 +5738,8 @@ var uvmap = UV468;
 // src/face/faceres.ts
 var tf13 = __toModule(require_tfjs_esm());
 var model9;
-var last6 = [];
-var lastTime4 = 0;
+var last3 = [];
+var lastTime7 = 0;
 var lastCount3 = 0;
 var skipped8 = Number.MAX_SAFE_INTEGER;
 async function load9(config3) {
@@ -5763,9 +5775,11 @@ async function predict7(image25, config3, idx, count2) {
   var _a, _b, _c, _d;
   if (!model9)
     return null;
-  if (skipped8 < (((_a = config3.face.description) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.description) == null ? void 0 : _b.skipTime) || 0) <= now() - lastTime4 && config3.skipFrame && lastCount3 === count2 && ((_c = last6[idx]) == null ? void 0 : _c.age) && ((_d = last6[idx]) == null ? void 0 : _d.age) > 0) {
+  const skipFrame = skipped8 < (((_a = config3.face.description) == null ? void 0 : _a.skipFrames) || 0);
+  const skipTime = (((_b = config3.face.description) == null ? void 0 : _b.skipTime) || 0) > now() - lastTime7;
+  if (config3.skipAllowed && skipFrame && skipTime && lastCount3 === count2 && ((_c = last3[idx]) == null ? void 0 : _c.age) && ((_d = last3[idx]) == null ? void 0 : _d.age) > 0) {
     skipped8++;
-    return last6[idx];
+    return last3[idx];
   }
   skipped8 = 0;
   return new Promise(async (resolve) => {
@@ -5779,7 +5793,7 @@ async function predict7(image25, config3, idx, count2) {
     if ((_a2 = config3.face.description) == null ? void 0 : _a2.enabled) {
       const enhanced = enhance(image25);
       const resT = await (model9 == null ? void 0 : model9.predict(enhanced));
-      lastTime4 = now();
+      lastTime7 = now();
       tf13.dispose(enhanced);
       const genderT = await resT.find((t) => t.shape[1] === 1);
       const gender = await genderT.data();
@@ -5799,7 +5813,7 @@ async function predict7(image25, config3, idx, count2) {
       obj.descriptor = Array.from(descriptor);
       resT.forEach((t) => tf13.dispose(t));
     }
-    last6[idx] = obj;
+    last3[idx] = obj;
     lastCount3 = count2;
     resolve(obj);
   });
@@ -8954,7 +8968,7 @@ var handBoxEnlargeFactor = 1.65;
 var palmLandmarkIds = [0, 5, 9, 13, 17, 1, 2];
 var palmLandmarksPalmBase = 0;
 var palmLandmarksMiddleFingerBase = 2;
-var lastTime5 = 0;
+var lastTime8 = 0;
 var HandPipeline = class {
   constructor(handDetector, handPoseModel2) {
     __publicField(this, "handDetector");
@@ -8967,7 +8981,7 @@ var HandPipeline = class {
     this.handPoseModel = handPoseModel2;
     this.inputSize = this.handPoseModel && this.handPoseModel.inputs[0].shape ? this.handPoseModel.inputs[0].shape[2] : 0;
     this.storedBoxes = [];
-    this.skipped = 0;
+    this.skipped = Number.MAX_SAFE_INTEGER;
     this.detectedHands = 0;
   }
   calculateLandmarksBoundingBox(landmarks) {
@@ -9019,11 +9033,13 @@ var HandPipeline = class {
   async estimateHands(image25, config3) {
     let useFreshBox = false;
     let boxes;
-    if (this.skipped === 0 || this.skipped > config3.hand.skipFrames && (config3.hand.skipTime || 0) <= now() - lastTime5 || !config3.hand.landmarks || !config3.skipFrame) {
+    const skipTime = (config3.hand.skipTime || 0) > now() - lastTime8;
+    const skipFrame = this.skipped < (config3.hand.skipFrames || 0);
+    if (config3.skipAllowed && skipTime && skipFrame) {
       boxes = await this.handDetector.estimateHandBounds(image25, config3);
       this.skipped = 0;
     }
-    if (config3.skipFrame)
+    if (config3.skipAllowed)
       this.skipped++;
     if (boxes && boxes.length > 0 && (boxes.length !== this.detectedHands && this.detectedHands !== config3.hand.maxDetected || !config3.hand.landmarks)) {
       this.detectedHands = 0;
@@ -9048,7 +9064,7 @@ var HandPipeline = class {
         tf16.dispose(croppedInput);
         tf16.dispose(rotatedImage);
         const [confidenceT, keypoints] = await this.handPoseModel.predict(handImage);
-        lastTime5 = now();
+        lastTime8 = now();
         tf16.dispose(handImage);
         const confidence = (await confidenceT.data())[0];
         tf16.dispose(confidenceT);
@@ -9617,8 +9633,8 @@ var faceIndex = 4;
 var boxExpandFact = 1.6;
 var maxDetectorResolution = 512;
 var detectorExpandFact = 1.4;
-var skipped9 = 0;
-var lastTime6 = 0;
+var skipped9 = Number.MAX_SAFE_INTEGER;
+var lastTime9 = 0;
 var outputSize = [0, 0];
 var cache3 = {
   boxes: [],
@@ -9758,17 +9774,21 @@ async function predict9(input, config3) {
     return [];
   outputSize = [input.shape[2] || 0, input.shape[1] || 0];
   skipped9++;
-  if (config3.skipFrame && skipped9 <= (config3.hand.skipFrames || 0) && (config3.hand.skipTime || 0) <= now() - lastTime6) {
+  const skipTime = (config3.hand.skipTime || 0) > now() - lastTime9;
+  const skipFrame = skipped9 < (config3.hand.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame) {
     return cache3.hands;
   }
   return new Promise(async (resolve) => {
-    if (config3.skipFrame && cache3.hands.length === config3.hand.maxDetected) {
+    const skipTimeExtended = 3 * (config3.hand.skipTime || 0) > now() - lastTime9;
+    const skipFrameExtended = skipped9 < 3 * (config3.hand.skipFrames || 0);
+    if (config3.skipAllowed && cache3.hands.length === config3.hand.maxDetected) {
       cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
-    } else if (config3.skipFrame && skipped9 < 3 * (config3.hand.skipFrames || 0) && (config3.hand.skipTime || 0) <= 3 * (now() - lastTime6) && cache3.hands.length > 0) {
+    } else if (config3.skipAllowed && skipTimeExtended && skipFrameExtended && cache3.hands.length > 0) {
       cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
     } else {
       cache3.boxes = await detectHands(input, config3);
-      lastTime6 = now();
+      lastTime9 = now();
       cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
       skipped9 = 0;
     }
@@ -10067,10 +10087,12 @@ async function parseMultiPose(res, config3, image25, inputBox) {
 async function predict10(input, config3) {
   if (!model10 || !(model10 == null ? void 0 : model10.inputs[0].shape))
     return [];
-  if (!config3.skipFrame)
+  if (!config3.skipAllowed)
     cache5.boxes.length = 0;
   skipped10++;
-  if (config3.skipFrame && (skipped10 <= (config3.body.skipFrames || 0) && (config3.body.skipTime || 0) <= now() - cache5.last)) {
+  const skipTime = (config3.body.skipTime || 0) > now() - cache5.last;
+  const skipFrame = skipped10 < (config3.body.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame) {
     return cache5.bodies;
   }
   return new Promise(async (resolve) => {
@@ -10093,8 +10115,8 @@ async function predict10(input, config3) {
 // src/object/nanodet.ts
 var tf21 = __toModule(require_tfjs_esm());
 var model11;
-var last7 = [];
-var lastTime7 = 0;
+var last4 = [];
+var lastTime10 = 0;
 var skipped11 = Number.MAX_SAFE_INTEGER;
 var scaleBox = 2.5;
 async function load12(config3) {
@@ -10174,13 +10196,15 @@ async function process4(res, inputSize8, outputShape, config3) {
   return results;
 }
 async function predict11(image25, config3) {
-  if (skipped11 < (config3.object.skipFrames || 0) && (config3.object.skipTime || 0) <= now() - lastTime7 && config3.skipFrame && last7.length > 0) {
+  const skipTime = (config3.object.skipTime || 0) > now() - lastTime10;
+  const skipFrame = skipped11 < (config3.object.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && last4.length > 0) {
     skipped11++;
-    return last7;
+    return last4;
   }
   skipped11 = 0;
   if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
-    return last7;
+    return last4;
   return new Promise(async (resolve) => {
     const outputSize2 = [image25.shape[2], image25.shape[1]];
     const resize = tf21.image.resizeBilinear(image25, [model11.inputSize, model11.inputSize], false);
@@ -10191,10 +10215,10 @@ async function predict11(image25, config3) {
     let objectT;
     if (config3.object.enabled)
       objectT = await model11.predict(transpose);
-    lastTime7 = now();
+    lastTime10 = now();
     tf21.dispose(transpose);
     const obj = await process4(objectT, model11.inputSize, outputSize2, config3);
-    last7 = obj;
+    last4 = obj;
     resolve(obj);
   });
 }
@@ -11394,7 +11418,7 @@ async function canvas2(input, output) {
 async function all(inCanvas2, result, drawOptions) {
   if (!result || !result.performance || !result || !inCanvas2)
     return null;
-  const timestamp = now();
+  const timeStamp = now();
   const localOptions = mergeDeep(options2, drawOptions);
   const promise = Promise.all([
     face(inCanvas2, result.face, localOptions),
@@ -11403,7 +11427,7 @@ async function all(inCanvas2, result, drawOptions) {
     object(inCanvas2, result.object, localOptions),
     gesture(inCanvas2, result.gesture, localOptions)
   ]);
-  result.performance.draw = Math.trunc(now() - timestamp);
+  result.performance.draw = env.perfadd ? (result.performance.draw || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
   return promise;
 }
 
@@ -11531,7 +11555,7 @@ var detectFace = async (parent, input) => {
   parent.state = "run:face";
   timeStamp = now();
   const faces = await predict6(input, parent.config);
-  parent.performance.face = Math.trunc(now() - timeStamp);
+  parent.performance.face = env.perfadd ? (parent.performance.face || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
   if (!input.shape || input.shape.length !== 4)
     return [];
   if (!faces)
@@ -11550,7 +11574,7 @@ var detectFace = async (parent, input) => {
       parent.state = "run:emotion";
       timeStamp = now();
       emotionRes = parent.config.face.emotion.enabled ? await predict5(faces[i].tensor || tf26.tensor([]), parent.config, i, faces.length) : null;
-      parent.performance.emotion = Math.trunc(now() - timeStamp);
+      parent.performance.emotion = env.perfadd ? (parent.performance.emotion || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     parent.analyze("End Emotion:");
     parent.analyze("Start AntiSpoof:");
@@ -11560,7 +11584,7 @@ var detectFace = async (parent, input) => {
       parent.state = "run:antispoof";
       timeStamp = now();
       antispoofRes = parent.config.face.antispoof.enabled ? await predict(faces[i].tensor || tf26.tensor([]), parent.config, i, faces.length) : null;
-      parent.performance.antispoof = Math.trunc(now() - timeStamp);
+      parent.performance.antispoof = env.perfadd ? (parent.performance.antispoof || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     parent.analyze("End AntiSpoof:");
     parent.analyze("Start Description:");
@@ -11570,7 +11594,7 @@ var detectFace = async (parent, input) => {
       parent.state = "run:description";
       timeStamp = now();
       descRes = parent.config.face.description.enabled ? await predict7(faces[i].tensor || tf26.tensor([]), parent.config, i, faces.length) : null;
-      parent.performance.embedding = Math.trunc(now() - timeStamp);
+      parent.performance.embedding = env.perfadd ? (parent.performance.embedding || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     parent.analyze("End Description:");
     if (parent.config.async) {
@@ -12889,7 +12913,7 @@ var Human = class {
     const count2 = Object.values(this.models).filter((model14) => model14).length;
     if (userConfig)
       this.config = mergeDeep(this.config, userConfig);
-    if (env.initial) {
+    if (this.env.initial) {
       if (this.config.debug)
         log(`version: ${this.version}`);
       if (this.config.debug)
@@ -12905,9 +12929,9 @@ var Human = class {
       }
     }
     await load15(this);
-    if (env.initial && this.config.debug)
+    if (this.env.initial && this.config.debug)
       log("tf engine state:", this.tf.engine().state.numBytes, "bytes", this.tf.engine().state.numTensors, "tensors");
-    env.initial = false;
+    this.env.initial = false;
     const loaded = Object.values(this.models).filter((model14) => model14).length;
     if (loaded !== count2) {
       await validate2(this);
@@ -12915,7 +12939,7 @@ var Human = class {
     }
     const current = Math.trunc(now() - timeStamp);
     if (current > (this.performance.load || 0))
-      this.performance.load = current;
+      this.performance.load = this.env.perfadd ? (this.performance.load || 0) + current : current;
   }
   next(result = this.result) {
     return calc2(result, this.config);
@@ -12929,7 +12953,6 @@ var Human = class {
       var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q, _r, _s, _t, _u, _v;
       this.state = "config";
       let timeStamp;
-      let elapsedTime;
       this.config = mergeDeep(this.config, userConfig);
       this.state = "check";
       const error = __privateGet(this, _sanity).call(this, input);
@@ -12944,7 +12967,7 @@ var Human = class {
       this.state = "image";
       const img = process2(input, this.config);
       this.process = img;
-      this.performance.image = Math.trunc(now() - timeStamp);
+      this.performance.image = this.env.perfadd ? (this.performance.image || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       this.analyze("Get Image:");
       if (!img.tensor) {
         if (this.config.debug)
@@ -12954,15 +12977,15 @@ var Human = class {
       }
       this.emit("image");
       timeStamp = now();
-      this.config.skipFrame = await skip(this.config, img.tensor);
+      this.config.skipAllowed = await skip(this.config, img.tensor);
       if (!this.performance.frames)
         this.performance.frames = 0;
       if (!this.performance.cached)
         this.performance.cached = 0;
       this.performance.frames++;
-      if (this.config.skipFrame)
+      if (this.config.skipAllowed)
         this.performance.cached++;
-      this.performance.changed = Math.trunc(now() - timeStamp);
+      this.performance.changed = this.env.perfadd ? (this.performance.changed || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       this.analyze("Check Changed:");
       let faceRes = [];
       let bodyRes = [];
@@ -12976,9 +12999,7 @@ var Human = class {
       } else {
         timeStamp = now();
         faceRes = this.config.face.enabled ? await detectFace(this, img.tensor) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0)
-          this.performance.face = elapsedTime;
+        this.performance.face = this.env.perfadd ? (this.performance.face || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       if (this.config.async && (this.config.body.maxDetected === -1 || this.config.hand.maxDetected === -1))
         faceRes = await faceRes;
@@ -13006,9 +13027,7 @@ var Human = class {
           bodyRes = this.config.body.enabled ? await predict4(img.tensor, bodyConfig) : [];
         else if ((_h = this.config.body.modelPath) == null ? void 0 : _h.includes("movenet"))
           bodyRes = this.config.body.enabled ? await predict10(img.tensor, bodyConfig) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0)
-          this.performance.body = elapsedTime;
+        this.performance.body = this.env.perfadd ? (this.performance.body || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       this.analyze("End Body:");
       this.analyze("Start Hand:");
@@ -13027,9 +13046,7 @@ var Human = class {
           handRes = this.config.hand.enabled ? await predict8(img.tensor, handConfig) : [];
         else if ((_p = (_o = this.config.hand.detector) == null ? void 0 : _o.modelPath) == null ? void 0 : _p.includes("handtrack"))
           handRes = this.config.hand.enabled ? await predict9(img.tensor, handConfig) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0)
-          this.performance.hand = elapsedTime;
+        this.performance.hand = this.env.perfadd ? (this.performance.hand || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       this.analyze("End Hand:");
       this.analyze("Start Object:");
@@ -13047,9 +13064,7 @@ var Human = class {
           objectRes = this.config.object.enabled ? await predict11(img.tensor, this.config) : [];
         else if ((_t = this.config.object.modelPath) == null ? void 0 : _t.includes("centernet"))
           objectRes = this.config.object.enabled ? await predict3(img.tensor, this.config) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0)
-          this.performance.object = elapsedTime;
+        this.performance.object = this.env.perfadd ? (this.performance.object || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       this.analyze("End Object:");
       this.state = "detect:await";
@@ -13061,7 +13076,7 @@ var Human = class {
         timeStamp = now();
         gestureRes = [...face2(faceRes), ...body2(bodyRes), ...hand2(handRes), ...iris3(faceRes)];
         if (!this.config.async)
-          this.performance.gesture = Math.trunc(now() - timeStamp);
+          this.performance.gesture = this.env.perfadd ? (this.performance.gesture || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
         else if (this.performance.gesture)
           delete this.performance.gesture;
       }

