check in latest build

build/commonjs/ageGenderNet/AgeGenderNet.d.ts

+import * as tf from '@tensorflow/tfjs-core';
+import { NetInput, NeuralNetwork, TNetInput } from 'tfjs-image-recognition-base';
+import { TinyXception } from '../xception/TinyXception';
+import { AgeAndGenderPrediction, NetOutput, NetParams } from './types';
+export declare class AgeGenderNet extends NeuralNetwork<NetParams> {
+    private _faceFeatureExtractor;
+    constructor(faceFeatureExtractor?: TinyXception);
+    readonly faceFeatureExtractor: TinyXception;
+    runNet(input: NetInput | tf.Tensor4D): NetOutput;
+    forwardInput(input: NetInput | tf.Tensor4D): NetOutput;
+    forward(input: TNetInput): Promise<NetOutput>;
+    predictAgeAndGender(input: TNetInput): Promise<AgeAndGenderPrediction | AgeAndGenderPrediction[]>;
+    protected getDefaultModelName(): string;
+    dispose(throwOnRedispose?: boolean): void;
+    loadClassifierParams(weights: Float32Array): void;
+    extractClassifierParams(weights: Float32Array): {
+        params: NetParams;
+        paramMappings: import("tfjs-image-recognition-base/build/commonjs/common").ParamMapping[];
+    };
+    protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap): {
+        params: NetParams;
+        paramMappings: import("tfjs-image-recognition-base/build/commonjs/common").ParamMapping[];
+    };
+    protected extractParams(weights: Float32Array): {
+        params: NetParams;
+        paramMappings: import("tfjs-image-recognition-base/build/commonjs/common").ParamMapping[];
+    };
+}

build/commonjs/ageGenderNet/AgeGenderNet.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+var tslib_1 = require("tslib");
+var tf = require("@tensorflow/tfjs-core");
+var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
+var fullyConnectedLayer_1 = require("../common/fullyConnectedLayer");
+var util_1 = require("../faceProcessor/util");
+var TinyXception_1 = require("../xception/TinyXception");
+var extractParams_1 = require("./extractParams");
+var extractParamsFromWeigthMap_1 = require("./extractParamsFromWeigthMap");
+var types_1 = require("./types");
+var AgeGenderNet = /** @class */ (function (_super) {
+    tslib_1.__extends(AgeGenderNet, _super);
+    function AgeGenderNet(faceFeatureExtractor) {
+        if (faceFeatureExtractor === void 0) { faceFeatureExtractor = new TinyXception_1.TinyXception(2); }
+        var _this = _super.call(this, 'AgeGenderNet') || this;
+        _this._faceFeatureExtractor = faceFeatureExtractor;
+        return _this;
+    }
+    Object.defineProperty(AgeGenderNet.prototype, "faceFeatureExtractor", {
+        get: function () {
+            return this._faceFeatureExtractor;
+        },
+        enumerable: true,
+        configurable: true
+    });
+    AgeGenderNet.prototype.runNet = function (input) {
+        var _this = this;
+        var params = this.params;
+        if (!params) {
+            throw new Error(this._name + " - load model before inference");
+        }
+        return tf.tidy(function () {
+            var bottleneckFeatures = input instanceof tfjs_image_recognition_base_1.NetInput
+                ? _this.faceFeatureExtractor.forwardInput(input)
+                : input;
+            var pooled = tf.avgPool(bottleneckFeatures, [7, 7], [2, 2], 'valid').as2D(bottleneckFeatures.shape[0], -1);
+            var age = fullyConnectedLayer_1.fullyConnectedLayer(pooled, params.fc.age).as1D();
+            var gender = fullyConnectedLayer_1.fullyConnectedLayer(pooled, params.fc.gender);
+            return { age: age, gender: gender };
+        });
+    };
+    AgeGenderNet.prototype.forwardInput = function (input) {
+        var _this = this;
+        return tf.tidy(function () {
+            var _a = _this.runNet(input), age = _a.age, gender = _a.gender;
+            return { age: age, gender: tf.softmax(gender) };
+        });
+    };
+    AgeGenderNet.prototype.forward = function (input) {
+        return tslib_1.__awaiter(this, void 0, void 0, function () {
+            var _a;
+            return tslib_1.__generator(this, function (_b) {
+                switch (_b.label) {
+                    case 0:
+                        _a = this.forwardInput;
+                        return [4 /*yield*/, tfjs_image_recognition_base_1.toNetInput(input)];
+                    case 1: return [2 /*return*/, _a.apply(this, [_b.sent()])];
+                }
+            });
+        });
+    };
+    AgeGenderNet.prototype.predictAgeAndGender = function (input) {
+        return tslib_1.__awaiter(this, void 0, void 0, function () {
+            var netInput, out, ages, genders, ageAndGenderTensors, predictionsByBatch;
+            var _this = this;
+            return tslib_1.__generator(this, function (_a) {
+                switch (_a.label) {
+                    case 0: return [4 /*yield*/, tfjs_image_recognition_base_1.toNetInput(input)];
+                    case 1:
+                        netInput = _a.sent();
+                        return [4 /*yield*/, this.forwardInput(netInput)];
+                    case 2:
+                        out = _a.sent();
+                        ages = tf.unstack(out.age);
+                        genders = tf.unstack(out.gender);
+                        ageAndGenderTensors = ages.map(function (ageTensor, i) { return ({
+                            ageTensor: ageTensor,
+                            genderTensor: genders[i]
+                        }); });
+                        return [4 /*yield*/, Promise.all(ageAndGenderTensors.map(function (_a) {
+                                var ageTensor = _a.ageTensor, genderTensor = _a.genderTensor;
+                                return tslib_1.__awaiter(_this, void 0, void 0, function () {
+                                    var age, probMale, isMale, gender, genderProbability;
+                                    return tslib_1.__generator(this, function (_b) {
+                                        switch (_b.label) {
+                                            case 0: return [4 /*yield*/, ageTensor.data()];
+                                            case 1:
+                                                age = (_b.sent())[0];
+                                                return [4 /*yield*/, genderTensor.data()];
+                                            case 2:
+                                                probMale = (_b.sent())[0];
+                                                isMale = probMale > 0.5;
+                                                gender = isMale ? types_1.Gender.MALE : types_1.Gender.FEMALE;
+                                                genderProbability = isMale ? probMale : (1 - probMale);
+                                                ageTensor.dispose();
+                                                genderTensor.dispose();
+                                                return [2 /*return*/, { age: age, gender: gender, genderProbability: genderProbability }];
+                                        }
+                                    });
+                                });
+                            }))];
+                    case 3:
+                        predictionsByBatch = _a.sent();
+                        out.age.dispose();
+                        out.gender.dispose();
+                        return [2 /*return*/, netInput.isBatchInput
+                                ? predictionsByBatch
+                                : predictionsByBatch[0]];
+                }
+            });
+        });
+    };
+    AgeGenderNet.prototype.getDefaultModelName = function () {
+        return 'age_gender_model';
+    };
+    AgeGenderNet.prototype.dispose = function (throwOnRedispose) {
+        if (throwOnRedispose === void 0) { throwOnRedispose = true; }
+        this.faceFeatureExtractor.dispose(throwOnRedispose);
+        _super.prototype.dispose.call(this, throwOnRedispose);
+    };
+    AgeGenderNet.prototype.loadClassifierParams = function (weights) {
+        var _a = this.extractClassifierParams(weights), params = _a.params, paramMappings = _a.paramMappings;
+        this._params = params;
+        this._paramMappings = paramMappings;
+    };
+    AgeGenderNet.prototype.extractClassifierParams = function (weights) {
+        return extractParams_1.extractParams(weights);
+    };
+    AgeGenderNet.prototype.extractParamsFromWeigthMap = function (weightMap) {
+        var _a = util_1.seperateWeightMaps(weightMap), featureExtractorMap = _a.featureExtractorMap, classifierMap = _a.classifierMap;
+        this.faceFeatureExtractor.loadFromWeightMap(featureExtractorMap);
+        return extractParamsFromWeigthMap_1.extractParamsFromWeigthMap(classifierMap);
+    };
+    AgeGenderNet.prototype.extractParams = function (weights) {
+        var classifierWeightSize = (512 * 1 + 1) + (512 * 2 + 2);
+        var featureExtractorWeights = weights.slice(0, weights.length - classifierWeightSize);
+        var classifierWeights = weights.slice(weights.length - classifierWeightSize);
+        this.faceFeatureExtractor.extractWeights(featureExtractorWeights);
+        return this.extractClassifierParams(classifierWeights);
+    };
+    return AgeGenderNet;
+}(tfjs_image_recognition_base_1.NeuralNetwork));
+exports.AgeGenderNet = AgeGenderNet;
+//# sourceMappingURL=AgeGenderNet.js.map
\ No newline at end of file

build/commonjs/ageGenderNet/AgeGenderNet.js.map

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\ No newline at end of file

build/commonjs/ageGenderNet/extractParams.d.ts

+import { TfjsImageRecognitionBase } from 'tfjs-image-recognition-base';
+import { NetParams } from './types';
+export declare function extractParams(weights: Float32Array): {
+    params: NetParams;
+    paramMappings: TfjsImageRecognitionBase.ParamMapping[];
+};

build/commonjs/ageGenderNet/extractParams.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
+function extractParams(weights) {
+    var paramMappings = [];
+    var _a = tfjs_image_recognition_base_1.TfjsImageRecognitionBase.extractWeightsFactory(weights), extractWeights = _a.extractWeights, getRemainingWeights = _a.getRemainingWeights;
+    var extractFCParams = tfjs_image_recognition_base_1.TfjsImageRecognitionBase.extractFCParamsFactory(extractWeights, paramMappings);
+    var age = extractFCParams(512, 1, 'fc/age');
+    var gender = extractFCParams(512, 2, 'fc/gender');
+    if (getRemainingWeights().length !== 0) {
+        throw new Error("weights remaing after extract: " + getRemainingWeights().length);
+    }
+    return {
+        paramMappings: paramMappings,
+        params: { fc: { age: age, gender: gender } }
+    };
+}
+exports.extractParams = extractParams;
+//# sourceMappingURL=extractParams.js.map
\ No newline at end of file

build/commonjs/ageGenderNet/extractParams.js.map

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build/commonjs/ageGenderNet/extractParamsFromWeigthMap.d.ts

+import * as tf from '@tensorflow/tfjs-core';
+import { TfjsImageRecognitionBase } from 'tfjs-image-recognition-base';
+import { NetParams } from './types';
+export declare function extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap): {
+    params: NetParams;
+    paramMappings: TfjsImageRecognitionBase.ParamMapping[];
+};

build/commonjs/ageGenderNet/extractParamsFromWeigthMap.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
+function extractParamsFromWeigthMap(weightMap) {
+    var paramMappings = [];
+    var extractWeightEntry = tfjs_image_recognition_base_1.TfjsImageRecognitionBase.extractWeightEntryFactory(weightMap, paramMappings);
+    function extractFcParams(prefix) {
+        var weights = extractWeightEntry(prefix + "/weights", 2);
+        var bias = extractWeightEntry(prefix + "/bias", 1);
+        return { weights: weights, bias: bias };
+    }
+    var params = {
+        fc: {
+            age: extractFcParams('fc/age'),
+            gender: extractFcParams('fc/gender')
+        }
+    };
+    tfjs_image_recognition_base_1.TfjsImageRecognitionBase.disposeUnusedWeightTensors(weightMap, paramMappings);
+    return { params: params, paramMappings: paramMappings };
+}
+exports.extractParamsFromWeigthMap = extractParamsFromWeigthMap;
+//# sourceMappingURL=extractParamsFromWeigthMap.js.map
\ No newline at end of file

build/commonjs/ageGenderNet/extractParamsFromWeigthMap.js.map

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\ No newline at end of file

build/commonjs/ageGenderNet/index.d.ts

+export * from './AgeGenderNet';
+export * from './types';

build/commonjs/ageGenderNet/index.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+var tslib_1 = require("tslib");
+tslib_1.__exportStar(require("./AgeGenderNet"), exports);
+tslib_1.__exportStar(require("./types"), exports);
+//# sourceMappingURL=index.js.map
\ No newline at end of file

build/commonjs/ageGenderNet/index.js.map

+{"version":3,"file":"index.js","sourceRoot":"","sources":["../../../src/ageGenderNet/index.ts"],"names":[],"mappings":";;;AAAA,yDAA+B;AAC/B,kDAAwB"}
\ No newline at end of file

build/commonjs/ageGenderNet/types.d.ts

+import * as tf from '@tensorflow/tfjs-core';
+import { TfjsImageRecognitionBase } from 'tfjs-image-recognition-base';
+export declare type AgeAndGenderPrediction = {
+    age: number;
+    gender: Gender;
+    genderProbability: number;
+};
+export declare enum Gender {
+    FEMALE = "female",
+    MALE = "male"
+}
+export declare type NetOutput = {
+    age: tf.Tensor1D;
+    gender: tf.Tensor2D;
+};
+export declare type NetParams = {
+    fc: {
+        age: TfjsImageRecognitionBase.FCParams;
+        gender: TfjsImageRecognitionBase.FCParams;
+    };
+};

build/commonjs/ageGenderNet/types.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+var Gender;
+(function (Gender) {
+    Gender["FEMALE"] = "female";
+    Gender["MALE"] = "male";
+})(Gender = exports.Gender || (exports.Gender = {}));
+//# sourceMappingURL=types.js.map
\ No newline at end of file

build/commonjs/ageGenderNet/types.js.map

+{"version":3,"file":"types.js","sourceRoot":"","sources":["../../../src/ageGenderNet/types.ts"],"names":[],"mappings":";;AASA,IAAY,MAGX;AAHD,WAAY,MAAM;IAChB,2BAAiB,CAAA;IACjB,uBAAa,CAAA;AACf,CAAC,EAHW,MAAM,GAAN,cAAM,KAAN,cAAM,QAGjB"}
\ No newline at end of file

build/commonjs/classes/FaceDetection.js

@@ -8,7 +8,8 @@ var FaceDetection = /** @class */ (function (_super) {
         return _super.call(this, score, score, '', relativeBox, imageDims) || this;
     }
     FaceDetection.prototype.forSize = function (width, height) {
-        return _super.prototype.forSize.call(this, width, height);
+        var _a = _super.prototype.forSize.call(this, width, height), score = _a.score, relativeBox = _a.relativeBox, imageDims = _a.imageDims;
+        return new FaceDetection(score, relativeBox, imageDims);
     };
     return FaceDetection;
 }(tfjs_image_recognition_base_1.ObjectDetection));

build/commonjs/classes/FaceDetection.js.map

-{"version":3,"file":"FaceDetection.js","sourceRoot":"","sources":["../../../src/classes/FaceDetection.ts"],"names":[],"mappings":";;;AAAA,2EAAsF;AAOtF;IAAmC,yCAAe;IAChD,uBACE,KAAa,EACb,WAAiB,EACjB,SAAsB;eAEtB,kBAAM,KAAK,EAAE,KAAK,EAAE,EAAE,EAAE,WAAW,EAAE,SAAS,CAAC;IACjD,CAAC;IAEM,+BAAO,GAAd,UAAe,KAAa,EAAE,MAAc;QAC1C,OAAO,iBAAM,OAAO,YAAC,KAAK,EAAE,MAAM,CAAC,CAAA;IACrC,CAAC;IACH,oBAAC;AAAD,CAAC,AAZD,CAAmC,6CAAe,GAYjD;AAZY,sCAAa"}
+{"version":3,"file":"FaceDetection.js","sourceRoot":"","sources":["../../../src/classes/FaceDetection.ts"],"names":[],"mappings":";;;AAAA,2EAAsF;AAOtF;IAAmC,yCAAe;IAChD,uBACE,KAAa,EACb,WAAiB,EACjB,SAAsB;eAEtB,kBAAM,KAAK,EAAE,KAAK,EAAE,EAAE,EAAE,WAAW,EAAE,SAAS,CAAC;IACjD,CAAC;IAEM,+BAAO,GAAd,UAAe,KAAa,EAAE,MAAc;QACpC,IAAA,uDAAgE,EAA9D,gBAAK,EAAE,4BAAW,EAAE,wBAA0C,CAAA;QACtE,OAAO,IAAI,aAAa,CAAC,KAAK,EAAE,WAAW,EAAE,SAAS,CAAC,CAAA;IACzD,CAAC;IACH,oBAAC;AAAD,CAAC,AAbD,CAAmC,6CAAe,GAajD;AAbY,sCAAa"}
\ No newline at end of file

build/commonjs/classes/FaceLandmarks.d.ts

-import { Dimensions, IDimensions, Point, Rect } from 'tfjs-image-recognition-base';
+import { Box, Dimensions, IBoundingBox, IDimensions, IRect, Point } from 'tfjs-image-recognition-base';
 import { FaceDetection } from './FaceDetection';
 export interface IFaceLandmarks {
     positions: Point[];
@@ -28,6 +28,11 @@ export declare class FaceLandmarks implements IFaceLandmarks {
      * it's current shift.
      * @returns The bounding box of the aligned face.
      */
-    align(detection?: FaceDetection | Rect): Rect;
+    align(detection?: FaceDetection | IRect | IBoundingBox | null, options?: {
+        useDlibAlignment?: boolean;
+        minBoxPadding?: number;
+    }): Box;
+    private alignDlib;
+    private alignMinBbox;
     protected getRefPointsForAlignment(): Point[];
 }

build/commonjs/classes/FaceLandmarks.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
 var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
+var minBbox_1 = require("../minBbox");
 var FaceDetection_1 = require("./FaceDetection");
 // face alignment constants
 var relX = 0.5;
@@ -62,13 +63,21 @@ var FaceLandmarks = /** @class */ (function () {
      * it's current shift.
      * @returns The bounding box of the aligned face.
      */
-    FaceLandmarks.prototype.align = function (detection) {
+    FaceLandmarks.prototype.align = function (detection, options) {
+        if (options === void 0) { options = {}; }
         if (detection) {
             var box = detection instanceof FaceDetection_1.FaceDetection
                 ? detection.box.floor()
-                : detection;
-            return this.shiftBy(box.x, box.y).align();
+                : new tfjs_image_recognition_base_1.Box(detection);
+            return this.shiftBy(box.x, box.y).align(null, options);
         }
+        var _a = Object.assign({}, { useDlibAlignment: false, minBoxPadding: 0.2 }, options), useDlibAlignment = _a.useDlibAlignment, minBoxPadding = _a.minBoxPadding;
+        if (useDlibAlignment) {
+            return this.alignDlib();
+        }
+        return this.alignMinBbox(minBoxPadding);
+    };
+    FaceLandmarks.prototype.alignDlib = function () {
         var centers = this.getRefPointsForAlignment();
         var leftEyeCenter = centers[0], rightEyeCenter = centers[1], mouthCenter = centers[2];
         var distToMouth = function (pt) { return mouthCenter.sub(pt).magnitude(); };
@@ -80,6 +89,10 @@ var FaceLandmarks = /** @class */ (function () {
         var y = Math.floor(Math.max(0, refPoint.y - (relY * size)));
         return new tfjs_image_recognition_base_1.Rect(x, y, Math.min(size, this.imageWidth + x), Math.min(size, this.imageHeight + y));
     };
+    FaceLandmarks.prototype.alignMinBbox = function (padding) {
+        var box = minBbox_1.minBbox(this.positions);
+        return box.pad(box.width * padding, box.height * padding);
+    };
     FaceLandmarks.prototype.getRefPointsForAlignment = function () {
         throw new Error('getRefPointsForAlignment not implemented by base class');
     };

build/commonjs/classes/FaceLandmarks.js.map

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\ No newline at end of file

build/commonjs/common/depthwiseSeparableConv.js.map

+{"version":3,"file":"depthwiseSeparableConv.js","sourceRoot":"","sources":["../../../src/common/depthwiseSeparableConv.ts"],"names":[],"mappings":";;AAAA,0CAA4C;AAG5C,SAAgB,sBAAsB,CACpC,CAAc,EACd,MAAoD,EACpD,MAAwB;IAExB,OAAO,EAAE,CAAC,IAAI,CAAC;QACb,IAAI,GAAG,GAAG,EAAE,CAAC,eAAe,CAAC,CAAC,EAAE,MAAM,CAAC,gBAAgB,EAAE,MAAM,CAAC,gBAAgB,EAAE,MAAM,EAAE,MAAM,CAAC,CAAA;QACjG,GAAG,GAAG,EAAE,CAAC,GAAG,CAAC,GAAG,EAAE,MAAM,CAAC,IAAI,CAAC,CAAA;QAC9B,OAAO,GAAG,CAAA;IACZ,CAAC,CAAC,CAAA;AACJ,CAAC;AAVD,wDAUC"}
\ No newline at end of file

build/commonjs/common/loadConvParamsFactory.d.ts

+import { TfjsImageRecognitionBase } from 'tfjs-image-recognition-base';
+export declare function loadConvParamsFactory(extractWeightEntry: <T>(originalPath: string, paramRank: number) => T): (prefix: string) => TfjsImageRecognitionBase.ConvParams;

build/commonjs/common/loadConvParamsFactory.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+function loadConvParamsFactory(extractWeightEntry) {
+    return function (prefix) {
+        var filters = extractWeightEntry(prefix + "/filters", 4);
+        var bias = extractWeightEntry(prefix + "/bias", 1);
+        return { filters: filters, bias: bias };
+    };
+}
+exports.loadConvParamsFactory = loadConvParamsFactory;
+//# sourceMappingURL=loadConvParamsFactory.js.map
\ No newline at end of file

build/commonjs/common/loadConvParamsFactory.js.map

+{"version":3,"file":"loadConvParamsFactory.js","sourceRoot":"","sources":["../../../src/common/loadConvParamsFactory.ts"],"names":[],"mappings":";;AAGA,SAAgB,qBAAqB,CAAC,kBAAqE;IACzG,OAAO,UAAS,MAAc;QAC5B,IAAM,OAAO,GAAG,kBAAkB,CAAiB,MAAM,aAAU,EAAE,CAAC,CAAC,CAAA;QACvE,IAAM,IAAI,GAAG,kBAAkB,CAAiB,MAAM,UAAO,EAAE,CAAC,CAAC,CAAA;QAEjE,OAAO,EAAE,OAAO,SAAA,EAAE,IAAI,MAAA,EAAE,CAAA;IAC1B,CAAC,CAAA;AACH,CAAC;AAPD,sDAOC"}
\ No newline at end of file

build/commonjs/dom/drawContour.js.map

-{"version":3,"file":"drawContour.js","sourceRoot":"","sources":["../../../src/dom/drawContour.ts"],"names":[],"mappings":";;AAEA,SAAgB,WAAW,CACzB,GAA6B,EAC7B,MAAe,EACf,QAAyB;IAAzB,yBAAA,EAAA,gBAAyB;IAEzB,GAAG,CAAC,SAAS,EAAE,CAAA;IAEf,MAAM,CAAC,KAAK,CAAC,CAAC,CAAC,CAAC,OAAO,CAAC,UAAC,EAAQ,EAAE,OAAO;YAAf,QAAC,EAAE,QAAC;QAC7B,IAAM,IAAI,GAAG,MAAM,CAAC,OAAO,CAAC,CAAA;QAC5B,GAAG,CAAC,MAAM,CAAC,IAAI,CAAC,CAAC,EAAE,IAAI,CAAC,CAAC,CAAC,CAAA;QAC1B,GAAG,CAAC,MAAM,CAAC,CAAC,EAAE,CAAC,CAAC,CAAA;IAClB,CAAC,CAAC,CAAA;IAEF,IAAI,QAAQ,EAAE;QACZ,IAAM,IAAI,GAAG,MAAM,CAAC,MAAM,CAAC,MAAM,GAAG,CAAC,CAAC,CAAA;QACtC,IAAM,EAAE,GAAG,MAAM,CAAC,CAAC,CAAC,CAAA;QACpB,IAAI,CAAC,IAAI,IAAI,CAAC,EAAE,EAAE;YAChB,OAAM;SACP;QAED,GAAG,CAAC,MAAM,CAAC,IAAI,CAAC,CAAC,EAAE,IAAI,CAAC,CAAC,CAAC,CAAA;QAC1B,GAAG,CAAC,MAAM,CAAC,EAAE,CAAC,CAAC,EAAE,EAAE,CAAC,CAAC,CAAC,CAAA;KACvB;IAED,GAAG,CAAC,MAAM,EAAE,CAAA;AACd,CAAC;AAzBD,kCAyBC"}
\ No newline at end of file

build/commonjs/dom/drawFaceExpressions.d.ts

-import { DrawFaceExpressionsInput, DrawFaceExpressionsOptions } from './types';
-export declare function drawFaceExpressions(canvasArg: string | HTMLCanvasElement, faceExpressions: DrawFaceExpressionsInput | DrawFaceExpressionsInput[], options?: DrawFaceExpressionsOptions): void;

