diff --git a/.eslintrc.json b/.eslintrc.json index 98c719d..bccb07d 100644 --- a/.eslintrc.json +++ b/.eslintrc.json @@ -7,7 +7,7 @@ "es2020": true }, "parser": "@typescript-eslint/parser", - "parserOptions": { "ecmaVersion": 2020 }, + "parserOptions": { "ecmaVersion": "latest" }, "plugins": [ "@typescript-eslint" ], diff --git a/CHANGELOG.md b/CHANGELOG.md index 4066eee..0eb6513 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,6 +1,6 @@ # @vladmandic/face-api - Version: **1.7.1** + Version: **1.7.2** Description: **FaceAPI: AI-powered Face Detection & Rotation Tracking, Face Description & Recognition, Age & Gender & Emotion Prediction for Browser and NodeJS using TensorFlow/JS** Author: **Vladimir Mandic ** @@ -9,7 +9,11 @@ ## Changelog -### **HEAD -> master** 2022/08/22 mandic00@live.com +### **1.7.2** 2022/08/23 mandic00@live.com + +- document and remove optional dependencies + +### **origin/master** 2022/08/22 mandic00@live.com ### **release: 1.7.1** 2022/07/25 mandic00@live.com 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s(m,p,u){let f=e(m,`${u}/depthwise_conv`),l=a(m,p,1,`${u}/pointwise_conv`);return{depthwise_conv:f,pointwise_conv:l}}function i(){let m=a(3,32,3,"mobilenetv1/conv_0"),p=s(32,64,"mobilenetv1/conv_1"),u=s(64,128,"mobilenetv1/conv_2"),f=s(128,128,"mobilenetv1/conv_3"),l=s(128,256,"mobilenetv1/conv_4"),d=s(256,256,"mobilenetv1/conv_5"),g=s(256,512,"mobilenetv1/conv_6"),_=s(512,512,"mobilenetv1/conv_7"),F=s(512,512,"mobilenetv1/conv_8"),h=s(512,512,"mobilenetv1/conv_9"),y=s(512,512,"mobilenetv1/conv_10"),x=s(512,512,"mobilenetv1/conv_11"),D=s(512,1024,"mobilenetv1/conv_12"),N=s(1024,1024,"mobilenetv1/conv_13");return{conv_0:m,conv_1:p,conv_2:u,conv_3:f,conv_4:l,conv_5:d,conv_6:g,conv_7:_,conv_8:F,conv_9:h,conv_10:y,conv_11:x,conv_12:D,conv_13:N}}function c(){let 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u=i(`Prediction/BoxPredictor_${p}/BoxEncodingPredictor`,`prediction_layer/box_predictor_${p}/box_encoding_predictor`),f=i(`Prediction/BoxPredictor_${p}/ClassPredictor`,`prediction_layer/box_predictor_${p}/class_predictor`);return{box_encoding_predictor:u,class_predictor:f}}function m(){return{conv_0:r("Prediction",0,"prediction_layer/conv_0"),conv_1:r("Prediction",1,"prediction_layer/conv_1"),conv_2:r("Prediction",2,"prediction_layer/conv_2"),conv_3:r("Prediction",3,"prediction_layer/conv_3"),conv_4:r("Prediction",4,"prediction_layer/conv_4"),conv_5:r("Prediction",5,"prediction_layer/conv_5"),conv_6:r("Prediction",6,"prediction_layer/conv_6"),conv_7:r("Prediction",7,"prediction_layer/conv_7"),box_predictor_0:c(0),box_predictor_1:c(1),box_predictor_2:c(2),box_predictor_3:c(3),box_predictor_4:c(4),box_predictor_5:c(5)}}return{extractMobilenetV1Params:s,extractPredictionLayerParams:m}}function Jr(o){let t=[],{extractMobilenetV1Params:e,extractPredictionLayerParams:r}=jo(o,t),a=o["Output/extra_dim"];if(t.push({originalPath:"Output/extra_dim",paramPath:"output_layer/extra_dim"}),!K(a))throw new Error(`expected weightMap['Output/extra_dim'] to be a Tensor3D, instead have ${a}`);let s={mobilenetv1:e(),prediction_layer:r(),output_layer:{extra_dim:a}};return L(o,t),{params:s,paramMappings:t}}function H(o,t,e){return n.tidy(()=>{let r=n.conv2d(o,t.filters,e,"same");return r=n.add(r,t.batch_norm_offset),n.clipByValue(r,0,6)})}var Uo=.0010000000474974513;function Xo(o,t,e){return n.tidy(()=>{let r=n.depthwiseConv2d(o,t.filters,e,"same");return r=n.batchNorm(r,t.batch_norm_mean,t.batch_norm_variance,t.batch_norm_offset,t.batch_norm_scale,Uo),n.clipByValue(r,0,6)})}function Jo(o){return[2,4,6,12].some(t=>t===o)?[2,2]:[1,1]}function qr(o,t){return n.tidy(()=>{let 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z=class{constructor({minConfidence:t,maxResults:e}={}){this._name="SsdMobilenetv1Options";if(this._minConfidence=t||.5,this._maxResults=e||100,typeof this._minConfidence!="number"||this._minConfidence<=0||this._minConfidence>=1)throw new Error(`${this._name} - expected minConfidence to be a number between 0 and 1`);if(typeof this._maxResults!="number")throw new Error(`${this._name} - expected maxResults to be a number`)}get minConfidence(){return this._minConfidence}get maxResults(){return this._maxResults}};var Pt=class extends I{constructor(){super("SsdMobilenetv1")}forwardInput(t){let{params:e}=this;if(!e)throw new Error("SsdMobilenetv1 - load model before inference");return n.tidy(()=>{let r=n.cast(t.toBatchTensor(512,!1),"float32"),a=n.sub(n.div(r,127.5),1),s=qr(a,e.mobilenetv1),{boxPredictions:i,classPredictions:c}=Qr(s.out,s.conv11,e.prediction_layer);return Kr(i,c,e.output_layer)})}async forward(t){return this.forwardInput(await M(t))}async 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co(o,t,e,r){let{extractWeights:a,getRemainingWeights:s}=A(o),i=[],{extractConvParams:c,extractConvWithBatchNormParams:m,extractSeparableConvParams:p}=tn(a,i),u;if(t.withSeparableConvs){let[f,l,d,g,_,F,h,y,x]=r,D=t.isFirstLayerConv2d?c(f,l,3,"conv0"):p(f,l,"conv0"),N=p(l,d,"conv1"),Y=p(d,g,"conv2"),q=p(g,_,"conv3"),O=p(_,F,"conv4"),at=p(F,h,"conv5"),st=y?p(h,y,"conv6"):void 0,it=x?p(y,x,"conv7"):void 0,gt=c(x||y||h,5*e,1,"conv8");u={conv0:D,conv1:N,conv2:Y,conv3:q,conv4:O,conv5:at,conv6:st,conv7:it,conv8:gt}}else{let[f,l,d,g,_,F,h,y,x]=r,D=m(f,l,"conv0"),N=m(l,d,"conv1"),Y=m(d,g,"conv2"),q=m(g,_,"conv3"),O=m(_,F,"conv4"),at=m(F,h,"conv5"),st=m(h,y,"conv6"),it=m(y,x,"conv7"),gt=c(x,5*e,1,"conv8");u={conv0:D,conv1:N,conv2:Y,conv3:q,conv4:O,conv5:at,conv6:st,conv7:it,conv8:gt}}if(s().length!==0)throw new Error(`weights remaing after extract: ${s().length}`);return{params:u,paramMappings:i}}function en(o,t){let e=B(o,t);function r(c){let m=e(`${c}/sub`,1),p=e(`${c}/truediv`,1);return{sub:m,truediv:p}}function a(c){let m=e(`${c}/filters`,4),p=e(`${c}/bias`,1);return{filters:m,bias:p}}function s(c){let m=a(`${c}/conv`),p=r(`${c}/bn`);return{conv:m,bn:p}}let i=Ht(e);return{extractConvParams:a,extractConvWithBatchNormParams:s,extractSeparableConvParams:i}}function mo(o,t){let e=[],{extractConvParams:r,extractConvWithBatchNormParams:a,extractSeparableConvParams:s}=en(o,e),i;if(t.withSeparableConvs){let c=t.filterSizes&&t.filterSizes.length||9;i={conv0:t.isFirstLayerConv2d?r("conv0"):s("conv0"),conv1:s("conv1"),conv2:s("conv2"),conv3:s("conv3"),conv4:s("conv4"),conv5:s("conv5"),conv6:c>7?s("conv6"):void 0,conv7:c>8?s("conv7"):void 0,conv8:r("conv8")}}else i={conv0:a("conv0"),conv1:a("conv1"),conv2:a("conv2"),conv3:a("conv3"),conv4:a("conv4"),conv5:a("conv5"),conv6:a("conv6"),conv7:a("conv7"),conv8:r("conv8")};return L(o,e),{params:i,paramMappings:e}}var J=class{constructor({inputSize:t,scoreThreshold:e}={}){this._name="TinyYolov2Options";if(this._inputSize=t||416,this._scoreThreshold=e||.5,typeof this._inputSize!="number"||this._inputSize%32!==0)throw new Error(`${this._name} - expected inputSize to be a number divisible by 32`);if(typeof this._scoreThreshold!="number"||this._scoreThreshold<=0||this._scoreThreshold>=1)throw new Error(`${this._name} - expected scoreThreshold to be a number between 0 and 1`)}get inputSize(){return this._inputSize}get scoreThreshold(){return this._scoreThreshold}};var cr=class extends I{constructor(e){super("TinyYolov2");io(e),this._config=e}get config(){return this._config}get withClassScores(){return this.config.withClassScores||this.config.classes.length>1}get boxEncodingSize(){return 5+(this.withClassScores?this.config.classes.length:0)}runTinyYolov2(e,r){let a=ot(e,r.conv0);return a=n.maxPool(a,[2,2],[2,2],"same"),a=ot(a,r.conv1),a=n.maxPool(a,[2,2],[2,2],"same"),a=ot(a,r.conv2),a=n.maxPool(a,[2,2],[2,2],"same"),a=ot(a,r.conv3),a=n.maxPool(a,[2,2],[2,2],"same"),a=ot(a,r.conv4),a=n.maxPool(a,[2,2],[2,2],"same"),a=ot(a,r.conv5),a=n.maxPool(a,[2,2],[1,1],"same"),a=ot(a,r.conv6),a=ot(a,r.conv7),_t(a,r.conv8,"valid",!1)}runMobilenet(e,r){let a=this.config.isFirstLayerConv2d?Xt(_t(e,r.conv0,"valid",!1)):nt(e,r.conv0);return a=n.maxPool(a,[2,2],[2,2],"same"),a=nt(a,r.conv1),a=n.maxPool(a,[2,2],[2,2],"same"),a=nt(a,r.conv2),a=n.maxPool(a,[2,2],[2,2],"same"),a=nt(a,r.conv3),a=n.maxPool(a,[2,2],[2,2],"same"),a=nt(a,r.conv4),a=n.maxPool(a,[2,2],[2,2],"same"),a=nt(a,r.conv5),a=n.maxPool(a,[2,2],[1,1],"same"),a=r.conv6?nt(a,r.conv6):a,a=r.conv7?nt(a,r.conv7):a,_t(a,r.conv8,"valid",!1)}forwardInput(e,r){let{params:a}=this;if(!a)throw new Error("TinyYolov2 - load model before inference");return n.tidy(()=>{let s=n.cast(e.toBatchTensor(r,!1),"float32");return s=this.config.meanRgb?X(s,this.config.meanRgb):s,s=s.div(255),this.config.withSeparableConvs?this.runMobilenet(s,a):this.runTinyYolov2(s,a)})}async forward(e,r){return this.forwardInput(await M(e),r)}async detect(e,r={}){let{inputSize:a,scoreThreshold:s}=new J(r),i=await M(e),c=await this.forwardInput(i,a),m=n.tidy(()=>n.unstack(c)[0].expandDims()),p={width:i.getInputWidth(0),height:i.getInputHeight(0)},u=await this.extractBoxes(m,i.getReshapedInputDimensions(0),s);c.dispose(),m.dispose();let f=u.map(h=>h.box),l=u.map(h=>h.score),d=u.map(h=>h.classScore),g=u.map(h=>this.config.classes[h.label]);return gr(f.map(h=>h.rescale(a)),l,this.config.iouThreshold,!0).map(h=>new ct(l[h],d[h],g[h],f[h],p))}getDefaultModelName(){return""}extractParamsFromWeightMap(e){return mo(e,this.config)}extractParams(e){let r=this.config.filterSizes||cr.DEFAULT_FILTER_SIZES,a=r?r.length:void 0;if(a!==7&&a!==8&&a!==9)throw new Error(`TinyYolov2 - expected 7 | 8 | 9 convolutional filters, but found ${a} filterSizes in config`);return co(e,this.config,this.boxEncodingSize,r)}async extractBoxes(e,r,a){let{width:s,height:i}=r,c=Math.max(s,i),m=c/s,p=c/i,u=e.shape[1],f=this.config.anchors.length,[l,d,g]=n.tidy(()=>{let y=e.reshape([u,u,f,this.boxEncodingSize]),x=y.slice([0,0,0,0],[u,u,f,4]),D=y.slice([0,0,0,4],[u,u,f,1]),N=this.withClassScores?n.softmax(y.slice([0,0,0,5],[u,u,f,this.config.classes.length]),3):n.scalar(0);return[x,D,N]}),_=[],F=await d.array(),h=await l.array();for(let y=0;ya){let Y=(x+fe(h[y][x][D][0]))/u*m,q=(y+fe(h[y][x][D][1]))/u*p,O=Math.exp(h[y][x][D][2])*this.config.anchors[D].x/u*m,at=Math.exp(h[y][x][D][3])*this.config.anchors[D].y/u*p,st=Y-O/2,it=q-at/2,gt={row:y,col:x,anchor:D},{classScore:pr,label:ur}=this.withClassScores?await this.extractPredictedClass(g,gt):{classScore:1,label:0};_.push({box:new Nt(st,it,st+O,it+at),score:N,classScore:N*pr,label:ur,...gt})}}return l.dispose(),d.dispose(),g.dispose(),_}async extractPredictedClass(e,r){let{row:a,col:s,anchor:i}=r,c=await e.array();return Array(this.config.classes.length).fill(0).map((m,p)=>c[a][s][i][p]).map((m,p)=>({classScore:m,label:p})).reduce((m,p)=>m.classScore>p.classScore?m:p)}},wt=cr;wt.DEFAULT_FILTER_SIZES=[3,16,32,64,128,256,512,1024,1024];var Jt=class extends wt{constructor(t=!0){let e={withSeparableConvs:t,iouThreshold:eo,classes:["face"],...t?{anchors:oo,meanRgb:no}:{anchors:ro,withClassScores:!0}};super(e)}get withSeparableConvs(){return this.config.withSeparableConvs}get anchors(){return this.config.anchors}async locateFaces(t,e){return(await this.detect(t,e)).map(a=>new E(a.score,a.relativeBox,{width:a.imageWidth,height:a.imageHeight}))}getDefaultModelName(){return this.withSeparableConvs?so:ao}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};function pd(o,t=!0){let e=new Jt(t);return e.extractWeights(o),e}var Le=class extends J{constructor(){super(...arguments);this._name="TinyFaceDetectorOptions"}};var V=class{async then(t){return t(await this.run())}async run(){throw new Error("ComposableTask - run is not implemented")}};async function Ft(o,t,e,r,a=({alignedRect:s})=>s){let s=o.map(m=>Yt(m)?a(m):m.detection),i=r||(t instanceof n.Tensor?await oe(t,s):await re(t,s)),c=await e(i);return i.forEach(m=>m instanceof n.Tensor&&m.dispose()),c}async function qt(o,t,e,r,a){return Ft([o],t,async s=>e(s[0]),r,a)}var po=.4,uo=[new b(1.603231,2.094468),new b(6.041143,7.080126),new b(2.882459,3.518061),new b(4.266906,5.178857),new b(9.041765,10.66308)],fo=[117.001,114.697,97.404];var Zt=class extends wt{constructor(){let t={withSeparableConvs:!0,iouThreshold:po,classes:["face"],anchors:uo,meanRgb:fo,isFirstLayerConv2d:!0,filterSizes:[3,16,32,64,128,256,512]};super(t)}get anchors(){return this.config.anchors}async locateFaces(t,e){return(await this.detect(t,e)).map(a=>new E(a.score,a.relativeBox,{width:a.imageWidth,height:a.imageHeight}))}getDefaultModelName(){return"tiny_face_detector_model"}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};var P={ssdMobilenetv1:new Pt,tinyFaceDetector:new Zt,tinyYolov2:new Jt,faceLandmark68Net:new jt,faceLandmark68TinyNet:new Ie,faceRecognitionNet:new Ut,faceExpressionNet:new we,ageGenderNet:new Me},rn=(o,t)=>P.ssdMobilenetv1.locateFaces(o,t),Od=(o,t)=>P.tinyFaceDetector.locateFaces(o,t),Hd=(o,t)=>P.tinyYolov2.locateFaces(o,t),on=o=>P.faceLandmark68Net.detectLandmarks(o),zd=o=>P.faceLandmark68TinyNet.detectLandmarks(o),Vd=o=>P.faceRecognitionNet.computeFaceDescriptor(o),Yd=o=>P.faceExpressionNet.predictExpressions(o),Gd=o=>P.ageGenderNet.predictAgeAndGender(o),nn=o=>P.ssdMobilenetv1.load(o),jd=o=>P.tinyFaceDetector.load(o),Ud=o=>P.tinyYolov2.load(o),Xd=o=>P.faceLandmark68Net.load(o),Jd=o=>P.faceLandmark68TinyNet.load(o),qd=o=>P.faceRecognitionNet.load(o),Zd=o=>P.faceExpressionNet.load(o),Kd=o=>P.ageGenderNet.load(o),Qd=nn,th=rn,eh=on;var Ae=class extends V{constructor(e,r,a){super();this.parentTask=e;this.input=r;this.extractedFaces=a}},Dt=class extends Ae{async run(){let t=await this.parentTask,e=await Ft(t,this.input,async r=>Promise.all(r.map(a=>P.faceExpressionNet.predictExpressions(a))),this.extractedFaces);return t.map((r,a)=>tr(r,e[a]))}withAgeAndGender(){return new Mt(this,this.input)}},Et=class extends Ae{async run(){let t=await this.parentTask;if(!t)return;let e=await qt(t,this.input,r=>P.faceExpressionNet.predictExpressions(r),this.extractedFaces);return tr(t,e)}withAgeAndGender(){return new Ct(this,this.input)}},ut=class extends Dt{withAgeAndGender(){return new lt(this,this.input)}withFaceDescriptors(){return new ht(this,this.input)}},ft=class extends Et{withAgeAndGender(){return new dt(this,this.input)}withFaceDescriptor(){return new bt(this,this.input)}};var We=class extends V{constructor(e,r,a){super();this.parentTask=e;this.input=r;this.extractedFaces=a}},Mt=class extends We{async run(){let t=await this.parentTask,e=await Ft(t,this.input,async r=>Promise.all(r.map(a=>P.ageGenderNet.predictAgeAndGender(a))),this.extractedFaces);return t.map((r,a)=>{let{age:s,gender:i,genderProbability:c}=e[a];return sr(ir(r,i,c),s)})}withFaceExpressions(){return new Dt(this,this.input)}},Ct=class extends We{async run(){let t=await this.parentTask;if(!t)return;let{age:e,gender:r,genderProbability:a}=await qt(t,this.input,s=>P.ageGenderNet.predictAgeAndGender(s),this.extractedFaces);return sr(ir(t,r,a),e)}withFaceExpressions(){return new Et(this,this.input)}},lt=class extends Mt{withFaceExpressions(){return new ut(this,this.input)}withFaceDescriptors(){return new ht(this,this.input)}},dt=class extends Ct{withFaceExpressions(){return new ft(this,this.input)}withFaceDescriptor(){return new bt(this,this.input)}};var ke=class extends V{constructor(e,r){super();this.parentTask=e;this.input=r}},ht=class extends ke{async run(){let t=await this.parentTask;return(await Ft(t,this.input,r=>Promise.all(r.map(a=>P.faceRecognitionNet.computeFaceDescriptor(a))),null,r=>r.landmarks.align(null,{useDlibAlignment:!0}))).map((r,a)=>ar(t[a],r))}withFaceExpressions(){return new ut(this,this.input)}withAgeAndGender(){return new lt(this,this.input)}},bt=class extends ke{async run(){let t=await this.parentTask;if(!t)return;let e=await qt(t,this.input,r=>P.faceRecognitionNet.computeFaceDescriptor(r),null,r=>r.landmarks.align(null,{useDlibAlignment:!0}));return ar(t,e)}withFaceExpressions(){return new ft(this,this.input)}withAgeAndGender(){return new dt(this,this.input)}};var Be=class extends V{constructor(e,r,a){super();this.parentTask=e;this.input=r;this.useTinyLandmarkNet=a}get landmarkNet(){return this.useTinyLandmarkNet?P.faceLandmark68TinyNet:P.faceLandmark68Net}},Re=class extends Be{async run(){let t=await this.parentTask,e=t.map(i=>i.detection),r=this.input instanceof n.Tensor?await oe(this.input,e):await re(this.input,e),a=await Promise.all(r.map(i=>this.landmarkNet.detectLandmarks(i)));return r.forEach(i=>i instanceof n.Tensor&&i.dispose()),t.filter((i,c)=>a[c]).map((i,c)=>ie(i,a[c]))}withFaceExpressions(){return new ut(this,this.input)}withAgeAndGender(){return new lt(this,this.input)}withFaceDescriptors(){return new ht(this,this.input)}},$e=class extends Be{async run(){let t=await this.parentTask;if(!t)return;let{detection:e}=t,r=this.input instanceof n.Tensor?await oe(this.input,[e]):await re(this.input,[e]),a=await this.landmarkNet.detectLandmarks(r[0]);return r.forEach(s=>s instanceof n.Tensor&&s.dispose()),ie(t,a)}withFaceExpressions(){return new ft(this,this.input)}withAgeAndGender(){return new dt(this,this.input)}withFaceDescriptor(){return new bt(this,this.input)}};var Oe=class extends V{constructor(e,r=new z){super();this.input=e;this.options=r}},me=class extends Oe{async run(){let{input:t,options:e}=this,r;if(e instanceof Le)r=P.tinyFaceDetector.locateFaces(t,e);else if(e instanceof z)r=P.ssdMobilenetv1.locateFaces(t,e);else if(e instanceof J)r=P.tinyYolov2.locateFaces(t,e);else throw new Error("detectFaces - expected options to be instance of TinyFaceDetectorOptions | SsdMobilenetv1Options | TinyYolov2Options");return r}runAndExtendWithFaceDetections(){return new Promise((t,e)=>{this.run().then(r=>t(r.map(a=>At({},a)))).catch(r=>e(r))})}withFaceLandmarks(t=!1){return new Re(this.runAndExtendWithFaceDetections(),this.input,t)}withFaceExpressions(){return new Dt(this.runAndExtendWithFaceDetections(),this.input)}withAgeAndGender(){return new Mt(this.runAndExtendWithFaceDetections(),this.input)}},He=class extends Oe{async run(){let t=await new me(this.input,this.options),e=t[0];return t.forEach(r=>{r.score>e.score&&(e=r)}),e}runAndExtendWithFaceDetection(){return new Promise(async t=>{let e=await this.run();t(e?At({},e):void 0)})}withFaceLandmarks(t=!1){return new $e(this.runAndExtendWithFaceDetection(),this.input,t)}withFaceExpressions(){return new Et(this.runAndExtendWithFaceDetection(),this.input)}withAgeAndGender(){return new Ct(this.runAndExtendWithFaceDetection(),this.input)}};function Kh(o,t=new z){return new He(o,t)}function mr(o,t=new z){return new me(o,t)}async function an(o,t){return mr(o,new 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this._labeledDescriptors}get distanceThreshold(){return this._distanceThreshold}computeMeanDistance(t,e){return e.map(r=>lo(r,t)).reduce((r,a)=>r+a,0)/(e.length||1)}matchDescriptor(t){return this.labeledDescriptors.map(({descriptors:e,label:r})=>new Kt(r,this.computeMeanDistance(t,e))).reduce((e,r)=>e.distancet.toJSON())}}static fromJSON(t){let e=t.labeledDescriptors.map(r=>Q.fromJSON(r));return new ze(e,t.distanceThreshold)}};function Pb(o){let t=new Zt;return t.extractWeights(o),t}function sn(o,t){let{width:e,height:r}=new S(t.width,t.height);if(e<=0||r<=0)throw new Error(`resizeResults - invalid dimensions: ${JSON.stringify({width:e,height:r})}`);if(Array.isArray(o))return o.map(a=>sn(a,{width:e,height:r}));if(Yt(o)){let a=o.detection.forSize(e,r),s=o.unshiftedLandmarks.forSize(a.box.width,a.box.height);return ie(At(o,a),s)}return tt(o)?At(o,o.detection.forSize(e,r)):o instanceof $||o instanceof E?o.forSize(e,r):o}var Ab=Wr;export{Me as AgeGenderNet,Nt as BoundingBox,w as Box,V as 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allFacesTinyYolov2,_r as awaitMediaLoaded,Tr as bufferToImage,Vd as computeFaceDescriptor,Rt as createCanvas,be as createCanvasFromMedia,vl as createFaceDetectionNet,vf as createFaceRecognitionNet,Qo as createSsdMobilenetv1,Pb as createTinyFaceDetector,pd as createTinyYolov2,mr as detectAllFaces,on as detectFaceLandmarks,zd as detectFaceLandmarksTiny,eh as detectLandmarks,Kh as detectSingleFace,Ar as draw,T as env,lo as euclideanDistance,sr as extendWithAge,ar as extendWithFaceDescriptor,At as extendWithFaceDetection,tr as extendWithFaceExpressions,ie as extendWithFaceLandmarks,ir as extendWithGender,oe as extractFaceTensors,re as extractFaces,Mi as fetchImage,Fr as fetchJson,Li as fetchNetWeights,mt as fetchOrThrow,$i as fetchVideo,k as getContext2dOrThrow,Bt as getMediaDimensions,Pr as imageTensorToCanvas,wr as imageToSquare,Vn as inverseSigmoid,hr as iou,Qe as isMediaElement,he as isMediaLoaded,Pf as isWithAge,tt as isWithFaceDetection,Lr as isWithFaceExpressions,Yt as 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s(m,p,u){let f=e(m,`${u}/depthwise_conv`),l=a(m,p,1,`${u}/pointwise_conv`);return{depthwise_conv:f,pointwise_conv:l}}function i(){let m=a(3,32,3,"mobilenetv1/conv_0"),p=s(32,64,"mobilenetv1/conv_1"),u=s(64,128,"mobilenetv1/conv_2"),f=s(128,128,"mobilenetv1/conv_3"),l=s(128,256,"mobilenetv1/conv_4"),d=s(256,256,"mobilenetv1/conv_5"),g=s(256,512,"mobilenetv1/conv_6"),_=s(512,512,"mobilenetv1/conv_7"),F=s(512,512,"mobilenetv1/conv_8"),h=s(512,512,"mobilenetv1/conv_9"),y=s(512,512,"mobilenetv1/conv_10"),x=s(512,512,"mobilenetv1/conv_11"),D=s(512,1024,"mobilenetv1/conv_12"),N=s(1024,1024,"mobilenetv1/conv_13");return{conv_0:m,conv_1:p,conv_2:u,conv_3:f,conv_4:l,conv_5:d,conv_6:g,conv_7:_,conv_8:F,conv_9:h,conv_10:y,conv_11:x,conv_12:D,conv_13:N}}function c(){let 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u=i(`Prediction/BoxPredictor_${p}/BoxEncodingPredictor`,`prediction_layer/box_predictor_${p}/box_encoding_predictor`),f=i(`Prediction/BoxPredictor_${p}/ClassPredictor`,`prediction_layer/box_predictor_${p}/class_predictor`);return{box_encoding_predictor:u,class_predictor:f}}function m(){return{conv_0:r("Prediction",0,"prediction_layer/conv_0"),conv_1:r("Prediction",1,"prediction_layer/conv_1"),conv_2:r("Prediction",2,"prediction_layer/conv_2"),conv_3:r("Prediction",3,"prediction_layer/conv_3"),conv_4:r("Prediction",4,"prediction_layer/conv_4"),conv_5:r("Prediction",5,"prediction_layer/conv_5"),conv_6:r("Prediction",6,"prediction_layer/conv_6"),conv_7:r("Prediction",7,"prediction_layer/conv_7"),box_predictor_0:c(0),box_predictor_1:c(1),box_predictor_2:c(2),box_predictor_3:c(3),box_predictor_4:c(4),box_predictor_5:c(5)}}return{extractMobilenetV1Params:s,extractPredictionLayerParams:m}}function Jr(o){let 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e,r=H(o,t.conv_0,[2,2]);if([t.conv_1,t.conv_2,t.conv_3,t.conv_4,t.conv_5,t.conv_6,t.conv_7,t.conv_8,t.conv_9,t.conv_10,t.conv_11,t.conv_12,t.conv_13].forEach((s,i)=>{let c=i+1,m=Jo(c);r=Xo(r,s.depthwise_conv,m),r=H(r,s.pointwise_conv,[1,1]),c===11&&(e=r)}),e===null)throw new Error("mobileNetV1 - output of conv layer 11 is null");return{out:r,conv11:e}})}function qo(o,t,e){let r=o.arraySync(),a=Math.min(r[t][0],r[t][2]),s=Math.min(r[t][1],r[t][3]),i=Math.max(r[t][0],r[t][2]),c=Math.max(r[t][1],r[t][3]),m=Math.min(r[e][0],r[e][2]),p=Math.min(r[e][1],r[e][3]),u=Math.max(r[e][0],r[e][2]),f=Math.max(r[e][1],r[e][3]),l=(i-a)*(c-s),d=(u-m)*(f-p);if(l<=0||d<=0)return 0;let g=Math.max(a,m),_=Math.max(s,p),F=Math.min(i,u),h=Math.min(c,f),y=Math.max(F-g,0)*Math.max(h-_,0);return y/(l+d-y)}function Zr(o,t,e,r,a){let s=o.shape[0],i=Math.min(e,s),c=t.map((u,f)=>({score:u,boxIndex:f})).filter(u=>u.score>a).sort((u,f)=>f.score-u.score),m=u=>u<=r?1:0,p=[];return c.forEach(u=>{if(p.length>=i)return;let f=u.score;for(let l=p.length-1;l>=0;--l){let d=qo(o,u.boxIndex,p[l]);if(d!==0&&(u.score*=m(d),u.score<=a))break}f===u.score&&p.push(u.boxIndex)}),p}function Zo(o){let t=n.unstack(n.transpose(o,[1,0])),e=[n.sub(t[2],t[0]),n.sub(t[3],t[1])],r=[n.add(t[0],n.div(e[0],2)),n.add(t[1],n.div(e[1],2))];return{sizes:e,centers:r}}function Ko(o,t){let{sizes:e,centers:r}=Zo(o),a=n.unstack(n.transpose(t,[1,0])),s=n.div(n.mul(n.exp(n.div(a[2],5)),e[0]),2),i=n.add(n.mul(n.div(a[0],10),e[0]),r[0]),c=n.div(n.mul(n.exp(n.div(a[3],5)),e[1]),2),m=n.add(n.mul(n.div(a[1],10),e[1]),r[1]);return n.transpose(n.stack([n.sub(i,s),n.sub(m,c),n.add(i,s),n.add(m,c)]),[1,0])}function Kr(o,t,e){return n.tidy(()=>{let r=o.shape[0],a=Ko(n.reshape(n.tile(e.extra_dim,[r,1,1]),[-1,4]),n.reshape(o,[-1,4]));a=n.reshape(a,[r,a.shape[0]/r,4]);let s=n.sigmoid(n.slice(t,[0,0,1],[-1,-1,-1])),i=n.slice(s,[0,0,0],[-1,-1,1]);i=n.reshape(i,[r,i.shape[1]]);let c=n.unstack(a),m=n.unstack(i);return{boxes:c,scores:m}})}function Tt(o,t){return n.tidy(()=>{let e=o.shape[0],r=n.reshape(_t(o,t.box_encoding_predictor),[e,-1,1,4]),a=n.reshape(_t(o,t.class_predictor),[e,-1,3]);return{boxPredictionEncoding:r,classPrediction:a}})}function Qr(o,t,e){return n.tidy(()=>{let r=H(o,e.conv_0,[1,1]),a=H(r,e.conv_1,[2,2]),s=H(a,e.conv_2,[1,1]),i=H(s,e.conv_3,[2,2]),c=H(i,e.conv_4,[1,1]),m=H(c,e.conv_5,[2,2]),p=H(m,e.conv_6,[1,1]),u=H(p,e.conv_7,[2,2]),f=Tt(t,e.box_predictor_0),l=Tt(o,e.box_predictor_1),d=Tt(a,e.box_predictor_2),g=Tt(i,e.box_predictor_3),_=Tt(m,e.box_predictor_4),F=Tt(u,e.box_predictor_5),h=n.concat([f.boxPredictionEncoding,l.boxPredictionEncoding,d.boxPredictionEncoding,g.boxPredictionEncoding,_.boxPredictionEncoding,F.boxPredictionEncoding],1),y=n.concat([f.classPrediction,l.classPrediction,d.classPrediction,g.classPrediction,_.classPrediction,F.classPrediction],1);return{boxPredictions:h,classPredictions:y}})}var z=class{constructor({minConfidence:t,maxResults:e}={}){this._name="SsdMobilenetv1Options";if(this._minConfidence=t||.5,this._maxResults=e||100,typeof this._minConfidence!="number"||this._minConfidence<=0||this._minConfidence>=1)throw new Error(`${this._name} - expected minConfidence to be a number between 0 and 1`);if(typeof this._maxResults!="number")throw new Error(`${this._name} - expected maxResults to be a number`)}get minConfidence(){return this._minConfidence}get maxResults(){return this._maxResults}};var Pt=class extends I{constructor(){super("SsdMobilenetv1")}forwardInput(t){let{params:e}=this;if(!e)throw new Error("SsdMobilenetv1 - load model before inference");return n.tidy(()=>{let r=n.cast(t.toBatchTensor(512,!1),"float32"),a=n.sub(n.div(r,127.5),1),s=qr(a,e.mobilenetv1),{boxPredictions:i,classPredictions:c}=Qr(s.out,s.conv11,e.prediction_layer);return Kr(i,c,e.output_layer)})}async forward(t){return this.forwardInput(await M(t))}async locateFaces(t,e={}){let{maxResults:r,minConfidence:a}=new z(e),s=await M(t),{boxes:i,scores:c}=this.forwardInput(s),m=i[0],p=c[0];for(let x=1;x{let[D,N]=[Math.max(0,h[x][0]),Math.min(1,h[x][2])].map(O=>O*F),[Y,q]=[Math.max(0,h[x][1]),Math.min(1,h[x][3])].map(O=>O*_);return new E(u[x],new St(Y,D,q-Y,N-D),{height:s.getInputHeight(0),width:s.getInputWidth(0)})});return m.dispose(),p.dispose(),y}getDefaultModelName(){return"ssd_mobilenetv1_model"}extractParamsFromWeightMap(t){return Jr(t)}extractParams(t){return Xr(t)}};function Qo(o){let t=new Pt;return t.extractWeights(o),t}function vl(o){return Qo(o)}var to=class extends Pt{};var eo=.4,ro=[new b(.738768,.874946),new b(2.42204,2.65704),new b(4.30971,7.04493),new b(10.246,4.59428),new b(12.6868,11.8741)],oo=[new b(1.603231,2.094468),new b(6.041143,7.080126),new b(2.882459,3.518061),new b(4.266906,5.178857),new b(9.041765,10.66308)],no=[117.001,114.697,97.404],ao="tiny_yolov2_model",so="tiny_yolov2_separable_conv_model";var Se=o=>typeof o=="number";function io(o){if(!o)throw new Error(`invalid config: ${o}`);if(typeof o.withSeparableConvs!="boolean")throw new Error(`config.withSeparableConvs has to be a boolean, have: ${o.withSeparableConvs}`);if(!Se(o.iouThreshold)||o.iouThreshold<0||o.iouThreshold>1)throw new Error(`config.iouThreshold has to be a number between [0, 1], have: ${o.iouThreshold}`);if(!Array.isArray(o.classes)||!o.classes.length||!o.classes.every(t=>typeof t=="string"))throw new Error(`config.classes has to be an array class names: string[], have: ${JSON.stringify(o.classes)}`);if(!Array.isArray(o.anchors)||!o.anchors.length||!o.anchors.map(t=>t||{}).every(t=>Se(t.x)&&Se(t.y)))throw new Error(`config.anchors has to be an array of { x: number, y: number }, have: ${JSON.stringify(o.anchors)}`);if(o.meanRgb&&(!Array.isArray(o.meanRgb)||o.meanRgb.length!==3||!o.meanRgb.every(Se)))throw new Error(`config.meanRgb has to be an array of shape [number, number, number], have: 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co(o,t,e,r){let{extractWeights:a,getRemainingWeights:s}=A(o),i=[],{extractConvParams:c,extractConvWithBatchNormParams:m,extractSeparableConvParams:p}=tn(a,i),u;if(t.withSeparableConvs){let[f,l,d,g,_,F,h,y,x]=r,D=t.isFirstLayerConv2d?c(f,l,3,"conv0"):p(f,l,"conv0"),N=p(l,d,"conv1"),Y=p(d,g,"conv2"),q=p(g,_,"conv3"),O=p(_,F,"conv4"),at=p(F,h,"conv5"),st=y?p(h,y,"conv6"):void 0,it=x?p(y,x,"conv7"):void 0,gt=c(x||y||h,5*e,1,"conv8");u={conv0:D,conv1:N,conv2:Y,conv3:q,conv4:O,conv5:at,conv6:st,conv7:it,conv8:gt}}else{let[f,l,d,g,_,F,h,y,x]=r,D=m(f,l,"conv0"),N=m(l,d,"conv1"),Y=m(d,g,"conv2"),q=m(g,_,"conv3"),O=m(_,F,"conv4"),at=m(F,h,"conv5"),st=m(h,y,"conv6"),it=m(y,x,"conv7"),gt=c(x,5*e,1,"conv8");u={conv0:D,conv1:N,conv2:Y,conv3:q,conv4:O,conv5:at,conv6:st,conv7:it,conv8:gt}}if(s().length!==0)throw new Error(`weights remaing after extract: ${s().length}`);return{params:u,paramMappings:i}}function en(o,t){let e=B(o,t);function r(c){let m=e(`${c}/sub`,1),p=e(`${c}/truediv`,1);return{sub:m,truediv:p}}function a(c){let m=e(`${c}/filters`,4),p=e(`${c}/bias`,1);return{filters:m,bias:p}}function s(c){let m=a(`${c}/conv`),p=r(`${c}/bn`);return{conv:m,bn:p}}let i=Ht(e);return{extractConvParams:a,extractConvWithBatchNormParams:s,extractSeparableConvParams:i}}function mo(o,t){let e=[],{extractConvParams:r,extractConvWithBatchNormParams:a,extractSeparableConvParams:s}=en(o,e),i;if(t.withSeparableConvs){let c=t.filterSizes&&t.filterSizes.length||9;i={conv0:t.isFirstLayerConv2d?r("conv0"):s("conv0"),conv1:s("conv1"),conv2:s("conv2"),conv3:s("conv3"),conv4:s("conv4"),conv5:s("conv5"),conv6:c>7?s("conv6"):void 0,conv7:c>8?s("conv7"):void 0,conv8:r("conv8")}}else i={conv0:a("conv0"),conv1:a("conv1"),conv2:a("conv2"),conv3:a("conv3"),conv4:a("conv4"),conv5:a("conv5"),conv6:a("conv6"),conv7:a("conv7"),conv8:r("conv8")};return L(o,e),{params:i,paramMappings:e}}var J=class{constructor({inputSize:t,scoreThreshold:e}={}){this._name="TinyYolov2Options";if(this._inputSize=t||416,this._scoreThreshold=e||.5,typeof this._inputSize!="number"||this._inputSize%32!==0)throw new Error(`${this._name} - expected inputSize to be a number divisible by 32`);if(typeof this._scoreThreshold!="number"||this._scoreThreshold<=0||this._scoreThreshold>=1)throw new Error(`${this._name} - expected scoreThreshold to be a number between 0 and 1`)}get inputSize(){return this._inputSize}get scoreThreshold(){return this._scoreThreshold}};var cr=class extends I{constructor(e){super("TinyYolov2");io(e),this._config=e}get config(){return this._config}get withClassScores(){return this.config.withClassScores||this.config.classes.length>1}get boxEncodingSize(){return 5+(this.withClassScores?this.config.classes.length:0)}runTinyYolov2(e,r){let a=ot(e,r.conv0);return a=n.maxPool(a,[2,2],[2,2],"same"),a=ot(a,r.conv1),a=n.maxPool(a,[2,2],[2,2],"same"),a=ot(a,r.conv2),a=n.maxPool(a,[2,2],[2,2],"same"),a=ot(a,r.conv3),a=n.maxPool(a,[2,2],[2,2],"same"),a=ot(a,r.conv4),a=n.maxPool(a,[2,2],[2,2],"same"),a=ot(a,r.conv5),a=n.maxPool(a,[2,2],[1,1],"same"),a=ot(a,r.conv6),a=ot(a,r.conv7),_t(a,r.conv8,"valid",!1)}runMobilenet(e,r){let a=this.config.isFirstLayerConv2d?Xt(_t(e,r.conv0,"valid",!1)):nt(e,r.conv0);return a=n.maxPool(a,[2,2],[2,2],"same"),a=nt(a,r.conv1),a=n.maxPool(a,[2,2],[2,2],"same"),a=nt(a,r.conv2),a=n.maxPool(a,[2,2],[2,2],"same"),a=nt(a,r.conv3),a=n.maxPool(a,[2,2],[2,2],"same"),a=nt(a,r.conv4),a=n.maxPool(a,[2,2],[2,2],"same"),a=nt(a,r.conv5),a=n.maxPool(a,[2,2],[1,1],"same"),a=r.conv6?nt(a,r.conv6):a,a=r.conv7?nt(a,r.conv7):a,_t(a,r.conv8,"valid",!1)}forwardInput(e,r){let{params:a}=this;if(!a)throw new Error("TinyYolov2 - load model before inference");return n.tidy(()=>{let s=n.cast(e.toBatchTensor(r,!1),"float32");return s=this.config.meanRgb?X(s,this.config.meanRgb):s,s=s.div(255),this.config.withSeparableConvs?this.runMobilenet(s,a):this.runTinyYolov2(s,a)})}async forward(e,r){return this.forwardInput(await M(e),r)}async detect(e,r={}){let{inputSize:a,scoreThreshold:s}=new J(r),i=await M(e),c=await this.forwardInput(i,a),m=n.tidy(()=>n.unstack(c)[0].expandDims()),p={width:i.getInputWidth(0),height:i.getInputHeight(0)},u=await this.extractBoxes(m,i.getReshapedInputDimensions(0),s);c.dispose(),m.dispose();let f=u.map(h=>h.box),l=u.map(h=>h.score),d=u.map(h=>h.classScore),g=u.map(h=>this.config.classes[h.label]);return gr(f.map(h=>h.rescale(a)),l,this.config.iouThreshold,!0).map(h=>new ct(l[h],d[h],g[h],f[h],p))}getDefaultModelName(){return""}extractParamsFromWeightMap(e){return mo(e,this.config)}extractParams(e){let r=this.config.filterSizes||cr.DEFAULT_FILTER_SIZES,a=r?r.length:void 0;if(a!==7&&a!==8&&a!==9)throw new Error(`TinyYolov2 - expected 7 | 8 | 9 convolutional filters, but found ${a} filterSizes in config`);return co(e,this.config,this.boxEncodingSize,r)}async extractBoxes(e,r,a){let{width:s,height:i}=r,c=Math.max(s,i),m=c/s,p=c/i,u=e.shape[1],f=this.config.anchors.length,[l,d,g]=n.tidy(()=>{let y=e.reshape([u,u,f,this.boxEncodingSize]),x=y.slice([0,0,0,0],[u,u,f,4]),D=y.slice([0,0,0,4],[u,u,f,1]),N=this.withClassScores?n.softmax(y.slice([0,0,0,5],[u,u,f,this.config.classes.length]),3):n.scalar(0);return[x,D,N]}),_=[],F=await d.array(),h=await l.array();for(let y=0;ya){let Y=(x+fe(h[y][x][D][0]))/u*m,q=(y+fe(h[y][x][D][1]))/u*p,O=Math.exp(h[y][x][D][2])*this.config.anchors[D].x/u*m,at=Math.exp(h[y][x][D][3])*this.config.anchors[D].y/u*p,st=Y-O/2,it=q-at/2,gt={row:y,col:x,anchor:D},{classScore:pr,label:ur}=this.withClassScores?await this.extractPredictedClass(g,gt):{classScore:1,label:0};_.push({box:new Nt(st,it,st+O,it+at),score:N,classScore:N*pr,label:ur,...gt})}}return l.dispose(),d.dispose(),g.dispose(),_}async extractPredictedClass(e,r){let{row:a,col:s,anchor:i}=r,c=await e.array();return Array(this.config.classes.length).fill(0).map((m,p)=>c[a][s][i][p]).map((m,p)=>({classScore:m,label:p})).reduce((m,p)=>m.classScore>p.classScore?m:p)}},wt=cr;wt.DEFAULT_FILTER_SIZES=[3,16,32,64,128,256,512,1024,1024];var Jt=class extends wt{constructor(t=!0){let e={withSeparableConvs:t,iouThreshold:eo,classes:["face"],...t?{anchors:oo,meanRgb:no}:{anchors:ro,withClassScores:!0}};super(e)}get withSeparableConvs(){return this.config.withSeparableConvs}get anchors(){return this.config.anchors}async locateFaces(t,e){return(await this.detect(t,e)).map(a=>new E(a.score,a.relativeBox,{width:a.imageWidth,height:a.imageHeight}))}getDefaultModelName(){return this.withSeparableConvs?so:ao}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};function pd(o,t=!0){let e=new Jt(t);return e.extractWeights(o),e}var Le=class extends J{constructor(){super(...arguments);this._name="TinyFaceDetectorOptions"}};var V=class{async then(t){return t(await this.run())}async run(){throw new Error("ComposableTask - run is not implemented")}};async function Ft(o,t,e,r,a=({alignedRect:s})=>s){let s=o.map(m=>Yt(m)?a(m):m.detection),i=r||(t instanceof n.Tensor?await oe(t,s):await re(t,s)),c=await e(i);return i.forEach(m=>m instanceof n.Tensor&&m.dispose()),c}async function qt(o,t,e,r,a){return Ft([o],t,async s=>e(s[0]),r,a)}var po=.4,uo=[new b(1.603231,2.094468),new b(6.041143,7.080126),new b(2.882459,3.518061),new b(4.266906,5.178857),new b(9.041765,10.66308)],fo=[117.001,114.697,97.404];var Zt=class extends wt{constructor(){let t={withSeparableConvs:!0,iouThreshold:po,classes:["face"],anchors:uo,meanRgb:fo,isFirstLayerConv2d:!0,filterSizes:[3,16,32,64,128,256,512]};super(t)}get anchors(){return this.config.anchors}async locateFaces(t,e){return(await this.detect(t,e)).map(a=>new E(a.score,a.relativeBox,{width:a.imageWidth,height:a.imageHeight}))}getDefaultModelName(){return"tiny_face_detector_model"}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};var P={ssdMobilenetv1:new Pt,tinyFaceDetector:new Zt,tinyYolov2:new Jt,faceLandmark68Net:new jt,faceLandmark68TinyNet:new Ie,faceRecognitionNet:new Ut,faceExpressionNet:new we,ageGenderNet:new Me},rn=(o,t)=>P.ssdMobilenetv1.locateFaces(o,t),Od=(o,t)=>P.tinyFaceDetector.locateFaces(o,t),Hd=(o,t)=>P.tinyYolov2.locateFaces(o,t),on=o=>P.faceLandmark68Net.detectLandmarks(o),zd=o=>P.faceLandmark68TinyNet.detectLandmarks(o),Vd=o=>P.faceRecognitionNet.computeFaceDescriptor(o),Yd=o=>P.faceExpressionNet.predictExpressions(o),Gd=o=>P.ageGenderNet.predictAgeAndGender(o),nn=o=>P.ssdMobilenetv1.load(o),jd=o=>P.tinyFaceDetector.load(o),Ud=o=>P.tinyYolov2.load(o),Xd=o=>P.faceLandmark68Net.load(o),Jd=o=>P.faceLandmark68TinyNet.load(o),qd=o=>P.faceRecognitionNet.load(o),Zd=o=>P.faceExpressionNet.load(o),Kd=o=>P.ageGenderNet.load(o),Qd=nn,th=rn,eh=on;var Ae=class extends V{constructor(e,r,a){super();this.parentTask=e;this.input=r;this.extractedFaces=a}},Dt=class extends Ae{async run(){let t=await this.parentTask,e=await Ft(t,this.input,async r=>Promise.all(r.map(a=>P.faceExpressionNet.predictExpressions(a))),this.extractedFaces);return t.map((r,a)=>tr(r,e[a]))}withAgeAndGender(){return new Mt(this,this.input)}},Et=class extends Ae{async run(){let t=await this.parentTask;if(!t)return;let e=await qt(t,this.input,r=>P.faceExpressionNet.predictExpressions(r),this.extractedFaces);return tr(t,e)}withAgeAndGender(){return new Ct(this,this.input)}},ut=class extends Dt{withAgeAndGender(){return new lt(this,this.input)}withFaceDescriptors(){return new ht(this,this.input)}},ft=class extends Et{withAgeAndGender(){return new dt(this,this.input)}withFaceDescriptor(){return new bt(this,this.input)}};var We=class extends V{constructor(e,r,a){super();this.parentTask=e;this.input=r;this.extractedFaces=a}},Mt=class extends We{async run(){let t=await this.parentTask,e=await Ft(t,this.input,async r=>Promise.all(r.map(a=>P.ageGenderNet.predictAgeAndGender(a))),this.extractedFaces);return t.map((r,a)=>{let{age:s,gender:i,genderProbability:c}=e[a];return sr(ir(r,i,c),s)})}withFaceExpressions(){return new Dt(this,this.input)}},Ct=class extends We{async run(){let t=await this.parentTask;if(!t)return;let{age:e,gender:r,genderProbability:a}=await qt(t,this.input,s=>P.ageGenderNet.predictAgeAndGender(s),this.extractedFaces);return sr(ir(t,r,a),e)}withFaceExpressions(){return new Et(this,this.input)}},lt=class extends Mt{withFaceExpressions(){return new ut(this,this.input)}withFaceDescriptors(){return new ht(this,this.input)}},dt=class extends Ct{withFaceExpressions(){return new ft(this,this.input)}withFaceDescriptor(){return new bt(this,this.input)}};var ke=class extends V{constructor(e,r){super();this.parentTask=e;this.input=r}},ht=class extends ke{async run(){let t=await this.parentTask;return(await Ft(t,this.input,r=>Promise.all(r.map(a=>P.faceRecognitionNet.computeFaceDescriptor(a))),null,r=>r.landmarks.align(null,{useDlibAlignment:!0}))).map((r,a)=>ar(t[a],r))}withFaceExpressions(){return new ut(this,this.input)}withAgeAndGender(){return new lt(this,this.input)}},bt=class extends ke{async run(){let t=await this.parentTask;if(!t)return;let e=await qt(t,this.input,r=>P.faceRecognitionNet.computeFaceDescriptor(r),null,r=>r.landmarks.align(null,{useDlibAlignment:!0}));return ar(t,e)}withFaceExpressions(){return new ft(this,this.input)}withAgeAndGender(){return new dt(this,this.input)}};var Be=class extends V{constructor(e,r,a){super();this.parentTask=e;this.input=r;this.useTinyLandmarkNet=a}get landmarkNet(){return this.useTinyLandmarkNet?P.faceLandmark68TinyNet:P.faceLandmark68Net}},Re=class extends Be{async run(){let t=await this.parentTask,e=t.map(i=>i.detection),r=this.input instanceof n.Tensor?await oe(this.input,e):await re(this.input,e),a=await Promise.all(r.map(i=>this.landmarkNet.detectLandmarks(i)));return r.forEach(i=>i instanceof n.Tensor&&i.dispose()),t.filter((i,c)=>a[c]).map((i,c)=>ie(i,a[c]))}withFaceExpressions(){return new ut(this,this.input)}withAgeAndGender(){return new lt(this,this.input)}withFaceDescriptors(){return new ht(this,this.input)}},$e=class extends Be{async run(){let t=await this.parentTask;if(!t)return;let{detection:e}=t,r=this.input instanceof n.Tensor?await oe(this.input,[e]):await re(this.input,[e]),a=await this.landmarkNet.detectLandmarks(r[0]);return r.forEach(s=>s instanceof n.Tensor&&s.dispose()),ie(t,a)}withFaceExpressions(){return new ft(this,this.input)}withAgeAndGender(){return new dt(this,this.input)}withFaceDescriptor(){return new bt(this,this.input)}};var Oe=class extends V{constructor(e,r=new z){super();this.input=e;this.options=r}},me=class extends Oe{async run(){let{input:t,options:e}=this,r;if(e instanceof Le)r=P.tinyFaceDetector.locateFaces(t,e);else if(e instanceof z)r=P.ssdMobilenetv1.locateFaces(t,e);else if(e instanceof J)r=P.tinyYolov2.locateFaces(t,e);else throw new Error("detectFaces - expected options to be instance of TinyFaceDetectorOptions | SsdMobilenetv1Options | TinyYolov2Options");return r}runAndExtendWithFaceDetections(){return new Promise((t,e)=>{this.run().then(r=>t(r.map(a=>At({},a)))).catch(r=>e(r))})}withFaceLandmarks(t=!1){return new Re(this.runAndExtendWithFaceDetections(),this.input,t)}withFaceExpressions(){return new Dt(this.runAndExtendWithFaceDetections(),this.input)}withAgeAndGender(){return new Mt(this.runAndExtendWithFaceDetections(),this.input)}},He=class extends Oe{async run(){let t=await new me(this.input,this.options),e=t[0];return t.forEach(r=>{r.score>e.score&&(e=r)}),e}runAndExtendWithFaceDetection(){return new Promise(async t=>{let e=await this.run();t(e?At({},e):void 0)})}withFaceLandmarks(t=!1){return new $e(this.runAndExtendWithFaceDetection(),this.input,t)}withFaceExpressions(){return new Et(this.runAndExtendWithFaceDetection(),this.input)}withAgeAndGender(){return new Ct(this.runAndExtendWithFaceDetection(),this.input)}};function Kh(o,t=new z){return new He(o,t)}function mr(o,t=new z){return new me(o,t)}async function an(o,t){return mr(o,new z(t?{minConfidence:t}:{})).withFaceLandmarks().withFaceDescriptors()}async function nb(o,t={}){return mr(o,new J(t)).withFaceLandmarks().withFaceDescriptors()}var ab=an;function lo(o,t){if(o.length!==t.length)throw new Error("euclideanDistance: arr1.length !== arr2.length");let e=Array.from(o),r=Array.from(t);return Math.sqrt(e.map((a,s)=>a-r[s]).reduce((a,s)=>a+s**2,0))}var ze=class{constructor(t,e=.6){this._distanceThreshold=e;let r=Array.isArray(t)?t:[t];if(!r.length)throw new Error("FaceRecognizer.constructor - expected atleast one input");let a=1,s=()=>`person ${a++}`;this._labeledDescriptors=r.map(i=>{if(i instanceof Q)return i;if(i instanceof Float32Array)return new Q(s(),[i]);if(i.descriptor&&i.descriptor instanceof Float32Array)return new Q(s(),[i.descriptor]);throw new Error("FaceRecognizer.constructor - expected inputs to be of type LabeledFaceDescriptors | WithFaceDescriptor | Float32Array | Array | Float32Array>")})}get labeledDescriptors(){return this._labeledDescriptors}get distanceThreshold(){return this._distanceThreshold}computeMeanDistance(t,e){return e.map(r=>lo(r,t)).reduce((r,a)=>r+a,0)/(e.length||1)}matchDescriptor(t){return this.labeledDescriptors.map(({descriptors:e,label:r})=>new Kt(r,this.computeMeanDistance(t,e))).reduce((e,r)=>e.distancet.toJSON())}}static fromJSON(t){let e=t.labeledDescriptors.map(r=>Q.fromJSON(r));return new ze(e,t.distanceThreshold)}};function Pb(o){let t=new Zt;return t.extractWeights(o),t}function sn(o,t){let{width:e,height:r}=new S(t.width,t.height);if(e<=0||r<=0)throw new Error(`resizeResults - invalid dimensions: ${JSON.stringify({width:e,height:r})}`);if(Array.isArray(o))return o.map(a=>sn(a,{width:e,height:r}));if(Yt(o)){let a=o.detection.forSize(e,r),s=o.unshiftedLandmarks.forSize(a.box.width,a.box.height);return ie(At(o,a),s)}return tt(o)?At(o,o.detection.forSize(e,r)):o instanceof $||o instanceof E?o.forSize(e,r):o}var Ab=Wr;export{Me as AgeGenderNet,Nt as BoundingBox,w as Box,V as ComposableTask,ht as ComputeAllFaceDescriptorsTask,ke as ComputeFaceDescriptorsTaskBase,bt as ComputeSingleFaceDescriptorTask,Re as DetectAllFaceLandmarksTask,me as DetectAllFacesTask,Be as DetectFaceLandmarksTaskBase,Oe as DetectFacesTaskBase,$e as DetectSingleFaceLandmarksTask,He as DetectSingleFaceTask,S as Dimensions,Sr as FACE_EXPRESSION_LABELS,E as FaceDetection,to as FaceDetectionNet,we as FaceExpressionNet,pt as FaceExpressions,jt as FaceLandmark68Net,Ie as FaceLandmark68TinyNet,Vr as FaceLandmarkNet,$ as FaceLandmarks,vr as FaceLandmarks5,Lt as FaceLandmarks68,Kt as FaceMatch,ze as FaceMatcher,Ut as FaceRecognitionNet,rr as Gender,Qt as LabeledBox,Q as LabeledFaceDescriptors,rt as NetInput,I as NeuralNetwork,ct as ObjectDetection,b as Point,yr as PredictedBox,St as Rect,Pt as SsdMobilenetv1,z as SsdMobilenetv1Options,Zt as TinyFaceDetector,Le as TinyFaceDetectorOptions,Jt as TinyYolov2,J as TinyYolov2Options,ab as allFaces,an as allFacesSsdMobilenetv1,nb as allFacesTinyYolov2,_r as awaitMediaLoaded,Tr as bufferToImage,Vd as computeFaceDescriptor,Rt as createCanvas,be as createCanvasFromMedia,vl as createFaceDetectionNet,vf as createFaceRecognitionNet,Qo as createSsdMobilenetv1,Pb as createTinyFaceDetector,pd as createTinyYolov2,mr as detectAllFaces,on as detectFaceLandmarks,zd as detectFaceLandmarksTiny,eh as detectLandmarks,Kh as detectSingleFace,Ar as draw,T as env,lo as euclideanDistance,sr as extendWithAge,ar as extendWithFaceDescriptor,At as extendWithFaceDetection,tr as extendWithFaceExpressions,ie as extendWithFaceLandmarks,ir as extendWithGender,oe as extractFaceTensors,re as extractFaces,Mi as fetchImage,Fr as fetchJson,Li as fetchNetWeights,mt as fetchOrThrow,$i as fetchVideo,k as getContext2dOrThrow,Bt as getMediaDimensions,Pr as imageTensorToCanvas,wr as imageToSquare,Vn as inverseSigmoid,hr as iou,Qe as isMediaElement,he as isMediaLoaded,Pf as isWithAge,tt as isWithFaceDetection,Lr as isWithFaceExpressions,Yt as isWithFaceLandmarks,Ef as isWithGender,Kd as loadAgeGenderModel,Qd as loadFaceDetectionModel,Zd as loadFaceExpressionModel,Xd as loadFaceLandmarkModel,Jd as loadFaceLandmarkTinyModel,qd as loadFaceRecognitionModel,nn as loadSsdMobilenetv1Model,jd as loadTinyFaceDetectorModel,Ud as loadTinyYolov2Model,Er as loadWeightMap,th as locateFaces,ji as matchDimensions,br as minBbox,P as nets,gr as nonMaxSuppression,X as normalize,xr as padToSquare,Gd as predictAgeAndGender,Yd as recognizeFaceExpressions,sn as resizeResults,Wt as resolveInput,Hn as shuffleArray,fe as sigmoid,rn as ssdMobilenetv1,n as tf,Od as tinyFaceDetector,Hd as tinyYolov2,M as toNetInput,dr as utils,io as validateConfig,Ab as version}; diff --git a/dist/face-api.esm.js b/dist/face-api.esm.js index b7bb2df..5ac2717 100644 --- a/dist/face-api.esm.js +++ b/dist/face-api.esm.js @@ -4686,5 +4686,5 @@ return a / b;`,fne=` } `}};function 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Gse={kernelName:zl,backendName:"wasm",kernelFunc:Use};function Qu(e){let{inputs:{x:t},attrs:{dtype:n},backend:a}=e,r=a.makeOutput(t.shape,n),s=a.typedArrayFromHeap(t);return a.typedArrayFromHeap(r).set(s),r}var Hse={kernelName:Si,backendName:"wasm",kernelFunc:Qu},jse=rn(Ni),SE;function qse(e){SE=e.wasm.cwrap(hs,null,["number","number","number","number"])}function Kse(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{clipValueMin:s,clipValueMax:i}=a,o=n.dataIdMap.get(r.dataId).id,l=n.makeOutput(r.shape,r.dtype),u=n.dataIdMap.get(l.dataId).id;return SE(o,s,i,u),l}var Xse={kernelName:hs,backendName:"wasm",setupFunc:qse,kernelFunc:Kse};function NE(e){let{inputs:t,backend:n}=e,a=w.parseAxisParam(e.attrs.axis,t[0].shape)[0],r=C.computeOutShape(t.map(h=>h.shape),a),s=t.filter(h=>w.sizeFromShape(h.shape)>0);if(s.length===1)return ng({inputs:{x:s[0]},backend:n});let i=n.makeOutput(r,t[0].dtype);if(w.sizeFromShape(r)===0)return i;let o=s.map(h=>h.shape);if(C.assertParamsConsistent(o,a),s[0].dtype==="string"){let h=s.map(x=>{let v=w.sizeFromShape(x.shape.slice(a));return Vn({inputs:{x},backend:n,attrs:{shape:[-1,v]}})}),m=h.map(x=>({vals:n.readSync(x.dataId),shape:x.shape}));r=C.computeOutShape(h.map(x=>x.shape),1);let f=h[0].shape[0]===1,g=z0(m,r,t[0].dtype,f),y=C.computeOutShape(s.map(x=>x.shape),a);i.shape=y;let b=n.dataIdMap.get(i.dataId);return b.stringBytes=C.fromStringArrayToUint8(g),h.forEach(x=>n.disposeData(x.dataId)),i}let l=w.sizeFromShape(s[0].shape.slice(0,a)),u=0,p=s.map(h=>{let m=w.sizeFromShape(h.shape.slice(a));return u+=m,m}),d=s.map(h=>n.typedArrayFromHeap(h)),c=n.typedArrayFromHeap(i);for(let h=0;h`cumprod does not support ${r.dtype} tensors in the WASM backend`);let u=C.getAxesPermutation([s],l),p=r;u!