dist/human.node.js

@@ -152,8 +152,8 @@ var config = {
   debug: true,
   async: true,
   warmup: "full",
-  cacheSensitivity: 0.75,
-  skipFrame: false,
+  cacheSensitivity: 0.7,
+  skipAllowed: false,
   filter: {
     enabled: true,
     width: 0,
@@ -183,8 +183,8 @@ var config = {
       modelPath: "blazeface.json",
       rotation: true,
       maxDetected: 1,
-      skipFrames: 11,
-      skipTime: 2e3,
+      skipFrames: 99,
+      skipTime: 2500,
       minConfidence: 0.2,
       iouThreshold: 0.1,
       return: false
@@ -200,21 +200,21 @@ var config = {
     emotion: {
       enabled: true,
       minConfidence: 0.1,
-      skipFrames: 12,
-      skipTime: 2e3,
+      skipFrames: 99,
+      skipTime: 1500,
       modelPath: "emotion.json"
     },
     description: {
       enabled: true,
       modelPath: "faceres.json",
-      skipFrames: 13,
-      skipTime: 2e3,
+      skipFrames: 99,
+      skipTime: 3e3,
       minConfidence: 0.1
     },
     antispoof: {
       enabled: false,
-      skipFrames: 14,
-      skipTime: 2e3,
+      skipFrames: 99,
+      skipTime: 4e3,
       modelPath: "antispoof.json"
     }
   },
@@ -227,12 +227,12 @@ var config = {
     maxDetected: -1,
     minConfidence: 0.3,
     skipFrames: 1,
-    skipTime: 2e3
+    skipTime: 200
   },
   hand: {
     enabled: true,
     rotation: true,
-    skipFrames: 2,
+    skipFrames: 99,
     skipTime: 2e3,
     minConfidence: 0.5,
     iouThreshold: 0.2,
@@ -251,8 +251,8 @@ var config = {
     minConfidence: 0.2,
     iouThreshold: 0.4,
     maxDetected: 10,
-    skipFrames: 15,
-    skipTime: 2e3
+    skipFrames: 99,
+    skipTime: 1e3
   },
   segmentation: {
     enabled: false,
@@ -1190,6 +1190,7 @@ var Env = class {
     __publicField(this, "filter");
     __publicField(this, "tfjs");
     __publicField(this, "offscreen");
+    __publicField(this, "perfadd", false);
     __publicField(this, "wasm", {
       supported: void 0,
       backend: void 0,
@@ -1321,7 +1322,7 @@ var model2;
 var cached = [];
 var skipped2 = Number.MAX_SAFE_INTEGER;
 var lastCount = 0;
-var last = 0;
+var lastTime = 0;
 async function load2(config3) {
   var _a, _b;
   if (env.initial)
@@ -1340,7 +1341,9 @@ async function predict(image25, config3, idx, count2) {
   var _a, _b;
   if (!model2)
     return null;
-  if (skipped2 < (((_a = config3.face.antispoof) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.antispoof) == null ? void 0 : _b.skipTime) || 0) <= now() - last && config3.skipFrame && lastCount === count2 && cached[idx]) {
+  const skipTime = (((_a = config3.face.antispoof) == null ? void 0 : _a.skipTime) || 0) > now() - lastTime;
+  const skipFrame = skipped2 < (((_b = config3.face.antispoof) == null ? void 0 : _b.skipFrames) || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && lastCount === count2 && cached[idx]) {
     skipped2++;
     return cached[idx];
   }
@@ -1351,7 +1354,7 @@ async function predict(image25, config3, idx, count2) {
     const num = (await res.data())[0];
     cached[idx] = Math.round(100 * num) / 100;
     lastCount = count2;
-    last = now();
+    lastTime = now();
     tf4.dispose([resize, res]);
     resolve(cached[idx]);
   });
@@ -4936,7 +4939,7 @@ var skipped3 = Number.MAX_SAFE_INTEGER;
 var outputNodes;
 var cache = null;
 var padding = [[0, 0], [0, 0], [0, 0], [0, 0]];
-var last2 = 0;
+var lastTime2 = 0;
 async function loadDetect(config3) {
   var _a, _b, _c;
   if (env3.initial)
@@ -5053,11 +5056,13 @@ async function detectParts(input, config3, outputSize2) {
 }
 async function predict2(input, config3) {
   const outputSize2 = [input.shape[2] || 0, input.shape[1] || 0];
-  if (skipped3 < (config3.body.skipFrames || 0) && (config3.body.skipTime || 0) <= now() - last2 && config3.skipFrame && cache !== null) {
+  const skipTime = (config3.body.skipTime || 0) > now() - lastTime2;
+  const skipFrame = skipped3 < (config3.body.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && cache !== null) {
     skipped3++;
   } else {
     cache = await detectParts(input, config3, outputSize2);
-    last2 = now();
+    lastTime2 = now();
     skipped3 = 0;
   }
   if (cache)
@@ -5155,8 +5160,8 @@ var labels = [
 // src/object/centernet.ts
 var model4;
 var inputSize3 = 0;
-var last3 = [];
-var lastTime = 0;
+var last = [];
+var lastTime3 = 0;
 var skipped4 = Number.MAX_SAFE_INTEGER;
 async function load4(config3) {
   if (env.initial)
@@ -5221,21 +5226,23 @@ async function process3(res, outputShape, config3) {
   return results;
 }
 async function predict3(input, config3) {
-  if (skipped4 < (config3.object.skipFrames || 0) && (config3.object.skipTime || 0) <= now() - lastTime && config3.skipFrame && last3.length > 0) {
+  const skipTime = (config3.object.skipTime || 0) > now() - lastTime3;
+  const skipFrame = skipped4 < (config3.object.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && last.length > 0) {
     skipped4++;
-    return last3;
+    return last;
   }
   skipped4 = 0;
   if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
-    return last3;
+    return last;
   return new Promise(async (resolve) => {
     const outputSize2 = [input.shape[2], input.shape[1]];
     const resize = tf8.image.resizeBilinear(input, [inputSize3, inputSize3]);
     const objectT = config3.object.enabled ? model4 == null ? void 0 : model4.execute(resize, ["tower_0/detections"]) : null;
-    lastTime = now();
+    lastTime3 = now();
     tf8.dispose(resize);
     const obj = await process3(objectT, outputSize2, config3);
-    last3 = obj;
+    last = obj;
     resolve(obj);
   });
 }
@@ -5278,7 +5285,7 @@ var connected2 = {
 