build/commonjs/dom/drawFaceExpressions.js

-"use strict";
-Object.defineProperty(exports, "__esModule", { value: true });
-var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
-function drawFaceExpressions(canvasArg, faceExpressions, options) {
-    var canvas = tfjs_image_recognition_base_1.resolveInput(canvasArg);
-    if (!(canvas instanceof tfjs_image_recognition_base_1.env.getEnv().Canvas)) {
-        throw new Error('drawFaceExpressions - expected canvas to be of type: HTMLCanvasElement');
-    }
-    var drawOptions = Object.assign(tfjs_image_recognition_base_1.getDefaultDrawOptions(options), (options || {}));
-    var ctx = tfjs_image_recognition_base_1.getContext2dOrThrow(canvas);
-    var _a = drawOptions.primaryColor, primaryColor = _a === void 0 ? 'red' : _a, _b = drawOptions.secondaryColor, secondaryColor = _b === void 0 ? 'blue' : _b, _c = drawOptions.primaryFontSize, primaryFontSize = _c === void 0 ? 22 : _c, _d = drawOptions.secondaryFontSize, secondaryFontSize = _d === void 0 ? 16 : _d, _e = drawOptions.minConfidence, minConfidence = _e === void 0 ? 0.2 : _e;
-    var faceExpressionsArray = Array.isArray(faceExpressions)
-        ? faceExpressions
-        : [faceExpressions];
-    faceExpressionsArray.forEach(function (_a) {
-        var position = _a.position, expressions = _a.expressions;
-        var x = position.x, y = position.y;
-        var height = position.height || 0;
-        var sorted = expressions.sort(function (a, b) { return b.probability - a.probability; });
-        var resultsToDisplay = sorted.filter(function (expr) { return expr.probability > minConfidence; });
-        var offset = (y + height + resultsToDisplay.length * primaryFontSize) > canvas.height
-            ? -(resultsToDisplay.length * primaryFontSize)
-            : 0;
-        resultsToDisplay.forEach(function (expr, i) {
-            var text = expr.expression + " (" + tfjs_image_recognition_base_1.round(expr.probability) + ")";
-            tfjs_image_recognition_base_1.drawText(ctx, x, y + height + (i * primaryFontSize) + offset, text, {
-                textColor: i === 0 ? primaryColor : secondaryColor,
-                fontSize: i === 0 ? primaryFontSize : secondaryFontSize
-            });
-        });
-    });
-}
-exports.drawFaceExpressions = drawFaceExpressions;
-//# sourceMappingURL=drawFaceExpressions.js.map
\ No newline at end of file

build/commonjs/dom/drawFaceExpressions.js.map

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\ No newline at end of file

build/commonjs/dom/drawLandmarks.d.ts

-import { FaceLandmarks } from '../classes/FaceLandmarks';
-import { DrawLandmarksOptions } from './types';
-export declare function drawLandmarks(canvasArg: string | HTMLCanvasElement, faceLandmarks: FaceLandmarks | FaceLandmarks[], options?: DrawLandmarksOptions): void;

build/commonjs/dom/drawLandmarks.js

-"use strict";
-Object.defineProperty(exports, "__esModule", { value: true });
-var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
-var FaceLandmarks68_1 = require("../classes/FaceLandmarks68");
-var drawContour_1 = require("./drawContour");
-function drawLandmarks(canvasArg, faceLandmarks, options) {
-    var canvas = tfjs_image_recognition_base_1.resolveInput(canvasArg);
-    if (!(canvas instanceof tfjs_image_recognition_base_1.env.getEnv().Canvas)) {
-        throw new Error('drawLandmarks - expected canvas to be of type: HTMLCanvasElement');
-    }
-    var drawOptions = Object.assign(tfjs_image_recognition_base_1.getDefaultDrawOptions(options), (options || {}));
-    var drawLines = Object.assign({ drawLines: false }, (options || {})).drawLines;
-    var ctx = tfjs_image_recognition_base_1.getContext2dOrThrow(canvas);
-    var lineWidth = drawOptions.lineWidth, _a = drawOptions.color, color = _a === void 0 ? 'blue' : _a;
-    var faceLandmarksArray = Array.isArray(faceLandmarks) ? faceLandmarks : [faceLandmarks];
-    faceLandmarksArray.forEach(function (landmarks) {
-        if (drawLines && landmarks instanceof FaceLandmarks68_1.FaceLandmarks68) {
-            ctx.strokeStyle = color;
-            ctx.lineWidth = lineWidth;
-            drawContour_1.drawContour(ctx, landmarks.getJawOutline());
-            drawContour_1.drawContour(ctx, landmarks.getLeftEyeBrow());
-            drawContour_1.drawContour(ctx, landmarks.getRightEyeBrow());
-            drawContour_1.drawContour(ctx, landmarks.getNose());
-            drawContour_1.drawContour(ctx, landmarks.getLeftEye(), true);
-            drawContour_1.drawContour(ctx, landmarks.getRightEye(), true);
-            drawContour_1.drawContour(ctx, landmarks.getMouth(), true);
-            return;
-        }
-        // else draw points
-        var ptOffset = lineWidth / 2;
-        ctx.fillStyle = color;
-        landmarks.positions.forEach(function (pt) { return ctx.fillRect(pt.x - ptOffset, pt.y - ptOffset, lineWidth, lineWidth); });
-    });
-}
-exports.drawLandmarks = drawLandmarks;
-//# sourceMappingURL=drawLandmarks.js.map
\ No newline at end of file

build/commonjs/dom/drawLandmarks.js.map

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\ No newline at end of file

build/commonjs/dom/index.d.ts

-export * from './drawContour';
-export * from './drawLandmarks';
-export * from './drawFaceExpressions';
 export * from './extractFaces';
 export * from './extractFaceTensors';
-export * from './types';

build/commonjs/dom/index.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
 var tslib_1 = require("tslib");
-tslib_1.__exportStar(require("./drawContour"), exports);
-tslib_1.__exportStar(require("./drawLandmarks"), exports);
-tslib_1.__exportStar(require("./drawFaceExpressions"), exports);
 tslib_1.__exportStar(require("./extractFaces"), exports);
 tslib_1.__exportStar(require("./extractFaceTensors"), exports);
 //# sourceMappingURL=index.js.map
\ No newline at end of file

build/commonjs/dom/index.js.map

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+{"version":3,"file":"index.js","sourceRoot":"","sources":["../../../src/dom/index.ts"],"names":[],"mappings":";;;AAAA,yDAA8B;AAC9B,+DAAoC"}
\ No newline at end of file

build/commonjs/dom/types.d.ts

-import { IPoint, IRect } from 'tfjs-image-recognition-base';
-import { WithFaceExpressions } from '../factories/WithFaceExpressions';
-export declare type DrawLandmarksOptions = {
-    lineWidth?: number;
-    color?: string;
-    drawLines?: boolean;
-};
-export declare type DrawFaceExpressionsOptions = {
-    primaryColor?: string;
-    secondaryColor?: string;
-    primaryFontSize?: number;
-    secondaryFontSize?: number;
-    minConfidence?: number;
-};
-export declare type DrawFaceExpressionsInput = WithFaceExpressions<{
-    position: IPoint | IRect;
-}>;

build/commonjs/dom/types.js.map

-{"version":3,"file":"types.js","sourceRoot":"","sources":["../../../src/dom/types.ts"],"names":[],"mappings":""}
\ No newline at end of file

build/commonjs/draw/DrawFaceLandmarks.d.ts

+import { FaceLandmarks } from '../classes/FaceLandmarks';
+import { WithFaceDetection } from '../factories/WithFaceDetection';
+import { WithFaceLandmarks } from '../factories/WithFaceLandmarks';
+export interface IDrawFaceLandmarksOptions {
+    drawLines?: boolean;
+    drawPoints?: boolean;
+    lineWidth?: number;
+    pointSize?: number;
+    lineColor?: string;
+    pointColor?: string;
+}
+export declare class DrawFaceLandmarksOptions {
+    drawLines: boolean;
+    drawPoints: boolean;
+    lineWidth: number;
+    pointSize: number;
+    lineColor: string;
+    pointColor: string;
+    constructor(options?: IDrawFaceLandmarksOptions);
+}
+export declare class DrawFaceLandmarks {
+    faceLandmarks: FaceLandmarks;
+    options: DrawFaceLandmarksOptions;
+    constructor(faceLandmarks: FaceLandmarks, options?: IDrawFaceLandmarksOptions);
+    draw(canvasArg: string | HTMLCanvasElement | CanvasRenderingContext2D): void;
+}
+export declare type DrawFaceLandmarksInput = FaceLandmarks | WithFaceLandmarks<WithFaceDetection<{}>>;
+export declare function drawFaceLandmarks(canvasArg: string | HTMLCanvasElement, faceLandmarks: DrawFaceLandmarksInput | Array<DrawFaceLandmarksInput>): void;

build/commonjs/draw/DrawFaceLandmarks.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
+var FaceLandmarks_1 = require("../classes/FaceLandmarks");
+var FaceLandmarks68_1 = require("../classes/FaceLandmarks68");
+var WithFaceLandmarks_1 = require("../factories/WithFaceLandmarks");
+var drawContour_1 = require("./drawContour");
+var DrawFaceLandmarksOptions = /** @class */ (function () {
+    function DrawFaceLandmarksOptions(options) {
+        if (options === void 0) { options = {}; }
+        var _a = options.drawLines, drawLines = _a === void 0 ? true : _a, _b = options.drawPoints, drawPoints = _b === void 0 ? true : _b, lineWidth = options.lineWidth, lineColor = options.lineColor, pointSize = options.pointSize, pointColor = options.pointColor;
+        this.drawLines = drawLines;
+        this.drawPoints = drawPoints;
+        this.lineWidth = lineWidth || 1;
+        this.pointSize = pointSize || 2;
+        this.lineColor = lineColor || 'rgba(0, 255, 255, 1)';
+        this.pointColor = pointColor || 'rgba(255, 0, 255, 1)';
+    }
+    return DrawFaceLandmarksOptions;
+}());
+exports.DrawFaceLandmarksOptions = DrawFaceLandmarksOptions;
+var DrawFaceLandmarks = /** @class */ (function () {
+    function DrawFaceLandmarks(faceLandmarks, options) {
+        if (options === void 0) { options = {}; }
+        this.faceLandmarks = faceLandmarks;
+        this.options = new DrawFaceLandmarksOptions(options);
+    }
+    DrawFaceLandmarks.prototype.draw = function (canvasArg) {
+        var ctx = tfjs_image_recognition_base_1.getContext2dOrThrow(canvasArg);
+        var _a = this.options, drawLines = _a.drawLines, drawPoints = _a.drawPoints, lineWidth = _a.lineWidth, lineColor = _a.lineColor, pointSize = _a.pointSize, pointColor = _a.pointColor;
+        if (drawLines && this.faceLandmarks instanceof FaceLandmarks68_1.FaceLandmarks68) {
+            ctx.strokeStyle = lineColor;
+            ctx.lineWidth = lineWidth;
+            drawContour_1.drawContour(ctx, this.faceLandmarks.getJawOutline());
+            drawContour_1.drawContour(ctx, this.faceLandmarks.getLeftEyeBrow());
+            drawContour_1.drawContour(ctx, this.faceLandmarks.getRightEyeBrow());
+            drawContour_1.drawContour(ctx, this.faceLandmarks.getNose());
+            drawContour_1.drawContour(ctx, this.faceLandmarks.getLeftEye(), true);
+            drawContour_1.drawContour(ctx, this.faceLandmarks.getRightEye(), true);
+            drawContour_1.drawContour(ctx, this.faceLandmarks.getMouth(), true);
+        }
+        if (drawPoints) {
+            ctx.strokeStyle = pointColor;
+            ctx.fillStyle = pointColor;
+            var drawPoint = function (pt) {
+                ctx.beginPath();
+                ctx.arc(pt.x, pt.y, pointSize, 0, 2 * Math.PI);
+                ctx.fill();
+            };
+            this.faceLandmarks.positions.forEach(drawPoint);
+        }
+    };
+    return DrawFaceLandmarks;
+}());
+exports.DrawFaceLandmarks = DrawFaceLandmarks;
+function drawFaceLandmarks(canvasArg, faceLandmarks) {
+    var faceLandmarksArray = Array.isArray(faceLandmarks) ? faceLandmarks : [faceLandmarks];
+    faceLandmarksArray.forEach(function (f) {
+        var landmarks = f instanceof FaceLandmarks_1.FaceLandmarks
+            ? f
+            : (WithFaceLandmarks_1.isWithFaceLandmarks(f) ? f.landmarks : undefined);
+        if (!landmarks) {
+            throw new Error('drawFaceLandmarks - expected faceExpressions to be FaceLandmarks | WithFaceLandmarks<WithFaceDetection<{}>> or array thereof');
+        }
+        new DrawFaceLandmarks(landmarks).draw(canvasArg);
+    });
+}
+exports.drawFaceLandmarks = drawFaceLandmarks;
+//# sourceMappingURL=DrawFaceLandmarks.js.map
\ No newline at end of file

build/commonjs/draw/DrawFaceLandmarks.js.map

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\ No newline at end of file

build/commonjs/draw/drawContour.js.map

+{"version":3,"file":"drawContour.js","sourceRoot":"","sources":["../../../src/draw/drawContour.ts"],"names":[],"mappings":";;AAEA,SAAgB,WAAW,CACzB,GAA6B,EAC7B,MAAe,EACf,QAAyB;IAAzB,yBAAA,EAAA,gBAAyB;IAEzB,GAAG,CAAC,SAAS,EAAE,CAAA;IAEf,MAAM,CAAC,KAAK,CAAC,CAAC,CAAC,CAAC,OAAO,CAAC,UAAC,EAAQ,EAAE,OAAO;YAAf,QAAC,EAAE,QAAC;QAC7B,IAAM,IAAI,GAAG,MAAM,CAAC,OAAO,CAAC,CAAA;QAC5B,GAAG,CAAC,MAAM,CAAC,IAAI,CAAC,CAAC,EAAE,IAAI,CAAC,CAAC,CAAC,CAAA;QAC1B,GAAG,CAAC,MAAM,CAAC,CAAC,EAAE,CAAC,CAAC,CAAA;IAClB,CAAC,CAAC,CAAA;IAEF,IAAI,QAAQ,EAAE;QACZ,IAAM,IAAI,GAAG,MAAM,CAAC,MAAM,CAAC,MAAM,GAAG,CAAC,CAAC,CAAA;QACtC,IAAM,EAAE,GAAG,MAAM,CAAC,CAAC,CAAC,CAAA;QACpB,IAAI,CAAC,IAAI,IAAI,CAAC,EAAE,EAAE;YAChB,OAAM;SACP;QAED,GAAG,CAAC,MAAM,CAAC,IAAI,CAAC,CAAC,EAAE,IAAI,CAAC,CAAC,CAAC,CAAA;QAC1B,GAAG,CAAC,MAAM,CAAC,EAAE,CAAC,CAAC,EAAE,EAAE,CAAC,CAAC,CAAC,CAAA;KACvB;IAED,GAAG,CAAC,MAAM,EAAE,CAAA;AACd,CAAC;AAzBD,kCAyBC"}
\ No newline at end of file

build/commonjs/draw/drawDetections.d.ts

+import { IBoundingBox, IRect } from 'tfjs-image-recognition-base';
+import { FaceDetection } from '../classes/FaceDetection';
+import { WithFaceDetection } from '../factories/WithFaceDetection';
+export declare type TDrawDetectionsInput = IRect | IBoundingBox | FaceDetection | WithFaceDetection<{}>;
+export declare function drawDetections(canvasArg: string | HTMLCanvasElement, detections: TDrawDetectionsInput | Array<TDrawDetectionsInput>): void;

build/commonjs/draw/drawDetections.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
+var FaceDetection_1 = require("../classes/FaceDetection");
+var WithFaceDetection_1 = require("../factories/WithFaceDetection");
+function drawDetections(canvasArg, detections) {
+    var detectionsArray = Array.isArray(detections) ? detections : [detections];
+    detectionsArray.forEach(function (det) {
+        var score = det instanceof FaceDetection_1.FaceDetection
+            ? det.score
+            : (WithFaceDetection_1.isWithFaceDetection(det) ? det.detection.score : undefined);
+        var box = det instanceof FaceDetection_1.FaceDetection
+            ? det.box
+            : (WithFaceDetection_1.isWithFaceDetection(det) ? det.detection.box : new tfjs_image_recognition_base_1.Box(det));
+        var label = score ? "" + tfjs_image_recognition_base_1.round(score) : undefined;
+        new tfjs_image_recognition_base_1.draw.DrawBox(box, { label: label }).draw(canvasArg);
+    });
+}
+exports.drawDetections = drawDetections;
+//# sourceMappingURL=drawDetections.js.map
\ No newline at end of file

build/commonjs/draw/drawDetections.js.map

+{"version":3,"file":"drawDetections.js","sourceRoot":"","sources":["../../../src/draw/drawDetections.ts"],"names":[],"mappings":";;AAAA,2EAAoF;AAEpF,0DAAyD;AACzD,oEAAwF;AAIxF,SAAgB,cAAc,CAC5B,SAAqC,EACrC,UAA8D;IAE9D,IAAM,eAAe,GAAG,KAAK,CAAC,OAAO,CAAC,UAAU,CAAC,CAAC,CAAC,CAAC,UAAU,CAAC,CAAC,CAAC,CAAC,UAAU,CAAC,CAAA;IAE7E,eAAe,CAAC,OAAO,CAAC,UAAA,GAAG;QACzB,IAAM,KAAK,GAAG,GAAG,YAAY,6BAAa;YACxC,CAAC,CAAC,GAAG,CAAC,KAAK;YACX,CAAC,CAAC,CAAC,uCAAmB,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC,GAAG,CAAC,SAAS,CAAC,KAAK,CAAC,CAAC,CAAC,SAAS,CAAC,CAAA;QAEhE,IAAM,GAAG,GAAG,GAAG,YAAY,6BAAa;YACtC,CAAC,CAAC,GAAG,CAAC,GAAG;YACT,CAAC,CAAC,CAAC,uCAAmB,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC,GAAG,CAAC,SAAS,CAAC,GAAG,CAAC,CAAC,CAAC,IAAI,iCAAG,CAAC,GAAG,CAAC,CAAC,CAAA;QAEjE,IAAM,KAAK,GAAG,KAAK,CAAC,CAAC,CAAC,KAAG,mCAAK,CAAC,KAAK,CAAG,CAAC,CAAC,CAAC,SAAS,CAAA;QACnD,IAAI,kCAAI,CAAC,OAAO,CAAC,GAAG,EAAE,EAAE,KAAK,OAAA,EAAE,CAAC,CAAC,IAAI,CAAC,SAAS,CAAC,CAAA;IAClD,CAAC,CAAC,CAAA;AACJ,CAAC;AAlBD,wCAkBC"}
\ No newline at end of file

build/commonjs/draw/drawFaceExpressions.d.ts

+import { IPoint } from 'tfjs-image-recognition-base';
+import { FaceExpressions } from '../faceExpressionNet';
+import { WithFaceExpressions } from '../factories/WithFaceExpressions';
+export declare type DrawFaceExpressionsInput = FaceExpressions | WithFaceExpressions<{}>;
+export declare function drawFaceExpressions(canvasArg: string | HTMLCanvasElement, faceExpressions: DrawFaceExpressionsInput | Array<DrawFaceExpressionsInput>, minConfidence?: number, textFieldAnchor?: IPoint): void;

build/commonjs/draw/drawFaceExpressions.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
+var faceExpressionNet_1 = require("../faceExpressionNet");
+var WithFaceDetection_1 = require("../factories/WithFaceDetection");
+var WithFaceExpressions_1 = require("../factories/WithFaceExpressions");
+function drawFaceExpressions(canvasArg, faceExpressions, minConfidence, textFieldAnchor) {
+    if (minConfidence === void 0) { minConfidence = 0.1; }
+    var faceExpressionsArray = Array.isArray(faceExpressions) ? faceExpressions : [faceExpressions];
+    faceExpressionsArray.forEach(function (e) {
+        var expr = e instanceof faceExpressionNet_1.FaceExpressions
+            ? e
+            : (WithFaceExpressions_1.isWithFaceExpressions(e) ? e.expressions : undefined);
+        if (!expr) {
+            throw new Error('drawFaceExpressions - expected faceExpressions to be FaceExpressions | WithFaceExpressions<{}> or array thereof');
+        }
+        var sorted = expr.asSortedArray();
+        var resultsToDisplay = sorted.filter(function (expr) { return expr.probability > minConfidence; });
+        var anchor = WithFaceDetection_1.isWithFaceDetection(e)
+            ? e.detection.box.bottomLeft
+            : (textFieldAnchor || new tfjs_image_recognition_base_1.Point(0, 0));
+        var drawTextField = new tfjs_image_recognition_base_1.draw.DrawTextField(resultsToDisplay.map(function (expr) { return expr.expression + " (" + tfjs_image_recognition_base_1.round(expr.probability) + ")"; }), anchor);
+        drawTextField.draw(canvasArg);
+    });
+}
+exports.drawFaceExpressions = drawFaceExpressions;
+//# sourceMappingURL=drawFaceExpressions.js.map
\ No newline at end of file

build/commonjs/draw/drawFaceExpressions.js.map

+{"version":3,"file":"drawFaceExpressions.js","sourceRoot":"","sources":["../../../src/draw/drawFaceExpressions.ts"],"names":[],"mappings":";;AAAA,2EAAyE;AAEzE,0DAAuD;AACvD,oEAAqE;AACrE,wEAA8F;AAI9F,SAAgB,mBAAmB,CACjC,SAAqC,EACrC,eAA2E,EAC3E,aAAmB,EACnB,eAAwB;IADxB,8BAAA,EAAA,mBAAmB;IAGnB,IAAM,oBAAoB,GAAG,KAAK,CAAC,OAAO,CAAC,eAAe,CAAC,CAAC,CAAC,CAAC,eAAe,CAAC,CAAC,CAAC,CAAC,eAAe,CAAC,CAAA;IAEjG,oBAAoB,CAAC,OAAO,CAAC,UAAA,CAAC;QAC5B,IAAM,IAAI,GAAG,CAAC,YAAY,mCAAe;YACvC,CAAC,CAAC,CAAC;YACH,CAAC,CAAC,CAAC,2CAAqB,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,WAAW,CAAC,CAAC,CAAC,SAAS,CAAC,CAAA;QAC1D,IAAI,CAAC,IAAI,EAAE;YACT,MAAM,IAAI,KAAK,CAAC,iHAAiH,CAAC,CAAA;SACnI;QAED,IAAM,MAAM,GAAG,IAAI,CAAC,aAAa,EAAE,CAAA;QACnC,IAAM,gBAAgB,GAAG,MAAM,CAAC,MAAM,CAAC,UAAA,IAAI,IAAI,OAAA,IAAI,CAAC,WAAW,GAAG,aAAa,EAAhC,CAAgC,CAAC,CAAA;QAEhF,IAAM,MAAM,GAAG,uCAAmB,CAAC,CAAC,CAAC;YACnC,CAAC,CAAC,CAAC,CAAC,SAAS,CAAC,GAAG,CAAC,UAAU;YAC5B,CAAC,CAAC,CAAC,eAAe,IAAI,IAAI,mCAAK,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAA;QAExC,IAAM,aAAa,GAAG,IAAI,kCAAI,CAAC,aAAa,CAC1C,gBAAgB,CAAC,GAAG,CAAC,UAAA,IAAI,IAAI,OAAG,IAAI,CAAC,UAAU,UAAK,mCAAK,CAAC,IAAI,CAAC,WAAW,CAAC,MAAG,EAAjD,CAAiD,CAAC,EAC/E,MAAM,CACP,CAAA;QACD,aAAa,CAAC,IAAI,CAAC,SAAS,CAAC,CAAA;IAC/B,CAAC,CAAC,CAAA;AACJ,CAAC;AA7BD,kDA6BC"}
\ No newline at end of file

build/commonjs/draw/index.d.ts

+export * from './drawContour';
+export * from './drawDetections';
+export * from './drawFaceExpressions';
+export * from './DrawFaceLandmarks';

build/commonjs/draw/index.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+var tslib_1 = require("tslib");
+tslib_1.__exportStar(require("./drawContour"), exports);
+tslib_1.__exportStar(require("./drawDetections"), exports);
+tslib_1.__exportStar(require("./drawFaceExpressions"), exports);
+tslib_1.__exportStar(require("./DrawFaceLandmarks"), exports);
+//# sourceMappingURL=index.js.map
\ No newline at end of file

build/commonjs/draw/index.js.map

+{"version":3,"file":"index.js","sourceRoot":"","sources":["../../../src/draw/index.ts"],"names":[],"mappings":";;;AAAA,wDAA6B;AAC7B,2DAAgC;AAChC,gEAAqC;AACrC,8DAAmC"}
\ No newline at end of file

build/commonjs/faceExpressionNet/FaceExpressionNet.d.ts

@@ -3,14 +3,12 @@ import { NetInput, TNetInput } from 'tfjs-image-recognition-base';
 import { FaceFeatureExtractor } from '../faceFeatureExtractor/FaceFeatureExtractor';
 import { FaceFeatureExtractorParams } from '../faceFeatureExtractor/types';
 import { FaceProcessor } from '../faceProcessor/FaceProcessor';
-import { FaceExpressionPrediction } from './types';
+import { FaceExpressions } from './FaceExpressions';
 export declare class FaceExpressionNet extends FaceProcessor<FaceFeatureExtractorParams> {
-    static getFaceExpressionLabel(faceExpression: string): number;
-    static decodeProbabilites(probabilities: number[] | Float32Array): FaceExpressionPrediction[];
     constructor(faceFeatureExtractor?: FaceFeatureExtractor);
     forwardInput(input: NetInput | tf.Tensor4D): tf.Tensor2D;
     forward(input: TNetInput): Promise<tf.Tensor2D>;
-    predictExpressions(input: TNetInput): Promise<FaceExpressionPrediction[] | FaceExpressionPrediction[][]>;
+    predictExpressions(input: TNetInput): Promise<FaceExpressions | FaceExpressions[]>;
     protected getDefaultModelName(): string;
     protected getClassifierChannelsIn(): number;
     protected getClassifierChannelsOut(): number;