==null&&(p=us({inputs:{x:r},attrs:{perm:u},backend:n}));let d=C.getInnerMostAxes(1,l)[0];C.assertAxesAreInnerMostDims("cumprod",[d],l);let c=n.makeOutput(p.shape,p.dtype),h=p.shape[d],m=n.dataIdMap.get(p.dataId).id,f=n.dataIdMap.get(c.dataId).id;EE(m,i?1:0,o?1:0,h,f,$t[r.dtype]);let g=c;if(u!==null){let y=C.getUndoAxesPermutation(u);g=us({inputs:{x:c},attrs:{perm:y},backend:n}),n.disposeData(p.dataId),n.disposeData(c.dataId)}return g}var pie={kernelName:Wl,backendName:"wasm",setupFunc:lie,kernelFunc:uie},AE;function cie(e){AE=e.wasm.cwrap(Ai,null,["number","number","number","number","number","number"])}function die(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=a,l=r.shape.length;w.assert(r.dtype==="float32"||r.dtype==="int32",()=>`cumsum does not support ${r.dtype} tensors in the WASM backend`);let u=C.getAxesPermutation([s],l),p=r;u!==null&&(p=us({inputs:{x:r},attrs:{perm:u},backend:n}));let d=C.getInnerMostAxes(1,l)[0];C.assertAxesAreInnerMostDims("cumsum",[d],l);let c=n.makeOutput(p.shape,p.dtype),h=p.shape[d],m=n.dataIdMap.get(p.dataId).id,f=n.dataIdMap.get(c.dataId).id;AE(m,i?1:0,o?1:0,h,f,$t[r.dtype]);let g=c;if(u!==null){let y=C.getUndoAxesPermutation(u);g=us({inputs:{x:c},attrs:{perm:y},backend:n}),n.disposeData(p.dataId),n.disposeData(c.dataId)}return g}var hie={kernelName:Ai,backendName:"wasm",setupFunc:cie,kernelFunc:die},$E;function mie(e){$E=e.wasm.cwrap(Ul,null,["number","number","number","array","number","array","array","number","number"])}function fie(e){let{backend:t,inputs:n,attrs:a}=e,{x:r}=n,{blockSize:s,dataFormat:i}=a,o=r.shape[0],l=i==="NHWC"?r.shape[1]:r.shape[2],u=i==="NHWC"?r.shape[2]:r.shape[3],p=i==="NHWC"?r.shape[3]:r.shape[1],d=l*s,c=u*s,h=p/(s*s),m=i==="NHWC"?[o,d,c,h]:[o,h,d,c],f=t.makeOutput(m,"float32"),g=t.dataIdMap.get(r.dataId).id,y=new Uint8Array(new Int32Array(w.computeStrides(r.shape)).buffer),b=new Uint8Array(new Int32Array(m).buffer),x=new Uint8Array(new Int32Array(w.computeStrides(m)).buffer),v=t.dataIdMap.get(f.dataId).id;return $E(g,s,i==="NHWC"?1:0,y,r.shape.length-1,b,x,m.length,v),f}var gie={kernelName:Ul,backendName:"wasm",setupFunc:mie,kernelFunc:fie},FE;function yie(e){FE=e.wasm.cwrap($i,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function bie(e){let{inputs:t,attrs:n,backend:a}=e,{x:r,filter:s}=t,i=a.dataIdMap.get(r.dataId).id,o=a.dataIdMap.get(s.dataId).id,{strides:l,dilations:u,pad:p,dimRoundingMode:d}=n,c=u==null?[1,1]:u,h=C.computeConv2DInfo(r.shape,s.shape,l,c,p,d,!0),m=h.filterHeight,f=h.filterWidth,g=h.padInfo.top,y=h.padInfo.right,b=h.padInfo.bottom,x=h.padInfo.left,v=h.dilationHeight,I=h.dilationWidth,T=h.strideHeight,_=h.strideWidth,A=h.inChannels,F=h.outChannels,P=h.padInfo.type==="SAME"?1:0;if(h.dataFormat!=="channelsLast")throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${h.dataFormat}'. Please use 'channelsLast'.`);let $=a.makeOutput(h.outShape,"float32"),S=a.dataIdMap.get($.dataId).id;return FE(i,r.shape[0],r.shape[1],r.shape[2],o,m,f,g,y,b,x,P,v,I,T,_,A,F,S),$}var xie={kernelName:$i,backendName:"wasm",setupFunc:yie,kernelFunc:bie},vie=rn(Di),wie=!1,kie=cn(Hl,wie,"bool"),Iie=rn(Ri,"float32");function Cx(e){let{inputs:t,attrs:n,backend:a}=e,{input:r}=t,{dim:s}=n,i=r.shape.length,o=r.shape.slice(),l=s;return s<0&&(w.assert(-(i+1)<=s,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+s+1),o.splice(l,0,1),Vn({inputs:{x:r},backend:a,attrs:{shape:o}})}var Sie={kernelName:jl,backendName:"wasm",kernelFunc:Cx};function DE(e){let{attrs:{shape:t,value:n,dtype:a},backend:r}=e,s=r.makeOutput(t,a);return r.typedArrayFromHeap(s).fill(n),s}var Nie={kernelName:wc,backendName:"wasm",kernelFunc:DE},RE;function Tie(e){RE=e.wasm.cwrap(Kl,null,["number","number","number","number","number","number"])}function Cie(e){let{inputs:t,backend:n}=e,{image:a}=t,r=n.makeOutput(a.shape,a.dtype),s=n.dataIdMap.get(a.dataId).id,i=n.dataIdMap.get(r.dataId).id,[o,l,u,p]=a.shape;return RE(s,o,l,u,p,i),r}var _ie={kernelName:Kl,backendName:"wasm",kernelFunc:Cie,setupFunc:Tie},Eie=rn(Mi),Aie=!1,$ie=cn(Pi,Aie),ME;function Fie(e){ME=e.wasm.cwrap(Oi,null,["number","number","number","number","number","number","number"])}function Die(e){let{backend:t,inputs:n,attrs:a}=e,{varianceEpsilon:r}=a,{x:s,mean:i,variance:o,offset:l,scale:u}=n,p=t.dataIdMap.get(s.dataId).id,d=t.dataIdMap.get(i.dataId).id,c=t.dataIdMap.get(o.dataId).id,h=l!=null?t.dataIdMap.get(l.dataId).id:0,m=u!=null?t.dataIdMap.get(u.dataId).id:0,f=t.makeOutput(s.shape,s.dtype);if(w.sizeFromShape(s.shape)===0)return f;let g=t.dataIdMap.get(f.dataId).id;return ME(p,d,c,h,m,r,g),f}var Rie={kernelName:Oi,backendName:"wasm",setupFunc:Fie,kernelFunc:Die},PE;function Mie(e){PE=e.wasm.cwrap(si,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Pie(e){let{inputs:t,attrs:n,backend:a}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:p,dataFormat:d,dimRoundingMode:c,activation:h,leakyreluAlpha:m}=n,f=C.computeConv2DInfo(r.shape,s.shape,l,p,u,c),g=mc[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedConv2D in the wasm backend.`);let y=a.dataIdMap.get(r.dataId).id,b=a.dataIdMap.get(s.dataId).id,x=f.outChannels,v=0;if(i!=null){let ae=a.dataIdMap.get(i.dataId);if(ae.shape.length!==1)throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${ae.shape.length}.`);if(ae.shape[0]!==x)throw new Error(`FusedConv2D bias shape (${ae.shape}) does not match the number of output channels (${x})`);v=ae.id}let I=f.filterHeight,T=f.filterWidth,_=f.padInfo.top,A=f.padInfo.right,F=f.padInfo.bottom,P=f.padInfo.left,$=f.dilationHeight,S=f.dilationWidth,M=f.strideHeight,U=f.strideWidth,j=f.inChannels,q=f.padInfo.type==="SAME"?1:0,K=f.batchSize,Y=f.inHeight,te=f.inWidth;if(d!=="NHWC")throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${d}'. Please use 'NHWC'.`);let re=a.makeOutput(f.outShape,"float32"),Q=a.dataIdMap.get(re.dataId).id,ie=o==null?0:a.dataIdMap.get(o.dataId).id;return PE(y,K,Y,te,b,I,T,v,_,A,F,P,q,$,S,M,U,j,x,g,ie,m||0,Q),re}var Oie={kernelName:si,backendName:"wasm",setupFunc:Mie,kernelFunc:Pie},OE;function Lie(e){OE=e.wasm.cwrap(ii,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function zie(e){let{inputs:t,attrs:n,backend:a}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:p,dataFormat:d,dimRoundingMode:c,activation:h,leakyreluAlpha:m}=n,f=C.computeConv2DInfo(r.shape,s.shape,l,p,u,c,!0),g=mc[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedDepthwiseConv2D in the wasm backend.`);let y=a.dataIdMap.get(r.dataId).id,b=a.dataIdMap.get(s.dataId).id,x=f.outChannels,v=0;if(i!=null){let ae=a.dataIdMap.get(i.dataId);if(ae.shape.length!==1)throw new Error(`FusedDepthwiseConv2D only supports rank-1 bias but got rank ${ae.shape.length}.`);if(ae.shape[0]!==x)throw new Error(`FusedDepthwiseConv2D bias shape (${ae.shape}) does not match the number of output channels (${x})`);v=ae.id}let I=f.filterHeight,T=f.filterWidth,_=f.padInfo.top,A=f.padInfo.right,F=f.padInfo.bottom,P=f.padInfo.left,$=f.dilationHeight,S=f.dilationWidth,M=f.strideHeight,U=f.strideWidth,j=f.inChannels,q=f.padInfo.type==="SAME"?1:0,K=f.batchSize,Y=f.inHeight,te=f.inWidth;if(d!=="NHWC")throw new Error(`wasm backend FusedDepthwiseConv2D does not support dataFormat:'${d}'. Please use 'NHWC'.`);let re=a.makeOutput(f.outShape,"float32"),Q=a.dataIdMap.get(re.dataId).id,ie=o==null?0:a.dataIdMap.get(o.dataId).id;return OE(y,K,Y,te,b,I,T,v,_,A,F,P,q,$,S,M,U,j,x,g,ie,m||0,Q),re}var Bie={kernelName:ii,backendName:"wasm",setupFunc:Lie,kernelFunc:zie},LE;function Wie(e){LE=e.wasm.cwrap(Yl,null,["number","number","number","number","number","number","array","number"])}function Vie(e){let{backend:t,inputs:n}=e,{params:a,indices:r}=n,[s,i,o,l]=Kx.prepareAndValidate(a,r),u=t.makeOutput(s,a.dtype);if(i===0)return u;let p=r.shape,d=p[p.length-1],c=t.dataIdMap.get(a.dataId).id,h=t.dataIdMap.get(r.dataId).id,m=new Uint8Array(new Int32Array(l).buffer),f=t.dataIdMap.get(u.dataId).id;return LE(c,$t[a.dtype],h,i,d,o,m,f),u}var Uie={kernelName:Yl,backendName:"wasm",setupFunc:Wie,kernelFunc:Vie},zE;function Gie(e){zE=e.wasm.cwrap("Gather",null,["number","number","array","number","number","number","array","number"])}function Hie(e){let{backend:t,inputs:n,attrs:a}=e,{x:r,indices:s}=n,{axis:i,batchDims:o}=a,l=w.parseAxisParam(i,r.shape)[0],u=t.readSync(s.dataId),p=r.shape[l];for(let _=0;_=0,()=>`GatherV2: the index value ${A} is not in [0, ${p-1}]`)}let d=C.segment_util.collectGatherOpShapeInfo(r,s,l,o),c=Vn({inputs:{x:r},attrs:{shape:[d.batchSize,d.outerSize,d.dimSize,d.sliceSize]},backend:t}),h=w.sizeFromShape(s.shape),m=Vn({inputs:{x:s},attrs:{shape:[d.batchSize,h/d.batchSize]},backend:t}),f=[d.batchSize,d.outerSize,h/d.batchSize,d.sliceSize],g=t.makeOutput(f,r.dtype);if(w.sizeFromShape(r.shape)===0)return g;let y=c.shape.length-1,b=t.dataIdMap.get(c.dataId).id,x=t.dataIdMap.get(m.dataId).id,v=t.dataIdMap.get(g.dataId).id,I=new Uint8Array(new Int32Array(w.computeStrides(c.shape)).buffer),T=new Uint8Array(new Int32Array(w.computeStrides(f)).buffer);return zE(b,$t[r.dtype],I,y,x,d.batchSize,T,v),t.disposeData(c.dataId),t.disposeData(m.dataId),g.shape=d.outputShape,g}var jie={kernelName:Xl,backendName:"wasm",setupFunc:Gie,kernelFunc:Hie},qie=!1,Kie=cn(Jl,qie,"bool"),Xie=!1,Yie=cn(Li,Xie,"bool"),BE;function Jie(e){BE=e.wasm.cwrap(Bi,null,["number","number","number","number"])}function Zie(e){let{inputs:{x:t},attrs:{alpha:n},backend:a}=e,r=a.dataIdMap.get(t.dataId).id,s=a.makeOutput(t.shape,"float32");if(w.sizeFromShape(t.shape)!==0){let i=a.dataIdMap.get(s.dataId).id;BE(r,$t[t.dtype],n,i)}return s}var Qie={kernelName:Bi,backendName:"wasm",setupFunc:Jie,kernelFunc:Zie},eoe=!1,toe=cn(tu,eoe,"bool"),noe=!1,aoe=cn(nu,noe,"bool"),roe=rn(Wi),soe=!1,ioe=cn(ru,soe,"bool"),ooe=rn(su),loe=!1,uoe=cn(iu,loe,"bool"),poe=!1,coe=cn(BI,poe,"bool"),WE;function doe(e){WE=e.wasm.cwrap(Vi,null,["number","number","number","number"])}function hoe(e){let{backend:t,inputs:n,attrs:a}=e,{reductionIndices:r,keepDims:s}=a,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:u,axes:p,originalAxes:d,inputWasTransposed:c}=Ts(i,r,t);if(c){let b=t.dataIdMap.get(u.dataId).id;l=u,o=b}let h=l.shape.length;C.assertAxesAreInnerMostDims("max",p,h);let[m,f]=C.computeOutAndReduceShapes(l.shape,p),g=w.sizeFromShape(f),y=t.makeOutput(m,i.dtype);if(w.sizeFromShape(l.shape)!==0){let b=t.dataIdMap.get(y.dataId).id;WE(o,$t[i.dtype],g,b)}if(c&&t.disposeData(u.dataId),s){let b=C.expandShapeToKeepDim(y.shape,d);y.shape=b}return y}var moe={kernelName:Vi,backendName:"wasm",setupFunc:doe,kernelFunc:hoe},foe=!1,goe=cn(Ui,foe),VE;function yoe(e){VE=e.wasm.cwrap(Gi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function boe(e){let{inputs:t,attrs:n,backend:a}=e,r=t.x,s=a.dataIdMap.get(r.dataId).id;w.assert(r.dtype==="float32",()=>`Error in MaxPool: only float32 input is supported. Got ${r.dtype}.`);let{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n,p=C.computePool2DInfo(r.shape,i,o,1,l,u),d=p.filterHeight,c=p.filterWidth,h=p.padInfo.top,m=p.padInfo.right,f=p.padInfo.bottom,g=p.padInfo.left,y=p.dilationHeight,b=p.dilationWidth,x=p.strideHeight,v=p.strideWidth,I=p.inChannels,T=p.outChannels;if(p.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${p.dataFormat}'. 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v=C.expandShapeToKeepDim(x.shape,c);x.shape=v}return u.dtype!=="float32"&&t.disposeData(b.dataId),x}var koe={kernelName:Hi,backendName:"wasm",setupFunc:voe,kernelFunc:woe},GE;function Ioe(e){GE=e.wasm.cwrap(ji,null,["number","number","number","number"])}function Soe(e){let{backend:t,inputs:n,attrs:a}=e,{axis:r,keepDims:s}=a,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:p,axes:d,originalAxes:c,inputWasTransposed:h}=Ts(i,r,t);if(h){let x=t.dataIdMap.get(p.dataId).id;x!==o&&(u=p,l=x)}let m=u.shape.length;C.assertAxesAreInnerMostDims("min",d,m);let[f,g]=C.computeOutAndReduceShapes(u.shape,d),y=w.sizeFromShape(g),b=t.makeOutput(f,u.dtype);if(w.sizeFromShape(u.shape)!==0){let x=t.dataIdMap.get(b.dataId).id;GE(l,$t[i.dtype],y,x)}if(h&&t.disposeData(p.dataId),s){let x=C.expandShapeToKeepDim(b.shape,c);b.shape=x}return b}var 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Voe={kernelName:du,backendName:"wasm",setupFunc:Boe,kernelFunc:Woe},Uoe=!1,Goe=cn(uu,Uoe,"bool"),XE;function Hoe(e){XE=e.wasm.cwrap(Yi,null,["number","number","number","number","number"])}function joe(e){let{inputs:t,backend:n,attrs:a}=e,{indices:r}=t,{depth:s,onValue:i,offValue:o}=a,l=n.makeOutput([...r.shape,s],"int32"),u=n.dataIdMap.get(l.dataId).id,p=n.dataIdMap.get(r.dataId).id;return XE(p,s,i,o,u),l}var qoe={kernelName:Yi,backendName:"wasm",setupFunc:Hoe,kernelFunc:joe};function Koe(e){let{inputs:{x:t},backend:n}=e,a=n.makeOutput(t.shape,t.dtype);return n.typedArrayFromHeap(a).fill(1),a}var Xoe={kernelName:hu,backendName:"wasm",kernelFunc:Koe};function Yoe(e){let{inputs:t,backend:n,attrs:a}=e,{axis:r}=a;if(t.length===1)return Cx({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let s=t[0].shape,i=t[0].dtype;t.forEach(p=>{w.assertShapesMatch(s,p.shape,"All tensors passed to stack must have matching shapes"),w.assert(i===p.dtype,()=>"All tensors passed to stack must have matching 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this.shiftBy(s.x,s.y).align(null,n)}let{useDlibAlignment:a,minBoxPadding:r}={useDlibAlignment:!1,minBoxPadding:.2,...n};return a?this.alignDlib():this.alignMinBbox(r)}alignDlib(){let t=this.getRefPointsForAlignment(),[n,a,r]=t,s=d=>r.sub(d).magnitude(),i=(s(n)+s(a))/2,o=Math.floor(i/lpe),l=Ao(t),u=Math.floor(Math.max(0,l.x-ipe*o)),p=Math.floor(Math.max(0,l.y-ope*o));return new np(u,p,Math.min(o,this.imageWidth+u),Math.min(o,this.imageHeight+p))}alignMinBbox(t){let n=IA(this.positions);return n.pad(n.width*t,n.height*t)}getRefPointsForAlignment(){throw new Error("getRefPointsForAlignment not implemented by base class")}};var TA=class extends xa{getRefPointsForAlignment(){let t=this.positions;return[t[0],t[1],Ao([t[3],t[4]])]}};var ap=class extends xa{getJawOutline(){return this.positions.slice(0,17)}getLeftEyeBrow(){return this.positions.slice(17,22)}getRightEyeBrow(){return this.positions.slice(22,27)}getNose(){return this.positions.slice(27,36)}getLeftEye(){return 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y1()?b1(f1()):bd()?b1(g1()):null}function ppe(e){if(sn||x1(),!sn)throw new Error("monkeyPatch - environment is not defined, check isNodejs() and isBrowser()");let{Canvas:t=sn.Canvas,Image:n=sn.Image}=e;sn.Canvas=t,sn.Image=n,sn.createCanvasElement=e.createCanvasElement||(()=>new t),sn.createImageElement=e.createImageElement||(()=>new n),sn.ImageData=e.ImageData||sn.ImageData,sn.Video=e.Video||sn.Video,sn.fetch=e.fetch||sn.fetch,sn.readFile=e.readFile||sn.readFile}var at={getEnv:upe,setEnv:b1,initialize:x1,createBrowserEnv:f1,createFileSystem:ig,createNodejsEnv:g1,monkeyPatch:ppe,isBrowser:y1,isNodejs:bd};x1();function sp(e){return!at.isNodejs()&&typeof e=="string"?document.getElementById(e):e}function aa(e){let{Canvas:t,CanvasRenderingContext2D:n}=at.getEnv();if(e instanceof n)return e;let a=sp(e);if(!(a instanceof t))throw new Error("resolveContext2d - expected canvas to be of instance of Canvas");let r=a.getContext("2d");if(!r)throw new Error("resolveContext2d - canvas 2d context is 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ip({...i,...s})}},xd=class{constructor(t,n={}){this.box=new ct(t),this.options=new og(n)}draw(t){let n=aa(t),{boxColor:a,lineWidth:r}=this.options,{x:s,y:i,width:o,height:l}=this.box;n.strokeStyle=a,n.lineWidth=r,n.strokeRect(s,i,o,l);let{label:u}=this.options;u&&new Or([u],{x:s-r/2,y:i},this.options.drawLabelOptions).draw(t)}};function cpe(e,t){(Array.isArray(t)?t:[t]).forEach(a=>{let r=a instanceof wt?a.score:Pr(a)?a.detection.score:void 0,s=a instanceof wt?a.box:Pr(a)?a.detection.box:new ct(a),i=r?`${Eo(r)}`:void 0;new xd(s,{label:i}).draw(e)})}function lg(e){let{Image:t,Video:n}=at.getEnv();return e instanceof t&&e.complete||e instanceof n&&e.readyState>=3}function _A(e){return new Promise((t,n)=>{(e instanceof at.getEnv().Canvas||lg(e))&&t(null);function a(s){!s.currentTarget||(s.currentTarget.removeEventListener("load",r),s.currentTarget.removeEventListener("error",a),n(s))}function 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Lr=class{constructor(t,n=!1){this._imageTensors=[];this._canvases=[];this._treatAsBatchInput=!1;this._inputDimensions=[];this._inputSize=0;if(!Array.isArray(t))throw new Error(`NetInput.constructor - expected inputs to be an Array of TResolvedNetInput or to be instanceof tf.Tensor4D, instead have ${t}`);this._treatAsBatchInput=n,this._batchSize=t.length,t.forEach((a,r)=>{if(Rr(a)){this._imageTensors[r]=a,this._inputDimensions[r]=a.shape;return}if(ba(a)){let i=a.shape[0];if(i!==1)throw new Error(`NetInput - tf.Tensor4D with batchSize ${i} passed, but not supported in input array`);this._imageTensors[r]=a,this._inputDimensions[r]=a.shape.slice(1);return}let s=a instanceof at.getEnv().Canvas?a:ug(a);this._canvases[r]=s,this._inputDimensions[r]=[s.height,s.width,3]})}get imageTensors(){return this._imageTensors}get canvases(){return this._canvases}get isBatchInput(){return this.batchSize>1||this._treatAsBatchInput}get batchSize(){return this._batchSize}get inputDimensions(){return 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a=le(t.toBatchTensor(112,!0),"float32"),s=yr(a,[122.782,117.001,104.298]).div(255),i=kd(s,n.dense0,!0);return i=kd(i,n.dense1),i=kd(i,n.dense2),i=kd(i,n.dense3),i=fa(i,[7,7],[2,2],"valid"),i})}async forward(t){return this.forwardInput(await kt(t))}getDefaultModelName(){return"face_feature_extractor_model"}extractParamsFromWeightMap(t){return PA(t)}extractParams(t){return MA(t)}};function Sd(e,t){return O(()=>Z(Re(e,t.weights),t.bias))}function OA(e,t,n){let a=[],{extractWeights:r,getRemainingWeights:s}=Dn(e),o=dg(r,a)(t,n,"fc");if(s().length!==0)throw new Error(`weights remaing after extract: ${s().length}`);return{paramMappings:a,params:{fc:o}}}function LA(e){let t=[],n=ra(e,t);function a(s){let i=n(`${s}/weights`,2),o=n(`${s}/bias`,1);return{weights:i,bias:o}}let r={fc:a("fc")};return Fn(e,t),{params:r,paramMappings:t}}function gg(e){let t={},n={};return Object.keys(e).forEach(a=>{let r=a.startsWith("fc")?n:t;r[a]=e[a]}),{featureExtractorMap:t,classifierMap:n}}var hp=class extends dn{constructor(n,a){super(n);this._faceFeatureExtractor=a}get faceFeatureExtractor(){return this._faceFeatureExtractor}runNet(n){let{params:a}=this;if(!a)throw new Error(`${this._name} - load model before inference`);return O(()=>{let r=n instanceof Lr?this.faceFeatureExtractor.forwardInput(n):n;return Sd(r.as2D(r.shape[0],-1),a.fc)})}dispose(n=!0){this.faceFeatureExtractor.dispose(n),super.dispose(n)}loadClassifierParams(n){let{params:a,paramMappings:r}=this.extractClassifierParams(n);this._params=a,this._paramMappings=r}extractClassifierParams(n){return OA(n,this.getClassifierChannelsIn(),this.getClassifierChannelsOut())}extractParamsFromWeightMap(n){let{featureExtractorMap:a,classifierMap:r}=gg(n);return this.faceFeatureExtractor.loadFromWeightMap(a),LA(r)}extractParams(n){let a=this.getClassifierChannelsIn(),r=this.getClassifierChannelsOut(),s=r*a+r,i=n.slice(0,n.length-s),o=n.slice(n.length-s);return this.faceFeatureExtractor.extractWeights(i),this.extractClassifierParams(o)}};var zA=["neutral","happy","sad","angry","fearful","disgusted","surprised"],Es=class{constructor(t){this.neutral=0;this.happy=0;this.sad=0;this.angry=0;this.fearful=0;this.disgusted=0;this.surprised=0;if(t.length!==7)throw new Error(`FaceExpressions.constructor - expected probabilities.length to be 7, have: ${t.length}`);zA.forEach((n,a)=>{this[n]=t[a]})}asSortedArray(){return zA.map(t=>({expression:t,probability:this[t]})).sort((t,n)=>n.probability-t.probability)}};var yg=class extends hp{constructor(t=new dp){super("FaceExpressionNet",t)}forwardInput(t){return O(()=>Za(this.runNet(t)))}async forward(t){return this.forwardInput(await kt(t))}async predictExpressions(t){let n=await kt(t),a=await this.forwardInput(n),r=await Promise.all(mt(a).map(async i=>{let o=i.dataSync();return i.dispose(),o}));a.dispose();let s=r.map(i=>new Es(i));return n.isBatchInput?s:s[0]}getDefaultModelName(){return"face_expression_model"}getClassifierChannelsIn(){return 256}getClassifierChannelsOut(){return 7}};function BA(e){return e.expressions instanceof Es}function k1(e,t){return{...e,...{expressions:t}}}function dpe(e,t,n=.1,a){(Array.isArray(t)?t:[t]).forEach(s=>{let i=s instanceof Es?s:BA(s)?s.expressions:void 0;if(!i)throw new Error("drawFaceExpressions - expected faceExpressions to be FaceExpressions | WithFaceExpressions<{}> or array thereof");let l=i.asSortedArray().filter(d=>d.probability>n),u=Pr(s)?s.detection.box.bottomLeft:a||new Oe(0,0);new Or(l.map(d=>`${d.expression} (${Eo(d.probability)})`),u).draw(e)})}function mp(e){return Pr(e)&&e.landmarks instanceof xa&&e.unshiftedLandmarks instanceof xa&&e.alignedRect instanceof wt}function hpe(e){let t=(o,l,u,p)=>Math.atan2(p-l,u-o)%Math.PI,n=o=>o*180/Math.PI,a={roll:void 0,pitch:void 0,yaw:void 0};if(!e||!e._positions||e._positions.length!==68)return a;let r=e._positions;a.roll=-t(r[36]._x,r[36]._y,r[45]._x,r[45]._y),a.pitch=t(0,Math.abs(r[0]._x-r[30]._x)/r[30]._x,Math.PI,Math.abs(r[16]._x-r[30]._x)/r[30]._x);let s=r.reduce((o,l)=>oo>l._y?o:l._y,-1/0);return a.yaw=Math.PI*(e._imgDims._height/(i-s)/1.4-1),a}function Nd(e,t){let{box:n}=e.detection,a=t.shiftBy(n.x,n.y),r=a.align(),{imageDims:s}=e.detection,i=new wt(e.detection.score,r.rescale(s.reverse()),s),o=hpe(t);return{...e,...{landmarks:a,unshiftedLandmarks:t,alignedRect:i,angle:o}}}var bg=class{constructor(t={}){let{drawLines:n=!0,drawPoints:a=!0,lineWidth:r,lineColor:s,pointSize:i,pointColor:o}=t;this.drawLines=n,this.drawPoints=a,this.lineWidth=r||1,this.pointSize=i||2,this.lineColor=s||"rgba(0, 255, 255, 1)",this.pointColor=o||"rgba(255, 0, 255, 1)"}},xg=class{constructor(t,n={}){this.faceLandmarks=t,this.options=new bg(n)}draw(t){let n=aa(t),{drawLines:a,drawPoints:r,lineWidth:s,lineColor:i,pointSize:o,pointColor:l}=this.options;if(a&&this.faceLandmarks instanceof ap&&(n.strokeStyle=i,n.lineWidth=s,Dr(n,this.faceLandmarks.getJawOutline()),Dr(n,this.faceLandmarks.getLeftEyeBrow()),Dr(n,this.faceLandmarks.getRightEyeBrow()),Dr(n,this.faceLandmarks.getNose()),Dr(n,this.faceLandmarks.getLeftEye(),!0),Dr(n,this.faceLandmarks.getRightEye(),!0),Dr(n,this.faceLandmarks.getMouth(),!0)),r){n.strokeStyle=l,n.fillStyle=l;let u=p=>{n.beginPath(),n.arc(p.x,p.y,o,0,2*Math.PI),n.fill()};this.faceLandmarks.positions.forEach(u)}}};function mpe(e,t){(Array.isArray(t)?t:[t]).forEach(a=>{let r=a instanceof xa?a:mp(a)?a.landmarks:void 0;if(!r)throw new Error("drawFaceLandmarks - expected faceExpressions to be FaceLandmarks | WithFaceLandmarks> or array thereof");new xg(r).draw(e)})}var VA="1.7.1";function ype(e,t){let n=up(e,t),a=pp(e,t);function r(i,o,l){let u=a(i,o,`${l}/separable_conv0`),p=a(o,o,`${l}/separable_conv1`),d=n(i,o,1,`${l}/expansion_conv`);return{separable_conv0:u,separable_conv1:p,expansion_conv:d}}function s(i,o){let l=a(i,i,`${o}/separable_conv0`),u=a(i,i,`${o}/separable_conv1`),p=a(i,i,`${o}/separable_conv2`);return{separable_conv0:l,separable_conv1:u,separable_conv2:p}}return{extractConvParams:n,extractSeparableConvParams:a,extractReductionBlockParams:r,extractMainBlockParams:s}}function UA(e,t){let n=[],{extractWeights:a,getRemainingWeights:r}=Dn(e),{extractConvParams:s,extractSeparableConvParams:i,extractReductionBlockParams:o,extractMainBlockParams:l}=ype(a,n),u=s(3,32,3,"entry_flow/conv_in"),p=o(32,64,"entry_flow/reduction_block_0"),d=o(64,128,"entry_flow/reduction_block_1"),c={conv_in:u,reduction_block_0:p,reduction_block_1:d},h={};gr(t,0,1).forEach(y=>{h[`main_block_${y}`]=l(128,`middle_flow/main_block_${y}`)});let m=o(128,256,"exit_flow/reduction_block"),f=i(256,512,"exit_flow/separable_conv"),g={reduction_block:m,separable_conv:f};if(r().length!==0)throw new Error(`weights remaing after extract: ${r().length}`);return{paramMappings:n,params:{entry_flow:c,middle_flow:h,exit_flow:g}}}function bpe(e,t){let n=ra(e,t),a=mg(n),r=cp(n);function s(o){let l=r(`${o}/separable_conv0`),u=r(`${o}/separable_conv1`),p=a(`${o}/expansion_conv`);return{separable_conv0:l,separable_conv1:u,expansion_conv:p}}function i(o){let l=r(`${o}/separable_conv0`),u=r(`${o}/separable_conv1`),p=r(`${o}/separable_conv2`);return{separable_conv0:l,separable_conv1:u,separable_conv2:p}}return{extractConvParams:a,extractSeparableConvParams:r,extractReductionBlockParams:s,extractMainBlockParams:i}}function GA(e,t){let n=[],{extractConvParams:a,extractSeparableConvParams:r,extractReductionBlockParams:s,extractMainBlockParams:i}=bpe(e,n),o=a("entry_flow/conv_in"),l=s("entry_flow/reduction_block_0"),u=s("entry_flow/reduction_block_1"),p={conv_in:o,reduction_block_0:l,reduction_block_1:u},d={};gr(t,0,1).forEach(f=>{d[`main_block_${f}`]=i(`middle_flow/main_block_${f}`)});let c=s("exit_flow/reduction_block"),h=r("exit_flow/separable_conv"),m={reduction_block:c,separable_conv:h};return Fn(e,n),{params:{entry_flow:p,middle_flow:d,exit_flow:m},paramMappings:n}}function HA(e,t,n){return Z(Dt(e,t.filters,n,"same"),t.bias)}function I1(e,t,n=!0){let a=n?Xe(e):e;return a=Kn(a,t.separable_conv0,[1,1]),a=Kn(Xe(a),t.separable_conv1,[1,1]),a=Mt(a,[3,3],[2,2],"same"),a=Z(a,HA(e,t.expansion_conv,[2,2])),a}function xpe(e,t){let n=Kn(Xe(e),t.separable_conv0,[1,1]);return n=Kn(Xe(n),t.separable_conv1,[1,1]),n=Kn(Xe(n),t.separable_conv2,[1,1]),n=Z(n,e),n}var vg=class extends dn{constructor(n){super("TinyXception");this._numMainBlocks=n}forwardInput(n){let{params:a}=this;if(!a)throw new Error("TinyXception - load model before inference");return O(()=>{let r=le(n.toBatchTensor(112,!0),"float32"),i=yr(r,[122.782,117.001,104.298]).div(255),o=Xe(HA(i,a.entry_flow.conv_in,[2,2]));return o=I1(o,a.entry_flow.reduction_block_0,!1),o=I1(o,a.entry_flow.reduction_block_1),gr(this._numMainBlocks,0,1).forEach(l=>{o=xpe(o,a.middle_flow[`main_block_${l}`])}),o=I1(o,a.exit_flow.reduction_block),o=Xe(Kn(o,a.exit_flow.separable_conv,[1,1])),o})}async forward(n){return this.forwardInput(await kt(n))}getDefaultModelName(){return"tiny_xception_model"}extractParamsFromWeightMap(n){return GA(n,this._numMainBlocks)}extractParams(n){return UA(n,this._numMainBlocks)}};function jA(e){let t=[],{extractWeights:n,getRemainingWeights:a}=Dn(e),r=dg(n,t),s=r(512,1,"fc/age"),i=r(512,2,"fc/gender");if(a().length!==0)throw new Error(`weights remaing after extract: ${a().length}`);return{paramMappings:t,params:{fc:{age:s,gender:i}}}}function qA(e){let t=[],n=ra(e,t);function a(s){let i=n(`${s}/weights`,2),o=n(`${s}/bias`,1);return{weights:i,bias:o}}let r={fc:{age:a("fc/age"),gender:a("fc/gender")}};return Fn(e,t),{params:r,paramMappings:t}}var S1=(n=>(n.FEMALE="female",n.MALE="male",n))(S1||{});var wg=class extends dn{constructor(n=new vg(2)){super("AgeGenderNet");this._faceFeatureExtractor=n}get faceFeatureExtractor(){return this._faceFeatureExtractor}runNet(n){let{params:a}=this;if(!a)throw new Error(`${this._name} - load model before inference`);return O(()=>{let r=n instanceof Lr?this.faceFeatureExtractor.forwardInput(n):n,s=fa(r,[7,7],[2,2],"valid").as2D(r.shape[0],-1),i=Sd(s,a.fc.age).as1D(),o=Sd(s,a.fc.gender);return{age:i,gender:o}})}forwardInput(n){return O(()=>{let{age:a,gender:r}=this.runNet(n);return{age:a,gender:Za(r)}})}async forward(n){return this.forwardInput(await kt(n))}async predictAgeAndGender(n){let a=await kt(n),r=await this.forwardInput(a),s=mt(r.age),i=mt(r.gender),o=s.map((u,p)=>({ageTensor:u,genderTensor:i[p]})),l=await Promise.all(o.map(async({ageTensor:u,genderTensor:p})=>{let d=u.dataSync()[0],c=p.dataSync()[0],h=c>.5,m=h?"male":"female",f=h?c:1-c;return u.dispose(),p.dispose(),{age:d,gender:m,genderProbability:f}}));return r.age.dispose(),r.gender.dispose(),a.isBatchInput?l:l[0]}getDefaultModelName(){return"age_gender_model"}dispose(n=!0){this.faceFeatureExtractor.dispose(n),super.dispose(n)}loadClassifierParams(n){let{params:a,paramMappings:r}=this.extractClassifierParams(n);this._params=a,this._paramMappings=r}extractClassifierParams(n){return jA(n)}extractParamsFromWeightMap(n){let{featureExtractorMap:a,classifierMap:r}=gg(n);return this.faceFeatureExtractor.loadFromWeightMap(a),qA(r)}extractParams(n){let r=n.slice(0,n.length-1539),s=n.slice(n.length-1539);return this.faceFeatureExtractor.extractWeights(r),this.extractClassifierParams(s)}};var fp=class extends hp{postProcess(t,n,a){let r=a.map(({width:i,height:o})=>{let l=n/Math.max(o,i);return{width:i*l,height:o*l}}),s=r.length;return O(()=>{let i=(d,c)=>Rt([En([68],d,"float32"),En([68],c,"float32")],1).as2D(1,136).as1D(),o=(d,c)=>{let{width:h,height:m}=r[d];return 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t=[],{extractDenseBlock3Params:n}=fg(e,t),a={dense0:n("dense0",!0),dense1:n("dense1"),dense2:n("dense2")};return Fn(e,t),{params:a,paramMappings:t}}function XA(e){let t=[],{extractWeights:n,getRemainingWeights:a}=Dn(e),{extractDenseBlock3Params:r}=hg(n,t),s=r(3,32,"dense0",!0),i=r(32,64,"dense1"),o=r(64,128,"dense2");if(a().length!==0)throw new Error(`weights remaing after extract: ${a().length}`);return{paramMappings:t,params:{dense0:s,dense1:i,dense2:o}}}var kg=class extends dn{constructor(){super("TinyFaceFeatureExtractor")}forwardInput(t){let{params:n}=this;if(!n)throw new Error("TinyFaceFeatureExtractor - load model before inference");return O(()=>{let a=le(t.toBatchTensor(112,!0),"float32"),s=yr(a,[122.782,117.001,104.298]).div(255),i=cg(s,n.dense0,!0);return i=cg(i,n.dense1),i=cg(i,n.dense2),i=fa(i,[14,14],[2,2],"valid"),i})}async forward(t){return this.forwardInput(await kt(t))}getDefaultModelName(){return"face_feature_extractor_tiny_model"}extractParamsFromWeightMap(t){return 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this._maxResults!="number")throw new Error(`${this._name} - expected maxResults to be a number`)}get minConfidence(){return this._minConfidence}get maxResults(){return this._maxResults}};var Do=class extends dn{constructor(){super("SsdMobilenetv1")}forwardInput(t){let{params:n}=this;if(!n)throw new Error("SsdMobilenetv1 - load model before inference");return O(()=>{let a=le(t.toBatchTensor(512,!1),"float32"),r=ce(fe(a,127.5),1),s=a$(r,n.mobilenetv1),{boxPredictions:i,classPredictions:o}=i$(s.out,s.conv11,n.prediction_layer);return s$(i,o,n.output_layer)})}async forward(t){return this.forwardInput(await kt(t))}async locateFaces(t,n={}){let{maxResults:a,minConfidence:r}=new Da(n),s=await kt(t),{boxes:i,scores:o}=this.forwardInput(s),l=i[0],u=o[0];for(let x=1;x{let[v,I]=[Math.max(0,y[x][0]),Math.min(1,y[x][2])].map(A=>A*g),[T,_]=[Math.max(0,y[x][1]),Math.min(1,y[x][3])].map(A=>A*f);return new wt(p[x],new np(T,v,_-T,I-v),{height:s.getInputHeight(0),width:s.getInputWidth(0)})});return l.dispose(),u.dispose(),b}getDefaultModelName(){return"ssd_mobilenetv1_model"}extractParamsFromWeightMap(t){return n$(t)}extractParams(t){return t$(t)}};function Ape(e){let t=new Do;return t.extractWeights(e),t}function $Ie(e){return Ape(e)}var o$=class extends Do{};var l$=.4,u$=[new Oe(.738768,.874946),new Oe(2.42204,2.65704),new Oe(4.30971,7.04493),new Oe(10.246,4.59428),new Oe(12.6868,11.8741)],p$=[new Oe(1.603231,2.094468),new Oe(6.041143,7.080126),new Oe(2.882459,3.518061),new Oe(4.266906,5.178857),new Oe(9.041765,10.66308)],c$=[117.001,114.697,97.404],d$="tiny_yolov2_model",h$="tiny_yolov2_separable_conv_model";var Ng=e=>typeof e=="number";function m$(e){if(!e)throw new Error(`invalid config: ${e}`);if(typeof e.withSeparableConvs!="boolean")throw new Error(`config.withSeparableConvs has to be a boolean, have: ${e.withSeparableConvs}`);if(!Ng(e.iouThreshold)||e.iouThreshold<0||e.iouThreshold>1)throw new Error(`config.iouThreshold has to be a number between [0, 1], have: ${e.iouThreshold}`);if(!Array.isArray(e.classes)||!e.classes.length||!e.classes.every(t=>typeof t=="string"))throw new Error(`config.classes has to be an array class names: string[], have: ${JSON.stringify(e.classes)}`);if(!Array.isArray(e.anchors)||!e.anchors.length||!e.anchors.map(t=>t||{}).every(t=>Ng(t.x)&&Ng(t.y)))throw new Error(`config.anchors has to be an array of { x: number, y: number }, have: ${JSON.stringify(e.anchors)}`);if(e.meanRgb&&(!Array.isArray(e.meanRgb)||e.meanRgb.length!==3||!e.meanRgb.every(Ng)))throw new Error(`config.meanRgb has to be an array of shape [number, number, number], have: ${JSON.stringify(e.meanRgb)}`)}function bp(e){return O(()=>{let t=B(e,ke(.10000000149011612));return Z(Xe(ce(e,t)),t)})}function zr(e,t){return O(()=>{let n=ga(e,[[0,0],[1,1],[1,1],[0,0]]);return n=Dt(n,t.conv.filters,[1,1],"valid"),n=ce(n,t.bn.sub),n=B(n,t.bn.truediv),n=Z(n,t.conv.bias),bp(n)})}function Br(e,t){return O(()=>{let n=ga(e,[[0,0],[1,1],[1,1],[0,0]]);return n=ks(n,t.depthwise_filter,t.pointwise_filter,[1,1],"valid"),n=Z(n,t.bias),bp(n)})}function $pe(e,t){let n=up(e,t);function a(i,o){let l=Ke(e(i)),u=Ke(e(i));return t.push({paramPath:`${o}/sub`},{paramPath:`${o}/truediv`}),{sub:l,truediv:u}}function r(i,o,l){let u=n(i,o,3,`${l}/conv`),p=a(o,`${l}/bn`);return{conv:u,bn:p}}let s=pp(e,t);return{extractConvParams:n,extractConvWithBatchNormParams:r,extractSeparableConvParams:s}}function f$(e,t,n,a){let{extractWeights:r,getRemainingWeights:s}=Dn(e),i=[],{extractConvParams:o,extractConvWithBatchNormParams:l,extractSeparableConvParams:u}=$pe(r,i),p;if(t.withSeparableConvs){let[d,c,h,m,f,g,y,b,x]=a,v=t.isFirstLayerConv2d?o(d,c,3,"conv0"):u(d,c,"conv0"),I=u(c,h,"conv1"),T=u(h,m,"conv2"),_=u(m,f,"conv3"),A=u(f,g,"conv4"),F=u(g,y,"conv5"),P=b?u(y,b,"conv6"):void 0,$=x?u(b,x,"conv7"):void 0,S=o(x||b||y,5*n,1,"conv8");p={conv0:v,conv1:I,conv2:T,conv3:_,conv4:A,conv5:F,conv6:P,conv7:$,conv8:S}}else{let[d,c,h,m,f,g,y,b,x]=a,v=l(d,c,"conv0"),I=l(c,h,"conv1"),T=l(h,m,"conv2"),_=l(m,f,"conv3"),A=l(f,g,"conv4"),F=l(g,y,"conv5"),P=l(y,b,"conv6"),$=l(b,x,"conv7"),S=o(x,5*n,1,"conv8");p={conv0:v,conv1:I,conv2:T,conv3:_,conv4:A,conv5:F,conv6:P,conv7:$,conv8:S}}if(s().length!==0)throw new Error(`weights remaing after extract: ${s().length}`);return{params:p,paramMappings:i}}function Fpe(e,t){let n=ra(e,t);function a(o){let l=n(`${o}/sub`,1),u=n(`${o}/truediv`,1);return{sub:l,truediv:u}}function r(o){let l=n(`${o}/filters`,4),u=n(`${o}/bias`,1);return{filters:l,bias:u}}function s(o){let l=r(`${o}/conv`),u=a(`${o}/bn`);return{conv:l,bn:u}}let i=cp(n);return{extractConvParams:r,extractConvWithBatchNormParams:s,extractSeparableConvParams:i}}function g$(e,t){let n=[],{extractConvParams:a,extractConvWithBatchNormParams:r,extractSeparableConvParams:s}=Fpe(e,n),i;if(t.withSeparableConvs){let o=t.filterSizes&&t.filterSizes.length||9;i={conv0:t.isFirstLayerConv2d?a("conv0"):s("conv0"),conv1:s("conv1"),conv2:s("conv2"),conv3:s("conv3"),conv4:s("conv4"),conv5:s("conv5"),conv6:o>7?s("conv6"):void 0,conv7:o>8?s("conv7"):void 0,conv8:a("conv8")}}else i={conv0:r("conv0"),conv1:r("conv1"),conv2:r("conv2"),conv3:r("conv3"),conv4:r("conv4"),conv5:r("conv5"),conv6:r("conv6"),conv7:r("conv7"),conv8:a("conv8")};return Fn(e,n),{params:i,paramMappings:n}}var br=class{constructor({inputSize:t,scoreThreshold:n}={}){this._name="TinyYolov2Options";if(this._inputSize=t||416,this._scoreThreshold=n||.5,typeof this._inputSize!="number"||this._inputSize%32!==0)throw new Error(`${this._name} - expected inputSize to be a number divisible by 32`);if(typeof this._scoreThreshold!="number"||this._scoreThreshold<=0||this._scoreThreshold>=1)throw new Error(`${this._name} - expected scoreThreshold to be a number between 0 and 1`)}get inputSize(){return this._inputSize}get scoreThreshold(){return this._scoreThreshold}};var A1=class extends dn{constructor(n){super("TinyYolov2");m$(n),this._config=n}get config(){return this._config}get withClassScores(){return this.config.withClassScores||this.config.classes.length>1}get boxEncodingSize(){return 5+(this.withClassScores?this.config.classes.length:0)}runTinyYolov2(n,a){let r=zr(n,a.conv0);return r=Mt(r,[2,2],[2,2],"same"),r=zr(r,a.conv1),r=Mt(r,[2,2],[2,2],"same"),r=zr(r,a.conv2),r=Mt(r,[2,2],[2,2],"same"),r=zr(r,a.conv3),r=Mt(r,[2,2],[2,2],"same"),r=zr(r,a.conv4),r=Mt(r,[2,2],[2,2],"same"),r=zr(r,a.conv5),r=Mt(r,[2,2],[1,1],"same"),r=zr(r,a.conv6),r=zr(r,a.conv7),$o(r,a.conv8,"valid",!1)}runMobilenet(n,a){let r=this.config.isFirstLayerConv2d?bp($o(n,a.conv0,"valid",!1)):Br(n,a.conv0);return r=Mt(r,[2,2],[2,2],"same"),r=Br(r,a.conv1),r=Mt(r,[2,2],[2,2],"same"),r=Br(r,a.conv2),r=Mt(r,[2,2],[2,2],"same"),r=Br(r,a.conv3),r=Mt(r,[2,2],[2,2],"same"),r=Br(r,a.conv4),r=Mt(r,[2,2],[2,2],"same"),r=Br(r,a.conv5),r=Mt(r,[2,2],[1,1],"same"),r=a.conv6?Br(r,a.conv6):r,r=a.conv7?Br(r,a.conv7):r,$o(r,a.conv8,"valid",!1)}forwardInput(n,a){let{params:r}=this;if(!r)throw new Error("TinyYolov2 - load model before inference");return O(()=>{let s=le(n.toBatchTensor(a,!1),"float32");return s=this.config.meanRgb?yr(s,this.config.meanRgb):s,s=s.div(255),this.config.withSeparableConvs?this.runMobilenet(s,r):this.runTinyYolov2(s,r)})}async forward(n,a){return this.forwardInput(await kt(n),a)}async detect(n,a={}){let{inputSize:r,scoreThreshold:s}=new br(a),i=await kt(n),o=await this.forwardInput(i,r),l=O(()=>mt(o)[0].expandDims()),u={width:i.getInputWidth(0),height:i.getInputHeight(0)},p=await this.extractBoxes(l,i.getReshapedInputDimensions(0),s);o.dispose(),l.dispose();let d=p.map(y=>y.box),c=p.map(y=>y.score),h=p.map(y=>y.classScore),m=p.map(y=>this.config.classes[y.label]);return SA(d.map(y=>y.rescale(r)),c,this.config.iouThreshold,!0).map(y=>new Cs(c[y],h[y],m[y],d[y],u))}getDefaultModelName(){return""}extractParamsFromWeightMap(n){return g$(n,this.config)}extractParams(n){let a=this.config.filterSizes||A1.DEFAULT_FILTER_SIZES,r=a?a.length:void 0;if(r!==7&&r!==8&&r!==9)throw new Error(`TinyYolov2 - expected 7 | 8 | 9 convolutional filters, but found ${r} filterSizes in config`);return f$(n,this.config,this.boxEncodingSize,a)}async extractBoxes(n,a,r){let{width:s,height:i}=a,o=Math.max(s,i),l=o/s,u=o/i,p=n.shape[1],d=this.config.anchors.length,[c,h,m]=O(()=>{let b=n.reshape([p,p,d,this.boxEncodingSize]),x=b.slice([0,0,0,0],[p,p,d,4]),v=b.slice([0,0,0,4],[p,p,d,1]),I=this.withClassScores?Za(b.slice([0,0,0,5],[p,p,d,this.config.classes.length]),3):ke(0);return[x,v,I]}),f=[],g=await h.array(),y=await c.array();for(let b=0;br){let T=(x+sg(y[b][x][v][0]))/p*l,_=(b+sg(y[b][x][v][1]))/p*u,A=Math.exp(y[b][x][v][2])*this.config.anchors[v].x/p*l,F=Math.exp(y[b][x][v][3])*this.config.anchors[v].y/p*u,P=T-A/2,$=_-F/2,S={row:b,col:x,anchor:v},{classScore:M,label:U}=this.withClassScores?await this.extractPredictedClass(m,S):{classScore:1,label:0};f.push({box:new tp(P,$,P+A,$+F),score:I,classScore:I*M,label:U,...S})}}return c.dispose(),h.dispose(),m.dispose(),f}async extractPredictedClass(n,a){let{row:r,col:s,anchor:i}=a,o=await n.array();return Array(this.config.classes.length).fill(0).map((l,u)=>o[r][s][i][u]).map((l,u)=>({classScore:l,label:u})).reduce((l,u)=>l.classScore>u.classScore?l:u)}},Ro=A1;Ro.DEFAULT_FILTER_SIZES=[3,16,32,64,128,256,512,1024,1024];var xp=class extends Ro{constructor(t=!0){let n={withSeparableConvs:t,iouThreshold:l$,classes:["face"],...t?{anchors:p$,meanRgb:c$}:{anchors:u$,withClassScores:!0}};super(n)}get withSeparableConvs(){return this.config.withSeparableConvs}get anchors(){return this.config.anchors}async locateFaces(t,n){return(await this.detect(t,n)).map(r=>new wt(r.score,r.relativeBox,{width:r.imageWidth,height:r.imageHeight}))}getDefaultModelName(){return this.withSeparableConvs?h$:d$}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};function kSe(e,t=!0){let n=new xp(t);return n.extractWeights(e),n}var Tg=class extends br{constructor(){super(...arguments);this._name="TinyFaceDetectorOptions"}};var Ra=class{async then(t){return t(await this.run())}async run(){throw new Error("ComposableTask - run is not implemented")}};async function Mo(e,t,n,a,r=({alignedRect:s})=>s){let s=e.map(l=>mp(l)?r(l):l.detection),i=a||(t instanceof Ae?await wd(t,s):await vd(t,s)),o=await n(i);return i.forEach(l=>l instanceof Ae&&l.dispose()),o}async function vp(e,t,n,a,r){return Mo([e],t,async s=>n(s[0]),a,r)}var y$=.4,b$=[new Oe(1.603231,2.094468),new Oe(6.041143,7.080126),new Oe(2.882459,3.518061),new Oe(4.266906,5.178857),new Oe(9.041765,10.66308)],x$=[117.001,114.697,97.404];var wp=class extends Ro{constructor(){let t={withSeparableConvs:!0,iouThreshold:y$,classes:["face"],anchors:b$,meanRgb:x$,isFirstLayerConv2d:!0,filterSizes:[3,16,32,64,128,256,512]};super(t)}get anchors(){return this.config.anchors}async locateFaces(t,n){return(await this.detect(t,n)).map(r=>new wt(r.score,r.relativeBox,{width:r.imageWidth,height:r.imageHeight}))}getDefaultModelName(){return"tiny_face_detector_model"}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};var rt={ssdMobilenetv1:new Do,tinyFaceDetector:new wp,tinyYolov2:new xp,faceLandmark68Net:new gp,faceLandmark68TinyNet:new Ig,faceRecognitionNet:new yp,faceExpressionNet:new yg,ageGenderNet:new wg},Dpe=(e,t)=>rt.ssdMobilenetv1.locateFaces(e,t),ZSe=(e,t)=>rt.tinyFaceDetector.locateFaces(e,t),QSe=(e,t)=>rt.tinyYolov2.locateFaces(e,t),Rpe=e=>rt.faceLandmark68Net.detectLandmarks(e),eNe=e=>rt.faceLandmark68TinyNet.detectLandmarks(e),tNe=e=>rt.faceRecognitionNet.computeFaceDescriptor(e),nNe=e=>rt.faceExpressionNet.predictExpressions(e),aNe=e=>rt.ageGenderNet.predictAgeAndGender(e),Mpe=e=>rt.ssdMobilenetv1.load(e),rNe=e=>rt.tinyFaceDetector.load(e),sNe=e=>rt.tinyYolov2.load(e),iNe=e=>rt.faceLandmark68Net.load(e),oNe=e=>rt.faceLandmark68TinyNet.load(e),lNe=e=>rt.faceRecognitionNet.load(e),uNe=e=>rt.faceExpressionNet.load(e),pNe=e=>rt.ageGenderNet.load(e),cNe=Mpe,dNe=Dpe,hNe=Rpe;var Cg=class extends Ra{constructor(n,a,r){super();this.parentTask=n;this.input=a;this.extractedFaces=r}},Po=class extends Cg{async run(){let t=await this.parentTask,n=await Mo(t,this.input,async a=>Promise.all(a.map(r=>rt.faceExpressionNet.predictExpressions(r))),this.extractedFaces);return t.map((a,r)=>k1(a,n[r]))}withAgeAndGender(){return new Lo(this,this.input)}},Oo=class extends Cg{async run(){let t=await this.parentTask;if(!t)return;let n=await vp(t,this.input,a=>rt.faceExpressionNet.predictExpressions(a),this.extractedFaces);return k1(t,n)}withAgeAndGender(){return new zo(this,this.input)}},As=class extends Po{withAgeAndGender(){return new Fs(this,this.input)}withFaceDescriptors(){return new Rs(this,this.input)}},$s=class extends Oo{withAgeAndGender(){return new Ds(this,this.input)}withFaceDescriptor(){return new Ms(this,this.input)}};var _g=class extends Ra{constructor(n,a,r){super();this.parentTask=n;this.input=a;this.extractedFaces=r}},Lo=class extends _g{async run(){let t=await this.parentTask,n=await Mo(t,this.input,async a=>Promise.all(a.map(r=>rt.ageGenderNet.predictAgeAndGender(r))),this.extractedFaces);return t.map((a,r)=>{let{age:s,gender:i,genderProbability:o}=n[r];return _1(E1(a,i,o),s)})}withFaceExpressions(){return new Po(this,this.input)}},zo=class extends _g{async run(){let t=await this.parentTask;if(!t)return;let{age:n,gender:a,genderProbability:r}=await vp(t,this.input,s=>rt.ageGenderNet.predictAgeAndGender(s),this.extractedFaces);return _1(E1(t,a,r),n)}withFaceExpressions(){return new Oo(this,this.input)}},Fs=class extends Lo{withFaceExpressions(){return new As(this,this.input)}withFaceDescriptors(){return new Rs(this,this.input)}},Ds=class extends zo{withFaceExpressions(){return new $s(this,this.input)}withFaceDescriptor(){return new Ms(this,this.input)}};var Eg=class extends Ra{constructor(n,a){super();this.parentTask=n;this.input=a}},Rs=class extends Eg{async run(){let t=await this.parentTask;return(await Mo(t,this.input,a=>Promise.all(a.map(r=>rt.faceRecognitionNet.computeFaceDescriptor(r))),null,a=>a.landmarks.align(null,{useDlibAlignment:!0}))).map((a,r)=>C1(t[r],a))}withFaceExpressions(){return new As(this,this.input)}withAgeAndGender(){return new Fs(this,this.input)}},Ms=class extends Eg{async run(){let t=await this.parentTask;if(!t)return;let n=await vp(t,this.input,a=>rt.faceRecognitionNet.computeFaceDescriptor(a),null,a=>a.landmarks.align(null,{useDlibAlignment:!0}));return C1(t,n)}withFaceExpressions(){return new $s(this,this.input)}withAgeAndGender(){return new Ds(this,this.input)}};var Ag=class extends Ra{constructor(n,a,r){super();this.parentTask=n;this.input=a;this.useTinyLandmarkNet=r}get landmarkNet(){return this.useTinyLandmarkNet?rt.faceLandmark68TinyNet:rt.faceLandmark68Net}},$g=class extends Ag{async run(){let t=await this.parentTask,n=t.map(i=>i.detection),a=this.input instanceof Ae?await wd(this.input,n):await vd(this.input,n),r=await Promise.all(a.map(i=>this.landmarkNet.detectLandmarks(i)));return a.forEach(i=>i instanceof Ae&&i.dispose()),t.filter((i,o)=>r[o]).map((i,o)=>Nd(i,r[o]))}withFaceExpressions(){return new As(this,this.input)}withAgeAndGender(){return new Fs(this,this.input)}withFaceDescriptors(){return new Rs(this,this.input)}},Fg=class extends Ag{async run(){let t=await this.parentTask;if(!t)return;let{detection:n}=t,a=this.input instanceof Ae?await wd(this.input,[n]):await vd(this.input,[n]),r=await this.landmarkNet.detectLandmarks(a[0]);return a.forEach(s=>s instanceof Ae&&s.dispose()),Nd(t,r)}withFaceExpressions(){return new $s(this,this.input)}withAgeAndGender(){return new Ds(this,this.input)}withFaceDescriptor(){return new Ms(this,this.input)}};var Dg=class extends Ra{constructor(n,a=new Da){super();this.input=n;this.options=a}},Cd=class extends Dg{async run(){let{input:t,options:n}=this,a;if(n instanceof Tg)a=rt.tinyFaceDetector.locateFaces(t,n);else if(n instanceof Da)a=rt.ssdMobilenetv1.locateFaces(t,n);else if(n instanceof br)a=rt.tinyYolov2.locateFaces(t,n);else throw new Error("detectFaces - expected options to be instance of TinyFaceDetectorOptions | SsdMobilenetv1Options | TinyYolov2Options");return a}runAndExtendWithFaceDetections(){return new Promise((t,n)=>{this.run().then(a=>t(a.map(r=>rp({},r)))).catch(a=>n(a))})}withFaceLandmarks(t=!1){return new $g(this.runAndExtendWithFaceDetections(),this.input,t)}withFaceExpressions(){return new Po(this.runAndExtendWithFaceDetections(),this.input)}withAgeAndGender(){return new Lo(this.runAndExtendWithFaceDetections(),this.input)}},Rg=class extends Dg{async run(){let t=await new Cd(this.input,this.options),n=t[0];return t.forEach(a=>{a.score>n.score&&(n=a)}),n}runAndExtendWithFaceDetection(){return new Promise(async t=>{let n=await this.run();t(n?rp({},n):void 0)})}withFaceLandmarks(t=!1){return new Fg(this.runAndExtendWithFaceDetection(),this.input,t)}withFaceExpressions(){return new Oo(this.runAndExtendWithFaceDetection(),this.input)}withAgeAndGender(){return new zo(this.runAndExtendWithFaceDetection(),this.input)}};function p2e(e,t=new Da){return new Rg(e,t)}function $1(e,t=new Da){return new Cd(e,t)}async function Ppe(e,t){return $1(e,new 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Box,Ra as ComposableTask,Rs as ComputeAllFaceDescriptorsTask,Eg as ComputeFaceDescriptorsTaskBase,Ms as ComputeSingleFaceDescriptorTask,$g as DetectAllFaceLandmarksTask,Cd as DetectAllFacesTask,Ag as DetectFaceLandmarksTaskBase,Dg as DetectFacesTaskBase,Fg as DetectSingleFaceLandmarksTask,Rg as DetectSingleFaceTask,$n as Dimensions,zA as FACE_EXPRESSION_LABELS,wt as FaceDetection,o$ as FaceDetectionNet,yg as FaceExpressionNet,Es as FaceExpressions,gp as FaceLandmark68Net,Ig as FaceLandmark68TinyNet,YA as FaceLandmarkNet,xa as FaceLandmarks,TA as FaceLandmarks5,ap as FaceLandmarks68,gd as FaceMatch,Mg as FaceMatcher,yp as FaceRecognitionNet,S1 as Gender,yd as LabeledBox,Mr as LabeledFaceDescriptors,Lr as NetInput,dn as NeuralNetwork,Cs as ObjectDetection,Oe as Point,CA as PredictedBox,np as Rect,Do as SsdMobilenetv1,Da as SsdMobilenetv1Options,wp as TinyFaceDetector,Tg as TinyFaceDetectorOptions,xp as TinyYolov2,br as TinyYolov2Options,y2e as allFaces,Ppe as allFacesSsdMobilenetv1,g2e 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a=le(t.toBatchTensor(112,!0),"float32"),s=yr(a,[122.782,117.001,104.298]).div(255),i=kd(s,n.dense0,!0);return i=kd(i,n.dense1),i=kd(i,n.dense2),i=kd(i,n.dense3),i=fa(i,[7,7],[2,2],"valid"),i})}async forward(t){return this.forwardInput(await kt(t))}getDefaultModelName(){return"face_feature_extractor_model"}extractParamsFromWeightMap(t){return PA(t)}extractParams(t){return MA(t)}};function Sd(e,t){return O(()=>Z(Re(e,t.weights),t.bias))}function OA(e,t,n){let a=[],{extractWeights:r,getRemainingWeights:s}=Dn(e),o=dg(r,a)(t,n,"fc");if(s().length!