 // src/body/efficientpose.ts
 var model5;
-var last4 = 0;
+var lastTime4 = 0;
 var cache2 = { id: 0, keypoints: [], box: [0, 0, 0, 0], boxRaw: [0, 0, 0, 0], score: 0, annotations: {} };
 var skipped5 = Number.MAX_SAFE_INTEGER;
 async function load5(config3) {
@@ -5310,14 +5317,15 @@ function max2d(inputs, minScore) {
   });
 }
 async function predict4(image25, config3) {
-  var _a;
-  if (skipped5 < (((_a = config3.body) == null ? void 0 : _a.skipFrames) || 0) && config3.skipFrame && Object.keys(cache2.keypoints).length > 0 && (config3.body.skipTime || 0) <= now() - last4) {
+  const skipTime = (config3.body.skipTime || 0) > now() - lastTime4;
+  const skipFrame = skipped5 < (config3.body.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && Object.keys(cache2.keypoints).length > 0) {
     skipped5++;
     return [cache2];
   }
   skipped5 = 0;
   return new Promise(async (resolve) => {
-    var _a2;
+    var _a;
     const tensor3 = tf9.tidy(() => {
       if (!(model5 == null ? void 0 : model5.inputs[0].shape))
         return null;
@@ -5329,7 +5337,7 @@ async function predict4(image25, config3) {
     let resT;
     if (config3.body.enabled)
       resT = await (model5 == null ? void 0 : model5.predict(tensor3));
-    last4 = now();
+    lastTime4 = now();
     tf9.dispose(tensor3);
     if (resT) {
       cache2.keypoints.length = 0;
@@ -5339,7 +5347,7 @@ async function predict4(image25, config3) {
       tf9.dispose(squeeze8);
       for (let id = 0; id < stack3.length; id++) {
         const [x2, y2, partScore] = max2d(stack3[id], config3.body.minConfidence);
-        if (partScore > (((_a2 = config3.body) == null ? void 0 : _a2.minConfidence) || 0)) {
+        if (partScore > (((_a = config3.body) == null ? void 0 : _a.minConfidence) || 0)) {
           cache2.keypoints.push({
             score: Math.round(100 * partScore) / 100,
             part: kpt2[id],
@@ -5391,9 +5399,9 @@ async function predict4(image25, config3) {
 var tf10 = __toModule(require_tfjs_esm());
 var annotations = ["angry", "disgust", "fear", "happy", "sad", "surprise", "neutral"];
 var model6;
-var last5 = [];
+var last2 = [];
 var lastCount2 = 0;
-var lastTime2 = 0;
+var lastTime5 = 0;
 var skipped6 = Number.MAX_SAFE_INTEGER;
 var rgb = [0.2989, 0.587, 0.114];
 async function load6(config3) {
@@ -5414,9 +5422,11 @@ async function predict5(image25, config3, idx, count2) {
   var _a, _b;
   if (!model6)
     return null;
-  if (skipped6 < (((_a = config3.face.emotion) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.emotion) == null ? void 0 : _b.skipTime) || 0) <= now() - lastTime2 && config3.skipFrame && lastCount2 === count2 && last5[idx] && last5[idx].length > 0) {
+  const skipFrame = skipped6 < (((_a = config3.face.emotion) == null ? void 0 : _a.skipFrames) || 0);
+  const skipTime = (((_b = config3.face.emotion) == null ? void 0 : _b.skipTime) || 0) > now() - lastTime5;
+  if (config3.skipAllowed && skipTime && skipFrame && lastCount2 === count2 && last2[idx] && last2[idx].length > 0) {
     skipped6++;
-    return last5[idx];
+    return last2[idx];
   }
   skipped6 = 0;
   return new Promise(async (resolve) => {
@@ -5439,7 +5449,7 @@ async function predict5(image25, config3, idx, count2) {
       const normalize = tf10.tidy(() => tf10.mul(tf10.sub(grayscale, 0.5), 2));
       tf10.dispose(grayscale);
       const emotionT = await (model6 == null ? void 0 : model6.predict(normalize));
-      lastTime2 = now();
+      lastTime5 = now();
       const data = await emotionT.data();
       tf10.dispose(emotionT);
       for (let i = 0; i < data.length; i++) {
@@ -5449,7 +5459,7 @@ async function predict5(image25, config3, idx, count2) {
       obj.sort((a, b) => b.score - a.score);
       tf10.dispose(normalize);
     }
-    last5[idx] = obj;
+    last2[idx] = obj;
     lastCount2 = count2;
     resolve(obj);
   });
@@ -5596,13 +5606,15 @@ var boxCache = [];
 var model8 = null;
 var inputSize5 = 0;
 var skipped7 = Number.MAX_SAFE_INTEGER;
-var lastTime3 = 0;
+var lastTime6 = 0;
 var detectedFaces = 0;
 async function predict6(input, config3) {
-  var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m;
-  if (!config3.skipFrame || (detectedFaces !== ((_a = config3.face.detector) == null ? void 0 : _a.maxDetected) || !((_b = config3.face.mesh) == null ? void 0 : _b.enabled)) && (skipped7 > (((_c = config3.face.detector) == null ? void 0 : _c.skipFrames) || 0) && (((_d = config3.face.description) == null ? void 0 : _d.skipTime) || 0) <= now() - lastTime3)) {
+  var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k;
+  const skipTime = (((_a = config3.face.detector) == null ? void 0 : _a.skipTime) || 0) > now() - lastTime6;
+  const skipFrame = skipped7 < (((_b = config3.face.detector) == null ? void 0 : _b.skipFrames) || 0);
+  if (!config3.skipAllowed || !skipTime || !skipFrame || detectedFaces === 0) {
     const newBoxes2 = await getBoxes(input, config3);
-    lastTime3 = now();
+    lastTime6 = now();
     boxCache = [];
     for (const possible of newBoxes2.boxes) {
       const startPoint = await possible.box.startPoint.data();
@@ -5638,16 +5650,16 @@ async function predict6(input, config3) {
       faceScore: 0,
       annotations: {}
     };
-    if (((_e = config3.face.detector) == null ? void 0 : _e.rotation) && ((_f = config3.face.mesh) == null ? void 0 : _f.enabled) && env.kernels.includes("rotatewithoffset")) {
+    if (((_c = config3.face.detector) == null ? void 0 : _c.rotation) && ((_d = config3.face.mesh) == null ? void 0 : _d.enabled) && env.kernels.includes("rotatewithoffset")) {
       [angle, rotationMatrix, face5.tensor] = correctFaceRotation(box4, input, inputSize5);
     } else {
       rotationMatrix = IDENTITY_MATRIX;
-      const cut = cutBoxFromImageAndResize({ startPoint: box4.startPoint, endPoint: box4.endPoint }, input, ((_g = config3.face.mesh) == null ? void 0 : _g.enabled) ? [inputSize5, inputSize5] : [size(), size()]);
+      const cut = cutBoxFromImageAndResize({ startPoint: box4.startPoint, endPoint: box4.endPoint }, input, ((_e = config3.face.mesh) == null ? void 0 : _e.enabled) ? [inputSize5, inputSize5] : [size(), size()]);
       face5.tensor = tf12.div(cut, 255);
       tf12.dispose(cut);
     }
     face5.boxScore = Math.round(100 * box4.confidence) / 100;
-    if (!((_h = config3.face.mesh) == null ? void 0 : _h.enabled)) {
+    if (!((_f = config3.face.mesh) == null ? void 0 : _f.enabled)) {
       face5.box = getClampedBox(box4, input);
       face5.boxRaw = getRawBox(box4, input);
       face5.score = Math.round(100 * box4.confidence || 0) / 100;
@@ -5670,17 +5682,17 @@ async function predict6(input, config3) {
       let rawCoords = await coordsReshaped.array();
       tf12.dispose(contourCoords);
       tf12.dispose(coordsReshaped);
-      if (faceConfidence < (((_i = config3.face.detector) == null ? void 0 : _i.minConfidence) || 1)) {
+      if (faceConfidence < (((_g = config3.face.detector) == null ? void 0 : _g.minConfidence) || 1)) {
         box4.confidence = faceConfidence;
       } else {
-        if ((_j = config3.face.iris) == null ? void 0 : _j.enabled)
+        if ((_h = config3.face.iris) == null ? void 0 : _h.enabled)
           rawCoords = await augmentIris(rawCoords, face5.tensor, config3, inputSize5);
         face5.mesh = transformRawCoords(rawCoords, box4, angle, rotationMatrix, inputSize5);
         face5.meshRaw = face5.mesh.map((pt) => [pt[0] / (input.shape[2] || 0), pt[1] / (input.shape[1] || 0), (pt[2] || 0) / inputSize5]);
         box4 = { ...enlargeBox(calculateLandmarksBoundingBox(face5.mesh), 1.5), confidence: box4.confidence };
         for (const key of Object.keys(meshAnnotations))
           face5.annotations[key] = meshAnnotations[key].map((index) => face5.mesh[index]);
-        if (((_k = config3.face.detector) == null ? void 0 : _k.rotation) && config3.face.mesh.enabled && ((_l = config3.face.description) == null ? void 0 : _l.enabled) && env.kernels.includes("rotatewithoffset")) {
+        if (((_i = config3.face.detector) == null ? void 0 : _i.rotation) && config3.face.mesh.enabled && ((_j = config3.face.description) == null ? void 0 : _j.enabled) && env.kernels.includes("rotatewithoffset")) {
           tf12.dispose(face5.tensor);
           [angle, rotationMatrix, face5.tensor] = correctFaceRotation(box4, input, inputSize5);
         }
@@ -5694,7 +5706,7 @@ async function predict6(input, config3) {
     faces.push(face5);
     newBoxes.push(box4);
   }
-  if ((_m = config3.face.mesh) == null ? void 0 : _m.enabled)
+  if ((_k = config3.face.mesh) == null ? void 0 : _k.enabled)
     boxCache = newBoxes.filter((a) => {
       var _a2;
       return a.confidence > (((_a2 = config3.face.detector) == null ? void 0 : _a2.minConfidence) || 0);
@@ -5725,8 +5737,8 @@ var uvmap = UV468;
 // src/face/faceres.ts
 var tf13 = __toModule(require_tfjs_esm());
 var model9;
-var last6 = [];
-var lastTime4 = 0;
+var last3 = [];
+var lastTime7 = 0;
 var lastCount3 = 0;
 var skipped8 = Number.MAX_SAFE_INTEGER;
 async function load9(config3) {
@@ -5762,9 +5774,11 @@ async function predict7(image25, config3, idx, count2) {
   var _a, _b, _c, _d;
   if (!model9)
     return null;
-  if (skipped8 < (((_a = config3.face.description) == null ? void 0 : _a.skipFrames) || 0) && (((_b = config3.face.description) == null ? void 0 : _b.skipTime) || 0) <= now() - lastTime4 && config3.skipFrame && lastCount3 === count2 && ((_c = last6[idx]) == null ? void 0 : _c.age) && ((_d = last6[idx]) == null ? void 0 : _d.age) > 0) {
+  const skipFrame = skipped8 < (((_a = config3.face.description) == null ? void 0 : _a.skipFrames) || 0);
+  const skipTime = (((_b = config3.face.description) == null ? void 0 : _b.skipTime) || 0) > now() - lastTime7;
+  if (config3.skipAllowed && skipFrame && skipTime && lastCount3 === count2 && ((_c = last3[idx]) == null ? void 0 : _c.age) && ((_d = last3[idx]) == null ? void 0 : _d.age) > 0) {
     skipped8++;
-    return last6[idx];
+    return last3[idx];
   }
   skipped8 = 0;
   return new Promise(async (resolve) => {
@@ -5778,7 +5792,7 @@ async function predict7(image25, config3, idx, count2) {
     if ((_a2 = config3.face.description) == null ? void 0 : _a2.enabled) {
       const enhanced = enhance(image25);
       const resT = await (model9 == null ? void 0 : model9.predict(enhanced));
-      lastTime4 = now();
+      lastTime7 = now();
       tf13.dispose(enhanced);
       const genderT = await resT.find((t) => t.shape[1] === 1);
       const gender = await genderT.data();
@@ -5798,7 +5812,7 @@ async function predict7(image25, config3, idx, count2) {
       obj.descriptor = Array.from(descriptor);
       resT.forEach((t) => tf13.dispose(t));
     }
-    last6[idx] = obj;
+    last3[idx] = obj;
     lastCount3 = count2;
     resolve(obj);
   });
@@ -8953,7 +8967,7 @@ var handBoxEnlargeFactor = 1.65;
 var palmLandmarkIds = [0, 5, 9, 13, 17, 1, 2];
 var palmLandmarksPalmBase = 0;
 var palmLandmarksMiddleFingerBase = 2;
-var lastTime5 = 0;
+var lastTime8 = 0;
 var HandPipeline = class {
   constructor(handDetector, handPoseModel2) {
     __publicField(this, "handDetector");
@@ -8966,7 +8980,7 @@ var HandPipeline = class {
     this.handPoseModel = handPoseModel2;
     this.inputSize = this.handPoseModel && this.handPoseModel.inputs[0].shape ? this.handPoseModel.inputs[0].shape[2] : 0;
     this.storedBoxes = [];
-    this.skipped = 0;
+    this.skipped = Number.MAX_SAFE_INTEGER;
     this.detectedHands = 0;
   }
   calculateLandmarksBoundingBox(landmarks) {
@@ -9018,11 +9032,13 @@ var HandPipeline = class {
   async estimateHands(image25, config3) {
     let useFreshBox = false;
     let boxes;
-    if (this.skipped === 0 || this.skipped > config3.hand.skipFrames && (config3.hand.skipTime || 0) <= now() - lastTime5 || !config3.hand.landmarks || !config3.skipFrame) {
+    const skipTime = (config3.hand.skipTime || 0) > now() - lastTime8;
+    const skipFrame = this.skipped < (config3.hand.skipFrames || 0);
+    if (config3.skipAllowed && skipTime && skipFrame) {
       boxes = await this.handDetector.estimateHandBounds(image25, config3);
       this.skipped = 0;
     }
-    if (config3.skipFrame)
+    if (config3.skipAllowed)
       this.skipped++;
     if (boxes && boxes.length > 0 && (boxes.length !== this.detectedHands && this.detectedHands !== config3.hand.maxDetected || !config3.hand.landmarks)) {
       this.detectedHands = 0;
@@ -9047,7 +9063,7 @@ var HandPipeline = class {
         tf16.dispose(croppedInput);
         tf16.dispose(rotatedImage);
         const [confidenceT, keypoints] = await this.handPoseModel.predict(handImage);
-        lastTime5 = now();
+        lastTime8 = now();
         tf16.dispose(handImage);
         const confidence = (await confidenceT.data())[0];
         tf16.dispose(confidenceT);
@@ -9616,8 +9632,8 @@ var faceIndex = 4;
 var boxExpandFact = 1.6;
 var maxDetectorResolution = 512;
 var detectorExpandFact = 1.4;
-var skipped9 = 0;
-var lastTime6 = 0;
+var skipped9 = Number.MAX_SAFE_INTEGER;
+var lastTime9 = 0;
 var outputSize = [0, 0];
 var cache3 = {
   boxes: [],
@@ -9757,17 +9773,21 @@ async function predict9(input, config3) {
     return [];
   outputSize = [input.shape[2] || 0, input.shape[1] || 0];
   skipped9++;
-  if (config3.skipFrame && skipped9 <= (config3.hand.skipFrames || 0) && (config3.hand.skipTime || 0) <= now() - lastTime6) {
+  const skipTime = (config3.hand.skipTime || 0) > now() - lastTime9;
+  const skipFrame = skipped9 < (config3.hand.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame) {
     return cache3.hands;
   }
   return new Promise(async (resolve) => {
-    if (config3.skipFrame && cache3.hands.length === config3.hand.maxDetected) {
+    const skipTimeExtended = 3 * (config3.hand.skipTime || 0) > now() - lastTime9;
+    const skipFrameExtended = skipped9 < 3 * (config3.hand.skipFrames || 0);
+    if (config3.skipAllowed && cache3.hands.length === config3.hand.maxDetected) {
       cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
-    } else if (config3.skipFrame && skipped9 < 3 * (config3.hand.skipFrames || 0) && (config3.hand.skipTime || 0) <= 3 * (now() - lastTime6) && cache3.hands.length > 0) {
+    } else if (config3.skipAllowed && skipTimeExtended && skipFrameExtended && cache3.hands.length > 0) {
       cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
     } else {
       cache3.boxes = await detectHands(input, config3);
-      lastTime6 = now();
+      lastTime9 = now();
       cache3.hands = await Promise.all(cache3.boxes.map((handBox) => detectFingers(input, handBox, config3)));
       skipped9 = 0;
     }
@@ -10066,10 +10086,12 @@ async function parseMultiPose(res, config3, image25, inputBox) {
 async function predict10(input, config3) {
   if (!model10 || !(model10 == null ? void 0 : model10.inputs[0].shape))
     return [];
-  if (!config3.skipFrame)
+  if (!config3.skipAllowed)
     cache5.boxes.length = 0;
   skipped10++;
-  if (config3.skipFrame && (skipped10 <= (config3.body.skipFrames || 0) && (config3.body.skipTime || 0) <= now() - cache5.last)) {
+  const skipTime = (config3.body.skipTime || 0) > now() - cache5.last;
+  const skipFrame = skipped10 < (config3.body.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame) {
     return cache5.bodies;
   }
   return new Promise(async (resolve) => {
@@ -10092,8 +10114,8 @@ async function predict10(input, config3) {
 // src/object/nanodet.ts
 var tf21 = __toModule(require_tfjs_esm());
 var model11;
-var last7 = [];
-var lastTime7 = 0;
+var last4 = [];
+var lastTime10 = 0;
 var skipped11 = Number.MAX_SAFE_INTEGER;
 var scaleBox = 2.5;
 async function load12(config3) {
@@ -10173,13 +10195,15 @@ async function process4(res, inputSize8, outputShape, config3) {
   return results;
 }
 async function predict11(image25, config3) {
-  if (skipped11 < (config3.object.skipFrames || 0) && (config3.object.skipTime || 0) <= now() - lastTime7 && config3.skipFrame && last7.length > 0) {
+  const skipTime = (config3.object.skipTime || 0) > now() - lastTime10;
+  const skipFrame = skipped11 < (config3.object.skipFrames || 0);
+  if (config3.skipAllowed && skipTime && skipFrame && last4.length > 0) {
     skipped11++;
-    return last7;
+    return last4;
   }
   skipped11 = 0;
   if (!env.kernels.includes("mod") || !env.kernels.includes("sparsetodense"))
-    return last7;
+    return last4;
   return new Promise(async (resolve) => {
     const outputSize2 = [image25.shape[2], image25.shape[1]];
     const resize = tf21.image.resizeBilinear(image25, [model11.inputSize, model11.inputSize], false);
@@ -10190,10 +10214,10 @@ async function predict11(image25, config3) {
     let objectT;
     if (config3.object.enabled)
       objectT = await model11.predict(transpose);
-    lastTime7 = now();
+    lastTime10 = now();
     tf21.dispose(transpose);
     const obj = await process4(objectT, model11.inputSize, outputSize2, config3);
-    last7 = obj;
+    last4 = obj;
     resolve(obj);
   });
 }
@@ -11393,7 +11417,7 @@ async function canvas2(input, output) {
 async function all(inCanvas2, result, drawOptions) {
   if (!result || !result.performance || !result || !inCanvas2)
     return null;
-  const timestamp = now();
+  const timeStamp = now();
   const localOptions = mergeDeep(options2, drawOptions);
   const promise = Promise.all([
     face(inCanvas2, result.face, localOptions),
@@ -11402,7 +11426,7 @@ async function all(inCanvas2, result, drawOptions) {
     object(inCanvas2, result.object, localOptions),
     gesture(inCanvas2, result.gesture, localOptions)
   ]);
-  result.performance.draw = Math.trunc(now() - timestamp);
+  result.performance.draw = env.perfadd ? (result.performance.draw || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
   return promise;
 }
 