build/commonjs/faceExpressionNet/FaceExpressionNet.js

@@ -5,27 +5,13 @@ var tf = require("@tensorflow/tfjs-core");
 var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
 var FaceFeatureExtractor_1 = require("../faceFeatureExtractor/FaceFeatureExtractor");
 var FaceProcessor_1 = require("../faceProcessor/FaceProcessor");
-var types_1 = require("./types");
+var FaceExpressions_1 = require("./FaceExpressions");
 var FaceExpressionNet = /** @class */ (function (_super) {
     tslib_1.__extends(FaceExpressionNet, _super);
     function FaceExpressionNet(faceFeatureExtractor) {
         if (faceFeatureExtractor === void 0) { faceFeatureExtractor = new FaceFeatureExtractor_1.FaceFeatureExtractor(); }
         return _super.call(this, 'FaceExpressionNet', faceFeatureExtractor) || this;
     }
-    FaceExpressionNet.getFaceExpressionLabel = function (faceExpression) {
-        var label = types_1.faceExpressionLabels[faceExpression];
-        if (typeof label !== 'number') {
-            throw new Error("getFaceExpressionLabel - no label for faceExpression: " + faceExpression);
-        }
-        return label;
-    };
-    FaceExpressionNet.decodeProbabilites = function (probabilities) {
-        if (probabilities.length !== 7) {
-            throw new Error("decodeProbabilites - expected probabilities.length to be 7, have: " + probabilities.length);
-        }
-        return Object.keys(types_1.faceExpressionLabels)
-            .map(function (expression) { return ({ expression: expression, probability: probabilities[types_1.faceExpressionLabels[expression]] }); });
-    };
     FaceExpressionNet.prototype.forwardInput = function (input) {
         var _this = this;
         return tf.tidy(function () { return tf.softmax(_this.runNet(input)); });
@@ -71,7 +57,7 @@ var FaceExpressionNet = /** @class */ (function (_super) {
                         probabilitesByBatch = _a.sent();
                         out.dispose();
                         predictionsByBatch = probabilitesByBatch
-                            .map(function (propablities) { return FaceExpressionNet.decodeProbabilites(propablities); });
+                            .map(function (probabilites) { return new FaceExpressions_1.FaceExpressions(probabilites); });
                         return [2 /*return*/, netInput.isBatchInput
                                 ? predictionsByBatch
                                 : predictionsByBatch[0]];

build/commonjs/faceExpressionNet/FaceExpressionNet.js.map

-{"version":3,"file":"FaceExpressionNet.js","sourceRoot":"","sources":["../../../src/faceExpressionNet/FaceExpressionNet.ts"],"names":[],"mappings":";;;AAAA,0CAA4C;AAC5C,2EAA8E;AAE9E,qFAAoF;AAEpF,gEAA+D;AAC/D,iCAAyF;AAEzF;IAAuC,6CAAyC;IAqB9E,2BAAY,oBAAuE;QAAvE,qCAAA,EAAA,2BAAiD,2CAAoB,EAAE;eACjF,kBAAM,mBAAmB,EAAE,oBAAoB,CAAC;IAClD,CAAC;IArBa,wCAAsB,GAApC,UAAqC,cAAsB;QACzD,IAAM,KAAK,GAAG,4BAAoB,CAAC,cAAc,CAAC,CAAA;QAElD,IAAI,OAAO,KAAK,KAAK,QAAQ,EAAE;YAC7B,MAAM,IAAI,KAAK,CAAC,2DAAyD,cAAgB,CAAC,CAAA;SAC3F;QAED,OAAO,KAAK,CAAA;IACd,CAAC;IAEa,oCAAkB,GAAhC,UAAiC,aAAsC;QACrE,IAAI,aAAa,CAAC,MAAM,KAAK,CAAC,EAAE;YAC9B,MAAM,IAAI,KAAK,CAAC,uEAAqE,aAAa,CAAC,MAAQ,CAAC,CAAA;SAC7G;QAED,OAAQ,MAAM,CAAC,IAAI,CAAC,4BAAoB,CAAsB;aAC3D,GAAG,CAAC,UAAA,UAAU,IAAI,OAAA,CAAC,EAAE,UAAU,YAAA,EAAE,WAAW,EAAE,aAAa,CAAC,4BAAoB,CAAC,UAAU,CAAC,CAAC,EAAE,CAAC,EAA9E,CAA8E,CAAC,CAAA;IACtG,CAAC;IAMM,wCAAY,GAAnB,UAAoB,KAA6B;QAAjD,iBAEC;QADC,OAAO,EAAE,CAAC,IAAI,CAAC,cAAM,OAAA,EAAE,CAAC,OAAO,CAAC,KAAI,CAAC,MAAM,CAAC,KAAK,CAAC,CAAC,EAA9B,CAA8B,CAAC,CAAA;IACtD,CAAC;IAEY,mCAAO,GAApB,UAAqB,KAAgB;;;;;;wBAC5B,KAAA,IAAI,CAAC,YAAY,CAAA;wBAAC,qBAAM,wCAAU,CAAC,KAAK,CAAC,EAAA;4BAAhD,sBAAO,SAAA,IAAI,GAAc,SAAuB,EAAC,EAAA;;;;KAClD;IAEY,8CAAkB,GAA/B,UAAgC,KAAgB;;;;;;4BAC7B,qBAAM,wCAAU,CAAC,KAAK,CAAC,EAAA;;wBAAlC,QAAQ,GAAG,SAAuB;wBAC5B,qBAAM,IAAI,CAAC,YAAY,CAAC,QAAQ,CAAC,EAAA;;wBAAvC,GAAG,GAAG,SAAiC;wBACjB,qBAAM,OAAO,CAAC,GAAG,CAAC,EAAE,CAAC,OAAO,CAAC,GAAG,CAAC,CAAC,GAAG,CAAC,UAAM,CAAC;;;;gDAC1D,qBAAM,CAAC,CAAC,IAAI,EAAE,EAAA;;4CAArB,IAAI,GAAG,SAAc;4CAC3B,CAAC,CAAC,OAAO,EAAE,CAAA;4CACX,sBAAO,IAAI,EAAA;;;iCACZ,CAAC,CAAC,EAAA;;wBAJG,mBAAmB,GAAG,SAIzB;wBACH,GAAG,CAAC,OAAO,EAAE,CAAA;wBAEP,kBAAkB,GAAG,mBAAmB;6BAC3C,GAAG,CAAC,UAAA,YAAY,IAAI,OAAA,iBAAiB,CAAC,kBAAkB,CAAC,YAA4B,CAAC,EAAlE,CAAkE,CAAC,CAAA;wBAE1F,sBAAO,QAAQ,CAAC,YAAY;gCAC1B,CAAC,CAAC,kBAAkB;gCACpB,CAAC,CAAC,kBAAkB,CAAC,CAAC,CAAC,EAAA;;;;KAC1B;IAES,+CAAmB,GAA7B;QACE,OAAO,uBAAuB,CAAA;IAChC,CAAC;IAES,mDAAuB,GAAjC;QACE,OAAO,GAAG,CAAA;IACZ,CAAC;IAES,oDAAwB,GAAlC;QACE,OAAO,CAAC,CAAA;IACV,CAAC;IACH,wBAAC;AAAD,CAAC,AA9DD,CAAuC,6BAAa,GA8DnD;AA9DY,8CAAiB"}
+{"version":3,"file":"FaceExpressionNet.js","sourceRoot":"","sources":["../../../src/faceExpressionNet/FaceExpressionNet.ts"],"names":[],"mappings":";;;AAAA,0CAA4C;AAC5C,2EAA8E;AAE9E,qFAAoF;AAEpF,gEAA+D;AAC/D,qDAAoD;AAEpD;IAAuC,6CAAyC;IAE9E,2BAAY,oBAAuE;QAAvE,qCAAA,EAAA,2BAAiD,2CAAoB,EAAE;eACjF,kBAAM,mBAAmB,EAAE,oBAAoB,CAAC;IAClD,CAAC;IAEM,wCAAY,GAAnB,UAAoB,KAA6B;QAAjD,iBAEC;QADC,OAAO,EAAE,CAAC,IAAI,CAAC,cAAM,OAAA,EAAE,CAAC,OAAO,CAAC,KAAI,CAAC,MAAM,CAAC,KAAK,CAAC,CAAC,EAA9B,CAA8B,CAAC,CAAA;IACtD,CAAC;IAEY,mCAAO,GAApB,UAAqB,KAAgB;;;;;;wBAC5B,KAAA,IAAI,CAAC,YAAY,CAAA;wBAAC,qBAAM,wCAAU,CAAC,KAAK,CAAC,EAAA;4BAAhD,sBAAO,SAAA,IAAI,GAAc,SAAuB,EAAC,EAAA;;;;KAClD;IAEY,8CAAkB,GAA/B,UAAgC,KAAgB;;;;;;4BAC7B,qBAAM,wCAAU,CAAC,KAAK,CAAC,EAAA;;wBAAlC,QAAQ,GAAG,SAAuB;wBAC5B,qBAAM,IAAI,CAAC,YAAY,CAAC,QAAQ,CAAC,EAAA;;wBAAvC,GAAG,GAAG,SAAiC;wBACjB,qBAAM,OAAO,CAAC,GAAG,CAAC,EAAE,CAAC,OAAO,CAAC,GAAG,CAAC,CAAC,GAAG,CAAC,UAAM,CAAC;;;;gDAC1D,qBAAM,CAAC,CAAC,IAAI,EAAE,EAAA;;4CAArB,IAAI,GAAG,SAAc;4CAC3B,CAAC,CAAC,OAAO,EAAE,CAAA;4CACX,sBAAO,IAAI,EAAA;;;iCACZ,CAAC,CAAC,EAAA;;wBAJG,mBAAmB,GAAG,SAIzB;wBACH,GAAG,CAAC,OAAO,EAAE,CAAA;wBAEP,kBAAkB,GAAG,mBAAmB;6BAC3C,GAAG,CAAC,UAAA,YAAY,IAAI,OAAA,IAAI,iCAAe,CAAC,YAA4B,CAAC,EAAjD,CAAiD,CAAC,CAAA;wBAEzE,sBAAO,QAAQ,CAAC,YAAY;gCAC1B,CAAC,CAAC,kBAAkB;gCACpB,CAAC,CAAC,kBAAkB,CAAC,CAAC,CAAC,EAAA;;;;KAC1B;IAES,+CAAmB,GAA7B;QACE,OAAO,uBAAuB,CAAA;IAChC,CAAC;IAES,mDAAuB,GAAjC;QACE,OAAO,GAAG,CAAA;IACZ,CAAC;IAES,oDAAwB,GAAlC;QACE,OAAO,CAAC,CAAA;IACV,CAAC;IACH,wBAAC;AAAD,CAAC,AA3CD,CAAuC,6BAAa,GA2CnD;AA3CY,8CAAiB"}
\ No newline at end of file

build/commonjs/faceExpressionNet/types.d.ts → build/commonjs/faceExpressionNet/FaceExpressions.d.ts

-export declare const faceExpressionLabels: {
+export declare const FACE_EXPRESSION_LABELS: string[];
+export declare class FaceExpressions {
     neutral: number;
     happy: number;
     sad: number;
@@ -6,9 +7,9 @@ export declare const faceExpressionLabels: {
     fearful: number;
     disgusted: number;
     surprised: number;
-};
-export declare type FaceExpression = 'neutral' | 'happy' | 'sad' | 'angry' | 'fearful' | 'disgusted' | 'surprised';
-export declare type FaceExpressionPrediction = {
-    expression: FaceExpression;
-    probability: number;
-};
+    constructor(probabilities: number[] | Float32Array);
+    asSortedArray(): {
+        expression: string;
+        probability: number;
+    }[];
+}

build/commonjs/faceExpressionNet/FaceExpressions.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+exports.FACE_EXPRESSION_LABELS = ['neutral', 'happy', 'sad', 'angry', 'fearful', 'disgusted', 'surprised'];
+var FaceExpressions = /** @class */ (function () {
+    function FaceExpressions(probabilities) {
+        var _this = this;
+        if (probabilities.length !== 7) {
+            throw new Error("FaceExpressions.constructor - expected probabilities.length to be 7, have: " + probabilities.length);
+        }
+        exports.FACE_EXPRESSION_LABELS.forEach(function (expression, idx) {
+            _this[expression] = probabilities[idx];
+        });
+    }
+    FaceExpressions.prototype.asSortedArray = function () {
+        var _this = this;
+        return exports.FACE_EXPRESSION_LABELS
+            .map(function (expression) { return ({ expression: expression, probability: _this[expression] }); })
+            .sort(function (e0, e1) { return e1.probability - e0.probability; });
+    };
+    return FaceExpressions;
+}());
+exports.FaceExpressions = FaceExpressions;
+//# sourceMappingURL=FaceExpressions.js.map
\ No newline at end of file

build/commonjs/faceExpressionNet/FaceExpressions.js.map

+{"version":3,"file":"FaceExpressions.js","sourceRoot":"","sources":["../../../src/faceExpressionNet/FaceExpressions.ts"],"names":[],"mappings":";;AAAa,QAAA,sBAAsB,GAAG,CAAC,SAAS,EAAE,OAAO,EAAE,KAAK,EAAE,OAAO,EAAE,SAAS,EAAE,WAAW,EAAE,WAAW,CAAC,CAAA;AAE/G;IASE,yBAAY,aAAsC;QAAlD,iBAQC;QAPC,IAAI,aAAa,CAAC,MAAM,KAAK,CAAC,EAAE;YAC9B,MAAM,IAAI,KAAK,CAAC,gFAA8E,aAAa,CAAC,MAAQ,CAAC,CAAA;SACtH;QAED,8BAAsB,CAAC,OAAO,CAAC,UAAC,UAAU,EAAE,GAAG;YAC7C,KAAI,CAAC,UAAU,CAAC,GAAG,aAAa,CAAC,GAAG,CAAC,CAAA;QACvC,CAAC,CAAC,CAAA;IACJ,CAAC;IAED,uCAAa,GAAb;QAAA,iBAIC;QAHC,OAAO,8BAAsB;aAC1B,GAAG,CAAC,UAAA,UAAU,IAAI,OAAA,CAAC,EAAE,UAAU,YAAA,EAAE,WAAW,EAAE,KAAI,CAAC,UAAU,CAAW,EAAE,CAAC,EAAzD,CAAyD,CAAC;aAC5E,IAAI,CAAC,UAAC,EAAE,EAAE,EAAE,IAAK,OAAA,EAAE,CAAC,WAAW,GAAG,EAAE,CAAC,WAAW,EAA/B,CAA+B,CAAC,CAAA;IACtD,CAAC;IACH,sBAAC;AAAD,CAAC,AAxBD,IAwBC;AAxBY,0CAAe"}
\ No newline at end of file

build/commonjs/faceExpressionNet/index.d.ts

 export * from './FaceExpressionNet';
-export * from './types';
+export * from './FaceExpressions';

build/commonjs/faceExpressionNet/index.js

@@ -2,5 +2,5 @@
 Object.defineProperty(exports, "__esModule", { value: true });
 var tslib_1 = require("tslib");
 tslib_1.__exportStar(require("./FaceExpressionNet"), exports);
-tslib_1.__exportStar(require("./types"), exports);
+tslib_1.__exportStar(require("./FaceExpressions"), exports);
 //# sourceMappingURL=index.js.map
\ No newline at end of file

build/commonjs/faceExpressionNet/index.js.map

-{"version":3,"file":"index.js","sourceRoot":"","sources":["../../../src/faceExpressionNet/index.ts"],"names":[],"mappings":";;;AAAA,8DAAoC;AACpC,kDAAwB"}
+{"version":3,"file":"index.js","sourceRoot":"","sources":["../../../src/faceExpressionNet/index.ts"],"names":[],"mappings":";;;AAAA,8DAAoC;AACpC,4DAAkC"}
\ No newline at end of file

build/commonjs/faceExpressionNet/types.js

-"use strict";
-Object.defineProperty(exports, "__esModule", { value: true });
-exports.faceExpressionLabels = {
-    neutral: 0,
-    happy: 1,
-    sad: 2,
-    angry: 3,
-    fearful: 4,
-    disgusted: 5,
-    surprised: 6
-};
-//# sourceMappingURL=types.js.map
\ No newline at end of file

build/commonjs/faceExpressionNet/types.js.map

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\ No newline at end of file

build/commonjs/faceFeatureExtractor/denseBlock.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
 var tf = require("@tensorflow/tfjs-core");
-var depthwiseSeparableConv_1 = require("./depthwiseSeparableConv");
+var depthwiseSeparableConv_1 = require("../common/depthwiseSeparableConv");
 function denseBlock3(x, denseBlockParams, isFirstLayer) {
     if (isFirstLayer === void 0) { isFirstLayer = false; }
     return tf.tidy(function () {

build/commonjs/faceFeatureExtractor/denseBlock.js.map

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+{"version":3,"file":"denseBlock.js","sourceRoot":"","sources":["../../../src/faceFeatureExtractor/denseBlock.ts"],"names":[],"mappings":";;AAAA,0CAA4C;AAG5C,2EAA0E;AAG1E,SAAgB,WAAW,CACzB,CAAc,EACd,gBAAmC,EACnC,YAA6B;IAA7B,6BAAA,EAAA,oBAA6B;IAE7B,OAAO,EAAE,CAAC,IAAI,CAAC;QACb,IAAM,IAAI,GAAG,EAAE,CAAC,IAAI,CAClB,YAAY;YACV,CAAC,CAAC,EAAE,CAAC,GAAG,CACN,EAAE,CAAC,MAAM,CAAC,CAAC,EAAG,gBAAgB,CAAC,KAA6C,CAAC,OAAO,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,MAAM,CAAC,EACrG,gBAAgB,CAAC,KAAK,CAAC,IAAI,CAC5B;YACD,CAAC,CAAC,+CAAsB,CAAC,CAAC,EAAE,gBAAgB,CAAC,KAAqD,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAC/F,CAAA;QAChB,IAAM,IAAI,GAAG,+CAAsB,CAAC,IAAI,EAAE,gBAAgB,CAAC,KAAK,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAA;QAEzE,IAAM,GAAG,GAAG,EAAE,CAAC,IAAI,CAAC,EAAE,CAAC,GAAG,CAAC,IAAI,EAAE,IAAI,CAAC,CAAgB,CAAA;QACtD,IAAM,IAAI,GAAG,+CAAsB,CAAC,GAAG,EAAE,gBAAgB,CAAC,KAAK,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAA;QAExE,OAAO,EAAE,CAAC,IAAI,CAAC,EAAE,CAAC,GAAG,CAAC,IAAI,EAAE,EAAE,CAAC,GAAG,CAAC,IAAI,EAAE,IAAI,CAAC,CAAC,CAAgB,CAAA;IACjE,CAAC,CAAC,CAAA;AACJ,CAAC;AArBD,kCAqBC;AAED,SAAgB,WAAW,CACzB,CAAc,EACd,gBAAmC,EACnC,YAA6B,EAC7B,WAA2B;IAD3B,6BAAA,EAAA,oBAA6B;IAC7B,4BAAA,EAAA,kBAA2B;IAE3B,OAAO,EAAE,CAAC,IAAI,CAAC;QACb,IAAM,IAAI,GAAG,EAAE,CAAC,IAAI,CAClB,YAAY;YACV,CAAC,CAAC,EAAE,CAAC,GAAG,CACN,EAAE,CAAC,MAAM,CAAC,CAAC,EAAG,gBAAgB,CAAC,KAA6C,CAAC,OAAO,EAAE,WAAW,CAAC,CAAC,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,MAAM,CAAC,EAC5H,gBAAgB,CAAC,KAAK,CAAC,IAAI,CAC5B;YACD,CAAC,CAAC,+CAAsB,CAAC,CAAC,EAAE,gBAAgB,CAAC,KAAqD,EAAE,WAAW,CAAC,CAAC,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CACtH,CAAA;QAChB,IAAM,IAAI,GAAG,+CAAsB,CAAC,IAAI,EAAE,gBAAgB,CAAC,KAAK,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAA;QAEzE,IAAM,GAAG,GAAG,EAAE,CAAC,IAAI,CAAC,EAAE,CAAC,GAAG,CAAC,IAAI,EAAE,IAAI,CAAC,CAAgB,CAAA;QACtD,IAAM,IAAI,GAAG,+CAAsB,CAAC,GAAG,EAAE,gBAAgB,CAAC,KAAK,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAA;QAExE,IAAM,GAAG,GAAG,EAAE,CAAC,IAAI,CAAC,EAAE,CAAC,GAAG,CAAC,IAAI,EAAE,EAAE,CAAC,GAAG,CAAC,IAAI,EAAE,IAAI,CAAC,CAAC,CAAgB,CAAA;QACpE,IAAM,IAAI,GAAG,+CAAsB,CAAC,GAAG,EAAE,gBAAgB,CAAC,KAAK,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAA;QAExE,OAAO,EAAE,CAAC,IAAI,CAAC,EAAE,CAAC,GAAG,CAAC,IAAI,EAAE,EAAE,CAAC,GAAG,CAAC,IAAI,EAAE,EAAE,CAAC,GAAG,CAAC,IAAI,EAAE,IAAI,CAAC,CAAC,CAAC,CAAgB,CAAA;IAC/E,CAAC,CAAC,CAAA;AACJ,CAAC;AAzBD,kCAyBC"}
\ No newline at end of file

build/commonjs/faceFeatureExtractor/depthwiseSeparableConv.js.map

-{"version":3,"file":"depthwiseSeparableConv.js","sourceRoot":"","sources":["../../../src/faceFeatureExtractor/depthwiseSeparableConv.ts"],"names":[],"mappings":";;AAAA,0CAA4C;AAG5C,SAAgB,sBAAsB,CACpC,CAAc,EACd,MAAoD,EACpD,MAAwB;IAExB,OAAO,EAAE,CAAC,IAAI,CAAC;QACb,IAAI,GAAG,GAAG,EAAE,CAAC,eAAe,CAAC,CAAC,EAAE,MAAM,CAAC,gBAAgB,EAAE,MAAM,CAAC,gBAAgB,EAAE,MAAM,EAAE,MAAM,CAAC,CAAA;QACjG,GAAG,GAAG,EAAE,CAAC,GAAG,CAAC,GAAG,EAAE,MAAM,CAAC,IAAI,CAAC,CAAA;QAC9B,OAAO,GAAG,CAAA;IACZ,CAAC,CAAC,CAAA;AACJ,CAAC;AAVD,wDAUC"}
\ No newline at end of file

build/commonjs/faceFeatureExtractor/extractorsFactory.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
-var tf = require("@tensorflow/tfjs-core");
 var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
 function extractorsFactory(extractWeights, paramMappings) {
-    function extractSeparableConvParams(channelsIn, channelsOut, mappedPrefix) {
-        var depthwise_filter = tf.tensor4d(extractWeights(3 * 3 * channelsIn), [3, 3, channelsIn, 1]);
-        var pointwise_filter = tf.tensor4d(extractWeights(channelsIn * channelsOut), [1, 1, channelsIn, channelsOut]);
-        var bias = tf.tensor1d(extractWeights(channelsOut));
-        paramMappings.push({ paramPath: mappedPrefix + "/depthwise_filter" }, { paramPath: mappedPrefix + "/pointwise_filter" }, { paramPath: mappedPrefix + "/bias" });
-        return new tfjs_image_recognition_base_1.TfjsImageRecognitionBase.SeparableConvParams(depthwise_filter, pointwise_filter, bias);
-    }
     var extractConvParams = tfjs_image_recognition_base_1.TfjsImageRecognitionBase.extractConvParamsFactory(extractWeights, paramMappings);
+    var extractSeparableConvParams = tfjs_image_recognition_base_1.TfjsImageRecognitionBase.extractSeparableConvParamsFactory(extractWeights, paramMappings);
     function extractDenseBlock3Params(channelsIn, channelsOut, mappedPrefix, isFirstLayer) {
         if (isFirstLayer === void 0) { isFirstLayer = false; }
         var conv0 = isFirstLayer