==0)throw new Error(`weights remaing after extract: ${s().length}`);return{paramMappings:a,params:{fc:o}}}function LA(e){let t=[],n=ra(e,t);function a(s){let i=n(`${s}/weights`,2),o=n(`${s}/bias`,1);return{weights:i,bias:o}}let r={fc:a("fc")};return Fn(e,t),{params:r,paramMappings:t}}function gg(e){let t={},n={};return Object.keys(e).forEach(a=>{let r=a.startsWith("fc")?n:t;r[a]=e[a]}),{featureExtractorMap:t,classifierMap:n}}var hp=class extends dn{constructor(n,a){super(n);this._faceFeatureExtractor=a}get faceFeatureExtractor(){return this._faceFeatureExtractor}runNet(n){let{params:a}=this;if(!a)throw new Error(`${this._name} - load model before inference`);return O(()=>{let r=n instanceof Lr?this.faceFeatureExtractor.forwardInput(n):n;return Sd(r.as2D(r.shape[0],-1),a.fc)})}dispose(n=!0){this.faceFeatureExtractor.dispose(n),super.dispose(n)}loadClassifierParams(n){let{params:a,paramMappings:r}=this.extractClassifierParams(n);this._params=a,this._paramMappings=r}extractClassifierParams(n){return OA(n,this.getClassifierChannelsIn(),this.getClassifierChannelsOut())}extractParamsFromWeightMap(n){let{featureExtractorMap:a,classifierMap:r}=gg(n);return this.faceFeatureExtractor.loadFromWeightMap(a),LA(r)}extractParams(n){let a=this.getClassifierChannelsIn(),r=this.getClassifierChannelsOut(),s=r*a+r,i=n.slice(0,n.length-s),o=n.slice(n.length-s);return this.faceFeatureExtractor.extractWeights(i),this.extractClassifierParams(o)}};var zA=["neutral","happy","sad","angry","fearful","disgusted","surprised"],Es=class{constructor(t){this.neutral=0;this.happy=0;this.sad=0;this.angry=0;this.fearful=0;this.disgusted=0;this.surprised=0;if(t.length!==7)throw new Error(`FaceExpressions.constructor - expected probabilities.length to be 7, have: ${t.length}`);zA.forEach((n,a)=>{this[n]=t[a]})}asSortedArray(){return zA.map(t=>({expression:t,probability:this[t]})).sort((t,n)=>n.probability-t.probability)}};var yg=class extends hp{constructor(t=new dp){super("FaceExpressionNet",t)}forwardInput(t){return O(()=>Za(this.runNet(t)))}async forward(t){return this.forwardInput(await kt(t))}async predictExpressions(t){let n=await kt(t),a=await this.forwardInput(n),r=await Promise.all(mt(a).map(async i=>{let o=i.dataSync();return i.dispose(),o}));a.dispose();let s=r.map(i=>new Es(i));return n.isBatchInput?s:s[0]}getDefaultModelName(){return"face_expression_model"}getClassifierChannelsIn(){return 256}getClassifierChannelsOut(){return 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s=r.reduce((o,l)=>oo>l._y?o:l._y,-1/0);return a.yaw=Math.PI*(e._imgDims._height/(i-s)/1.4-1),a}function Nd(e,t){let{box:n}=e.detection,a=t.shiftBy(n.x,n.y),r=a.align(),{imageDims:s}=e.detection,i=new wt(e.detection.score,r.rescale(s.reverse()),s),o=hpe(t);return{...e,...{landmarks:a,unshiftedLandmarks:t,alignedRect:i,angle:o}}}var bg=class{constructor(t={}){let{drawLines:n=!0,drawPoints:a=!0,lineWidth:r,lineColor:s,pointSize:i,pointColor:o}=t;this.drawLines=n,this.drawPoints=a,this.lineWidth=r||1,this.pointSize=i||2,this.lineColor=s||"rgba(0, 255, 255, 1)",this.pointColor=o||"rgba(255, 0, 255, 1)"}},xg=class{constructor(t,n={}){this.faceLandmarks=t,this.options=new bg(n)}draw(t){let n=aa(t),{drawLines:a,drawPoints:r,lineWidth:s,lineColor:i,pointSize:o,pointColor:l}=this.options;if(a&&this.faceLandmarks instanceof ap&&(n.strokeStyle=i,n.lineWidth=s,Dr(n,this.faceLandmarks.getJawOutline()),Dr(n,this.faceLandmarks.getLeftEyeBrow()),Dr(n,this.faceLandmarks.getRightEyeBrow()),Dr(n,this.faceLandmarks.getNose()),Dr(n,this.faceLandmarks.getLeftEye(),!0),Dr(n,this.faceLandmarks.getRightEye(),!0),Dr(n,this.faceLandmarks.getMouth(),!0)),r){n.strokeStyle=l,n.fillStyle=l;let u=p=>{n.beginPath(),n.arc(p.x,p.y,o,0,2*Math.PI),n.fill()};this.faceLandmarks.positions.forEach(u)}}};function mpe(e,t){(Array.isArray(t)?t:[t]).forEach(a=>{let r=a instanceof xa?a:mp(a)?a.landmarks:void 0;if(!r)throw new Error("drawFaceLandmarks - expected faceExpressions to be FaceLandmarks | WithFaceLandmarks> or array thereof");new xg(r).draw(e)})}var VA="1.7.2";function ype(e,t){let n=up(e,t),a=pp(e,t);function r(i,o,l){let u=a(i,o,`${l}/separable_conv0`),p=a(o,o,`${l}/separable_conv1`),d=n(i,o,1,`${l}/expansion_conv`);return{separable_conv0:u,separable_conv1:p,expansion_conv:d}}function s(i,o){let l=a(i,i,`${o}/separable_conv0`),u=a(i,i,`${o}/separable_conv1`),p=a(i,i,`${o}/separable_conv2`);return{separable_conv0:l,separable_conv1:u,separable_conv2:p}}return{extractConvParams:n,extractSeparableConvParams:a,extractReductionBlockParams:r,extractMainBlockParams:s}}function UA(e,t){let n=[],{extractWeights:a,getRemainingWeights:r}=Dn(e),{extractConvParams:s,extractSeparableConvParams:i,extractReductionBlockParams:o,extractMainBlockParams:l}=ype(a,n),u=s(3,32,3,"entry_flow/conv_in"),p=o(32,64,"entry_flow/reduction_block_0"),d=o(64,128,"entry_flow/reduction_block_1"),c={conv_in:u,reduction_block_0:p,reduction_block_1:d},h={};gr(t,0,1).forEach(y=>{h[`main_block_${y}`]=l(128,`middle_flow/main_block_${y}`)});let m=o(128,256,"exit_flow/reduction_block"),f=i(256,512,"exit_flow/separable_conv"),g={reduction_block:m,separable_conv:f};if(r().length!==0)throw new Error(`weights remaing after extract: 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c=s("exit_flow/reduction_block"),h=r("exit_flow/separable_conv"),m={reduction_block:c,separable_conv:h};return Fn(e,n),{params:{entry_flow:p,middle_flow:d,exit_flow:m},paramMappings:n}}function HA(e,t,n){return Z(Dt(e,t.filters,n,"same"),t.bias)}function I1(e,t,n=!0){let a=n?Xe(e):e;return a=Kn(a,t.separable_conv0,[1,1]),a=Kn(Xe(a),t.separable_conv1,[1,1]),a=Mt(a,[3,3],[2,2],"same"),a=Z(a,HA(e,t.expansion_conv,[2,2])),a}function xpe(e,t){let n=Kn(Xe(e),t.separable_conv0,[1,1]);return n=Kn(Xe(n),t.separable_conv1,[1,1]),n=Kn(Xe(n),t.separable_conv2,[1,1]),n=Z(n,e),n}var vg=class extends dn{constructor(n){super("TinyXception");this._numMainBlocks=n}forwardInput(n){let{params:a}=this;if(!a)throw new Error("TinyXception - load model before inference");return O(()=>{let r=le(n.toBatchTensor(112,!0),"float32"),i=yr(r,[122.782,117.001,104.298]).div(255),o=Xe(HA(i,a.entry_flow.conv_in,[2,2]));return o=I1(o,a.entry_flow.reduction_block_0,!1),o=I1(o,a.entry_flow.reduction_block_1),gr(this._numMainBlocks,0,1).forEach(l=>{o=xpe(o,a.middle_flow[`main_block_${l}`])}),o=I1(o,a.exit_flow.reduction_block),o=Xe(Kn(o,a.exit_flow.separable_conv,[1,1])),o})}async forward(n){return this.forwardInput(await kt(n))}getDefaultModelName(){return"tiny_xception_model"}extractParamsFromWeightMap(n){return GA(n,this._numMainBlocks)}extractParams(n){return UA(n,this._numMainBlocks)}};function jA(e){let t=[],{extractWeights:n,getRemainingWeights:a}=Dn(e),r=dg(n,t),s=r(512,1,"fc/age"),i=r(512,2,"fc/gender");if(a().length!==0)throw new Error(`weights remaing after extract: ${a().length}`);return{paramMappings:t,params:{fc:{age:s,gender:i}}}}function qA(e){let t=[],n=ra(e,t);function a(s){let i=n(`${s}/weights`,2),o=n(`${s}/bias`,1);return{weights:i,bias:o}}let r={fc:{age:a("fc/age"),gender:a("fc/gender")}};return Fn(e,t),{params:r,paramMappings:t}}var S1=(n=>(n.FEMALE="female",n.MALE="male",n))(S1||{});var wg=class extends dn{constructor(n=new vg(2)){super("AgeGenderNet");this._faceFeatureExtractor=n}get faceFeatureExtractor(){return this._faceFeatureExtractor}runNet(n){let{params:a}=this;if(!a)throw new Error(`${this._name} - load model before inference`);return O(()=>{let r=n instanceof Lr?this.faceFeatureExtractor.forwardInput(n):n,s=fa(r,[7,7],[2,2],"valid").as2D(r.shape[0],-1),i=Sd(s,a.fc.age).as1D(),o=Sd(s,a.fc.gender);return{age:i,gender:o}})}forwardInput(n){return O(()=>{let{age:a,gender:r}=this.runNet(n);return{age:a,gender:Za(r)}})}async forward(n){return this.forwardInput(await kt(n))}async predictAgeAndGender(n){let a=await kt(n),r=await this.forwardInput(a),s=mt(r.age),i=mt(r.gender),o=s.map((u,p)=>({ageTensor:u,genderTensor:i[p]})),l=await Promise.all(o.map(async({ageTensor:u,genderTensor:p})=>{let d=u.dataSync()[0],c=p.dataSync()[0],h=c>.5,m=h?"male":"female",f=h?c:1-c;return u.dispose(),p.dispose(),{age:d,gender:m,genderProbability:f}}));return r.age.dispose(),r.gender.dispose(),a.isBatchInput?l:l[0]}getDefaultModelName(){return"age_gender_model"}dispose(n=!0){this.faceFeatureExtractor.dispose(n),super.dispose(n)}loadClassifierParams(n){let{params:a,paramMappings:r}=this.extractClassifierParams(n);this._params=a,this._paramMappings=r}extractClassifierParams(n){return jA(n)}extractParamsFromWeightMap(n){let{featureExtractorMap:a,classifierMap:r}=gg(n);return this.faceFeatureExtractor.loadFromWeightMap(a),qA(r)}extractParams(n){let r=n.slice(0,n.length-1539),s=n.slice(n.length-1539);return this.faceFeatureExtractor.extractWeights(r),this.extractClassifierParams(s)}};var fp=class extends hp{postProcess(t,n,a){let r=a.map(({width:i,height:o})=>{let l=n/Math.max(o,i);return{width:i*l,height:o*l}}),s=r.length;return O(()=>{let i=(d,c)=>Rt([En([68],d,"float32"),En([68],c,"float32")],1).as2D(1,136).as1D(),o=(d,c)=>{let{width:h,height:m}=r[d];return 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t=[],{extractDenseBlock3Params:n}=fg(e,t),a={dense0:n("dense0",!0),dense1:n("dense1"),dense2:n("dense2")};return Fn(e,t),{params:a,paramMappings:t}}function XA(e){let t=[],{extractWeights:n,getRemainingWeights:a}=Dn(e),{extractDenseBlock3Params:r}=hg(n,t),s=r(3,32,"dense0",!0),i=r(32,64,"dense1"),o=r(64,128,"dense2");if(a().length!==0)throw new Error(`weights remaing after extract: ${a().length}`);return{paramMappings:t,params:{dense0:s,dense1:i,dense2:o}}}var kg=class extends dn{constructor(){super("TinyFaceFeatureExtractor")}forwardInput(t){let{params:n}=this;if(!n)throw new Error("TinyFaceFeatureExtractor - load model before inference");return O(()=>{let a=le(t.toBatchTensor(112,!0),"float32"),s=yr(a,[122.782,117.001,104.298]).div(255),i=cg(s,n.dense0,!0);return i=cg(i,n.dense1),i=cg(i,n.dense2),i=fa(i,[14,14],[2,2],"valid"),i})}async forward(t){return this.forwardInput(await kt(t))}getDefaultModelName(){return"face_feature_extractor_tiny_model"}extractParamsFromWeightMap(t){return KA(t)}extractParams(t){return XA(t)}};var Ig=class extends fp{constructor(t=new kg){super("FaceLandmark68TinyNet",t)}getDefaultModelName(){return"face_landmark_68_tiny_model"}getClassifierChannelsIn(){return 128}};var YA=class extends gp{};function JA(e,t){return Z(B(e,t.weights),t.biases)}function N1(e,t,n,a,r="same"){let{filters:s,bias:i}=t.conv,o=Dt(e,s,n,r);return o=Z(o,i),o=JA(o,t.scale),a?Xe(o):o}function ZA(e,t){return N1(e,t,[1,1],!0)}function T1(e,t){return N1(e,t,[1,1],!1)}function Sg(e,t){return N1(e,t,[2,2],!0,"valid")}function vpe(e,t){function n(o,l,u){let p=e(o),d=p.length/(l*u*u);if(h1(d))throw new Error(`depth has to be an integer: ${d}, weights.length: ${p.length}, numFilters: ${l}, filterSize: ${u}`);return O(()=>$e(Ea(p,[l,d,u,u]),[2,3,1,0]))}function a(o,l,u,p){let d=n(o,l,u),c=Ke(e(l));return t.push({paramPath:`${p}/filters`},{paramPath:`${p}/bias`}),{filters:d,bias:c}}function r(o,l){let u=Ke(e(o)),p=Ke(e(o));return t.push({paramPath:`${l}/weights`},{paramPath:`${l}/biases`}),{weights:u,biases:p}}function s(o,l,u,p){let d=a(o,l,u,`${p}/conv`),c=r(l,`${p}/scale`);return{conv:d,scale:c}}function i(o,l,u,p,d=!1){let c=s((d?.5:1)*o,l,u,`${p}/conv1`),h=s(o,l,u,`${p}/conv2`);return{conv1:c,conv2:h}}return{extractConvLayerParams:s,extractResidualLayerParams:i}}function QA(e){let{extractWeights:t,getRemainingWeights:n}=Dn(e),a=[],{extractConvLayerParams:r,extractResidualLayerParams:s}=vpe(t,a),i=r(4704,32,7,"conv32_down"),o=s(9216,32,3,"conv32_1"),l=s(9216,32,3,"conv32_2"),u=s(9216,32,3,"conv32_3"),p=s(36864,64,3,"conv64_down",!0),d=s(36864,64,3,"conv64_1"),c=s(36864,64,3,"conv64_2"),h=s(36864,64,3,"conv64_3"),m=s(147456,128,3,"conv128_down",!0),f=s(147456,128,3,"conv128_1"),g=s(147456,128,3,"conv128_2"),y=s(589824,256,3,"conv256_down",!0),b=s(589824,256,3,"conv256_1"),x=s(589824,256,3,"conv256_2"),v=s(589824,256,3,"conv256_down_out"),I=O(()=>$e(Na(t(256*128),[128,256]),[1,0]));if(a.push({paramPath:"fc"}),n().length!==0)throw new Error(`weights remaing after extract: ${n().length}`);return{params:{conv32_down:i,conv32_1:o,conv32_2:l,conv32_3:u,conv64_down:p,conv64_1:d,conv64_2:c,conv64_3:h,conv128_down:m,conv128_1:f,conv128_2:g,conv256_down:y,conv256_1:b,conv256_2:x,conv256_down_out:v,fc:I},paramMappings:a}}function wpe(e,t){let n=ra(e,t);function a(i){let o=n(`${i}/scale/weights`,1),l=n(`${i}/scale/biases`,1);return{weights:o,biases:l}}function r(i){let o=n(`${i}/conv/filters`,4),l=n(`${i}/conv/bias`,1),u=a(i);return{conv:{filters:o,bias:l},scale:u}}function s(i){return{conv1:r(`${i}/conv1`),conv2:r(`${i}/conv2`)}}return{extractConvLayerParams:r,extractResidualLayerParams:s}}function e$(e){let t=[],{extractConvLayerParams:n,extractResidualLayerParams:a}=wpe(e,t),r=n("conv32_down"),s=a("conv32_1"),i=a("conv32_2"),o=a("conv32_3"),l=a("conv64_down"),u=a("conv64_1"),p=a("conv64_2"),d=a("conv64_3"),c=a("conv128_down"),h=a("conv128_1"),m=a("conv128_2"),f=a("conv256_down"),g=a("conv256_1"),y=a("conv256_2"),b=a("conv256_down_out"),{fc:x}=e;if(t.push({originalPath:"fc",paramPath:"fc"}),!d1(x))throw new Error(`expected weightMap[fc] to be a Tensor2D, instead have ${x}`);let v={conv32_down:r,conv32_1:s,conv32_2:i,conv32_3:o,conv64_down:l,conv64_1:u,conv64_2:p,conv64_3:d,conv128_down:c,conv128_1:h,conv128_2:m,conv256_down:f,conv256_1:g,conv256_2:y,conv256_down_out:b,fc:x};return Fn(e,t),{params:v,paramMappings:t}}function tr(e,t){let n=ZA(e,t.conv1);return n=T1(n,t.conv2),n=Z(n,e),n=Xe(n),n}function Td(e,t){let n=Sg(e,t.conv1);n=T1(n,t.conv2);let a=fa(e,2,2,"valid"),r=It(a.shape),s=a.shape[3]!==n.shape[3];if(a.shape[1]!==n.shape[1]||a.shape[2]!==n.shape[2]){let o=[...n.shape];o[1]=1;let l=It(o);n=Qe([n,l],1);let u=[...n.shape];u[2]=1;let p=It(u);n=Qe([n,p],2)}return a=s?Qe([a,r],3):a,n=Z(a,n),n=Xe(n),n}var yp=class extends dn{constructor(){super("FaceRecognitionNet")}forwardInput(t){let{params:n}=this;if(!n)throw new Error("FaceRecognitionNet - load model before inference");return O(()=>{let a=le(t.toBatchTensor(150,!0),"float32"),s=yr(a,[122.782,117.001,104.298]).div(255),i=Sg(s,n.conv32_down);i=Mt(i,3,2,"valid"),i=tr(i,n.conv32_1),i=tr(i,n.conv32_2),i=tr(i,n.conv32_3),i=Td(i,n.conv64_down),i=tr(i,n.conv64_1),i=tr(i,n.conv64_2),i=tr(i,n.conv64_3),i=Td(i,n.conv128_down),i=tr(i,n.conv128_1),i=tr(i,n.conv128_2),i=Td(i,n.conv256_down),i=tr(i,n.conv256_1),i=tr(i,n.conv256_2),i=Td(i,n.conv256_down_out);let o=i.mean([1,2]);return Re(o,n.fc)})}async forward(t){return this.forwardInput(await kt(t))}async computeFaceDescriptor(t){var s;if((s=t==null?void 0:t.shape)!=null&&s.some(i=>i<=0))return new Float32Array(128);let n=await kt(t),a=O(()=>mt(this.forwardInput(n))),r=await Promise.all(a.map(i=>i.data()));return a.forEach(i=>i.dispose()),n.isBatchInput?r:r[0]}getDefaultModelName(){return"face_recognition_model"}extractParamsFromWeightMap(t){return e$(t)}extractParams(t){return QA(t)}};function $ke(e){let t=new yp;return t.extractWeights(e),t}function C1(e,t){return{...e,...{descriptor:t}}}function Mke(e){return typeof e.age=="number"}function _1(e,t){return{...e,...{age:t}}}function zke(e){return(e.gender==="male"||e.gender==="female")&&ep(e.genderProbability)}function E1(e,t,n){return{...e,...{gender:t,genderProbability:n}}}function kpe(e,t){function n(l,u){let p=Ea(e(9*l),[3,3,l,1]),d=Ke(e(l)),c=Ke(e(l)),h=Ke(e(l)),m=Ke(e(l));return t.push({paramPath:`${u}/filters`},{paramPath:`${u}/batch_norm_scale`},{paramPath:`${u}/batch_norm_offset`},{paramPath:`${u}/batch_norm_mean`},{paramPath:`${u}/batch_norm_variance`}),{filters:p,batch_norm_scale:d,batch_norm_offset:c,batch_norm_mean:h,batch_norm_variance:m}}function a(l,u,p,d,c){let h=Ea(e(l*u*p*p),[p,p,l,u]),m=Ke(e(u));return t.push({paramPath:`${d}/filters`},{paramPath:`${d}/${c?"batch_norm_offset":"bias"}`}),{filters:h,bias:m}}function r(l,u,p,d){let{filters:c,bias:h}=a(l,u,p,d,!0);return{filters:c,batch_norm_offset:h}}function s(l,u,p){let 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r=Mt(r,[2,2],[2,2],"same"),r=Br(r,a.conv1),r=Mt(r,[2,2],[2,2],"same"),r=Br(r,a.conv2),r=Mt(r,[2,2],[2,2],"same"),r=Br(r,a.conv3),r=Mt(r,[2,2],[2,2],"same"),r=Br(r,a.conv4),r=Mt(r,[2,2],[2,2],"same"),r=Br(r,a.conv5),r=Mt(r,[2,2],[1,1],"same"),r=a.conv6?Br(r,a.conv6):r,r=a.conv7?Br(r,a.conv7):r,$o(r,a.conv8,"valid",!1)}forwardInput(n,a){let{params:r}=this;if(!r)throw new Error("TinyYolov2 - load model before inference");return O(()=>{let s=le(n.toBatchTensor(a,!1),"float32");return s=this.config.meanRgb?yr(s,this.config.meanRgb):s,s=s.div(255),this.config.withSeparableConvs?this.runMobilenet(s,r):this.runTinyYolov2(s,r)})}async forward(n,a){return this.forwardInput(await kt(n),a)}async detect(n,a={}){let{inputSize:r,scoreThreshold:s}=new br(a),i=await kt(n),o=await this.forwardInput(i,r),l=O(()=>mt(o)[0].expandDims()),u={width:i.getInputWidth(0),height:i.getInputHeight(0)},p=await this.extractBoxes(l,i.getReshapedInputDimensions(0),s);o.dispose(),l.dispose();let d=p.map(y=>y.box),c=p.map(y=>y.score),h=p.map(y=>y.classScore),m=p.map(y=>this.config.classes[y.label]);return SA(d.map(y=>y.rescale(r)),c,this.config.iouThreshold,!0).map(y=>new Cs(c[y],h[y],m[y],d[y],u))}getDefaultModelName(){return""}extractParamsFromWeightMap(n){return g$(n,this.config)}extractParams(n){let a=this.config.filterSizes||A1.DEFAULT_FILTER_SIZES,r=a?a.length:void 0;if(r!==7&&r!==8&&r!==9)throw new Error(`TinyYolov2 - expected 7 | 8 | 9 convolutional filters, but found ${r} filterSizes in config`);return f$(n,this.config,this.boxEncodingSize,a)}async extractBoxes(n,a,r){let{width:s,height:i}=a,o=Math.max(s,i),l=o/s,u=o/i,p=n.shape[1],d=this.config.anchors.length,[c,h,m]=O(()=>{let b=n.reshape([p,p,d,this.boxEncodingSize]),x=b.slice([0,0,0,0],[p,p,d,4]),v=b.slice([0,0,0,4],[p,p,d,1]),I=this.withClassScores?Za(b.slice([0,0,0,5],[p,p,d,this.config.classes.length]),3):ke(0);return[x,v,I]}),f=[],g=await h.array(),y=await c.array();for(let b=0;br){let T=(x+sg(y[b][x][v][0]))/p*l,_=(b+sg(y[b][x][v][1]))/p*u,A=Math.exp(y[b][x][v][2])*this.config.anchors[v].x/p*l,F=Math.exp(y[b][x][v][3])*this.config.anchors[v].y/p*u,P=T-A/2,$=_-F/2,S={row:b,col:x,anchor:v},{classScore:M,label:U}=this.withClassScores?await this.extractPredictedClass(m,S):{classScore:1,label:0};f.push({box:new tp(P,$,P+A,$+F),score:I,classScore:I*M,label:U,...S})}}return c.dispose(),h.dispose(),m.dispose(),f}async extractPredictedClass(n,a){let{row:r,col:s,anchor:i}=a,o=await n.array();return Array(this.config.classes.length).fill(0).map((l,u)=>o[r][s][i][u]).map((l,u)=>({classScore:l,label:u})).reduce((l,u)=>l.classScore>u.classScore?l:u)}},Ro=A1;Ro.DEFAULT_FILTER_SIZES=[3,16,32,64,128,256,512,1024,1024];var xp=class extends Ro{constructor(t=!0){let n={withSeparableConvs:t,iouThreshold:l$,classes:["face"],...t?{anchors:p$,meanRgb:c$}:{anchors:u$,withClassScores:!0}};super(n)}get withSeparableConvs(){return this.config.withSeparableConvs}get anchors(){return this.config.anchors}async locateFaces(t,n){return(await this.detect(t,n)).map(r=>new wt(r.score,r.relativeBox,{width:r.imageWidth,height:r.imageHeight}))}getDefaultModelName(){return this.withSeparableConvs?h$:d$}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};function kSe(e,t=!0){let n=new xp(t);return n.extractWeights(e),n}var Tg=class extends br{constructor(){super(...arguments);this._name="TinyFaceDetectorOptions"}};var Ra=class{async then(t){return t(await this.run())}async run(){throw new Error("ComposableTask - run is not implemented")}};async function Mo(e,t,n,a,r=({alignedRect:s})=>s){let s=e.map(l=>mp(l)?r(l):l.detection),i=a||(t instanceof Ae?await wd(t,s):await vd(t,s)),o=await n(i);return i.forEach(l=>l instanceof Ae&&l.dispose()),o}async function vp(e,t,n,a,r){return Mo([e],t,async s=>n(s[0]),a,r)}var y$=.4,b$=[new Oe(1.603231,2.094468),new Oe(6.041143,7.080126),new Oe(2.882459,3.518061),new Oe(4.266906,5.178857),new Oe(9.041765,10.66308)],x$=[117.001,114.697,97.404];var wp=class extends Ro{constructor(){let t={withSeparableConvs:!0,iouThreshold:y$,classes:["face"],anchors:b$,meanRgb:x$,isFirstLayerConv2d:!0,filterSizes:[3,16,32,64,128,256,512]};super(t)}get anchors(){return this.config.anchors}async locateFaces(t,n){return(await this.detect(t,n)).map(r=>new wt(r.score,r.relativeBox,{width:r.imageWidth,height:r.imageHeight}))}getDefaultModelName(){return"tiny_face_detector_model"}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};var rt={ssdMobilenetv1:new Do,tinyFaceDetector:new wp,tinyYolov2:new xp,faceLandmark68Net:new gp,faceLandmark68TinyNet:new Ig,faceRecognitionNet:new yp,faceExpressionNet:new yg,ageGenderNet:new wg},Dpe=(e,t)=>rt.ssdMobilenetv1.locateFaces(e,t),ZSe=(e,t)=>rt.tinyFaceDetector.locateFaces(e,t),QSe=(e,t)=>rt.tinyYolov2.locateFaces(e,t),Rpe=e=>rt.faceLandmark68Net.detectLandmarks(e),eNe=e=>rt.faceLandmark68TinyNet.detectLandmarks(e),tNe=e=>rt.faceRecognitionNet.computeFaceDescriptor(e),nNe=e=>rt.faceExpressionNet.predictExpressions(e),aNe=e=>rt.ageGenderNet.predictAgeAndGender(e),Mpe=e=>rt.ssdMobilenetv1.load(e),rNe=e=>rt.tinyFaceDetector.load(e),sNe=e=>rt.tinyYolov2.load(e),iNe=e=>rt.faceLandmark68Net.load(e),oNe=e=>rt.faceLandmark68TinyNet.load(e),lNe=e=>rt.faceRecognitionNet.load(e),uNe=e=>rt.faceExpressionNet.load(e),pNe=e=>rt.ageGenderNet.load(e),cNe=Mpe,dNe=Dpe,hNe=Rpe;var Cg=class extends Ra{constructor(n,a,r){super();this.parentTask=n;this.input=a;this.extractedFaces=r}},Po=class extends Cg{async run(){let t=await this.parentTask,n=await Mo(t,this.input,async a=>Promise.all(a.map(r=>rt.faceExpressionNet.predictExpressions(r))),this.extractedFaces);return t.map((a,r)=>k1(a,n[r]))}withAgeAndGender(){return new Lo(this,this.input)}},Oo=class extends Cg{async run(){let t=await this.parentTask;if(!t)return;let n=await vp(t,this.input,a=>rt.faceExpressionNet.predictExpressions(a),this.extractedFaces);return k1(t,n)}withAgeAndGender(){return new zo(this,this.input)}},As=class extends Po{withAgeAndGender(){return new Fs(this,this.input)}withFaceDescriptors(){return new Rs(this,this.input)}},$s=class extends Oo{withAgeAndGender(){return new Ds(this,this.input)}withFaceDescriptor(){return new Ms(this,this.input)}};var _g=class extends Ra{constructor(n,a,r){super();this.parentTask=n;this.input=a;this.extractedFaces=r}},Lo=class extends _g{async run(){let t=await this.parentTask,n=await Mo(t,this.input,async a=>Promise.all(a.map(r=>rt.ageGenderNet.predictAgeAndGender(r))),this.extractedFaces);return t.map((a,r)=>{let{age:s,gender:i,genderProbability:o}=n[r];return _1(E1(a,i,o),s)})}withFaceExpressions(){return new Po(this,this.input)}},zo=class extends _g{async run(){let t=await this.parentTask;if(!t)return;let{age:n,gender:a,genderProbability:r}=await vp(t,this.input,s=>rt.ageGenderNet.predictAgeAndGender(s),this.extractedFaces);return _1(E1(t,a,r),n)}withFaceExpressions(){return new Oo(this,this.input)}},Fs=class extends Lo{withFaceExpressions(){return new As(this,this.input)}withFaceDescriptors(){return new Rs(this,this.input)}},Ds=class extends zo{withFaceExpressions(){return new $s(this,this.input)}withFaceDescriptor(){return new Ms(this,this.input)}};var Eg=class extends Ra{constructor(n,a){super();this.parentTask=n;this.input=a}},Rs=class extends Eg{async run(){let t=await this.parentTask;return(await Mo(t,this.input,a=>Promise.all(a.map(r=>rt.faceRecognitionNet.computeFaceDescriptor(r))),null,a=>a.landmarks.align(null,{useDlibAlignment:!0}))).map((a,r)=>C1(t[r],a))}withFaceExpressions(){return new As(this,this.input)}withAgeAndGender(){return new Fs(this,this.input)}},Ms=class extends Eg{async run(){let t=await this.parentTask;if(!t)return;let n=await vp(t,this.input,a=>rt.faceRecognitionNet.computeFaceDescriptor(a),null,a=>a.landmarks.align(null,{useDlibAlignment:!0}));return C1(t,n)}withFaceExpressions(){return new $s(this,this.input)}withAgeAndGender(){return new Ds(this,this.input)}};var Ag=class extends Ra{constructor(n,a,r){super();this.parentTask=n;this.input=a;this.useTinyLandmarkNet=r}get landmarkNet(){return this.useTinyLandmarkNet?rt.faceLandmark68TinyNet:rt.faceLandmark68Net}},$g=class extends Ag{async run(){let t=await this.parentTask,n=t.map(i=>i.detection),a=this.input instanceof Ae?await wd(this.input,n):await vd(this.input,n),r=await Promise.all(a.map(i=>this.landmarkNet.detectLandmarks(i)));return a.forEach(i=>i instanceof Ae&&i.dispose()),t.filter((i,o)=>r[o]).map((i,o)=>Nd(i,r[o]))}withFaceExpressions(){return new As(this,this.input)}withAgeAndGender(){return new Fs(this,this.input)}withFaceDescriptors(){return new Rs(this,this.input)}},Fg=class extends Ag{async run(){let t=await this.parentTask;if(!t)return;let{detection:n}=t,a=this.input instanceof Ae?await wd(this.input,[n]):await vd(this.input,[n]),r=await this.landmarkNet.detectLandmarks(a[0]);return a.forEach(s=>s instanceof Ae&&s.dispose()),Nd(t,r)}withFaceExpressions(){return new $s(this,this.input)}withAgeAndGender(){return new Ds(this,this.input)}withFaceDescriptor(){return new Ms(this,this.input)}};var Dg=class extends Ra{constructor(n,a=new Da){super();this.input=n;this.options=a}},Cd=class extends Dg{async run(){let{input:t,options:n}=this,a;if(n instanceof Tg)a=rt.tinyFaceDetector.locateFaces(t,n);else if(n instanceof Da)a=rt.ssdMobilenetv1.locateFaces(t,n);else if(n instanceof br)a=rt.tinyYolov2.locateFaces(t,n);else throw new Error("detectFaces - expected options to be instance of TinyFaceDetectorOptions | SsdMobilenetv1Options | TinyYolov2Options");return a}runAndExtendWithFaceDetections(){return new Promise((t,n)=>{this.run().then(a=>t(a.map(r=>rp({},r)))).catch(a=>n(a))})}withFaceLandmarks(t=!1){return new $g(this.runAndExtendWithFaceDetections(),this.input,t)}withFaceExpressions(){return new Po(this.runAndExtendWithFaceDetections(),this.input)}withAgeAndGender(){return new Lo(this.runAndExtendWithFaceDetections(),this.input)}},Rg=class extends Dg{async run(){let t=await new Cd(this.input,this.options),n=t[0];return t.forEach(a=>{a.score>n.score&&(n=a)}),n}runAndExtendWithFaceDetection(){return new Promise(async t=>{let n=await this.run();t(n?rp({},n):void 0)})}withFaceLandmarks(t=!1){return new Fg(this.runAndExtendWithFaceDetection(),this.input,t)}withFaceExpressions(){return new Oo(this.runAndExtendWithFaceDetection(),this.input)}withAgeAndGender(){return new zo(this.runAndExtendWithFaceDetection(),this.input)}};function p2e(e,t=new Da){return new Rg(e,t)}function $1(e,t=new Da){return new Cd(e,t)}async function Ppe(e,t){return $1(e,new Da(t?{minConfidence:t}:{})).withFaceLandmarks().withFaceDescriptors()}async function g2e(e,t={}){return $1(e,new br(t)).withFaceLandmarks().withFaceDescriptors()}var y2e=Ppe;function v$(e,t){if(e.length!==t.length)throw new Error("euclideanDistance: arr1.length !== arr2.length");let n=Array.from(e),a=Array.from(t);return Math.sqrt(n.map((r,s)=>r-a[s]).reduce((r,s)=>r+s**2,0))}var Mg=class{constructor(t,n=.6){this._distanceThreshold=n;let a=Array.isArray(t)?t:[t];if(!a.length)throw new Error("FaceRecognizer.constructor - expected atleast one input");let r=1,s=()=>`person ${r++}`;this._labeledDescriptors=a.map(i=>{if(i instanceof Mr)return i;if(i instanceof Float32Array)return new Mr(s(),[i]);if(i.descriptor&&i.descriptor instanceof Float32Array)return new Mr(s(),[i.descriptor]);throw new Error("FaceRecognizer.constructor - expected inputs to be of type LabeledFaceDescriptors | WithFaceDescriptor | Float32Array | Array | Float32Array>")})}get labeledDescriptors(){return this._labeledDescriptors}get distanceThreshold(){return this._distanceThreshold}computeMeanDistance(t,n){return n.map(a=>v$(a,t)).reduce((a,r)=>a+r,0)/(n.length||1)}matchDescriptor(t){return this.labeledDescriptors.map(({descriptors:n,label:a})=>new gd(a,this.computeMeanDistance(t,n))).reduce((n,a)=>n.distancet.toJSON())}}static fromJSON(t){let n=t.labeledDescriptors.map(a=>Mr.fromJSON(a));return new Mg(n,t.distanceThreshold)}};function M2e(e){let t=new wp;return t.extractWeights(e),t}function Ope(e,t){let{width:n,height:a}=new $n(t.width,t.height);if(n<=0||a<=0)throw new Error(`resizeResults - invalid dimensions: ${JSON.stringify({width:n,height:a})}`);if(Array.isArray(e))return e.map(r=>Ope(r,{width:n,height:a}));if(mp(e)){let r=e.detection.forSize(n,a),s=e.unshiftedLandmarks.forSize(r.box.width,r.box.height);return Nd(rp(e,r),s)}return Pr(e)?rp(e,e.detection.forSize(n,a)):e instanceof xa||e instanceof wt?e.forSize(n,a):e}var j2e=VA;export{wg as AgeGenderNet,tp as BoundingBox,ct as Box,Ra as ComposableTask,Rs as ComputeAllFaceDescriptorsTask,Eg as ComputeFaceDescriptorsTaskBase,Ms as ComputeSingleFaceDescriptorTask,$g as DetectAllFaceLandmarksTask,Cd as DetectAllFacesTask,Ag as DetectFaceLandmarksTaskBase,Dg as DetectFacesTaskBase,Fg as DetectSingleFaceLandmarksTask,Rg as DetectSingleFaceTask,$n as Dimensions,zA as FACE_EXPRESSION_LABELS,wt as FaceDetection,o$ as FaceDetectionNet,yg as FaceExpressionNet,Es as FaceExpressions,gp as FaceLandmark68Net,Ig as FaceLandmark68TinyNet,YA as FaceLandmarkNet,xa as FaceLandmarks,TA as FaceLandmarks5,ap as FaceLandmarks68,gd as FaceMatch,Mg as FaceMatcher,yp as FaceRecognitionNet,S1 as Gender,yd as LabeledBox,Mr as LabeledFaceDescriptors,Lr as NetInput,dn as NeuralNetwork,Cs as ObjectDetection,Oe as Point,CA as PredictedBox,np as Rect,Do as SsdMobilenetv1,Da as SsdMobilenetv1Options,wp as TinyFaceDetector,Tg as TinyFaceDetectorOptions,xp as TinyYolov2,br as TinyYolov2Options,y2e as allFaces,Ppe as allFacesSsdMobilenetv1,g2e as allFacesTinyYolov2,_A as awaitMediaLoaded,EA as bufferToImage,tNe as computeFaceDescriptor,lp as createCanvas,ug as createCanvasFromMedia,$Ie as createFaceDetectionNet,$ke as createFaceRecognitionNet,Ape as createSsdMobilenetv1,M2e as createTinyFaceDetector,kSe as createTinyYolov2,$1 as detectAllFaces,Rpe as detectFaceLandmarks,eNe as detectFaceLandmarksTiny,hNe as detectLandmarks,p2e as detectSingleFace,WA as draw,at as env,v$ as euclideanDistance,_1 as extendWithAge,C1 as extendWithFaceDescriptor,rp as extendWithFaceDetection,k1 as extendWithFaceExpressions,Nd as extendWithFaceLandmarks,E1 as extendWithGender,wd as extractFaceTensors,vd as extractFaces,Wxe as fetchImage,FA as fetchJson,jxe as fetchNetWeights,_s as fetchOrThrow,Zxe as fetchVideo,aa as getContext2dOrThrow,op as getMediaDimensions,AA as imageTensorToCanvas,$A as imageToSquare,nye as inverseSigmoid,kA as iou,w1 as isMediaElement,lg as isMediaLoaded,Mke as isWithAge,Pr as isWithFaceDetection,BA as isWithFaceExpressions,mp as isWithFaceLandmarks,zke as isWithGender,pNe as loadAgeGenderModel,cNe as loadFaceDetectionModel,uNe as loadFaceExpressionModel,iNe as loadFaceLandmarkModel,oNe as loadFaceLandmarkTinyModel,lNe as loadFaceRecognitionModel,Mpe as loadSsdMobilenetv1Model,rNe as loadTinyFaceDetectorModel,sNe as loadTinyYolov2Model,RA as loadWeightMap,dNe as locateFaces,sve as matchDimensions,IA as minBbox,rt as nets,SA as nonMaxSuppression,yr as normalize,NA as padToSquare,aNe as predictAgeAndGender,nNe as recognizeFaceExpressions,Ope as resizeResults,sp as resolveInput,eye as shuffleArray,sg as sigmoid,Dpe as ssdMobilenetv1,Be as tf,ZSe as tinyFaceDetector,QSe as tinyYolov2,kt as toNetInput,wA as utils,m$ as validateConfig,j2e as version}; //# sourceMappingURL=face-api.esm.js.map diff --git a/dist/face-api.js b/dist/face-api.js index b568252..692f361 100644 --- a/dist/face-api.js +++ b/dist/face-api.js @@ -4686,4 +4686,4 @@ return a / b;`,Tne=` } `}};function yse(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,segmentIds:s}=t,{numSegments:i}=a,o=r.shape.length,l=[],u=0,p=C.getAxesPermutation([u],o),d=r;p!=null&&(d=Cn({inputs:{x:r},backend:n,attrs:{perm:p}}),l.push(d),u=C.getInnerMostAxes(1,o)[0]);let c=C.segment_util.computeOutShape(d.shape,u,i),h=w.sizeFromShape([d.shape[u]]),m=he({inputs:{x:d},backend:n,attrs:{shape:[-1,h]}});l.push(m);let f=rf(r.dtype),g=(v,I,T,_,A)=>{let F=v.shape[0],P=v.shape[1],$=C.segment_util.segOpComputeOptimalWindowSize(P,A),S={windowSize:$,inSize:P,batchSize:F,numSegments:A},M=new gse(S,I),U=n.compileAndRun(M,[v,T],_);if(l.push(U),U.shape[1]===A)return U;let j=RE({backend:n,attrs:{start:0,stop:A,step:1,dtype:"float32"}}),q=PE({inputs:{x:j},backend:n,attrs:{reps:[P/$]}});return l.push(j),l.push(q),g(U,I,q,_,A)},y=g(m,"unsortedSegmentSum",s,f,i),b=he({inputs:{x:y},backend:n,attrs:{shape:c}}),x=b;if(p!=null){l.push(b);let v=C.getUndoAxesPermutation(p);x=Cn({inputs:{x},backend:n,attrs:{perm:v}})}return 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vc;(function(e){e[e.linear=0]="linear",e[e.relu=1]="relu",e[e.relu6=2]="relu6",e[e.prelu=3]="prelu",e[e.leakyrelu=4]="leakyrelu",e[e.sigmoid=5]="sigmoid",e[e.elu=6]="elu"})(vc||(vc={}));var OE;function vse(e){OE=e.wasm.cwrap(si,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function wse(e){let{inputs:t,backend:n,attrs:a}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t;if(r.dtype!=="float32"||s.dtype!=="float32")throw new Error("_FusedMatMul for non non-float32 tensors not yet supported.");let{transposeA:l,transposeB:u,activation:p,leakyreluAlpha:d}=a,c=n.dataIdMap.get(r.dataId).id,h=n.dataIdMap.get(s.dataId).id,m=0;if(i!=null){let A=n.dataIdMap.get(i.dataId);if(A.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${A.shape.length}.`);m=A.id}let f=o==null?0:n.dataIdMap.get(o.dataId).id,g=vc[p];if(g==null)throw new Error(`${p} activation not yet supported for FusedConv2D in the wasm backend.`);let y=l?r.shape[2]:r.shape[1],b=u?s.shape[1]:s.shape[2],x=Hu.assertAndGetBroadcastShape(r.shape.slice(0,-2),s.shape.slice(0,-2)),v=n.makeOutput([...x,y,b],r.dtype),I=n.dataIdMap.get(v.dataId).id,T=new Uint8Array(new Int32Array(r.shape).buffer),_=new Uint8Array(new Int32Array(s.shape).buffer);return OE(c,T,r.shape.length,h,_,s.shape.length,l,u,g,m,f,d||0,I),v}var kse={kernelName:si,backendName:"wasm",setupFunc:vse,kernelFunc:wse};function rn(e,t){let n;function a(s){n=s.wasm.cwrap(e,null,["number","number","number"])}function r(s){let{backend:i,inputs:{x:o}}=s,l=i.dataIdMap.get(o.dataId).id,u=i.makeOutput(o.shape,t||o.dtype),p=i.dataIdMap.get(u.dataId).id;return w.sizeFromShape(u.shape)===0||n(l,$t[o.dtype],p),u}return{kernelName:e,backendName:"wasm",setupFunc:a,kernelFunc:r}}var Ise=rn(Wl);function dn(e,t,n){let a;function r(i){a=i.wasm.cwrap(e,null,["number","array","number","number","array","number","number","number"])}function s(i){let{backend:o,inputs:l}=i,{a:u,b:p}=l,d=o.dataIdMap.get(u.dataId).id,c=o.dataIdMap.get(p.dataId).id,h=n!=null?n:u.dtype,m=C.assertAndGetBroadcastShape(u.shape,p.shape),f=o.makeOutput(m,h);if(w.sizeFromShape(m)===0)return f;let g=new Uint8Array(new Int32Array(u.shape).buffer),y=new Uint8Array(new Int32Array(p.shape).buffer),b=o.dataIdMap.get(f.dataId).id;return a(d,g,u.shape.length,c,y,p.shape.length,$t[u.dtype],b),f}return{kernelName:e,backendName:"wasm",setupFunc:r,kernelFunc:s}}var Sse=!0,Nse=dn(ys,Sse),LE;function Tse(e){LE=e.wasm.cwrap(wi,null,["array","number","number","number"])}function Cse(e){let{inputs:t,backend:n}=e,a=n.makeOutput(t[0].shape,t[0].dtype);if(w.sizeFromShape(a.shape)===0)return a;let r=t.map(o=>n.dataIdMap.get(o.dataId).id),s=new Uint8Array(new Int32Array(r).buffer),i=n.dataIdMap.get(a.dataId).id;return LE(s,r.length,$t[a.dtype],i),a}var _se={kernelName:wi,backendName:"wasm",setupFunc:Tse,kernelFunc:Cse};function yg(e){let{inputs:{x:t},backend:n}=e,a=n.makeOutput(t.shape,t.dtype),r=n.typedArrayFromHeap(t);return n.typedArrayFromHeap(a).set(r),a}var Ese={kernelName:Bi,backendName:"wasm",kernelFunc:yg},zE;function Ase(e){zE=e.wasm.cwrap(Er,null,["number","array","number","number","number","array","number"])}function ms(e){let{inputs:t,backend:n,attrs:a}=e,[r,s]=Fse(t.x.shape,a.perm),i=!0;for(let m=0;m=r&&(s===-1||a[s]>a[i])&&(s=i);a[s]=r}return[n,a]}var Dse={kernelName:Er,backendName:"wasm",kernelFunc:ms,setupFunc:Ase};function $s(e,t,n){let a=e.shape,r=e.shape.length,s=w.parseAxisParam(t,a),i=s,o=C.getAxesPermutation(i,r),l=null,u=!1;if(o!=null){let p=new Array(r);for(let c=0;c`new shape: ${i}, old shape: ${a.shape}. New shape and old shape must have the same number of elements.`),e.backend.incRef(a.dataId),{dataId:a.dataId,shape:i,dtype:a.dtype}}var jse={kernelName:_u,backendName:"wasm",kernelFunc:Vn},GE;function qse(e){GE=e.wasm.cwrap(Si,null,["number","array","number","number","array","number","number","number","number"])}function Kse(e){let{inputs:t,backend:n,attrs:a}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=a;if(r.dtype!=="float32"||s.dtype!=="float32")throw new Error("BatchMatMul for non non-float32 tensors not yet supported.");let l=r.shape.length,u=s.shape.length,p=i?r.shape[l-2]:r.shape[l-1],d=o?s.shape[u-1]:s.shape[u-2],c=i?r.shape[l-1]:r.shape[l-2],h=o?s.shape[u-2]:s.shape[u-1],m=r.shape.slice(0,-2),f=s.shape.slice(0,-2),g=w.sizeFromShape(m),y=w.sizeFromShape(f),b=Hu.assertAndGetBroadcastShape(r.shape.slice(0,-2),s.shape.slice(0,-2)).concat([c,h]);w.assert(p===d,()=>`Error in matMul: inner shapes (${p}) and (${d}) of Tensors with shapes ${r.shape} and ${s.shape} and transposeA=${i} and transposeB=${o} must match.`);let x=i?[g,p,c]:[g,c,p],v=o?[y,h,d]:[y,d,h],I=Vn({inputs:{x:r},backend:n,attrs:{shape:x}}),T=Vn({inputs:{x:s},backend:n,attrs:{shape:v}}),_=n.dataIdMap.get(I.dataId).id,A=n.dataIdMap.get(T.dataId).id,F=i?I.shape[2]:I.shape[1],P=o?T.shape[1]:T.shape[2],$=Math.max(g,y),S=n.makeOutput([$,F,P],I.dtype),M=n.dataIdMap.get(S.dataId).id,U=new Uint8Array(new Int32Array(I.shape).buffer),j=new Uint8Array(new Int32Array(T.shape).buffer);return GE(_,U,I.shape.length,A,j,T.shape.length,i,o,M),n.disposeData(I.dataId),n.disposeData(T.dataId),S.shape=b,S}var Xse={kernelName:Si,backendName:"wasm",setupFunc:qse,kernelFunc:Kse};function xi(e){let{inputs:{x:t},attrs:{begin:n,size:a},backend:r}=e,[s,i]=qt.parseSliceParams(t,n,a),o=qt.isSliceContinous(t.shape,s,i),l=r.readSync(t.dataId),u=r.makeOutput(i,t.dtype),p=w.computeStrides(t.shape),d=r.dataIdMap.get(u.dataId);if(o){let m=qt.computeFlatOffset(s,p);return t.dtype==="string"?d.stringBytes=l.slice(m,m+w.sizeFromShape(i)):r.typedArrayFromHeap(u).set(l.subarray(m,m+w.sizeFromShape(i))),u}if(t.dtype==="string"){let m=gm(l,s,i,t.shape,t.dtype);return d.stringBytes=m,u}let c=r.typedArrayFromHeap(u),h=t.shape.length;if(h===2)Yse(l,p[0],c,s,i);else if(h===3)Jse(l,p[0],p[1],c,s,i);else if(h===4)Zse(l,p[0],p[1],p[2],c,s,i);else{let m=gm(l,s,i,t.shape,t.dtype);c.set(m)}return u}function Yse(e,t,n,a,r){let s=0,i=a[0],o=a[1],l=i+r[0];for(let u=i;uy*b),l=C.getReshaped(r.shape,s,o),u=C.getPermuted(l.length,s.length),p=C.getReshapedPermuted(r.shape,s,o),d=C.getSliceBeginCoords(i,s.length),c=C.getSliceSize(p,i,s.length),h=Vn({inputs:{x:r},backend:n,attrs:{shape:l}}),m=ms({inputs:{x:h},backend:n,attrs:{perm:u}}),f=Vn({inputs:{x:m},backend:n,attrs:{shape:p}}),g=xi({inputs:{x:f},backend:n,attrs:{begin:d,size:c}});return n.disposeData(h.dataId),n.disposeData(m.dataId),n.disposeData(h.dataId),g}var tie={kernelName:Jl,backendName:"wasm",kernelFunc:eie};function cp(e){let{inputs:{x:t},attrs:{dtype:n},backend:a}=e,r=a.makeOutput(t.shape,n),s=a.typedArrayFromHeap(t);return a.typedArrayFromHeap(r).set(s),r}var nie={kernelName:Ni,backendName:"wasm",kernelFunc:cp},aie=rn(Ti),HE;function rie(e){HE=e.wasm.cwrap(bs,null,["number","number","number","number"])}function sie(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{clipValueMin:s,clipValueMax:i}=a,o=n.dataIdMap.get(r.dataId).id,l=n.makeOutput(r.shape,r.dtype),u=n.dataIdMap.get(l.dataId).id;return HE(o,s,i,u),l}var iie={kernelName:bs,backendName:"wasm",setupFunc:rie,kernelFunc:sie};function jE(e){let{inputs:t,backend:n}=e,a=w.parseAxisParam(e.attrs.axis,t[0].shape)[0],r=C.computeOutShape(t.map(h=>h.shape),a),s=t.filter(h=>w.sizeFromShape(h.shape)>0);if(s.length===1)return yg({inputs:{x:s[0]},backend:n});let i=n.makeOutput(r,t[0].dtype);if(w.sizeFromShape(r)===0)return i;let o=s.map(h=>h.shape);if(C.assertParamsConsistent(o,a),s[0].dtype==="string"){let h=s.map(x=>{let v=w.sizeFromShape(x.shape.slice(a));return Vn({inputs:{x},backend:n,attrs:{shape:[-1,v]}})}),m=h.map(x=>({vals:n.readSync(x.dataId),shape:x.shape}));r=C.computeOutShape(h.map(x=>x.shape),1);let f=h[0].shape[0]===1,g=q0(m,r,t[0].dtype,f),y=C.computeOutShape(s.map(x=>x.shape),a);i.shape=y;let b=n.dataIdMap.get(i.dataId);return b.stringBytes=C.fromStringArrayToUint8(g),h.forEach(x=>n.disposeData(x.dataId)),i}let l=w.sizeFromShape(s[0].shape.slice(0,a)),u=0,p=s.map(h=>{let m=w.sizeFromShape(h.shape.slice(a));return u+=m,m}),d=s.map(h=>n.typedArrayFromHeap(h)),c=n.typedArrayFromHeap(i);for(let h=0;h`cumprod does not support ${r.dtype} tensors in the WASM backend`);let u=C.getAxesPermutation([s],l),p=r;u!==null&&(p=ms({inputs:{x:r},attrs:{perm:u},backend:n}));let d=C.getInnerMostAxes(1,l)[0];C.assertAxesAreInnerMostDims("cumprod",[d],l);let c=n.makeOutput(p.shape,p.dtype),h=p.shape[d],m=n.dataIdMap.get(p.dataId).id,f=n.dataIdMap.get(c.dataId).id;YE(m,i?1:0,o?1:0,h,f,$t[r.dtype]);let g=c;if(u!==null){let y=C.getUndoAxesPermutation(u);g=ms({inputs:{x:c},attrs:{perm:y},backend:n}),n.disposeData(p.dataId),n.disposeData(c.dataId)}return g}var wie={kernelName:Ql,backendName:"wasm",setupFunc:xie,kernelFunc:vie},JE;function kie(e){JE=e.wasm.cwrap($i,null,["number","number","number","number","number","number"])}function Iie(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=a,l=r.shape.length;w.assert(r.dtype==="float32"||r.dtype==="int32",()=>`cumsum does not support ${r.dtype} tensors in the WASM backend`);let u=C.getAxesPermutation([s],l),p=r;u!==null&&(p=ms({inputs:{x:r},attrs:{perm:u},backend:n}));let d=C.getInnerMostAxes(1,l)[0];C.assertAxesAreInnerMostDims("cumsum",[d],l);let c=n.makeOutput(p.shape,p.dtype),h=p.shape[d],m=n.dataIdMap.get(p.dataId).id,f=n.dataIdMap.get(c.dataId).id;JE(m,i?1:0,o?1:0,h,f,$t[r.dtype]);let g=c;if(u!==null){let y=C.getUndoAxesPermutation(u);g=ms({inputs:{x:c},attrs:{perm:y},backend:n}),n.disposeData(p.dataId),n.disposeData(c.dataId)}return g}var Sie={kernelName:$i,backendName:"wasm",setupFunc:kie,kernelFunc:Iie},ZE;function Nie(e){ZE=e.wasm.cwrap(tu,null,["number","number","number","array","number","array","array","number","number"])}function Tie(e){let{backend:t,inputs:n,attrs:a}=e,{x:r}=n,{blockSize:s,dataFormat:i}=a,o=r.shape[0],l=i==="NHWC"?r.shape[1]:r.shape[2],u=i==="NHWC"?r.shape[2]:r.shape[3],p=i==="NHWC"?r.shape[3]:r.shape[1],d=l*s,c=u*s,h=p/(s*s),m=i==="NHWC"?