@@ -11530,7 +11554,7 @@ var detectFace = async (parent, input) => {
   parent.state = "run:face";
   timeStamp = now();
   const faces = await predict6(input, parent.config);
-  parent.performance.face = Math.trunc(now() - timeStamp);
+  parent.performance.face = env.perfadd ? (parent.performance.face || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
   if (!input.shape || input.shape.length !== 4)
     return [];
   if (!faces)
@@ -11549,7 +11573,7 @@ var detectFace = async (parent, input) => {
       parent.state = "run:emotion";
       timeStamp = now();
       emotionRes = parent.config.face.emotion.enabled ? await predict5(faces[i].tensor || tf26.tensor([]), parent.config, i, faces.length) : null;
-      parent.performance.emotion = Math.trunc(now() - timeStamp);
+      parent.performance.emotion = env.perfadd ? (parent.performance.emotion || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     parent.analyze("End Emotion:");
     parent.analyze("Start AntiSpoof:");
@@ -11559,7 +11583,7 @@ var detectFace = async (parent, input) => {
       parent.state = "run:antispoof";
       timeStamp = now();
       antispoofRes = parent.config.face.antispoof.enabled ? await predict(faces[i].tensor || tf26.tensor([]), parent.config, i, faces.length) : null;
-      parent.performance.antispoof = Math.trunc(now() - timeStamp);
+      parent.performance.antispoof = env.perfadd ? (parent.performance.antispoof || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     parent.analyze("End AntiSpoof:");
     parent.analyze("Start Description:");
@@ -11569,7 +11593,7 @@ var detectFace = async (parent, input) => {
       parent.state = "run:description";
       timeStamp = now();
       descRes = parent.config.face.description.enabled ? await predict7(faces[i].tensor || tf26.tensor([]), parent.config, i, faces.length) : null;
-      parent.performance.embedding = Math.trunc(now() - timeStamp);
+      parent.performance.embedding = env.perfadd ? (parent.performance.embedding || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     parent.analyze("End Description:");
     if (parent.config.async) {
@@ -12888,7 +12912,7 @@ var Human = class {
     const count2 = Object.values(this.models).filter((model14) => model14).length;
     if (userConfig)
       this.config = mergeDeep(this.config, userConfig);
-    if (env.initial) {
+    if (this.env.initial) {
       if (this.config.debug)
         log(`version: ${this.version}`);
       if (this.config.debug)
@@ -12904,9 +12928,9 @@ var Human = class {
       }
     }
     await load15(this);
-    if (env.initial && this.config.debug)
+    if (this.env.initial && this.config.debug)
       log("tf engine state:", this.tf.engine().state.numBytes, "bytes", this.tf.engine().state.numTensors, "tensors");
-    env.initial = false;
+    this.env.initial = false;
     const loaded = Object.values(this.models).filter((model14) => model14).length;
     if (loaded !== count2) {
       await validate2(this);
@@ -12914,7 +12938,7 @@ var Human = class {
     }
     const current = Math.trunc(now() - timeStamp);
     if (current > (this.performance.load || 0))
-      this.performance.load = current;
+      this.performance.load = this.env.perfadd ? (this.performance.load || 0) + current : current;
   }
   next(result = this.result) {
     return calc2(result, this.config);
@@ -12928,7 +12952,6 @@ var Human = class {
       var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q, _r, _s, _t, _u, _v;
       this.state = "config";
       let timeStamp;
-      let elapsedTime;
       this.config = mergeDeep(this.config, userConfig);
       this.state = "check";
       const error = __privateGet(this, _sanity).call(this, input);
@@ -12943,7 +12966,7 @@ var Human = class {
       this.state = "image";
       const img = process2(input, this.config);
       this.process = img;
-      this.performance.image = Math.trunc(now() - timeStamp);
+      this.performance.image = this.env.perfadd ? (this.performance.image || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       this.analyze("Get Image:");
       if (!img.tensor) {
         if (this.config.debug)
@@ -12953,15 +12976,15 @@ var Human = class {
       }
       this.emit("image");
       timeStamp = now();
-      this.config.skipFrame = await skip(this.config, img.tensor);
+      this.config.skipAllowed = await skip(this.config, img.tensor);
       if (!this.performance.frames)
         this.performance.frames = 0;
       if (!this.performance.cached)
         this.performance.cached = 0;
       this.performance.frames++;
-      if (this.config.skipFrame)
+      if (this.config.skipAllowed)
         this.performance.cached++;
-      this.performance.changed = Math.trunc(now() - timeStamp);
+      this.performance.changed = this.env.perfadd ? (this.performance.changed || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       this.analyze("Check Changed:");
       let faceRes = [];
       let bodyRes = [];
@@ -12975,9 +12998,7 @@ var Human = class {
       } else {
         timeStamp = now();
         faceRes = this.config.face.enabled ? await detectFace(this, img.tensor) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0)
-          this.performance.face = elapsedTime;
+        this.performance.face = this.env.perfadd ? (this.performance.face || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       if (this.config.async && (this.config.body.maxDetected === -1 || this.config.hand.maxDetected === -1))
         faceRes = await faceRes;
@@ -13005,9 +13026,7 @@ var Human = class {
           bodyRes = this.config.body.enabled ? await predict4(img.tensor, bodyConfig) : [];
         else if ((_h = this.config.body.modelPath) == null ? void 0 : _h.includes("movenet"))
           bodyRes = this.config.body.enabled ? await predict10(img.tensor, bodyConfig) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0)
-          this.performance.body = elapsedTime;
+        this.performance.body = this.env.perfadd ? (this.performance.body || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       this.analyze("End Body:");
       this.analyze("Start Hand:");
@@ -13026,9 +13045,7 @@ var Human = class {
           handRes = this.config.hand.enabled ? await predict8(img.tensor, handConfig) : [];
         else if ((_p = (_o = this.config.hand.detector) == null ? void 0 : _o.modelPath) == null ? void 0 : _p.includes("handtrack"))
           handRes = this.config.hand.enabled ? await predict9(img.tensor, handConfig) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0)
-          this.performance.hand = elapsedTime;
+        this.performance.hand = this.env.perfadd ? (this.performance.hand || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       this.analyze("End Hand:");
       this.analyze("Start Object:");
@@ -13046,9 +13063,7 @@ var Human = class {
           objectRes = this.config.object.enabled ? await predict11(img.tensor, this.config) : [];
         else if ((_t = this.config.object.modelPath) == null ? void 0 : _t.includes("centernet"))
           objectRes = this.config.object.enabled ? await predict3(img.tensor, this.config) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0)
-          this.performance.object = elapsedTime;
+        this.performance.object = this.env.perfadd ? (this.performance.object || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       this.analyze("End Object:");
       this.state = "detect:await";
@@ -13060,7 +13075,7 @@ var Human = class {
         timeStamp = now();
         gestureRes = [...face2(faceRes), ...body2(bodyRes), ...hand2(handRes), ...iris3(faceRes)];
         if (!this.config.async)
-          this.performance.gesture = Math.trunc(now() - timeStamp);
+          this.performance.gesture = this.env.perfadd ? (this.performance.gesture || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
         else if (this.performance.gesture)
           delete this.performance.gesture;
       }

src/body/blazepose.ts

@@ -16,7 +16,7 @@ let skipped = Number.MAX_SAFE_INTEGER;
 let outputNodes: string[]; // different for lite/full/heavy
 let cache: BodyResult | null = null;
 let padding: [number, number][] = [[0, 0], [0, 0], [0, 0], [0, 0]];
-let last = 0;
+let lastTime = 0;
 
 export async function loadDetect(config: Config): Promise<GraphModel> {
   if (env.initial) models[0] = null;
@@ -136,11 +136,13 @@ async function detectParts(input: Tensor, config: Config, outputSize: [number, n
 
 export async function predict(input: Tensor, config: Config): Promise<BodyResult[]> {
   const outputSize: [number, number] = [input.shape[2] || 0, input.shape[1] || 0];
-  if ((skipped < (config.body.skipFrames || 0)) && ((config.body.skipTime || 0) <= (now() - last)) && config.skipFrame && cache !== null) {
+  const skipTime = (config.body.skipTime || 0) > (now() - lastTime);
+  const skipFrame = skipped < (config.body.skipFrames || 0);
+  if (config.skipAllowed && skipTime && skipFrame && cache !== null) {
     skipped++;
   } else {
     cache = await detectParts(input, config, outputSize);
-    last = now();
+    lastTime = now();
     skipped = 0;
   }
   if (cache) return [cache];

src/body/efficientpose.ts

@@ -13,7 +13,7 @@ import type { Config } from '../config';
 import { env } from '../util/env';
 
 let model: GraphModel | null;
-let last = 0;
+let lastTime = 0;
 const cache: BodyResult = { id: 0, keypoints: [], box: [0, 0, 0, 0], boxRaw: [0, 0, 0, 0], score: 0, annotations: {} };
 
 // const keypoints: Array<BodyKeypoint> = [];
@@ -50,7 +50,9 @@ function max2d(inputs, minScore) {
 }
 
 export async function predict(image: Tensor, config: Config): Promise<BodyResult[]> {
-  if ((skipped < (config.body?.skipFrames || 0)) && config.skipFrame && Object.keys(cache.keypoints).length > 0 && ((config.body.skipTime || 0) <= (now() - last))) {
+  const skipTime = (config.body.skipTime || 0) > (now() - lastTime);
+  const skipFrame = skipped < (config.body.skipFrames || 0);
+  if (config.skipAllowed && skipTime && skipFrame && Object.keys(cache.keypoints).length > 0) {
     skipped++;
     return [cache];
   }
@@ -66,7 +68,7 @@ export async function predict(image: Tensor, config: Config): Promise<BodyResult
 
     let resT;
     if (config.body.enabled) resT = await model?.predict(tensor);
-    last = now();
+    lastTime = now();
     tf.dispose(tensor);
 
     if (resT) {

src/body/movenet.ts

@@ -132,9 +132,11 @@ async function parseMultiPose(res, config, image, inputBox) {
 
 export async function predict(input: Tensor, config: Config): Promise<BodyResult[]> {
   if (!model || !model?.inputs[0].shape) return []; // something is wrong with the model
-  if (!config.skipFrame) cache.boxes.length = 0; // allowed to use cache or not
+  if (!config.skipAllowed) cache.boxes.length = 0; // allowed to use cache or not
   skipped++; // increment skip frames
-  if (config.skipFrame && (skipped <= (config.body.skipFrames || 0) && ((config.body.skipTime || 0) <= (now() - cache.last)))) {
+  const skipTime = (config.body.skipTime || 0) > (now() - cache.last);
+  const skipFrame = skipped < (config.body.skipFrames || 0);
+  if (config.skipAllowed && skipTime && skipFrame) {
     return cache.bodies; // return cached results without running anything
   }
   return new Promise(async (resolve) => {

src/config.ts

@@ -255,7 +255,7 @@ export interface Config {
   cacheSensitivity: number;
 
   /** Internal Variable */
-  skipFrame: boolean;
+  skipAllowed: boolean;
 