build/commonjs/faceFeatureExtractor/extractorsFactory.js.map

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+{"version":3,"file":"extractorsFactory.js","sourceRoot":"","sources":["../../../src/faceFeatureExtractor/extractorsFactory.ts"],"names":[],"mappings":";;AAAA,2EAAuE;AAIvE,SAAgB,iBAAiB,CAAC,cAA+D,EAAE,aAAsD;IAEvJ,IAAM,iBAAiB,GAAG,sDAAwB,CAAC,wBAAwB,CAAC,cAAc,EAAE,aAAa,CAAC,CAAA;IAC1G,IAAM,0BAA0B,GAAG,sDAAwB,CAAC,iCAAiC,CAAC,cAAc,EAAE,aAAa,CAAC,CAAA;IAE5H,SAAS,wBAAwB,CAAC,UAAkB,EAAE,WAAmB,EAAE,YAAoB,EAAE,YAA6B;QAA7B,6BAAA,EAAA,oBAA6B;QAE5H,IAAM,KAAK,GAAG,YAAY;YACxB,CAAC,CAAC,iBAAiB,CAAC,UAAU,EAAE,WAAW,EAAE,CAAC,EAAK,YAAY,WAAQ,CAAC;YACxE,CAAC,CAAC,0BAA0B,CAAC,UAAU,EAAE,WAAW,EAAK,YAAY,WAAQ,CAAC,CAAA;QAChF,IAAM,KAAK,GAAG,0BAA0B,CAAC,WAAW,EAAE,WAAW,EAAK,YAAY,WAAQ,CAAC,CAAA;QAC3F,IAAM,KAAK,GAAG,0BAA0B,CAAC,WAAW,EAAE,WAAW,EAAK,YAAY,WAAQ,CAAC,CAAA;QAE3F,OAAO,EAAE,KAAK,OAAA,EAAE,KAAK,OAAA,EAAE,KAAK,OAAA,EAAE,CAAA;IAChC,CAAC;IAED,SAAS,wBAAwB,CAAC,UAAkB,EAAE,WAAmB,EAAE,YAAoB,EAAE,YAA6B;QAA7B,6BAAA,EAAA,oBAA6B;QAEtH,IAAA,kFAAuG,EAArG,gBAAK,EAAE,gBAAK,EAAE,gBAAuF,CAAA;QAC7G,IAAM,KAAK,GAAG,0BAA0B,CAAC,WAAW,EAAE,WAAW,EAAK,YAAY,WAAQ,CAAC,CAAA;QAE3F,OAAO,EAAE,KAAK,OAAA,EAAE,KAAK,OAAA,EAAE,KAAK,OAAA,EAAE,KAAK,OAAA,EAAE,CAAA;IACvC,CAAC;IAED,OAAO;QACL,wBAAwB,0BAAA;QACxB,wBAAwB,0BAAA;KACzB,CAAA;AAEH,CAAC;AA7BD,8CA6BC"}
\ No newline at end of file

build/commonjs/faceFeatureExtractor/loadParamsFactory.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
 var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
+var loadConvParamsFactory_1 = require("../common/loadConvParamsFactory");
 function loadParamsFactory(weightMap, paramMappings) {
     var extractWeightEntry = tfjs_image_recognition_base_1.TfjsImageRecognitionBase.extractWeightEntryFactory(weightMap, paramMappings);
-    function extractConvParams(prefix) {
-        var filters = extractWeightEntry(prefix + "/filters", 4);
-        var bias = extractWeightEntry(prefix + "/bias", 1);
-        return { filters: filters, bias: bias };
-    }
-    function extractSeparableConvParams(prefix) {
-        var depthwise_filter = extractWeightEntry(prefix + "/depthwise_filter", 4);
-        var pointwise_filter = extractWeightEntry(prefix + "/pointwise_filter", 4);
-        var bias = extractWeightEntry(prefix + "/bias", 1);
-        return new tfjs_image_recognition_base_1.TfjsImageRecognitionBase.SeparableConvParams(depthwise_filter, pointwise_filter, bias);
-    }
+    var extractConvParams = loadConvParamsFactory_1.loadConvParamsFactory(extractWeightEntry);
+    var extractSeparableConvParams = tfjs_image_recognition_base_1.TfjsImageRecognitionBase.loadSeparableConvParamsFactory(extractWeightEntry);
     function extractDenseBlock3Params(prefix, isFirstLayer) {
         if (isFirstLayer === void 0) { isFirstLayer = false; }
         var conv0 = isFirstLayer

build/commonjs/faceFeatureExtractor/loadParamsFactory.js.map

-{"version":3,"file":"loadParamsFactory.js","sourceRoot":"","sources":["../../../src/faceFeatureExtractor/loadParamsFactory.ts"],"names":[],"mappings":";;AACA,2EAAuE;AAIvE,SAAgB,iBAAiB,CAAC,SAAc,EAAE,aAAsD;IAEtG,IAAM,kBAAkB,GAAG,sDAAwB,CAAC,yBAAyB,CAAC,SAAS,EAAE,aAAa,CAAC,CAAA;IAEvG,SAAS,iBAAiB,CAAC,MAAc;QACvC,IAAM,OAAO,GAAG,kBAAkB,CAAiB,MAAM,aAAU,EAAE,CAAC,CAAC,CAAA;QACvE,IAAM,IAAI,GAAG,kBAAkB,CAAiB,MAAM,UAAO,EAAE,CAAC,CAAC,CAAA;QAEjE,OAAO,EAAE,OAAO,SAAA,EAAE,IAAI,MAAA,EAAE,CAAA;IAC1B,CAAC;IAED,SAAS,0BAA0B,CAAC,MAAc;QAChD,IAAM,gBAAgB,GAAG,kBAAkB,CAAiB,MAAM,sBAAmB,EAAE,CAAC,CAAC,CAAA;QACzF,IAAM,gBAAgB,GAAG,kBAAkB,CAAiB,MAAM,sBAAmB,EAAE,CAAC,CAAC,CAAA;QACzF,IAAM,IAAI,GAAG,kBAAkB,CAAiB,MAAM,UAAO,EAAE,CAAC,CAAC,CAAA;QAEjE,OAAO,IAAI,sDAAwB,CAAC,mBAAmB,CACrD,gBAAgB,EAChB,gBAAgB,EAChB,IAAI,CACL,CAAA;IACH,CAAC;IAED,SAAS,wBAAwB,CAAC,MAAc,EAAE,YAA6B;QAA7B,6BAAA,EAAA,oBAA6B;QAC7E,IAAM,KAAK,GAAG,YAAY;YACxB,CAAC,CAAC,iBAAiB,CAAI,MAAM,WAAQ,CAAC;YACtC,CAAC,CAAC,0BAA0B,CAAI,MAAM,WAAQ,CAAC,CAAA;QACjD,IAAM,KAAK,GAAG,0BAA0B,CAAI,MAAM,WAAQ,CAAC,CAAA;QAC3D,IAAM,KAAK,GAAG,0BAA0B,CAAI,MAAM,WAAQ,CAAC,CAAA;QAE3D,OAAO,EAAE,KAAK,OAAA,EAAE,KAAK,OAAA,EAAE,KAAK,OAAA,EAAE,CAAA;IAChC,CAAC;IAED,SAAS,wBAAwB,CAAC,MAAc,EAAE,YAA6B;QAA7B,6BAAA,EAAA,oBAA6B;QAC7E,IAAM,KAAK,GAAG,YAAY;YACxB,CAAC,CAAC,iBAAiB,CAAI,MAAM,WAAQ,CAAC;YACtC,CAAC,CAAC,0BAA0B,CAAI,MAAM,WAAQ,CAAC,CAAA;QACjD,IAAM,KAAK,GAAG,0BAA0B,CAAI,MAAM,WAAQ,CAAC,CAAA;QAC3D,IAAM,KAAK,GAAG,0BAA0B,CAAI,MAAM,WAAQ,CAAC,CAAA;QAC3D,IAAM,KAAK,GAAG,0BAA0B,CAAI,MAAM,WAAQ,CAAC,CAAA;QAE3D,OAAO,EAAE,KAAK,OAAA,EAAE,KAAK,OAAA,EAAE,KAAK,OAAA,EAAE,KAAK,OAAA,EAAE,CAAA;IACvC,CAAC;IAED,OAAO;QACL,wBAAwB,0BAAA;QACxB,wBAAwB,0BAAA;KACzB,CAAA;AACH,CAAC;AAhDD,8CAgDC"}
+{"version":3,"file":"loadParamsFactory.js","sourceRoot":"","sources":["../../../src/faceFeatureExtractor/loadParamsFactory.ts"],"names":[],"mappings":";;AAAA,2EAAuE;AAEvE,yEAAwE;AAGxE,SAAgB,iBAAiB,CAAC,SAAc,EAAE,aAAsD;IAEtG,IAAM,kBAAkB,GAAG,sDAAwB,CAAC,yBAAyB,CAAC,SAAS,EAAE,aAAa,CAAC,CAAA;IAEvG,IAAM,iBAAiB,GAAG,6CAAqB,CAAC,kBAAkB,CAAC,CAAA;IACnE,IAAM,0BAA0B,GAAG,sDAAwB,CAAC,8BAA8B,CAAC,kBAAkB,CAAC,CAAA;IAE9G,SAAS,wBAAwB,CAAC,MAAc,EAAE,YAA6B;QAA7B,6BAAA,EAAA,oBAA6B;QAC7E,IAAM,KAAK,GAAG,YAAY;YACxB,CAAC,CAAC,iBAAiB,CAAI,MAAM,WAAQ,CAAC;YACtC,CAAC,CAAC,0BAA0B,CAAI,MAAM,WAAQ,CAAC,CAAA;QACjD,IAAM,KAAK,GAAG,0BAA0B,CAAI,MAAM,WAAQ,CAAC,CAAA;QAC3D,IAAM,KAAK,GAAG,0BAA0B,CAAI,MAAM,WAAQ,CAAC,CAAA;QAE3D,OAAO,EAAE,KAAK,OAAA,EAAE,KAAK,OAAA,EAAE,KAAK,OAAA,EAAE,CAAA;IAChC,CAAC;IAED,SAAS,wBAAwB,CAAC,MAAc,EAAE,YAA6B;QAA7B,6BAAA,EAAA,oBAA6B;QAC7E,IAAM,KAAK,GAAG,YAAY;YACxB,CAAC,CAAC,iBAAiB,CAAI,MAAM,WAAQ,CAAC;YACtC,CAAC,CAAC,0BAA0B,CAAI,MAAM,WAAQ,CAAC,CAAA;QACjD,IAAM,KAAK,GAAG,0BAA0B,CAAI,MAAM,WAAQ,CAAC,CAAA;QAC3D,IAAM,KAAK,GAAG,0BAA0B,CAAI,MAAM,WAAQ,CAAC,CAAA;QAC3D,IAAM,KAAK,GAAG,0BAA0B,CAAI,MAAM,WAAQ,CAAC,CAAA;QAE3D,OAAO,EAAE,KAAK,OAAA,EAAE,KAAK,OAAA,EAAE,KAAK,OAAA,EAAE,KAAK,OAAA,EAAE,CAAA;IACvC,CAAC;IAED,OAAO;QACL,wBAAwB,0BAAA;QACxB,wBAAwB,0BAAA;KACzB,CAAA;AACH,CAAC;AAhCD,8CAgCC"}
\ No newline at end of file

build/commonjs/factories/WithAge.d.ts

+export declare type WithAge<TSource> = TSource & {
+    age: number;
+};
+export declare function isWithAge(obj: any): obj is WithAge<{}>;
+export declare function extendWithAge<TSource>(sourceObj: TSource, age: number): WithAge<TSource>;

build/commonjs/factories/WithAge.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+function isWithAge(obj) {
+    return typeof obj['age'] === 'number';
+}
+exports.isWithAge = isWithAge;
+function extendWithAge(sourceObj, age) {
+    var extension = { age: age };
+    return Object.assign({}, sourceObj, extension);
+}
+exports.extendWithAge = extendWithAge;
+//# sourceMappingURL=WithAge.js.map
\ No newline at end of file

build/commonjs/factories/WithAge.js.map

+{"version":3,"file":"WithAge.js","sourceRoot":"","sources":["../../../src/factories/WithAge.ts"],"names":[],"mappings":";;AAIA,SAAgB,SAAS,CAAC,GAAQ;IAChC,OAAO,OAAO,GAAG,CAAC,KAAK,CAAC,KAAK,QAAQ,CAAA;AACvC,CAAC;AAFD,8BAEC;AAED,SAAgB,aAAa,CAG3B,SAAkB,EAClB,GAAW;IAGX,IAAM,SAAS,GAAG,EAAE,GAAG,KAAA,EAAE,CAAA;IACzB,OAAO,MAAM,CAAC,MAAM,CAAC,EAAE,EAAE,SAAS,EAAE,SAAS,CAAC,CAAA;AAChD,CAAC;AATD,sCASC"}
\ No newline at end of file

build/commonjs/factories/WithFaceDetection.d.ts

@@ -2,4 +2,5 @@ import { FaceDetection } from '../classes/FaceDetection';
 export declare type WithFaceDetection<TSource> = TSource & {
     detection: FaceDetection;
 };
+export declare function isWithFaceDetection(obj: any): obj is WithFaceDetection<{}>;
 export declare function extendWithFaceDetection<TSource>(sourceObj: TSource, detection: FaceDetection): WithFaceDetection<TSource>;

build/commonjs/factories/WithFaceDetection.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
+var FaceDetection_1 = require("../classes/FaceDetection");
+function isWithFaceDetection(obj) {
+    return obj['detection'] instanceof FaceDetection_1.FaceDetection;
+}
+exports.isWithFaceDetection = isWithFaceDetection;
 function extendWithFaceDetection(sourceObj, detection) {
     var extension = { detection: detection };
     return Object.assign({}, sourceObj, extension);

build/commonjs/factories/WithFaceDetection.js.map

-{"version":3,"file":"WithFaceDetection.js","sourceRoot":"","sources":["../../../src/factories/WithFaceDetection.ts"],"names":[],"mappings":";;AAMA,SAAgB,uBAAuB,CAGrC,SAAkB,EAClB,SAAwB;IAGxB,IAAM,SAAS,GAAG,EAAE,SAAS,WAAA,EAAE,CAAA;IAC/B,OAAO,MAAM,CAAC,MAAM,CAAC,EAAE,EAAE,SAAS,EAAE,SAAS,CAAC,CAAA;AAChD,CAAC;AATD,0DASC"}
+{"version":3,"file":"WithFaceDetection.js","sourceRoot":"","sources":["../../../src/factories/WithFaceDetection.ts"],"names":[],"mappings":";;AAAA,0DAAyD;AAMzD,SAAgB,mBAAmB,CAAC,GAAQ;IAC1C,OAAO,GAAG,CAAC,WAAW,CAAC,YAAY,6BAAa,CAAA;AAClD,CAAC;AAFD,kDAEC;AAED,SAAgB,uBAAuB,CAGrC,SAAkB,EAClB,SAAwB;IAGxB,IAAM,SAAS,GAAG,EAAE,SAAS,WAAA,EAAE,CAAA;IAC/B,OAAO,MAAM,CAAC,MAAM,CAAC,EAAE,EAAE,SAAS,EAAE,SAAS,CAAC,CAAA;AAChD,CAAC;AATD,0DASC"}
\ No newline at end of file

build/commonjs/factories/WithFaceExpressions.d.ts

-import { FaceExpressionPrediction } from '../faceExpressionNet/types';
+import { FaceExpressions } from '../faceExpressionNet/FaceExpressions';
 export declare type WithFaceExpressions<TSource> = TSource & {
-    expressions: FaceExpressionPrediction[];
+    expressions: FaceExpressions;
 };
-export declare function extendWithFaceExpressions<TSource>(sourceObj: TSource, expressions: FaceExpressionPrediction[]): WithFaceExpressions<TSource>;
+export declare function isWithFaceExpressions(obj: any): obj is WithFaceExpressions<{}>;
+export declare function extendWithFaceExpressions<TSource>(sourceObj: TSource, expressions: FaceExpressions): WithFaceExpressions<TSource>;

build/commonjs/factories/WithFaceExpressions.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
+var FaceExpressions_1 = require("../faceExpressionNet/FaceExpressions");
+function isWithFaceExpressions(obj) {
+    return obj['expressions'] instanceof FaceExpressions_1.FaceExpressions;
+}
+exports.isWithFaceExpressions = isWithFaceExpressions;
 function extendWithFaceExpressions(sourceObj, expressions) {
     var extension = { expressions: expressions };
     return Object.assign({}, sourceObj, extension);

build/commonjs/factories/WithFaceExpressions.js.map

-{"version":3,"file":"WithFaceExpressions.js","sourceRoot":"","sources":["../../../src/factories/WithFaceExpressions.ts"],"names":[],"mappings":";;AAMA,SAAgB,yBAAyB,CAGvC,SAAkB,EAClB,WAAuC;IAGvC,IAAM,SAAS,GAAG,EAAE,WAAW,aAAA,EAAE,CAAA;IACjC,OAAO,MAAM,CAAC,MAAM,CAAC,EAAE,EAAE,SAAS,EAAE,SAAS,CAAC,CAAA;AAChD,CAAC;AATD,8DASC"}
+{"version":3,"file":"WithFaceExpressions.js","sourceRoot":"","sources":["../../../src/factories/WithFaceExpressions.ts"],"names":[],"mappings":";;AAAA,wEAAuE;AAMvE,SAAgB,qBAAqB,CAAC,GAAQ;IAC5C,OAAO,GAAG,CAAC,aAAa,CAAC,YAAY,iCAAe,CAAA;AACtD,CAAC;AAFD,sDAEC;AAED,SAAgB,yBAAyB,CAGvC,SAAkB,EAClB,WAA4B;IAG5B,IAAM,SAAS,GAAG,EAAE,WAAW,aAAA,EAAE,CAAA;IACjC,OAAO,MAAM,CAAC,MAAM,CAAC,EAAE,EAAE,SAAS,EAAE,SAAS,CAAC,CAAA;AAChD,CAAC;AATD,8DASC"}
\ No newline at end of file

build/commonjs/factories/WithFaceLandmarks.d.ts

@@ -7,4 +7,5 @@ export declare type WithFaceLandmarks<TSource extends WithFaceDetection<{}>, TFa
     unshiftedLandmarks: TFaceLandmarks;
     alignedRect: FaceDetection;
 };
+export declare function isWithFaceLandmarks(obj: any): obj is WithFaceLandmarks<WithFaceDetection<{}>, FaceLandmarks>;
 export declare function extendWithFaceLandmarks<TSource extends WithFaceDetection<{}>, TFaceLandmarks extends FaceLandmarks = FaceLandmarks68>(sourceObj: TSource, unshiftedLandmarks: TFaceLandmarks): WithFaceLandmarks<TSource, TFaceLandmarks>;

build/commonjs/factories/WithFaceLandmarks.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
 var FaceDetection_1 = require("../classes/FaceDetection");
+var FaceLandmarks_1 = require("../classes/FaceLandmarks");
+var WithFaceDetection_1 = require("./WithFaceDetection");
+function isWithFaceLandmarks(obj) {
+    return WithFaceDetection_1.isWithFaceDetection(obj)
+        && obj['landmarks'] instanceof FaceLandmarks_1.FaceLandmarks
+        && obj['unshiftedLandmarks'] instanceof FaceLandmarks_1.FaceLandmarks
+        && obj['alignedRect'] instanceof FaceDetection_1.FaceDetection;
+}
+exports.isWithFaceLandmarks = isWithFaceLandmarks;
 function extendWithFaceLandmarks(sourceObj, unshiftedLandmarks) {
     var shift = sourceObj.detection.box;
     var landmarks = unshiftedLandmarks.shiftBy(shift.x, shift.y);

build/commonjs/factories/WithFaceLandmarks.js.map

-{"version":3,"file":"WithFaceLandmarks.js","sourceRoot":"","sources":["../../../src/factories/WithFaceLandmarks.ts"],"names":[],"mappings":";;AAAA,0DAAyD;AAczD,SAAgB,uBAAuB,CAIrC,SAAkB,EAClB,kBAAkC;IAG1B,IAAA,+BAAU,CAAwB;IAC1C,IAAM,SAAS,GAAG,kBAAkB,CAAC,OAAO,CAAiB,KAAK,CAAC,CAAC,EAAE,KAAK,CAAC,CAAC,CAAC,CAAA;IAE9E,IAAM,IAAI,GAAG,SAAS,CAAC,KAAK,EAAE,CAAA;IACtB,IAAA,yCAAS,CAAwB;IACzC,IAAM,WAAW,GAAG,IAAI,6BAAa,CAAC,SAAS,CAAC,SAAS,CAAC,KAAK,EAAE,IAAI,CAAC,OAAO,CAAC,SAAS,CAAC,OAAO,EAAE,CAAC,EAAE,SAAS,CAAC,CAAA;IAE9G,IAAM,SAAS,GAAG;QAChB,SAAS,WAAA;QACT,kBAAkB,oBAAA;QAClB,WAAW,aAAA;KACZ,CAAA;IAED,OAAO,MAAM,CAAC,MAAM,CAAC,EAAE,EAAE,SAAS,EAAE,SAAS,CAAC,CAAA;AAChD,CAAC;AAtBD,0DAsBC"}
+{"version":3,"file":"WithFaceLandmarks.js","sourceRoot":"","sources":["../../../src/factories/WithFaceLandmarks.ts"],"names":[],"mappings":";;AAAA,0DAAyD;AACzD,0DAAyD;AAEzD,yDAA6E;AAW7E,SAAgB,mBAAmB,CAAC,GAAQ;IAC1C,OAAO,uCAAmB,CAAC,GAAG,CAAC;WAC1B,GAAG,CAAC,WAAW,CAAC,YAAY,6BAAa;WACzC,GAAG,CAAC,oBAAoB,CAAC,YAAY,6BAAa;WAClD,GAAG,CAAC,aAAa,CAAC,YAAY,6BAAa,CAAA;AAClD,CAAC;AALD,kDAKC;AAED,SAAgB,uBAAuB,CAIrC,SAAkB,EAClB,kBAAkC;IAG1B,IAAA,+BAAU,CAAwB;IAC1C,IAAM,SAAS,GAAG,kBAAkB,CAAC,OAAO,CAAiB,KAAK,CAAC,CAAC,EAAE,KAAK,CAAC,CAAC,CAAC,CAAA;IAE9E,IAAM,IAAI,GAAG,SAAS,CAAC,KAAK,EAAE,CAAA;IACtB,IAAA,yCAAS,CAAwB;IACzC,IAAM,WAAW,GAAG,IAAI,6BAAa,CAAC,SAAS,CAAC,SAAS,CAAC,KAAK,EAAE,IAAI,CAAC,OAAO,CAAC,SAAS,CAAC,OAAO,EAAE,CAAC,EAAE,SAAS,CAAC,CAAA;IAE9G,IAAM,SAAS,GAAG;QAChB,SAAS,WAAA;QACT,kBAAkB,oBAAA;QAClB,WAAW,aAAA;KACZ,CAAA;IAED,OAAO,MAAM,CAAC,MAAM,CAAC,EAAE,EAAE,SAAS,EAAE,SAAS,CAAC,CAAA;AAChD,CAAC;AAtBD,0DAsBC"}
\ No newline at end of file

build/commonjs/factories/WithGender.d.ts

+import { Gender } from '../ageGenderNet/types';
+export declare type WithGender<TSource> = TSource & {
+    gender: Gender;
+    genderProbability: number;
+};
+export declare function isWithGender(obj: any): obj is WithGender<{}>;
+export declare function extendWithGender<TSource>(sourceObj: TSource, gender: Gender, genderProbability: number): WithGender<TSource>;

build/commonjs/factories/WithGender.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
+var types_1 = require("../ageGenderNet/types");
+function isWithGender(obj) {
+    return (obj['gender'] === types_1.Gender.MALE || obj['gender'] === types_1.Gender.FEMALE)
+        && tfjs_image_recognition_base_1.isValidProbablitiy(obj['genderProbability']);
+}
+exports.isWithGender = isWithGender;
+function extendWithGender(sourceObj, gender, genderProbability) {
+    var extension = { gender: gender, genderProbability: genderProbability };
+    return Object.assign({}, sourceObj, extension);
+}
+exports.extendWithGender = extendWithGender;
+//# sourceMappingURL=WithGender.js.map
\ No newline at end of file

build/commonjs/factories/WithGender.js.map

+{"version":3,"file":"WithGender.js","sourceRoot":"","sources":["../../../src/factories/WithGender.ts"],"names":[],"mappings":";;AAAA,2EAAiE;AAEjE,+CAA+C;AAO/C,SAAgB,YAAY,CAAC,GAAQ;IACnC,OAAO,CAAC,GAAG,CAAC,QAAQ,CAAC,KAAK,cAAM,CAAC,IAAI,IAAI,GAAG,CAAC,QAAQ,CAAC,KAAK,cAAM,CAAC,MAAM,CAAC;WACpE,gDAAkB,CAAC,GAAG,CAAC,mBAAmB,CAAC,CAAC,CAAA;AACnD,CAAC;AAHD,oCAGC;AAED,SAAgB,gBAAgB,CAG9B,SAAkB,EAClB,MAAc,EACd,iBAAyB;IAGzB,IAAM,SAAS,GAAG,EAAE,MAAM,QAAA,EAAE,iBAAiB,mBAAA,EAAE,CAAA;IAC/C,OAAO,MAAM,CAAC,MAAM,CAAC,EAAE,EAAE,SAAS,EAAE,SAAS,CAAC,CAAA;AAChD,CAAC;AAVD,4CAUC"}
\ No newline at end of file

build/commonjs/globalApi/ComputeFaceDescriptorsTasks.d.ts

@@ -3,6 +3,8 @@ import { WithFaceDescriptor } from '../factories/WithFaceDescriptor';
 import { WithFaceDetection } from '../factories/WithFaceDetection';
 import { WithFaceLandmarks } from '../factories/WithFaceLandmarks';
 import { ComposableTask } from './ComposableTask';
+import { PredictAllAgeAndGenderWithFaceAlignmentTask, PredictSingleAgeAndGenderWithFaceAlignmentTask } from './PredictAgeAndGenderTask';
+import { PredictAllFaceExpressionsWithFaceAlignmentTask, PredictSingleFaceExpressionsWithFaceAlignmentTask } from './PredictFaceExpressionsTask';
 export declare class ComputeFaceDescriptorsTaskBase<TReturn, TParentReturn> extends ComposableTask<TReturn> {
     protected parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>;
     protected input: TNetInput;
@@ -10,7 +12,11 @@ export declare class ComputeFaceDescriptorsTaskBase<TReturn, TParentReturn> exte
 }
 export declare class ComputeAllFaceDescriptorsTask<TSource extends WithFaceLandmarks<WithFaceDetection<{}>>> extends ComputeFaceDescriptorsTaskBase<WithFaceDescriptor<TSource>[], TSource[]> {
     run(): Promise<WithFaceDescriptor<TSource>[]>;
+    withFaceExpressions(): PredictAllFaceExpressionsWithFaceAlignmentTask<WithFaceDescriptor<TSource>>;
+    withAgeAndGender(): PredictAllAgeAndGenderWithFaceAlignmentTask<WithFaceDescriptor<TSource>>;
 }
 export declare class ComputeSingleFaceDescriptorTask<TSource extends WithFaceLandmarks<WithFaceDetection<{}>>> extends ComputeFaceDescriptorsTaskBase<WithFaceDescriptor<TSource> | undefined, TSource | undefined> {
     run(): Promise<WithFaceDescriptor<TSource> | undefined>;
+    withFaceExpressions(): PredictSingleFaceExpressionsWithFaceAlignmentTask<WithFaceDescriptor<TSource>>;
+    withAgeAndGender(): PredictSingleAgeAndGenderWithFaceAlignmentTask<WithFaceDescriptor<TSource>>;
 }