[o,d,c,h]:[o,h,d,c],f=t.makeOutput(m,"float32"),g=t.dataIdMap.get(r.dataId).id,y=new Uint8Array(new Int32Array(w.computeStrides(r.shape)).buffer),b=new Uint8Array(new Int32Array(m).buffer),x=new Uint8Array(new Int32Array(w.computeStrides(m)).buffer),v=t.dataIdMap.get(f.dataId).id;return ZE(g,s,i==="NHWC"?1:0,y,r.shape.length-1,b,x,m.length,v),f}var Cie={kernelName:tu,backendName:"wasm",setupFunc:Nie,kernelFunc:Tie},QE;function _ie(e){QE=e.wasm.cwrap(Fi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Eie(e){let{inputs:t,attrs:n,backend:a}=e,{x:r,filter:s}=t,i=a.dataIdMap.get(r.dataId).id,o=a.dataIdMap.get(s.dataId).id,{strides:l,dilations:u,pad:p,dimRoundingMode:d}=n,c=u==null?[1,1]:u,h=C.computeConv2DInfo(r.shape,s.shape,l,c,p,d,!0),m=h.filterHeight,f=h.filterWidth,g=h.padInfo.top,y=h.padInfo.right,b=h.padInfo.bottom,x=h.padInfo.left,v=h.dilationHeight,I=h.dilationWidth,T=h.strideHeight,_=h.strideWidth,A=h.inChannels,F=h.outChannels,P=h.padInfo.type==="SAME"?1:0;if(h.dataFormat!=="channelsLast")throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${h.dataFormat}'. Please use 'channelsLast'.`);let $=a.makeOutput(h.outShape,"float32"),S=a.dataIdMap.get($.dataId).id;return QE(i,r.shape[0],r.shape[1],r.shape[2],o,m,f,g,y,b,x,P,v,I,T,_,A,F,S),$}var Aie={kernelName:Fi,backendName:"wasm",setupFunc:_ie,kernelFunc:Eie},$ie=rn(Ri),Fie=!1,Die=dn(au,Fie,"bool"),Rie=rn(Mi,"float32");function Mx(e){let{inputs:t,attrs:n,backend:a}=e,{input:r}=t,{dim:s}=n,i=r.shape.length,o=r.shape.slice(),l=s;return s<0&&(w.assert(-(i+1)<=s,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+s+1),o.splice(l,0,1),Vn({inputs:{x:r},backend:a,attrs:{shape:o}})}var Mie={kernelName:ru,backendName:"wasm",kernelFunc:Mx};function eA(e){let{attrs:{shape:t,value:n,dtype:a},backend:r}=e,s=r.makeOutput(t,a);return r.typedArrayFromHeap(s).fill(n),s}var Pie={kernelName:Cc,backendName:"wasm",kernelFunc:eA},tA;function Oie(e){tA=e.wasm.cwrap(iu,null,["number","number","number","number","number","number"])}function Lie(e){let{inputs:t,backend:n}=e,{image:a}=t,r=n.makeOutput(a.shape,a.dtype),s=n.dataIdMap.get(a.dataId).id,i=n.dataIdMap.get(r.dataId).id,[o,l,u,p]=a.shape;return tA(s,o,l,u,p,i),r}var zie={kernelName:iu,backendName:"wasm",kernelFunc:Lie,setupFunc:Oie},Bie=rn(Pi),Wie=!1,Vie=dn(Oi,Wie),nA;function Uie(e){nA=e.wasm.cwrap(Li,null,["number","number","number","number","number","number","number"])}function Gie(e){let{backend:t,inputs:n,attrs:a}=e,{varianceEpsilon:r}=a,{x:s,mean:i,variance:o,offset:l,scale:u}=n,p=t.dataIdMap.get(s.dataId).id,d=t.dataIdMap.get(i.dataId).id,c=t.dataIdMap.get(o.dataId).id,h=l!=null?t.dataIdMap.get(l.dataId).id:0,m=u!=null?t.dataIdMap.get(u.dataId).id:0,f=t.makeOutput(s.shape,s.dtype);if(w.sizeFromShape(s.shape)===0)return f;let g=t.dataIdMap.get(f.dataId).id;return nA(p,d,c,h,m,r,g),f}var Hie={kernelName:Li,backendName:"wasm",setupFunc:Uie,kernelFunc:Gie},aA;function jie(e){aA=e.wasm.cwrap(ii,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function qie(e){let{inputs:t,attrs:n,backend:a}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:p,dataFormat:d,dimRoundingMode:c,activation:h,leakyreluAlpha:m}=n,f=C.computeConv2DInfo(r.shape,s.shape,l,p,u,c),g=vc[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedConv2D in the wasm backend.`);let y=a.dataIdMap.get(r.dataId).id,b=a.dataIdMap.get(s.dataId).id,x=f.outChannels,v=0;if(i!=null){let ae=a.dataIdMap.get(i.dataId);if(ae.shape.length!==1)throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${ae.shape.length}.`);if(ae.shape[0]!==x)throw new Error(`FusedConv2D bias shape (${ae.shape}) does not match the number of output channels (${x})`);v=ae.id}let I=f.filterHeight,T=f.filterWidth,_=f.padInfo.top,A=f.padInfo.right,F=f.padInfo.bottom,P=f.padInfo.left,$=f.dilationHeight,S=f.dilationWidth,M=f.strideHeight,U=f.strideWidth,j=f.inChannels,q=f.padInfo.type==="SAME"?1:0,K=f.batchSize,Y=f.inHeight,te=f.inWidth;if(d!=="NHWC")throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${d}'. Please use 'NHWC'.`);let re=a.makeOutput(f.outShape,"float32"),Q=a.dataIdMap.get(re.dataId).id,ie=o==null?0:a.dataIdMap.get(o.dataId).id;return aA(y,K,Y,te,b,I,T,v,_,A,F,P,q,$,S,M,U,j,x,g,ie,m||0,Q),re}var Kie={kernelName:ii,backendName:"wasm",setupFunc:jie,kernelFunc:qie},rA;function Xie(e){rA=e.wasm.cwrap(oi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Yie(e){let{inputs:t,attrs:n,backend:a}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:p,dataFormat:d,dimRoundingMode:c,activation:h,leakyreluAlpha:m}=n,f=C.computeConv2DInfo(r.shape,s.shape,l,p,u,c,!0),g=vc[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedDepthwiseConv2D in the wasm backend.`);let y=a.dataIdMap.get(r.dataId).id,b=a.dataIdMap.get(s.dataId).id,x=f.outChannels,v=0;if(i!=null){let ae=a.dataIdMap.get(i.dataId);if(ae.shape.length!==1)throw new Error(`FusedDepthwiseConv2D only supports rank-1 bias but got rank ${ae.shape.length}.`);if(ae.shape[0]!==x)throw new Error(`FusedDepthwiseConv2D bias shape (${ae.shape}) does not match the number of output channels (${x})`);v=ae.id}let I=f.filterHeight,T=f.filterWidth,_=f.padInfo.top,A=f.padInfo.right,F=f.padInfo.bottom,P=f.padInfo.left,$=f.dilationHeight,S=f.dilationWidth,M=f.strideHeight,U=f.strideWidth,j=f.inChannels,q=f.padInfo.type==="SAME"?1:0,K=f.batchSize,Y=f.inHeight,te=f.inWidth;if(d!=="NHWC")throw new Error(`wasm backend FusedDepthwiseConv2D does not support dataFormat:'${d}'. Please use 'NHWC'.`);let re=a.makeOutput(f.outShape,"float32"),Q=a.dataIdMap.get(re.dataId).id,ie=o==null?0:a.dataIdMap.get(o.dataId).id;return rA(y,K,Y,te,b,I,T,v,_,A,F,P,q,$,S,M,U,j,x,g,ie,m||0,Q),re}var Jie={kernelName:oi,backendName:"wasm",setupFunc:Xie,kernelFunc:Yie},sA;function Zie(e){sA=e.wasm.cwrap(lu,null,["number","number","number","number","number","number","array","number"])}function Qie(e){let{backend:t,inputs:n}=e,{params:a,indices:r}=n,[s,i,o,l]=nv.prepareAndValidate(a,r),u=t.makeOutput(s,a.dtype);if(i===0)return u;let p=r.shape,d=p[p.length-1],c=t.dataIdMap.get(a.dataId).id,h=t.dataIdMap.get(r.dataId).id,m=new Uint8Array(new Int32Array(l).buffer),f=t.dataIdMap.get(u.dataId).id;return sA(c,$t[a.dtype],h,i,d,o,m,f),u}var eoe={kernelName:lu,backendName:"wasm",setupFunc:Zie,kernelFunc:Qie},iA;function toe(e){iA=e.wasm.cwrap("Gather",null,["number","number","array","number","number","number","array","number"])}function noe(e){let{backend:t,inputs:n,attrs:a}=e,{x:r,indices:s}=n,{axis:i,batchDims:o}=a,l=w.parseAxisParam(i,r.shape)[0],u=t.readSync(s.dataId),p=r.shape[l];for(let _=0;_=0,()=>`GatherV2: the index value ${A} is not in [0, ${p-1}]`)}let d=C.segment_util.collectGatherOpShapeInfo(r,s,l,o),c=Vn({inputs:{x:r},attrs:{shape:[d.batchSize,d.outerSize,d.dimSize,d.sliceSize]},backend:t}),h=w.sizeFromShape(s.shape),m=Vn({inputs:{x:s},attrs:{shape:[d.batchSize,h/d.batchSize]},backend:t}),f=[d.batchSize,d.outerSize,h/d.batchSize,d.sliceSize],g=t.makeOutput(f,r.dtype);if(w.sizeFromShape(r.shape)===0)return g;let y=c.shape.length-1,b=t.dataIdMap.get(c.dataId).id,x=t.dataIdMap.get(m.dataId).id,v=t.dataIdMap.get(g.dataId).id,I=new Uint8Array(new Int32Array(w.computeStrides(c.shape)).buffer),T=new Uint8Array(new Int32Array(w.computeStrides(f)).buffer);return iA(b,$t[r.dtype],I,y,x,d.batchSize,T,v),t.disposeData(c.dataId),t.disposeData(m.dataId),g.shape=d.outputShape,g}var aoe={kernelName:ou,backendName:"wasm",setupFunc:toe,kernelFunc:noe},roe=!1,soe=dn(uu,roe,"bool"),ioe=!1,ooe=dn(zi,ioe,"bool"),oA;function loe(e){oA=e.wasm.cwrap(Wi,null,["number","number","number","number"])}function uoe(e){let{inputs:{x:t},attrs:{alpha:n},backend:a}=e,r=a.dataIdMap.get(t.dataId).id,s=a.makeOutput(t.shape,"float32");if(w.sizeFromShape(t.shape)!==0){let i=a.dataIdMap.get(s.dataId).id;oA(r,$t[t.dtype],n,i)}return s}var poe={kernelName:Wi,backendName:"wasm",setupFunc:loe,kernelFunc:uoe},coe=!1,doe=dn(hu,coe,"bool"),hoe=!1,moe=dn(mu,hoe,"bool"),foe=rn(Vi),goe=!1,yoe=dn(gu,goe,"bool"),boe=rn(yu),xoe=!1,voe=dn(bu,xoe,"bool"),woe=!1,koe=dn(oS,woe,"bool"),lA;function Ioe(e){lA=e.wasm.cwrap(Ui,null,["number","number","number","number"])}function Soe(e){let{backend:t,inputs:n,attrs:a}=e,{reductionIndices:r,keepDims:s}=a,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:u,axes:p,originalAxes:d,inputWasTransposed:c}=$s(i,r,t);if(c){let b=t.dataIdMap.get(u.dataId).id;l=u,o=b}let h=l.shape.length;C.assertAxesAreInnerMostDims("max",p,h);let[m,f]=C.computeOutAndReduceShapes(l.shape,p),g=w.sizeFromShape(f),y=t.makeOutput(m,i.dtype);if(w.sizeFromShape(l.shape)!==0){let b=t.dataIdMap.get(y.dataId).id;lA(o,$t[i.dtype],g,b)}if(c&&t.disposeData(u.dataId),s){let b=C.expandShapeToKeepDim(y.shape,d);y.shape=b}return y}var Noe={kernelName:Ui,backendName:"wasm",setupFunc:Ioe,kernelFunc:Soe},Toe=!1,Coe=dn(Gi,Toe),uA;function _oe(e){uA=e.wasm.cwrap(Hi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Eoe(e){let{inputs:t,attrs:n,backend:a}=e,r=t.x,s=a.dataIdMap.get(r.dataId).id;w.assert(r.dtype==="float32",()=>`Error in MaxPool: only float32 input is supported. Got ${r.dtype}.`);let{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n,p=C.computePool2DInfo(r.shape,i,o,1,l,u),d=p.filterHeight,c=p.filterWidth,h=p.padInfo.top,m=p.padInfo.right,f=p.padInfo.bottom,g=p.padInfo.left,y=p.dilationHeight,b=p.dilationWidth,x=p.strideHeight,v=p.strideWidth,I=p.inChannels,T=p.outChannels;if(p.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${p.dataFormat}'. Please use 'channelsLast'.`);let _=a.makeOutput(p.outShape,"float32"),A=a.dataIdMap.get(_.dataId).id;return uA(s,r.shape[0],r.shape[1],r.shape[2],d,c,h,m,f,g,y,b,x,v,I,T,A),_}var Aoe={kernelName:Hi,backendName:"wasm",setupFunc:_oe,kernelFunc:Eoe},pA;function $oe(e){pA=e.wasm.cwrap(ji,null,["number, number, number"])}function Foe(e){let{backend:t,inputs:n,attrs:a}=e,{axis:r,keepDims:s}=a,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:p,axes:d,originalAxes:c,inputWasTransposed:h}=$s(i,r,t),m=d;if(h){let v=t.dataIdMap.get(p.dataId).id;v!==o&&(u=p,l=v,m=C.getInnerMostAxes(m.length,u.shape.length))}C.assertAxesAreInnerMostDims("mean",m,u.shape.length);let[f,g]=C.computeOutAndReduceShapes(u.shape,m),y=w.sizeFromShape(g),b=u;u.dtype!=="float32"&&(b=cp({backend:t,inputs:{x:u},attrs:{dtype:"float32"}}),l=t.dataIdMap.get(b.dataId).id);let x=t.makeOutput(f,"float32");if(w.sizeFromShape(u.shape)!==0){let v=t.dataIdMap.get(x.dataId).id;pA(l,y,v)}if(h&&t.disposeData(p.dataId),s){let v=C.expandShapeToKeepDim(x.shape,c);x.shape=v}return u.dtype!=="float32"&&t.disposeData(b.dataId),x}var Doe={kernelName:ji,backendName:"wasm",setupFunc:$oe,kernelFunc:Foe},cA;function Roe(e){cA=e.wasm.cwrap(qi,null,["number","number","number","number"])}function Moe(e){let{backend:t,inputs:n,attrs:a}=e,{axis:r,keepDims:s}=a,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:p,axes:d,originalAxes:c,inputWasTransposed:h}=$s(i,r,t);if(h){let x=t.dataIdMap.get(p.dataId).id;x!==o&&(u=p,l=x)}let m=u.shape.length;C.assertAxesAreInnerMostDims("min",d,m);let[f,g]=C.computeOutAndReduceShapes(u.shape,d),y=w.sizeFromShape(g),b=t.makeOutput(f,u.dtype);if(w.sizeFromShape(u.shape)!==0){let x=t.dataIdMap.get(b.dataId).id;cA(l,$t[i.dtype],y,x)}if(h&&t.disposeData(p.dataId),s){let x=C.expandShapeToKeepDim(b.shape,c);b.shape=x}return b}var Poe={kernelName:qi,backendName:"wasm",setupFunc:Roe,kernelFunc:Moe},Ooe=!1,Loe=dn(Ki,Ooe),Px;(function(e){e[e.reflect=0]="reflect",e[e.symmetric=1]="symmetric"})(Px||(Px={}));var dA;function zoe(e){dA=e.wasm.cwrap(Xi,null,["number","array","number","number","array","array","number","number"])}function Boe(e){let{inputs:{x:t},backend:n,attrs:{paddings:a,mode:r}}=e,s=a.map((m,f)=>m[0]+t.shape[f]+m[1]),i=n.dataIdMap.get(t.dataId).id,o=n.makeOutput(s,t.dtype),l=n.dataIdMap.get(o.dataId).id,u=new Uint8Array(new Int32Array(t.shape).buffer),p=a.map(m=>m[0]),d=a.map(m=>m[1]),c=new Uint8Array(new Int32Array(p).buffer),h=new Uint8Array(new Int32Array(d).buffer);return dA(i,u,t.shape.length,$t[t.dtype],c,h,Px[r],l),o}var Woe={kernelName:Xi,backendName:"wasm",kernelFunc:Boe,setupFunc:zoe},Voe=!0,Uoe=dn(Yi,Voe),Goe=rn(vu);function b1(e,t){let n=new Int32Array(e.wasm.HEAPU8.buffer,t,4),a=n[0],r=n[1],s=n[2],i=n[3];return e.wasm._free(t),{pSelectedIndices:a,selectedSize:r,pSelectedScores:s,pValidOutputs:i}}var hA;function Hoe(e){hA=e.wasm.cwrap(ku,"number",["number","number","number","number","number"])}function joe(e){let{backend:t,inputs:n,attrs:a}=e,{iouThreshold:r,maxOutputSize:s,scoreThreshold:i}=a,{boxes:o,scores:l}=n,u=t.dataIdMap.get(o.dataId).id,p=t.dataIdMap.get(l.dataId).id,d=hA(u,p,s,r,i),{pSelectedIndices:c,selectedSize:h,pSelectedScores:m,pValidOutputs:f}=b1(t,d);return t.wasm._free(m),t.wasm._free(f),t.makeOutput([h],"int32",c)}var qoe={kernelName:ku,backendName:"wasm",setupFunc:Hoe,kernelFunc:joe},mA;function Koe(e){mA=e.wasm.cwrap(Iu,"number",["number","number","number","number","number","bool"])}function Xoe(e){let{backend:t,inputs:n,attrs:a}=e,{iouThreshold:r,maxOutputSize:s,scoreThreshold:i,padToMaxOutputSize:o}=a,{boxes:l,scores:u}=n,p=t.dataIdMap.get(l.dataId).id,d=t.dataIdMap.get(u.dataId).id,c=mA(p,d,s,r,i,o),{pSelectedIndices:h,selectedSize:m,pSelectedScores:f,pValidOutputs:g}=b1(t,c);t.wasm._free(f);let y=t.makeOutput([m],"int32",h),b=t.makeOutput([],"int32",g);return[y,b]}var Yoe={kernelName:Iu,backendName:"wasm",setupFunc:Koe,kernelFunc:Xoe},fA;function Joe(e){fA=e.wasm.cwrap(Su,"number",["number","number","number","number","number","number"])}function Zoe(e){let{backend:t,inputs:n,attrs:a}=e,{iouThreshold:r,maxOutputSize:s,scoreThreshold:i,softNmsSigma:o}=a,{boxes:l,scores:u}=n,p=t.dataIdMap.get(l.dataId).id,d=t.dataIdMap.get(u.dataId).id,c=fA(p,d,s,r,i,o),{pSelectedIndices:h,selectedSize:m,pSelectedScores:f,pValidOutputs:g}=b1(t,c);t.wasm._free(g);let y=t.makeOutput([m],"int32",h),b=t.makeOutput([m],"float32",f);return[y,b]}var Qoe={kernelName:Su,backendName:"wasm",setupFunc:Joe,kernelFunc:Zoe},ele=!1,tle=dn(wu,ele,"bool"),gA;function nle(e){gA=e.wasm.cwrap(Ji,null,["number","number","number","number","number"])}function ale(e){let{inputs:t,backend:n,attrs:a}=e,{indices:r}=t,{depth:s,onValue:i,offValue:o}=a,l=n.makeOutput([...r.shape,s],"int32"),u=n.dataIdMap.get(l.dataId).id,p=n.dataIdMap.get(r.dataId).id;return gA(p,s,i,o,u),l}var rle={kernelName:Ji,backendName:"wasm",setupFunc:nle,kernelFunc:ale};function sle(e){let{inputs:{x:t},backend:n}=e,a=n.makeOutput(t.shape,t.dtype);return n.typedArrayFromHeap(a).fill(1),a}var ile={kernelName:Nu,backendName:"wasm",kernelFunc:sle};function ole(e){let{inputs:t,backend:n,attrs:a}=e,{axis:r}=a;if(t.length===1)return Mx({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let s=t[0].shape,i=t[0].dtype;t.forEach(p=>{w.assertShapesMatch(s,p.shape,"All tensors passed to stack must have matching shapes"),w.assert(i===p.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(p=>{let d=Mx({inputs:{input:p},backend:n,attrs:{dim:r}});return o.push(d),d}),u=jE({inputs:l,backend:n,attrs:{axis:r}});return o.forEach(p=>n.disposeData(p.dataId)),u}var lle={kernelName:Tu,backendName:"wasm",kernelFunc:ole},yA;function ule(e){yA=e.wasm.cwrap(Zi,null,["number","array","number","number","array","array","number","number"])}function ple(e){let{inputs:{x:t},backend:n,attrs:{paddings:a,constantValue:r}}=e,s=a.map((m,f)=>m[0]+t.shape[f]+m[1]);if(w.sizeFromShape(t.shape)===0)return eA({backend:n,attrs:{shape:s,value:r,dtype:t.dtype}});let i=n.dataIdMap.get(t.dataId).id,o=n.makeOutput(s,t.dtype),l=n.dataIdMap.get(o.dataId).id,u=new Uint8Array(new Int32Array(t.shape).buffer),p=a.map(m=>m[0]),d=a.map(m=>m[1]),c=new Uint8Array(new Int32Array(p).buffer),h=new Uint8Array(new Int32Array(d).buffer);return yA(i,u,t.shape.length,$t[t.dtype],c,h,r,l),o}var bA={kernelName:Zi,backendName:"wasm",kernelFunc:ple,setupFunc:ule},cle=!1,dle=dn(Qi,cle),xA;function hle(e){xA=e.wasm.cwrap(eo,null,["number","number","number"])}function mle(e){let{inputs:t,backend:n}=e,{x:a,alpha:r}=t,s=n.dataIdMap.get(a.dataId).id,i=n.dataIdMap.get(r.dataId).id,o=s,l=a,u=l;l.dtype!=="float32"&&(u=cp({backend:n,inputs:{x:a},attrs:{dtype:"float32"}}),o=n.dataIdMap.get(u.dataId).id);let p=n.makeOutput(a.shape,"float32"),d=n.dataIdMap.get(p.dataId).id;return xA(o,i,d),l.dtype!=="float32"&&n.disposeData(u.dataId),p}var fle={kernelName:eo,backendName:"wasm",setupFunc:hle,kernelFunc:mle},vA;function gle(e){vA=e.wasm.cwrap(to,null,["number","number","number","number"])}function yle(e){let{backend:t,inputs:n,attrs:a}=e,{axis:r,keepDims:s}=a,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:p,axes:d,originalAxes:c,inputWasTransposed:h}=$s(i,r,t),m=d;if(h){let x=t.dataIdMap.get(p.dataId).id;x!==o&&(u=p,l=x,m=C.getInnerMostAxes(m.length,u.shape.length))}C.assertAxesAreInnerMostDims("prod",m,u.shape.length);let[f,g]=C.computeOutAndReduceShapes(u.shape,m),y=w.sizeFromShape(g),b=t.makeOutput(f,u.dtype);if(w.sizeFromShape(u.shape)!==0){let x=t.dataIdMap.get(b.dataId).id;vA(l,y,$t[b.dtype],x)}if(h&&t.disposeData(p.dataId),s){let x=C.expandShapeToKeepDim(b.shape,c);b.shape=x}return b}var ble={kernelName:to,backendName:"wasm",setupFunc:gle,kernelFunc:yle},xle=e=>{let{backend:t,attrs:n}=e,{start:a,stop:r,step:s,dtype:i}=n,o=Y0(a,r,s,i),l=t.makeOutput([o.length],i);return t.typedArrayFromHeap(l).set(o),l},vle={kernelName:Ac,backendName:"wasm",kernelFunc:xle},wle=!0,kle=dn(Di,wle),Ile=rn(no),Sle=rn(so),wA;function Nle(e){wA=e.wasm.cwrap(ro,null,["number","number","number","number","number","number","number","number","number","number"])}function 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r=Mt(r,[2,2],[2,2],"same"),r=Ur(r,a.conv1),r=Mt(r,[2,2],[2,2],"same"),r=Ur(r,a.conv2),r=Mt(r,[2,2],[2,2],"same"),r=Ur(r,a.conv3),r=Mt(r,[2,2],[2,2],"same"),r=Ur(r,a.conv4),r=Mt(r,[2,2],[2,2],"same"),r=Ur(r,a.conv5),r=Mt(r,[2,2],[1,1],"same"),r=a.conv6?Ur(r,a.conv6):r,r=a.conv7?Ur(r,a.conv7):r,zo(r,a.conv8,"valid",!1)}forwardInput(n,a){let{params:r}=this;if(!r)throw new Error("TinyYolov2 - load model before inference");return O(()=>{let s=le(n.toBatchTensor(a,!1),"float32");return s=this.config.meanRgb?tr(s,this.config.meanRgb):s,s=s.div(255),this.config.withSeparableConvs?this.runMobilenet(s,r):this.runTinyYolov2(s,r)})}async forward(n,a){return this.forwardInput(await vt(n),a)}async detect(n,a={}){let{inputSize:r,scoreThreshold:s}=new ar(a),i=await vt(n),o=await this.forwardInput(i,r),l=O(()=>mt(o)[0].expandDims()),u={width:i.getInputWidth(0),height:i.getInputHeight(0)},p=await this.extractBoxes(l,i.getReshapedInputDimensions(0),s);o.dispose(),l.dispose();let d=p.map(y=>y.box),c=p.map(y=>y.score),h=p.map(y=>y.classScore),m=p.map(y=>this.config.classes[y.label]);return T1(d.map(y=>y.rescale(r)),c,this.config.iouThreshold,!0).map(y=>new Lr(c[y],h[y],m[y],d[y],u))}getDefaultModelName(){return""}extractParamsFromWeightMap(n){return x$(n,this.config)}extractParams(n){let a=this.config.filterSizes||J1.DEFAULT_FILTER_SIZES,r=a?a.length:void 0;if(r!==7&&r!==8&&r!==9)throw new Error(`TinyYolov2 - expected 7 | 8 | 9 convolutional filters, but found ${r} filterSizes in config`);return b$(n,this.config,this.boxEncodingSize,a)}async extractBoxes(n,a,r){let{width:s,height:i}=a,o=Math.max(s,i),l=o/s,u=o/i,p=n.shape[1],d=this.config.anchors.length,[c,h,m]=O(()=>{let b=n.reshape([p,p,d,this.boxEncodingSize]),x=b.slice([0,0,0,0],[p,p,d,4]),v=b.slice([0,0,0,4],[p,p,d,1]),I=this.withClassScores?Za(b.slice([0,0,0,5],[p,p,d,this.config.classes.length]),3):ke(0);return[x,v,I]}),f=[],g=await h.array(),y=await c.array();for(let b=0;br){let T=(x+kd(y[b][x][v][0]))/p*l,_=(b+kd(y[b][x][v][1]))/p*u,A=Math.exp(y[b][x][v][2])*this.config.anchors[v].x/p*l,F=Math.exp(y[b][x][v][3])*this.config.anchors[v].y/p*u,P=T-A/2,$=_-F/2,S={row:b,col:x,anchor:v},{classScore:M,label:U}=this.withClassScores?await this.extractPredictedClass(m,S):{classScore:1,label:0};f.push({box:new Fo(P,$,P+A,$+F),score:I,classScore:I*M,label:U,...S})}}return c.dispose(),h.dispose(),m.dispose(),f}async extractPredictedClass(n,a){let{row:r,col:s,anchor:i}=a,o=await n.array();return Array(this.config.classes.length).fill(0).map((l,u)=>o[r][s][i][u]).map((l,u)=>({classScore:l,label:u})).reduce((l,u)=>l.classScore>u.classScore?l:u)}},Go=J1;Go.DEFAULT_FILTER_SIZES=[3,16,32,64,128,256,512,1024,1024];var Ho=class extends Go{constructor(t=!0){let n={withSeparableConvs:t,iouThreshold:d$,classes:["face"],...t?{anchors:m$,meanRgb:f$}:{anchors:h$,withClassScores:!0}};super(n)}get withSeparableConvs(){return this.config.withSeparableConvs}get anchors(){return 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Pe(9.041765,10.66308)],k$=[117.001,114.697,97.404];var qo=class extends Go{constructor(){let t={withSeparableConvs:!0,iouThreshold:v$,classes:["face"],anchors:w$,meanRgb:k$,isFirstLayerConv2d:!0,filterSizes:[3,16,32,64,128,256,512]};super(t)}get anchors(){return this.config.anchors}async locateFaces(t,n){return(await this.detect(t,n)).map(r=>new xt(r.score,r.relativeBox,{width:r.imageWidth,height:r.imageHeight}))}getDefaultModelName(){return"tiny_face_detector_model"}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};var tt={ssdMobilenetv1:new Fs,tinyFaceDetector:new qo,tinyYolov2:new Ho,faceLandmark68Net:new Wo,faceLandmark68TinyNet:new Fd,faceRecognitionNet:new Vo,faceExpressionNet:new Ad,ageGenderNet:new $d},I$=(e,t)=>tt.ssdMobilenetv1.locateFaces(e,t),ece=(e,t)=>tt.tinyFaceDetector.locateFaces(e,t),tce=(e,t)=>tt.tinyYolov2.locateFaces(e,t),S$=e=>tt.faceLandmark68Net.detectLandmarks(e),nce=e=>tt.faceLandmark68TinyNet.detectLandmarks(e),ace=e=>tt.faceRecognitionNet.computeFaceDescriptor(e),rce=e=>tt.faceExpressionNet.predictExpressions(e),sce=e=>tt.ageGenderNet.predictAgeAndGender(e),N$=e=>tt.ssdMobilenetv1.load(e),ice=e=>tt.tinyFaceDetector.load(e),oce=e=>tt.tinyYolov2.load(e),lce=e=>tt.faceLandmark68Net.load(e),uce=e=>tt.faceLandmark68TinyNet.load(e),pce=e=>tt.faceRecognitionNet.load(e),cce=e=>tt.faceExpressionNet.load(e),dce=e=>tt.ageGenderNet.load(e),hce=N$,mce=I$,fce=S$;var Wg=class extends wa{constructor(n,a,r){super();this.parentTask=n;this.input=a;this.extractedFaces=r}},Ko=class extends Wg{async run(){let t=await this.parentTask,n=await jo(t,this.input,async a=>Promise.all(a.map(r=>tt.faceExpressionNet.predictExpressions(r))),this.extractedFaces);return 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extends Vg{async run(){let t=await this.parentTask;if(!t)return;let{age:n,gender:a,genderProbability:r}=await Tp(t,this.input,s=>tt.ageGenderNet.predictAgeAndGender(s),this.extractedFaces);return Lg(zg(t,a,r),n)}withFaceExpressions(){return new Xo(this,this.input)}},Ms=class extends Yo{withFaceExpressions(){return new Ds(this,this.input)}withFaceDescriptors(){return new Gr(this,this.input)}},Ps=class extends Jo{withFaceExpressions(){return new Rs(this,this.input)}withFaceDescriptor(){return new Hr(this,this.input)}};var Md=class extends wa{constructor(n,a){super();this.parentTask=n;this.input=a}},Gr=class extends Md{async run(){let t=await this.parentTask;return(await jo(t,this.input,a=>Promise.all(a.map(r=>tt.faceRecognitionNet.computeFaceDescriptor(r))),null,a=>a.landmarks.align(null,{useDlibAlignment:!0}))).map((a,r)=>Og(t[r],a))}withFaceExpressions(){return new Ds(this,this.input)}withAgeAndGender(){return new Ms(this,this.input)}},Hr=class extends Md{async run(){let t=await this.parentTask;if(!t)return;let n=await Tp(t,this.input,a=>tt.faceRecognitionNet.computeFaceDescriptor(a),null,a=>a.landmarks.align(null,{useDlibAlignment:!0}));return Og(t,n)}withFaceExpressions(){return new Rs(this,this.input)}withAgeAndGender(){return new Ps(this,this.input)}};var Pd=class extends wa{constructor(n,a,r){super();this.parentTask=n;this.input=a;this.useTinyLandmarkNet=r}get landmarkNet(){return this.useTinyLandmarkNet?tt.faceLandmark68TinyNet:tt.faceLandmark68Net}},Od=class extends Pd{async run(){let t=await this.parentTask,n=t.map(i=>i.detection),a=this.input instanceof Ae?await yp(this.input,n):await gp(this.input,n),r=await Promise.all(a.map(i=>this.landmarkNet.detectLandmarks(i)));return a.forEach(i=>i instanceof Ae&&i.dispose()),t.filter((i,o)=>r[o]).map((i,o)=>Ip(i,r[o]))}withFaceExpressions(){return new Ds(this,this.input)}withAgeAndGender(){return new Ms(this,this.input)}withFaceDescriptors(){return new Gr(this,this.input)}},Ld=class extends Pd{async run(){let 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Promise((t,n)=>{this.run().then(a=>t(a.map(r=>Mo({},r)))).catch(a=>n(a))})}withFaceLandmarks(t=!1){return new Od(this.runAndExtendWithFaceDetections(),this.input,t)}withFaceExpressions(){return new Ko(this.runAndExtendWithFaceDetections(),this.input)}withAgeAndGender(){return new Yo(this.runAndExtendWithFaceDetections(),this.input)}},Bd=class extends zd{async run(){let t=await new Cp(this.input,this.options),n=t[0];return t.forEach(a=>{a.score>n.score&&(n=a)}),n}runAndExtendWithFaceDetection(){return new Promise(async t=>{let n=await this.run();t(n?Mo({},n):void 0)})}withFaceLandmarks(t=!1){return new Ld(this.runAndExtendWithFaceDetection(),this.input,t)}withFaceExpressions(){return new Xo(this.runAndExtendWithFaceDetection(),this.input)}withAgeAndGender(){return new Jo(this.runAndExtendWithFaceDetection(),this.input)}};function gce(e,t=new va){return new Bd(e,t)}function Ug(e,t=new va){return new Cp(e,t)}async function T$(e,t){return Ug(e,new 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wr=class{constructor(t,n=!1){this._imageTensors=[];this._canvases=[];this._treatAsBatchInput=!1;this._inputDimensions=[];this._inputSize=0;if(!Array.isArray(t))throw new Error(`NetInput.constructor - expected inputs to be an Array of TResolvedNetInput or to be instanceof tf.Tensor4D, instead have ${t}`);this._treatAsBatchInput=n,this._batchSize=t.length,t.forEach((a,r)=>{if(Or(a)){this._imageTensors[r]=a,this._inputDimensions[r]=a.shape;return}if(xa(a)){let i=a.shape[0];if(i!==1)throw new Error(`NetInput - tf.Tensor4D with batchSize ${i} passed, but not supported in input array`);this._imageTensors[r]=a,this._inputDimensions[r]=a.shape.slice(1);return}let s=a instanceof et.getEnv().Canvas?a:Td(a);this._canvases[r]=s,this._inputDimensions[r]=[s.height,s.width,3]})}get imageTensors(){return this._imageTensors}get canvases(){return this._canvases}get isBatchInput(){return this.batchSize>1||this._treatAsBatchInput}get batchSize(){return this._batchSize}get inputDimensions(){return 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on{constructor(n,a){super(n);this._faceFeatureExtractor=a}get faceFeatureExtractor(){return this._faceFeatureExtractor}runNet(n){let{params:a}=this;if(!a)throw new Error(`${this._name} - load model before inference`);return O(()=>{let r=n instanceof wr?this.faceFeatureExtractor.forwardInput(n):n;return Ed(r.as2D(r.shape[0],-1),a.fc)})}dispose(n=!0){this.faceFeatureExtractor.dispose(n),super.dispose(n)}loadClassifierParams(n){let{params:a,paramMappings:r}=this.extractClassifierParams(n);this._params=a,this._paramMappings=r}extractClassifierParams(n){return HA(n,this.getClassifierChannelsIn(),this.getClassifierChannelsOut())}extractParamsFromWeightMap(n){let{featureExtractorMap:a,classifierMap:r}=Eg(n);return this.faceFeatureExtractor.loadFromWeightMap(a),jA(r)}extractParams(n){let a=this.getClassifierChannelsIn(),r=this.getClassifierChannelsOut(),s=r*a+r,i=n.slice(0,n.length-s),o=n.slice(n.length-s);return this.faceFeatureExtractor.extractWeights(i),this.extractClassifierParams(o)}};var 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c=s("exit_flow/reduction_block"),h=r("exit_flow/separable_conv"),m={reduction_block:c,separable_conv:h};return Fn(e,n),{params:{entry_flow:p,middle_flow:d,exit_flow:m},paramMappings:n}}function YA(e,t,n){return Z(Dt(e,t.filters,n,"same"),t.bias)}function H1(e,t,n=!0){let a=n?Xe(e):e;return a=Xn(a,t.separable_conv0,[1,1]),a=Xn(Xe(a),t.separable_conv1,[1,1]),a=Mt(a,[3,3],[2,2],"same"),a=Z(a,YA(e,t.expansion_conv,[2,2])),a}function Ppe(e,t){let n=Xn(Xe(e),t.separable_conv0,[1,1]);return n=Xn(Xe(n),t.separable_conv1,[1,1]),n=Xn(Xe(n),t.separable_conv2,[1,1]),n=Z(n,e),n}var Dg=class extends on{constructor(n){super("TinyXception");this._numMainBlocks=n}forwardInput(n){let{params:a}=this;if(!a)throw new Error("TinyXception - load model before inference");return O(()=>{let r=le(n.toBatchTensor(112,!0),"float32"),i=tr(r,[122.782,117.001,104.298]).div(255),o=Xe(YA(i,a.entry_flow.conv_in,[2,2]));return o=H1(o,a.entry_flow.reduction_block_0,!1),o=H1(o,a.entry_flow.reduction_block_1),br(this._numMainBlocks,0,1).forEach(l=>{o=Ppe(o,a.middle_flow[`main_block_${l}`])}),o=H1(o,a.exit_flow.reduction_block),o=Xe(Xn(o,a.exit_flow.separable_conv,[1,1])),o})}async forward(n){return this.forwardInput(await vt(n))}getDefaultModelName(){return"tiny_xception_model"}extractParamsFromWeightMap(n){return XA(n,this._numMainBlocks)}extractParams(n){return KA(n,this._numMainBlocks)}};function JA(e){let t=[],{extractWeights:n,getRemainingWeights:a}=Dn(e),r=Ng(n,t),s=r(512,1,"fc/age"),i=r(512,2,"fc/gender");if(a().length!==0)throw new Error(`weights remaing after extract: ${a().length}`);return{paramMappings:t,params:{fc:{age:s,gender:i}}}}function ZA(e){let t=[],n=sa(e,t);function a(s){let i=n(`${s}/weights`,2),o=n(`${s}/bias`,1);return{weights:i,bias:o}}let r={fc:{age:a("fc/age"),gender:a("fc/gender")}};return Fn(e,t),{params:r,paramMappings:t}}var Rg=(n=>(n.FEMALE="female",n.MALE="male",n))(Rg||{});var $d=class extends on{constructor(n=new Dg(2)){super("AgeGenderNet");this._faceFeatureExtractor=n}get faceFeatureExtractor(){return this._faceFeatureExtractor}runNet(n){let{params:a}=this;if(!a)throw new Error(`${this._name} - load model before inference`);return O(()=>{let r=n instanceof wr?this.faceFeatureExtractor.forwardInput(n):n,s=ga(r,[7,7],[2,2],"valid").as2D(r.shape[0],-1),i=Ed(s,a.fc.age).as1D(),o=Ed(s,a.fc.gender);return{age:i,gender:o}})}forwardInput(n){return O(()=>{let{age:a,gender:r}=this.runNet(n);return{age:a,gender:Za(r)}})}async forward(n){return this.forwardInput(await vt(n))}async predictAgeAndGender(n){let a=await vt(n),r=await this.forwardInput(a),s=mt(r.age),i=mt(r.gender),o=s.map((u,p)=>({ageTensor:u,genderTensor:i[p]})),l=await Promise.all(o.map(async({ageTensor:u,genderTensor:p})=>{let d=u.dataSync()[0],c=p.dataSync()[0],h=c>.5,m=h?"male":"female",f=h?c:1-c;return u.dispose(),p.dispose(),{age:d,gender:m,genderProbability:f}}));return r.age.dispose(),r.gender.dispose(),a.isBatchInput?l:l[0]}getDefaultModelName(){return"age_gender_model"}dispose(n=!0){this.faceFeatureExtractor.dispose(n),super.dispose(n)}loadClassifierParams(n){let{params:a,paramMappings:r}=this.extractClassifierParams(n);this._params=a,this._paramMappings=r}extractClassifierParams(n){return JA(n)}extractParamsFromWeightMap(n){let{featureExtractorMap:a,classifierMap:r}=Eg(n);return this.faceFeatureExtractor.loadFromWeightMap(a),ZA(r)}extractParams(n){let r=n.slice(0,n.length-1539),s=n.slice(n.length-1539);return this.faceFeatureExtractor.extractWeights(r),this.extractClassifierParams(s)}};var Sp=class extends kp{postProcess(t,n,a){let r=a.map(({width:i,height:o})=>{let l=n/Math.max(o,i);return{width:i*l,height:o*l}}),s=r.length;return O(()=>{let i=(d,c)=>Rt([An([68],d,"float32"),An([68],c,"float32")],1).as2D(1,136).as1D(),o=(d,c)=>{let{width:h,height:m}=r[d];return 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n=[],{extractConvParams:a,extractConvWithBatchNormParams:r,extractSeparableConvParams:s}=Zpe(e,n),i;if(t.withSeparableConvs){let o=t.filterSizes&&t.filterSizes.length||9;i={conv0:t.isFirstLayerConv2d?a("conv0"):s("conv0"),conv1:s("conv1"),conv2:s("conv2"),conv3:s("conv3"),conv4:s("conv4"),conv5:s("conv5"),conv6:o>7?s("conv6"):void 0,conv7:o>8?s("conv7"):void 0,conv8:a("conv8")}}else i={conv0:r("conv0"),conv1:r("conv1"),conv2:r("conv2"),conv3:r("conv3"),conv4:r("conv4"),conv5:r("conv5"),conv6:r("conv6"),conv7:r("conv7"),conv8:a("conv8")};return Fn(e,n),{params:i,paramMappings:n}}var ar=class{constructor({inputSize:t,scoreThreshold:n}={}){this._name="TinyYolov2Options";if(this._inputSize=t||416,this._scoreThreshold=n||.5,typeof this._inputSize!="number"||this._inputSize%32!==0)throw new Error(`${this._name} - expected inputSize to be a number divisible by 32`);if(typeof this._scoreThreshold!="number"||this._scoreThreshold<=0||this._scoreThreshold>=1)throw new Error(`${this._name} - 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r=Mt(r,[2,2],[2,2],"same"),r=Ur(r,a.conv1),r=Mt(r,[2,2],[2,2],"same"),r=Ur(r,a.conv2),r=Mt(r,[2,2],[2,2],"same"),r=Ur(r,a.conv3),r=Mt(r,[2,2],[2,2],"same"),r=Ur(r,a.conv4),r=Mt(r,[2,2],[2,2],"same"),r=Ur(r,a.conv5),r=Mt(r,[2,2],[1,1],"same"),r=a.conv6?Ur(r,a.conv6):r,r=a.conv7?Ur(r,a.conv7):r,zo(r,a.conv8,"valid",!1)}forwardInput(n,a){let{params:r}=this;if(!r)throw new Error("TinyYolov2 - load model before inference");return O(()=>{let s=le(n.toBatchTensor(a,!1),"float32");return s=this.config.meanRgb?tr(s,this.config.meanRgb):s,s=s.div(255),this.config.withSeparableConvs?this.runMobilenet(s,r):this.runTinyYolov2(s,r)})}async forward(n,a){return this.forwardInput(await vt(n),a)}async detect(n,a={}){let{inputSize:r,scoreThreshold:s}=new ar(a),i=await vt(n),o=await this.forwardInput(i,r),l=O(()=>mt(o)[0].expandDims()),u={width:i.getInputWidth(0),height:i.getInputHeight(0)},p=await this.extractBoxes(l,i.getReshapedInputDimensions(0),s);o.dispose(),l.dispose();let d=p.map(y=>y.box),c=p.map(y=>y.score),h=p.map(y=>y.classScore),m=p.map(y=>this.config.classes[y.label]);return T1(d.map(y=>y.rescale(r)),c,this.config.iouThreshold,!0).map(y=>new Lr(c[y],h[y],m[y],d[y],u))}getDefaultModelName(){return""}extractParamsFromWeightMap(n){return x$(n,this.config)}extractParams(n){let a=this.config.filterSizes||J1.DEFAULT_FILTER_SIZES,r=a?a.length:void 0;if(r!==7&&r!==8&&r!==9)throw new Error(`TinyYolov2 - expected 7 | 8 | 9 convolutional filters, but found ${r} filterSizes in config`);return b$(n,this.config,this.boxEncodingSize,a)}async extractBoxes(n,a,r){let{width:s,height:i}=a,o=Math.max(s,i),l=o/s,u=o/i,p=n.shape[1],d=this.config.anchors.length,[c,h,m]=O(()=>{let b=n.reshape([p,p,d,this.boxEncodingSize]),x=b.slice([0,0,0,0],[p,p,d,4]),v=b.slice([0,0,0,4],[p,p,d,1]),I=this.withClassScores?Za(b.slice([0,0,0,5],[p,p,d,this.config.classes.length]),3):ke(0);return[x,v,I]}),f=[],g=await h.array(),y=await c.array();for(let b=0;br){let T=(x+kd(y[b][x][v][0]))/p*l,_=(b+kd(y[b][x][v][1]))/p*u,A=Math.exp(y[b][x][v][2])*this.config.anchors[v].x/p*l,F=Math.exp(y[b][x][v][3])*this.config.anchors[v].y/p*u,P=T-A/2,$=_-F/2,S={row:b,col:x,anchor:v},{classScore:M,label:U}=this.withClassScores?await this.extractPredictedClass(m,S):{classScore:1,label:0};f.push({box:new Fo(P,$,P+A,$+F),score:I,classScore:I*M,label:U,...S})}}return c.dispose(),h.dispose(),m.dispose(),f}async extractPredictedClass(n,a){let{row:r,col:s,anchor:i}=a,o=await n.array();return Array(this.config.classes.length).fill(0).map((l,u)=>o[r][s][i][u]).map((l,u)=>({classScore:l,label:u})).reduce((l,u)=>l.classScore>u.classScore?l:u)}},Go=J1;Go.DEFAULT_FILTER_SIZES=[3,16,32,64,128,256,512,1024,1024];var Ho=class extends Go{constructor(t=!0){let n={withSeparableConvs:t,iouThreshold:d$,classes:["face"],...t?{anchors:m$,meanRgb:f$}:{anchors:h$,withClassScores:!0}};super(n)}get withSeparableConvs(){return this.config.withSeparableConvs}get anchors(){return this.config.anchors}async locateFaces(t,n){return(await this.detect(t,n)).map(r=>new xt(r.score,r.relativeBox,{width:r.imageWidth,height:r.imageHeight}))}getDefaultModelName(){return this.withSeparableConvs?y$:g$}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};function Qpe(e,t=!0){let n=new Ho(t);return n.extractWeights(e),n}var Rd=class extends ar{constructor(){super(...arguments);this._name="TinyFaceDetectorOptions"}};var wa=class{async then(t){return t(await this.run())}async run(){throw new Error("ComposableTask - run is not implemented")}};async function jo(e,t,n,a,r=({alignedRect:s})=>s){let s=e.map(l=>Bo(l)?r(l):l.detection),i=a||(t instanceof Ae?await yp(t,s):await gp(t,s)),o=await n(i);return i.forEach(l=>l instanceof Ae&&l.dispose()),o}async function Tp(e,t,n,a,r){return jo([e],t,async s=>n(s[0]),a,r)}var v$=.4,w$=[new Pe(1.603231,2.094468),new Pe(6.041143,7.080126),new Pe(2.882459,3.518061),new Pe(4.266906,5.178857),new Pe(9.041765,10.66308)],k$=[117.001,114.697,97.404];var qo=class extends Go{constructor(){let t={withSeparableConvs:!0,iouThreshold:v$,classes:["face"],anchors:w$,meanRgb:k$,isFirstLayerConv2d:!0,filterSizes:[3,16,32,64,128,256,512]};super(t)}get anchors(){return this.config.anchors}async locateFaces(t,n){return(await this.detect(t,n)).map(r=>new xt(r.score,r.relativeBox,{width:r.imageWidth,height:r.imageHeight}))}getDefaultModelName(){return"tiny_face_detector_model"}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};var tt={ssdMobilenetv1:new Fs,tinyFaceDetector:new qo,tinyYolov2:new Ho,faceLandmark68Net:new Wo,faceLandmark68TinyNet:new Fd,faceRecognitionNet:new Vo,faceExpressionNet:new Ad,ageGenderNet:new $d},I$=(e,t)=>tt.ssdMobilenetv1.locateFaces(e,t),ece=(e,t)=>tt.tinyFaceDetector.locateFaces(e,t),tce=(e,t)=>tt.tinyYolov2.locateFaces(e,t),S$=e=>tt.faceLandmark68Net.detectLandmarks(e),nce=e=>tt.faceLandmark68TinyNet.detectLandmarks(e),ace=e=>tt.faceRecognitionNet.computeFaceDescriptor(e),rce=e=>tt.faceExpressionNet.predictExpressions(e),sce=e=>tt.ageGenderNet.predictAgeAndGender(e),N$=e=>tt.ssdMobilenetv1.load(e),ice=e=>tt.tinyFaceDetector.load(e),oce=e=>tt.tinyYolov2.load(e),lce=e=>tt.faceLandmark68Net.load(e),uce=e=>tt.faceLandmark68TinyNet.load(e),pce=e=>tt.faceRecognitionNet.load(e),cce=e=>tt.faceExpressionNet.load(e),dce=e=>tt.ageGenderNet.load(e),hce=N$,mce=I$,fce=S$;var Wg=class extends wa{constructor(n,a,r){super();this.parentTask=n;this.input=a;this.extractedFaces=r}},Ko=class extends Wg{async run(){let t=await this.parentTask,n=await jo(t,this.input,async a=>Promise.all(a.map(r=>tt.faceExpressionNet.predictExpressions(r))),this.extractedFaces);return t.map((a,r)=>Ag(a,n[r]))}withAgeAndGender(){return new Yo(this,this.input)}},Xo=class extends Wg{async run(){let t=await this.parentTask;if(!t)return;let n=await Tp(t,this.input,a=>tt.faceExpressionNet.predictExpressions(a),this.extractedFaces);return Ag(t,n)}withAgeAndGender(){return new Jo(this,this.input)}},Ds=class extends Ko{withAgeAndGender(){return new Ms(this,this.input)}withFaceDescriptors(){return new Gr(this,this.input)}},Rs=class extends Xo{withAgeAndGender(){return new Ps(this,this.input)}withFaceDescriptor(){return new Hr(this,this.input)}};var Vg=class extends wa{constructor(n,a,r){super();this.parentTask=n;this.input=a;this.extractedFaces=r}},Yo=class extends Vg{async run(){let t=await this.parentTask,n=await jo(t,this.input,async a=>Promise.all(a.map(r=>tt.ageGenderNet.predictAgeAndGender(r))),this.extractedFaces);return t.map((a,r)=>{let{age:s,gender:i,genderProbability:o}=n[r];return Lg(zg(a,i,o),s)})}withFaceExpressions(){return new Ko(this,this.input)}},Jo=class extends Vg{async run(){let t=await this.parentTask;if(!t)return;let{age:n,gender:a,genderProbability:r}=await Tp(t,this.input,s=>tt.ageGenderNet.predictAgeAndGender(s),this.extractedFaces);return Lg(zg(t,a,r),n)}withFaceExpressions(){return new Xo(this,this.input)}},Ms=class extends Yo{withFaceExpressions(){return new Ds(this,this.input)}withFaceDescriptors(){return new Gr(this,this.input)}},Ps=class extends Jo{withFaceExpressions(){return new Rs(this,this.input)}withFaceDescriptor(){return new Hr(this,this.input)}};var Md=class extends wa{constructor(n,a){super();this.parentTask=n;this.input=a}},Gr=class extends Md{async run(){let t=await this.parentTask;return(await jo(t,this.input,a=>Promise.all(a.map(r=>tt.faceRecognitionNet.computeFaceDescriptor(r))),null,a=>a.landmarks.align(null,{useDlibAlignment:!0}))).map((a,r)=>Og(t[r],a))}withFaceExpressions(){return new Ds(this,this.input)}withAgeAndGender(){return new Ms(this,this.input)}},Hr=class extends Md{async run(){let t=await this.parentTask;if(!t)return;let n=await Tp(t,this.input,a=>tt.faceRecognitionNet.computeFaceDescriptor(a),null,a=>a.landmarks.align(null,{useDlibAlignment:!0}));return Og(t,n)}withFaceExpressions(){return new Rs(this,this.input)}withAgeAndGender(){return new Ps(this,this.input)}};var Pd=class extends wa{constructor(n,a,r){super();this.parentTask=n;this.input=a;this.useTinyLandmarkNet=r}get landmarkNet(){return this.useTinyLandmarkNet?tt.faceLandmark68TinyNet:tt.faceLandmark68Net}},Od=class extends Pd{async run(){let t=await this.parentTask,n=t.map(i=>i.detection),a=this.input instanceof Ae?await yp(this.input,n):await gp(this.input,n),r=await Promise.all(a.map(i=>this.landmarkNet.detectLandmarks(i)));return a.forEach(i=>i instanceof Ae&&i.dispose()),t.filter((i,o)=>r[o]).map((i,o)=>Ip(i,r[o]))}withFaceExpressions(){return new Ds(this,this.input)}withAgeAndGender(){return new Ms(this,this.input)}withFaceDescriptors(){return new Gr(this,this.input)}},Ld=class extends Pd{async run(){let t=await this.parentTask;if(!t)return;let{detection:n}=t,a=this.input instanceof Ae?await yp(this.input,[n]):await gp(this.input,[n]),r=await this.landmarkNet.detectLandmarks(a[0]);return a.forEach(s=>s instanceof Ae&&s.dispose()),Ip(t,r)}withFaceExpressions(){return new Rs(this,this.input)}withAgeAndGender(){return new Ps(this,this.input)}withFaceDescriptor(){return new Hr(this,this.input)}};var zd=class extends wa{constructor(n,a=new va){super();this.input=n;this.options=a}},Cp=class extends zd{async run(){let{input:t,options:n}=this,a;if(n instanceof Rd)a=tt.tinyFaceDetector.locateFaces(t,n);else if(n instanceof va)a=tt.ssdMobilenetv1.locateFaces(t,n);else if(n instanceof ar)a=tt.tinyYolov2.locateFaces(t,n);else throw new Error("detectFaces - expected options to be instance of TinyFaceDetectorOptions | SsdMobilenetv1Options | TinyYolov2Options");return a}runAndExtendWithFaceDetections(){return new Promise((t,n)=>{this.run().then(a=>t(a.map(r=>Mo({},r)))).catch(a=>n(a))})}withFaceLandmarks(t=!1){return new Od(this.runAndExtendWithFaceDetections(),this.input,t)}withFaceExpressions(){return new Ko(this.runAndExtendWithFaceDetections(),this.input)}withAgeAndGender(){return new Yo(this.runAndExtendWithFaceDetections(),this.input)}},Bd=class extends zd{async run(){let t=await new Cp(this.input,this.options),n=t[0];return t.forEach(a=>{a.score>n.score&&(n=a)}),n}runAndExtendWithFaceDetection(){return new Promise(async t=>{let n=await this.run();t(n?Mo({},n):void 0)})}withFaceLandmarks(t=!1){return new Ld(this.runAndExtendWithFaceDetection(),this.input,t)}withFaceExpressions(){return new Xo(this.runAndExtendWithFaceDetection(),this.input)}withAgeAndGender(){return new Jo(this.runAndExtendWithFaceDetection(),this.input)}};function gce(e,t=new va){return new Bd(e,t)}function Ug(e,t=new va){return new Cp(e,t)}async function T$(e,t){return Ug(e,new 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C(e))}getDefaultModelName(){return"tiny_xception_model"}extractParamsFromWeightMap(e){return Lo(e,this._numMainBlocks)}extractParams(e){return So(e,this._numMainBlocks)}};function Wo(o){let t=[],{extractWeights:e,getRemainingWeights:r}=R(o),n=lr(e,t),a=n(512,1,"fc/age"),s=n(512,2,"fc/gender");if(r().length!==0)throw new Error(`weights remaing after extract: ${r().length}`);return{paramMappings:t,params:{fc:{age:a,gender:s}}}}function ko(o){let t=[],e=Y(o,t);function r(a){let s=e(`${a}/weights`,2),i=e(`${a}/bias`,1);return{weights:s,bias:i}}let n={fc:{age:r("fc/age"),gender:r("fc/gender")}};return B(o,t),{params:n,paramMappings:t}}var Tr=(e=>(e.FEMALE="female",e.MALE="male",e))(Tr||{});var He=class extends A{constructor(e=new _r(2)){super("AgeGenderNet");this._faceFeatureExtractor=e}get faceFeatureExtractor(){return this._faceFeatureExtractor}runNet(e){let{params:r}=this;if(!r)throw new Error(`${this._name} - load model before inference`);return ft.tidy(()=>{let n=e instanceof ut?this.faceFeatureExtractor.forwardInput(e):e,a=ft.avgPool(n,[7,7],[2,2],"valid").as2D(n.shape[0],-1),s=$e(a,r.fc.age).as1D(),i=$e(a,r.fc.gender);return{age:s,gender:i}})}forwardInput(e){return ft.tidy(()=>{let{age:r,gender:n}=this.runNet(e);return{age:r,gender:ft.softmax(n)}})}async forward(e){return this.forwardInput(await C(e))}async predictAgeAndGender(e){let r=await C(e),n=await this.forwardInput(r),a=ft.unstack(n.age),s=ft.unstack(n.gender),i=a.map((m,p)=>({ageTensor:m,genderTensor:s[p]})),c=await Promise.all(i.map(async({ageTensor:m,genderTensor:p})=>{let u=m.dataSync()[0],f=p.dataSync()[0],l=f>.5,g=l?"male":"female",T=l?f:1-f;return m.dispose(),p.dispose(),{age:u,gender:g,genderProbability:T}}));return n.age.dispose(),n.gender.dispose(),r.isBatchInput?c:c[0]}getDefaultModelName(){return"age_gender_model"}dispose(e=!0){this.faceFeatureExtractor.dispose(e),super.dispose(e)}loadClassifierParams(e){let{params:r,paramMappings:n}=this.extractClassifierParams(e);this._params=r,this._paramMappings=n}extractClassifierParams(e){return Wo(e)}extractParamsFromWeightMap(e){let{featureExtractorMap:r,classifierMap:n}=gr(e);return this.faceFeatureExtractor.loadFromWeightMap(r),ko(n)}extractParams(e){let n=e.slice(0,e.length-1539),a=e.slice(e.length-1539);return this.faceFeatureExtractor.extractWeights(n),this.extractClassifierParams(a)}};var G=v(x());var Fe=class extends Te{postProcess(t,e,r){let n=r.map(({width:s,height:i})=>{let c=e/Math.max(i,s);return{width:s*c,height:i*c}}),a=n.length;return G.tidy(()=>{let s=(u,f)=>G.stack([G.fill([68],u,"float32"),G.fill([68],f,"float32")],1).as2D(1,136).as1D(),i=(u,f)=>{let{width:l,height:g}=n[u];return 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st=class{constructor({inputSize:t,scoreThreshold:e}={}){this._name="TinyYolov2Options";if(this._inputSize=t||416,this._scoreThreshold=e||.5,typeof this._inputSize!="number"||this._inputSize%32!==0)throw new Error(`${this._name} - expected inputSize to be a number divisible by 32`);if(typeof this._scoreThreshold!="number"||this._scoreThreshold<=0||this._scoreThreshold>=1)throw new Error(`${this._name} - expected scoreThreshold to be a number between 0 and 1`)}get inputSize(){return this._inputSize}get scoreThreshold(){return this._scoreThreshold}};var ho=class extends A{constructor(e){super("TinyYolov2");fo(e),this._config=e}get config(){return this._config}get withClassScores(){return this.config.withClassScores||this.config.classes.length>1}get boxEncodingSize(){return 5+(this.withClassScores?this.config.classes.length:0)}runTinyYolov2(e,r){let n=Tt(e,r.conv0);return 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extractPredictedClass(e,r){let{row:n,col:a,anchor:s}=r,i=await e.array();return Array(this.config.classes.length).fill(0).map((c,m)=>i[n][a][s][m]).map((c,m)=>({classScore:c,label:m})).reduce((c,m)=>c.classScore>m.classScore?c:m)}},ee=ho;ee.DEFAULT_FILTER_SIZES=[3,16,32,64,128,256,512,1024,1024];var re=class extends ee{constructor(t=!0){let e={withSeparableConvs:t,iouThreshold:qo,classes:["face"],...t?