   /** Run input through image filters before inference
    * - image filters run with near-zero latency as they are executed on the GPU
@@ -302,10 +302,10 @@ const config: Config = {
                              // warmup pre-initializes all models for faster inference but can take
                              // significant time on startup
                              // only used for `webgl` and `humangl` backends
-  cacheSensitivity: 0.75,    // cache sensitivity
+  cacheSensitivity: 0.70,    // cache sensitivity
                              // values 0..1 where 0.01 means reset cache if input changed more than 1%
                              // set to 0 to disable caching
-  skipFrame: false,          // internal & dynamic
+  skipAllowed: false,        // internal & dynamic
   filter: {                  // run input through image filters before inference
                              // image filters run with near-zero latency as they are executed on the GPU
     enabled: true,           // enable image pre-processing filters
@@ -347,9 +347,9 @@ const config: Config = {
                              // this parameter is not valid in nodejs
       maxDetected: 1,        // maximum number of faces detected in the input
                              // should be set to the minimum number for performance
-      skipFrames: 11,        // how many max frames to go without re-running the face bounding box detector
+      skipFrames: 99,        // how many max frames to go without re-running the face bounding box detector
                              // only used when cacheSensitivity is not zero
-      skipTime: 2000,        // how many ms to go without re-running the face bounding box detector
+      skipTime: 2500,        // how many ms to go without re-running the face bounding box detector
                              // only used when cacheSensitivity is not zero
       minConfidence: 0.2,    // threshold for discarding a prediction
       iouThreshold: 0.1,     // ammount of overlap between two detected objects before one object is removed
@@ -371,9 +371,9 @@ const config: Config = {
     emotion: {
       enabled: true,
       minConfidence: 0.1,    // threshold for discarding a prediction
-      skipFrames: 12,        // how max many frames to go without re-running the detector
+      skipFrames: 99,        // how max many frames to go without re-running the detector
                              // only used when cacheSensitivity is not zero
-      skipTime: 2000,        // how many ms to go without re-running the face bounding box detector
+      skipTime: 1500,        // how many ms to go without re-running the face bounding box detector
                              // only used when cacheSensitivity is not zero
       modelPath: 'emotion.json',  // face emotion model, can be absolute path or relative to modelBasePath
     },
@@ -383,18 +383,18 @@ const config: Config = {
                              // recommended to enable detector.rotation and mesh.enabled
       modelPath: 'faceres.json',  // face description model
                              // can be either absolute path or relative to modelBasePath
-      skipFrames: 13,        // how many max frames to go without re-running the detector
+      skipFrames: 99,        // how many max frames to go without re-running the detector
                              // only used when cacheSensitivity is not zero
-      skipTime: 2000,        // how many ms to go without re-running the face bounding box detector
+      skipTime: 3000,        // how many ms to go without re-running the face bounding box detector
                              // only used when cacheSensitivity is not zero
       minConfidence: 0.1,    // threshold for discarding a prediction
     },
 
     antispoof: {
       enabled: false,
-      skipFrames: 14,        // how max many frames to go without re-running the detector
+      skipFrames: 99,        // how max many frames to go without re-running the detector
                              // only used when cacheSensitivity is not zero
-      skipTime: 2000,        // how many ms to go without re-running the face bounding box detector
+      skipTime: 4000,        // how many ms to go without re-running the face bounding box detector
                              // only used when cacheSensitivity is not zero
       modelPath: 'antispoof.json',  // face description model
                              // can be either absolute path or relative to modelBasePath
@@ -415,7 +415,7 @@ const config: Config = {
     minConfidence: 0.3,      // threshold for discarding a prediction
     skipFrames: 1,           // how many max frames to go without re-running the detector
                              // only used when cacheSensitivity is not zero
-    skipTime: 2000,          // how many ms to go without re-running the face bounding box detector
+    skipTime: 200,           // how many ms to go without re-running the face bounding box detector
                              // only used when cacheSensitivity is not zero
 },
 
@@ -424,7 +424,7 @@ const config: Config = {
     rotation: true,          // use best-guess rotated hand image or just box with rotation as-is
                              // false means higher performance, but incorrect finger mapping if hand is inverted
                              // only valid for `handdetect` variation
-    skipFrames: 2,           // how many max frames to go without re-running the hand bounding box detector
+    skipFrames: 99,          // how many max frames to go without re-running the hand bounding box detector
                              // only used when cacheSensitivity is not zero
     skipTime: 2000,          // how many ms to go without re-running the face bounding box detector
                              // only used when cacheSensitivity is not zero
@@ -450,9 +450,9 @@ const config: Config = {
     minConfidence: 0.2,      // threshold for discarding a prediction
     iouThreshold: 0.4,       // ammount of overlap between two detected objects before one object is removed
     maxDetected: 10,         // maximum number of objects detected in the input
-    skipFrames: 15,          // how many max frames to go without re-running the detector
+    skipFrames: 99,          // how many max frames to go without re-running the detector
                              // only used when cacheSensitivity is not zero
-    skipTime: 2000,          // how many ms to go without re-running the face bounding box detector
+    skipTime: 1000,          // how many ms to go without re-running object detector
                              // only used when cacheSensitivity is not zero
   },
 

src/face/antispoof.ts

@@ -12,7 +12,7 @@ let model: GraphModel | null;
 const cached: Array<number> = [];
 let skipped = Number.MAX_SAFE_INTEGER;
 let lastCount = 0;
-let last = 0;
+let lastTime = 0;
 
 export async function load(config: Config): Promise<GraphModel> {
   if (env.initial) model = null;
@@ -26,7 +26,9 @@ export async function load(config: Config): Promise<GraphModel> {
 
 export async function predict(image: Tensor, config: Config, idx, count) {
   if (!model) return null;
-  if ((skipped < (config.face.antispoof?.skipFrames || 0)) && ((config.face.antispoof?.skipTime || 0) <= (now() - last)) && config.skipFrame && (lastCount === count) && cached[idx]) {
+  const skipTime = (config.face.antispoof?.skipTime || 0) > (now() - lastTime);
+  const skipFrame = skipped < (config.face.antispoof?.skipFrames || 0);
+  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && cached[idx]) {
     skipped++;
     return cached[idx];
   }
@@ -37,7 +39,7 @@ export async function predict(image: Tensor, config: Config, idx, count) {
     const num = (await res.data())[0];
     cached[idx] = Math.round(100 * num) / 100;
     lastCount = count;
-    last = now();
+    lastTime = now();
     tf.dispose([resize, res]);
     resolve(cached[idx]);
   });

src/face/face.ts

@@ -4,6 +4,7 @@
  */
 
 import { log, now } from '../util/util';
+import { env } from '../util/env';
 import * as tf from '../../dist/tfjs.esm.js';
 import * as facemesh from './facemesh';
 import * as emotion from '../gear/emotion';
@@ -29,7 +30,7 @@ export const detectFace = async (parent /* instance of human */, input: Tensor):
   timeStamp = now();
 
   const faces = await facemesh.predict(input, parent.config);
-  parent.performance.face = Math.trunc(now() - timeStamp);
+  parent.performance.face = env.perfadd ? (parent.performance.face || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
   if (!input.shape || input.shape.length !== 4) return [];
   if (!faces) return [];
   // for (const face of faces) {
@@ -53,7 +54,7 @@ export const detectFace = async (parent /* instance of human */, input: Tensor):
       parent.state = 'run:emotion';
       timeStamp = now();
       emotionRes = parent.config.face.emotion.enabled ? await emotion.predict(faces[i].tensor || tf.tensor([]), parent.config, i, faces.length) : null;
-      parent.performance.emotion = Math.trunc(now() - timeStamp);
+      parent.performance.emotion = env.perfadd ? (parent.performance.emotion || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     parent.analyze('End Emotion:');
 
@@ -65,7 +66,7 @@ export const detectFace = async (parent /* instance of human */, input: Tensor):
       parent.state = 'run:antispoof';
       timeStamp = now();
       antispoofRes = parent.config.face.antispoof.enabled ? await antispoof.predict(faces[i].tensor || tf.tensor([]), parent.config, i, faces.length) : null;
-      parent.performance.antispoof = Math.trunc(now() - timeStamp);
+      parent.performance.antispoof = env.perfadd ? (parent.performance.antispoof || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     parent.analyze('End AntiSpoof:');
 
@@ -91,7 +92,7 @@ export const detectFace = async (parent /* instance of human */, input: Tensor):
       parent.state = 'run:description';
       timeStamp = now();
       descRes = parent.config.face.description.enabled ? await faceres.predict(faces[i].tensor || tf.tensor([]), parent.config, i, faces.length) : null;
-      parent.performance.embedding = Math.trunc(now() - timeStamp);
+      parent.performance.embedding = env.perfadd ? (parent.performance.embedding || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
     }
     parent.analyze('End Description:');
 

src/face/facemesh.ts

@@ -28,7 +28,10 @@ let detectedFaces = 0;
 
 export async function predict(input: Tensor, config: Config): Promise<FaceResult[]> {
   // reset cached boxes
-  if (!config.skipFrame || (((detectedFaces !== config.face.detector?.maxDetected) || !config.face.mesh?.enabled)) && (skipped > (config.face.detector?.skipFrames || 0) && ((config.face.description?.skipTime || 0) <= (now() - lastTime)))) {
+
+  const skipTime = (config.face.detector?.skipTime || 0) > (now() - lastTime);
+  const skipFrame = skipped < (config.face.detector?.skipFrames || 0);
+  if (!config.skipAllowed || !skipTime || !skipFrame || detectedFaces === 0) {
     const newBoxes = await blazeface.getBoxes(input, config); // get results from blazeface detector
     lastTime = now();
     boxCache = []; // empty cache

src/face/faceres.ts

@@ -91,7 +91,9 @@ export function enhance(input): Tensor {
 
 export async function predict(image: Tensor, config: Config, idx, count) {
   if (!model) return null;
-  if ((skipped < (config.face.description?.skipFrames || 0)) && ((config.face.description?.skipTime || 0) <= (now() - lastTime)) && config.skipFrame && (lastCount === count) && last[idx]?.age && (last[idx]?.age > 0)) {
+  const skipFrame = skipped < (config.face.description?.skipFrames || 0);
+  const skipTime = (config.face.description?.skipTime || 0) > (now() - lastTime);
+  if (config.skipAllowed && skipFrame && skipTime && (lastCount === count) && last[idx]?.age && (last[idx]?.age > 0)) {
     skipped++;
     return last[idx];
   }

src/gear/emotion.ts

@@ -33,7 +33,9 @@ export async function load(config: Config): Promise<GraphModel> {
 
 export async function predict(image: Tensor, config: Config, idx, count) {
   if (!model) return null;
-  if ((skipped < (config.face.emotion?.skipFrames || 0)) && ((config.face.emotion?.skipTime || 0) <= (now() - lastTime)) && config.skipFrame && (lastCount === count) && last[idx] && (last[idx].length > 0)) {
+  const skipFrame = skipped < (config.face.emotion?.skipFrames || 0);
+  const skipTime = (config.face.emotion?.skipTime || 0) > (now() - lastTime);
+  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && last[idx] && (last[idx].length > 0)) {
     skipped++;
     return last[idx];
   }

src/gear/gear-agegenderrace.ts

@@ -34,7 +34,11 @@ export async function load(config: Config | any) {
 export async function predict(image: Tensor, config: Config) {
   if (!model) return null;
   // @ts-ignore config disabled
-  if ((skipped < config.face.agegenderrace?.skipFrames) && ((config.face.agegenderrace?.skipTime || 0) <= (now() - lastTime)) && config.skipFrame && last.age && (last.age > 0)) {
+  const skipFrame = skipped < (config.face.agegenderrace?.skipFrames || 0);
+  // @ts-ignore config disabled
+  const skipTime = (config.face.agegenderrace?.skipTime || 0) > (now() - lastTime);
+  // @ts-ignore config disabled
+  if (config.skipAllowed && skipTime && skipFrame && last.age && (last.age > 0)) {
     skipped++;
     return last;
   }

src/gear/ssrnet-age.ts

@@ -33,7 +33,9 @@ export async function load(config: Config | any) {
 // eslint-disable-next-line @typescript-eslint/no-explicit-any
 export async function predict(image: Tensor, config: Config | any) {
   if (!model) return null;
-  if ((skipped < config.face.age.skipFrames) && ((config.face.age.skipTime || 0) <= (now() - lastTime)) && config.skipFrame && last.age && (last.age > 0)) {
+  const skipTime = (config.face.age?.skipTime || 0) > (now() - lastTime);
+  const skipFrame = skipped < (config.face.age?.skipFrames || 0);
+  if (config.skipAllowed && skipTime && skipFrame && last.age && (last.age > 0)) {
     skipped++;
     return last;
   }

src/gear/ssrnet-gender.ts

@@ -36,7 +36,9 @@ export async function load(config: Config | any) {
 // eslint-disable-next-line @typescript-eslint/no-explicit-any
 export async function predict(image: Tensor, config: Config | any) {
   if (!model) return null;
-  if ((skipped < config.face.gender.skipFrames) && ((config.face.gender.skipTime || 0) <= (now() - lastTime)) && config.skipFrame && last.gender !== '') {
+  const skipTime = (config.face.gender?.skipTime || 0) > (now() - lastTime);
+  const skipFrame = skipped < (config.face.gender?.skipFrames || 0);
+  if (config.skipAllowed && skipTime && skipFrame && last.gender !== '') {
     skipped++;
     return last;
   }

src/hand/handposepipeline.ts

@@ -30,7 +30,7 @@ export class HandPipeline {
     this.handPoseModel = handPoseModel;
     this.inputSize = this.handPoseModel && this.handPoseModel.inputs[0].shape ? this.handPoseModel.inputs[0].shape[2] : 0;
     this.storedBoxes = [];
-    this.skipped = 0;
+    this.skipped = Number.MAX_SAFE_INTEGER;
     this.detectedHands = 0;
   }
 
@@ -88,15 +88,15 @@ export class HandPipeline {
   async estimateHands(image, config) {
     let useFreshBox = false;
 
-    // run new detector every skipFrames unless we only want box to start with
+    // run new detector every skipFrames
     let boxes;
-
-    // console.log('handpipeline:estimateHands:skip criteria', this.skipped, config.hand.skipFrames, !config.hand.landmarks, !config.skipFrame); // should skip hand detector?
-    if ((this.skipped === 0) || ((this.skipped > config.hand.skipFrames) && ((config.hand.skipTime || 0) <= (now() - lastTime))) || !config.hand.landmarks || !config.skipFrame) {
+    const skipTime = (config.hand.skipTime || 0) > (now() - lastTime);
+    const skipFrame = this.skipped < (config.hand.skipFrames || 0);
+    if (config.skipAllowed && skipTime && skipFrame) {
       boxes = await this.handDetector.estimateHandBounds(image, config);
       this.skipped = 0;
     }
-    if (config.skipFrame) this.skipped++;
+    if (config.skipAllowed) this.skipped++;
 
     // if detector result count doesn't match current working set, use it to reset current working set
     if (boxes && (boxes.length > 0) && ((boxes.length !== this.detectedHands) && (this.detectedHands !== config.hand.maxDetected) || !config.hand.landmarks)) {

src/hand/handtrack.ts

@@ -28,7 +28,7 @@ const boxExpandFact = 1.6;
 const maxDetectorResolution = 512;
 const detectorExpandFact = 1.4;
 