build/commonjs/globalApi/ComputeFaceDescriptorsTasks.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
 var tslib_1 = require("tslib");
-var tf = require("@tensorflow/tfjs-core");
-var dom_1 = require("../dom");
 var WithFaceDescriptor_1 = require("../factories/WithFaceDescriptor");
 var ComposableTask_1 = require("./ComposableTask");
+var extractFacesAndComputeResults_1 = require("./extractFacesAndComputeResults");
 var nets_1 = require("./nets");
+var PredictAgeAndGenderTask_1 = require("./PredictAgeAndGenderTask");
+var PredictFaceExpressionsTask_1 = require("./PredictFaceExpressionsTask");
 var ComputeFaceDescriptorsTaskBase = /** @class */ (function (_super) {
     tslib_1.__extends(ComputeFaceDescriptorsTaskBase, _super);
     function ComputeFaceDescriptorsTaskBase(parentTask, input) {
@@ -24,47 +25,28 @@ var ComputeAllFaceDescriptorsTask = /** @class */ (function (_super) {
     }
     ComputeAllFaceDescriptorsTask.prototype.run = function () {
         return tslib_1.__awaiter(this, void 0, void 0, function () {
-            var parentResults, alignedRects, alignedFaces, _a, results;
-            var _this = this;
-            return tslib_1.__generator(this, function (_b) {
-                switch (_b.label) {
+            var parentResults, descriptors;
+            return tslib_1.__generator(this, function (_a) {
+                switch (_a.label) {
                     case 0: return [4 /*yield*/, this.parentTask];
                     case 1:
-                        parentResults = _b.sent();
-                        alignedRects = parentResults.map(function (_a) {
-                            var alignedRect = _a.alignedRect;
-                            return alignedRect;
-                        });
-                        if (!(this.input instanceof tf.Tensor)) return [3 /*break*/, 3];
-                        return [4 /*yield*/, dom_1.extractFaceTensors(this.input, alignedRects)];
+                        parentResults = _a.sent();
+                        return [4 /*yield*/, extractFacesAndComputeResults_1.extractAllFacesAndComputeResults(parentResults, this.input, function (faces) { return Promise.all(faces.map(function (face) {
+                                return nets_1.nets.faceRecognitionNet.computeFaceDescriptor(face);
+                            })); }, null, function (parentResult) { return parentResult.landmarks.align(null, { useDlibAlignment: true }); })];
                     case 2:
-                        _a = _b.sent();
-                        return [3 /*break*/, 5];
-                    case 3: return [4 /*yield*/, dom_1.extractFaces(this.input, alignedRects)];
-                    case 4:
-                        _a = _b.sent();
-                        _b.label = 5;
-                    case 5:
-                        alignedFaces = _a;
-                        return [4 /*yield*/, Promise.all(parentResults.map(function (parentResult, i) { return tslib_1.__awaiter(_this, void 0, void 0, function () {
-                                var descriptor;
-                                return tslib_1.__generator(this, function (_a) {
-                                    switch (_a.label) {
-                                        case 0: return [4 /*yield*/, nets_1.nets.faceRecognitionNet.computeFaceDescriptor(alignedFaces[i])];
-                                        case 1:
-                                            descriptor = _a.sent();
-                                            return [2 /*return*/, WithFaceDescriptor_1.extendWithFaceDescriptor(parentResult, descriptor)];
-                                    }
-                                });
-                            }); }))];
-                    case 6:
-                        results = _b.sent();
-                        alignedFaces.forEach(function (f) { return f instanceof tf.Tensor && f.dispose(); });
-                        return [2 /*return*/, results];
+                        descriptors = _a.sent();
+                        return [2 /*return*/, descriptors.map(function (descriptor, i) { return WithFaceDescriptor_1.extendWithFaceDescriptor(parentResults[i], descriptor); })];
                 }
             });
         });
     };
+    ComputeAllFaceDescriptorsTask.prototype.withFaceExpressions = function () {
+        return new PredictFaceExpressionsTask_1.PredictAllFaceExpressionsWithFaceAlignmentTask(this, this.input);
+    };
+    ComputeAllFaceDescriptorsTask.prototype.withAgeAndGender = function () {
+        return new PredictAgeAndGenderTask_1.PredictAllAgeAndGenderWithFaceAlignmentTask(this, this.input);
+    };
     return ComputeAllFaceDescriptorsTask;
 }(ComputeFaceDescriptorsTaskBase));
 exports.ComputeAllFaceDescriptorsTask = ComputeAllFaceDescriptorsTask;
@@ -75,36 +57,29 @@ var ComputeSingleFaceDescriptorTask = /** @class */ (function (_super) {
     }
     ComputeSingleFaceDescriptorTask.prototype.run = function () {
         return tslib_1.__awaiter(this, void 0, void 0, function () {
-            var parentResult, alignedRect, alignedFaces, _a, descriptor;
-            return tslib_1.__generator(this, function (_b) {
-                switch (_b.label) {
+            var parentResult, descriptor;
+            return tslib_1.__generator(this, function (_a) {
+                switch (_a.label) {
                     case 0: return [4 /*yield*/, this.parentTask];
                     case 1:
-                        parentResult = _b.sent();
+                        parentResult = _a.sent();
                         if (!parentResult) {
                             return [2 /*return*/];
                         }
-                        alignedRect = parentResult.alignedRect;
-                        if (!(this.input instanceof tf.Tensor)) return [3 /*break*/, 3];
-                        return [4 /*yield*/, dom_1.extractFaceTensors(this.input, [alignedRect])];
+                        return [4 /*yield*/, extractFacesAndComputeResults_1.extractSingleFaceAndComputeResult(parentResult, this.input, function (face) { return nets_1.nets.faceRecognitionNet.computeFaceDescriptor(face); }, null, function (parentResult) { return parentResult.landmarks.align(null, { useDlibAlignment: true }); })];
                     case 2:
-                        _a = _b.sent();
-                        return [3 /*break*/, 5];
-                    case 3: return [4 /*yield*/, dom_1.extractFaces(this.input, [alignedRect])];
-                    case 4:
-                        _a = _b.sent();
-                        _b.label = 5;
-                    case 5:
-                        alignedFaces = _a;
-                        return [4 /*yield*/, nets_1.nets.faceRecognitionNet.computeFaceDescriptor(alignedFaces[0])];
-                    case 6:
-                        descriptor = _b.sent();
-                        alignedFaces.forEach(function (f) { return f instanceof tf.Tensor && f.dispose(); });
+                        descriptor = _a.sent();
                         return [2 /*return*/, WithFaceDescriptor_1.extendWithFaceDescriptor(parentResult, descriptor)];
                 }
             });
         });
     };
+    ComputeSingleFaceDescriptorTask.prototype.withFaceExpressions = function () {
+        return new PredictFaceExpressionsTask_1.PredictSingleFaceExpressionsWithFaceAlignmentTask(this, this.input);
+    };
+    ComputeSingleFaceDescriptorTask.prototype.withAgeAndGender = function () {
+        return new PredictAgeAndGenderTask_1.PredictSingleAgeAndGenderWithFaceAlignmentTask(this, this.input);
+    };
     return ComputeSingleFaceDescriptorTask;
 }(ComputeFaceDescriptorsTaskBase));
 exports.ComputeSingleFaceDescriptorTask = ComputeSingleFaceDescriptorTask;

build/commonjs/globalApi/ComputeFaceDescriptorsTasks.js.map

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\ No newline at end of file

build/commonjs/globalApi/DetectFaceLandmarksTasks.d.ts

 import { TNetInput } from 'tfjs-image-recognition-base';
+import { FaceLandmarks68 } from '../classes/FaceLandmarks68';
 import { FaceLandmark68Net } from '../faceLandmarkNet/FaceLandmark68Net';
 import { FaceLandmark68TinyNet } from '../faceLandmarkNet/FaceLandmark68TinyNet';
 import { WithFaceDetection } from '../factories/WithFaceDetection';
 import { WithFaceLandmarks } from '../factories/WithFaceLandmarks';
 import { ComposableTask } from './ComposableTask';
 import { ComputeAllFaceDescriptorsTask, ComputeSingleFaceDescriptorTask } from './ComputeFaceDescriptorsTasks';
+import { PredictAllAgeAndGenderWithFaceAlignmentTask, PredictSingleAgeAndGenderWithFaceAlignmentTask } from './PredictAgeAndGenderTask';
+import { PredictAllFaceExpressionsWithFaceAlignmentTask, PredictSingleFaceExpressionsWithFaceAlignmentTask } from './PredictFaceExpressionsTask';
 export declare class DetectFaceLandmarksTaskBase<TReturn, TParentReturn> extends ComposableTask<TReturn> {
     protected parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>;
     protected input: TNetInput;
@@ -14,9 +17,13 @@ export declare class DetectFaceLandmarksTaskBase<TReturn, TParentReturn> extends
 }
 export declare class DetectAllFaceLandmarksTask<TSource extends WithFaceDetection<{}>> extends DetectFaceLandmarksTaskBase<WithFaceLandmarks<TSource>[], TSource[]> {
     run(): Promise<WithFaceLandmarks<TSource>[]>;
-    withFaceDescriptors(): ComputeAllFaceDescriptorsTask<WithFaceLandmarks<TSource>>;
+    withFaceExpressions(): PredictAllFaceExpressionsWithFaceAlignmentTask<WithFaceLandmarks<TSource, FaceLandmarks68>>;
+    withAgeAndGender(): PredictAllAgeAndGenderWithFaceAlignmentTask<WithFaceLandmarks<TSource, FaceLandmarks68>>;
+    withFaceDescriptors(): ComputeAllFaceDescriptorsTask<WithFaceLandmarks<TSource, FaceLandmarks68>>;
 }
 export declare class DetectSingleFaceLandmarksTask<TSource extends WithFaceDetection<{}>> extends DetectFaceLandmarksTaskBase<WithFaceLandmarks<TSource> | undefined, TSource | undefined> {
     run(): Promise<WithFaceLandmarks<TSource> | undefined>;
-    withFaceDescriptor(): ComputeSingleFaceDescriptorTask<WithFaceLandmarks<TSource>>;
+    withFaceExpressions(): PredictSingleFaceExpressionsWithFaceAlignmentTask<WithFaceLandmarks<TSource, FaceLandmarks68>>;
+    withAgeAndGender(): PredictSingleAgeAndGenderWithFaceAlignmentTask<WithFaceLandmarks<TSource, FaceLandmarks68>>;
+    withFaceDescriptor(): ComputeSingleFaceDescriptorTask<WithFaceLandmarks<TSource, FaceLandmarks68>>;
 }

build/commonjs/globalApi/DetectFaceLandmarksTasks.js

@@ -7,6 +7,8 @@ var WithFaceLandmarks_1 = require("../factories/WithFaceLandmarks");
 var ComposableTask_1 = require("./ComposableTask");
 var ComputeFaceDescriptorsTasks_1 = require("./ComputeFaceDescriptorsTasks");
 var nets_1 = require("./nets");
+var PredictAgeAndGenderTask_1 = require("./PredictAgeAndGenderTask");
+var PredictFaceExpressionsTask_1 = require("./PredictFaceExpressionsTask");
 var DetectFaceLandmarksTaskBase = /** @class */ (function (_super) {
     tslib_1.__extends(DetectFaceLandmarksTaskBase, _super);
     function DetectFaceLandmarksTaskBase(parentTask, input, useTinyLandmarkNet) {
@@ -65,6 +67,12 @@ var DetectAllFaceLandmarksTask = /** @class */ (function (_super) {
             });
         });
     };
+    DetectAllFaceLandmarksTask.prototype.withFaceExpressions = function () {
+        return new PredictFaceExpressionsTask_1.PredictAllFaceExpressionsWithFaceAlignmentTask(this, this.input);
+    };
+    DetectAllFaceLandmarksTask.prototype.withAgeAndGender = function () {
+        return new PredictAgeAndGenderTask_1.PredictAllAgeAndGenderWithFaceAlignmentTask(this, this.input);
+    };
     DetectAllFaceLandmarksTask.prototype.withFaceDescriptors = function () {
         return new ComputeFaceDescriptorsTasks_1.ComputeAllFaceDescriptorsTask(this, this.input);
     };
@@ -108,6 +116,12 @@ var DetectSingleFaceLandmarksTask = /** @class */ (function (_super) {
             });
         });
     };
+    DetectSingleFaceLandmarksTask.prototype.withFaceExpressions = function () {
+        return new PredictFaceExpressionsTask_1.PredictSingleFaceExpressionsWithFaceAlignmentTask(this, this.input);
+    };
+    DetectSingleFaceLandmarksTask.prototype.withAgeAndGender = function () {
+        return new PredictAgeAndGenderTask_1.PredictSingleAgeAndGenderWithFaceAlignmentTask(this, this.input);
+    };
     DetectSingleFaceLandmarksTask.prototype.withFaceDescriptor = function () {
         return new ComputeFaceDescriptorsTasks_1.ComputeSingleFaceDescriptorTask(this, this.input);
     };

build/commonjs/globalApi/DetectFaceLandmarksTasks.js.map

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\ No newline at end of file

build/commonjs/globalApi/DetectFacesTasks.d.ts

 import { TNetInput } from 'tfjs-image-recognition-base';
 import { FaceDetection } from '../classes/FaceDetection';
-import { WithFaceDetection } from '../factories/WithFaceDetection';
 import { ComposableTask } from './ComposableTask';
 import { DetectAllFaceLandmarksTask, DetectSingleFaceLandmarksTask } from './DetectFaceLandmarksTasks';
-import { PredictAllFaceExpressionsTask, PredictSingleFaceExpressionTask } from './PredictFaceExpressionsTask';
+import { PredictAllAgeAndGenderTask, PredictSingleAgeAndGenderTask } from './PredictAgeAndGenderTask';
+import { PredictAllFaceExpressionsTask, PredictSingleFaceExpressionsTask } from './PredictFaceExpressionsTask';
 import { FaceDetectionOptions } from './types';
 export declare class DetectFacesTaskBase<TReturn> extends ComposableTask<TReturn> {
     protected input: TNetInput;
@@ -13,12 +13,26 @@ export declare class DetectFacesTaskBase<TReturn> extends ComposableTask<TReturn
 export declare class DetectAllFacesTask extends DetectFacesTaskBase<FaceDetection[]> {
     run(): Promise<FaceDetection[]>;
     private runAndExtendWithFaceDetections;
-    withFaceLandmarks(useTinyLandmarkNet?: boolean): DetectAllFaceLandmarksTask<WithFaceDetection<{}>>;
-    withFaceExpressions(): PredictAllFaceExpressionsTask<WithFaceDetection<{}>>;
+    withFaceLandmarks(useTinyLandmarkNet?: boolean): DetectAllFaceLandmarksTask<{
+        detection: FaceDetection;
+    }>;
+    withFaceExpressions(): PredictAllFaceExpressionsTask<{
+        detection: FaceDetection;
+    }>;
+    withAgeAndGender(): PredictAllAgeAndGenderTask<{
+        detection: FaceDetection;
+    }>;
 }
 export declare class DetectSingleFaceTask extends DetectFacesTaskBase<FaceDetection | undefined> {
     run(): Promise<FaceDetection | undefined>;
     private runAndExtendWithFaceDetection;
-    withFaceLandmarks(useTinyLandmarkNet?: boolean): DetectSingleFaceLandmarksTask<WithFaceDetection<{}>>;
-    withFaceExpressions(): PredictSingleFaceExpressionTask<WithFaceDetection<{}>>;
+    withFaceLandmarks(useTinyLandmarkNet?: boolean): DetectSingleFaceLandmarksTask<{
+        detection: FaceDetection;
+    }>;
+    withFaceExpressions(): PredictSingleFaceExpressionsTask<{
+        detection: FaceDetection;
+    }>;
+    withAgeAndGender(): PredictSingleAgeAndGenderTask<{
+        detection: FaceDetection;
+    }>;
 }

build/commonjs/globalApi/DetectFacesTasks.js

@@ -9,6 +9,7 @@ var TinyFaceDetectorOptions_1 = require("../tinyFaceDetector/TinyFaceDetectorOpt
 var ComposableTask_1 = require("./ComposableTask");
 var DetectFaceLandmarksTasks_1 = require("./DetectFaceLandmarksTasks");
 var nets_1 = require("./nets");
+var PredictAgeAndGenderTask_1 = require("./PredictAgeAndGenderTask");
 var PredictFaceExpressionsTask_1 = require("./PredictFaceExpressionsTask");
 var DetectFacesTaskBase = /** @class */ (function (_super) {
     tslib_1.__extends(DetectFacesTaskBase, _super);
@@ -75,6 +76,9 @@ var DetectAllFacesTask = /** @class */ (function (_super) {
     DetectAllFacesTask.prototype.withFaceExpressions = function () {
         return new PredictFaceExpressionsTask_1.PredictAllFaceExpressionsTask(this.runAndExtendWithFaceDetections(), this.input);
     };
+    DetectAllFacesTask.prototype.withAgeAndGender = function () {
+        return new PredictAgeAndGenderTask_1.PredictAllAgeAndGenderTask(this.runAndExtendWithFaceDetections(), this.input);
+    };
     return DetectAllFacesTask;
 }(DetectFacesTaskBase));
 exports.DetectAllFacesTask = DetectAllFacesTask;
@@ -121,7 +125,10 @@ var DetectSingleFaceTask = /** @class */ (function (_super) {
         return new DetectFaceLandmarksTasks_1.DetectSingleFaceLandmarksTask(this.runAndExtendWithFaceDetection(), this.input, useTinyLandmarkNet);
     };
     DetectSingleFaceTask.prototype.withFaceExpressions = function () {
-        return new PredictFaceExpressionsTask_1.PredictSingleFaceExpressionTask(this.runAndExtendWithFaceDetection(), this.input);
+        return new PredictFaceExpressionsTask_1.PredictSingleFaceExpressionsTask(this.runAndExtendWithFaceDetection(), this.input);
+    };
+    DetectSingleFaceTask.prototype.withAgeAndGender = function () {
+        return new PredictAgeAndGenderTask_1.PredictSingleAgeAndGenderTask(this.runAndExtendWithFaceDetection(), this.input);
     };
     return DetectSingleFaceTask;
 }(DetectFacesTaskBase));

build/commonjs/globalApi/DetectFacesTasks.js.map

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build/commonjs/globalApi/PredictAgeAndGenderTask.d.ts

+import * as tf from '@tensorflow/tfjs-core';
+import { TNetInput } from 'tfjs-image-recognition-base';
+import { WithAge } from '../factories/WithAge';
+import { WithFaceDetection } from '../factories/WithFaceDetection';
+import { WithFaceLandmarks } from '../factories/WithFaceLandmarks';
+import { WithGender } from '../factories/WithGender';
+import { ComposableTask } from './ComposableTask';
+import { ComputeAllFaceDescriptorsTask, ComputeSingleFaceDescriptorTask } from './ComputeFaceDescriptorsTasks';
+import { PredictAllFaceExpressionsTask, PredictAllFaceExpressionsWithFaceAlignmentTask, PredictSingleFaceExpressionsTask, PredictSingleFaceExpressionsWithFaceAlignmentTask } from './PredictFaceExpressionsTask';
+export declare class PredictAgeAndGenderTaskBase<TReturn, TParentReturn> extends ComposableTask<TReturn> {
+    protected parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>;
+    protected input: TNetInput;
+    protected extractedFaces?: (HTMLCanvasElement | tf.Tensor<tf.Rank.R3>)[] | undefined;
+    constructor(parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>, input: TNetInput, extractedFaces?: (HTMLCanvasElement | tf.Tensor<tf.Rank.R3>)[] | undefined);
+}
+export declare class PredictAllAgeAndGenderTask<TSource extends WithFaceDetection<{}>> extends PredictAgeAndGenderTaskBase<WithAge<WithGender<TSource>>[], TSource[]> {
+    run(): Promise<WithAge<WithGender<TSource>>[]>;
+    withFaceExpressions(): PredictAllFaceExpressionsTask<WithAge<WithGender<TSource>>>;
+}
+export declare class PredictSingleAgeAndGenderTask<TSource extends WithFaceDetection<{}>> extends PredictAgeAndGenderTaskBase<WithAge<WithGender<TSource>> | undefined, TSource | undefined> {
+    run(): Promise<WithAge<WithGender<TSource>> | undefined>;
+    withFaceExpressions(): PredictSingleFaceExpressionsTask<WithAge<WithGender<TSource>>>;
+}
+export declare class PredictAllAgeAndGenderWithFaceAlignmentTask<TSource extends WithFaceLandmarks<WithFaceDetection<{}>>> extends PredictAllAgeAndGenderTask<TSource> {
+    withFaceExpressions(): PredictAllFaceExpressionsWithFaceAlignmentTask<WithAge<WithGender<TSource>>>;
+    withFaceDescriptors(): ComputeAllFaceDescriptorsTask<WithAge<WithGender<TSource>>>;
+}
+export declare class PredictSingleAgeAndGenderWithFaceAlignmentTask<TSource extends WithFaceLandmarks<WithFaceDetection<{}>>> extends PredictSingleAgeAndGenderTask<TSource> {
+    withFaceExpressions(): PredictSingleFaceExpressionsWithFaceAlignmentTask<WithAge<WithGender<TSource>>>;
+    withFaceDescriptor(): ComputeSingleFaceDescriptorTask<WithAge<WithGender<TSource>>>;
+}