{anchors:Ko,meanRgb:Qo}:{anchors:Zo,withClassScores:!0}};super(e)}get withSeparableConvs(){return this.config.withSeparableConvs}get anchors(){return this.config.anchors}async locateFaces(t,e){return(await this.detect(t,e)).map(n=>new M(n.score,n.relativeBox,{width:n.imageWidth,height:n.imageHeight}))}getDefaultModelName(){return this.withSeparableConvs?en:tn}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};function ca(o,t=!0){let e=new re(t);return e.extractWeights(o),e}var je=class extends st{constructor(){super(...arguments);this._name="TinyFaceDetectorOptions"}};var J=class{async then(t){return t(await this.run())}async run(){throw new Error("ComposableTask - run is not implemented")}};var Xe=v(x());var bo=v(x());async function oe(o,t,e,r,n=({alignedRect:a})=>a){let a=o.map(c=>Zt(c)?n(c):c.detection),s=r||(t instanceof bo.Tensor?await de(t,a):await le(t,a)),i=await e(s);return s.forEach(c=>c instanceof bo.Tensor&&c.dispose()),i}async function Ce(o,t,e,r,n){return oe([o],t,async a=>e(a[0]),r,n)}var nn=.4,an=[new b(1.603231,2.094468),new b(6.041143,7.080126),new b(2.882459,3.518061),new b(4.266906,5.178857),new b(9.041765,10.66308)],sn=[117.001,114.697,97.404];var ne=class extends ee{constructor(){let t={withSeparableConvs:!0,iouThreshold:nn,classes:["face"],anchors:an,meanRgb:sn,isFirstLayerConv2d:!0,filterSizes:[3,16,32,64,128,256,512]};super(t)}get anchors(){return this.config.anchors}async locateFaces(t,e){return(await this.detect(t,e)).map(n=>new M(n.score,n.relativeBox,{width:n.imageWidth,height:n.imageHeight}))}getDefaultModelName(){return"tiny_face_detector_model"}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};var w={ssdMobilenetv1:new St,tinyFaceDetector:new ne,tinyYolov2:new re,faceLandmark68Net:new Kt,faceLandmark68TinyNet:new ze,faceRecognitionNet:new Qt,faceExpressionNet:new Oe,ageGenderNet:new He},cn=(o,t)=>w.ssdMobilenetv1.locateFaces(o,t),ma=(o,t)=>w.tinyFaceDetector.locateFaces(o,t),pa=(o,t)=>w.tinyYolov2.locateFaces(o,t),mn=o=>w.faceLandmark68Net.detectLandmarks(o),ua=o=>w.faceLandmark68TinyNet.detectLandmarks(o),fa=o=>w.faceRecognitionNet.computeFaceDescriptor(o),la=o=>w.faceExpressionNet.predictExpressions(o),da=o=>w.ageGenderNet.predictAgeAndGender(o),pn=o=>w.ssdMobilenetv1.load(o),ha=o=>w.tinyFaceDetector.load(o),ba=o=>w.tinyYolov2.load(o),ga=o=>w.faceLandmark68Net.load(o),xa=o=>w.faceLandmark68TinyNet.load(o),va=o=>w.faceRecognitionNet.load(o),ya=o=>w.faceExpressionNet.load(o),_a=o=>w.ageGenderNet.load(o),Ta=pn,Pa=cn,wa=mn;var Ir=class extends J{constructor(e,r,n){super();this.parentTask=e;this.input=r;this.extractedFaces=n}},ae=class extends Ir{async run(){let t=await this.parentTask,e=await oe(t,this.input,async r=>Promise.all(r.map(n=>w.faceExpressionNet.predictExpressions(n))),this.extractedFaces);return t.map((r,n)=>xr(r,e[n]))}withAgeAndGender(){return new ie(this,this.input)}},se=class extends Ir{async run(){let t=await this.parentTask;if(!t)return;let e=await Ce(t,this.input,r=>w.faceExpressionNet.predictExpressions(r),this.extractedFaces);return xr(t,e)}withAgeAndGender(){return new ce(this,this.input)}},Wt=class extends ae{withAgeAndGender(){return new Bt(this,this.input)}withFaceDescriptors(){return new wt(this,this.input)}},kt=class extends se{withAgeAndGender(){return new Rt(this,this.input)}withFaceDescriptor(){return new Ft(this,this.input)}};var Nr=class extends J{constructor(e,r,n){super();this.parentTask=e;this.input=r;this.extractedFaces=n}},ie=class extends Nr{async run(){let t=await this.parentTask,e=await oe(t,this.input,async r=>Promise.all(r.map(n=>w.ageGenderNet.predictAgeAndGender(n))),this.extractedFaces);return t.map((r,n)=>{let{age:a,gender:s,genderProbability:i}=e[n];return Er(Mr(r,s,i),a)})}withFaceExpressions(){return new ae(this,this.input)}},ce=class extends Nr{async run(){let t=await this.parentTask;if(!t)return;let{age:e,gender:r,genderProbability:n}=await Ce(t,this.input,a=>w.ageGenderNet.predictAgeAndGender(a),this.extractedFaces);return Er(Mr(t,r,n),e)}withFaceExpressions(){return new se(this,this.input)}},Bt=class extends ie{withFaceExpressions(){return new Wt(this,this.input)}withFaceDescriptors(){return new wt(this,this.input)}},Rt=class extends ce{withFaceExpressions(){return new kt(this,this.input)}withFaceDescriptor(){return new Ft(this,this.input)}};var Ue=class extends J{constructor(e,r){super();this.parentTask=e;this.input=r}},wt=class extends Ue{async run(){let t=await this.parentTask;return(await oe(t,this.input,r=>Promise.all(r.map(n=>w.faceRecognitionNet.computeFaceDescriptor(n))),null,r=>r.landmarks.align(null,{useDlibAlignment:!0}))).map((r,n)=>Dr(t[n],r))}withFaceExpressions(){return new Wt(this,this.input)}withAgeAndGender(){return new Bt(this,this.input)}},Ft=class extends Ue{async run(){let t=await this.parentTask;if(!t)return;let e=await Ce(t,this.input,r=>w.faceRecognitionNet.computeFaceDescriptor(r),null,r=>r.landmarks.align(null,{useDlibAlignment:!0}));return Dr(t,e)}withFaceExpressions(){return new kt(this,this.input)}withAgeAndGender(){return new Rt(this,this.input)}};var Je=class extends J{constructor(e,r,n){super();this.parentTask=e;this.input=r;this.useTinyLandmarkNet=n}get landmarkNet(){return this.useTinyLandmarkNet?w.faceLandmark68TinyNet:w.faceLandmark68Net}},qe=class extends Je{async run(){let t=await this.parentTask,e=t.map(s=>s.detection),r=this.input instanceof Xe.Tensor?await de(this.input,e):await le(this.input,e),n=await Promise.all(r.map(s=>this.landmarkNet.detectLandmarks(s)));return r.forEach(s=>s instanceof Xe.Tensor&&s.dispose()),t.filter((s,i)=>n[i]).map((s,i)=>we(s,n[i]))}withFaceExpressions(){return new Wt(this,this.input)}withAgeAndGender(){return new Bt(this,this.input)}withFaceDescriptors(){return new wt(this,this.input)}},Ze=class extends Je{async run(){let t=await this.parentTask;if(!t)return;let{detection:e}=t,r=this.input instanceof Xe.Tensor?await de(this.input,[e]):await le(this.input,[e]),n=await this.landmarkNet.detectLandmarks(r[0]);return r.forEach(a=>a instanceof Xe.Tensor&&a.dispose()),we(t,n)}withFaceExpressions(){return new kt(this,this.input)}withAgeAndGender(){return new Rt(this,this.input)}withFaceDescriptor(){return new Ft(this,this.input)}};var Ke=class extends J{constructor(e,r=new X){super();this.input=e;this.options=r}},Ie=class extends Ke{async run(){let{input:t,options:e}=this,r;if(e instanceof je)r=w.tinyFaceDetector.locateFaces(t,e);else if(e instanceof X)r=w.ssdMobilenetv1.locateFaces(t,e);else if(e instanceof st)r=w.tinyYolov2.locateFaces(t,e);else throw new Error("detectFaces - expected options to be instance of TinyFaceDetectorOptions | SsdMobilenetv1Options | TinyYolov2Options");return r}runAndExtendWithFaceDetections(){return new Promise((t,e)=>{this.run().then(r=>t(r.map(n=>jt({},n)))).catch(r=>e(r))})}withFaceLandmarks(t=!1){return new qe(this.runAndExtendWithFaceDetections(),this.input,t)}withFaceExpressions(){return new ae(this.runAndExtendWithFaceDetections(),this.input)}withAgeAndGender(){return new ie(this.runAndExtendWithFaceDetections(),this.input)}},Qe=class extends Ke{async run(){let t=await new Ie(this.input,this.options),e=t[0];return t.forEach(r=>{r.score>e.score&&(e=r)}),e}runAndExtendWithFaceDetection(){return new Promise(async t=>{let e=await this.run();t(e?jt({},e):void 0)})}withFaceLandmarks(t=!1){return new Ze(this.runAndExtendWithFaceDetection(),this.input,t)}withFaceExpressions(){return new se(this.runAndExtendWithFaceDetection(),this.input)}withAgeAndGender(){return new ce(this.runAndExtendWithFaceDetection(),this.input)}};function Fa(o,t=new X){return new Qe(o,t)}function Sr(o,t=new X){return new Ie(o,t)}async function un(o,t){return Sr(o,new 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this._labeledDescriptors}get distanceThreshold(){return this._distanceThreshold}computeMeanDistance(t,e){return e.map(r=>go(r,t)).reduce((r,n)=>r+n,0)/(e.length||1)}matchDescriptor(t){return this.labeledDescriptors.map(({descriptors:e,label:r})=>new pe(r,this.computeMeanDistance(t,e))).reduce((e,r)=>e.distancet.toJSON())}}static fromJSON(t){let e=t.labeledDescriptors.map(r=>mt.fromJSON(r));return new tr(e,t.distanceThreshold)}};function Ma(o){let t=new ne;return t.extractWeights(o),t}function fn(o,t){let{width:e,height:r}=new k(t.width,t.height);if(e<=0||r<=0)throw new Error(`resizeResults - invalid dimensions: ${JSON.stringify({width:e,height:r})}`);if(Array.isArray(o))return o.map(n=>fn(n,{width:e,height:r}));if(Zt(o)){let n=o.detection.forSize(e,r),a=o.unshiftedLandmarks.forSize(n.box.width,n.box.height);return we(jt(o,n),a)}return pt(o)?jt(o,o.detection.forSize(e,r)):o instanceof z||o instanceof M?o.forSize(e,r):o}var 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st=class{constructor({inputSize:t,scoreThreshold:e}={}){this._name="TinyYolov2Options";if(this._inputSize=t||416,this._scoreThreshold=e||.5,typeof this._inputSize!="number"||this._inputSize%32!==0)throw new Error(`${this._name} - expected inputSize to be a number divisible by 32`);if(typeof this._scoreThreshold!="number"||this._scoreThreshold<=0||this._scoreThreshold>=1)throw new Error(`${this._name} - expected scoreThreshold to be a number between 0 and 1`)}get inputSize(){return this._inputSize}get scoreThreshold(){return this._scoreThreshold}};var ho=class extends A{constructor(e){super("TinyYolov2");fo(e),this._config=e}get config(){return this._config}get withClassScores(){return this.config.withClassScores||this.config.classes.length>1}get boxEncodingSize(){return 5+(this.withClassScores?this.config.classes.length:0)}runTinyYolov2(e,r){let n=Tt(e,r.conv0);return n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv1),n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv2),n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv3),n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv4),n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv5),n=N.maxPool(n,[2,2],[1,1],"same"),n=Tt(n,r.conv6),n=Tt(n,r.conv7),qt(n,r.conv8,"valid",!1)}runMobilenet(e,r){let n=this.config.isFirstLayerConv2d?Me(qt(e,r.conv0,"valid",!1)):Pt(e,r.conv0);return n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv1),n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv2),n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv3),n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv4),n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv5),n=N.maxPool(n,[2,2],[1,1],"same"),n=r.conv6?Pt(n,r.conv6):n,n=r.conv7?Pt(n,r.conv7):n,qt(n,r.conv8,"valid",!1)}forwardInput(e,r){let{params:n}=this;if(!n)throw new Error("TinyYolov2 - load model before inference");return N.tidy(()=>{let a=N.cast(e.toBatchTensor(r,!1),"float32");return a=this.config.meanRgb?rt(a,this.config.meanRgb):a,a=a.div(255),this.config.withSeparableConvs?this.runMobilenet(a,n):this.runTinyYolov2(a,n)})}async forward(e,r){return this.forwardInput(await C(e),r)}async detect(e,r={}){let{inputSize:n,scoreThreshold:a}=new st(r),s=await C(e),i=await this.forwardInput(s,n),c=N.tidy(()=>N.unstack(i)[0].expandDims()),m={width:s.getInputWidth(0),height:s.getInputHeight(0)},p=await this.extractBoxes(c,s.getReshapedInputDimensions(0),a);i.dispose(),c.dispose();let u=p.map(h=>h.box),f=p.map(h=>h.score),l=p.map(h=>h.classScore),g=p.map(h=>this.config.classes[h.label]);return zr(u.map(h=>h.rescale(n)),f,this.config.iouThreshold,!0).map(h=>new bt(f[h],l[h],g[h],u[h],m))}getDefaultModelName(){return""}extractParamsFromWeightMap(e){return on(e,this.config)}extractParams(e){let r=this.config.filterSizes||ho.DEFAULT_FILTER_SIZES,n=r?r.length:void 0;if(n!==7&&n!==8&&n!==9)throw new Error(`TinyYolov2 - expected 7 | 8 | 9 convolutional filters, but found ${n} filterSizes in config`);return rn(e,this.config,this.boxEncodingSize,r)}async extractBoxes(e,r,n){let{width:a,height:s}=r,i=Math.max(a,s),c=i/a,m=i/s,p=e.shape[1],u=this.config.anchors.length,[f,l,g]=N.tidy(()=>{let _=e.reshape([p,p,u,this.boxEncodingSize]),y=_.slice([0,0,0,0],[p,p,u,4]),E=_.slice([0,0,0,4],[p,p,u,1]),W=this.withClassScores?N.softmax(_.slice([0,0,0,5],[p,p,u,this.config.classes.length]),3):N.scalar(0);return[y,E,W]}),T=[],D=await l.array(),h=await f.array();for(let _=0;_n){let tt=(y+Ne(h[_][y][E][0]))/p*c,lt=(_+Ne(h[_][y][E][1]))/p*m,q=Math.exp(h[_][y][E][2])*this.config.anchors[E].x/p*c,Dt=Math.exp(h[_][y][E][3])*this.config.anchors[E].y/p*m,Et=tt-q/2,Mt=lt-Dt/2,$t={row:_,col:y,anchor:E},{classScore:xo,label:vo}=this.withClassScores?await this.extractPredictedClass(g,$t):{classScore:1,label:0};T.push({box:new Vt(Et,Mt,Et+q,Mt+Dt),score:W,classScore:W*xo,label:vo,...$t})}}return f.dispose(),l.dispose(),g.dispose(),T}async extractPredictedClass(e,r){let{row:n,col:a,anchor:s}=r,i=await e.array();return Array(this.config.classes.length).fill(0).map((c,m)=>i[n][a][s][m]).map((c,m)=>({classScore:c,label:m})).reduce((c,m)=>c.classScore>m.classScore?c:m)}},ee=ho;ee.DEFAULT_FILTER_SIZES=[3,16,32,64,128,256,512,1024,1024];var re=class extends ee{constructor(t=!0){let e={withSeparableConvs:t,iouThreshold:qo,classes:["face"],...t?{anchors:Ko,meanRgb:Qo}:{anchors:Zo,withClassScores:!0}};super(e)}get withSeparableConvs(){return this.config.withSeparableConvs}get anchors(){return this.config.anchors}async locateFaces(t,e){return(await this.detect(t,e)).map(n=>new M(n.score,n.relativeBox,{width:n.imageWidth,height:n.imageHeight}))}getDefaultModelName(){return this.withSeparableConvs?en:tn}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};function ca(o,t=!0){let e=new re(t);return e.extractWeights(o),e}var je=class extends st{constructor(){super(...arguments);this._name="TinyFaceDetectorOptions"}};var J=class{async then(t){return t(await this.run())}async run(){throw new Error("ComposableTask - run is not implemented")}};var Xe=v(x());var bo=v(x());async function oe(o,t,e,r,n=({alignedRect:a})=>a){let a=o.map(c=>Zt(c)?n(c):c.detection),s=r||(t instanceof bo.Tensor?await de(t,a):await le(t,a)),i=await e(s);return s.forEach(c=>c instanceof bo.Tensor&&c.dispose()),i}async function Ce(o,t,e,r,n){return oe([o],t,async a=>e(a[0]),r,n)}var nn=.4,an=[new b(1.603231,2.094468),new b(6.041143,7.080126),new b(2.882459,3.518061),new b(4.266906,5.178857),new b(9.041765,10.66308)],sn=[117.001,114.697,97.404];var ne=class extends ee{constructor(){let t={withSeparableConvs:!0,iouThreshold:nn,classes:["face"],anchors:an,meanRgb:sn,isFirstLayerConv2d:!0,filterSizes:[3,16,32,64,128,256,512]};super(t)}get anchors(){return this.config.anchors}async locateFaces(t,e){return(await this.detect(t,e)).map(n=>new M(n.score,n.relativeBox,{width:n.imageWidth,height:n.imageHeight}))}getDefaultModelName(){return"tiny_face_detector_model"}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};var w={ssdMobilenetv1:new St,tinyFaceDetector:new ne,tinyYolov2:new re,faceLandmark68Net:new Kt,faceLandmark68TinyNet:new ze,faceRecognitionNet:new Qt,faceExpressionNet:new Oe,ageGenderNet:new He},cn=(o,t)=>w.ssdMobilenetv1.locateFaces(o,t),ma=(o,t)=>w.tinyFaceDetector.locateFaces(o,t),pa=(o,t)=>w.tinyYolov2.locateFaces(o,t),mn=o=>w.faceLandmark68Net.detectLandmarks(o),ua=o=>w.faceLandmark68TinyNet.detectLandmarks(o),fa=o=>w.faceRecognitionNet.computeFaceDescriptor(o),la=o=>w.faceExpressionNet.predictExpressions(o),da=o=>w.ageGenderNet.predictAgeAndGender(o),pn=o=>w.ssdMobilenetv1.load(o),ha=o=>w.tinyFaceDetector.load(o),ba=o=>w.tinyYolov2.load(o),ga=o=>w.faceLandmark68Net.load(o),xa=o=>w.faceLandmark68TinyNet.load(o),va=o=>w.faceRecognitionNet.load(o),ya=o=>w.faceExpressionNet.load(o),_a=o=>w.ageGenderNet.load(o),Ta=pn,Pa=cn,wa=mn;var Ir=class extends J{constructor(e,r,n){super();this.parentTask=e;this.input=r;this.extractedFaces=n}},ae=class extends Ir{async run(){let t=await this.parentTask,e=await oe(t,this.input,async r=>Promise.all(r.map(n=>w.faceExpressionNet.predictExpressions(n))),this.extractedFaces);return t.map((r,n)=>xr(r,e[n]))}withAgeAndGender(){return new ie(this,this.input)}},se=class extends Ir{async run(){let t=await this.parentTask;if(!t)return;let e=await Ce(t,this.input,r=>w.faceExpressionNet.predictExpressions(r),this.extractedFaces);return xr(t,e)}withAgeAndGender(){return new ce(this,this.input)}},Wt=class extends ae{withAgeAndGender(){return new Bt(this,this.input)}withFaceDescriptors(){return new wt(this,this.input)}},kt=class extends se{withAgeAndGender(){return new Rt(this,this.input)}withFaceDescriptor(){return new Ft(this,this.input)}};var Nr=class extends J{constructor(e,r,n){super();this.parentTask=e;this.input=r;this.extractedFaces=n}},ie=class extends Nr{async run(){let t=await this.parentTask,e=await oe(t,this.input,async r=>Promise.all(r.map(n=>w.ageGenderNet.predictAgeAndGender(n))),this.extractedFaces);return t.map((r,n)=>{let{age:a,gender:s,genderProbability:i}=e[n];return Er(Mr(r,s,i),a)})}withFaceExpressions(){return new ae(this,this.input)}},ce=class extends Nr{async run(){let t=await this.parentTask;if(!t)return;let{age:e,gender:r,genderProbability:n}=await Ce(t,this.input,a=>w.ageGenderNet.predictAgeAndGender(a),this.extractedFaces);return Er(Mr(t,r,n),e)}withFaceExpressions(){return new se(this,this.input)}},Bt=class extends ie{withFaceExpressions(){return new Wt(this,this.input)}withFaceDescriptors(){return new wt(this,this.input)}},Rt=class extends ce{withFaceExpressions(){return new kt(this,this.input)}withFaceDescriptor(){return new Ft(this,this.input)}};var Ue=class extends J{constructor(e,r){super();this.parentTask=e;this.input=r}},wt=class extends Ue{async run(){let t=await this.parentTask;return(await oe(t,this.input,r=>Promise.all(r.map(n=>w.faceRecognitionNet.computeFaceDescriptor(n))),null,r=>r.landmarks.align(null,{useDlibAlignment:!0}))).map((r,n)=>Dr(t[n],r))}withFaceExpressions(){return new Wt(this,this.input)}withAgeAndGender(){return new Bt(this,this.input)}},Ft=class extends Ue{async run(){let t=await this.parentTask;if(!t)return;let e=await Ce(t,this.input,r=>w.faceRecognitionNet.computeFaceDescriptor(r),null,r=>r.landmarks.align(null,{useDlibAlignment:!0}));return Dr(t,e)}withFaceExpressions(){return new kt(this,this.input)}withAgeAndGender(){return new Rt(this,this.input)}};var Je=class extends J{constructor(e,r,n){super();this.parentTask=e;this.input=r;this.useTinyLandmarkNet=n}get landmarkNet(){return this.useTinyLandmarkNet?w.faceLandmark68TinyNet:w.faceLandmark68Net}},qe=class extends Je{async run(){let t=await this.parentTask,e=t.map(s=>s.detection),r=this.input instanceof Xe.Tensor?await de(this.input,e):await le(this.input,e),n=await Promise.all(r.map(s=>this.landmarkNet.detectLandmarks(s)));return r.forEach(s=>s instanceof Xe.Tensor&&s.dispose()),t.filter((s,i)=>n[i]).map((s,i)=>we(s,n[i]))}withFaceExpressions(){return new Wt(this,this.input)}withAgeAndGender(){return new Bt(this,this.input)}withFaceDescriptors(){return new wt(this,this.input)}},Ze=class extends Je{async run(){let t=await this.parentTask;if(!t)return;let{detection:e}=t,r=this.input instanceof Xe.Tensor?await de(this.input,[e]):await le(this.input,[e]),n=await this.landmarkNet.detectLandmarks(r[0]);return r.forEach(a=>a instanceof Xe.Tensor&&a.dispose()),we(t,n)}withFaceExpressions(){return new kt(this,this.input)}withAgeAndGender(){return new Rt(this,this.input)}withFaceDescriptor(){return new Ft(this,this.input)}};var Ke=class extends J{constructor(e,r=new X){super();this.input=e;this.options=r}},Ie=class extends Ke{async run(){let{input:t,options:e}=this,r;if(e instanceof je)r=w.tinyFaceDetector.locateFaces(t,e);else if(e instanceof X)r=w.ssdMobilenetv1.locateFaces(t,e);else if(e instanceof st)r=w.tinyYolov2.locateFaces(t,e);else throw new Error("detectFaces - expected options to be instance of TinyFaceDetectorOptions | SsdMobilenetv1Options | TinyYolov2Options");return r}runAndExtendWithFaceDetections(){return new Promise((t,e)=>{this.run().then(r=>t(r.map(n=>jt({},n)))).catch(r=>e(r))})}withFaceLandmarks(t=!1){return new qe(this.runAndExtendWithFaceDetections(),this.input,t)}withFaceExpressions(){return new ae(this.runAndExtendWithFaceDetections(),this.input)}withAgeAndGender(){return new ie(this.runAndExtendWithFaceDetections(),this.input)}},Qe=class extends Ke{async run(){let t=await new Ie(this.input,this.options),e=t[0];return t.forEach(r=>{r.score>e.score&&(e=r)}),e}runAndExtendWithFaceDetection(){return new Promise(async t=>{let e=await this.run();t(e?jt({},e):void 0)})}withFaceLandmarks(t=!1){return new Ze(this.runAndExtendWithFaceDetection(),this.input,t)}withFaceExpressions(){return new se(this.runAndExtendWithFaceDetection(),this.input)}withAgeAndGender(){return new ce(this.runAndExtendWithFaceDetection(),this.input)}};function Fa(o,t=new X){return new Qe(o,t)}function Sr(o,t=new X){return new Ie(o,t)}async function un(o,t){return Sr(o,new X(t?{minConfidence:t}:{})).withFaceLandmarks().withFaceDescriptors()}async function Da(o,t={}){return Sr(o,new st(t)).withFaceLandmarks().withFaceDescriptors()}var Ea=un;function go(o,t){if(o.length!==t.length)throw new Error("euclideanDistance: arr1.length !== arr2.length");let e=Array.from(o),r=Array.from(t);return Math.sqrt(e.map((n,a)=>n-r[a]).reduce((n,a)=>n+a**2,0))}var tr=class{constructor(t,e=.6){this._distanceThreshold=e;let r=Array.isArray(t)?t:[t];if(!r.length)throw new Error("FaceRecognizer.constructor - expected atleast one input");let n=1,a=()=>`person ${n++}`;this._labeledDescriptors=r.map(s=>{if(s instanceof mt)return s;if(s instanceof Float32Array)return new mt(a(),[s]);if(s.descriptor&&s.descriptor instanceof Float32Array)return new mt(a(),[s.descriptor]);throw new Error("FaceRecognizer.constructor - expected inputs to be of type LabeledFaceDescriptors | WithFaceDescriptor | Float32Array | Array | Float32Array>")})}get labeledDescriptors(){return this._labeledDescriptors}get distanceThreshold(){return this._distanceThreshold}computeMeanDistance(t,e){return e.map(r=>go(r,t)).reduce((r,n)=>r+n,0)/(e.length||1)}matchDescriptor(t){return this.labeledDescriptors.map(({descriptors:e,label:r})=>new pe(r,this.computeMeanDistance(t,e))).reduce((e,r)=>e.distancet.toJSON())}}static fromJSON(t){let e=t.labeledDescriptors.map(r=>mt.fromJSON(r));return new tr(e,t.distanceThreshold)}};function Ma(o){let t=new ne;return t.extractWeights(o),t}function fn(o,t){let{width:e,height:r}=new k(t.width,t.height);if(e<=0||r<=0)throw new Error(`resizeResults - invalid dimensions: ${JSON.stringify({width:e,height:r})}`);if(Array.isArray(o))return o.map(n=>fn(n,{width:e,height:r}));if(Zt(o)){let n=o.detection.forSize(e,r),a=o.unshiftedLandmarks.forSize(n.box.width,n.box.height);return we(jt(o,n),a)}return pt(o)?jt(o,o.detection.forSize(e,r)):o instanceof z||o instanceof M?o.forSize(e,r):o}var Ia=No;0&&(module.exports={AgeGenderNet,BoundingBox,Box,ComposableTask,ComputeAllFaceDescriptorsTask,ComputeFaceDescriptorsTaskBase,ComputeSingleFaceDescriptorTask,DetectAllFaceLandmarksTask,DetectAllFacesTask,DetectFaceLandmarksTaskBase,DetectFacesTaskBase,DetectSingleFaceLandmarksTask,DetectSingleFaceTask,Dimensions,FACE_EXPRESSION_LABELS,FaceDetection,FaceDetectionNet,FaceExpressionNet,FaceExpressions,FaceLandmark68Net,FaceLandmark68TinyNet,FaceLandmarkNet,FaceLandmarks,FaceLandmarks5,FaceLandmarks68,FaceMatch,FaceMatcher,FaceRecognitionNet,Gender,LabeledBox,LabeledFaceDescriptors,NetInput,NeuralNetwork,ObjectDetection,Point,PredictedBox,Rect,SsdMobilenetv1,SsdMobilenetv1Options,TinyFaceDetector,TinyFaceDetectorOptions,TinyYolov2,TinyYolov2Options,allFaces,allFacesSsdMobilenetv1,allFacesTinyYolov2,awaitMediaLoaded,bufferToImage,computeFaceDescriptor,createCanvas,createCanvasFromMedia,createFaceDetectionNet,createFaceRecognitionNet,createSsdMobilenetv1,createTinyFaceDetector,createTinyYolov2,detectAllFaces,detectFaceLandmarks,detectFaceLandmarksTiny,detectLandmarks,detectSingleFace,draw,env,euclideanDistance,extendWithAge,extendWithFaceDescriptor,extendWithFaceDetection,extendWithFaceExpressions,extendWithFaceLandmarks,extendWithGender,extractFaceTensors,extractFaces,fetchImage,fetchJson,fetchNetWeights,fetchOrThrow,fetchVideo,getContext2dOrThrow,getMediaDimensions,imageTensorToCanvas,imageToSquare,inverseSigmoid,iou,isMediaElement,isMediaLoaded,isWithAge,isWithFaceDetection,isWithFaceExpressions,isWithFaceLandmarks,isWithGender,loadAgeGenderModel,loadFaceDetectionModel,loadFaceExpressionModel,loadFaceLandmarkModel,loadFaceLandmarkTinyModel,loadFaceRecognitionModel,loadSsdMobilenetv1Model,loadTinyFaceDetectorModel,loadTinyYolov2Model,loadWeightMap,locateFaces,matchDimensions,minBbox,nets,nonMaxSuppression,normalize,padToSquare,predictAgeAndGender,recognizeFaceExpressions,resizeResults,resolveInput,shuffleArray,sigmoid,ssdMobilenetv1,tf,tinyFaceDetector,tinyYolov2,toNetInput,utils,validateConfig,version}); diff --git a/dist/face-api.node-wasm.js b/dist/face-api.node-wasm.js index de274cd..0d6f665 100644 --- a/dist/face-api.node-wasm.js +++ b/dist/face-api.node-wasm.js @@ -4,4 +4,4 @@ author: ' */ -"use strict";var dn=Object.create;var er=Object.defineProperty;var hn=Object.getOwnPropertyDescriptor;var bn=Object.getOwnPropertyNames;var gn=Object.getPrototypeOf,xn=Object.prototype.hasOwnProperty;var vn=(o,t)=>()=>(t||o((t={exports:{}}).exports,t),t.exports),Ar=(o,t)=>{for(var e in t)er(o,e,{get:t[e],enumerable:!0})},_o=(o,t,e,r)=>{if(t&&typeof t=="object"||typeof t=="function")for(let n of bn(t))!xn.call(o,n)&&n!==e&&er(o,n,{get:()=>t[n],enumerable:!(r=hn(t,n))||r.enumerable});return o};var v=(o,t,e)=>(e=o!=null?dn(gn(o)):{},_o(t||!o||!o.__esModule?er(e,"default",{value:o,enumerable:!0}):e,o)),yn=o=>_o(er({},"__esModule",{value:!0}),o);var x=vn((ka,rr)=>{"use strict";var To=Object.defineProperty,_n=Object.getOwnPropertyDescriptor,Tn=Object.getOwnPropertyNames,Pn=Object.prototype.hasOwnProperty,Wr=(o,t,e,r)=>{if(t&&typeof t=="object"||typeof t=="function")for(let n of Tn(t))!Pn.call(o,n)&&n!==e&&To(o,n,{get:()=>t[n],enumerable:!(r=_n(t,n))||r.enumerable});return o},Po=(o,t,e)=>(Wr(o,t,"default"),e&&Wr(e,t,"default")),wn=o=>Wr(To({},"__esModule",{value:!0}),o),kr={};rr.exports=wn(kr);Po(kr,require("@tensorflow/tfjs"),rr.exports);Po(kr,require("@tensorflow/tfjs-backend-wasm"),rr.exports)});var Na={};Ar(Na,{AgeGenderNet:()=>He,BoundingBox:()=>Vt,Box:()=>F,ComposableTask:()=>J,ComputeAllFaceDescriptorsTask:()=>wt,ComputeFaceDescriptorsTaskBase:()=>Ue,ComputeSingleFaceDescriptorTask:()=>Ft,DetectAllFaceLandmarksTask:()=>qe,DetectAllFacesTask:()=>Ie,DetectFaceLandmarksTaskBase:()=>Je,DetectFacesTaskBase:()=>Ke,DetectSingleFaceLandmarksTask:()=>Ze,DetectSingleFaceTask:()=>Qe,Dimensions:()=>k,FACE_EXPRESSION_LABELS:()=>ao,FaceDetection:()=>M,FaceDetectionNet:()=>fo,FaceExpressionNet:()=>Oe,FaceExpressions:()=>yt,FaceLandmark68Net:()=>Kt,FaceLandmark68TinyNet:()=>ze,FaceLandmarkNet:()=>mo,FaceLandmarks:()=>z,FaceLandmarks5:()=>Gr,FaceLandmarks68:()=>Gt,FaceMatch:()=>pe,FaceMatcher:()=>tr,FaceRecognitionNet:()=>Qt,Gender:()=>Pr,LabeledBox:()=>ue,LabeledFaceDescriptors:()=>mt,NetInput:()=>ut,NeuralNetwork:()=>A,ObjectDetection:()=>bt,Point:()=>b,PredictedBox:()=>jr,Rect:()=>Yt,SsdMobilenetv1:()=>St,SsdMobilenetv1Options:()=>X,TinyFaceDetector:()=>ne,TinyFaceDetectorOptions:()=>je,TinyYolov2:()=>re,TinyYolov2Options:()=>st,allFaces:()=>Ea,allFacesSsdMobilenetv1:()=>fn,allFacesTinyYolov2:()=>Da,awaitMediaLoaded:()=>Qr,bufferToImage:()=>to,computeFaceDescriptor:()=>fa,createCanvas:()=>Jt,createCanvasFromMedia:()=>We,createFaceDetectionNet:()=>aa,createFaceRecognitionNet:()=>Xn,createSsdMobilenetv1:()=>qo,createTinyFaceDetector:()=>Ma,createTinyYolov2:()=>ca,detectAllFaces:()=>Lr,detectFaceLandmarks:()=>pn,detectFaceLandmarksTiny:()=>ua,detectLandmarks:()=>wa,detectSingleFace:()=>Fa,draw:()=>io,env:()=>P,euclideanDistance:()=>xo,extendWithAge:()=>Mr,extendWithFaceDescriptor:()=>Er,extendWithFaceDetection:()=>jt,extendWithFaceExpressions:()=>vr,extendWithFaceLandmarks:()=>we,extendWithGender:()=>Cr,extractFaceTensors:()=>de,extractFaces:()=>le,fetchImage:()=>An,fetchJson:()=>oo,fetchNetWeights:()=>Wn,fetchOrThrow:()=>xt,fetchVideo:()=>kn,getContext2dOrThrow:()=>O,getMediaDimensions:()=>Xt,imageTensorToCanvas:()=>eo,imageToSquare:()=>ro,inverseSigmoid:()=>En,iou:()=>Hr,isMediaElement:()=>cr,isMediaLoaded:()=>Ae,isWithAge:()=>Jn,isWithFaceDetection:()=>pt,isWithFaceExpressions:()=>so,isWithFaceLandmarks:()=>Zt,isWithGender:()=>qn,loadAgeGenderModel:()=>_a,loadFaceDetectionModel:()=>Ta,loadFaceExpressionModel:()=>ya,loadFaceLandmarkModel:()=>ga,loadFaceLandmarkTinyModel:()=>xa,loadFaceRecognitionModel:()=>va,loadSsdMobilenetv1Model:()=>un,loadTinyFaceDetectorModel:()=>ha,loadTinyYolov2Model:()=>ba,loadWeightMap:()=>no,locateFaces:()=>Pa,matchDimensions:()=>Bn,minBbox:()=>zr,nets:()=>w,nonMaxSuppression:()=>Vr,normalize:()=>rt,padToSquare:()=>Yr,predictAgeAndGender:()=>da,recognizeFaceExpressions:()=>la,resizeResults:()=>ln,resolveInput:()=>Ut,shuffleArray:()=>Dn,sigmoid:()=>Ne,ssdMobilenetv1:()=>mn,tf:()=>Ca,tinyFaceDetector:()=>ma,tinyYolov2:()=>pa,toNetInput:()=>C,utils:()=>Or,validateConfig:()=>lo,version:()=>Ia});module.exports=yn(Na);var 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st=class{constructor({inputSize:t,scoreThreshold:e}={}){this._name="TinyYolov2Options";if(this._inputSize=t||416,this._scoreThreshold=e||.5,typeof this._inputSize!="number"||this._inputSize%32!==0)throw new Error(`${this._name} - expected inputSize to be a number divisible by 32`);if(typeof this._scoreThreshold!="number"||this._scoreThreshold<=0||this._scoreThreshold>=1)throw new Error(`${this._name} - expected scoreThreshold to be a number between 0 and 1`)}get inputSize(){return this._inputSize}get scoreThreshold(){return this._scoreThreshold}};var bo=class extends A{constructor(e){super("TinyYolov2");lo(e),this._config=e}get config(){return this._config}get withClassScores(){return this.config.withClassScores||this.config.classes.length>1}get boxEncodingSize(){return 5+(this.withClassScores?this.config.classes.length:0)}runTinyYolov2(e,r){let n=Tt(e,r.conv0);return n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv1),n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv2),n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv3),n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv4),n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv5),n=N.maxPool(n,[2,2],[1,1],"same"),n=Tt(n,r.conv6),n=Tt(n,r.conv7),qt(n,r.conv8,"valid",!1)}runMobilenet(e,r){let n=this.config.isFirstLayerConv2d?Me(qt(e,r.conv0,"valid",!1)):Pt(e,r.conv0);return n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv1),n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv2),n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv3),n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv4),n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv5),n=N.maxPool(n,[2,2],[1,1],"same"),n=r.conv6?Pt(n,r.conv6):n,n=r.conv7?Pt(n,r.conv7):n,qt(n,r.conv8,"valid",!1)}forwardInput(e,r){let{params:n}=this;if(!n)throw new Error("TinyYolov2 - load model before inference");return N.tidy(()=>{let a=N.cast(e.toBatchTensor(r,!1),"float32");return a=this.config.meanRgb?rt(a,this.config.meanRgb):a,a=a.div(255),this.config.withSeparableConvs?this.runMobilenet(a,n):this.runTinyYolov2(a,n)})}async forward(e,r){return this.forwardInput(await C(e),r)}async detect(e,r={}){let{inputSize:n,scoreThreshold:a}=new st(r),s=await C(e),i=await this.forwardInput(s,n),c=N.tidy(()=>N.unstack(i)[0].expandDims()),m={width:s.getInputWidth(0),height:s.getInputHeight(0)},p=await this.extractBoxes(c,s.getReshapedInputDimensions(0),a);i.dispose(),c.dispose();let u=p.map(h=>h.box),f=p.map(h=>h.score),l=p.map(h=>h.classScore),g=p.map(h=>this.config.classes[h.label]);return Vr(u.map(h=>h.rescale(n)),f,this.config.iouThreshold,!0).map(h=>new bt(f[h],l[h],g[h],u[h],m))}getDefaultModelName(){return""}extractParamsFromWeightMap(e){return nn(e,this.config)}extractParams(e){let r=this.config.filterSizes||bo.DEFAULT_FILTER_SIZES,n=r?r.length:void 0;if(n!==7&&n!==8&&n!==9)throw new Error(`TinyYolov2 - expected 7 | 8 | 9 convolutional filters, but found ${n} filterSizes in config`);return on(e,this.config,this.boxEncodingSize,r)}async extractBoxes(e,r,n){let{width:a,height:s}=r,i=Math.max(a,s),c=i/a,m=i/s,p=e.shape[1],u=this.config.anchors.length,[f,l,g]=N.tidy(()=>{let _=e.reshape([p,p,u,this.boxEncodingSize]),y=_.slice([0,0,0,0],[p,p,u,4]),E=_.slice([0,0,0,4],[p,p,u,1]),W=this.withClassScores?N.softmax(_.slice([0,0,0,5],[p,p,u,this.config.classes.length]),3):N.scalar(0);return[y,E,W]}),T=[],D=await l.array(),h=await f.array();for(let _=0;_n){let tt=(y+Ne(h[_][y][E][0]))/p*c,lt=(_+Ne(h[_][y][E][1]))/p*m,q=Math.exp(h[_][y][E][2])*this.config.anchors[E].x/p*c,Dt=Math.exp(h[_][y][E][3])*this.config.anchors[E].y/p*m,Et=tt-q/2,Mt=lt-Dt/2,$t={row:_,col:y,anchor:E},{classScore:vo,label:yo}=this.withClassScores?await this.extractPredictedClass(g,$t):{classScore:1,label:0};T.push({box:new Vt(Et,Mt,Et+q,Mt+Dt),score:W,classScore:W*vo,label:yo,...$t})}}return f.dispose(),l.dispose(),g.dispose(),T}async extractPredictedClass(e,r){let{row:n,col:a,anchor:s}=r,i=await e.array();return Array(this.config.classes.length).fill(0).map((c,m)=>i[n][a][s][m]).map((c,m)=>({classScore:c,label:m})).reduce((c,m)=>c.classScore>m.classScore?c:m)}},ee=bo;ee.DEFAULT_FILTER_SIZES=[3,16,32,64,128,256,512,1024,1024];var re=class extends ee{constructor(t=!0){let e={withSeparableConvs:t,iouThreshold:Zo,classes:["face"],...t?{anchors:Qo,meanRgb:tn}:{anchors:Ko,withClassScores:!0}};super(e)}get withSeparableConvs(){return this.config.withSeparableConvs}get anchors(){return this.config.anchors}async locateFaces(t,e){return(await this.detect(t,e)).map(n=>new M(n.score,n.relativeBox,{width:n.imageWidth,height:n.imageHeight}))}getDefaultModelName(){return this.withSeparableConvs?rn:en}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};function ca(o,t=!0){let e=new re(t);return e.extractWeights(o),e}var je=class extends st{constructor(){super(...arguments);this._name="TinyFaceDetectorOptions"}};var J=class{async then(t){return t(await this.run())}async run(){throw new Error("ComposableTask - run is not implemented")}};var Xe=v(x());var go=v(x());async function oe(o,t,e,r,n=({alignedRect:a})=>a){let a=o.map(c=>Zt(c)?n(c):c.detection),s=r||(t instanceof go.Tensor?await de(t,a):await le(t,a)),i=await e(s);return s.forEach(c=>c instanceof go.Tensor&&c.dispose()),i}async function Ce(o,t,e,r,n){return oe([o],t,async a=>e(a[0]),r,n)}var an=.4,sn=[new b(1.603231,2.094468),new b(6.041143,7.080126),new b(2.882459,3.518061),new b(4.266906,5.178857),new b(9.041765,10.66308)],cn=[117.001,114.697,97.404];var ne=class extends ee{constructor(){let t={withSeparableConvs:!0,iouThreshold:an,classes:["face"],anchors:sn,meanRgb:cn,isFirstLayerConv2d:!0,filterSizes:[3,16,32,64,128,256,512]};super(t)}get anchors(){return this.config.anchors}async locateFaces(t,e){return(await this.detect(t,e)).map(n=>new M(n.score,n.relativeBox,{width:n.imageWidth,height:n.imageHeight}))}getDefaultModelName(){return"tiny_face_detector_model"}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};var w={ssdMobilenetv1:new St,tinyFaceDetector:new ne,tinyYolov2:new re,faceLandmark68Net:new Kt,faceLandmark68TinyNet:new ze,faceRecognitionNet:new Qt,faceExpressionNet:new Oe,ageGenderNet:new He},mn=(o,t)=>w.ssdMobilenetv1.locateFaces(o,t),ma=(o,t)=>w.tinyFaceDetector.locateFaces(o,t),pa=(o,t)=>w.tinyYolov2.locateFaces(o,t),pn=o=>w.faceLandmark68Net.detectLandmarks(o),ua=o=>w.faceLandmark68TinyNet.detectLandmarks(o),fa=o=>w.faceRecognitionNet.computeFaceDescriptor(o),la=o=>w.faceExpressionNet.predictExpressions(o),da=o=>w.ageGenderNet.predictAgeAndGender(o),un=o=>w.ssdMobilenetv1.load(o),ha=o=>w.tinyFaceDetector.load(o),ba=o=>w.tinyYolov2.load(o),ga=o=>w.faceLandmark68Net.load(o),xa=o=>w.faceLandmark68TinyNet.load(o),va=o=>w.faceRecognitionNet.load(o),ya=o=>w.faceExpressionNet.load(o),_a=o=>w.ageGenderNet.load(o),Ta=un,Pa=mn,wa=pn;var Nr=class extends J{constructor(e,r,n){super();this.parentTask=e;this.input=r;this.extractedFaces=n}},ae=class extends Nr{async run(){let t=await this.parentTask,e=await oe(t,this.input,async r=>Promise.all(r.map(n=>w.faceExpressionNet.predictExpressions(n))),this.extractedFaces);return t.map((r,n)=>vr(r,e[n]))}withAgeAndGender(){return new ie(this,this.input)}},se=class extends Nr{async run(){let t=await this.parentTask;if(!t)return;let e=await Ce(t,this.input,r=>w.faceExpressionNet.predictExpressions(r),this.extractedFaces);return vr(t,e)}withAgeAndGender(){return new ce(this,this.input)}},Wt=class extends ae{withAgeAndGender(){return new Bt(this,this.input)}withFaceDescriptors(){return new wt(this,this.input)}},kt=class extends se{withAgeAndGender(){return new Rt(this,this.input)}withFaceDescriptor(){return new Ft(this,this.input)}};var Sr=class extends J{constructor(e,r,n){super();this.parentTask=e;this.input=r;this.extractedFaces=n}},ie=class extends Sr{async run(){let t=await this.parentTask,e=await oe(t,this.input,async r=>Promise.all(r.map(n=>w.ageGenderNet.predictAgeAndGender(n))),this.extractedFaces);return t.map((r,n)=>{let{age:a,gender:s,genderProbability:i}=e[n];return Mr(Cr(r,s,i),a)})}withFaceExpressions(){return new ae(this,this.input)}},ce=class extends Sr{async run(){let t=await this.parentTask;if(!t)return;let{age:e,gender:r,genderProbability:n}=await Ce(t,this.input,a=>w.ageGenderNet.predictAgeAndGender(a),this.extractedFaces);return Mr(Cr(t,r,n),e)}withFaceExpressions(){return new se(this,this.input)}},Bt=class extends ie{withFaceExpressions(){return new Wt(this,this.input)}withFaceDescriptors(){return new wt(this,this.input)}},Rt=class extends ce{withFaceExpressions(){return new kt(this,this.input)}withFaceDescriptor(){return new Ft(this,this.input)}};var Ue=class extends J{constructor(e,r){super();this.parentTask=e;this.input=r}},wt=class extends Ue{async run(){let t=await this.parentTask;return(await oe(t,this.input,r=>Promise.all(r.map(n=>w.faceRecognitionNet.computeFaceDescriptor(n))),null,r=>r.landmarks.align(null,{useDlibAlignment:!0}))).map((r,n)=>Er(t[n],r))}withFaceExpressions(){return new Wt(this,this.input)}withAgeAndGender(){return new Bt(this,this.input)}},Ft=class extends Ue{async run(){let t=await this.parentTask;if(!t)return;let e=await Ce(t,this.input,r=>w.faceRecognitionNet.computeFaceDescriptor(r),null,r=>r.landmarks.align(null,{useDlibAlignment:!0}));return Er(t,e)}withFaceExpressions(){return new kt(this,this.input)}withAgeAndGender(){return new Rt(this,this.input)}};var Je=class extends J{constructor(e,r,n){super();this.parentTask=e;this.input=r;this.useTinyLandmarkNet=n}get landmarkNet(){return this.useTinyLandmarkNet?w.faceLandmark68TinyNet:w.faceLandmark68Net}},qe=class extends Je{async run(){let t=await this.parentTask,e=t.map(s=>s.detection),r=this.input instanceof Xe.Tensor?await de(this.input,e):await le(this.input,e),n=await Promise.all(r.map(s=>this.landmarkNet.detectLandmarks(s)));return r.forEach(s=>s instanceof Xe.Tensor&&s.dispose()),t.filter((s,i)=>n[i]).map((s,i)=>we(s,n[i]))}withFaceExpressions(){return new Wt(this,this.input)}withAgeAndGender(){return new Bt(this,this.input)}withFaceDescriptors(){return new wt(this,this.input)}},Ze=class extends Je{async run(){let t=await this.parentTask;if(!t)return;let{detection:e}=t,r=this.input instanceof Xe.Tensor?await de(this.input,[e]):await le(this.input,[e]),n=await this.landmarkNet.detectLandmarks(r[0]);return r.forEach(a=>a instanceof Xe.Tensor&&a.dispose()),we(t,n)}withFaceExpressions(){return new kt(this,this.input)}withAgeAndGender(){return new Rt(this,this.input)}withFaceDescriptor(){return new Ft(this,this.input)}};var Ke=class extends J{constructor(e,r=new X){super();this.input=e;this.options=r}},Ie=class extends Ke{async run(){let{input:t,options:e}=this,r;if(e instanceof je)r=w.tinyFaceDetector.locateFaces(t,e);else if(e instanceof X)r=w.ssdMobilenetv1.locateFaces(t,e);else if(e instanceof st)r=w.tinyYolov2.locateFaces(t,e);else throw new Error("detectFaces - expected options to be instance of TinyFaceDetectorOptions | SsdMobilenetv1Options | TinyYolov2Options");return r}runAndExtendWithFaceDetections(){return new Promise((t,e)=>{this.run().then(r=>t(r.map(n=>jt({},n)))).catch(r=>e(r))})}withFaceLandmarks(t=!1){return new qe(this.runAndExtendWithFaceDetections(),this.input,t)}withFaceExpressions(){return new ae(this.runAndExtendWithFaceDetections(),this.input)}withAgeAndGender(){return new ie(this.runAndExtendWithFaceDetections(),this.input)}},Qe=class extends Ke{async run(){let t=await new Ie(this.input,this.options),e=t[0];return t.forEach(r=>{r.score>e.score&&(e=r)}),e}runAndExtendWithFaceDetection(){return new Promise(async t=>{let e=await this.run();t(e?jt({},e):void 0)})}withFaceLandmarks(t=!1){return new Ze(this.runAndExtendWithFaceDetection(),this.input,t)}withFaceExpressions(){return new se(this.runAndExtendWithFaceDetection(),this.input)}withAgeAndGender(){return new ce(this.runAndExtendWithFaceDetection(),this.input)}};function Fa(o,t=new X){return new Qe(o,t)}function Lr(o,t=new X){return new Ie(o,t)}async function fn(o,t){return Lr(o,new X(t?{minConfidence:t}:{})).withFaceLandmarks().withFaceDescriptors()}async function Da(o,t={}){return Lr(o,new st(t)).withFaceLandmarks().withFaceDescriptors()}var Ea=fn;function xo(o,t){if(o.length!==t.length)throw new Error("euclideanDistance: arr1.length !== arr2.length");let e=Array.from(o),r=Array.from(t);return Math.sqrt(e.map((n,a)=>n-r[a]).reduce((n,a)=>n+a**2,0))}var tr=class{constructor(t,e=.6){this._distanceThreshold=e;let r=Array.isArray(t)?t:[t];if(!r.length)throw new Error("FaceRecognizer.constructor - expected atleast one input");let n=1,a=()=>`person ${n++}`;this._labeledDescriptors=r.map(s=>{if(s instanceof mt)return s;if(s instanceof Float32Array)return new mt(a(),[s]);if(s.descriptor&&s.descriptor instanceof Float32Array)return new mt(a(),[s.descriptor]);throw new Error("FaceRecognizer.constructor - expected inputs to be of type LabeledFaceDescriptors | WithFaceDescriptor | Float32Array | Array | Float32Array>")})}get labeledDescriptors(){return this._labeledDescriptors}get distanceThreshold(){return this._distanceThreshold}computeMeanDistance(t,e){return e.map(r=>xo(r,t)).reduce((r,n)=>r+n,0)/(e.length||1)}matchDescriptor(t){return this.labeledDescriptors.map(({descriptors:e,label:r})=>new pe(r,this.computeMeanDistance(t,e))).reduce((e,r)=>e.distancet.toJSON())}}static fromJSON(t){let e=t.labeledDescriptors.map(r=>mt.fromJSON(r));return new tr(e,t.distanceThreshold)}};function Ma(o){let t=new ne;return t.extractWeights(o),t}function ln(o,t){let{width:e,height:r}=new k(t.width,t.height);if(e<=0||r<=0)throw new Error(`resizeResults - invalid dimensions: ${JSON.stringify({width:e,height:r})}`);if(Array.isArray(o))return o.map(n=>ln(n,{width:e,height:r}));if(Zt(o)){let n=o.detection.forSize(e,r),a=o.unshiftedLandmarks.forSize(n.box.width,n.box.height);return we(jt(o,n),a)}return pt(o)?jt(o,o.detection.forSize(e,r)):o instanceof z||o instanceof M?o.forSize(e,r):o}var Ia=So;0&&(module.exports={AgeGenderNet,BoundingBox,Box,ComposableTask,ComputeAllFaceDescriptorsTask,ComputeFaceDescriptorsTaskBase,ComputeSingleFaceDescriptorTask,DetectAllFaceLandmarksTask,DetectAllFacesTask,DetectFaceLandmarksTaskBase,DetectFacesTaskBase,DetectSingleFaceLandmarksTask,DetectSingleFaceTask,Dimensions,FACE_EXPRESSION_LABELS,FaceDetection,FaceDetectionNet,FaceExpressionNet,FaceExpressions,FaceLandmark68Net,FaceLandmark68TinyNet,FaceLandmarkNet,FaceLandmarks,FaceLandmarks5,FaceLandmarks68,FaceMatch,FaceMatcher,FaceRecognitionNet,Gender,LabeledBox,LabeledFaceDescriptors,NetInput,NeuralNetwork,ObjectDetection,Point,PredictedBox,Rect,SsdMobilenetv1,SsdMobilenetv1Options,TinyFaceDetector,TinyFaceDetectorOptions,TinyYolov2,TinyYolov2Options,allFaces,allFacesSsdMobilenetv1,allFacesTinyYolov2,awaitMediaLoaded,bufferToImage,computeFaceDescriptor,createCanvas,createCanvasFromMedia,createFaceDetectionNet,createFaceRecognitionNet,createSsdMobilenetv1,createTinyFaceDetector,createTinyYolov2,detectAllFaces,detectFaceLandmarks,detectFaceLandmarksTiny,detectLandmarks,detectSingleFace,draw,env,euclideanDistance,extendWithAge,extendWithFaceDescriptor,extendWithFaceDetection,extendWithFaceExpressions,extendWithFaceLandmarks,extendWithGender,extractFaceTensors,extractFaces,fetchImage,fetchJson,fetchNetWeights,fetchOrThrow,fetchVideo,getContext2dOrThrow,getMediaDimensions,imageTensorToCanvas,imageToSquare,inverseSigmoid,iou,isMediaElement,isMediaLoaded,isWithAge,isWithFaceDetection,isWithFaceExpressions,isWithFaceLandmarks,isWithGender,loadAgeGenderModel,loadFaceDetectionModel,loadFaceExpressionModel,loadFaceLandmarkModel,loadFaceLandmarkTinyModel,loadFaceRecognitionModel,loadSsdMobilenetv1Model,loadTinyFaceDetectorModel,loadTinyYolov2Model,loadWeightMap,locateFaces,matchDimensions,minBbox,nets,nonMaxSuppression,normalize,padToSquare,predictAgeAndGender,recognizeFaceExpressions,resizeResults,resolveInput,shuffleArray,sigmoid,ssdMobilenetv1,tf,tinyFaceDetector,tinyYolov2,toNetInput,utils,validateConfig,version}); 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N=v(x());var Ir=o=>typeof o=="number";function lo(o){if(!o)throw new Error(`invalid config: ${o}`);if(typeof o.withSeparableConvs!="boolean")throw new Error(`config.withSeparableConvs has to be a boolean, have: ${o.withSeparableConvs}`);if(!Ir(o.iouThreshold)||o.iouThreshold<0||o.iouThreshold>1)throw new Error(`config.iouThreshold has to be a number between [0, 1], have: ${o.iouThreshold}`);if(!Array.isArray(o.classes)||!o.classes.length||!o.classes.every(t=>typeof t=="string"))throw new Error(`config.classes has to be an array class names: string[], have: ${JSON.stringify(o.classes)}`);if(!Array.isArray(o.anchors)||!o.anchors.length||!o.anchors.map(t=>t||{}).every(t=>Ir(t.x)&&Ir(t.y)))throw new Error(`config.anchors has to be an array of { x: number, y: number }, have: ${JSON.stringify(o.anchors)}`);if(o.meanRgb&&(!Array.isArray(o.meanRgb)||o.meanRgb.length!