-let skipped = 0;
+let skipped = Number.MAX_SAFE_INTEGER;
 let lastTime = 0;
 let outputSize: [number, number] = [0, 0];
 
@@ -183,23 +183,20 @@ async function detectFingers(input: Tensor, h: HandDetectResult, config: Config)
 }
 
 export async function predict(input: Tensor, config: Config): Promise<HandResult[]> {
-  /** handtrack caching
-   * 1. if skipFrame returned cached
-   * 2. if any cached results but although not sure if its enough we continute anyhow for 3x skipframes
-   * 3. if not skipframe or eventually rerun detector to generated new cached boxes and reset skipped
-   * 4. generate cached boxes based on detected keypoints
-   */
   if (!models[0] || !models[1] || !models[0]?.inputs[0].shape || !models[1]?.inputs[0].shape) return []; // something is wrong with the model
   outputSize = [input.shape[2] || 0, input.shape[1] || 0];
-
   skipped++; // increment skip frames
-  if (config.skipFrame && (skipped <= (config.hand.skipFrames || 0)) && ((config.hand.skipTime || 0) <= (now() - lastTime))) {
+  const skipTime = (config.hand.skipTime || 0) > (now() - lastTime);
+  const skipFrame = skipped < (config.hand.skipFrames || 0);
+  if (config.skipAllowed && skipTime && skipFrame) {
     return cache.hands; // return cached results without running anything
   }
   return new Promise(async (resolve) => {
-    if (config.skipFrame && cache.hands.length === config.hand.maxDetected) { // we have all detected hands
+    const skipTimeExtended = 3 * (config.hand.skipTime || 0) > (now() - lastTime);
+    const skipFrameExtended = skipped < 3 * (config.hand.skipFrames || 0);
+    if (config.skipAllowed && cache.hands.length === config.hand.maxDetected) { // we have all detected hands so we're definitely skipping
       cache.hands = await Promise.all(cache.boxes.map((handBox) => detectFingers(input, handBox, config)));
-    } else if (config.skipFrame && skipped < 3 * (config.hand.skipFrames || 0) && ((config.hand.skipTime || 0) <= 3 * (now() - lastTime)) && cache.hands.length > 0) { // we have some cached results: maybe not enough but anyhow continue for bit longer
+    } else if (config.skipAllowed && skipTimeExtended && skipFrameExtended && cache.hands.length > 0) { // we have some cached results: maybe not enough but anyhow continue for bit longer
       cache.hands = await Promise.all(cache.boxes.map((handBox) => detectFingers(input, handBox, config)));
     } else { // finally rerun detector
       cache.boxes = await detectHands(input, config);

src/human.ts

@@ -326,7 +326,7 @@ export class Human {
     const count = Object.values(this.models).filter((model) => model).length;
     if (userConfig) this.config = mergeDeep(this.config, userConfig) as Config;
 
-    if (env.initial) { // print version info on first run and check for correct backend setup
+    if (this.env.initial) { // print version info on first run and check for correct backend setup
       if (this.config.debug) log(`version: ${this.version}`);
       if (this.config.debug) log(`tfjs version: ${this.tf.version_core}`);
       if (!await backend.check(this)) log('error: backend check failed');
@@ -338,8 +338,8 @@ export class Human {
     }
 
     await models.load(this); // actually loads models
-    if (env.initial && this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors'); // print memory stats on first run
-    env.initial = false;
+    if (this.env.initial && this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors'); // print memory stats on first run
+    this.env.initial = false;
 
     const loaded = Object.values(this.models).filter((model) => model).length;
     if (loaded !== count) { // number of loaded models changed
@@ -348,7 +348,7 @@ export class Human {
     }
 
     const current = Math.trunc(now() - timeStamp);
-    if (current > (this.performance.load as number || 0)) this.performance.load = current;
+    if (current > (this.performance.load as number || 0)) this.performance.load = this.env.perfadd ? (this.performance.load || 0) + current : current;
   }
 
   // emit event
@@ -393,7 +393,6 @@ export class Human {
     return new Promise(async (resolve) => {
       this.state = 'config';
       let timeStamp;
-      let elapsedTime;
 
       // update configuration
       this.config = mergeDeep(this.config, userConfig) as Config;
@@ -418,7 +417,7 @@ export class Human {
       this.state = 'image';
       const img = image.process(input, this.config) as { canvas: HTMLCanvasElement | OffscreenCanvas, tensor: Tensor };
       this.process = img;
-      this.performance.image = Math.trunc(now() - timeStamp);
+      this.performance.image = this.env.perfadd ? (this.performance.image || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       this.analyze('Get Image:');
 
       if (!img.tensor) {
@@ -429,12 +428,12 @@ export class Human {
       this.emit('image');
 
       timeStamp = now();
-      this.config.skipFrame = await image.skip(this.config, img.tensor);
+      this.config.skipAllowed = await image.skip(this.config, img.tensor);
       if (!this.performance.frames) this.performance.frames = 0;
       if (!this.performance.cached) this.performance.cached = 0;
       (this.performance.frames as number)++;
-      if (this.config.skipFrame) this.performance.cached++;
-      this.performance.changed = Math.trunc(now() - timeStamp);
+      if (this.config.skipAllowed) this.performance.cached++;
+      this.performance.changed = this.env.perfadd ? (this.performance.changed || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       this.analyze('Check Changed:');
 
       // prepare where to store model results
@@ -452,8 +451,7 @@ export class Human {
       } else {
         timeStamp = now();
         faceRes = this.config.face.enabled ? await face.detectFace(this, img.tensor) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0) this.performance.face = elapsedTime;
+        this.performance.face = this.env.perfadd ? (this.performance.face || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
 
       if (this.config.async && (this.config.body.maxDetected === -1 || this.config.hand.maxDetected === -1)) faceRes = await faceRes; // need face result for auto-detect number of hands or bodies
@@ -474,8 +472,7 @@ export class Human {
         else if (this.config.body.modelPath?.includes('blazepose')) bodyRes = this.config.body.enabled ? await blazepose.predict(img.tensor, bodyConfig) : [];
         else if (this.config.body.modelPath?.includes('efficientpose')) bodyRes = this.config.body.enabled ? await efficientpose.predict(img.tensor, bodyConfig) : [];
         else if (this.config.body.modelPath?.includes('movenet')) bodyRes = this.config.body.enabled ? await movenet.predict(img.tensor, bodyConfig) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0) this.performance.body = elapsedTime;
+        this.performance.body = this.env.perfadd ? (this.performance.body || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       this.analyze('End Body:');
 
@@ -491,8 +488,7 @@ export class Human {
         timeStamp = now();
         if (this.config.hand.detector?.modelPath?.includes('handdetect')) handRes = this.config.hand.enabled ? await handpose.predict(img.tensor, handConfig) : [];
         else if (this.config.hand.detector?.modelPath?.includes('handtrack')) handRes = this.config.hand.enabled ? await handtrack.predict(img.tensor, handConfig) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0) this.performance.hand = elapsedTime;
+        this.performance.hand = this.env.perfadd ? (this.performance.hand || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       this.analyze('End Hand:');
 
@@ -507,8 +503,7 @@ export class Human {
         timeStamp = now();
         if (this.config.object.modelPath?.includes('nanodet')) objectRes = this.config.object.enabled ? await nanodet.predict(img.tensor, this.config) : [];
         else if (this.config.object.modelPath?.includes('centernet')) objectRes = this.config.object.enabled ? await centernet.predict(img.tensor, this.config) : [];
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0) this.performance.object = elapsedTime;
+        this.performance.object = this.env.perfadd ? (this.performance.object || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
       }
       this.analyze('End Object:');
 
@@ -522,7 +517,7 @@ export class Human {
       if (this.config.gesture.enabled) {
         timeStamp = now();
         gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];
-        if (!this.config.async) this.performance.gesture = Math.trunc(now() - timeStamp);
+        if (!this.config.async) this.performance.gesture = this.env.perfadd ? (this.performance.gesture || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
         else if (this.performance.gesture) delete this.performance.gesture;
       }
 

src/object/centernet.ts

@@ -79,7 +79,9 @@ async function process(res: Tensor | null, outputShape, config: Config) {
 }
 
 export async function predict(input: Tensor, config: Config): Promise<ObjectResult[]> {
-  if ((skipped < (config.object.skipFrames || 0)) && ((config.object.skipTime || 0) <= (now() - lastTime)) && config.skipFrame && (last.length > 0)) {
+  const skipTime = (config.object.skipTime || 0) > (now() - lastTime);
+  const skipFrame = skipped < (config.object.skipFrames || 0);
+  if (config.skipAllowed && skipTime && skipFrame && (last.length > 0)) {
     skipped++;
     return last;
   }

src/object/nanodet.ts

@@ -107,7 +107,9 @@ async function process(res, inputSize, outputShape, config) {
 }
 
 export async function predict(image: Tensor, config: Config): Promise<ObjectResult[]> {
-  if ((skipped < (config.object.skipFrames || 0)) && ((config.object.skipTime || 0) <= (now() - lastTime)) && config.skipFrame && (last.length > 0)) {
+  const skipTime = (config.object.skipTime || 0) > (now() - lastTime);
+  const skipFrame = skipped < (config.object.skipFrames || 0);
+  if (config.skipAllowed && skipTime && skipFrame && (last.length > 0)) {
     skipped++;
     return last;
   }

src/result.ts

@@ -194,7 +194,7 @@ export interface Result {
   /** {@link ObjectResult}: detection & analysis results */
   object: Array<ObjectResult>
   /** global performance object with timing values for each operation */
-  performance: Record<string, unknown>,
+  performance: Record<string, number>,
   /** optional processed canvas that can be used to draw input on screen */
   canvas?: OffscreenCanvas | HTMLCanvasElement | null | undefined,
   /** timestamp of detection representing the milliseconds elapsed since the UNIX epoch */

src/util/draw.ts

@@ -4,6 +4,7 @@
 
 import { TRI468 as triangulation } from '../face/facemeshcoords';
 import { mergeDeep, now } from './util';
+import { env } from './env';
 import type { Result, FaceResult, BodyResult, HandResult, ObjectResult, GestureResult, PersonResult, Point } from '../result';
 
 /**
@@ -479,7 +480,7 @@ export async function canvas(input: HTMLCanvasElement | OffscreenCanvas | HTMLIm
 
 export async function all(inCanvas: HTMLCanvasElement | OffscreenCanvas, result: Result, drawOptions?: Partial<DrawOptions>) {
   if (!result || !result.performance || !result || !inCanvas) return null;
-  const timestamp = now();
+  const timeStamp = now();
   const localOptions = mergeDeep(options, drawOptions);
   const promise = Promise.all([
     face(inCanvas, result.face, localOptions),
@@ -489,6 +490,6 @@ export async function all(inCanvas: HTMLCanvasElement | OffscreenCanvas, result:
     gesture(inCanvas, result.gesture, localOptions), // gestures do not have buffering
     // person(inCanvas, result.persons, localOptions); // already included above
   ]);
-  result.performance.draw = Math.trunc(now() - timestamp);
+  result.performance.draw = env.perfadd ? (result.performance.draw as number || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
   return promise;
 }

src/util/env.ts

@@ -25,6 +25,8 @@ export class Env {
   };
   /** Is offscreenCanvas supported? */
   offscreen: undefined | boolean;
+  /** Are performance counter instant values or additive */
+  perfadd: boolean = false;
   /** WASM detected capabilities */
   wasm: {
     supported: undefined | boolean,