build/commonjs/globalApi/PredictAgeAndGenderTask.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+var tslib_1 = require("tslib");
+var WithAge_1 = require("../factories/WithAge");
+var WithGender_1 = require("../factories/WithGender");
+var ComposableTask_1 = require("./ComposableTask");
+var ComputeFaceDescriptorsTasks_1 = require("./ComputeFaceDescriptorsTasks");
+var extractFacesAndComputeResults_1 = require("./extractFacesAndComputeResults");
+var nets_1 = require("./nets");
+var PredictFaceExpressionsTask_1 = require("./PredictFaceExpressionsTask");
+var PredictAgeAndGenderTaskBase = /** @class */ (function (_super) {
+    tslib_1.__extends(PredictAgeAndGenderTaskBase, _super);
+    function PredictAgeAndGenderTaskBase(parentTask, input, extractedFaces) {
+        var _this = _super.call(this) || this;
+        _this.parentTask = parentTask;
+        _this.input = input;
+        _this.extractedFaces = extractedFaces;
+        return _this;
+    }
+    return PredictAgeAndGenderTaskBase;
+}(ComposableTask_1.ComposableTask));
+exports.PredictAgeAndGenderTaskBase = PredictAgeAndGenderTaskBase;
+var PredictAllAgeAndGenderTask = /** @class */ (function (_super) {
+    tslib_1.__extends(PredictAllAgeAndGenderTask, _super);
+    function PredictAllAgeAndGenderTask() {
+        return _super !== null && _super.apply(this, arguments) || this;
+    }
+    PredictAllAgeAndGenderTask.prototype.run = function () {
+        return tslib_1.__awaiter(this, void 0, void 0, function () {
+            var parentResults, ageAndGenderByFace;
+            var _this = this;
+            return tslib_1.__generator(this, function (_a) {
+                switch (_a.label) {
+                    case 0: return [4 /*yield*/, this.parentTask];
+                    case 1:
+                        parentResults = _a.sent();
+                        return [4 /*yield*/, extractFacesAndComputeResults_1.extractAllFacesAndComputeResults(parentResults, this.input, function (faces) { return tslib_1.__awaiter(_this, void 0, void 0, function () {
+                                return tslib_1.__generator(this, function (_a) {
+                                    switch (_a.label) {
+                                        case 0: return [4 /*yield*/, Promise.all(faces.map(function (face) { return nets_1.nets.ageGenderNet.predictAgeAndGender(face); }))];
+                                        case 1: return [2 /*return*/, _a.sent()];
+                                    }
+                                });
+                            }); }, this.extractedFaces)];
+                    case 2:
+                        ageAndGenderByFace = _a.sent();
+                        return [2 /*return*/, parentResults.map(function (parentResult, i) {
+                                var _a = ageAndGenderByFace[i], age = _a.age, gender = _a.gender, genderProbability = _a.genderProbability;
+                                return WithAge_1.extendWithAge(WithGender_1.extendWithGender(parentResult, gender, genderProbability), age);
+                            })];
+                }
+            });
+        });
+    };
+    PredictAllAgeAndGenderTask.prototype.withFaceExpressions = function () {
+        return new PredictFaceExpressionsTask_1.PredictAllFaceExpressionsTask(this, this.input);
+    };
+    return PredictAllAgeAndGenderTask;
+}(PredictAgeAndGenderTaskBase));
+exports.PredictAllAgeAndGenderTask = PredictAllAgeAndGenderTask;
+var PredictSingleAgeAndGenderTask = /** @class */ (function (_super) {
+    tslib_1.__extends(PredictSingleAgeAndGenderTask, _super);
+    function PredictSingleAgeAndGenderTask() {
+        return _super !== null && _super.apply(this, arguments) || this;
+    }
+    PredictSingleAgeAndGenderTask.prototype.run = function () {
+        return tslib_1.__awaiter(this, void 0, void 0, function () {
+            var parentResult, _a, age, gender, genderProbability;
+            return tslib_1.__generator(this, function (_b) {
+                switch (_b.label) {
+                    case 0: return [4 /*yield*/, this.parentTask];
+                    case 1:
+                        parentResult = _b.sent();
+                        if (!parentResult) {
+                            return [2 /*return*/];
+                        }
+                        return [4 /*yield*/, extractFacesAndComputeResults_1.extractSingleFaceAndComputeResult(parentResult, this.input, function (face) { return nets_1.nets.ageGenderNet.predictAgeAndGender(face); }, this.extractedFaces)];
+                    case 2:
+                        _a = _b.sent(), age = _a.age, gender = _a.gender, genderProbability = _a.genderProbability;
+                        return [2 /*return*/, WithAge_1.extendWithAge(WithGender_1.extendWithGender(parentResult, gender, genderProbability), age)];
+                }
+            });
+        });
+    };
+    PredictSingleAgeAndGenderTask.prototype.withFaceExpressions = function () {
+        return new PredictFaceExpressionsTask_1.PredictSingleFaceExpressionsTask(this, this.input);
+    };
+    return PredictSingleAgeAndGenderTask;
+}(PredictAgeAndGenderTaskBase));
+exports.PredictSingleAgeAndGenderTask = PredictSingleAgeAndGenderTask;
+var PredictAllAgeAndGenderWithFaceAlignmentTask = /** @class */ (function (_super) {
+    tslib_1.__extends(PredictAllAgeAndGenderWithFaceAlignmentTask, _super);
+    function PredictAllAgeAndGenderWithFaceAlignmentTask() {
+        return _super !== null && _super.apply(this, arguments) || this;
+    }
+    PredictAllAgeAndGenderWithFaceAlignmentTask.prototype.withFaceExpressions = function () {
+        return new PredictFaceExpressionsTask_1.PredictAllFaceExpressionsWithFaceAlignmentTask(this, this.input);
+    };
+    PredictAllAgeAndGenderWithFaceAlignmentTask.prototype.withFaceDescriptors = function () {
+        return new ComputeFaceDescriptorsTasks_1.ComputeAllFaceDescriptorsTask(this, this.input);
+    };
+    return PredictAllAgeAndGenderWithFaceAlignmentTask;
+}(PredictAllAgeAndGenderTask));
+exports.PredictAllAgeAndGenderWithFaceAlignmentTask = PredictAllAgeAndGenderWithFaceAlignmentTask;
+var PredictSingleAgeAndGenderWithFaceAlignmentTask = /** @class */ (function (_super) {
+    tslib_1.__extends(PredictSingleAgeAndGenderWithFaceAlignmentTask, _super);
+    function PredictSingleAgeAndGenderWithFaceAlignmentTask() {
+        return _super !== null && _super.apply(this, arguments) || this;
+    }
+    PredictSingleAgeAndGenderWithFaceAlignmentTask.prototype.withFaceExpressions = function () {
+        return new PredictFaceExpressionsTask_1.PredictSingleFaceExpressionsWithFaceAlignmentTask(this, this.input);
+    };
+    PredictSingleAgeAndGenderWithFaceAlignmentTask.prototype.withFaceDescriptor = function () {
+        return new ComputeFaceDescriptorsTasks_1.ComputeSingleFaceDescriptorTask(this, this.input);
+    };
+    return PredictSingleAgeAndGenderWithFaceAlignmentTask;
+}(PredictSingleAgeAndGenderTask));
+exports.PredictSingleAgeAndGenderWithFaceAlignmentTask = PredictSingleAgeAndGenderWithFaceAlignmentTask;
+//# sourceMappingURL=PredictAgeAndGenderTask.js.map
\ No newline at end of file

build/commonjs/globalApi/PredictAgeAndGenderTask.js.map

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build/commonjs/globalApi/PredictFaceExpressionsTask.d.ts

+import * as tf from '@tensorflow/tfjs-core';
 import { TNetInput } from 'tfjs-image-recognition-base';
 import { WithFaceDetection } from '../factories/WithFaceDetection';
 import { WithFaceExpressions } from '../factories/WithFaceExpressions';
+import { WithFaceLandmarks } from '../factories/WithFaceLandmarks';
 import { ComposableTask } from './ComposableTask';
-import { DetectAllFaceLandmarksTask, DetectSingleFaceLandmarksTask } from './DetectFaceLandmarksTasks';
+import { ComputeAllFaceDescriptorsTask, ComputeSingleFaceDescriptorTask } from './ComputeFaceDescriptorsTasks';
+import { PredictAllAgeAndGenderTask, PredictAllAgeAndGenderWithFaceAlignmentTask, PredictSingleAgeAndGenderTask, PredictSingleAgeAndGenderWithFaceAlignmentTask } from './PredictAgeAndGenderTask';
 export declare class PredictFaceExpressionsTaskBase<TReturn, TParentReturn> extends ComposableTask<TReturn> {
     protected parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>;
     protected input: TNetInput;
-    constructor(parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>, input: TNetInput);
+    protected extractedFaces?: (HTMLCanvasElement | tf.Tensor<tf.Rank.R3>)[] | undefined;
+    constructor(parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>, input: TNetInput, extractedFaces?: (HTMLCanvasElement | tf.Tensor<tf.Rank.R3>)[] | undefined);
 }
 export declare class PredictAllFaceExpressionsTask<TSource extends WithFaceDetection<{}>> extends PredictFaceExpressionsTaskBase<WithFaceExpressions<TSource>[], TSource[]> {
     run(): Promise<WithFaceExpressions<TSource>[]>;
-    withFaceLandmarks(): DetectAllFaceLandmarksTask<WithFaceExpressions<TSource>>;
+    withAgeAndGender(): PredictAllAgeAndGenderTask<WithFaceExpressions<TSource>>;
 }
-export declare class PredictSingleFaceExpressionTask<TSource extends WithFaceDetection<{}>> extends PredictFaceExpressionsTaskBase<WithFaceExpressions<TSource> | undefined, TSource | undefined> {
+export declare class PredictSingleFaceExpressionsTask<TSource extends WithFaceDetection<{}>> extends PredictFaceExpressionsTaskBase<WithFaceExpressions<TSource> | undefined, TSource | undefined> {
     run(): Promise<WithFaceExpressions<TSource> | undefined>;
-    withFaceLandmarks(): DetectSingleFaceLandmarksTask<WithFaceExpressions<TSource>>;
+    withAgeAndGender(): PredictSingleAgeAndGenderTask<WithFaceExpressions<TSource>>;
+}
+export declare class PredictAllFaceExpressionsWithFaceAlignmentTask<TSource extends WithFaceLandmarks<WithFaceDetection<{}>>> extends PredictAllFaceExpressionsTask<TSource> {
+    withAgeAndGender(): PredictAllAgeAndGenderWithFaceAlignmentTask<WithFaceExpressions<TSource>>;
+    withFaceDescriptors(): ComputeAllFaceDescriptorsTask<WithFaceExpressions<TSource>>;
+}
+export declare class PredictSingleFaceExpressionsWithFaceAlignmentTask<TSource extends WithFaceLandmarks<WithFaceDetection<{}>>> extends PredictSingleFaceExpressionsTask<TSource> {
+    withAgeAndGender(): PredictSingleAgeAndGenderWithFaceAlignmentTask<WithFaceExpressions<TSource>>;
+    withFaceDescriptor(): ComputeSingleFaceDescriptorTask<WithFaceExpressions<TSource>>;
 }

build/commonjs/globalApi/PredictFaceExpressionsTask.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
 var tslib_1 = require("tslib");
-var tf = require("@tensorflow/tfjs-core");
-var dom_1 = require("../dom");
 var WithFaceExpressions_1 = require("../factories/WithFaceExpressions");
 var ComposableTask_1 = require("./ComposableTask");
-var DetectFaceLandmarksTasks_1 = require("./DetectFaceLandmarksTasks");
+var ComputeFaceDescriptorsTasks_1 = require("./ComputeFaceDescriptorsTasks");
+var extractFacesAndComputeResults_1 = require("./extractFacesAndComputeResults");
 var nets_1 = require("./nets");
+var PredictAgeAndGenderTask_1 = require("./PredictAgeAndGenderTask");
 var PredictFaceExpressionsTaskBase = /** @class */ (function (_super) {
     tslib_1.__extends(PredictFaceExpressionsTaskBase, _super);
-    function PredictFaceExpressionsTaskBase(parentTask, input) {
+    function PredictFaceExpressionsTaskBase(parentTask, input, extractedFaces) {
         var _this = _super.call(this) || this;
         _this.parentTask = parentTask;
         _this.input = input;
+        _this.extractedFaces = extractedFaces;
         return _this;
     }
     return PredictFaceExpressionsTaskBase;
@@ -25,80 +26,90 @@ var PredictAllFaceExpressionsTask = /** @class */ (function (_super) {
     }
     PredictAllFaceExpressionsTask.prototype.run = function () {
         return tslib_1.__awaiter(this, void 0, void 0, function () {
-            var parentResults, detections, faces, _a, faceExpressionsByFace;
-            return tslib_1.__generator(this, function (_b) {
-                switch (_b.label) {
+            var parentResults, faceExpressionsByFace;
+            var _this = this;
+            return tslib_1.__generator(this, function (_a) {
+                switch (_a.label) {
                     case 0: return [4 /*yield*/, this.parentTask];
                     case 1:
-                        parentResults = _b.sent();
-                        detections = parentResults.map(function (parentResult) { return parentResult.detection; });
-                        if (!(this.input instanceof tf.Tensor)) return [3 /*break*/, 3];
-                        return [4 /*yield*/, dom_1.extractFaceTensors(this.input, detections)];
+                        parentResults = _a.sent();
+                        return [4 /*yield*/, extractFacesAndComputeResults_1.extractAllFacesAndComputeResults(parentResults, this.input, function (faces) { return tslib_1.__awaiter(_this, void 0, void 0, function () {
+                                return tslib_1.__generator(this, function (_a) {
+                                    switch (_a.label) {
+                                        case 0: return [4 /*yield*/, Promise.all(faces.map(function (face) { return nets_1.nets.faceExpressionNet.predictExpressions(face); }))];
+                                        case 1: return [2 /*return*/, _a.sent()];
+                                    }
+                                });
+                            }); }, this.extractedFaces)];
                     case 2:
-                        _a = _b.sent();
-                        return [3 /*break*/, 5];
-                    case 3: return [4 /*yield*/, dom_1.extractFaces(this.input, detections)];
-                    case 4:
-                        _a = _b.sent();
-                        _b.label = 5;
-                    case 5:
-                        faces = _a;
-                        return [4 /*yield*/, Promise.all(faces.map(function (face) { return nets_1.nets.faceExpressionNet.predictExpressions(face); }))];
-                    case 6:
-                        faceExpressionsByFace = _b.sent();
-                        faces.forEach(function (f) { return f instanceof tf.Tensor && f.dispose(); });
+                        faceExpressionsByFace = _a.sent();
                         return [2 /*return*/, parentResults.map(function (parentResult, i) { return WithFaceExpressions_1.extendWithFaceExpressions(parentResult, faceExpressionsByFace[i]); })];
                 }
             });
         });
     };
-    PredictAllFaceExpressionsTask.prototype.withFaceLandmarks = function () {
-        return new DetectFaceLandmarksTasks_1.DetectAllFaceLandmarksTask(this, this.input, false);
+    PredictAllFaceExpressionsTask.prototype.withAgeAndGender = function () {
+        return new PredictAgeAndGenderTask_1.PredictAllAgeAndGenderTask(this, this.input);
     };
     return PredictAllFaceExpressionsTask;
 }(PredictFaceExpressionsTaskBase));
 exports.PredictAllFaceExpressionsTask = PredictAllFaceExpressionsTask;
-var PredictSingleFaceExpressionTask = /** @class */ (function (_super) {
-    tslib_1.__extends(PredictSingleFaceExpressionTask, _super);
-    function PredictSingleFaceExpressionTask() {
+var PredictSingleFaceExpressionsTask = /** @class */ (function (_super) {
+    tslib_1.__extends(PredictSingleFaceExpressionsTask, _super);
+    function PredictSingleFaceExpressionsTask() {
         return _super !== null && _super.apply(this, arguments) || this;
     }
-    PredictSingleFaceExpressionTask.prototype.run = function () {
+    PredictSingleFaceExpressionsTask.prototype.run = function () {
         return tslib_1.__awaiter(this, void 0, void 0, function () {
-            var parentResult, detection, faces, _a, faceExpressions;
-            return tslib_1.__generator(this, function (_b) {
-                switch (_b.label) {
+            var parentResult, faceExpressions;
+            return tslib_1.__generator(this, function (_a) {
+                switch (_a.label) {
                     case 0: return [4 /*yield*/, this.parentTask];
                     case 1:
-                        parentResult = _b.sent();
+                        parentResult = _a.sent();
                         if (!parentResult) {
                             return [2 /*return*/];
                         }
-                        detection = parentResult.detection;
-                        if (!(this.input instanceof tf.Tensor)) return [3 /*break*/, 3];
-                        return [4 /*yield*/, dom_1.extractFaceTensors(this.input, [detection])];
+                        return [4 /*yield*/, extractFacesAndComputeResults_1.extractSingleFaceAndComputeResult(parentResult, this.input, function (face) { return nets_1.nets.faceExpressionNet.predictExpressions(face); }, this.extractedFaces)];
                     case 2:
-                        _a = _b.sent();
-                        return [3 /*break*/, 5];
-                    case 3: return [4 /*yield*/, dom_1.extractFaces(this.input, [detection])];
-                    case 4:
-                        _a = _b.sent();
-                        _b.label = 5;
-                    case 5:
-                        faces = _a;
-                        return [4 /*yield*/, nets_1.nets.faceExpressionNet.predictExpressions(faces[0])];
-                    case 6:
-                        faceExpressions = _b.sent();
-                        faces.forEach(function (f) { return f instanceof tf.Tensor && f.dispose(); });
+                        faceExpressions = _a.sent();
                         return [2 /*return*/, WithFaceExpressions_1.extendWithFaceExpressions(parentResult, faceExpressions)];
                 }
             });
         });
     };
-    PredictSingleFaceExpressionTask.prototype.withFaceLandmarks = function () {
-        return new DetectFaceLandmarksTasks_1.DetectSingleFaceLandmarksTask(this, this.input, false);
+    PredictSingleFaceExpressionsTask.prototype.withAgeAndGender = function () {
+        return new PredictAgeAndGenderTask_1.PredictSingleAgeAndGenderTask(this, this.input);
     };
-    return PredictSingleFaceExpressionTask;
+    return PredictSingleFaceExpressionsTask;
 }(PredictFaceExpressionsTaskBase));
-exports.PredictSingleFaceExpressionTask = PredictSingleFaceExpressionTask;
+exports.PredictSingleFaceExpressionsTask = PredictSingleFaceExpressionsTask;
+var PredictAllFaceExpressionsWithFaceAlignmentTask = /** @class */ (function (_super) {
+    tslib_1.__extends(PredictAllFaceExpressionsWithFaceAlignmentTask, _super);
+    function PredictAllFaceExpressionsWithFaceAlignmentTask() {
+        return _super !== null && _super.apply(this, arguments) || this;
+    }
+    PredictAllFaceExpressionsWithFaceAlignmentTask.prototype.withAgeAndGender = function () {
+        return new PredictAgeAndGenderTask_1.PredictAllAgeAndGenderWithFaceAlignmentTask(this, this.input);
+    };
+    PredictAllFaceExpressionsWithFaceAlignmentTask.prototype.withFaceDescriptors = function () {
+        return new ComputeFaceDescriptorsTasks_1.ComputeAllFaceDescriptorsTask(this, this.input);
+    };
+    return PredictAllFaceExpressionsWithFaceAlignmentTask;
+}(PredictAllFaceExpressionsTask));
+exports.PredictAllFaceExpressionsWithFaceAlignmentTask = PredictAllFaceExpressionsWithFaceAlignmentTask;
+var PredictSingleFaceExpressionsWithFaceAlignmentTask = /** @class */ (function (_super) {
+    tslib_1.__extends(PredictSingleFaceExpressionsWithFaceAlignmentTask, _super);
+    function PredictSingleFaceExpressionsWithFaceAlignmentTask() {
+        return _super !== null && _super.apply(this, arguments) || this;
+    }
+    PredictSingleFaceExpressionsWithFaceAlignmentTask.prototype.withAgeAndGender = function () {
+        return new PredictAgeAndGenderTask_1.PredictSingleAgeAndGenderWithFaceAlignmentTask(this, this.input);
+    };
+    PredictSingleFaceExpressionsWithFaceAlignmentTask.prototype.withFaceDescriptor = function () {
+        return new ComputeFaceDescriptorsTasks_1.ComputeSingleFaceDescriptorTask(this, this.input);
+    };
+    return PredictSingleFaceExpressionsWithFaceAlignmentTask;
+}(PredictSingleFaceExpressionsTask));
+exports.PredictSingleFaceExpressionsWithFaceAlignmentTask = PredictSingleFaceExpressionsWithFaceAlignmentTask;
 //# sourceMappingURL=PredictFaceExpressionsTask.js.map
\ No newline at end of file

build/commonjs/globalApi/PredictFaceExpressionsTask.js.map

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+{"version":3,"file":"PredictFaceExpressionsTask.js","sourceRoot":"","sources":["../../../src/globalApi/PredictFaceExpressionsTask.ts"],"names":[],"mappings":";;;AAKA,wEAAkG;AAElG,mDAAkD;AAClD,6EAA+G;AAC/G,iFAAsH;AACtH,+BAA8B;AAC9B,qEAKmC;AAEnC;IAA4E,0DAAuB;IACjG,wCACY,UAAkE,EAClE,KAAgB,EAChB,cAAuD;QAHnE,YAKE,iBAAO,SACR;QALW,gBAAU,GAAV,UAAU,CAAwD;QAClE,WAAK,GAAL,KAAK,CAAW;QAChB,oBAAc,GAAd,cAAc,CAAyC;;IAGnE,CAAC;IACH,qCAAC;AAAD,CAAC,AARD,CAA4E,+BAAc,GAQzF;AARY,wEAA8B;AAU3C;IAEU,yDAAyE;IAFnF;;IAyBA,CAAC;IArBc,2CAAG,GAAhB;;;;;;4BAEwB,qBAAM,IAAI,CAAC,UAAU,EAAA;;wBAArC,aAAa,GAAG,SAAqB;wBAEb,qBAAM,gEAAgC,CAClE,aAAa,EACb,IAAI,CAAC,KAAK,EACV,UAAM,KAAK;;;gDAAI,qBAAM,OAAO,CAAC,GAAG,CAAC,KAAK,CAAC,GAAG,CACxC,UAAA,IAAI,IAAI,OAAA,WAAI,CAAC,iBAAiB,CAAC,kBAAkB,CAAC,IAAI,CAA6B,EAA3E,CAA2E,CACpF,CAAC,EAAA;gDAFa,sBAAA,SAEb,EAAA;;;iCAAA,EACF,IAAI,CAAC,cAAc,CACpB,EAAA;;wBAPK,qBAAqB,GAAG,SAO7B;wBAED,sBAAO,aAAa,CAAC,GAAG,CACtB,UAAC,YAAY,EAAE,CAAC,IAAK,OAAA,+CAAyB,CAAU,YAAY,EAAE,qBAAqB,CAAC,CAAC,CAAC,CAAC,EAA1E,CAA0E,CAChG,EAAA;;;;KACF;IAED,wDAAgB,GAAhB;QACE,OAAO,IAAI,oDAA0B,CAAC,IAAI,EAAE,IAAI,CAAC,KAAK,CAAC,CAAA;IACzD,CAAC;IACH,oCAAC;AAAD,CAAC,AAzBD,CAEU,8BAA8B,GAuBvC;AAzBY,sEAA6B;AA2B1C;IAEW,4DAA6F;IAFxG;;IAwBA,CAAC;IApBc,8CAAG,GAAhB;;;;;4BAEuB,qBAAM,IAAI,CAAC,UAAU,EAAA;;wBAApC,YAAY,GAAG,SAAqB;wBAC1C,IAAI,CAAC,YAAY,EAAE;4BACjB,sBAAM;yBACP;wBAEuB,qBAAM,iEAAiC,CAC7D,YAAY,EACZ,IAAI,CAAC,KAAK,EACV,UAAA,IAAI,IAAI,OAAA,WAAI,CAAC,iBAAiB,CAAC,kBAAkB,CAAC,IAAI,CAA6B,EAA3E,CAA2E,EACnF,IAAI,CAAC,cAAc,CACpB,EAAA;;wBALK,eAAe,GAAG,SAKvB;wBAED,sBAAO,+CAAyB,CAAC,YAAY,EAAE,eAAe,CAAC,EAAA;;;;KAChE;IAED,2DAAgB,GAAhB;QACE,OAAO,IAAI,uDAA6B,CAAC,IAAI,EAAE,IAAI,CAAC,KAAK,CAAC,CAAA;IAC5D,CAAC;IACH,uCAAC;AAAD,CAAC,AAxBD,CAEW,8BAA8B,GAsBxC;AAxBY,4EAAgC;AA0B7C;IAEU,0EAAsC;IAFhD;;IAWA,CAAC;IAPC,yEAAgB,GAAhB;QACE,OAAO,IAAI,qEAA2C,CAAC,IAAI,EAAE,IAAI,CAAC,KAAK,CAAC,CAAA;IAC1E,CAAC;IAED,4EAAmB,GAAnB;QACE,OAAO,IAAI,2DAA6B,CAAC,IAAI,EAAE,IAAI,CAAC,KAAK,CAAC,CAAA;IAC5D,CAAC;IACH,qDAAC;AAAD,CAAC,AAXD,CAEU,6BAA6B,GAStC;AAXY,wGAA8C;AAa3D;IAEU,6EAAyC;IAFnD;;IAWA,CAAC;IAPC,4EAAgB,GAAhB;QACE,OAAO,IAAI,wEAA8C,CAAC,IAAI,EAAE,IAAI,CAAC,KAAK,CAAC,CAAA;IAC7E,CAAC;IAED,8EAAkB,GAAlB;QACE,OAAO,IAAI,6DAA+B,CAAC,IAAI,EAAE,IAAI,CAAC,KAAK,CAAC,CAAA;IAC9D,CAAC;IACH,wDAAC;AAAD,CAAC,AAXD,CAEU,gCAAgC,GASzC;AAXY,8GAAiD"}
\ No newline at end of file

build/commonjs/globalApi/extractFacesAndComputeResults.d.ts

+import * as tf from '@tensorflow/tfjs-core';
+import { TNetInput } from 'tfjs-image-recognition-base';
+import { FaceDetection } from '../classes/FaceDetection';
+import { WithFaceDetection } from '../factories/WithFaceDetection';
+import { WithFaceLandmarks } from '../factories/WithFaceLandmarks';
+export declare function extractAllFacesAndComputeResults<TSource extends WithFaceDetection<{}>, TResult>(parentResults: TSource[], input: TNetInput, computeResults: (faces: Array<HTMLCanvasElement | tf.Tensor3D>) => Promise<TResult>, extractedFaces?: Array<HTMLCanvasElement | tf.Tensor3D> | null, getRectForAlignment?: (parentResult: WithFaceLandmarks<TSource, any>) => FaceDetection): Promise<TResult>;
+export declare function extractSingleFaceAndComputeResult<TSource extends WithFaceDetection<{}>, TResult>(parentResult: TSource, input: TNetInput, computeResult: (face: HTMLCanvasElement | tf.Tensor3D) => Promise<TResult>, extractedFaces?: Array<HTMLCanvasElement | tf.Tensor3D> | null, getRectForAlignment?: (parentResult: WithFaceLandmarks<TSource, any>) => FaceDetection): Promise<TResult>;