==3||!o.meanRgb.every(Ir)))throw new Error(`config.meanRgb has to be an array of shape [number, number, number], have: 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c=e(`${i}/sub`,1),m=e(`${i}/truediv`,1);return{sub:c,truediv:m}}function n(i){let c=e(`${i}/filters`,4),m=e(`${i}/bias`,1);return{filters:c,bias:m}}function a(i){let c=n(`${i}/conv`),m=r(`${i}/bn`);return{conv:c,bn:m}}let s=xe(e);return{extractConvParams:n,extractConvWithBatchNormParams:a,extractSeparableConvParams:s}}function nn(o,t){let e=[],{extractConvParams:r,extractConvWithBatchNormParams:n,extractSeparableConvParams:a}=ia(o,e),s;if(t.withSeparableConvs){let i=t.filterSizes&&t.filterSizes.length||9;s={conv0:t.isFirstLayerConv2d?r("conv0"):a("conv0"),conv1:a("conv1"),conv2:a("conv2"),conv3:a("conv3"),conv4:a("conv4"),conv5:a("conv5"),conv6:i>7?a("conv6"):void 0,conv7:i>8?a("conv7"):void 0,conv8:r("conv8")}}else s={conv0:n("conv0"),conv1:n("conv1"),conv2:n("conv2"),conv3:n("conv3"),conv4:n("conv4"),conv5:n("conv5"),conv6:n("conv6"),conv7:n("conv7"),conv8:r("conv8")};return B(o,e),{params:s,paramMappings:e}}var st=class{constructor({inputSize:t,scoreThreshold:e}={}){this._name="TinyYolov2Options";if(this._inputSize=t||416,this._scoreThreshold=e||.5,typeof this._inputSize!="number"||this._inputSize%32!==0)throw new Error(`${this._name} - expected inputSize to be a number divisible by 32`);if(typeof this._scoreThreshold!="number"||this._scoreThreshold<=0||this._scoreThreshold>=1)throw new Error(`${this._name} - expected scoreThreshold to be a number between 0 and 1`)}get inputSize(){return this._inputSize}get scoreThreshold(){return this._scoreThreshold}};var bo=class extends A{constructor(e){super("TinyYolov2");lo(e),this._config=e}get config(){return this._config}get withClassScores(){return this.config.withClassScores||this.config.classes.length>1}get boxEncodingSize(){return 5+(this.withClassScores?this.config.classes.length:0)}runTinyYolov2(e,r){let n=Tt(e,r.conv0);return n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv1),n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv2),n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv3),n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv4),n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv5),n=N.maxPool(n,[2,2],[1,1],"same"),n=Tt(n,r.conv6),n=Tt(n,r.conv7),qt(n,r.conv8,"valid",!1)}runMobilenet(e,r){let n=this.config.isFirstLayerConv2d?Me(qt(e,r.conv0,"valid",!1)):Pt(e,r.conv0);return n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv1),n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv2),n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv3),n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv4),n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv5),n=N.maxPool(n,[2,2],[1,1],"same"),n=r.conv6?Pt(n,r.conv6):n,n=r.conv7?Pt(n,r.conv7):n,qt(n,r.conv8,"valid",!1)}forwardInput(e,r){let{params:n}=this;if(!n)throw new Error("TinyYolov2 - load model before inference");return N.tidy(()=>{let a=N.cast(e.toBatchTensor(r,!1),"float32");return a=this.config.meanRgb?rt(a,this.config.meanRgb):a,a=a.div(255),this.config.withSeparableConvs?this.runMobilenet(a,n):this.runTinyYolov2(a,n)})}async forward(e,r){return this.forwardInput(await C(e),r)}async detect(e,r={}){let{inputSize:n,scoreThreshold:a}=new st(r),s=await C(e),i=await this.forwardInput(s,n),c=N.tidy(()=>N.unstack(i)[0].expandDims()),m={width:s.getInputWidth(0),height:s.getInputHeight(0)},p=await this.extractBoxes(c,s.getReshapedInputDimensions(0),a);i.dispose(),c.dispose();let u=p.map(h=>h.box),f=p.map(h=>h.score),l=p.map(h=>h.classScore),g=p.map(h=>this.config.classes[h.label]);return Vr(u.map(h=>h.rescale(n)),f,this.config.iouThreshold,!0).map(h=>new bt(f[h],l[h],g[h],u[h],m))}getDefaultModelName(){return""}extractParamsFromWeightMap(e){return nn(e,this.config)}extractParams(e){let r=this.config.filterSizes||bo.DEFAULT_FILTER_SIZES,n=r?r.length:void 0;if(n!==7&&n!==8&&n!==9)throw new Error(`TinyYolov2 - expected 7 | 8 | 9 convolutional filters, but found ${n} filterSizes in config`);return on(e,this.config,this.boxEncodingSize,r)}async extractBoxes(e,r,n){let{width:a,height:s}=r,i=Math.max(a,s),c=i/a,m=i/s,p=e.shape[1],u=this.config.anchors.length,[f,l,g]=N.tidy(()=>{let _=e.reshape([p,p,u,this.boxEncodingSize]),y=_.slice([0,0,0,0],[p,p,u,4]),E=_.slice([0,0,0,4],[p,p,u,1]),W=this.withClassScores?N.softmax(_.slice([0,0,0,5],[p,p,u,this.config.classes.length]),3):N.scalar(0);return[y,E,W]}),T=[],D=await l.array(),h=await f.array();for(let _=0;_n){let tt=(y+Ne(h[_][y][E][0]))/p*c,lt=(_+Ne(h[_][y][E][1]))/p*m,q=Math.exp(h[_][y][E][2])*this.config.anchors[E].x/p*c,Dt=Math.exp(h[_][y][E][3])*this.config.anchors[E].y/p*m,Et=tt-q/2,Mt=lt-Dt/2,$t={row:_,col:y,anchor:E},{classScore:vo,label:yo}=this.withClassScores?await this.extractPredictedClass(g,$t):{classScore:1,label:0};T.push({box:new Vt(Et,Mt,Et+q,Mt+Dt),score:W,classScore:W*vo,label:yo,...$t})}}return f.dispose(),l.dispose(),g.dispose(),T}async extractPredictedClass(e,r){let{row:n,col:a,anchor:s}=r,i=await e.array();return Array(this.config.classes.length).fill(0).map((c,m)=>i[n][a][s][m]).map((c,m)=>({classScore:c,label:m})).reduce((c,m)=>c.classScore>m.classScore?c:m)}},ee=bo;ee.DEFAULT_FILTER_SIZES=[3,16,32,64,128,256,512,1024,1024];var re=class extends ee{constructor(t=!0){let e={withSeparableConvs:t,iouThreshold:Zo,classes:["face"],...t?{anchors:Qo,meanRgb:tn}:{anchors:Ko,withClassScores:!0}};super(e)}get withSeparableConvs(){return this.config.withSeparableConvs}get anchors(){return this.config.anchors}async locateFaces(t,e){return(await this.detect(t,e)).map(n=>new M(n.score,n.relativeBox,{width:n.imageWidth,height:n.imageHeight}))}getDefaultModelName(){return this.withSeparableConvs?rn:en}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};function ca(o,t=!0){let e=new re(t);return e.extractWeights(o),e}var je=class extends st{constructor(){super(...arguments);this._name="TinyFaceDetectorOptions"}};var J=class{async then(t){return t(await this.run())}async run(){throw new Error("ComposableTask - run is not implemented")}};var Xe=v(x());var go=v(x());async function oe(o,t,e,r,n=({alignedRect:a})=>a){let a=o.map(c=>Zt(c)?n(c):c.detection),s=r||(t instanceof go.Tensor?await de(t,a):await le(t,a)),i=await e(s);return s.forEach(c=>c instanceof go.Tensor&&c.dispose()),i}async function Ce(o,t,e,r,n){return oe([o],t,async a=>e(a[0]),r,n)}var an=.4,sn=[new b(1.603231,2.094468),new b(6.041143,7.080126),new b(2.882459,3.518061),new b(4.266906,5.178857),new b(9.041765,10.66308)],cn=[117.001,114.697,97.404];var ne=class extends ee{constructor(){let t={withSeparableConvs:!0,iouThreshold:an,classes:["face"],anchors:sn,meanRgb:cn,isFirstLayerConv2d:!0,filterSizes:[3,16,32,64,128,256,512]};super(t)}get anchors(){return this.config.anchors}async locateFaces(t,e){return(await this.detect(t,e)).map(n=>new M(n.score,n.relativeBox,{width:n.imageWidth,height:n.imageHeight}))}getDefaultModelName(){return"tiny_face_detector_model"}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};var w={ssdMobilenetv1:new St,tinyFaceDetector:new ne,tinyYolov2:new re,faceLandmark68Net:new Kt,faceLandmark68TinyNet:new ze,faceRecognitionNet:new Qt,faceExpressionNet:new Oe,ageGenderNet:new He},mn=(o,t)=>w.ssdMobilenetv1.locateFaces(o,t),ma=(o,t)=>w.tinyFaceDetector.locateFaces(o,t),pa=(o,t)=>w.tinyYolov2.locateFaces(o,t),pn=o=>w.faceLandmark68Net.detectLandmarks(o),ua=o=>w.faceLandmark68TinyNet.detectLandmarks(o),fa=o=>w.faceRecognitionNet.computeFaceDescriptor(o),la=o=>w.faceExpressionNet.predictExpressions(o),da=o=>w.ageGenderNet.predictAgeAndGender(o),un=o=>w.ssdMobilenetv1.load(o),ha=o=>w.tinyFaceDetector.load(o),ba=o=>w.tinyYolov2.load(o),ga=o=>w.faceLandmark68Net.load(o),xa=o=>w.faceLandmark68TinyNet.load(o),va=o=>w.faceRecognitionNet.load(o),ya=o=>w.faceExpressionNet.load(o),_a=o=>w.ageGenderNet.load(o),Ta=un,Pa=mn,wa=pn;var Nr=class extends J{constructor(e,r,n){super();this.parentTask=e;this.input=r;this.extractedFaces=n}},ae=class extends Nr{async run(){let t=await this.parentTask,e=await oe(t,this.input,async r=>Promise.all(r.map(n=>w.faceExpressionNet.predictExpressions(n))),this.extractedFaces);return t.map((r,n)=>vr(r,e[n]))}withAgeAndGender(){return new ie(this,this.input)}},se=class extends Nr{async run(){let t=await this.parentTask;if(!t)return;let e=await Ce(t,this.input,r=>w.faceExpressionNet.predictExpressions(r),this.extractedFaces);return vr(t,e)}withAgeAndGender(){return new ce(this,this.input)}},Wt=class extends ae{withAgeAndGender(){return new Bt(this,this.input)}withFaceDescriptors(){return new wt(this,this.input)}},kt=class extends se{withAgeAndGender(){return new Rt(this,this.input)}withFaceDescriptor(){return new Ft(this,this.input)}};var Sr=class extends J{constructor(e,r,n){super();this.parentTask=e;this.input=r;this.extractedFaces=n}},ie=class extends Sr{async run(){let t=await this.parentTask,e=await oe(t,this.input,async r=>Promise.all(r.map(n=>w.ageGenderNet.predictAgeAndGender(n))),this.extractedFaces);return t.map((r,n)=>{let{age:a,gender:s,genderProbability:i}=e[n];return Mr(Cr(r,s,i),a)})}withFaceExpressions(){return new ae(this,this.input)}},ce=class extends Sr{async run(){let t=await this.parentTask;if(!t)return;let{age:e,gender:r,genderProbability:n}=await Ce(t,this.input,a=>w.ageGenderNet.predictAgeAndGender(a),this.extractedFaces);return Mr(Cr(t,r,n),e)}withFaceExpressions(){return new se(this,this.input)}},Bt=class extends ie{withFaceExpressions(){return new Wt(this,this.input)}withFaceDescriptors(){return new wt(this,this.input)}},Rt=class extends ce{withFaceExpressions(){return new kt(this,this.input)}withFaceDescriptor(){return new Ft(this,this.input)}};var Ue=class extends J{constructor(e,r){super();this.parentTask=e;this.input=r}},wt=class extends Ue{async run(){let t=await this.parentTask;return(await oe(t,this.input,r=>Promise.all(r.map(n=>w.faceRecognitionNet.computeFaceDescriptor(n))),null,r=>r.landmarks.align(null,{useDlibAlignment:!0}))).map((r,n)=>Er(t[n],r))}withFaceExpressions(){return new Wt(this,this.input)}withAgeAndGender(){return new Bt(this,this.input)}},Ft=class extends Ue{async run(){let t=await this.parentTask;if(!t)return;let e=await Ce(t,this.input,r=>w.faceRecognitionNet.computeFaceDescriptor(r),null,r=>r.landmarks.align(null,{useDlibAlignment:!0}));return Er(t,e)}withFaceExpressions(){return new kt(this,this.input)}withAgeAndGender(){return new Rt(this,this.input)}};var Je=class extends J{constructor(e,r,n){super();this.parentTask=e;this.input=r;this.useTinyLandmarkNet=n}get landmarkNet(){return this.useTinyLandmarkNet?w.faceLandmark68TinyNet:w.faceLandmark68Net}},qe=class extends Je{async run(){let t=await this.parentTask,e=t.map(s=>s.detection),r=this.input instanceof Xe.Tensor?await de(this.input,e):await le(this.input,e),n=await Promise.all(r.map(s=>this.landmarkNet.detectLandmarks(s)));return r.forEach(s=>s instanceof Xe.Tensor&&s.dispose()),t.filter((s,i)=>n[i]).map((s,i)=>we(s,n[i]))}withFaceExpressions(){return new Wt(this,this.input)}withAgeAndGender(){return new Bt(this,this.input)}withFaceDescriptors(){return new wt(this,this.input)}},Ze=class extends Je{async run(){let t=await this.parentTask;if(!t)return;let{detection:e}=t,r=this.input instanceof Xe.Tensor?await de(this.input,[e]):await le(this.input,[e]),n=await this.landmarkNet.detectLandmarks(r[0]);return r.forEach(a=>a instanceof Xe.Tensor&&a.dispose()),we(t,n)}withFaceExpressions(){return new kt(this,this.input)}withAgeAndGender(){return new Rt(this,this.input)}withFaceDescriptor(){return new Ft(this,this.input)}};var Ke=class extends J{constructor(e,r=new X){super();this.input=e;this.options=r}},Ie=class extends Ke{async run(){let{input:t,options:e}=this,r;if(e instanceof je)r=w.tinyFaceDetector.locateFaces(t,e);else if(e instanceof X)r=w.ssdMobilenetv1.locateFaces(t,e);else if(e instanceof st)r=w.tinyYolov2.locateFaces(t,e);else throw new Error("detectFaces - expected options to be instance of TinyFaceDetectorOptions | SsdMobilenetv1Options | TinyYolov2Options");return r}runAndExtendWithFaceDetections(){return new Promise((t,e)=>{this.run().then(r=>t(r.map(n=>jt({},n)))).catch(r=>e(r))})}withFaceLandmarks(t=!1){return new qe(this.runAndExtendWithFaceDetections(),this.input,t)}withFaceExpressions(){return new ae(this.runAndExtendWithFaceDetections(),this.input)}withAgeAndGender(){return new ie(this.runAndExtendWithFaceDetections(),this.input)}},Qe=class extends Ke{async run(){let t=await new Ie(this.input,this.options),e=t[0];return t.forEach(r=>{r.score>e.score&&(e=r)}),e}runAndExtendWithFaceDetection(){return new Promise(async t=>{let e=await this.run();t(e?jt({},e):void 0)})}withFaceLandmarks(t=!1){return new Ze(this.runAndExtendWithFaceDetection(),this.input,t)}withFaceExpressions(){return new se(this.runAndExtendWithFaceDetection(),this.input)}withAgeAndGender(){return new ce(this.runAndExtendWithFaceDetection(),this.input)}};function Fa(o,t=new X){return new Qe(o,t)}function Lr(o,t=new X){return new Ie(o,t)}async function fn(o,t){return Lr(o,new X(t?{minConfidence:t}:{})).withFaceLandmarks().withFaceDescriptors()}async function Da(o,t={}){return Lr(o,new st(t)).withFaceLandmarks().withFaceDescriptors()}var Ea=fn;function xo(o,t){if(o.length!==t.length)throw new Error("euclideanDistance: arr1.length !== arr2.length");let e=Array.from(o),r=Array.from(t);return Math.sqrt(e.map((n,a)=>n-r[a]).reduce((n,a)=>n+a**2,0))}var tr=class{constructor(t,e=.6){this._distanceThreshold=e;let r=Array.isArray(t)?t:[t];if(!r.length)throw new Error("FaceRecognizer.constructor - expected atleast one input");let n=1,a=()=>`person ${n++}`;this._labeledDescriptors=r.map(s=>{if(s instanceof mt)return s;if(s instanceof Float32Array)return new mt(a(),[s]);if(s.descriptor&&s.descriptor instanceof Float32Array)return new mt(a(),[s.descriptor]);throw new Error("FaceRecognizer.constructor - expected inputs to be of type LabeledFaceDescriptors | WithFaceDescriptor | Float32Array | Array | Float32Array>")})}get labeledDescriptors(){return this._labeledDescriptors}get distanceThreshold(){return this._distanceThreshold}computeMeanDistance(t,e){return e.map(r=>xo(r,t)).reduce((r,n)=>r+n,0)/(e.length||1)}matchDescriptor(t){return this.labeledDescriptors.map(({descriptors:e,label:r})=>new pe(r,this.computeMeanDistance(t,e))).reduce((e,r)=>e.distancet.toJSON())}}static fromJSON(t){let e=t.labeledDescriptors.map(r=>mt.fromJSON(r));return new tr(e,t.distanceThreshold)}};function Ma(o){let t=new ne;return t.extractWeights(o),t}function ln(o,t){let{width:e,height:r}=new k(t.width,t.height);if(e<=0||r<=0)throw new Error(`resizeResults - invalid dimensions: ${JSON.stringify({width:e,height:r})}`);if(Array.isArray(o))return o.map(n=>ln(n,{width:e,height:r}));if(Zt(o)){let n=o.detection.forSize(e,r),a=o.unshiftedLandmarks.forSize(n.box.width,n.box.height);return we(jt(o,n),a)}return pt(o)?jt(o,o.detection.forSize(e,r)):o instanceof z||o instanceof M?o.forSize(e,r):o}var Ia=So;0&&(module.exports={AgeGenderNet,BoundingBox,Box,ComposableTask,ComputeAllFaceDescriptorsTask,ComputeFaceDescriptorsTaskBase,ComputeSingleFaceDescriptorTask,DetectAllFaceLandmarksTask,DetectAllFacesTask,DetectFaceLandmarksTaskBase,DetectFacesTaskBase,DetectSingleFaceLandmarksTask,DetectSingleFaceTask,Dimensions,FACE_EXPRESSION_LABELS,FaceDetection,FaceDetectionNet,FaceExpressionNet,FaceExpressions,FaceLandmark68Net,FaceLandmark68TinyNet,FaceLandmarkNet,FaceLandmarks,FaceLandmarks5,FaceLandmarks68,FaceMatch,FaceMatcher,FaceRecognitionNet,Gender,LabeledBox,LabeledFaceDescriptors,NetInput,NeuralNetwork,ObjectDetection,Point,PredictedBox,Rect,SsdMobilenetv1,SsdMobilenetv1Options,TinyFaceDetector,TinyFaceDetectorOptions,TinyYolov2,TinyYolov2Options,allFaces,allFacesSsdMobilenetv1,allFacesTinyYolov2,awaitMediaLoaded,bufferToImage,computeFaceDescriptor,createCanvas,createCanvasFromMedia,createFaceDetectionNet,createFaceRecognitionNet,createSsdMobilenetv1,createTinyFaceDetector,createTinyYolov2,detectAllFaces,detectFaceLandmarks,detectFaceLandmarksTiny,detectLandmarks,detectSingleFace,draw,env,euclideanDistance,extendWithAge,extendWithFaceDescriptor,extendWithFaceDetection,extendWithFaceExpressions,extendWithFaceLandmarks,extendWithGender,extractFaceTensors,extractFaces,fetchImage,fetchJson,fetchNetWeights,fetchOrThrow,fetchVideo,getContext2dOrThrow,getMediaDimensions,imageTensorToCanvas,imageToSquare,inverseSigmoid,iou,isMediaElement,isMediaLoaded,isWithAge,isWithFaceDetection,isWithFaceExpressions,isWithFaceLandmarks,isWithGender,loadAgeGenderModel,loadFaceDetectionModel,loadFaceExpressionModel,loadFaceLandmarkModel,loadFaceLandmarkTinyModel,loadFaceRecognitionModel,loadSsdMobilenetv1Model,loadTinyFaceDetectorModel,loadTinyYolov2Model,loadWeightMap,locateFaces,matchDimensions,minBbox,nets,nonMaxSuppression,normalize,padToSquare,predictAgeAndGender,recognizeFaceExpressions,resizeResults,resolveInput,shuffleArray,sigmoid,ssdMobilenetv1,tf,tinyFaceDetector,tinyYolov2,toNetInput,utils,validateConfig,version}); diff --git a/dist/face-api.node.js b/dist/face-api.node.js index aa28585..09b3d39 100644 --- a/dist/face-api.node.js +++ b/dist/face-api.node.js @@ -4,4 +4,4 @@ author: ' */ -"use strict";var ln=Object.create;var er=Object.defineProperty;var dn=Object.getOwnPropertyDescriptor;var hn=Object.getOwnPropertyNames;var bn=Object.getPrototypeOf,gn=Object.prototype.hasOwnProperty;var xn=(o,t)=>()=>(t||o((t={exports:{}}).exports,t),t.exports),Lr=(o,t)=>{for(var e in t)er(o,e,{get:t[e],enumerable:!0})},yo=(o,t,e,r)=>{if(t&&typeof t=="object"||typeof t=="function")for(let n of hn(t))!gn.call(o,n)&&n!==e&&er(o,n,{get:()=>t[n],enumerable:!(r=dn(t,n))||r.enumerable});return o};var v=(o,t,e)=>(e=o!=null?ln(bn(o)):{},yo(t||!o||!o.__esModule?er(e,"default",{value:o,enumerable:!0}):e,o)),vn=o=>yo(er({},"__esModule",{value:!0}),o);var x=xn((ka,Wr)=>{"use strict";var _o=Object.defineProperty,yn=Object.getOwnPropertyDescriptor,_n=Object.getOwnPropertyNames,Tn=Object.prototype.hasOwnProperty,Ar=(o,t,e,r)=>{if(t&&typeof t=="object"||typeof t=="function")for(let n of _n(t))!Tn.call(o,n)&&n!==e&&_o(o,n,{get:()=>t[n],enumerable:!(r=yn(t,n))||r.enumerable});return o},Pn=(o,t,e)=>(Ar(o,t,"default"),e&&Ar(e,t,"default")),wn=o=>Ar(_o({},"__esModule",{value:!0}),o),To={};Wr.exports=wn(To);Pn(To,require("@tensorflow/tfjs-node"),Wr.exports)});var Na={};Lr(Na,{AgeGenderNet:()=>He,BoundingBox:()=>Vt,Box:()=>F,ComposableTask:()=>J,ComputeAllFaceDescriptorsTask:()=>wt,ComputeFaceDescriptorsTaskBase:()=>Ue,ComputeSingleFaceDescriptorTask:()=>Ft,DetectAllFaceLandmarksTask:()=>qe,DetectAllFacesTask:()=>Ie,DetectFaceLandmarksTaskBase:()=>Je,DetectFacesTaskBase:()=>Ke,DetectSingleFaceLandmarksTask:()=>Ze,DetectSingleFaceTask:()=>Qe,Dimensions:()=>k,FACE_EXPRESSION_LABELS:()=>no,FaceDetection:()=>M,FaceDetectionNet:()=>uo,FaceExpressionNet:()=>Oe,FaceExpressions:()=>yt,FaceLandmark68Net:()=>Kt,FaceLandmark68TinyNet:()=>ze,FaceLandmarkNet:()=>co,FaceLandmarks:()=>z,FaceLandmarks5:()=>Yr,FaceLandmarks68:()=>Gt,FaceMatch:()=>pe,FaceMatcher:()=>tr,FaceRecognitionNet:()=>Qt,Gender:()=>Tr,LabeledBox:()=>ue,LabeledFaceDescriptors:()=>mt,NetInput:()=>ut,NeuralNetwork:()=>A,ObjectDetection:()=>bt,Point:()=>b,PredictedBox:()=>Gr,Rect:()=>Yt,SsdMobilenetv1:()=>St,SsdMobilenetv1Options:()=>X,TinyFaceDetector:()=>ne,TinyFaceDetectorOptions:()=>je,TinyYolov2:()=>re,TinyYolov2Options:()=>st,allFaces:()=>Ea,allFacesSsdMobilenetv1:()=>un,allFacesTinyYolov2:()=>Da,awaitMediaLoaded:()=>Kr,bufferToImage:()=>Qr,computeFaceDescriptor:()=>fa,createCanvas:()=>Jt,createCanvasFromMedia:()=>We,createFaceDetectionNet:()=>aa,createFaceRecognitionNet:()=>Xn,createSsdMobilenetv1:()=>Jo,createTinyFaceDetector:()=>Ma,createTinyYolov2:()=>ca,detectAllFaces:()=>Sr,detectFaceLandmarks:()=>mn,detectFaceLandmarksTiny:()=>ua,detectLandmarks:()=>wa,detectSingleFace:()=>Fa,draw:()=>so,env:()=>P,euclideanDistance:()=>go,extendWithAge:()=>Er,extendWithFaceDescriptor:()=>Dr,extendWithFaceDetection:()=>jt,extendWithFaceExpressions:()=>xr,extendWithFaceLandmarks:()=>we,extendWithGender:()=>Mr,extractFaceTensors:()=>de,extractFaces:()=>le,fetchImage:()=>An,fetchJson:()=>ro,fetchNetWeights:()=>Wn,fetchOrThrow:()=>xt,fetchVideo:()=>kn,getContext2dOrThrow:()=>O,getMediaDimensions:()=>Xt,imageTensorToCanvas:()=>to,imageToSquare:()=>eo,inverseSigmoid:()=>En,iou:()=>Or,isMediaElement:()=>ir,isMediaLoaded:()=>Ae,isWithAge:()=>Jn,isWithFaceDetection:()=>pt,isWithFaceExpressions:()=>ao,isWithFaceLandmarks:()=>Zt,isWithGender:()=>qn,loadAgeGenderModel:()=>_a,loadFaceDetectionModel:()=>Ta,loadFaceExpressionModel:()=>ya,loadFaceLandmarkModel:()=>ga,loadFaceLandmarkTinyModel:()=>xa,loadFaceRecognitionModel:()=>va,loadSsdMobilenetv1Model:()=>pn,loadTinyFaceDetectorModel:()=>ha,loadTinyYolov2Model:()=>ba,loadWeightMap:()=>oo,locateFaces:()=>Pa,matchDimensions:()=>Bn,minBbox:()=>Hr,nets:()=>w,nonMaxSuppression:()=>zr,normalize:()=>rt,padToSquare:()=>Vr,predictAgeAndGender:()=>da,recognizeFaceExpressions:()=>la,resizeResults:()=>fn,resolveInput:()=>Ut,shuffleArray:()=>Dn,sigmoid:()=>Ne,ssdMobilenetv1:()=>cn,tf:()=>Ca,tinyFaceDetector:()=>ma,tinyYolov2:()=>pa,toNetInput:()=>C,utils:()=>$r,validateConfig:()=>fo,version:()=>Ia});module.exports=vn(Na);var 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N=v(x());var Cr=o=>typeof o=="number";function fo(o){if(!o)throw new Error(`invalid config: ${o}`);if(typeof o.withSeparableConvs!="boolean")throw new Error(`config.withSeparableConvs has to be a boolean, have: ${o.withSeparableConvs}`);if(!Cr(o.iouThreshold)||o.iouThreshold<0||o.iouThreshold>1)throw new Error(`config.iouThreshold has to be a number between [0, 1], have: ${o.iouThreshold}`);if(!Array.isArray(o.classes)||!o.classes.length||!o.classes.every(t=>typeof t=="string"))throw new Error(`config.classes has to be an array class names: string[], have: ${JSON.stringify(o.classes)}`);if(!Array.isArray(o.anchors)||!o.anchors.length||!o.anchors.map(t=>t||{}).every(t=>Cr(t.x)&&Cr(t.y)))throw new Error(`config.anchors has to be an array of { x: number, y: number }, have: ${JSON.stringify(o.anchors)}`);if(o.meanRgb&&(!Array.isArray(o.meanRgb)||o.meanRgb.length!==3||!o.meanRgb.every(Cr)))throw new Error(`config.meanRgb has to be an array of shape [number, number, number], have: 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st=class{constructor({inputSize:t,scoreThreshold:e}={}){this._name="TinyYolov2Options";if(this._inputSize=t||416,this._scoreThreshold=e||.5,typeof this._inputSize!="number"||this._inputSize%32!==0)throw new Error(`${this._name} - expected inputSize to be a number divisible by 32`);if(typeof this._scoreThreshold!="number"||this._scoreThreshold<=0||this._scoreThreshold>=1)throw new Error(`${this._name} - expected scoreThreshold to be a number between 0 and 1`)}get inputSize(){return this._inputSize}get scoreThreshold(){return this._scoreThreshold}};var ho=class extends A{constructor(e){super("TinyYolov2");fo(e),this._config=e}get config(){return this._config}get withClassScores(){return this.config.withClassScores||this.config.classes.length>1}get boxEncodingSize(){return 5+(this.withClassScores?this.config.classes.length:0)}runTinyYolov2(e,r){let n=Tt(e,r.conv0);return n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv1),n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv2),n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv3),n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv4),n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv5),n=N.maxPool(n,[2,2],[1,1],"same"),n=Tt(n,r.conv6),n=Tt(n,r.conv7),qt(n,r.conv8,"valid",!1)}runMobilenet(e,r){let n=this.config.isFirstLayerConv2d?Me(qt(e,r.conv0,"valid",!1)):Pt(e,r.conv0);return n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv1),n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv2),n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv3),n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv4),n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv5),n=N.maxPool(n,[2,2],[1,1],"same"),n=r.conv6?Pt(n,r.conv6):n,n=r.conv7?Pt(n,r.conv7):n,qt(n,r.conv8,"valid",!1)}forwardInput(e,r){let{params:n}=this;if(!n)throw new Error("TinyYolov2 - load model before inference");return N.tidy(()=>{let a=N.cast(e.toBatchTensor(r,!1),"float32");return 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extractPredictedClass(e,r){let{row:n,col:a,anchor:s}=r,i=await e.array();return Array(this.config.classes.length).fill(0).map((c,m)=>i[n][a][s][m]).map((c,m)=>({classScore:c,label:m})).reduce((c,m)=>c.classScore>m.classScore?c:m)}},ee=ho;ee.DEFAULT_FILTER_SIZES=[3,16,32,64,128,256,512,1024,1024];var re=class extends ee{constructor(t=!0){let e={withSeparableConvs:t,iouThreshold:qo,classes:["face"],...t?{anchors:Ko,meanRgb:Qo}:{anchors:Zo,withClassScores:!0}};super(e)}get withSeparableConvs(){return this.config.withSeparableConvs}get anchors(){return this.config.anchors}async locateFaces(t,e){return(await this.detect(t,e)).map(n=>new M(n.score,n.relativeBox,{width:n.imageWidth,height:n.imageHeight}))}getDefaultModelName(){return this.withSeparableConvs?en:tn}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};function ca(o,t=!0){let e=new re(t);return e.extractWeights(o),e}var je=class extends 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ie(this,this.input)}},se=class extends Ir{async run(){let t=await this.parentTask;if(!t)return;let e=await Ce(t,this.input,r=>w.faceExpressionNet.predictExpressions(r),this.extractedFaces);return xr(t,e)}withAgeAndGender(){return new ce(this,this.input)}},Wt=class extends ae{withAgeAndGender(){return new Bt(this,this.input)}withFaceDescriptors(){return new wt(this,this.input)}},kt=class extends se{withAgeAndGender(){return new Rt(this,this.input)}withFaceDescriptor(){return new Ft(this,this.input)}};var Nr=class extends J{constructor(e,r,n){super();this.parentTask=e;this.input=r;this.extractedFaces=n}},ie=class extends Nr{async run(){let t=await this.parentTask,e=await oe(t,this.input,async r=>Promise.all(r.map(n=>w.ageGenderNet.predictAgeAndGender(n))),this.extractedFaces);return t.map((r,n)=>{let{age:a,gender:s,genderProbability:i}=e[n];return Er(Mr(r,s,i),a)})}withFaceExpressions(){return new ae(this,this.input)}},ce=class extends Nr{async run(){let t=await this.parentTask;if(!t)return;let{age:e,gender:r,genderProbability:n}=await Ce(t,this.input,a=>w.ageGenderNet.predictAgeAndGender(a),this.extractedFaces);return Er(Mr(t,r,n),e)}withFaceExpressions(){return new se(this,this.input)}},Bt=class extends ie{withFaceExpressions(){return new Wt(this,this.input)}withFaceDescriptors(){return new wt(this,this.input)}},Rt=class extends ce{withFaceExpressions(){return new kt(this,this.input)}withFaceDescriptor(){return new Ft(this,this.input)}};var Ue=class extends J{constructor(e,r){super();this.parentTask=e;this.input=r}},wt=class extends Ue{async run(){let t=await this.parentTask;return(await oe(t,this.input,r=>Promise.all(r.map(n=>w.faceRecognitionNet.computeFaceDescriptor(n))),null,r=>r.landmarks.align(null,{useDlibAlignment:!0}))).map((r,n)=>Dr(t[n],r))}withFaceExpressions(){return new Wt(this,this.input)}withAgeAndGender(){return new Bt(this,this.input)}},Ft=class extends Ue{async run(){let t=await this.parentTask;if(!t)return;let e=await 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this.parentTask;if(!t)return;let{detection:e}=t,r=this.input instanceof Xe.Tensor?await de(this.input,[e]):await le(this.input,[e]),n=await this.landmarkNet.detectLandmarks(r[0]);return r.forEach(a=>a instanceof Xe.Tensor&&a.dispose()),we(t,n)}withFaceExpressions(){return new kt(this,this.input)}withAgeAndGender(){return new Rt(this,this.input)}withFaceDescriptor(){return new Ft(this,this.input)}};var Ke=class extends J{constructor(e,r=new X){super();this.input=e;this.options=r}},Ie=class extends Ke{async run(){let{input:t,options:e}=this,r;if(e instanceof je)r=w.tinyFaceDetector.locateFaces(t,e);else if(e instanceof X)r=w.ssdMobilenetv1.locateFaces(t,e);else if(e instanceof st)r=w.tinyYolov2.locateFaces(t,e);else throw new Error("detectFaces - expected options to be instance of TinyFaceDetectorOptions | SsdMobilenetv1Options | TinyYolov2Options");return r}runAndExtendWithFaceDetections(){return new Promise((t,e)=>{this.run().then(r=>t(r.map(n=>jt({},n)))).catch(r=>e(r))})}withFaceLandmarks(t=!1){return new qe(this.runAndExtendWithFaceDetections(),this.input,t)}withFaceExpressions(){return new ae(this.runAndExtendWithFaceDetections(),this.input)}withAgeAndGender(){return new ie(this.runAndExtendWithFaceDetections(),this.input)}},Qe=class extends Ke{async run(){let t=await new Ie(this.input,this.options),e=t[0];return t.forEach(r=>{r.score>e.score&&(e=r)}),e}runAndExtendWithFaceDetection(){return new Promise(async t=>{let e=await this.run();t(e?jt({},e):void 0)})}withFaceLandmarks(t=!1){return new Ze(this.runAndExtendWithFaceDetection(),this.input,t)}withFaceExpressions(){return new se(this.runAndExtendWithFaceDetection(),this.input)}withAgeAndGender(){return new ce(this.runAndExtendWithFaceDetection(),this.input)}};function Fa(o,t=new X){return new Qe(o,t)}function Sr(o,t=new X){return new Ie(o,t)}async function un(o,t){return Sr(o,new 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N=v(x());var Cr=o=>typeof o=="number";function fo(o){if(!o)throw new Error(`invalid config: ${o}`);if(typeof o.withSeparableConvs!="boolean")throw new Error(`config.withSeparableConvs has to be a boolean, have: ${o.withSeparableConvs}`);if(!Cr(o.iouThreshold)||o.iouThreshold<0||o.iouThreshold>1)throw new Error(`config.iouThreshold has to be a number between [0, 1], have: ${o.iouThreshold}`);if(!Array.isArray(o.classes)||!o.classes.length||!o.classes.every(t=>typeof t=="string"))throw new Error(`config.classes has to be an array class names: string[], have: ${JSON.stringify(o.classes)}`);if(!Array.isArray(o.anchors)||!o.anchors.length||!o.anchors.map(t=>t||{}).every(t=>Cr(t.x)&&Cr(t.y)))throw new Error(`config.anchors has to be an array of { x: number, y: number }, have: ${JSON.stringify(o.anchors)}`);if(o.meanRgb&&(!Array.isArray(o.meanRgb)||o.meanRgb.length!==3||!o.meanRgb.every(Cr)))throw new Error(`config.meanRgb has to be an array of shape [number, number, number], have: 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st=class{constructor({inputSize:t,scoreThreshold:e}={}){this._name="TinyYolov2Options";if(this._inputSize=t||416,this._scoreThreshold=e||.5,typeof this._inputSize!="number"||this._inputSize%32!==0)throw new Error(`${this._name} - expected inputSize to be a number divisible by 32`);if(typeof this._scoreThreshold!="number"||this._scoreThreshold<=0||this._scoreThreshold>=1)throw new Error(`${this._name} - expected scoreThreshold to be a number between 0 and 1`)}get inputSize(){return this._inputSize}get scoreThreshold(){return this._scoreThreshold}};var ho=class extends A{constructor(e){super("TinyYolov2");fo(e),this._config=e}get config(){return this._config}get withClassScores(){return this.config.withClassScores||this.config.classes.length>1}get boxEncodingSize(){return 5+(this.withClassScores?this.config.classes.length:0)}runTinyYolov2(e,r){let n=Tt(e,r.conv0);return n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv1),n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv2),n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv3),n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv4),n=N.maxPool(n,[2,2],[2,2],"same"),n=Tt(n,r.conv5),n=N.maxPool(n,[2,2],[1,1],"same"),n=Tt(n,r.conv6),n=Tt(n,r.conv7),qt(n,r.conv8,"valid",!1)}runMobilenet(e,r){let n=this.config.isFirstLayerConv2d?Me(qt(e,r.conv0,"valid",!1)):Pt(e,r.conv0);return n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv1),n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv2),n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv3),n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv4),n=N.maxPool(n,[2,2],[2,2],"same"),n=Pt(n,r.conv5),n=N.maxPool(n,[2,2],[1,1],"same"),n=r.conv6?Pt(n,r.conv6):n,n=r.conv7?Pt(n,r.conv7):n,qt(n,r.conv8,"valid",!1)}forwardInput(e,r){let{params:n}=this;if(!n)throw new Error("TinyYolov2 - load model before inference");return N.tidy(()=>{let a=N.cast(e.toBatchTensor(r,!1),"float32");return a=this.config.meanRgb?rt(a,this.config.meanRgb):a,a=a.div(255),this.config.withSeparableConvs?this.runMobilenet(a,n):this.runTinyYolov2(a,n)})}async forward(e,r){return this.forwardInput(await C(e),r)}async detect(e,r={}){let{inputSize:n,scoreThreshold:a}=new st(r),s=await C(e),i=await this.forwardInput(s,n),c=N.tidy(()=>N.unstack(i)[0].expandDims()),m={width:s.getInputWidth(0),height:s.getInputHeight(0)},p=await this.extractBoxes(c,s.getReshapedInputDimensions(0),a);i.dispose(),c.dispose();let u=p.map(h=>h.box),f=p.map(h=>h.score),l=p.map(h=>h.classScore),g=p.map(h=>this.config.classes[h.label]);return zr(u.map(h=>h.rescale(n)),f,this.config.iouThreshold,!0).map(h=>new bt(f[h],l[h],g[h],u[h],m))}getDefaultModelName(){return""}extractParamsFromWeightMap(e){return on(e,this.config)}extractParams(e){let r=this.config.filterSizes||ho.DEFAULT_FILTER_SIZES,n=r?r.length:void 0;if(n!==7&&n!==8&&n!==9)throw new Error(`TinyYolov2 - expected 7 | 8 | 9 convolutional filters, but found ${n} filterSizes in config`);return rn(e,this.config,this.boxEncodingSize,r)}async extractBoxes(e,r,n){let{width:a,height:s}=r,i=Math.max(a,s),c=i/a,m=i/s,p=e.shape[1],u=this.config.anchors.length,[f,l,g]=N.tidy(()=>{let _=e.reshape([p,p,u,this.boxEncodingSize]),y=_.slice([0,0,0,0],[p,p,u,4]),E=_.slice([0,0,0,4],[p,p,u,1]),W=this.withClassScores?N.softmax(_.slice([0,0,0,5],[p,p,u,this.config.classes.length]),3):N.scalar(0);return[y,E,W]}),T=[],D=await l.array(),h=await f.array();for(let _=0;_n){let tt=(y+Ne(h[_][y][E][0]))/p*c,lt=(_+Ne(h[_][y][E][1]))/p*m,q=Math.exp(h[_][y][E][2])*this.config.anchors[E].x/p*c,Dt=Math.exp(h[_][y][E][3])*this.config.anchors[E].y/p*m,Et=tt-q/2,Mt=lt-Dt/2,$t={row:_,col:y,anchor:E},{classScore:xo,label:vo}=this.withClassScores?await this.extractPredictedClass(g,$t):{classScore:1,label:0};T.push({box:new Vt(Et,Mt,Et+q,Mt+Dt),score:W,classScore:W*xo,label:vo,...$t})}}return f.dispose(),l.dispose(),g.dispose(),T}async extractPredictedClass(e,r){let{row:n,col:a,anchor:s}=r,i=await e.array();return Array(this.config.classes.length).fill(0).map((c,m)=>i[n][a][s][m]).map((c,m)=>({classScore:c,label:m})).reduce((c,m)=>c.classScore>m.classScore?c:m)}},ee=ho;ee.DEFAULT_FILTER_SIZES=[3,16,32,64,128,256,512,1024,1024];var re=class extends ee{constructor(t=!0){let e={withSeparableConvs:t,iouThreshold:qo,classes:["face"],...t?{anchors:Ko,meanRgb:Qo}:{anchors:Zo,withClassScores:!0}};super(e)}get withSeparableConvs(){return this.config.withSeparableConvs}get anchors(){return this.config.anchors}async locateFaces(t,e){return(await this.detect(t,e)).map(n=>new M(n.score,n.relativeBox,{width:n.imageWidth,height:n.imageHeight}))}getDefaultModelName(){return this.withSeparableConvs?en:tn}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};function ca(o,t=!0){let e=new re(t);return e.extractWeights(o),e}var je=class extends st{constructor(){super(...arguments);this._name="TinyFaceDetectorOptions"}};var J=class{async then(t){return t(await this.run())}async run(){throw new Error("ComposableTask - run is not implemented")}};var Xe=v(x());var bo=v(x());async function oe(o,t,e,r,n=({alignedRect:a})=>a){let a=o.map(c=>Zt(c)?n(c):c.detection),s=r||(t instanceof bo.Tensor?await de(t,a):await le(t,a)),i=await e(s);return s.forEach(c=>c instanceof bo.Tensor&&c.dispose()),i}async function Ce(o,t,e,r,n){return oe([o],t,async a=>e(a[0]),r,n)}var nn=.4,an=[new b(1.603231,2.094468),new b(6.041143,7.080126),new b(2.882459,3.518061),new b(4.266906,5.178857),new b(9.041765,10.66308)],sn=[117.001,114.697,97.404];var ne=class extends ee{constructor(){let t={withSeparableConvs:!0,iouThreshold:nn,classes:["face"],anchors:an,meanRgb:sn,isFirstLayerConv2d:!0,filterSizes:[3,16,32,64,128,256,512]};super(t)}get anchors(){return this.config.anchors}async locateFaces(t,e){return(await this.detect(t,e)).map(n=>new M(n.score,n.relativeBox,{width:n.imageWidth,height:n.imageHeight}))}getDefaultModelName(){return"tiny_face_detector_model"}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};var w={ssdMobilenetv1:new St,tinyFaceDetector:new ne,tinyYolov2:new re,faceLandmark68Net:new Kt,faceLandmark68TinyNet:new ze,faceRecognitionNet:new Qt,faceExpressionNet:new Oe,ageGenderNet:new He},cn=(o,t)=>w.ssdMobilenetv1.locateFaces(o,t),ma=(o,t)=>w.tinyFaceDetector.locateFaces(o,t),pa=(o,t)=>w.tinyYolov2.locateFaces(o,t),mn=o=>w.faceLandmark68Net.detectLandmarks(o),ua=o=>w.faceLandmark68TinyNet.detectLandmarks(o),fa=o=>w.faceRecognitionNet.computeFaceDescriptor(o),la=o=>w.faceExpressionNet.predictExpressions(o),da=o=>w.ageGenderNet.predictAgeAndGender(o),pn=o=>w.ssdMobilenetv1.load(o),ha=o=>w.tinyFaceDetector.load(o),ba=o=>w.tinyYolov2.load(o),ga=o=>w.faceLandmark68Net.load(o),xa=o=>w.faceLandmark68TinyNet.load(o),va=o=>w.faceRecognitionNet.load(o),ya=o=>w.faceExpressionNet.load(o),_a=o=>w.ageGenderNet.load(o),Ta=pn,Pa=cn,wa=mn;var Ir=class extends J{constructor(e,r,n){super();this.parentTask=e;this.input=r;this.extractedFaces=n}},ae=class extends Ir{async run(){let t=await this.parentTask,e=await oe(t,this.input,async r=>Promise.all(r.map(n=>w.faceExpressionNet.predictExpressions(n))),this.extractedFaces);return t.map((r,n)=>xr(r,e[n]))}withAgeAndGender(){return new ie(this,this.input)}},se=class extends Ir{async run(){let t=await this.parentTask;if(!t)return;let e=await Ce(t,this.input,r=>w.faceExpressionNet.predictExpressions(r),this.extractedFaces);return xr(t,e)}withAgeAndGender(){return new ce(this,this.input)}},Wt=class extends ae{withAgeAndGender(){return new Bt(this,this.input)}withFaceDescriptors(){return new wt(this,this.input)}},kt=class extends se{withAgeAndGender(){return new Rt(this,this.input)}withFaceDescriptor(){return new Ft(this,this.input)}};var Nr=class extends J{constructor(e,r,n){super();this.parentTask=e;this.input=r;this.extractedFaces=n}},ie=class extends Nr{async run(){let t=await this.parentTask,e=await oe(t,this.input,async r=>Promise.all(r.map(n=>w.ageGenderNet.predictAgeAndGender(n))),this.extractedFaces);return t.map((r,n)=>{let{age:a,gender:s,genderProbability:i}=e[n];return Er(Mr(r,s,i),a)})}withFaceExpressions(){return new ae(this,this.input)}},ce=class extends Nr{async run(){let t=await this.parentTask;if(!t)return;let{age:e,gender:r,genderProbability:n}=await Ce(t,this.input,a=>w.ageGenderNet.predictAgeAndGender(a),this.extractedFaces);return Er(Mr(t,r,n),e)}withFaceExpressions(){return new se(this,this.input)}},Bt=class extends ie{withFaceExpressions(){return new Wt(this,this.input)}withFaceDescriptors(){return new wt(this,this.input)}},Rt=class extends ce{withFaceExpressions(){return new kt(this,this.input)}withFaceDescriptor(){return new Ft(this,this.input)}};var Ue=class extends J{constructor(e,r){super();this.parentTask=e;this.input=r}},wt=class extends Ue{async run(){let t=await this.parentTask;return(await oe(t,this.input,r=>Promise.all(r.map(n=>w.faceRecognitionNet.computeFaceDescriptor(n))),null,r=>r.landmarks.align(null,{useDlibAlignment:!0}))).map((r,n)=>Dr(t[n],r))}withFaceExpressions(){return new Wt(this,this.input)}withAgeAndGender(){return new Bt(this,this.input)}},Ft=class extends Ue{async run(){let t=await this.parentTask;if(!t)return;let e=await Ce(t,this.input,r=>w.faceRecognitionNet.computeFaceDescriptor(r),null,r=>r.landmarks.align(null,{useDlibAlignment:!0}));return Dr(t,e)}withFaceExpressions(){return new kt(this,this.input)}withAgeAndGender(){return new Rt(this,this.input)}};var Je=class extends J{constructor(e,r,n){super();this.parentTask=e;this.input=r;this.useTinyLandmarkNet=n}get landmarkNet(){return this.useTinyLandmarkNet?w.faceLandmark68TinyNet:w.faceLandmark68Net}},qe=class extends Je{async run(){let t=await this.parentTask,e=t.map(s=>s.detection),r=this.input instanceof Xe.Tensor?await de(this.input,e):await le(this.input,e),n=await Promise.all(r.map(s=>this.landmarkNet.detectLandmarks(s)));return r.forEach(s=>s instanceof Xe.Tensor&&s.dispose()),t.filter((s,i)=>n[i]).map((s,i)=>we(s,n[i]))}withFaceExpressions(){return new Wt(this,this.input)}withAgeAndGender(){return new Bt(this,this.input)}withFaceDescriptors(){return new wt(this,this.input)}},Ze=class extends Je{async run(){let t=await this.parentTask;if(!t)return;let{detection:e}=t,r=this.input instanceof Xe.Tensor?await de(this.input,[e]):await le(this.input,[e]),n=await this.landmarkNet.detectLandmarks(r[0]);return r.forEach(a=>a instanceof Xe.Tensor&&a.dispose()),we(t,n)}withFaceExpressions(){return new kt(this,this.input)}withAgeAndGender(){return new Rt(this,this.input)}withFaceDescriptor(){return new Ft(this,this.input)}};var Ke=class extends J{constructor(e,r=new X){super();this.input=e;this.options=r}},Ie=class extends Ke{async run(){let{input:t,options:e}=this,r;if(e instanceof je)r=w.tinyFaceDetector.locateFaces(t,e);else if(e instanceof X)r=w.ssdMobilenetv1.locateFaces(t,e);else if(e instanceof st)r=w.tinyYolov2.locateFaces(t,e);else throw new Error("detectFaces - expected options to be instance of TinyFaceDetectorOptions | SsdMobilenetv1Options | TinyYolov2Options");return r}runAndExtendWithFaceDetections(){return new Promise((t,e)=>{this.run().then(r=>t(r.map(n=>jt({},n)))).catch(r=>e(r))})}withFaceLandmarks(t=!1){return new qe(this.runAndExtendWithFaceDetections(),this.input,t)}withFaceExpressions(){return new ae(this.runAndExtendWithFaceDetections(),this.input)}withAgeAndGender(){return new ie(this.runAndExtendWithFaceDetections(),this.input)}},Qe=class extends Ke{async run(){let t=await new Ie(this.input,this.options),e=t[0];return t.forEach(r=>{r.score>e.score&&(e=r)}),e}runAndExtendWithFaceDetection(){return new Promise(async t=>{let e=await this.run();t(e?jt({},e):void 0)})}withFaceLandmarks(t=!1){return new Ze(this.runAndExtendWithFaceDetection(),this.input,t)}withFaceExpressions(){return new se(this.runAndExtendWithFaceDetection(),this.input)}withAgeAndGender(){return new ce(this.runAndExtendWithFaceDetection(),this.input)}};function Fa(o,t=new X){return new Qe(o,t)}function Sr(o,t=new X){return new Ie(o,t)}async function un(o,t){return Sr(o,new X(t?{minConfidence:t}:{})).withFaceLandmarks().withFaceDescriptors()}async function Da(o,t={}){return Sr(o,new st(t)).withFaceLandmarks().withFaceDescriptors()}var Ea=un;function go(o,t){if(o.length!==t.length)throw new Error("euclideanDistance: arr1.length !== arr2.length");let e=Array.from(o),r=Array.from(t);return Math.sqrt(e.map((n,a)=>n-r[a]).reduce((n,a)=>n+a**2,0))}var tr=class{constructor(t,e=.6){this._distanceThreshold=e;let r=Array.isArray(t)?t:[t];if(!r.length)throw new Error("FaceRecognizer.constructor - expected atleast one input");let n=1,a=()=>`person ${n++}`;this._labeledDescriptors=r.map(s=>{if(s instanceof mt)return s;if(s instanceof Float32Array)return new mt(a(),[s]);if(s.descriptor&&s.descriptor instanceof Float32Array)return new mt(a(),[s.descriptor]);throw new Error("FaceRecognizer.constructor - expected inputs to be of type LabeledFaceDescriptors | WithFaceDescriptor | Float32Array | Array | Float32Array>")})}get labeledDescriptors(){return this._labeledDescriptors}get distanceThreshold(){return this._distanceThreshold}computeMeanDistance(t,e){return e.map(r=>go(r,t)).reduce((r,n)=>r+n,0)/(e.length||1)}matchDescriptor(t){return this.labeledDescriptors.map(({descriptors:e,label:r})=>new pe(r,this.computeMeanDistance(t,e))).reduce((e,r)=>e.distancet.toJSON())}}static fromJSON(t){let e=t.labeledDescriptors.map(r=>mt.fromJSON(r));return new tr(e,t.distanceThreshold)}};function Ma(o){let t=new ne;return t.extractWeights(o),t}function fn(o,t){let{width:e,height:r}=new k(t.width,t.height);if(e<=0||r<=0)throw new Error(`resizeResults - invalid dimensions: ${JSON.stringify({width:e,height:r})}`);if(Array.isArray(o))return o.map(n=>fn(n,{width:e,height:r}));if(Zt(o)){let n=o.detection.forSize(e,r),a=o.unshiftedLandmarks.forSize(n.box.width,n.box.height);return we(jt(o,n),a)}return pt(o)?jt(o,o.detection.forSize(e,r)):o instanceof z||o instanceof M?o.forSize(e,r):o}var Ia=No;0&&(module.exports={AgeGenderNet,BoundingBox,Box,ComposableTask,ComputeAllFaceDescriptorsTask,ComputeFaceDescriptorsTaskBase,ComputeSingleFaceDescriptorTask,DetectAllFaceLandmarksTask,DetectAllFacesTask,DetectFaceLandmarksTaskBase,DetectFacesTaskBase,DetectSingleFaceLandmarksTask,DetectSingleFaceTask,Dimensions,FACE_EXPRESSION_LABELS,FaceDetection,FaceDetectionNet,FaceExpressionNet,FaceExpressions,FaceLandmark68Net,FaceLandmark68TinyNet,FaceLandmarkNet,FaceLandmarks,FaceLandmarks5,FaceLandmarks68,FaceMatch,FaceMatcher,FaceRecognitionNet,Gender,LabeledBox,LabeledFaceDescriptors,NetInput,NeuralNetwork,ObjectDetection,Point,PredictedBox,Rect,SsdMobilenetv1,SsdMobilenetv1Options,TinyFaceDetector,TinyFaceDetectorOptions,TinyYolov2,TinyYolov2Options,allFaces,allFacesSsdMobilenetv1,allFacesTinyYolov2,awaitMediaLoaded,bufferToImage,computeFaceDescriptor,createCanvas,createCanvasFromMedia,createFaceDetectionNet,createFaceRecognitionNet,createSsdMobilenetv1,createTinyFaceDetector,createTinyYolov2,detectAllFaces,detectFaceLandmarks,detectFaceLandmarksTiny,detectLandmarks,detectSingleFace,draw,env,euclideanDistance,extendWithAge,extendWithFaceDescriptor,extendWithFaceDetection,extendWithFaceExpressions,extendWithFaceLandmarks,extendWithGender,extractFaceTensors,extractFaces,fetchImage,fetchJson,fetchNetWeights,fetchOrThrow,fetchVideo,getContext2dOrThrow,getMediaDimensions,imageTensorToCanvas,imageToSquare,inverseSigmoid,iou,isMediaElement,isMediaLoaded,isWithAge,isWithFaceDetection,isWithFaceExpressions,isWithFaceLandmarks,isWithGender,loadAgeGenderModel,loadFaceDetectionModel,loadFaceExpressionModel,loadFaceLandmarkModel,loadFaceLandmarkTinyModel,loadFaceRecognitionModel,loadSsdMobilenetv1Model,loadTinyFaceDetectorModel,loadTinyYolov2Model,loadWeightMap,locateFaces,matchDimensions,minBbox,nets,nonMaxSuppression,normalize,padToSquare,predictAgeAndGender,recognizeFaceExpressions,resizeResults,resolveInput,shuffleArray,sigmoid,ssdMobilenetv1,tf,tinyFaceDetector,tinyYolov2,toNetInput,utils,validateConfig,version}); diff --git a/typedoc/classes/AgeGenderNet.html b/typedoc/classes/AgeGenderNet.html index f386b7d..b7ed703 100644 --- a/typedoc/classes/AgeGenderNet.html +++ b/typedoc/classes/AgeGenderNet.html @@ -1,16 +1,16 @@ -AgeGenderNet | @vladmandic/face-api - v1.7.1
+AgeGenderNet | @vladmandic/face-api - v1.7.2
+
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class AgeGenderNet