test/build.log

@@ -1,26 +1,26 @@
-2021-10-22 20:12:29 INFO:  @vladmandic/human version 2.4.0 
-2021-10-22 20:12:29 INFO:  User: vlado Platform: linux Arch: x64 Node: v16.10.0 
-2021-10-22 20:12:29 INFO:  Application: {"name":"@vladmandic/human","version":"2.4.0"} 
-2021-10-22 20:12:29 INFO:  Environment: {"profile":"production","config":".build.json","package":"package.json","tsconfig":true,"eslintrc":true,"git":true} 
-2021-10-22 20:12:29 INFO:  Toolchain: {"build":"0.6.2","esbuild":"0.13.8","typescript":"4.4.4","typedoc":"0.22.6","eslint":"8.0.1"} 
-2021-10-22 20:12:29 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]} 
-2021-10-22 20:12:29 STATE: Clean: {"locations":["dist/*","types/*","typedoc/*"]} 
-2021-10-22 20:12:29 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":1275} 
-2021-10-22 20:12:29 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":54,"inputBytes":525194,"outputBytes":437512} 
-2021-10-22 20:12:29 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":1283} 
-2021-10-22 20:12:29 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":54,"inputBytes":525202,"outputBytes":437516} 
-2021-10-22 20:12:29 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":1350} 
-2021-10-22 20:12:29 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":54,"inputBytes":525269,"outputBytes":437588} 
-2021-10-22 20:12:29 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":1652} 
-2021-10-22 20:12:29 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":2323,"outputBytes":973} 
-2021-10-22 20:12:29 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":54,"inputBytes":524892,"outputBytes":439413} 
-2021-10-22 20:12:29 STATE: Compile: {"name":"tfjs/browser/esm/custom","format":"esm","platform":"browser","input":"tfjs/tf-custom.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":2572202,"outputBytes":2491625} 
-2021-10-22 20:12:30 STATE: Compile: {"name":"human/browser/esm/custom","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.custom.esm.js","files":54,"inputBytes":3015544,"outputBytes":1606543} 
-2021-10-22 20:12:31 STATE: Compile: {"name":"tfjs/browser/esm/bundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":8,"inputBytes":2323,"outputBytes":1155160} 
-2021-10-22 20:12:31 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":54,"inputBytes":1679079,"outputBytes":1430229} 
-2021-10-22 20:12:32 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":54,"inputBytes":1679079,"outputBytes":1878008} 
-2021-10-22 20:12:50 STATE: Typings: {"input":"src/human.ts","output":"types","files":16} 
-2021-10-22 20:12:57 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":37,"generated":true} 
-2021-10-22 20:13:38 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":89,"errors":0,"warnings":0} 
-2021-10-22 20:13:39 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"} 
-2021-10-22 20:13:39 INFO:  Done... 
+2021-10-23 09:35:22 INFO:  @vladmandic/human version 2.4.0 
+2021-10-23 09:35:22 INFO:  User: vlado Platform: linux Arch: x64 Node: v16.10.0 
+2021-10-23 09:35:22 INFO:  Application: {"name":"@vladmandic/human","version":"2.4.0"} 
+2021-10-23 09:35:22 INFO:  Environment: {"profile":"production","config":".build.json","package":"package.json","tsconfig":true,"eslintrc":true,"git":true} 
+2021-10-23 09:35:22 INFO:  Toolchain: {"build":"0.6.2","esbuild":"0.13.8","typescript":"4.4.4","typedoc":"0.22.6","eslint":"8.0.1"} 
+2021-10-23 09:35:22 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]} 
+2021-10-23 09:35:22 STATE: Clean: {"locations":["dist/*","types/*","typedoc/*"]} 
+2021-10-23 09:35:22 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":1275} 
+2021-10-23 09:35:22 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":54,"inputBytes":526471,"outputBytes":438971} 
+2021-10-23 09:35:22 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":1283} 
+2021-10-23 09:35:22 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":54,"inputBytes":526479,"outputBytes":438975} 
+2021-10-23 09:35:22 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":1350} 
+2021-10-23 09:35:22 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":54,"inputBytes":526546,"outputBytes":439047} 
+2021-10-23 09:35:22 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":1652} 
+2021-10-23 09:35:22 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":2323,"outputBytes":973} 
+2021-10-23 09:35:22 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":54,"inputBytes":526169,"outputBytes":440872} 
+2021-10-23 09:35:23 STATE: Compile: {"name":"tfjs/browser/esm/custom","format":"esm","platform":"browser","input":"tfjs/tf-custom.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":2572202,"outputBytes":2491625} 
+2021-10-23 09:35:23 STATE: Compile: {"name":"human/browser/esm/custom","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.custom.esm.js","files":54,"inputBytes":3016821,"outputBytes":1607405} 
+2021-10-23 09:35:24 STATE: Compile: {"name":"tfjs/browser/esm/bundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":8,"inputBytes":2323,"outputBytes":1155160} 
+2021-10-23 09:35:24 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":54,"inputBytes":1680356,"outputBytes":1431091} 
+2021-10-23 09:35:25 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":54,"inputBytes":1680356,"outputBytes":1879461} 
+2021-10-23 09:35:44 STATE: Typings: {"input":"src/human.ts","output":"types","files":16} 
+2021-10-23 09:35:50 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":37,"generated":true} 
+2021-10-23 09:36:28 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":89,"errors":0,"warnings":0} 
+2021-10-23 09:36:28 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"} 
+2021-10-23 09:36:28 INFO:  Done... 

typedoc/interfaces/Config.html

@@ -1,7 +1,7 @@
 <!DOCTYPE html><html class="default no-js"><head><meta charSet="utf-8"/><meta http-equiv="x-ua-compatible" content="IE=edge"/><title>Config | @vladmandic/human - v2.4.0</title><meta name="description" content="Documentation for @vladmandic/human - v2.4.0"/><meta name="viewport" content="width=device-width, initial-scale=1"/><link rel="stylesheet" href="../assets/style.css"/><link rel="stylesheet" href="../assets/highlight.css"/><script async src="../assets/search.js" id="search-script"></script></head><body><script>document.body.classList.add(localStorage.getItem(&quot;tsd-theme&quot;) || &quot;os&quot;)</script><header><div class="tsd-page-toolbar"><div class="container"><div class="table-wrap"><div class="table-cell" id="tsd-search" data-base=".."><div class="field"><label for="tsd-search-field" class="tsd-widget search no-caption">Search</label><input type="text" id="tsd-search-field"/></div><ul class="results"><li class="state loading">Preparing search index...</li><li class="state failure">The search index is not available</li></ul><a href="../index.html" class="title">@vladmandic/human - v2.4.0</a></div><div class="table-cell" id="tsd-widgets"><div id="tsd-filter"><a href="#" class="tsd-widget options no-caption" data-toggle="options">Options</a><div class="tsd-filter-group"><div class="tsd-select" id="tsd-filter-visibility"><span class="tsd-select-label">All</span><ul class="tsd-select-list"><li data-value="public">Public</li><li data-value="protected">Public/Protected</li><li data-value="private" class="selected">All</li></ul></div> <input type="checkbox" id="tsd-filter-inherited" checked/><label class="tsd-widget" for="tsd-filter-inherited">Inherited</label></div></div><a href="#" class="tsd-widget menu no-caption" data-toggle="menu">Menu</a></div></div></div></div><div class="tsd-page-title"><div class="container"><ul class="tsd-breadcrumb"><li><a href="../index.html">@vladmandic/human - v2.4.0</a></li><li><a href="Config.html">Config</a></li></ul><h1>Interface Config</h1></div></div></header><div class="container container-main"><div class="row"><div class="col-8 col-content"><section class="tsd-panel tsd-comment"><div class="tsd-comment tsd-typography"><div class="lead">
 <p>Configuration interface definition for <strong>Human</strong> library</p>
 </div><div><p>Contains all configurable parameters</p>
-</div></div></section><section class="tsd-panel tsd-hierarchy"><h3>Hierarchy</h3><ul class="tsd-hierarchy"><li><span class="target">Config</span></li></ul></section><section class="tsd-panel-group tsd-index-group"><h2>Index</h2><section class="tsd-panel tsd-index-panel"><div class="tsd-index-content"><section class="tsd-index-section "><h3>Properties</h3><ul class="tsd-index-list"><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#async" class="tsd-kind-icon">async</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#backend" class="tsd-kind-icon">backend</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#body" class="tsd-kind-icon">body</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#cacheSensitivity" class="tsd-kind-icon">cache<wbr/>Sensitivity</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#debug" class="tsd-kind-icon">debug</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#face" class="tsd-kind-icon">face</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#filter" class="tsd-kind-icon">filter</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#gesture" class="tsd-kind-icon">gesture</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#hand" class="tsd-kind-icon">hand</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#modelBasePath" class="tsd-kind-icon">model<wbr/>Base<wbr/>Path</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#object" class="tsd-kind-icon">object</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#segmentation" class="tsd-kind-icon">segmentation</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#skipFrame" class="tsd-kind-icon">skip<wbr/>Frame</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#warmup" class="tsd-kind-icon">warmup</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#wasmPath" class="tsd-kind-icon">wasm<wbr/>Path</a></li></ul></section></div></section></section><section class="tsd-panel-group tsd-member-group "><h2>Properties</h2><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="async" class="tsd-anchor"></a><h3>async</h3><div class="tsd-signature tsd-kind-icon">async<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L238">config.ts:238</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
+</div></div></section><section class="tsd-panel tsd-hierarchy"><h3>Hierarchy</h3><ul class="tsd-hierarchy"><li><span class="target">Config</span></li></ul></section><section class="tsd-panel-group tsd-index-group"><h2>Index</h2><section class="tsd-panel tsd-index-panel"><div class="tsd-index-content"><section class="tsd-index-section "><h3>Properties</h3><ul class="tsd-index-list"><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#async" class="tsd-kind-icon">async</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#backend" class="tsd-kind-icon">backend</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#body" class="tsd-kind-icon">body</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#cacheSensitivity" class="tsd-kind-icon">cache<wbr/>Sensitivity</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#debug" class="tsd-kind-icon">debug</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#face" class="tsd-kind-icon">face</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#filter" class="tsd-kind-icon">filter</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#gesture" class="tsd-kind-icon">gesture</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#hand" class="tsd-kind-icon">hand</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#modelBasePath" class="tsd-kind-icon">model<wbr/>Base<wbr/>Path</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#object" class="tsd-kind-icon">object</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#segmentation" class="tsd-kind-icon">segmentation</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#skipAllowed" class="tsd-kind-icon">skip<wbr/>Allowed</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#warmup" class="tsd-kind-icon">warmup</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#wasmPath" class="tsd-kind-icon">wasm<wbr/>Path</a></li></ul></section></div></section></section><section class="tsd-panel-group tsd-member-group "><h2>Properties</h2><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="async" class="tsd-anchor"></a><h3>async</h3><div class="tsd-signature tsd-kind-icon">async<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L238">config.ts:238</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
 <p>Perform model loading and inference concurrently or sequentially</p>
 </div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="backend" class="tsd-anchor"></a><h3>backend</h3><div class="tsd-signature tsd-kind-icon">backend<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">&quot;&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;cpu&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;wasm&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;webgl&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;humangl&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;tensorflow&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;webgpu&quot;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L226">config.ts:226</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
 <p>Backend used for TFJS operations
@@ -46,7 +46,7 @@ Valid build-in backends are:</p>
 <p><a href="ObjectConfig.html">ObjectConfig</a></p>
 </div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="segmentation" class="tsd-anchor"></a><h3>segmentation</h3><div class="tsd-signature tsd-kind-icon">segmentation<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="SegmentationConfig.html" class="tsd-signature-type" data-tsd-kind="Interface">SegmentationConfig</a><span class="tsd-signature-symbol">&gt;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L283">config.ts:283</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
 <p><a href="SegmentationConfig.html">SegmentationConfig</a></p>
-</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="skipFrame" class="tsd-anchor"></a><h3>skip<wbr/>Frame</h3><div class="tsd-signature tsd-kind-icon">skip<wbr/>Frame<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L258">config.ts:258</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
+</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="skipAllowed" class="tsd-anchor"></a><h3>skip<wbr/>Allowed</h3><div class="tsd-signature tsd-kind-icon">skip<wbr/>Allowed<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">boolean</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L258">config.ts:258</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
 <p>Internal Variable</p>
 </div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="warmup" class="tsd-anchor"></a><h3>warmup</h3><div class="tsd-signature tsd-kind-icon">warmup<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">&quot;face&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;body&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;none&quot;</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">&quot;full&quot;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/config.ts#L243">config.ts:243</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
 <p>What to use for <code>human.warmup()</code></p>
@@ -58,4 +58,4 @@ Valid build-in backends are:</p>
 <ul>
 <li>if not set, auto-detects to link to CDN <code>jsdelivr</code> when running in browser</li>
 </ul>
-</div></div></section></section></div><div class="col-4 col-menu menu-sticky-wrap menu-highlight"><nav class="tsd-navigation primary"><ul><li class=""><a href="../index.html">Exports</a></li></ul></nav><nav class="tsd-navigation secondary menu-sticky"><ul><li class="current tsd-kind-interface"><a href="Config.html" class="tsd-kind-icon">Config</a><ul><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#async" class="tsd-kind-icon">async</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#backend" class="tsd-kind-icon">backend</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#body" class="tsd-kind-icon">body</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#cacheSensitivity" class="tsd-kind-icon">cache<wbr/>Sensitivity</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#debug" class="tsd-kind-icon">debug</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#face" class="tsd-kind-icon">face</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#filter" class="tsd-kind-icon">filter</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#gesture" class="tsd-kind-icon">gesture</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#hand" class="tsd-kind-icon">hand</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#modelBasePath" class="tsd-kind-icon">model<wbr/>Base<wbr/>Path</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#object" class="tsd-kind-icon">object</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#segmentation" class="tsd-kind-icon">segmentation</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#skipFrame" class="tsd-kind-icon">skip<wbr/>Frame</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#warmup" class="tsd-kind-icon">warmup</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#wasmPath" class="tsd-kind-icon">wasm<wbr/>Path</a></li></ul></li></ul></nav></div></div></div><footer class=""><div class="container"><h2>Legend</h2><div class="tsd-legend-group"><ul class="tsd-legend"><li class="tsd-kind-constructor tsd-parent-kind-class"><span class="tsd-kind-icon">Constructor</span></li><li class="tsd-kind-property tsd-parent-kind-class"><span class="tsd-kind-icon">Property</span></li><li class="tsd-kind-method tsd-parent-kind-class"><span class="tsd-kind-icon">Method</span></li></ul><ul class="tsd-legend"><li class="tsd-kind-property tsd-parent-kind-interface"><span class="tsd-kind-icon">Property</span></li></ul></div><h2>Settings</h2><p>Theme <select id="theme"><option value="os">OS</option><option value="light">Light</option><option value="dark">Dark</option></select></p></div></footer><div class="overlay"></div><script src="../assets/main.js"></script></body></html>
+</div></div></section></section></div><div class="col-4 col-menu menu-sticky-wrap menu-highlight"><nav class="tsd-navigation primary"><ul><li class=""><a href="../index.html">Exports</a></li></ul></nav><nav class="tsd-navigation secondary menu-sticky"><ul><li class="current tsd-kind-interface"><a href="Config.html" class="tsd-kind-icon">Config</a><ul><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#async" class="tsd-kind-icon">async</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#backend" class="tsd-kind-icon">backend</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#body" class="tsd-kind-icon">body</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#cacheSensitivity" class="tsd-kind-icon">cache<wbr/>Sensitivity</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#debug" class="tsd-kind-icon">debug</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#face" class="tsd-kind-icon">face</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#filter" class="tsd-kind-icon">filter</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#gesture" class="tsd-kind-icon">gesture</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#hand" class="tsd-kind-icon">hand</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#modelBasePath" class="tsd-kind-icon">model<wbr/>Base<wbr/>Path</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#object" class="tsd-kind-icon">object</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#segmentation" class="tsd-kind-icon">segmentation</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#skipAllowed" class="tsd-kind-icon">skip<wbr/>Allowed</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#warmup" class="tsd-kind-icon">warmup</a></li><li class="tsd-kind-property tsd-parent-kind-interface"><a href="Config.html#wasmPath" class="tsd-kind-icon">wasm<wbr/>Path</a></li></ul></li></ul></nav></div></div></div><footer class=""><div class="container"><h2>Legend</h2><div class="tsd-legend-group"><ul class="tsd-legend"><li class="tsd-kind-constructor tsd-parent-kind-class"><span class="tsd-kind-icon">Constructor</span></li><li class="tsd-kind-property tsd-parent-kind-class"><span class="tsd-kind-icon">Property</span></li><li class="tsd-kind-method tsd-parent-kind-class"><span class="tsd-kind-icon">Method</span></li></ul><ul class="tsd-legend"><li class="tsd-kind-property tsd-parent-kind-interface"><span class="tsd-kind-icon">Property</span></li></ul></div><h2>Settings</h2><p>Theme <select id="theme"><option value="os">OS</option><option value="light">Light</option><option value="dark">Dark</option></select></p></div></footer><div class="overlay"></div><script src="../assets/main.js"></script></body></html>