build/commonjs/globalApi/extractFacesAndComputeResults.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+var tslib_1 = require("tslib");
+var tf = require("@tensorflow/tfjs-core");
+var dom_1 = require("../dom");
+var WithFaceLandmarks_1 = require("../factories/WithFaceLandmarks");
+function extractAllFacesAndComputeResults(parentResults, input, computeResults, extractedFaces, getRectForAlignment) {
+    if (getRectForAlignment === void 0) { getRectForAlignment = function (_a) {
+        var alignedRect = _a.alignedRect;
+        return alignedRect;
+    }; }
+    return tslib_1.__awaiter(this, void 0, void 0, function () {
+        var faceBoxes, faces, _a, _b, results;
+        return tslib_1.__generator(this, function (_c) {
+            switch (_c.label) {
+                case 0:
+                    faceBoxes = parentResults.map(function (parentResult) {
+                        return WithFaceLandmarks_1.isWithFaceLandmarks(parentResult)
+                            ? getRectForAlignment(parentResult)
+                            : parentResult.detection;
+                    });
+                    _a = extractedFaces;
+                    if (_a) return [3 /*break*/, 5];
+                    if (!(input instanceof tf.Tensor)) return [3 /*break*/, 2];
+                    return [4 /*yield*/, dom_1.extractFaceTensors(input, faceBoxes)];
+                case 1:
+                    _b = _c.sent();
+                    return [3 /*break*/, 4];
+                case 2: return [4 /*yield*/, dom_1.extractFaces(input, faceBoxes)];
+                case 3:
+                    _b = _c.sent();
+                    _c.label = 4;
+                case 4:
+                    _a = (_b);
+                    _c.label = 5;
+                case 5:
+                    faces = _a;
+                    return [4 /*yield*/, computeResults(faces)];
+                case 6:
+                    results = _c.sent();
+                    faces.forEach(function (f) { return f instanceof tf.Tensor && f.dispose(); });
+                    return [2 /*return*/, results];
+            }
+        });
+    });
+}
+exports.extractAllFacesAndComputeResults = extractAllFacesAndComputeResults;
+function extractSingleFaceAndComputeResult(parentResult, input, computeResult, extractedFaces, getRectForAlignment) {
+    return tslib_1.__awaiter(this, void 0, void 0, function () {
+        var _this = this;
+        return tslib_1.__generator(this, function (_a) {
+            return [2 /*return*/, extractAllFacesAndComputeResults([parentResult], input, function (faces) { return tslib_1.__awaiter(_this, void 0, void 0, function () { return tslib_1.__generator(this, function (_a) {
+                    return [2 /*return*/, computeResult(faces[0])];
+                }); }); }, extractedFaces, getRectForAlignment)];
+        });
+    });
+}
+exports.extractSingleFaceAndComputeResult = extractSingleFaceAndComputeResult;
+//# sourceMappingURL=extractFacesAndComputeResults.js.map
\ No newline at end of file

build/commonjs/globalApi/extractFacesAndComputeResults.js.map

+{"version":3,"file":"extractFacesAndComputeResults.js","sourceRoot":"","sources":["../../../src/globalApi/extractFacesAndComputeResults.ts"],"names":[],"mappings":";;;AAAA,0CAA4C;AAI5C,8BAA0D;AAE1D,oEAAwF;AAExF,SAAsB,gCAAgC,CACpD,aAAwB,EACxB,KAAgB,EAChB,cAAmF,EACnF,cAA8D,EAC9D,mBAAwH;IAAxH,oCAAA,EAAA,gCAAyF,EAAe;YAAb,4BAAW;QAAO,OAAA,WAAW;IAAX,CAAW;;;;;;oBAElH,SAAS,GAAG,aAAa,CAAC,GAAG,CAAC,UAAA,YAAY;wBAC9C,OAAA,uCAAmB,CAAC,YAAY,CAAC;4BAC/B,CAAC,CAAC,mBAAmB,CAAC,YAAY,CAAC;4BACnC,CAAC,CAAC,YAAY,CAAC,SAAS;oBAF1B,CAE0B,CAC3B,CAAA;oBACqD,KAAA,cAAc,CAAA;4BAAd,wBAAc;yBAClE,CAAA,KAAK,YAAY,EAAE,CAAC,MAAM,CAAA,EAA1B,wBAA0B;oBACtB,qBAAM,wBAAkB,CAAC,KAAK,EAAE,SAAS,CAAC,EAAA;;oBAA1C,KAAA,SAA0C,CAAA;;wBAC1C,qBAAM,kBAAY,CAAC,KAAK,EAAE,SAAS,CAAC,EAAA;;oBAApC,KAAA,SAAoC,CAAA;;;oBAH8B,KAAA,IAIvE,CAAA;;;oBAJK,KAAK,KAIV;oBAEe,qBAAM,cAAc,CAAC,KAAK,CAAC,EAAA;;oBAArC,OAAO,GAAG,SAA2B;oBAE3C,KAAK,CAAC,OAAO,CAAC,UAAA,CAAC,IAAI,OAAA,CAAC,YAAY,EAAE,CAAC,MAAM,IAAI,CAAC,CAAC,OAAO,EAAE,EAArC,CAAqC,CAAC,CAAA;oBAEzD,sBAAO,OAAO,EAAA;;;;CACf;AAvBD,4EAuBC;AAED,SAAsB,iCAAiC,CACrD,YAAqB,EACrB,KAAgB,EAChB,aAA0E,EAC1E,cAA8D,EAC9D,mBAAsF;;;;YAEtF,sBAAO,gCAAgC,CACrC,CAAC,YAAY,CAAC,EACd,KAAK,EACL,UAAM,KAAK;oBAAI,sBAAA,aAAa,CAAC,KAAK,CAAC,CAAC,CAAC,CAAC,EAAA;yBAAA,EACtC,cAAc,EACd,mBAAmB,CACpB,EAAA;;;CACF;AAdD,8EAcC"}
\ No newline at end of file

build/commonjs/globalApi/nets.d.ts

 import { TfjsImageRecognitionBase, TNetInput } from 'tfjs-image-recognition-base';
+import { AgeGenderNet } from '../ageGenderNet/AgeGenderNet';
+import { AgeAndGenderPrediction } from '../ageGenderNet/types';
 import { FaceDetection } from '../classes/FaceDetection';
 import { FaceLandmarks5 } from '../classes/FaceLandmarks5';
 import { FaceLandmarks68 } from '../classes/FaceLandmarks68';
 import { FaceExpressionNet } from '../faceExpressionNet/FaceExpressionNet';
-import { FaceExpressionPrediction } from '../faceExpressionNet/types';
+import { FaceExpressions } from '../faceExpressionNet/FaceExpressions';
 import { FaceLandmark68Net } from '../faceLandmarkNet/FaceLandmark68Net';
 import { FaceLandmark68TinyNet } from '../faceLandmarkNet/FaceLandmark68TinyNet';
 import { FaceRecognitionNet } from '../faceRecognitionNet/FaceRecognitionNet';
@@ -24,6 +26,7 @@ export declare const nets: {
     faceLandmark68TinyNet: FaceLandmark68TinyNet;
     faceRecognitionNet: FaceRecognitionNet;
     faceExpressionNet: FaceExpressionNet;
+    ageGenderNet: AgeGenderNet;
 };
 /**
  * Attempts to detect all faces in an image using SSD Mobilenetv1 Network.
@@ -90,14 +93,21 @@ export declare const detectFaceLandmarksTiny: (input: TNetInput) => Promise<Face
  */
 export declare const computeFaceDescriptor: (input: TNetInput) => Promise<Float32Array | Float32Array[]>;
 /**
- * Recognizes the facial expressions of a face and returns the likelyhood of
- * each facial expression.
+ * Recognizes the facial expressions from a face image.
  *
  * @param inputs The face image extracted from the bounding box of a face. Can
  * also be an array of input images, which will be batch processed.
- * @returns An array of facial expressions with corresponding probabilities or array thereof in case of batch input.
+ * @returns Facial expressions with corresponding probabilities or array thereof in case of batch input.
  */
-export declare const recognizeFaceExpressions: (input: TNetInput) => Promise<FaceExpressionPrediction[] | FaceExpressionPrediction[][]>;
+export declare const recognizeFaceExpressions: (input: TNetInput) => Promise<FaceExpressions | FaceExpressions[]>;
+/**
+ * Predicts age and gender from a face image.
+ *
+ * @param inputs The face image extracted from the bounding box of a face. Can
+ * also be an array of input images, which will be batch processed.
+ * @returns Predictions with age, gender and gender probability or array thereof in case of batch input.
+ */
+export declare const predictAgeAndGender: (input: TNetInput) => Promise<AgeAndGenderPrediction | AgeAndGenderPrediction[]>;
 export declare const loadSsdMobilenetv1Model: (url: string) => Promise<void>;
 export declare const loadTinyFaceDetectorModel: (url: string) => Promise<void>;
 export declare const loadMtcnnModel: (url: string) => Promise<void>;
@@ -106,6 +116,7 @@ export declare const loadFaceLandmarkModel: (url: string) => Promise<void>;
 export declare const loadFaceLandmarkTinyModel: (url: string) => Promise<void>;
 export declare const loadFaceRecognitionModel: (url: string) => Promise<void>;
 export declare const loadFaceExpressionModel: (url: string) => Promise<void>;
+export declare const loadAgeGenderModel: (url: string) => Promise<void>;
 export declare const loadFaceDetectionModel: (url: string) => Promise<void>;
 export declare const locateFaces: (input: TNetInput, options: SsdMobilenetv1Options) => Promise<FaceDetection[]>;
 export declare const detectLandmarks: (input: TNetInput) => Promise<FaceLandmarks68 | FaceLandmarks68[]>;

build/commonjs/globalApi/nets.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
+var AgeGenderNet_1 = require("../ageGenderNet/AgeGenderNet");
 var FaceExpressionNet_1 = require("../faceExpressionNet/FaceExpressionNet");
 var FaceLandmark68Net_1 = require("../faceLandmarkNet/FaceLandmark68Net");
 var FaceLandmark68TinyNet_1 = require("../faceLandmarkNet/FaceLandmark68TinyNet");
@@ -16,7 +17,8 @@ exports.nets = {
     faceLandmark68Net: new FaceLandmark68Net_1.FaceLandmark68Net(),
     faceLandmark68TinyNet: new FaceLandmark68TinyNet_1.FaceLandmark68TinyNet(),
     faceRecognitionNet: new FaceRecognitionNet_1.FaceRecognitionNet(),
-    faceExpressionNet: new FaceExpressionNet_1.FaceExpressionNet()
+    faceExpressionNet: new FaceExpressionNet_1.FaceExpressionNet(),
+    ageGenderNet: new AgeGenderNet_1.AgeGenderNet()
 };
 /**
  * Attempts to detect all faces in an image using SSD Mobilenetv1 Network.
@@ -95,16 +97,25 @@ exports.computeFaceDescriptor = function (input) {
     return exports.nets.faceRecognitionNet.computeFaceDescriptor(input);
 };
 /**
- * Recognizes the facial expressions of a face and returns the likelyhood of
- * each facial expression.
+ * Recognizes the facial expressions from a face image.
  *
  * @param inputs The face image extracted from the bounding box of a face. Can
  * also be an array of input images, which will be batch processed.
- * @returns An array of facial expressions with corresponding probabilities or array thereof in case of batch input.
+ * @returns Facial expressions with corresponding probabilities or array thereof in case of batch input.
  */
 exports.recognizeFaceExpressions = function (input) {
     return exports.nets.faceExpressionNet.predictExpressions(input);
 };
+/**
+ * Predicts age and gender from a face image.
+ *
+ * @param inputs The face image extracted from the bounding box of a face. Can
+ * also be an array of input images, which will be batch processed.
+ * @returns Predictions with age, gender and gender probability or array thereof in case of batch input.
+ */
+exports.predictAgeAndGender = function (input) {
+    return exports.nets.ageGenderNet.predictAgeAndGender(input);
+};
 exports.loadSsdMobilenetv1Model = function (url) { return exports.nets.ssdMobilenetv1.load(url); };
 exports.loadTinyFaceDetectorModel = function (url) { return exports.nets.tinyFaceDetector.load(url); };
 exports.loadMtcnnModel = function (url) { return exports.nets.mtcnn.load(url); };
@@ -113,6 +124,7 @@ exports.loadFaceLandmarkModel = function (url) { return exports.nets.faceLandmar
 exports.loadFaceLandmarkTinyModel = function (url) { return exports.nets.faceLandmark68TinyNet.load(url); };
 exports.loadFaceRecognitionModel = function (url) { return exports.nets.faceRecognitionNet.load(url); };
 exports.loadFaceExpressionModel = function (url) { return exports.nets.faceExpressionNet.load(url); };
+exports.loadAgeGenderModel = function (url) { return exports.nets.ageGenderNet.load(url); };
 // backward compatibility
 exports.loadFaceDetectionModel = exports.loadSsdMobilenetv1Model;
 exports.locateFaces = exports.ssdMobilenetv1;

build/commonjs/globalApi/nets.js.map

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\ No newline at end of file

build/commonjs/index.d.ts

 import * as tf from '@tensorflow/tfjs-core';
+import { draw as drawBase } from 'tfjs-image-recognition-base';
+import * as drawExtended from './draw';
 export { tf };
 export * from 'tfjs-image-recognition-base';
+export * from './ageGenderNet/index';
+declare const draw: {
+    drawContour(ctx: CanvasRenderingContext2D, points: import("tfjs-image-recognition-base").Point[], isClosed?: boolean): void;
+    drawDetections(canvasArg: string | HTMLCanvasElement, detections: import("tfjs-image-recognition-base").IRect | import("tfjs-image-recognition-base").IBoundingBox | import("./classes").FaceDetection | {
+        detection: import("./classes").FaceDetection;
+    } | drawExtended.TDrawDetectionsInput[]): void;
+    drawFaceExpressions(canvasArg: string | HTMLCanvasElement, faceExpressions: import("./faceExpressionNet").FaceExpressions | {
+        expressions: import("./faceExpressionNet").FaceExpressions;
+    } | drawExtended.DrawFaceExpressionsInput[], minConfidence?: number, textFieldAnchor?: import("tfjs-image-recognition-base").IPoint | undefined): void;
+    drawFaceLandmarks(canvasArg: string | HTMLCanvasElement, faceLandmarks: import("./classes").FaceLandmarks | import("./factories").WithFaceLandmarks<{
+        detection: import("./classes").FaceDetection;
+    }, import("./classes").FaceLandmarks68> | drawExtended.DrawFaceLandmarksInput[]): void;
+    DrawFaceLandmarksOptions: typeof drawExtended.DrawFaceLandmarksOptions;
+    DrawFaceLandmarks: typeof drawExtended.DrawFaceLandmarks;
+    DrawBoxOptions: typeof drawBase.DrawBoxOptions;
+    DrawBox: typeof drawBase.DrawBox;
+    AnchorPosition: typeof drawBase.AnchorPosition;
+    DrawTextFieldOptions: typeof drawBase.DrawTextFieldOptions;
+    DrawTextField: typeof drawBase.DrawTextField;
+};
+export { draw };
 export * from './classes/index';
 export * from './dom/index';
 export * from './faceExpressionNet/index';

build/commonjs/index.js

@@ -3,7 +3,12 @@ Object.defineProperty(exports, "__esModule", { value: true });
 var tslib_1 = require("tslib");
 var tf = require("@tensorflow/tfjs-core");
 exports.tf = tf;
+var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
+var drawExtended = require("./draw");
 tslib_1.__exportStar(require("tfjs-image-recognition-base"), exports);
+tslib_1.__exportStar(require("./ageGenderNet/index"), exports);
+var draw = tslib_1.__assign({}, tfjs_image_recognition_base_1.draw, drawExtended);
+exports.draw = draw;
 tslib_1.__exportStar(require("./classes/index"), exports);
 tslib_1.__exportStar(require("./dom/index"), exports);
 tslib_1.__exportStar(require("./faceExpressionNet/index"), exports);

build/commonjs/index.js.map

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+{"version":3,"file":"index.js","sourceRoot":"","sources":["../../src/index.ts"],"names":[],"mappings":";;;AAAA,0CAA4C;AAM1C,gBAAE;AALJ,2EAA+D;AAE/D,qCAAuC;AAMvC,sEAA4C;AAE5C,+DAAqC;AACrC,IAAM,IAAI,wBAAO,kCAAQ,EAAK,YAAY,CAAE,CAAA;AACnC,oBAAI;AAEb,0DAAgC;AAChC,sDAA2B;AAC3B,oEAA0C;AAC1C,kEAAwC;AACxC,qEAA2C;AAC3C,4DAAkC;AAClC,4DAAkC;AAClC,wDAA8B;AAC9B,iEAAuC;AACvC,mEAAyC;AACzC,6DAAmC;AAEnC,8DAAoC;AACpC,0DAAgC"}
\ No newline at end of file

build/commonjs/minBbox.d.ts

+import { BoundingBox, IPoint } from 'tfjs-image-recognition-base';
+export declare function minBbox(pts: IPoint[]): BoundingBox;

build/commonjs/minBbox.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
+function minBbox(pts) {
+    var xs = pts.map(function (pt) { return pt.x; });
+    var ys = pts.map(function (pt) { return pt.y; });
+    var minX = xs.reduce(function (min, x) { return x < min ? x : min; }, Infinity);
+    var minY = ys.reduce(function (min, y) { return y < min ? y : min; }, Infinity);
+    var maxX = xs.reduce(function (max, x) { return max < x ? x : max; }, 0);
+    var maxY = ys.reduce(function (max, y) { return max < y ? y : max; }, 0);
+    return new tfjs_image_recognition_base_1.BoundingBox(minX, minY, maxX, maxY);
+}
+exports.minBbox = minBbox;
+//# sourceMappingURL=minBbox.js.map
\ No newline at end of file

build/commonjs/minBbox.js.map

+{"version":3,"file":"minBbox.js","sourceRoot":"","sources":["../../src/minBbox.ts"],"names":[],"mappings":";;AAAA,2EAAkE;AAElE,SAAgB,OAAO,CAAC,GAAa;IACnC,IAAM,EAAE,GAAG,GAAG,CAAC,GAAG,CAAC,UAAA,EAAE,IAAI,OAAA,EAAE,CAAC,CAAC,EAAJ,CAAI,CAAC,CAAA;IAC9B,IAAM,EAAE,GAAG,GAAG,CAAC,GAAG,CAAC,UAAA,EAAE,IAAI,OAAA,EAAE,CAAC,CAAC,EAAJ,CAAI,CAAC,CAAA;IAC9B,IAAM,IAAI,GAAG,EAAE,CAAC,MAAM,CAAC,UAAC,GAAG,EAAE,CAAC,IAAK,OAAA,CAAC,GAAG,GAAG,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,GAAG,EAAjB,CAAiB,EAAE,QAAQ,CAAC,CAAA;IAC/D,IAAM,IAAI,GAAG,EAAE,CAAC,MAAM,CAAC,UAAC,GAAG,EAAE,CAAC,IAAK,OAAA,CAAC,GAAG,GAAG,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,GAAG,EAAjB,CAAiB,EAAE,QAAQ,CAAC,CAAA;IAC/D,IAAM,IAAI,GAAG,EAAE,CAAC,MAAM,CAAC,UAAC,GAAG,EAAE,CAAC,IAAK,OAAA,GAAG,GAAG,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,GAAG,EAAjB,CAAiB,EAAE,CAAC,CAAC,CAAA;IACxD,IAAM,IAAI,GAAG,EAAE,CAAC,MAAM,CAAC,UAAC,GAAG,EAAE,CAAC,IAAK,OAAA,GAAG,GAAG,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,GAAG,EAAjB,CAAiB,EAAE,CAAC,CAAC,CAAA;IAExD,OAAO,IAAI,yCAAW,CAAC,IAAI,EAAE,IAAI,EAAE,IAAI,EAAE,IAAI,CAAC,CAAA;AAChD,CAAC;AATD,0BASC"}
\ No newline at end of file

build/commonjs/resizeResults.d.ts

 import { IDimensions } from 'tfjs-image-recognition-base';
-export declare function resizeResults<T>(results: T, { width, height }: IDimensions): T;
+export declare function resizeResults<T>(results: T, dimensions: IDimensions): T;

build/commonjs/resizeResults.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
+var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
 var FaceDetection_1 = require("./classes/FaceDetection");
 var FaceLandmarks_1 = require("./classes/FaceLandmarks");
 var WithFaceDetection_1 = require("./factories/WithFaceDetection");
 var WithFaceLandmarks_1 = require("./factories/WithFaceLandmarks");
-function resizeResults(results, _a) {
-    var width = _a.width, height = _a.height;
+function resizeResults(results, dimensions) {
+    var _a = new tfjs_image_recognition_base_1.Dimensions(dimensions.width, dimensions.height), width = _a.width, height = _a.height;
+    if (width <= 0 || height <= 0) {
+        throw new Error("resizeResults - invalid dimensions: " + JSON.stringify({ width: width, height: height }));
+    }
     if (Array.isArray(results)) {
         return results.map(function (obj) { return resizeResults(obj, { width: width, height: height }); });
     }
-    var hasLandmarks = results['unshiftedLandmarks'] && results['unshiftedLandmarks'] instanceof FaceLandmarks_1.FaceLandmarks;
-    var hasDetection = results['detection'] && results['detection'] instanceof FaceDetection_1.FaceDetection;
-    if (hasLandmarks) {
-        var resizedDetection = results['detection'].forSize(width, height);
-        var resizedLandmarks = results['unshiftedLandmarks'].forSize(resizedDetection.box.width, resizedDetection.box.height);
+    if (WithFaceLandmarks_1.isWithFaceLandmarks(results)) {
+        var resizedDetection = results.detection.forSize(width, height);
+        var resizedLandmarks = results.unshiftedLandmarks.forSize(resizedDetection.box.width, resizedDetection.box.height);
         return WithFaceLandmarks_1.extendWithFaceLandmarks(WithFaceDetection_1.extendWithFaceDetection(results, resizedDetection), resizedLandmarks);
     }
-    if (hasDetection) {
-        return WithFaceDetection_1.extendWithFaceDetection(results, results['detection'].forSize(width, height));
+    if (WithFaceDetection_1.isWithFaceDetection(results)) {
+        return WithFaceDetection_1.extendWithFaceDetection(results, results.detection.forSize(width, height));
     }
     if (results instanceof FaceLandmarks_1.FaceLandmarks || results instanceof FaceDetection_1.FaceDetection) {
         return results.forSize(width, height);

build/commonjs/resizeResults.js.map

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\ No newline at end of file

build/commonjs/xception/TinyXception.d.ts

+import * as tf from '@tensorflow/tfjs-core';
+import { NetInput, NeuralNetwork, TfjsImageRecognitionBase, TNetInput } from 'tfjs-image-recognition-base';
+import { TinyXceptionParams } from './types';
+export declare class TinyXception extends NeuralNetwork<TinyXceptionParams> {
+    private _numMainBlocks;
+    constructor(numMainBlocks: number);
+    forwardInput(input: NetInput): tf.Tensor4D;
+    forward(input: TNetInput): Promise<tf.Tensor4D>;
+    protected getDefaultModelName(): string;
+    protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap): {
+        params: TinyXceptionParams;
+        paramMappings: TfjsImageRecognitionBase.ParamMapping[];
+    };
+    protected extractParams(weights: Float32Array): {
+        params: TinyXceptionParams;
+        paramMappings: TfjsImageRecognitionBase.ParamMapping[];
+    };
+}

build/commonjs/xception/TinyXception.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+var tslib_1 = require("tslib");
+var tf = require("@tensorflow/tfjs-core");
+var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
+var depthwiseSeparableConv_1 = require("../common/depthwiseSeparableConv");
+var extractParams_1 = require("./extractParams");
+var extractParamsFromWeigthMap_1 = require("./extractParamsFromWeigthMap");
+function conv(x, params, stride) {
+    return tf.add(tf.conv2d(x, params.filters, stride, 'same'), params.bias);
+}
+function reductionBlock(x, params, isActivateInput) {
+    if (isActivateInput === void 0) { isActivateInput = true; }
+    var out = isActivateInput ? tf.relu(x) : x;
+    out = depthwiseSeparableConv_1.depthwiseSeparableConv(out, params.separable_conv0, [1, 1]);
+    out = depthwiseSeparableConv_1.depthwiseSeparableConv(tf.relu(out), params.separable_conv1, [1, 1]);
+    out = tf.maxPool(out, [3, 3], [2, 2], 'same');
+    out = tf.add(out, conv(x, params.expansion_conv, [2, 2]));
+    return out;
+}
+function mainBlock(x, params) {
+    var out = depthwiseSeparableConv_1.depthwiseSeparableConv(tf.relu(x), params.separable_conv0, [1, 1]);
+    out = depthwiseSeparableConv_1.depthwiseSeparableConv(tf.relu(out), params.separable_conv1, [1, 1]);
+    out = depthwiseSeparableConv_1.depthwiseSeparableConv(tf.relu(out), params.separable_conv2, [1, 1]);
+    out = tf.add(out, x);
+    return out;
+}
+var TinyXception = /** @class */ (function (_super) {
+    tslib_1.__extends(TinyXception, _super);
+    function TinyXception(numMainBlocks) {
+        var _this = _super.call(this, 'TinyXception') || this;
+        _this._numMainBlocks = numMainBlocks;
+        return _this;
+    }
+    TinyXception.prototype.forwardInput = function (input) {
+        var _this = this;
+        var params = this.params;
+        if (!params) {
+            throw new Error('TinyXception - load model before inference');
+        }
+        return tf.tidy(function () {
+            var batchTensor = input.toBatchTensor(112, true);
+            var meanRgb = [122.782, 117.001, 104.298];
+            var normalized = tfjs_image_recognition_base_1.normalize(batchTensor, meanRgb).div(tf.scalar(256));
+            var out = tf.relu(conv(normalized, params.entry_flow.conv_in, [2, 2]));
+            out = reductionBlock(out, params.entry_flow.reduction_block_0, false);
+            out = reductionBlock(out, params.entry_flow.reduction_block_1);
+            tfjs_image_recognition_base_1.range(_this._numMainBlocks, 0, 1).forEach(function (idx) {
+                out = mainBlock(out, params.middle_flow["main_block_" + idx]);
+            });
+            out = reductionBlock(out, params.exit_flow.reduction_block);
+            out = tf.relu(depthwiseSeparableConv_1.depthwiseSeparableConv(out, params.exit_flow.separable_conv, [1, 1]));
+            return out;
+        });
+    };
+    TinyXception.prototype.forward = function (input) {
+        return tslib_1.__awaiter(this, void 0, void 0, function () {
+            var _a;
+            return tslib_1.__generator(this, function (_b) {
+                switch (_b.label) {
+                    case 0:
+                        _a = this.forwardInput;
+                        return [4 /*yield*/, tfjs_image_recognition_base_1.toNetInput(input)];
+                    case 1: return [2 /*return*/, _a.apply(this, [_b.sent()])];
+                }
+            });
+        });
+    };
+    TinyXception.prototype.getDefaultModelName = function () {
+        return 'tiny_xception_model';
+    };
+    TinyXception.prototype.extractParamsFromWeigthMap = function (weightMap) {
+        return extractParamsFromWeigthMap_1.extractParamsFromWeigthMap(weightMap, this._numMainBlocks);
+    };
+    TinyXception.prototype.extractParams = function (weights) {
+        return extractParams_1.extractParams(weights, this._numMainBlocks);
+    };
+    return TinyXception;
+}(tfjs_image_recognition_base_1.NeuralNetwork));
+exports.TinyXception = TinyXception;
+//# sourceMappingURL=TinyXception.js.map
\ No newline at end of file