    @@ -394,7 +394,7 @@

    Modules

    diff --git a/typedoc/classes/BoundingBox.html b/typedoc/classes/BoundingBox.html index 05d25a7..5bd5200 100644 --- a/typedoc/classes/BoundingBox.html +++ b/typedoc/classes/BoundingBox.html @@ -1,16 +1,16 @@ -BoundingBox | @vladmandic/face-api - v1.7.1
    +BoundingBox | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class BoundingBox

    @@ -401,7 +401,7 @@

    Modules

    diff --git a/typedoc/classes/Box.html b/typedoc/classes/Box.html index 3141002..e5c2f21 100644 --- a/typedoc/classes/Box.html +++ b/typedoc/classes/Box.html @@ -1,16 +1,16 @@ -Box | @vladmandic/face-api - v1.7.1
    +Box | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class Box<BoxType>

    @@ -387,7 +387,7 @@

    Modules

    diff --git a/typedoc/classes/ComposableTask.html b/typedoc/classes/ComposableTask.html index 66a4fca..8c7e73b 100644 --- a/typedoc/classes/ComposableTask.html +++ b/typedoc/classes/ComposableTask.html @@ -1,16 +1,16 @@ -ComposableTask | @vladmandic/face-api - v1.7.1
    +ComposableTask | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class ComposableTask<T>

    @@ -105,7 +105,7 @@

    Modules

    diff --git a/typedoc/classes/ComputeAllFaceDescriptorsTask.html b/typedoc/classes/ComputeAllFaceDescriptorsTask.html index 9fcbc84..333a34b 100644 --- a/typedoc/classes/ComputeAllFaceDescriptorsTask.html +++ b/typedoc/classes/ComputeAllFaceDescriptorsTask.html @@ -1,16 +1,16 @@ -ComputeAllFaceDescriptorsTask | @vladmandic/face-api - v1.7.1
    +ComputeAllFaceDescriptorsTask | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class ComputeAllFaceDescriptorsTask<TSource>

    @@ -133,7 +133,7 @@

    Modules

    diff --git a/typedoc/classes/ComputeFaceDescriptorsTaskBase.html b/typedoc/classes/ComputeFaceDescriptorsTaskBase.html index ea090e0..903a663 100644 --- a/typedoc/classes/ComputeFaceDescriptorsTaskBase.html +++ b/typedoc/classes/ComputeFaceDescriptorsTaskBase.html @@ -1,16 +1,16 @@ -ComputeFaceDescriptorsTaskBase | @vladmandic/face-api - v1.7.1
    +ComputeFaceDescriptorsTaskBase | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class ComputeFaceDescriptorsTaskBase<TReturn, TParentReturn>

    @@ -122,7 +122,7 @@

    Modules

    diff --git a/typedoc/classes/ComputeSingleFaceDescriptorTask.html b/typedoc/classes/ComputeSingleFaceDescriptorTask.html index 832fcf7..69a6b1d 100644 --- a/typedoc/classes/ComputeSingleFaceDescriptorTask.html +++ b/typedoc/classes/ComputeSingleFaceDescriptorTask.html @@ -1,16 +1,16 @@ -ComputeSingleFaceDescriptorTask | @vladmandic/face-api - v1.7.1
    +ComputeSingleFaceDescriptorTask | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class ComputeSingleFaceDescriptorTask<TSource>

    @@ -133,7 +133,7 @@

    Modules

    diff --git a/typedoc/classes/DetectAllFaceLandmarksTask.html b/typedoc/classes/DetectAllFaceLandmarksTask.html index 38bc970..a12008a 100644 --- a/typedoc/classes/DetectAllFaceLandmarksTask.html +++ b/typedoc/classes/DetectAllFaceLandmarksTask.html @@ -1,16 +1,16 @@ -DetectAllFaceLandmarksTask | @vladmandic/face-api - v1.7.1
    +DetectAllFaceLandmarksTask | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class DetectAllFaceLandmarksTask<TSource>

    @@ -144,7 +144,7 @@

    Modules

    diff --git a/typedoc/classes/DetectAllFacesTask.html b/typedoc/classes/DetectAllFacesTask.html index a01d510..216a2f1 100644 --- a/typedoc/classes/DetectAllFacesTask.html +++ b/typedoc/classes/DetectAllFacesTask.html @@ -1,16 +1,16 @@ -DetectAllFacesTask | @vladmandic/face-api - v1.7.1
    +DetectAllFacesTask | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class DetectAllFacesTask

    @@ -137,7 +137,7 @@

    Modules

    diff --git a/typedoc/classes/DetectFaceLandmarksTaskBase.html b/typedoc/classes/DetectFaceLandmarksTaskBase.html index fec6ec0..24bcc25 100644 --- a/typedoc/classes/DetectFaceLandmarksTaskBase.html +++ b/typedoc/classes/DetectFaceLandmarksTaskBase.html @@ -1,16 +1,16 @@ -DetectFaceLandmarksTaskBase | @vladmandic/face-api - v1.7.1
    +DetectFaceLandmarksTaskBase | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class DetectFaceLandmarksTaskBase<TReturn, TParentReturn>

    @@ -124,7 +124,7 @@

    Modules

    diff --git a/typedoc/classes/DetectFacesTaskBase.html b/typedoc/classes/DetectFacesTaskBase.html index 5d13956..2040af4 100644 --- a/typedoc/classes/DetectFacesTaskBase.html +++ b/typedoc/classes/DetectFacesTaskBase.html @@ -1,16 +1,16 @@ -DetectFacesTaskBase | @vladmandic/face-api - v1.7.1
    +DetectFacesTaskBase | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class DetectFacesTaskBase<TReturn>

    @@ -118,7 +118,7 @@

    Modules

    diff --git a/typedoc/classes/DetectSingleFaceLandmarksTask.html b/typedoc/classes/DetectSingleFaceLandmarksTask.html index 18ef30e..a0396c4 100644 --- a/typedoc/classes/DetectSingleFaceLandmarksTask.html +++ b/typedoc/classes/DetectSingleFaceLandmarksTask.html @@ -1,16 +1,16 @@ -DetectSingleFaceLandmarksTask | @vladmandic/face-api - v1.7.1
    +DetectSingleFaceLandmarksTask | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class DetectSingleFaceLandmarksTask<TSource>

    @@ -144,7 +144,7 @@

    Modules

    diff --git a/typedoc/classes/DetectSingleFaceTask.html b/typedoc/classes/DetectSingleFaceTask.html index 9b3ea1e..f6be378 100644 --- a/typedoc/classes/DetectSingleFaceTask.html +++ b/typedoc/classes/DetectSingleFaceTask.html @@ -1,16 +1,16 @@ -DetectSingleFaceTask | @vladmandic/face-api - v1.7.1
    +DetectSingleFaceTask | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class DetectSingleFaceTask

    @@ -137,7 +137,7 @@

    Modules

    diff --git a/typedoc/classes/Dimensions.html b/typedoc/classes/Dimensions.html index d035bda..536d599 100644 --- a/typedoc/classes/Dimensions.html +++ b/typedoc/classes/Dimensions.html @@ -1,16 +1,16 @@ -Dimensions | @vladmandic/face-api - v1.7.1
    +Dimensions | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class Dimensions

    @@ -104,7 +104,7 @@

    Modules

    diff --git a/typedoc/classes/FaceDetection.html b/typedoc/classes/FaceDetection.html index b30fd03..c207389 100644 --- a/typedoc/classes/FaceDetection.html +++ b/typedoc/classes/FaceDetection.html @@ -1,16 +1,16 @@ -FaceDetection | @vladmandic/face-api - v1.7.1
    +FaceDetection | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class FaceDetection

    @@ -179,7 +179,7 @@

    Modules

    diff --git a/typedoc/classes/FaceDetectionNet.html b/typedoc/classes/FaceDetectionNet.html index 0e0c97d..06af33b 100644 --- a/typedoc/classes/FaceDetectionNet.html +++ b/typedoc/classes/FaceDetectionNet.html @@ -1,16 +1,16 @@ -FaceDetectionNet | @vladmandic/face-api - v1.7.1
    +FaceDetectionNet | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class FaceDetectionNet

    @@ -338,7 +338,7 @@

    Modules

    diff --git a/typedoc/classes/FaceExpressionNet.html b/typedoc/classes/FaceExpressionNet.html index f7c5eaf..be0026b 100644 --- a/typedoc/classes/FaceExpressionNet.html +++ b/typedoc/classes/FaceExpressionNet.html @@ -1,16 +1,16 @@ -FaceExpressionNet | @vladmandic/face-api - v1.7.1
    +FaceExpressionNet | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class FaceExpressionNet

    @@ -398,7 +398,7 @@

    Modules

    diff --git a/typedoc/classes/FaceExpressions.html b/typedoc/classes/FaceExpressions.html index ba642b9..9aa1dd4 100644 --- a/typedoc/classes/FaceExpressions.html +++ b/typedoc/classes/FaceExpressions.html @@ -1,16 +1,16 @@ -FaceExpressions | @vladmandic/face-api - v1.7.1
    +FaceExpressions | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class FaceExpressions

    @@ -120,7 +120,7 @@

    Modules

    diff --git a/typedoc/classes/FaceLandmark68Net.html b/typedoc/classes/FaceLandmark68Net.html index 842d831..2b20146 100644 --- a/typedoc/classes/FaceLandmark68Net.html +++ b/typedoc/classes/FaceLandmark68Net.html @@ -1,16 +1,16 @@ -FaceLandmark68Net | @vladmandic/face-api - v1.7.1
    +FaceLandmark68Net | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class FaceLandmark68Net

    @@ -422,7 +422,7 @@

    Modules

    diff --git a/typedoc/classes/FaceLandmark68TinyNet.html b/typedoc/classes/FaceLandmark68TinyNet.html index c69459a..c9fd8e1 100644 --- a/typedoc/classes/FaceLandmark68TinyNet.html +++ b/typedoc/classes/FaceLandmark68TinyNet.html @@ -1,16 +1,16 @@ -FaceLandmark68TinyNet | @vladmandic/face-api - v1.7.1
    +FaceLandmark68TinyNet | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class FaceLandmark68TinyNet

    @@ -420,7 +420,7 @@

    Modules

    diff --git a/typedoc/classes/FaceLandmarkNet.html b/typedoc/classes/FaceLandmarkNet.html index 98f2b0f..e358857 100644 --- a/typedoc/classes/FaceLandmarkNet.html +++ b/typedoc/classes/FaceLandmarkNet.html @@ -1,16 +1,16 @@ -FaceLandmarkNet | @vladmandic/face-api - v1.7.1
    +FaceLandmarkNet | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class FaceLandmarkNet

    @@ -420,7 +420,7 @@

    Modules

    diff --git a/typedoc/classes/FaceLandmarks.html b/typedoc/classes/FaceLandmarks.html index 74e740a..58a4293 100644 --- a/typedoc/classes/FaceLandmarks.html +++ b/typedoc/classes/FaceLandmarks.html @@ -1,16 +1,16 @@ -FaceLandmarks | @vladmandic/face-api - v1.7.1
    +FaceLandmarks | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class FaceLandmarks

    @@ -220,7 +220,7 @@ it's current shift.

    Modules

    diff --git a/typedoc/classes/FaceLandmarks5.html b/typedoc/classes/FaceLandmarks5.html index 5dd21e5..8f310d0 100644 --- a/typedoc/classes/FaceLandmarks5.html +++ b/typedoc/classes/FaceLandmarks5.html @@ -1,16 +1,16 @@ -FaceLandmarks5 | @vladmandic/face-api - v1.7.1
    +FaceLandmarks5 | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class FaceLandmarks5

    @@ -223,7 +223,7 @@ it's current shift.

    Modules

    diff --git a/typedoc/classes/FaceLandmarks68.html b/typedoc/classes/FaceLandmarks68.html index bb52031..7fd1e19 100644 --- a/typedoc/classes/FaceLandmarks68.html +++ b/typedoc/classes/FaceLandmarks68.html @@ -1,16 +1,16 @@ -FaceLandmarks68 | @vladmandic/face-api - v1.7.1
    +FaceLandmarks68 | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class FaceLandmarks68

    @@ -286,7 +286,7 @@ it's current shift.

    Modules

    diff --git a/typedoc/classes/FaceMatch.html b/typedoc/classes/FaceMatch.html index b73e7aa..7703532 100644 --- a/typedoc/classes/FaceMatch.html +++ b/typedoc/classes/FaceMatch.html @@ -1,16 +1,16 @@ -FaceMatch | @vladmandic/face-api - v1.7.1
    +FaceMatch | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class FaceMatch

    @@ -109,7 +109,7 @@

    Modules

    diff --git a/typedoc/classes/FaceMatcher.html b/typedoc/classes/FaceMatcher.html index 84ec202..6013d72 100644 --- a/typedoc/classes/FaceMatcher.html +++ b/typedoc/classes/FaceMatcher.html @@ -1,16 +1,16 @@ -FaceMatcher | @vladmandic/face-api - v1.7.1
    +FaceMatcher | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class FaceMatcher

    @@ -156,7 +156,7 @@

    Modules

    diff --git a/typedoc/classes/FaceRecognitionNet.html b/typedoc/classes/FaceRecognitionNet.html index d1e533f..1bfcf58 100644 --- a/typedoc/classes/FaceRecognitionNet.html +++ b/typedoc/classes/FaceRecognitionNet.html @@ -1,16 +1,16 @@ -FaceRecognitionNet | @vladmandic/face-api - v1.7.1
    +FaceRecognitionNet | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class FaceRecognitionNet

    @@ -333,7 +333,7 @@

    Modules

    diff --git a/typedoc/classes/LabeledBox.html b/typedoc/classes/LabeledBox.html index e0e287f..2ae2e9a 100644 --- a/typedoc/classes/LabeledBox.html +++ b/typedoc/classes/LabeledBox.html @@ -1,16 +1,16 @@ -LabeledBox | @vladmandic/face-api - v1.7.1
    +LabeledBox | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class LabeledBox

    @@ -414,7 +414,7 @@

    Modules

    diff --git a/typedoc/classes/LabeledFaceDescriptors.html b/typedoc/classes/LabeledFaceDescriptors.html index fc04e31..afc6cc5 100644 --- a/typedoc/classes/LabeledFaceDescriptors.html +++ b/typedoc/classes/LabeledFaceDescriptors.html @@ -1,16 +1,16 @@ -LabeledFaceDescriptors | @vladmandic/face-api - v1.7.1
    +LabeledFaceDescriptors | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class LabeledFaceDescriptors

    @@ -112,7 +112,7 @@

    Modules

    diff --git a/typedoc/classes/NetInput.html b/typedoc/classes/NetInput.html index 2a333af..5cc9b66 100644 --- a/typedoc/classes/NetInput.html +++ b/typedoc/classes/NetInput.html @@ -1,16 +1,16 @@ -NetInput | @vladmandic/face-api - v1.7.1
    +NetInput | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class NetInput

    @@ -227,7 +227,7 @@ with size [batchSize, inputSize, inputSize, 3].

    Modules

    diff --git a/typedoc/classes/NeuralNetwork.html b/typedoc/classes/NeuralNetwork.html index add336e..78ca5fe 100644 --- a/typedoc/classes/NeuralNetwork.html +++ b/typedoc/classes/NeuralNetwork.html @@ -1,16 +1,16 @@ -NeuralNetwork | @vladmandic/face-api - v1.7.1
    +NeuralNetwork | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class NeuralNetwork<TNetParams>Abstract

    @@ -289,7 +289,7 @@

    Modules

    diff --git a/typedoc/classes/ObjectDetection.html b/typedoc/classes/ObjectDetection.html index ff756d9..ff179ea 100644 --- a/typedoc/classes/ObjectDetection.html +++ b/typedoc/classes/ObjectDetection.html @@ -1,16 +1,16 @@ -ObjectDetection | @vladmandic/face-api - v1.7.1
    +ObjectDetection | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class ObjectDetection

    @@ -167,7 +167,7 @@

    Modules

    diff --git a/typedoc/classes/Point.html b/typedoc/classes/Point.html index 2092191..c56b609 100644 --- a/typedoc/classes/Point.html +++ b/typedoc/classes/Point.html @@ -1,16 +1,16 @@ -Point | @vladmandic/face-api - v1.7.1
    +Point | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class Point

    @@ -178,7 +178,7 @@

    Modules

    diff --git a/typedoc/classes/PredictedBox.html b/typedoc/classes/PredictedBox.html index 56c5d25..b86c7d4 100644 --- a/typedoc/classes/PredictedBox.html +++ b/typedoc/classes/PredictedBox.html @@ -1,16 +1,16 @@ -PredictedBox | @vladmandic/face-api - v1.7.1
    +PredictedBox | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class PredictedBox

    @@ -452,7 +452,7 @@

    Modules

    diff --git a/typedoc/classes/Rect.html b/typedoc/classes/Rect.html index 085b98d..26ca957 100644 --- a/typedoc/classes/Rect.html +++ b/typedoc/classes/Rect.html @@ -1,16 +1,16 @@ -Rect | @vladmandic/face-api - v1.7.1
    +Rect | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class Rect

    @@ -401,7 +401,7 @@

    Modules

    diff --git a/typedoc/classes/SsdMobilenetv1.html b/typedoc/classes/SsdMobilenetv1.html index f8c30fc..3f3db13 100644 --- a/typedoc/classes/SsdMobilenetv1.html +++ b/typedoc/classes/SsdMobilenetv1.html @@ -1,16 +1,16 @@ -SsdMobilenetv1 | @vladmandic/face-api - v1.7.1
    +SsdMobilenetv1 | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class SsdMobilenetv1

    @@ -337,7 +337,7 @@

    Modules

    diff --git a/typedoc/classes/SsdMobilenetv1Options.html b/typedoc/classes/SsdMobilenetv1Options.html index 1896063..39a1883 100644 --- a/typedoc/classes/SsdMobilenetv1Options.html +++ b/typedoc/classes/SsdMobilenetv1Options.html @@ -1,16 +1,16 @@ -SsdMobilenetv1Options | @vladmandic/face-api - v1.7.1
    +SsdMobilenetv1Options | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class SsdMobilenetv1Options

    @@ -82,7 +82,7 @@

    Modules

    diff --git a/typedoc/classes/TinyFaceDetector.html b/typedoc/classes/TinyFaceDetector.html index 039b481..498d012 100644 --- a/typedoc/classes/TinyFaceDetector.html +++ b/typedoc/classes/TinyFaceDetector.html @@ -1,16 +1,16 @@ -TinyFaceDetector | @vladmandic/face-api - v1.7.1
    +TinyFaceDetector | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class TinyFaceDetector

    @@ -438,7 +438,7 @@

    Modules

    diff --git a/typedoc/classes/TinyFaceDetectorOptions.html b/typedoc/classes/TinyFaceDetectorOptions.html index 6bba5db..a8abc9d 100644 --- a/typedoc/classes/TinyFaceDetectorOptions.html +++ b/typedoc/classes/TinyFaceDetectorOptions.html @@ -1,16 +1,16 @@ -TinyFaceDetectorOptions | @vladmandic/face-api - v1.7.1
    +TinyFaceDetectorOptions | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class TinyFaceDetectorOptions

    @@ -87,7 +87,7 @@

    Modules

    diff --git a/typedoc/classes/TinyYolov2.html b/typedoc/classes/TinyYolov2.html index 4573140..a0243fb 100644 --- a/typedoc/classes/TinyYolov2.html +++ b/typedoc/classes/TinyYolov2.html @@ -1,16 +1,16 @@ -TinyYolov2 | @vladmandic/face-api - v1.7.1
    +TinyYolov2 | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class TinyYolov2

    @@ -452,7 +452,7 @@

    Modules

    diff --git a/typedoc/classes/TinyYolov2Options.html b/typedoc/classes/TinyYolov2Options.html index 1a993e1..8f479d4 100644 --- a/typedoc/classes/TinyYolov2Options.html +++ b/typedoc/classes/TinyYolov2Options.html @@ -1,16 +1,16 @@ -TinyYolov2Options | @vladmandic/face-api - v1.7.1
    +TinyYolov2Options | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class TinyYolov2Options

    @@ -84,7 +84,7 @@

    Modules

    diff --git a/typedoc/classes/draw.DrawBox.html b/typedoc/classes/draw.DrawBox.html index b8a3649..da7a3f1 100644 --- a/typedoc/classes/draw.DrawBox.html +++ b/typedoc/classes/draw.DrawBox.html @@ -1,16 +1,16 @@ -DrawBox | @vladmandic/face-api - v1.7.1
    +DrawBox | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class DrawBox

    @@ -98,7 +98,7 @@

    Modules

    diff --git a/typedoc/classes/draw.DrawBoxOptions.html b/typedoc/classes/draw.DrawBoxOptions.html index b8fd93b..61f386a 100644 --- a/typedoc/classes/draw.DrawBoxOptions.html +++ b/typedoc/classes/draw.DrawBoxOptions.html @@ -1,16 +1,16 @@ -DrawBoxOptions | @vladmandic/face-api - v1.7.1
    +DrawBoxOptions | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class DrawBoxOptions

    @@ -89,7 +89,7 @@

    Modules

    diff --git a/typedoc/classes/draw.DrawFaceLandmarks.html b/typedoc/classes/draw.DrawFaceLandmarks.html index b178ce0..6731595 100644 --- a/typedoc/classes/draw.DrawFaceLandmarks.html +++ b/typedoc/classes/draw.DrawFaceLandmarks.html @@ -1,16 +1,16 @@ -DrawFaceLandmarks | @vladmandic/face-api - v1.7.1
    +DrawFaceLandmarks | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class DrawFaceLandmarks

    @@ -98,7 +98,7 @@

    Modules

    diff --git a/typedoc/classes/draw.DrawFaceLandmarksOptions.html b/typedoc/classes/draw.DrawFaceLandmarksOptions.html index bcd76c4..8a74fb4 100644 --- a/typedoc/classes/draw.DrawFaceLandmarksOptions.html +++ b/typedoc/classes/draw.DrawFaceLandmarksOptions.html @@ -1,16 +1,16 @@ -DrawFaceLandmarksOptions | @vladmandic/face-api - v1.7.1
    +DrawFaceLandmarksOptions | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class DrawFaceLandmarksOptions

    @@ -101,7 +101,7 @@

    Modules

    diff --git a/typedoc/classes/draw.DrawTextField.html b/typedoc/classes/draw.DrawTextField.html index 1743b69..6a3b50f 100644 --- a/typedoc/classes/draw.DrawTextField.html +++ b/typedoc/classes/draw.DrawTextField.html @@ -1,16 +1,16 @@ -DrawTextField | @vladmandic/face-api - v1.7.1
    +DrawTextField | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class DrawTextField

    @@ -145,7 +145,7 @@

    Modules

    diff --git a/typedoc/classes/draw.DrawTextFieldOptions.html b/typedoc/classes/draw.DrawTextFieldOptions.html index 3f7c1cc..c2e9a61 100644 --- a/typedoc/classes/draw.DrawTextFieldOptions.html +++ b/typedoc/classes/draw.DrawTextFieldOptions.html @@ -1,16 +1,16 @@ -DrawTextFieldOptions | @vladmandic/face-api - v1.7.1
    +DrawTextFieldOptions | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Class DrawTextFieldOptions

    @@ -111,7 +111,7 @@

    Modules

    diff --git a/typedoc/enums/Gender.html b/typedoc/enums/Gender.html index a238d75..8be80f3 100644 --- a/typedoc/enums/Gender.html +++ b/typedoc/enums/Gender.html @@ -1,16 +1,16 @@ -Gender | @vladmandic/face-api - v1.7.1
    +Gender | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Enumeration Gender

    Enumeration AnchorPosition

    Function allFaces

    @@ -43,7 +43,7 @@

    Modules

    diff --git a/typedoc/functions/allFacesSsdMobilenetv1.html b/typedoc/functions/allFacesSsdMobilenetv1.html index eed2995..a5ff0a9 100644 --- a/typedoc/functions/allFacesSsdMobilenetv1.html +++ b/typedoc/functions/allFacesSsdMobilenetv1.html @@ -1,16 +1,16 @@ -allFacesSsdMobilenetv1 | @vladmandic/face-api - v1.7.1
    +allFacesSsdMobilenetv1 | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function allFacesSsdMobilenetv1

    @@ -43,7 +43,7 @@

    Modules

    diff --git a/typedoc/functions/allFacesTinyYolov2.html b/typedoc/functions/allFacesTinyYolov2.html index 734fd77..b58568f 100644 --- a/typedoc/functions/allFacesTinyYolov2.html +++ b/typedoc/functions/allFacesTinyYolov2.html @@ -1,16 +1,16 @@ -allFacesTinyYolov2 | @vladmandic/face-api - v1.7.1
    +allFacesTinyYolov2 | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function allFacesTinyYolov2

    @@ -43,7 +43,7 @@

    Modules

    diff --git a/typedoc/functions/awaitMediaLoaded.html b/typedoc/functions/awaitMediaLoaded.html index ea30272..38d45ec 100644 --- a/typedoc/functions/awaitMediaLoaded.html +++ b/typedoc/functions/awaitMediaLoaded.html @@ -1,16 +1,16 @@ -awaitMediaLoaded | @vladmandic/face-api - v1.7.1
    +awaitMediaLoaded | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function awaitMediaLoaded

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/bufferToImage.html b/typedoc/functions/bufferToImage.html index 21fabe0..513400f 100644 --- a/typedoc/functions/bufferToImage.html +++ b/typedoc/functions/bufferToImage.html @@ -1,16 +1,16 @@ -bufferToImage | @vladmandic/face-api - v1.7.1
    +bufferToImage | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function bufferToImage

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/computeFaceDescriptor.html b/typedoc/functions/computeFaceDescriptor.html index 07481cd..cc25bfd 100644 --- a/typedoc/functions/computeFaceDescriptor.html +++ b/typedoc/functions/computeFaceDescriptor.html @@ -1,16 +1,16 @@ -computeFaceDescriptor | @vladmandic/face-api - v1.7.1
    +computeFaceDescriptor | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function computeFaceDescriptor

    @@ -48,7 +48,7 @@ face descriptors.

    Modules

    diff --git a/typedoc/functions/createCanvas.html b/typedoc/functions/createCanvas.html index 3e5c683..9029b30 100644 --- a/typedoc/functions/createCanvas.html +++ b/typedoc/functions/createCanvas.html @@ -1,16 +1,16 @@ -createCanvas | @vladmandic/face-api - v1.7.1
    +createCanvas | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function createCanvas

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/createCanvasFromMedia.html b/typedoc/functions/createCanvasFromMedia.html index 11a92b4..835cbe5 100644 --- a/typedoc/functions/createCanvasFromMedia.html +++ b/typedoc/functions/createCanvasFromMedia.html @@ -1,16 +1,16 @@ -createCanvasFromMedia | @vladmandic/face-api - v1.7.1
    +createCanvasFromMedia | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function createCanvasFromMedia

    @@ -43,7 +43,7 @@

    Modules

    diff --git a/typedoc/functions/createFaceDetectionNet.html b/typedoc/functions/createFaceDetectionNet.html index bbb3a23..1d17458 100644 --- a/typedoc/functions/createFaceDetectionNet.html +++ b/typedoc/functions/createFaceDetectionNet.html @@ -1,16 +1,16 @@ -createFaceDetectionNet | @vladmandic/face-api - v1.7.1
    +createFaceDetectionNet | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function createFaceDetectionNet

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/createFaceRecognitionNet.html b/typedoc/functions/createFaceRecognitionNet.html index 5df1944..65d140b 100644 --- a/typedoc/functions/createFaceRecognitionNet.html +++ b/typedoc/functions/createFaceRecognitionNet.html @@ -1,16 +1,16 @@ -createFaceRecognitionNet | @vladmandic/face-api - v1.7.1
    +createFaceRecognitionNet | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function createFaceRecognitionNet

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/createSsdMobilenetv1.html b/typedoc/functions/createSsdMobilenetv1.html index 6503840..be2cfe5 100644 --- a/typedoc/functions/createSsdMobilenetv1.html +++ b/typedoc/functions/createSsdMobilenetv1.html @@ -1,16 +1,16 @@ -createSsdMobilenetv1 | @vladmandic/face-api - v1.7.1
    +createSsdMobilenetv1 | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function createSsdMobilenetv1

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/createTinyFaceDetector.html b/typedoc/functions/createTinyFaceDetector.html index 31d5dfc..655ba14 100644 --- a/typedoc/functions/createTinyFaceDetector.html +++ b/typedoc/functions/createTinyFaceDetector.html @@ -1,16 +1,16 @@ -createTinyFaceDetector | @vladmandic/face-api - v1.7.1
    +createTinyFaceDetector | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function createTinyFaceDetector

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/createTinyYolov2.html b/typedoc/functions/createTinyYolov2.html index 7ba9ad1..a58537c 100644 --- a/typedoc/functions/createTinyYolov2.html +++ b/typedoc/functions/createTinyYolov2.html @@ -1,16 +1,16 @@ -createTinyYolov2 | @vladmandic/face-api - v1.7.1
    +createTinyYolov2 | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function createTinyYolov2

    @@ -43,7 +43,7 @@

    Modules

    diff --git a/typedoc/functions/detectAllFaces.html b/typedoc/functions/detectAllFaces.html index b0da57a..c52e97e 100644 --- a/typedoc/functions/detectAllFaces.html +++ b/typedoc/functions/detectAllFaces.html @@ -1,16 +1,16 @@ -detectAllFaces | @vladmandic/face-api - v1.7.1
    +detectAllFaces | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function detectAllFaces

    @@ -43,7 +43,7 @@

    Modules

    diff --git a/typedoc/functions/detectFaceLandmarks.html b/typedoc/functions/detectFaceLandmarks.html index 2674ee2..16b78c1 100644 --- a/typedoc/functions/detectFaceLandmarks.html +++ b/typedoc/functions/detectFaceLandmarks.html @@ -1,16 +1,16 @@ -detectFaceLandmarks | @vladmandic/face-api - v1.7.1
    +detectFaceLandmarks | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function detectFaceLandmarks

    @@ -45,7 +45,7 @@

    Modules

    diff --git a/typedoc/functions/detectFaceLandmarksTiny.html b/typedoc/functions/detectFaceLandmarksTiny.html index 49c3965..6516fe7 100644 --- a/typedoc/functions/detectFaceLandmarksTiny.html +++ b/typedoc/functions/detectFaceLandmarksTiny.html @@ -1,16 +1,16 @@ -detectFaceLandmarksTiny | @vladmandic/face-api - v1.7.1
    +detectFaceLandmarksTiny | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function detectFaceLandmarksTiny

    @@ -47,7 +47,7 @@ faster at inference, but also slightly less accurate.