typedoc/interfaces/Result.html

@@ -13,7 +13,7 @@
 <p><a href="HandResult.html">HandResult</a>: detection &amp; analysis results</p>
 </div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="object" class="tsd-anchor"></a><h3>object</h3><div class="tsd-signature tsd-kind-icon">object<span class="tsd-signature-symbol">:</span> <a href="ObjectResult.html" class="tsd-signature-type" data-tsd-kind="Interface">ObjectResult</a><span class="tsd-signature-symbol">[]</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/result.ts#L195">result.ts:195</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
 <p><a href="ObjectResult.html">ObjectResult</a>: detection &amp; analysis results</p>
-</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="performance" class="tsd-anchor"></a><h3>performance</h3><div class="tsd-signature tsd-kind-icon">performance<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Record</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">unknown</span><span class="tsd-signature-symbol">&gt;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/result.ts#L197">result.ts:197</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
+</div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="performance" class="tsd-anchor"></a><h3>performance</h3><div class="tsd-signature tsd-kind-icon">performance<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-type">Record</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">&gt;</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/result.ts#L197">result.ts:197</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
 <p>global performance object with timing values for each operation</p>
 </div></div></section><section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-interface"><a id="persons" class="tsd-anchor"></a><h3>persons</h3><div class="tsd-signature tsd-kind-icon">persons<span class="tsd-signature-symbol">:</span> <a href="PersonResult.html" class="tsd-signature-type" data-tsd-kind="Interface">PersonResult</a><span class="tsd-signature-symbol">[]</span></div><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/result.ts#L203">result.ts:203</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
 <p>getter property that returns unified persons object</p>

types/src/body/blazepose.d.ts.map

@@ -1 +1 @@
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+{"version":3,"file":"blazepose.d.ts","sourceRoot":"","sources":["../../../src/body/blazepose.ts"],"names":[],"mappings":"AAAA;;GAEG;AAIH,OAAO,KAAK,EAAgB,UAAU,EAAc,MAAM,WAAW,CAAC;AACtE,OAAO,KAAK,EAAE,UAAU,EAAE,MAAM,EAAE,MAAM,eAAe,CAAC;AACxD,OAAO,KAAK,EAAE,MAAM,EAAE,MAAM,WAAW,CAAC;AAYxC,wBAAsB,UAAU,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,CAAC,CAWpE;AAED,wBAAsB,QAAQ,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,CAAC,CAalE;AAED,wBAAsB,IAAI,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,CAAC,UAAU,GAAG,IAAI,EAAE,UAAU,GAAG,IAAI,CAAC,CAAC,CAI1F;AAoFD,wBAAsB,OAAO,CAAC,KAAK,EAAE,MAAM,EAAE,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,EAAE,CAAC,CAalF"}

types/src/body/efficientpose.d.ts.map

@@ -1 +1 @@
-{"version":3,"file":"efficientpose.d.ts","sourceRoot":"","sources":["../../../src/body/efficientpose.ts"],"names":[],"mappings":"AAAA;;;;GAIG;AAKH,OAAO,KAAK,EAAE,UAAU,EAAS,MAAM,WAAW,CAAC;AACnD,OAAO,KAAK,EAAE,UAAU,EAAE,MAAM,EAAE,MAAM,eAAe,CAAC;AACxD,OAAO,KAAK,EAAE,MAAM,EAAE,MAAM,WAAW,CAAC;AAaxC,wBAAsB,IAAI,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,CAAC,CAQ9D;AAmBD,wBAAsB,OAAO,CAAC,KAAK,EAAE,MAAM,EAAE,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,EAAE,CAAC,CA4ElF"}
+{"version":3,"file":"efficientpose.d.ts","sourceRoot":"","sources":["../../../src/body/efficientpose.ts"],"names":[],"mappings":"AAAA;;;;GAIG;AAKH,OAAO,KAAK,EAAE,UAAU,EAAS,MAAM,WAAW,CAAC;AACnD,OAAO,KAAK,EAAE,UAAU,EAAE,MAAM,EAAE,MAAM,eAAe,CAAC;AACxD,OAAO,KAAK,EAAE,MAAM,EAAE,MAAM,WAAW,CAAC;AAaxC,wBAAsB,IAAI,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,CAAC,CAQ9D;AAmBD,wBAAsB,OAAO,CAAC,KAAK,EAAE,MAAM,EAAE,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,EAAE,CAAC,CA8ElF"}

types/src/body/movenet.d.ts.map

@@ -1 +1 @@
-{"version":3,"file":"movenet.d.ts","sourceRoot":"","sources":["../../../src/body/movenet.ts"],"names":[],"mappings":"AAAA;;;;GAIG;AAOH,OAAO,KAAK,EAAgB,UAAU,EAAc,MAAM,WAAW,CAAC;AACtE,OAAO,KAAK,EAAE,UAAU,EAAE,MAAM,EAAE,MAAM,eAAe,CAAC;AACxD,OAAO,KAAK,EAAE,MAAM,EAAE,MAAM,WAAW,CAAC;AAmBxC,wBAAsB,IAAI,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,CAAC,CAW9D;AAyFD,wBAAsB,OAAO,CAAC,KAAK,EAAE,MAAM,EAAE,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,EAAE,CAAC,CA2DlF"}
+{"version":3,"file":"movenet.d.ts","sourceRoot":"","sources":["../../../src/body/movenet.ts"],"names":[],"mappings":"AAAA;;;;GAIG;AAOH,OAAO,KAAK,EAAgB,UAAU,EAAc,MAAM,WAAW,CAAC;AACtE,OAAO,KAAK,EAAE,UAAU,EAAE,MAAM,EAAE,MAAM,eAAe,CAAC;AACxD,OAAO,KAAK,EAAE,MAAM,EAAE,MAAM,WAAW,CAAC;AAmBxC,wBAAsB,IAAI,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,CAAC,CAW9D;AAyFD,wBAAsB,OAAO,CAAC,KAAK,EAAE,MAAM,EAAE,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,EAAE,CAAC,CA6DlF"}

types/src/config.d.ts

@@ -229,7 +229,7 @@ export interface Config {
     */
     cacheSensitivity: number;
     /** Internal Variable */
-    skipFrame: boolean;
+    skipAllowed: boolean;
     /** Run input through image filters before inference
      * - image filters run with near-zero latency as they are executed on the GPU
      *

types/src/config.d.ts.map

@@ -1 +1 @@
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types/src/face/antispoof.d.ts.map

@@ -1 +1 @@
-{"version":3,"file":"antispoof.d.ts","sourceRoot":"","sources":["../../../src/face/antispoof.ts"],"names":[],"mappings":"AAAA;;GAEG;AAGH,OAAO,KAAK,EAAE,MAAM,EAAE,MAAM,WAAW,CAAC;AACxC,OAAO,KAAK,EAAE,UAAU,EAAE,MAAM,EAAE,MAAM,eAAe,CAAC;AAUxD,wBAAsB,IAAI,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,CAAC,CAQ9D;AAED,wBAAsB,OAAO,CAAC,KAAK,EAAE,MAAM,EAAE,MAAM,EAAE,MAAM,EAAE,GAAG,KAAA,EAAE,KAAK,KAAA,oBAiBtE"}
+{"version":3,"file":"antispoof.d.ts","sourceRoot":"","sources":["../../../src/face/antispoof.ts"],"names":[],"mappings":"AAAA;;GAEG;AAGH,OAAO,KAAK,EAAE,MAAM,EAAE,MAAM,WAAW,CAAC;AACxC,OAAO,KAAK,EAAE,UAAU,EAAE,MAAM,EAAE,MAAM,eAAe,CAAC;AAUxD,wBAAsB,IAAI,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,CAAC,CAQ9D;AAED,wBAAsB,OAAO,CAAC,KAAK,EAAE,MAAM,EAAE,MAAM,EAAE,MAAM,EAAE,GAAG,KAAA,EAAE,KAAK,KAAA,oBAmBtE"}

types/src/face/face.d.ts.map

@@ -1 +1 @@
-{"version":3,"file":"face.d.ts","sourceRoot":"","sources":["../../../src/face/face.ts"],"names":[],"mappings":"AAAA;;;GAGG;AAQH,OAAO,KAAK,EAAE,UAAU,EAAE,MAAM,WAAW,CAAC;AAC5C,OAAO,KAAK,EAAE,MAAM,EAAE,MAAM,eAAe,CAAC;AAG5C,eAAO,MAAM,UAAU,uBAAiD,MAAM,KAAG,QAAQ,UAAU,EAAE,CAmIpG,CAAC"}
+{"version":3,"file":"face.d.ts","sourceRoot":"","sources":["../../../src/face/face.ts"],"names":[],"mappings":"AAAA;;;GAGG;AASH,OAAO,KAAK,EAAE,UAAU,EAAE,MAAM,WAAW,CAAC;AAC5C,OAAO,KAAK,EAAE,MAAM,EAAE,MAAM,eAAe,CAAC;AAG5C,eAAO,MAAM,UAAU,uBAAiD,MAAM,KAAG,QAAQ,UAAU,EAAE,CAmIpG,CAAC"}

types/src/face/facemesh.d.ts.map

@@ -1 +1 @@
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types/src/face/faceres.d.ts.map

@@ -1 +1 @@
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types/src/gear/emotion.d.ts.map

@@ -1 +1 @@
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types/src/gear/gear-agegenderrace.d.ts.map

@@ -1 +1 @@
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types/src/hand/handtrack.d.ts.map

@@ -1 +1 @@
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types/src/human.d.ts.map

@@ -1 +1 @@
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types/src/object/centernet.d.ts.map

@@ -1 +1 @@
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+{"version":3,"file":"centernet.d.ts","sourceRoot":"","sources":["../../../src/object/centernet.ts"],"names":[],"mappings":"AAAA;;;;GAIG;AAKH,OAAO,KAAK,EAAE,YAAY,EAAO,MAAM,WAAW,CAAC;AACnD,OAAO,KAAK,EAAE,UAAU,EAAE,MAAM,EAAE,MAAM,eAAe,CAAC;AACxD,OAAO,KAAK,EAAE,MAAM,EAAE,MAAM,WAAW,CAAC;AAUxC,wBAAsB,IAAI,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,CAAC,CAW9D;AAgDD,wBAAsB,OAAO,CAAC,KAAK,EAAE,MAAM,EAAE,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,YAAY,EAAE,CAAC,CAqBpF"}

types/src/object/nanodet.d.ts.map

@@ -1 +1 @@
-{"version":3,"file":"nanodet.d.ts","sourceRoot":"","sources":["../../../src/object/nanodet.ts"],"names":[],"mappings":"AAAA;;;;GAIG;AAKH,OAAO,KAAK,EAAE,YAAY,EAAO,MAAM,WAAW,CAAC;AACnD,OAAO,KAAK,EAAE,UAAU,EAAE,MAAM,EAAE,MAAM,eAAe,CAAC;AACxD,OAAO,KAAK,EAAE,MAAM,EAAE,MAAM,WAAW,CAAC;AAUxC,wBAAsB,IAAI,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,CAAC,CAU9D;AA6ED,wBAAsB,OAAO,CAAC,KAAK,EAAE,MAAM,EAAE,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,YAAY,EAAE,CAAC,CAwBpF"}
+{"version":3,"file":"nanodet.d.ts","sourceRoot":"","sources":["../../../src/object/nanodet.ts"],"names":[],"mappings":"AAAA;;;;GAIG;AAKH,OAAO,KAAK,EAAE,YAAY,EAAO,MAAM,WAAW,CAAC;AACnD,OAAO,KAAK,EAAE,UAAU,EAAE,MAAM,EAAE,MAAM,eAAe,CAAC;AACxD,OAAO,KAAK,EAAE,MAAM,EAAE,MAAM,WAAW,CAAC;AAUxC,wBAAsB,IAAI,CAAC,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,UAAU,CAAC,CAU9D;AA6ED,wBAAsB,OAAO,CAAC,KAAK,EAAE,MAAM,EAAE,MAAM,EAAE,MAAM,GAAG,OAAO,CAAC,YAAY,EAAE,CAAC,CA0BpF"}

types/src/result.d.ts

@@ -202,7 +202,7 @@ export interface Result {
     /** {@link ObjectResult}: detection & analysis results */
     object: Array<ObjectResult>;
     /** global performance object with timing values for each operation */
-    performance: Record<string, unknown>;
+    performance: Record<string, number>;
     /** optional processed canvas that can be used to draw input on screen */
     canvas?: OffscreenCanvas | HTMLCanvasElement | null | undefined;
     /** timestamp of detection representing the milliseconds elapsed since the UNIX epoch */

types/src/result.d.ts.map

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types/src/util/draw.d.ts.map

@@ -1 +1 @@
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types/src/util/env.d.ts

@@ -22,6 +22,8 @@ export declare class Env {
     };
     /** Is offscreenCanvas supported? */
     offscreen: undefined | boolean;
+    /** Are performance counter instant values or additive */
+    perfadd: boolean;
     /** WASM detected capabilities */
     wasm: {
         supported: undefined | boolean;

types/src/util/env.d.ts.map

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wiki

@@ -1 +1 @@
-Subproject commit d6c2c8c474f1d55f36e4ab4ffc9a1852f2f2b4fb
+Subproject commit 97e86c65f64df007c25250bcb513d48e5c602242