    Modules

    diff --git a/typedoc/functions/detectLandmarks.html b/typedoc/functions/detectLandmarks.html index 8b3a7a4..2f91498 100644 --- a/typedoc/functions/detectLandmarks.html +++ b/typedoc/functions/detectLandmarks.html @@ -1,16 +1,16 @@ -detectLandmarks | @vladmandic/face-api - v1.7.1
    +detectLandmarks | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function detectLandmarks

    @@ -45,7 +45,7 @@

    Modules

    diff --git a/typedoc/functions/detectSingleFace.html b/typedoc/functions/detectSingleFace.html index 32601d5..47ac0fa 100644 --- a/typedoc/functions/detectSingleFace.html +++ b/typedoc/functions/detectSingleFace.html @@ -1,16 +1,16 @@ -detectSingleFace | @vladmandic/face-api - v1.7.1
    +detectSingleFace | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function detectSingleFace

    @@ -43,7 +43,7 @@

    Modules

    diff --git a/typedoc/functions/draw.drawContour.html b/typedoc/functions/draw.drawContour.html index 46aea94..2624693 100644 --- a/typedoc/functions/draw.drawContour.html +++ b/typedoc/functions/draw.drawContour.html @@ -1,16 +1,16 @@ -drawContour | @vladmandic/face-api - v1.7.1
    +drawContour | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function drawContour

    @@ -46,7 +46,7 @@

    Modules

    diff --git a/typedoc/functions/draw.drawDetections.html b/typedoc/functions/draw.drawDetections.html index efac342..bf67adf 100644 --- a/typedoc/functions/draw.drawDetections.html +++ b/typedoc/functions/draw.drawDetections.html @@ -1,16 +1,16 @@ -drawDetections | @vladmandic/face-api - v1.7.1
    +drawDetections | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function drawDetections

    @@ -44,7 +44,7 @@

    Modules

    diff --git a/typedoc/functions/draw.drawFaceExpressions.html b/typedoc/functions/draw.drawFaceExpressions.html index aa45cff..ff6d67d 100644 --- a/typedoc/functions/draw.drawFaceExpressions.html +++ b/typedoc/functions/draw.drawFaceExpressions.html @@ -1,16 +1,16 @@ -drawFaceExpressions | @vladmandic/face-api - v1.7.1
    +drawFaceExpressions | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function drawFaceExpressions

    @@ -48,7 +48,7 @@

    Modules

    diff --git a/typedoc/functions/draw.drawFaceLandmarks-1.html b/typedoc/functions/draw.drawFaceLandmarks-1.html index c2fef6f..00985ef 100644 --- a/typedoc/functions/draw.drawFaceLandmarks-1.html +++ b/typedoc/functions/draw.drawFaceLandmarks-1.html @@ -1,16 +1,16 @@ -drawFaceLandmarks | @vladmandic/face-api - v1.7.1
    +drawFaceLandmarks | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function drawFaceLandmarks

    @@ -44,7 +44,7 @@

    Modules

    diff --git a/typedoc/functions/euclideanDistance.html b/typedoc/functions/euclideanDistance.html index 11650da..809f3e6 100644 --- a/typedoc/functions/euclideanDistance.html +++ b/typedoc/functions/euclideanDistance.html @@ -1,16 +1,16 @@ -euclideanDistance | @vladmandic/face-api - v1.7.1
    +euclideanDistance | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function euclideanDistance

    @@ -43,7 +43,7 @@

    Modules

    diff --git a/typedoc/functions/extendWithAge.html b/typedoc/functions/extendWithAge.html index 0e15c97..fd8fb4f 100644 --- a/typedoc/functions/extendWithAge.html +++ b/typedoc/functions/extendWithAge.html @@ -1,16 +1,16 @@ -extendWithAge | @vladmandic/face-api - v1.7.1
    +extendWithAge | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function extendWithAge

    @@ -48,7 +48,7 @@

    Modules

    diff --git a/typedoc/functions/extendWithFaceDescriptor.html b/typedoc/functions/extendWithFaceDescriptor.html index 17b7a15..482af93 100644 --- a/typedoc/functions/extendWithFaceDescriptor.html +++ b/typedoc/functions/extendWithFaceDescriptor.html @@ -1,16 +1,16 @@ -extendWithFaceDescriptor | @vladmandic/face-api - v1.7.1
    +extendWithFaceDescriptor | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function extendWithFaceDescriptor

    @@ -48,7 +48,7 @@

    Modules

    diff --git a/typedoc/functions/extendWithFaceDetection.html b/typedoc/functions/extendWithFaceDetection.html index dbf8f35..884a0d2 100644 --- a/typedoc/functions/extendWithFaceDetection.html +++ b/typedoc/functions/extendWithFaceDetection.html @@ -1,16 +1,16 @@ -extendWithFaceDetection | @vladmandic/face-api - v1.7.1
    +extendWithFaceDetection | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function extendWithFaceDetection

    @@ -48,7 +48,7 @@

    Modules

    diff --git a/typedoc/functions/extendWithFaceExpressions.html b/typedoc/functions/extendWithFaceExpressions.html index 047290a..12bd7cf 100644 --- a/typedoc/functions/extendWithFaceExpressions.html +++ b/typedoc/functions/extendWithFaceExpressions.html @@ -1,16 +1,16 @@ -extendWithFaceExpressions | @vladmandic/face-api - v1.7.1
    +extendWithFaceExpressions | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function extendWithFaceExpressions

    @@ -48,7 +48,7 @@

    Modules

    diff --git a/typedoc/functions/extendWithFaceLandmarks.html b/typedoc/functions/extendWithFaceLandmarks.html index 154101a..cda2023 100644 --- a/typedoc/functions/extendWithFaceLandmarks.html +++ b/typedoc/functions/extendWithFaceLandmarks.html @@ -1,16 +1,16 @@ -extendWithFaceLandmarks | @vladmandic/face-api - v1.7.1
    +extendWithFaceLandmarks | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function extendWithFaceLandmarks

    @@ -50,7 +50,7 @@

    Modules

    diff --git a/typedoc/functions/extendWithGender.html b/typedoc/functions/extendWithGender.html index 67df00f..8588aff 100644 --- a/typedoc/functions/extendWithGender.html +++ b/typedoc/functions/extendWithGender.html @@ -1,16 +1,16 @@ -extendWithGender | @vladmandic/face-api - v1.7.1
    +extendWithGender | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function extendWithGender

    @@ -50,7 +50,7 @@

    Modules

    diff --git a/typedoc/functions/extractFaceTensors.html b/typedoc/functions/extractFaceTensors.html index 4fb4611..fbfa2c8 100644 --- a/typedoc/functions/extractFaceTensors.html +++ b/typedoc/functions/extractFaceTensors.html @@ -1,16 +1,16 @@ -extractFaceTensors | @vladmandic/face-api - v1.7.1
    +extractFaceTensors | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function extractFaceTensors

    @@ -54,7 +54,7 @@ converting them to tensors individually.

    Modules

    diff --git a/typedoc/functions/extractFaces.html b/typedoc/functions/extractFaces.html index 36851cb..445db0b 100644 --- a/typedoc/functions/extractFaces.html +++ b/typedoc/functions/extractFaces.html @@ -1,16 +1,16 @@ -extractFaces | @vladmandic/face-api - v1.7.1
    +extractFaces | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function extractFaces

    @@ -51,7 +51,7 @@

    Modules

    diff --git a/typedoc/functions/fetchImage.html b/typedoc/functions/fetchImage.html index 4d5e34b..a20e1e9 100644 --- a/typedoc/functions/fetchImage.html +++ b/typedoc/functions/fetchImage.html @@ -1,16 +1,16 @@ -fetchImage | @vladmandic/face-api - v1.7.1
    +fetchImage | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function fetchImage

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/fetchJson.html b/typedoc/functions/fetchJson.html index c2d4352..0da6ffd 100644 --- a/typedoc/functions/fetchJson.html +++ b/typedoc/functions/fetchJson.html @@ -1,16 +1,16 @@ -fetchJson | @vladmandic/face-api - v1.7.1
    +fetchJson | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function fetchJson

    @@ -46,7 +46,7 @@

    Modules

    diff --git a/typedoc/functions/fetchNetWeights.html b/typedoc/functions/fetchNetWeights.html index ddf1ae2..a5a740d 100644 --- a/typedoc/functions/fetchNetWeights.html +++ b/typedoc/functions/fetchNetWeights.html @@ -1,16 +1,16 @@ -fetchNetWeights | @vladmandic/face-api - v1.7.1
    +fetchNetWeights | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function fetchNetWeights

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/fetchOrThrow.html b/typedoc/functions/fetchOrThrow.html index 2707883..1d2a645 100644 --- a/typedoc/functions/fetchOrThrow.html +++ b/typedoc/functions/fetchOrThrow.html @@ -1,16 +1,16 @@ -fetchOrThrow | @vladmandic/face-api - v1.7.1
    +fetchOrThrow | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function fetchOrThrow

    @@ -43,7 +43,7 @@

    Modules

    diff --git a/typedoc/functions/fetchVideo.html b/typedoc/functions/fetchVideo.html index 7e000ac..e07e246 100644 --- a/typedoc/functions/fetchVideo.html +++ b/typedoc/functions/fetchVideo.html @@ -1,16 +1,16 @@ -fetchVideo | @vladmandic/face-api - v1.7.1
    +fetchVideo | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function fetchVideo

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/getContext2dOrThrow.html b/typedoc/functions/getContext2dOrThrow.html index 8ee6f2a..3b08543 100644 --- a/typedoc/functions/getContext2dOrThrow.html +++ b/typedoc/functions/getContext2dOrThrow.html @@ -1,16 +1,16 @@ -getContext2dOrThrow | @vladmandic/face-api - v1.7.1
    +getContext2dOrThrow | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function getContext2dOrThrow

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/getMediaDimensions.html b/typedoc/functions/getMediaDimensions.html index d963263..07fa2d2 100644 --- a/typedoc/functions/getMediaDimensions.html +++ b/typedoc/functions/getMediaDimensions.html @@ -1,16 +1,16 @@ -getMediaDimensions | @vladmandic/face-api - v1.7.1
    +getMediaDimensions | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function getMediaDimensions

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/imageTensorToCanvas.html b/typedoc/functions/imageTensorToCanvas.html index 7e52088..d656fea 100644 --- a/typedoc/functions/imageTensorToCanvas.html +++ b/typedoc/functions/imageTensorToCanvas.html @@ -1,16 +1,16 @@ -imageTensorToCanvas | @vladmandic/face-api - v1.7.1
    +imageTensorToCanvas | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function imageTensorToCanvas

    @@ -43,7 +43,7 @@

    Modules

    diff --git a/typedoc/functions/imageToSquare.html b/typedoc/functions/imageToSquare.html index 82e253e..98466a3 100644 --- a/typedoc/functions/imageToSquare.html +++ b/typedoc/functions/imageToSquare.html @@ -1,16 +1,16 @@ -imageToSquare | @vladmandic/face-api - v1.7.1
    +imageToSquare | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function imageToSquare

    @@ -45,7 +45,7 @@

    Modules

    diff --git a/typedoc/functions/inverseSigmoid.html b/typedoc/functions/inverseSigmoid.html index 5a16cc1..9d49907 100644 --- a/typedoc/functions/inverseSigmoid.html +++ b/typedoc/functions/inverseSigmoid.html @@ -1,16 +1,16 @@ -inverseSigmoid | @vladmandic/face-api - v1.7.1
    +inverseSigmoid | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function inverseSigmoid

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/iou.html b/typedoc/functions/iou.html index 2e8cb71..357b5ba 100644 --- a/typedoc/functions/iou.html +++ b/typedoc/functions/iou.html @@ -1,16 +1,16 @@ -iou | @vladmandic/face-api - v1.7.1
    +iou | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function iou

    @@ -45,7 +45,7 @@

    Modules

    diff --git a/typedoc/functions/isMediaElement.html b/typedoc/functions/isMediaElement.html index 54c15cb..449abeb 100644 --- a/typedoc/functions/isMediaElement.html +++ b/typedoc/functions/isMediaElement.html @@ -1,16 +1,16 @@ -isMediaElement | @vladmandic/face-api - v1.7.1
    +isMediaElement | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function isMediaElement

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/isMediaLoaded.html b/typedoc/functions/isMediaLoaded.html index f3b6f8e..4bbe940 100644 --- a/typedoc/functions/isMediaLoaded.html +++ b/typedoc/functions/isMediaLoaded.html @@ -1,16 +1,16 @@ -isMediaLoaded | @vladmandic/face-api - v1.7.1
    +isMediaLoaded | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function isMediaLoaded

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/isWithAge.html b/typedoc/functions/isWithAge.html index 7142bef..4e8627a 100644 --- a/typedoc/functions/isWithAge.html +++ b/typedoc/functions/isWithAge.html @@ -1,16 +1,16 @@ -isWithAge | @vladmandic/face-api - v1.7.1
    +isWithAge | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function isWithAge

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/isWithFaceDetection.html b/typedoc/functions/isWithFaceDetection.html index 4274755..7d2524e 100644 --- a/typedoc/functions/isWithFaceDetection.html +++ b/typedoc/functions/isWithFaceDetection.html @@ -1,16 +1,16 @@ -isWithFaceDetection | @vladmandic/face-api - v1.7.1
    +isWithFaceDetection | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function isWithFaceDetection

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/isWithFaceExpressions.html b/typedoc/functions/isWithFaceExpressions.html index ac558ad..5982d02 100644 --- a/typedoc/functions/isWithFaceExpressions.html +++ b/typedoc/functions/isWithFaceExpressions.html @@ -1,16 +1,16 @@ -isWithFaceExpressions | @vladmandic/face-api - v1.7.1
    +isWithFaceExpressions | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function isWithFaceExpressions

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/isWithFaceLandmarks.html b/typedoc/functions/isWithFaceLandmarks.html index bd50c63..b56d923 100644 --- a/typedoc/functions/isWithFaceLandmarks.html +++ b/typedoc/functions/isWithFaceLandmarks.html @@ -1,16 +1,16 @@ -isWithFaceLandmarks | @vladmandic/face-api - v1.7.1
    +isWithFaceLandmarks | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function isWithFaceLandmarks

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/isWithGender.html b/typedoc/functions/isWithGender.html index eac6e4a..f76ffe3 100644 --- a/typedoc/functions/isWithGender.html +++ b/typedoc/functions/isWithGender.html @@ -1,16 +1,16 @@ -isWithGender | @vladmandic/face-api - v1.7.1
    +isWithGender | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function isWithGender

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/loadAgeGenderModel.html b/typedoc/functions/loadAgeGenderModel.html index 3ab2806..23977c5 100644 --- a/typedoc/functions/loadAgeGenderModel.html +++ b/typedoc/functions/loadAgeGenderModel.html @@ -1,16 +1,16 @@ -loadAgeGenderModel | @vladmandic/face-api - v1.7.1
    +loadAgeGenderModel | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function loadAgeGenderModel

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/loadFaceDetectionModel.html b/typedoc/functions/loadFaceDetectionModel.html index 41690db..4254d95 100644 --- a/typedoc/functions/loadFaceDetectionModel.html +++ b/typedoc/functions/loadFaceDetectionModel.html @@ -1,16 +1,16 @@ -loadFaceDetectionModel | @vladmandic/face-api - v1.7.1
    +loadFaceDetectionModel | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function loadFaceDetectionModel

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/loadFaceExpressionModel.html b/typedoc/functions/loadFaceExpressionModel.html index 5630795..451b931 100644 --- a/typedoc/functions/loadFaceExpressionModel.html +++ b/typedoc/functions/loadFaceExpressionModel.html @@ -1,16 +1,16 @@ -loadFaceExpressionModel | @vladmandic/face-api - v1.7.1
    +loadFaceExpressionModel | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function loadFaceExpressionModel

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/loadFaceLandmarkModel.html b/typedoc/functions/loadFaceLandmarkModel.html index a6b4f6d..72b13d6 100644 --- a/typedoc/functions/loadFaceLandmarkModel.html +++ b/typedoc/functions/loadFaceLandmarkModel.html @@ -1,16 +1,16 @@ -loadFaceLandmarkModel | @vladmandic/face-api - v1.7.1
    +loadFaceLandmarkModel | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function loadFaceLandmarkModel

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/loadFaceLandmarkTinyModel.html b/typedoc/functions/loadFaceLandmarkTinyModel.html index 4184316..e0796e3 100644 --- a/typedoc/functions/loadFaceLandmarkTinyModel.html +++ b/typedoc/functions/loadFaceLandmarkTinyModel.html @@ -1,16 +1,16 @@ -loadFaceLandmarkTinyModel | @vladmandic/face-api - v1.7.1
    +loadFaceLandmarkTinyModel | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function loadFaceLandmarkTinyModel

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/loadFaceRecognitionModel.html b/typedoc/functions/loadFaceRecognitionModel.html index 947d17f..344dde4 100644 --- a/typedoc/functions/loadFaceRecognitionModel.html +++ b/typedoc/functions/loadFaceRecognitionModel.html @@ -1,16 +1,16 @@ -loadFaceRecognitionModel | @vladmandic/face-api - v1.7.1
    +loadFaceRecognitionModel | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function loadFaceRecognitionModel

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/loadSsdMobilenetv1Model.html b/typedoc/functions/loadSsdMobilenetv1Model.html index 43671e2..df14c8d 100644 --- a/typedoc/functions/loadSsdMobilenetv1Model.html +++ b/typedoc/functions/loadSsdMobilenetv1Model.html @@ -1,16 +1,16 @@ -loadSsdMobilenetv1Model | @vladmandic/face-api - v1.7.1
    +loadSsdMobilenetv1Model | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function loadSsdMobilenetv1Model

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/loadTinyFaceDetectorModel.html b/typedoc/functions/loadTinyFaceDetectorModel.html index ccba3a7..f7d71ae 100644 --- a/typedoc/functions/loadTinyFaceDetectorModel.html +++ b/typedoc/functions/loadTinyFaceDetectorModel.html @@ -1,16 +1,16 @@ -loadTinyFaceDetectorModel | @vladmandic/face-api - v1.7.1
    +loadTinyFaceDetectorModel | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function loadTinyFaceDetectorModel

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/loadTinyYolov2Model.html b/typedoc/functions/loadTinyYolov2Model.html index d426c35..c9931a5 100644 --- a/typedoc/functions/loadTinyYolov2Model.html +++ b/typedoc/functions/loadTinyYolov2Model.html @@ -1,16 +1,16 @@ -loadTinyYolov2Model | @vladmandic/face-api - v1.7.1
    +loadTinyYolov2Model | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function loadTinyYolov2Model

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/loadWeightMap.html b/typedoc/functions/loadWeightMap.html index 326da37..d6f83e9 100644 --- a/typedoc/functions/loadWeightMap.html +++ b/typedoc/functions/loadWeightMap.html @@ -1,16 +1,16 @@ -loadWeightMap | @vladmandic/face-api - v1.7.1
    +loadWeightMap | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function loadWeightMap

    @@ -43,7 +43,7 @@

    Modules

    diff --git a/typedoc/functions/locateFaces.html b/typedoc/functions/locateFaces.html index 606c6bc..4058041 100644 --- a/typedoc/functions/locateFaces.html +++ b/typedoc/functions/locateFaces.html @@ -1,16 +1,16 @@ -locateFaces | @vladmandic/face-api - v1.7.1
    +locateFaces | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function locateFaces

    @@ -51,7 +51,7 @@

    Modules

    diff --git a/typedoc/functions/matchDimensions.html b/typedoc/functions/matchDimensions.html index 73e9334..8e66e35 100644 --- a/typedoc/functions/matchDimensions.html +++ b/typedoc/functions/matchDimensions.html @@ -1,16 +1,16 @@ -matchDimensions | @vladmandic/face-api - v1.7.1
    +matchDimensions | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function matchDimensions

    @@ -50,7 +50,7 @@

    Modules

    diff --git a/typedoc/functions/minBbox.html b/typedoc/functions/minBbox.html index e0b3ecd..0f866ba 100644 --- a/typedoc/functions/minBbox.html +++ b/typedoc/functions/minBbox.html @@ -1,16 +1,16 @@ -minBbox | @vladmandic/face-api - v1.7.1
    +minBbox | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function minBbox

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/nonMaxSuppression.html b/typedoc/functions/nonMaxSuppression.html index 1e588ee..6c642a1 100644 --- a/typedoc/functions/nonMaxSuppression.html +++ b/typedoc/functions/nonMaxSuppression.html @@ -1,16 +1,16 @@ -nonMaxSuppression | @vladmandic/face-api - v1.7.1
    +nonMaxSuppression | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function nonMaxSuppression

    @@ -47,7 +47,7 @@

    Modules

    diff --git a/typedoc/functions/normalize.html b/typedoc/functions/normalize.html index b837154..abbca27 100644 --- a/typedoc/functions/normalize.html +++ b/typedoc/functions/normalize.html @@ -1,16 +1,16 @@ -normalize | @vladmandic/face-api - v1.7.1
    +normalize | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function normalize

    @@ -43,7 +43,7 @@

    Modules

    diff --git a/typedoc/functions/padToSquare.html b/typedoc/functions/padToSquare.html index 373006d..e0c3756 100644 --- a/typedoc/functions/padToSquare.html +++ b/typedoc/functions/padToSquare.html @@ -1,16 +1,16 @@ -padToSquare | @vladmandic/face-api - v1.7.1
    +padToSquare | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function padToSquare

    @@ -52,7 +52,7 @@ both sides of the minor dimension oof the image.

    Modules

    diff --git a/typedoc/functions/predictAgeAndGender.html b/typedoc/functions/predictAgeAndGender.html index ac78f98..f2fd139 100644 --- a/typedoc/functions/predictAgeAndGender.html +++ b/typedoc/functions/predictAgeAndGender.html @@ -1,16 +1,16 @@ -predictAgeAndGender | @vladmandic/face-api - v1.7.1
    +predictAgeAndGender | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function predictAgeAndGender

    @@ -45,7 +45,7 @@

    Modules

    diff --git a/typedoc/functions/recognizeFaceExpressions.html b/typedoc/functions/recognizeFaceExpressions.html index 3bbd32b..2d4fbf2 100644 --- a/typedoc/functions/recognizeFaceExpressions.html +++ b/typedoc/functions/recognizeFaceExpressions.html @@ -1,16 +1,16 @@ -recognizeFaceExpressions | @vladmandic/face-api - v1.7.1
    +recognizeFaceExpressions | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function recognizeFaceExpressions

    @@ -45,7 +45,7 @@

    Modules

    diff --git a/typedoc/functions/resizeResults.html b/typedoc/functions/resizeResults.html index e55ba66..01551eb 100644 --- a/typedoc/functions/resizeResults.html +++ b/typedoc/functions/resizeResults.html @@ -1,16 +1,16 @@ -resizeResults | @vladmandic/face-api - v1.7.1
    +resizeResults | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function resizeResults

    @@ -48,7 +48,7 @@

    Modules

    diff --git a/typedoc/functions/resolveInput.html b/typedoc/functions/resolveInput.html index b043d0d..30b2883 100644 --- a/typedoc/functions/resolveInput.html +++ b/typedoc/functions/resolveInput.html @@ -1,16 +1,16 @@ -resolveInput | @vladmandic/face-api - v1.7.1
    +resolveInput | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function resolveInput

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/shuffleArray.html b/typedoc/functions/shuffleArray.html index 8594d6a..e7a715d 100644 --- a/typedoc/functions/shuffleArray.html +++ b/typedoc/functions/shuffleArray.html @@ -1,16 +1,16 @@ -shuffleArray | @vladmandic/face-api - v1.7.1
    +shuffleArray | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function shuffleArray

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/sigmoid.html b/typedoc/functions/sigmoid.html index a96fbdc..9902b8a 100644 --- a/typedoc/functions/sigmoid.html +++ b/typedoc/functions/sigmoid.html @@ -1,16 +1,16 @@ -sigmoid | @vladmandic/face-api - v1.7.1
    +sigmoid | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function sigmoid

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/functions/ssdMobilenetv1-1.html b/typedoc/functions/ssdMobilenetv1-1.html index 8804e99..329a479 100644 --- a/typedoc/functions/ssdMobilenetv1-1.html +++ b/typedoc/functions/ssdMobilenetv1-1.html @@ -1,16 +1,16 @@ -ssdMobilenetv1 | @vladmandic/face-api - v1.7.1
    +ssdMobilenetv1 | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function ssdMobilenetv1

    @@ -51,7 +51,7 @@

    Modules

    diff --git a/typedoc/functions/tinyFaceDetector-1.html b/typedoc/functions/tinyFaceDetector-1.html index aa1bc0d..7c55b77 100644 --- a/typedoc/functions/tinyFaceDetector-1.html +++ b/typedoc/functions/tinyFaceDetector-1.html @@ -1,16 +1,16 @@ -tinyFaceDetector | @vladmandic/face-api - v1.7.1
    +tinyFaceDetector | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function tinyFaceDetector

    @@ -51,7 +51,7 @@

    Modules

    diff --git a/typedoc/functions/tinyYolov2-1.html b/typedoc/functions/tinyYolov2-1.html index 798088e..3bf96f7 100644 --- a/typedoc/functions/tinyYolov2-1.html +++ b/typedoc/functions/tinyYolov2-1.html @@ -1,16 +1,16 @@ -tinyYolov2 | @vladmandic/face-api - v1.7.1
    +tinyYolov2 | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function tinyYolov2

    @@ -51,7 +51,7 @@

    Modules

    diff --git a/typedoc/functions/toNetInput.html b/typedoc/functions/toNetInput.html index 557f6fd..970c0f4 100644 --- a/typedoc/functions/toNetInput.html +++ b/typedoc/functions/toNetInput.html @@ -1,16 +1,16 @@ -toNetInput | @vladmandic/face-api - v1.7.1
    +toNetInput | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function toNetInput

    @@ -46,7 +46,7 @@ to be finished loading.

    Modules

    diff --git a/typedoc/functions/utils.computeReshapedDimensions.html b/typedoc/functions/utils.computeReshapedDimensions.html index 6aeb402..65807da 100644 --- a/typedoc/functions/utils.computeReshapedDimensions.html +++ b/typedoc/functions/utils.computeReshapedDimensions.html @@ -1,16 +1,16 @@ -computeReshapedDimensions | @vladmandic/face-api - v1.7.1
    +computeReshapedDimensions | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function computeReshapedDimensions

    @@ -44,7 +44,7 @@

    Modules

    diff --git a/typedoc/functions/utils.getCenterPoint.html b/typedoc/functions/utils.getCenterPoint.html index f769202..ff9deb6 100644 --- a/typedoc/functions/utils.getCenterPoint.html +++ b/typedoc/functions/utils.getCenterPoint.html @@ -1,16 +1,16 @@ -getCenterPoint | @vladmandic/face-api - v1.7.1
    +getCenterPoint | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function getCenterPoint

    @@ -42,7 +42,7 @@

    Modules

    diff --git a/typedoc/functions/utils.isDimensions.html b/typedoc/functions/utils.isDimensions.html index 900ca37..dc21f76 100644 --- a/typedoc/functions/utils.isDimensions.html +++ b/typedoc/functions/utils.isDimensions.html @@ -1,16 +1,16 @@ -isDimensions | @vladmandic/face-api - v1.7.1
    +isDimensions | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function isDimensions

    @@ -42,7 +42,7 @@

    Modules

    diff --git a/typedoc/functions/utils.isEven.html b/typedoc/functions/utils.isEven.html index e3e4c74..ef6a9df 100644 --- a/typedoc/functions/utils.isEven.html +++ b/typedoc/functions/utils.isEven.html @@ -1,16 +1,16 @@ -isEven | @vladmandic/face-api - v1.7.1
    +isEven | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function isEven

    @@ -42,7 +42,7 @@

    Modules

    diff --git a/typedoc/functions/utils.isFloat.html b/typedoc/functions/utils.isFloat.html index 6cf4482..db7e04d 100644 --- a/typedoc/functions/utils.isFloat.html +++ b/typedoc/functions/utils.isFloat.html @@ -1,16 +1,16 @@ -isFloat | @vladmandic/face-api - v1.7.1
    +isFloat | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function isFloat

    @@ -42,7 +42,7 @@

    Modules

    diff --git a/typedoc/functions/utils.isTensor.html b/typedoc/functions/utils.isTensor.html index bc8f45f..087d4fc 100644 --- a/typedoc/functions/utils.isTensor.html +++ b/typedoc/functions/utils.isTensor.html @@ -1,16 +1,16 @@ -isTensor | @vladmandic/face-api - v1.7.1
    +isTensor | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function isTensor

    @@ -44,7 +44,7 @@

    Modules

    diff --git a/typedoc/functions/utils.isTensor1D.html b/typedoc/functions/utils.isTensor1D.html index 2d95c44..3b567b8 100644 --- a/typedoc/functions/utils.isTensor1D.html +++ b/typedoc/functions/utils.isTensor1D.html @@ -1,16 +1,16 @@ -isTensor1D | @vladmandic/face-api - v1.7.1
    +isTensor1D | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function isTensor1D

    @@ -42,7 +42,7 @@

    Modules

    diff --git a/typedoc/functions/utils.isTensor2D.html b/typedoc/functions/utils.isTensor2D.html index 6957aac..3bd26ec 100644 --- a/typedoc/functions/utils.isTensor2D.html +++ b/typedoc/functions/utils.isTensor2D.html @@ -1,16 +1,16 @@ -isTensor2D | @vladmandic/face-api - v1.7.1
    +isTensor2D | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function isTensor2D

    @@ -42,7 +42,7 @@

    Modules

    diff --git a/typedoc/functions/utils.isTensor3D.html b/typedoc/functions/utils.isTensor3D.html index 918b25c..aadd980 100644 --- a/typedoc/functions/utils.isTensor3D.html +++ b/typedoc/functions/utils.isTensor3D.html @@ -1,16 +1,16 @@ -isTensor3D | @vladmandic/face-api - v1.7.1
    +isTensor3D | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function isTensor3D

    @@ -42,7 +42,7 @@

    Modules

    diff --git a/typedoc/functions/utils.isTensor4D.html b/typedoc/functions/utils.isTensor4D.html index 0d2952d..68d4e00 100644 --- a/typedoc/functions/utils.isTensor4D.html +++ b/typedoc/functions/utils.isTensor4D.html @@ -1,16 +1,16 @@ -isTensor4D | @vladmandic/face-api - v1.7.1
    +isTensor4D | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function isTensor4D

    @@ -42,7 +42,7 @@

    Modules

    diff --git a/typedoc/functions/utils.isValidNumber.html b/typedoc/functions/utils.isValidNumber.html index e6f41dc..1672676 100644 --- a/typedoc/functions/utils.isValidNumber.html +++ b/typedoc/functions/utils.isValidNumber.html @@ -1,16 +1,16 @@ -isValidNumber | @vladmandic/face-api - v1.7.1
    +isValidNumber | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function isValidNumber

    @@ -42,7 +42,7 @@

    Modules

    diff --git a/typedoc/functions/utils.isValidProbablitiy.html b/typedoc/functions/utils.isValidProbablitiy.html index b7ce718..54588ae 100644 --- a/typedoc/functions/utils.isValidProbablitiy.html +++ b/typedoc/functions/utils.isValidProbablitiy.html @@ -1,16 +1,16 @@ -isValidProbablitiy | @vladmandic/face-api - v1.7.1
    +isValidProbablitiy | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function isValidProbablitiy

    @@ -42,7 +42,7 @@

    Modules

    diff --git a/typedoc/functions/utils.range.html b/typedoc/functions/utils.range.html index 685e082..286f7d8 100644 --- a/typedoc/functions/utils.range.html +++ b/typedoc/functions/utils.range.html @@ -1,16 +1,16 @@ -range | @vladmandic/face-api - v1.7.1
    +range | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function range

    @@ -46,7 +46,7 @@

    Modules

    diff --git a/typedoc/functions/utils.round.html b/typedoc/functions/utils.round.html index aab0ce0..5561b33 100644 --- a/typedoc/functions/utils.round.html +++ b/typedoc/functions/utils.round.html @@ -1,16 +1,16 @@ -round | @vladmandic/face-api - v1.7.1
    +round | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function round

    @@ -44,7 +44,7 @@

    Modules

    diff --git a/typedoc/functions/validateConfig.html b/typedoc/functions/validateConfig.html index 8ae1892..f5f76cb 100644 --- a/typedoc/functions/validateConfig.html +++ b/typedoc/functions/validateConfig.html @@ -1,16 +1,16 @@ -validateConfig | @vladmandic/face-api - v1.7.1
    +validateConfig | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Function validateConfig

    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/index.html b/typedoc/index.html index 21e3b50..97c3c16 100644 --- a/typedoc/index.html +++ b/typedoc/index.html @@ -1,15 +1,15 @@ -@vladmandic/face-api - v1.7.1
    +@vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2
    -

    @vladmandic/face-api - v1.7.1

    +

    @vladmandic/face-api - v1.7.2

    @@ -214,7 +214,7 @@

    Modules
    diff --git a/typedoc/interfaces/IBoundingBox.html b/typedoc/interfaces/IBoundingBox.html index 9d97c37..ecc2ae0 100644 --- a/typedoc/interfaces/IBoundingBox.html +++ b/typedoc/interfaces/IBoundingBox.html @@ -1,16 +1,16 @@ -IBoundingBox | @vladmandic/face-api - v1.7.1
    +IBoundingBox | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Interface IBoundingBox

    @@ -74,7 +74,7 @@

    Modules

    diff --git a/typedoc/interfaces/IDimensions.html b/typedoc/interfaces/IDimensions.html index 6459c7a..d1c7036 100644 --- a/typedoc/interfaces/IDimensions.html +++ b/typedoc/interfaces/IDimensions.html @@ -1,16 +1,16 @@ -IDimensions | @vladmandic/face-api - v1.7.1
    +IDimensions | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Interface IDimensions

    @@ -61,7 +61,7 @@

    Modules

    diff --git a/typedoc/interfaces/IFaceDetecion.html b/typedoc/interfaces/IFaceDetecion.html index 6d66177..9f6f0e3 100644 --- a/typedoc/interfaces/IFaceDetecion.html +++ b/typedoc/interfaces/IFaceDetecion.html @@ -1,16 +1,16 @@ -IFaceDetecion | @vladmandic/face-api - v1.7.1
    +IFaceDetecion | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Interface IFaceDetecion

    @@ -61,7 +61,7 @@

    Modules

    diff --git a/typedoc/interfaces/IFaceLandmarks.html b/typedoc/interfaces/IFaceLandmarks.html index 96b32a1..bcb7787 100644 --- a/typedoc/interfaces/IFaceLandmarks.html +++ b/typedoc/interfaces/IFaceLandmarks.html @@ -1,16 +1,16 @@ -IFaceLandmarks | @vladmandic/face-api - v1.7.1
    +IFaceLandmarks | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Interface IFaceLandmarks

    @@ -61,7 +61,7 @@

    Modules

    diff --git a/typedoc/interfaces/IFaceMatch.html b/typedoc/interfaces/IFaceMatch.html index 867aae6..a8c7b74 100644 --- a/typedoc/interfaces/IFaceMatch.html +++ b/typedoc/interfaces/IFaceMatch.html @@ -1,16 +1,16 @@ -IFaceMatch | @vladmandic/face-api - v1.7.1
    +IFaceMatch | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Interface IFaceMatch

    @@ -61,7 +61,7 @@

    Modules

    diff --git a/typedoc/interfaces/IPoint.html b/typedoc/interfaces/IPoint.html index c8fc3f4..5c2adef 100644 --- a/typedoc/interfaces/IPoint.html +++ b/typedoc/interfaces/IPoint.html @@ -1,16 +1,16 @@ -IPoint | @vladmandic/face-api - v1.7.1
    +IPoint | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Interface IPoint

    @@ -61,7 +61,7 @@

    Modules

    diff --git a/typedoc/interfaces/IRect.html b/typedoc/interfaces/IRect.html index 76dc3f3..82e5bbd 100644 --- a/typedoc/interfaces/IRect.html +++ b/typedoc/interfaces/IRect.html @@ -1,16 +1,16 @@ -IRect | @vladmandic/face-api - v1.7.1
    +IRect | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Interface IRect

    @@ -74,7 +74,7 @@

    Modules

    diff --git a/typedoc/interfaces/ISsdMobilenetv1Options.html b/typedoc/interfaces/ISsdMobilenetv1Options.html index bb3543b..f4bdfc8 100644 --- a/typedoc/interfaces/ISsdMobilenetv1Options.html +++ b/typedoc/interfaces/ISsdMobilenetv1Options.html @@ -1,16 +1,16 @@ -ISsdMobilenetv1Options | @vladmandic/face-api - v1.7.1
    +ISsdMobilenetv1Options | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Interface ISsdMobilenetv1Options

    @@ -57,7 +57,7 @@

    Modules

    diff --git a/typedoc/interfaces/ITinyYolov2Options.html b/typedoc/interfaces/ITinyYolov2Options.html index 120b9a7..a15026b 100644 --- a/typedoc/interfaces/ITinyYolov2Options.html +++ b/typedoc/interfaces/ITinyYolov2Options.html @@ -1,16 +1,16 @@ -ITinyYolov2Options | @vladmandic/face-api - v1.7.1
    +ITinyYolov2Options | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Interface ITinyYolov2Options

    @@ -57,7 +57,7 @@

    Modules

    diff --git a/typedoc/interfaces/draw.IDrawBoxOptions.html b/typedoc/interfaces/draw.IDrawBoxOptions.html index e784297..a2f80d7 100644 --- a/typedoc/interfaces/draw.IDrawBoxOptions.html +++ b/typedoc/interfaces/draw.IDrawBoxOptions.html @@ -1,16 +1,16 @@ -IDrawBoxOptions | @vladmandic/face-api - v1.7.1
    +IDrawBoxOptions | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Interface IDrawBoxOptions

    @@ -70,7 +70,7 @@

    Modules

    diff --git a/typedoc/interfaces/draw.IDrawFaceLandmarksOptions.html b/typedoc/interfaces/draw.IDrawFaceLandmarksOptions.html index c525747..0db2678 100644 --- a/typedoc/interfaces/draw.IDrawFaceLandmarksOptions.html +++ b/typedoc/interfaces/draw.IDrawFaceLandmarksOptions.html @@ -1,16 +1,16 @@ -IDrawFaceLandmarksOptions | @vladmandic/face-api - v1.7.1
    +IDrawFaceLandmarksOptions | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Interface IDrawFaceLandmarksOptions

    @@ -82,7 +82,7 @@

    Modules

    diff --git a/typedoc/interfaces/draw.IDrawTextFieldOptions.html b/typedoc/interfaces/draw.IDrawTextFieldOptions.html index 7b091c5..7eac8ea 100644 --- a/typedoc/interfaces/draw.IDrawTextFieldOptions.html +++ b/typedoc/interfaces/draw.IDrawTextFieldOptions.html @@ -1,16 +1,16 @@ -IDrawTextFieldOptions | @vladmandic/face-api - v1.7.1
    +IDrawTextFieldOptions | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Interface IDrawTextFieldOptions

    @@ -86,7 +86,7 @@

    Modules

    diff --git a/typedoc/modules/draw.html b/typedoc/modules/draw.html index 0beb110..7ea90c0 100644 --- a/typedoc/modules/draw.html +++ b/typedoc/modules/draw.html @@ -1,16 +1,16 @@ -draw | @vladmandic/face-api - v1.7.1
    +draw | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Namespace draw

    Namespace utils

    Type alias AgeAndGenderPrediction

    AgeAndGenderPrediction: { age: number; gender: Gender; genderProbability: number }
    @@ -41,7 +41,7 @@

    Modules

    diff --git a/typedoc/types/BatchNorm.html b/typedoc/types/BatchNorm.html index cf07b81..de6e6c4 100644 --- a/typedoc/types/BatchNorm.html +++ b/typedoc/types/BatchNorm.html @@ -1,16 +1,16 @@ -BatchNorm | @vladmandic/face-api - v1.7.1
    +BatchNorm | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Type alias BatchNorm

    BatchNorm: { sub: tf.Tensor1D; truediv: tf.Tensor1D }
    @@ -39,7 +39,7 @@

    Modules

    diff --git a/typedoc/types/ConvWithBatchNorm.html b/typedoc/types/ConvWithBatchNorm.html index 83c8f9f..02b851f 100644 --- a/typedoc/types/ConvWithBatchNorm.html +++ b/typedoc/types/ConvWithBatchNorm.html @@ -1,16 +1,16 @@ -ConvWithBatchNorm | @vladmandic/face-api - v1.7.1
    +ConvWithBatchNorm | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Type alias ConvWithBatchNorm

    ConvWithBatchNorm: { bn: BatchNorm; conv: ConvParams }
    @@ -39,7 +39,7 @@

    Modules

    diff --git a/typedoc/types/DefaultTinyYolov2NetParams.html b/typedoc/types/DefaultTinyYolov2NetParams.html index 344c646..252e123 100644 --- a/typedoc/types/DefaultTinyYolov2NetParams.html +++ b/typedoc/types/DefaultTinyYolov2NetParams.html @@ -1,16 +1,16 @@ -DefaultTinyYolov2NetParams | @vladmandic/face-api - v1.7.1
    +DefaultTinyYolov2NetParams | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Type alias DefaultTinyYolov2NetParams

    DefaultTinyYolov2NetParams: { conv0: ConvWithBatchNorm; conv1: ConvWithBatchNorm; conv2: ConvWithBatchNorm; conv3: ConvWithBatchNorm; conv4: ConvWithBatchNorm; conv5: ConvWithBatchNorm; conv6: ConvWithBatchNorm; conv7: ConvWithBatchNorm; conv8: ConvParams }
    @@ -53,7 +53,7 @@

    Modules

    diff --git a/typedoc/types/Environment.html b/typedoc/types/Environment.html index c9c5473..c8dd3b4 100644 --- a/typedoc/types/Environment.html +++ b/typedoc/types/Environment.html @@ -1,16 +1,16 @@ -Environment | @vladmandic/face-api - v1.7.1
    +Environment | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Type alias Environment

    Environment: FileSystem & { Canvas: typeof HTMLCanvasElement; CanvasRenderingContext2D: typeof CanvasRenderingContext2D; Image: typeof HTMLImageElement; ImageData: typeof ImageData; Video: typeof HTMLVideoElement; createCanvasElement: (() => HTMLCanvasElement); createImageElement: (() => HTMLImageElement); createVideoElement: (() => HTMLVideoElement); fetch: ((url: string, init?: RequestInit) => Promise<Response>) }

    Type alias FaceDetectionFunction

    FaceDetectionFunction: ((input: TNetInput) => Promise<FaceDetection[]>)
    @@ -45,7 +45,7 @@

    Modules

    diff --git a/typedoc/types/FaceDetectionOptions.html b/typedoc/types/FaceDetectionOptions.html index 865bb6e..9ae4411 100644 --- a/typedoc/types/FaceDetectionOptions.html +++ b/typedoc/types/FaceDetectionOptions.html @@ -1,16 +1,16 @@ -FaceDetectionOptions | @vladmandic/face-api - v1.7.1
    +FaceDetectionOptions | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Type alias FaceDetectionOptions

    FaceDetectionOptions: TinyFaceDetectorOptions | SsdMobilenetv1Options | TinyYolov2Options

    Type alias FileSystem

    FileSystem: { readFile: ((filePath: string) => Promise<any>) }
    @@ -48,7 +48,7 @@

    Modules

    diff --git a/typedoc/types/ITinyFaceDetectorOptions.html b/typedoc/types/ITinyFaceDetectorOptions.html index e7888b8..469cf6d 100644 --- a/typedoc/types/ITinyFaceDetectorOptions.html +++ b/typedoc/types/ITinyFaceDetectorOptions.html @@ -1,16 +1,16 @@ -ITinyFaceDetectorOptions | @vladmandic/face-api - v1.7.1
    +ITinyFaceDetectorOptions | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Type alias ITinyFaceDetectorOptions

    ITinyFaceDetectorOptions: ITinyYolov2Options

    Type alias MobilenetParams

    MobilenetParams: { conv0: SeparableConvParams | ConvParams; conv1: SeparableConvParams; conv2: SeparableConvParams; conv3: SeparableConvParams; conv4: SeparableConvParams; conv5: SeparableConvParams; conv6?: SeparableConvParams; conv7?: SeparableConvParams; conv8: ConvParams }
    @@ -53,7 +53,7 @@

    Modules

    diff --git a/typedoc/types/NetOutput.html b/typedoc/types/NetOutput.html index be334f2..29b770d 100644 --- a/typedoc/types/NetOutput.html +++ b/typedoc/types/NetOutput.html @@ -1,16 +1,16 @@ -NetOutput | @vladmandic/face-api - v1.7.1
    +NetOutput | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Type alias NetOutput

    NetOutput: { age: tf.Tensor1D; gender: tf.Tensor2D }
    @@ -39,7 +39,7 @@

    Modules

    diff --git a/typedoc/types/NetParams.html b/typedoc/types/NetParams.html index 2f0f134..847b043 100644 --- a/typedoc/types/NetParams.html +++ b/typedoc/types/NetParams.html @@ -1,16 +1,16 @@ -NetParams | @vladmandic/face-api - v1.7.1
    +NetParams | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Type alias NetParams

    NetParams: { fc: { age: FCParams; gender: FCParams } }
    @@ -42,7 +42,7 @@

    Modules

    diff --git a/typedoc/types/TMediaElement.html b/typedoc/types/TMediaElement.html index 7d0fd8b..fc67e15 100644 --- a/typedoc/types/TMediaElement.html +++ b/typedoc/types/TMediaElement.html @@ -1,16 +1,16 @@ -TMediaElement | @vladmandic/face-api - v1.7.1
    +TMediaElement | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Type alias TMediaElement

    TMediaElement: HTMLImageElement | HTMLVideoElement | HTMLCanvasElement

    Type alias TNetInput

    TNetInput: TNetInputArg | TNetInputArg[] | NetInput | tf.Tensor4D

    Type alias TNetInputArg

    TNetInputArg: string | TResolvedNetInput

    Type alias TResolvedNetInput

    TResolvedNetInput: TMediaElement | tf.Tensor3D | tf.Tensor4D

    Type alias TinyYolov2Config

    TinyYolov2Config: { anchors: Point[]; classes: string[]; filterSizes?: number[]; iouThreshold: number; isFirstLayerConv2d?: boolean; meanRgb?: [number, number, number]; withClassScores?: boolean; withSeparableConvs: boolean }
    @@ -51,7 +51,7 @@

    Modules

    diff --git a/typedoc/types/TinyYolov2NetParams.html b/typedoc/types/TinyYolov2NetParams.html index 079268d..e11cb61 100644 --- a/typedoc/types/TinyYolov2NetParams.html +++ b/typedoc/types/TinyYolov2NetParams.html @@ -1,16 +1,16 @@ -TinyYolov2NetParams | @vladmandic/face-api - v1.7.1
    +TinyYolov2NetParams | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Type alias TinyYolov2NetParams

    TinyYolov2NetParams: DefaultTinyYolov2NetParams | MobilenetParams

    Type alias WithAge<TSource>

    WithAge<TSource>: TSource & { age: number }
    @@ -36,7 +36,7 @@

    Modules

    diff --git a/typedoc/types/WithFaceDescriptor.html b/typedoc/types/WithFaceDescriptor.html index 464a0d4..7354c25 100644 --- a/typedoc/types/WithFaceDescriptor.html +++ b/typedoc/types/WithFaceDescriptor.html @@ -1,16 +1,16 @@ -WithFaceDescriptor | @vladmandic/face-api - v1.7.1
    +WithFaceDescriptor | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Type alias WithFaceDescriptor<TSource>

    WithFaceDescriptor<TSource>: TSource & { descriptor: Float32Array }
    @@ -36,7 +36,7 @@

    Modules

    diff --git a/typedoc/types/WithFaceDetection.html b/typedoc/types/WithFaceDetection.html index d49c608..1d9e07c 100644 --- a/typedoc/types/WithFaceDetection.html +++ b/typedoc/types/WithFaceDetection.html @@ -1,16 +1,16 @@ -WithFaceDetection | @vladmandic/face-api - v1.7.1
    +WithFaceDetection | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Type alias WithFaceDetection<TSource>

    WithFaceDetection<TSource>: TSource & { detection: FaceDetection }
    @@ -36,7 +36,7 @@

    Modules

    diff --git a/typedoc/types/WithFaceExpressions.html b/typedoc/types/WithFaceExpressions.html index cf534b9..5ec800e 100644 --- a/typedoc/types/WithFaceExpressions.html +++ b/typedoc/types/WithFaceExpressions.html @@ -1,16 +1,16 @@ -WithFaceExpressions | @vladmandic/face-api - v1.7.1
    +WithFaceExpressions | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Type alias WithFaceExpressions<TSource>

    WithFaceExpressions<TSource>: TSource & { expressions: FaceExpressions }
    @@ -36,7 +36,7 @@

    Modules

    diff --git a/typedoc/types/WithFaceLandmarks.html b/typedoc/types/WithFaceLandmarks.html index b2cbb2d..b1a79f3 100644 --- a/typedoc/types/WithFaceLandmarks.html +++ b/typedoc/types/WithFaceLandmarks.html @@ -1,16 +1,16 @@ -WithFaceLandmarks | @vladmandic/face-api - v1.7.1
    +WithFaceLandmarks | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Type alias WithFaceLandmarks<TSource, TFaceLandmarks>

    WithFaceLandmarks<TSource, TFaceLandmarks>: TSource & { alignedRect: FaceDetection; angle: { pitch: number | undefined; roll: number | undefined; yaw: number | undefined }; landmarks: TFaceLandmarks; unshiftedLandmarks: TFaceLandmarks }
    @@ -38,7 +38,7 @@

    Modules

    diff --git a/typedoc/types/WithGender.html b/typedoc/types/WithGender.html index 60e6c6b..9c25063 100644 --- a/typedoc/types/WithGender.html +++ b/typedoc/types/WithGender.html @@ -1,16 +1,16 @@ -WithGender | @vladmandic/face-api - v1.7.1
    +WithGender | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Type alias WithGender<TSource>

    WithGender<TSource>: TSource & { gender: Gender; genderProbability: number }
    @@ -36,7 +36,7 @@

    Modules

    diff --git a/typedoc/types/draw.DrawFaceExpressionsInput.html b/typedoc/types/draw.DrawFaceExpressionsInput.html index f7174ad..275d6dc 100644 --- a/typedoc/types/draw.DrawFaceExpressionsInput.html +++ b/typedoc/types/draw.DrawFaceExpressionsInput.html @@ -1,16 +1,16 @@ -DrawFaceExpressionsInput | @vladmandic/face-api - v1.7.1
    +DrawFaceExpressionsInput | @vladmandic/face-api - v1.7.2
    +
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    • @vladmandic/face-api - v1.7.2

    Type alias DrawFaceExpressionsInput

    @@ -33,7 +33,7 @@

    Modules

    diff --git a/typedoc/types/draw.DrawFaceLandmarksInput.html b/typedoc/types/draw.DrawFaceLandmarksInput.html index ef57852..b68918f 100644 --- a/typedoc/types/draw.DrawFaceLandmarksInput.html +++ b/typedoc/types/draw.DrawFaceLandmarksInput.html @@ -1,16 +1,16 @@ -DrawFaceLandmarksInput | @vladmandic/face-api - v1.7.1
    +DrawFaceLandmarksInput | @vladmandic/face-api - v1.7.2
    +
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    • @vladmandic/face-api - v1.7.2

    Type alias DrawFaceLandmarksInput

    @@ -33,7 +33,7 @@

    Modules

    diff --git a/typedoc/types/draw.TDrawDetectionsInput.html b/typedoc/types/draw.TDrawDetectionsInput.html index 1295a14..f7896c2 100644 --- a/typedoc/types/draw.TDrawDetectionsInput.html +++ b/typedoc/types/draw.TDrawDetectionsInput.html @@ -1,16 +1,16 @@ -TDrawDetectionsInput | @vladmandic/face-api - v1.7.1
    +TDrawDetectionsInput | @vladmandic/face-api - v1.7.2
    +
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    • @vladmandic/face-api - v1.7.2

    Type alias TDrawDetectionsInput

    @@ -33,7 +33,7 @@

    Modules

    diff --git a/typedoc/variables/FACE_EXPRESSION_LABELS.html b/typedoc/variables/FACE_EXPRESSION_LABELS.html index 0c0bf09..a978c7e 100644 --- a/typedoc/variables/FACE_EXPRESSION_LABELS.html +++ b/typedoc/variables/FACE_EXPRESSION_LABELS.html @@ -1,16 +1,16 @@ -FACE_EXPRESSION_LABELS | @vladmandic/face-api - v1.7.1
    +FACE_EXPRESSION_LABELS | @vladmandic/face-api - v1.7.2
    +
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    • @vladmandic/face-api - v1.7.2

    Variable FACE_EXPRESSION_LABELSConst

    FACE_EXPRESSION_LABELS: string[] = ...

    Variable envConst

    env: { createBrowserEnv: (() => Environment); createFileSystem: ((fs?: any) => FileSystem); createNodejsEnv: (() => Environment); getEnv: (() => Environment); initialize: (() => null | void); isBrowser: (() => boolean); isNodejs: (() => boolean); monkeyPatch: ((env: Partial<Environment>) => void); setEnv: ((env: Environment) => void) } = ...
    @@ -122,7 +122,7 @@

    Modules

    diff --git a/typedoc/variables/nets.html b/typedoc/variables/nets.html index 7c5c05f..7d88b29 100644 --- a/typedoc/variables/nets.html +++ b/typedoc/variables/nets.html @@ -1,16 +1,16 @@ -nets | @vladmandic/face-api - v1.7.1
    +nets | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Variable netsConst

    nets: { ageGenderNet: AgeGenderNet; faceExpressionNet: FaceExpressionNet; faceLandmark68Net: FaceLandmark68Net; faceLandmark68TinyNet: FaceLandmark68TinyNet; faceRecognitionNet: FaceRecognitionNet; ssdMobilenetv1: SsdMobilenetv1; tinyFaceDetector: TinyFaceDetector; tinyYolov2: TinyYolov2 } = ...
    @@ -51,7 +51,7 @@

    Modules

    diff --git a/typedoc/variables/version.html b/typedoc/variables/version.html index 4f85e80..4669da2 100644 --- a/typedoc/variables/version.html +++ b/typedoc/variables/version.html @@ -1,16 +1,16 @@ -version | @vladmandic/face-api - v1.7.1
    +version | @vladmandic/face-api - v1.7.2
    +
  • The search index is not available
    • @vladmandic/face-api - v1.7.2

    Variable versionConst

    version: string = ...