build/commonjs/xception/TinyXception.js.map

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\ No newline at end of file

build/commonjs/xception/extractParams.d.ts

+import { TfjsImageRecognitionBase } from 'tfjs-image-recognition-base';
+import { TinyXceptionParams } from './types';
+export declare function extractParams(weights: Float32Array, numMainBlocks: number): {
+    params: TinyXceptionParams;
+    paramMappings: TfjsImageRecognitionBase.ParamMapping[];
+};

build/commonjs/xception/extractParams.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
+function extractorsFactory(extractWeights, paramMappings) {
+    var extractConvParams = tfjs_image_recognition_base_1.TfjsImageRecognitionBase.extractConvParamsFactory(extractWeights, paramMappings);
+    var extractSeparableConvParams = tfjs_image_recognition_base_1.TfjsImageRecognitionBase.extractSeparableConvParamsFactory(extractWeights, paramMappings);
+    function extractReductionBlockParams(channelsIn, channelsOut, mappedPrefix) {
+        var separable_conv0 = extractSeparableConvParams(channelsIn, channelsOut, mappedPrefix + "/separable_conv0");
+        var separable_conv1 = extractSeparableConvParams(channelsOut, channelsOut, mappedPrefix + "/separable_conv1");
+        var expansion_conv = extractConvParams(channelsIn, channelsOut, 1, mappedPrefix + "/expansion_conv");
+        return { separable_conv0: separable_conv0, separable_conv1: separable_conv1, expansion_conv: expansion_conv };
+    }
+    function extractMainBlockParams(channels, mappedPrefix) {
+        var separable_conv0 = extractSeparableConvParams(channels, channels, mappedPrefix + "/separable_conv0");
+        var separable_conv1 = extractSeparableConvParams(channels, channels, mappedPrefix + "/separable_conv1");
+        var separable_conv2 = extractSeparableConvParams(channels, channels, mappedPrefix + "/separable_conv2");
+        return { separable_conv0: separable_conv0, separable_conv1: separable_conv1, separable_conv2: separable_conv2 };
+    }
+    return {
+        extractConvParams: extractConvParams,
+        extractSeparableConvParams: extractSeparableConvParams,
+        extractReductionBlockParams: extractReductionBlockParams,
+        extractMainBlockParams: extractMainBlockParams
+    };
+}
+function extractParams(weights, numMainBlocks) {
+    var paramMappings = [];
+    var _a = tfjs_image_recognition_base_1.TfjsImageRecognitionBase.extractWeightsFactory(weights), extractWeights = _a.extractWeights, getRemainingWeights = _a.getRemainingWeights;
+    var _b = extractorsFactory(extractWeights, paramMappings), extractConvParams = _b.extractConvParams, extractSeparableConvParams = _b.extractSeparableConvParams, extractReductionBlockParams = _b.extractReductionBlockParams, extractMainBlockParams = _b.extractMainBlockParams;
+    var entry_flow_conv_in = extractConvParams(3, 32, 3, 'entry_flow/conv_in');
+    var entry_flow_reduction_block_0 = extractReductionBlockParams(32, 64, 'entry_flow/reduction_block_0');
+    var entry_flow_reduction_block_1 = extractReductionBlockParams(64, 128, 'entry_flow/reduction_block_1');
+    var entry_flow = {
+        conv_in: entry_flow_conv_in,
+        reduction_block_0: entry_flow_reduction_block_0,
+        reduction_block_1: entry_flow_reduction_block_1
+    };
+    var middle_flow = {};
+    tfjs_image_recognition_base_1.range(numMainBlocks, 0, 1).forEach(function (idx) {
+        middle_flow["main_block_" + idx] = extractMainBlockParams(128, "middle_flow/main_block_" + idx);
+    });
+    var exit_flow_reduction_block = extractReductionBlockParams(128, 256, 'exit_flow/reduction_block');
+    var exit_flow_separable_conv = extractSeparableConvParams(256, 512, 'exit_flow/separable_conv');
+    var exit_flow = {
+        reduction_block: exit_flow_reduction_block,
+        separable_conv: exit_flow_separable_conv
+    };
+    if (getRemainingWeights().length !== 0) {
+        throw new Error("weights remaing after extract: " + getRemainingWeights().length);
+    }
+    return {
+        paramMappings: paramMappings,
+        params: { entry_flow: entry_flow, middle_flow: middle_flow, exit_flow: exit_flow }
+    };
+}
+exports.extractParams = extractParams;
+//# sourceMappingURL=extractParams.js.map
\ No newline at end of file

build/commonjs/xception/extractParams.js.map

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\ No newline at end of file

build/commonjs/xception/extractParamsFromWeigthMap.d.ts

+import * as tf from '@tensorflow/tfjs-core';
+import { TfjsImageRecognitionBase } from 'tfjs-image-recognition-base';
+import { TinyXceptionParams } from './types';
+export declare function extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap, numMainBlocks: number): {
+    params: TinyXceptionParams;
+    paramMappings: TfjsImageRecognitionBase.ParamMapping[];
+};

build/commonjs/xception/extractParamsFromWeigthMap.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
+var loadConvParamsFactory_1 = require("../common/loadConvParamsFactory");
+function loadParamsFactory(weightMap, paramMappings) {
+    var extractWeightEntry = tfjs_image_recognition_base_1.TfjsImageRecognitionBase.extractWeightEntryFactory(weightMap, paramMappings);
+    var extractConvParams = loadConvParamsFactory_1.loadConvParamsFactory(extractWeightEntry);
+    var extractSeparableConvParams = tfjs_image_recognition_base_1.TfjsImageRecognitionBase.loadSeparableConvParamsFactory(extractWeightEntry);
+    function extractReductionBlockParams(mappedPrefix) {
+        var separable_conv0 = extractSeparableConvParams(mappedPrefix + "/separable_conv0");
+        var separable_conv1 = extractSeparableConvParams(mappedPrefix + "/separable_conv1");
+        var expansion_conv = extractConvParams(mappedPrefix + "/expansion_conv");
+        return { separable_conv0: separable_conv0, separable_conv1: separable_conv1, expansion_conv: expansion_conv };
+    }
+    function extractMainBlockParams(mappedPrefix) {
+        var separable_conv0 = extractSeparableConvParams(mappedPrefix + "/separable_conv0");
+        var separable_conv1 = extractSeparableConvParams(mappedPrefix + "/separable_conv1");
+        var separable_conv2 = extractSeparableConvParams(mappedPrefix + "/separable_conv2");
+        return { separable_conv0: separable_conv0, separable_conv1: separable_conv1, separable_conv2: separable_conv2 };
+    }
+    return {
+        extractConvParams: extractConvParams,
+        extractSeparableConvParams: extractSeparableConvParams,
+        extractReductionBlockParams: extractReductionBlockParams,
+        extractMainBlockParams: extractMainBlockParams
+    };
+}
+function extractParamsFromWeigthMap(weightMap, numMainBlocks) {
+    var paramMappings = [];
+    var _a = loadParamsFactory(weightMap, paramMappings), extractConvParams = _a.extractConvParams, extractSeparableConvParams = _a.extractSeparableConvParams, extractReductionBlockParams = _a.extractReductionBlockParams, extractMainBlockParams = _a.extractMainBlockParams;
+    var entry_flow_conv_in = extractConvParams('entry_flow/conv_in');
+    var entry_flow_reduction_block_0 = extractReductionBlockParams('entry_flow/reduction_block_0');
+    var entry_flow_reduction_block_1 = extractReductionBlockParams('entry_flow/reduction_block_1');
+    var entry_flow = {
+        conv_in: entry_flow_conv_in,
+        reduction_block_0: entry_flow_reduction_block_0,
+        reduction_block_1: entry_flow_reduction_block_1
+    };
+    var middle_flow = {};
+    tfjs_image_recognition_base_1.range(numMainBlocks, 0, 1).forEach(function (idx) {
+        middle_flow["main_block_" + idx] = extractMainBlockParams("middle_flow/main_block_" + idx);
+    });
+    var exit_flow_reduction_block = extractReductionBlockParams('exit_flow/reduction_block');
+    var exit_flow_separable_conv = extractSeparableConvParams('exit_flow/separable_conv');
+    var exit_flow = {
+        reduction_block: exit_flow_reduction_block,
+        separable_conv: exit_flow_separable_conv
+    };
+    tfjs_image_recognition_base_1.TfjsImageRecognitionBase.disposeUnusedWeightTensors(weightMap, paramMappings);
+    return { params: { entry_flow: entry_flow, middle_flow: middle_flow, exit_flow: exit_flow }, paramMappings: paramMappings };
+}
+exports.extractParamsFromWeigthMap = extractParamsFromWeigthMap;
+//# sourceMappingURL=extractParamsFromWeigthMap.js.map
\ No newline at end of file

build/commonjs/xception/extractParamsFromWeigthMap.js.map

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\ No newline at end of file

build/commonjs/xception/index.d.ts

+export * from './TinyXception';

build/commonjs/xception/index.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+var tslib_1 = require("tslib");
+tslib_1.__exportStar(require("./TinyXception"), exports);
+//# sourceMappingURL=index.js.map
\ No newline at end of file

build/commonjs/xception/index.js.map

+{"version":3,"file":"index.js","sourceRoot":"","sources":["../../../src/xception/index.ts"],"names":[],"mappings":";;;AAAA,yDAA+B"}
\ No newline at end of file

build/commonjs/xception/types.d.ts

+import { TfjsImageRecognitionBase } from "tfjs-image-recognition-base";
+export declare type ReductionBlockParams = {
+    separable_conv0: TfjsImageRecognitionBase.SeparableConvParams;
+    separable_conv1: TfjsImageRecognitionBase.SeparableConvParams;
+    expansion_conv: TfjsImageRecognitionBase.ConvParams;
+};
+export declare type MainBlockParams = {
+    separable_conv0: TfjsImageRecognitionBase.SeparableConvParams;
+    separable_conv1: TfjsImageRecognitionBase.SeparableConvParams;
+    separable_conv2: TfjsImageRecognitionBase.SeparableConvParams;
+};
+export declare type TinyXceptionParams = {
+    entry_flow: {
+        conv_in: TfjsImageRecognitionBase.ConvParams;
+        reduction_block_0: ReductionBlockParams;
+        reduction_block_1: ReductionBlockParams;
+    };
+    middle_flow: any;
+    exit_flow: {
+        reduction_block: ReductionBlockParams;
+        separable_conv: TfjsImageRecognitionBase.SeparableConvParams;
+    };
+};

build/commonjs/xception/types.js.map

+{"version":3,"file":"types.js","sourceRoot":"","sources":["../../../src/xception/types.ts"],"names":[],"mappings":""}
\ No newline at end of file

build/es6/ageGenderNet/AgeGenderNet.d.ts

+import * as tf from '@tensorflow/tfjs-core';
+import { NetInput, NeuralNetwork, TNetInput } from 'tfjs-image-recognition-base';
+import { TinyXception } from '../xception/TinyXception';
+import { AgeAndGenderPrediction, NetOutput, NetParams } from './types';
+export declare class AgeGenderNet extends NeuralNetwork<NetParams> {
+    private _faceFeatureExtractor;
+    constructor(faceFeatureExtractor?: TinyXception);
+    readonly faceFeatureExtractor: TinyXception;
+    runNet(input: NetInput | tf.Tensor4D): NetOutput;
+    forwardInput(input: NetInput | tf.Tensor4D): NetOutput;
+    forward(input: TNetInput): Promise<NetOutput>;
+    predictAgeAndGender(input: TNetInput): Promise<AgeAndGenderPrediction | AgeAndGenderPrediction[]>;
+    protected getDefaultModelName(): string;
+    dispose(throwOnRedispose?: boolean): void;
+    loadClassifierParams(weights: Float32Array): void;
+    extractClassifierParams(weights: Float32Array): {
+        params: NetParams;
+        paramMappings: import("tfjs-image-recognition-base/build/commonjs/common").ParamMapping[];
+    };
+    protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap): {
+        params: NetParams;
+        paramMappings: import("tfjs-image-recognition-base/build/commonjs/common").ParamMapping[];
+    };
+    protected extractParams(weights: Float32Array): {
+        params: NetParams;
+        paramMappings: import("tfjs-image-recognition-base/build/commonjs/common").ParamMapping[];
+    };
+}

build/es6/ageGenderNet/AgeGenderNet.js

+import * as tslib_1 from "tslib";
+import * as tf from '@tensorflow/tfjs-core';
+import { NetInput, NeuralNetwork, toNetInput } from 'tfjs-image-recognition-base';
+import { fullyConnectedLayer } from '../common/fullyConnectedLayer';
+import { seperateWeightMaps } from '../faceProcessor/util';
+import { TinyXception } from '../xception/TinyXception';
+import { extractParams } from './extractParams';
+import { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';
+import { Gender } from './types';
+var AgeGenderNet = /** @class */ (function (_super) {
+    tslib_1.__extends(AgeGenderNet, _super);
+    function AgeGenderNet(faceFeatureExtractor) {
+        if (faceFeatureExtractor === void 0) { faceFeatureExtractor = new TinyXception(2); }
+        var _this = _super.call(this, 'AgeGenderNet') || this;
+        _this._faceFeatureExtractor = faceFeatureExtractor;
+        return _this;
+    }
+    Object.defineProperty(AgeGenderNet.prototype, "faceFeatureExtractor", {
+        get: function () {
+            return this._faceFeatureExtractor;
+        },
+        enumerable: true,
+        configurable: true
+    });
+    AgeGenderNet.prototype.runNet = function (input) {
+        var _this = this;
+        var params = this.params;
+        if (!params) {
+            throw new Error(this._name + " - load model before inference");
+        }
+        return tf.tidy(function () {
+            var bottleneckFeatures = input instanceof NetInput
+                ? _this.faceFeatureExtractor.forwardInput(input)
+                : input;
+            var pooled = tf.avgPool(bottleneckFeatures, [7, 7], [2, 2], 'valid').as2D(bottleneckFeatures.shape[0], -1);
+            var age = fullyConnectedLayer(pooled, params.fc.age).as1D();
+            var gender = fullyConnectedLayer(pooled, params.fc.gender);
+            return { age: age, gender: gender };
+        });
+    };
+    AgeGenderNet.prototype.forwardInput = function (input) {
+        var _this = this;
+        return tf.tidy(function () {
+            var _a = _this.runNet(input), age = _a.age, gender = _a.gender;
+            return { age: age, gender: tf.softmax(gender) };
+        });
+    };
+    AgeGenderNet.prototype.forward = function (input) {
+        return tslib_1.__awaiter(this, void 0, void 0, function () {
+            var _a;
+            return tslib_1.__generator(this, function (_b) {
+                switch (_b.label) {
+                    case 0:
+                        _a = this.forwardInput;
+                        return [4 /*yield*/, toNetInput(input)];
+                    case 1: return [2 /*return*/, _a.apply(this, [_b.sent()])];
+                }
+            });
+        });
+    };
+    AgeGenderNet.prototype.predictAgeAndGender = function (input) {
+        return tslib_1.__awaiter(this, void 0, void 0, function () {
+            var netInput, out, ages, genders, ageAndGenderTensors, predictionsByBatch;
+            var _this = this;
+            return tslib_1.__generator(this, function (_a) {
+                switch (_a.label) {
+                    case 0: return [4 /*yield*/, toNetInput(input)];
+                    case 1:
+                        netInput = _a.sent();
+                        return [4 /*yield*/, this.forwardInput(netInput)];
+                    case 2:
+                        out = _a.sent();
+                        ages = tf.unstack(out.age);
+                        genders = tf.unstack(out.gender);
+                        ageAndGenderTensors = ages.map(function (ageTensor, i) { return ({
+                            ageTensor: ageTensor,
+                            genderTensor: genders[i]
+                        }); });
+                        return [4 /*yield*/, Promise.all(ageAndGenderTensors.map(function (_a) {
+                                var ageTensor = _a.ageTensor, genderTensor = _a.genderTensor;
+                                return tslib_1.__awaiter(_this, void 0, void 0, function () {
+                                    var age, probMale, isMale, gender, genderProbability;
+                                    return tslib_1.__generator(this, function (_b) {
+                                        switch (_b.label) {
+                                            case 0: return [4 /*yield*/, ageTensor.data()];
+                                            case 1:
+                                                age = (_b.sent())[0];
+                                                return [4 /*yield*/, genderTensor.data()];
+                                            case 2:
+                                                probMale = (_b.sent())[0];
+                                                isMale = probMale > 0.5;
+                                                gender = isMale ? Gender.MALE : Gender.FEMALE;
+                                                genderProbability = isMale ? probMale : (1 - probMale);
+                                                ageTensor.dispose();
+                                                genderTensor.dispose();
+                                                return [2 /*return*/, { age: age, gender: gender, genderProbability: genderProbability }];
+                                        }
+                                    });
+                                });
+                            }))];
+                    case 3:
+                        predictionsByBatch = _a.sent();
+                        out.age.dispose();
+                        out.gender.dispose();
+                        return [2 /*return*/, netInput.isBatchInput
+                                ? predictionsByBatch
+                                : predictionsByBatch[0]];
+                }
+            });
+        });
+    };
+    AgeGenderNet.prototype.getDefaultModelName = function () {
+        return 'age_gender_model';
+    };
+    AgeGenderNet.prototype.dispose = function (throwOnRedispose) {
+        if (throwOnRedispose === void 0) { throwOnRedispose = true; }
+        this.faceFeatureExtractor.dispose(throwOnRedispose);
+        _super.prototype.dispose.call(this, throwOnRedispose);
+    };
+    AgeGenderNet.prototype.loadClassifierParams = function (weights) {
+        var _a = this.extractClassifierParams(weights), params = _a.params, paramMappings = _a.paramMappings;
+        this._params = params;
+        this._paramMappings = paramMappings;
+    };
+    AgeGenderNet.prototype.extractClassifierParams = function (weights) {
+        return extractParams(weights);
+    };
+    AgeGenderNet.prototype.extractParamsFromWeigthMap = function (weightMap) {
+        var _a = seperateWeightMaps(weightMap), featureExtractorMap = _a.featureExtractorMap, classifierMap = _a.classifierMap;
+        this.faceFeatureExtractor.loadFromWeightMap(featureExtractorMap);
+        return extractParamsFromWeigthMap(classifierMap);
+    };
+    AgeGenderNet.prototype.extractParams = function (weights) {
+        var classifierWeightSize = (512 * 1 + 1) + (512 * 2 + 2);
+        var featureExtractorWeights = weights.slice(0, weights.length - classifierWeightSize);
+        var classifierWeights = weights.slice(weights.length - classifierWeightSize);
+        this.faceFeatureExtractor.extractWeights(featureExtractorWeights);
+        return this.extractClassifierParams(classifierWeights);
+    };
+    return AgeGenderNet;
+}(NeuralNetwork));
+export { AgeGenderNet };
+//# sourceMappingURL=AgeGenderNet.js.map
\ No newline at end of file

build/es6/ageGenderNet/AgeGenderNet.js.map

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\ No newline at end of file

build/es6/ageGenderNet/extractParams.d.ts

+import { TfjsImageRecognitionBase } from 'tfjs-image-recognition-base';
+import { NetParams } from './types';
+export declare function extractParams(weights: Float32Array): {
+    params: NetParams;
+    paramMappings: TfjsImageRecognitionBase.ParamMapping[];
+};

build/es6/ageGenderNet/extractParams.js

+import { TfjsImageRecognitionBase } from 'tfjs-image-recognition-base';
+export function extractParams(weights) {
+    var paramMappings = [];
+    var _a = TfjsImageRecognitionBase.extractWeightsFactory(weights), extractWeights = _a.extractWeights, getRemainingWeights = _a.getRemainingWeights;
+    var extractFCParams = TfjsImageRecognitionBase.extractFCParamsFactory(extractWeights, paramMappings);
+    var age = extractFCParams(512, 1, 'fc/age');
+    var gender = extractFCParams(512, 2, 'fc/gender');
+    if (getRemainingWeights().length !== 0) {
+        throw new Error("weights remaing after extract: " + getRemainingWeights().length);
+    }
+    return {
+        paramMappings: paramMappings,
+        params: { fc: { age: age, gender: gender } }
+    };
+}
+//# sourceMappingURL=extractParams.js.map
\ No newline at end of file

build/es6/ageGenderNet/extractParams.js.map

+{"version":3,"file":"extractParams.js","sourceRoot":"","sources":["../../../src/ageGenderNet/extractParams.ts"],"names":[],"mappings":"AAAA,OAAO,EAAE,wBAAwB,EAAE,MAAM,6BAA6B,CAAC;AAIvE,MAAM,UAAU,aAAa,CAAC,OAAqB;IAEjD,IAAM,aAAa,GAA4C,EAAE,CAAA;IAE3D,IAAA,4DAGqD,EAFzD,kCAAc,EACd,4CACyD,CAAA;IAE3D,IAAM,eAAe,GAAG,wBAAwB,CAAC,sBAAsB,CAAC,cAAc,EAAE,aAAa,CAAC,CAAA;IAEtG,IAAM,GAAG,GAAG,eAAe,CAAC,GAAG,EAAE,CAAC,EAAE,QAAQ,CAAC,CAAA;IAC7C,IAAM,MAAM,GAAG,eAAe,CAAC,GAAG,EAAE,CAAC,EAAE,WAAW,CAAC,CAAA;IAEnD,IAAI,mBAAmB,EAAE,CAAC,MAAM,KAAK,CAAC,EAAE;QACtC,MAAM,IAAI,KAAK,CAAC,oCAAkC,mBAAmB,EAAE,CAAC,MAAQ,CAAC,CAAA;KAClF;IAED,OAAO;QACL,aAAa,eAAA;QACb,MAAM,EAAE,EAAE,EAAE,EAAE,EAAE,GAAG,KAAA,EAAE,MAAM,QAAA,EAAE,EAAE;KAChC,CAAA;AACH,CAAC"}
\ No newline at end of file

build/es6/ageGenderNet/extractParamsFromWeigthMap.d.ts

+import * as tf from '@tensorflow/tfjs-core';
+import { TfjsImageRecognitionBase } from 'tfjs-image-recognition-base';
+import { NetParams } from './types';
+export declare function extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap): {
+    params: NetParams;
+    paramMappings: TfjsImageRecognitionBase.ParamMapping[];
+};

build/es6/ageGenderNet/extractParamsFromWeigthMap.js

+import { TfjsImageRecognitionBase } from 'tfjs-image-recognition-base';
+export function extractParamsFromWeigthMap(weightMap) {
+    var paramMappings = [];
+    var extractWeightEntry = TfjsImageRecognitionBase.extractWeightEntryFactory(weightMap, paramMappings);
+    function extractFcParams(prefix) {
+        var weights = extractWeightEntry(prefix + "/weights", 2);
+        var bias = extractWeightEntry(prefix + "/bias", 1);
+        return { weights: weights, bias: bias };
+    }
+    var params = {
+        fc: {
+            age: extractFcParams('fc/age'),
+            gender: extractFcParams('fc/gender')
+        }
+    };
+    TfjsImageRecognitionBase.disposeUnusedWeightTensors(weightMap, paramMappings);
+    return { params: params, paramMappings: paramMappings };
+}
+//# sourceMappingURL=extractParamsFromWeigthMap.js.map
\ No newline at end of file

build/es6/ageGenderNet/extractParamsFromWeigthMap.js.map

+{"version":3,"file":"extractParamsFromWeigthMap.js","sourceRoot":"","sources":["../../../src/ageGenderNet/extractParamsFromWeigthMap.ts"],"names":[],"mappings":"AACA,OAAO,EAAE,wBAAwB,EAAE,MAAM,6BAA6B,CAAC;AAIvE,MAAM,UAAU,0BAA0B,CACxC,SAA4B;IAG5B,IAAM,aAAa,GAA4C,EAAE,CAAA;IAEjE,IAAM,kBAAkB,GAAG,wBAAwB,CAAC,yBAAyB,CAAC,SAAS,EAAE,aAAa,CAAC,CAAA;IAEvG,SAAS,eAAe,CAAC,MAAc;QACrC,IAAM,OAAO,GAAG,kBAAkB,CAAiB,MAAM,aAAU,EAAE,CAAC,CAAC,CAAA;QACvE,IAAM,IAAI,GAAG,kBAAkB,CAAiB,MAAM,UAAO,EAAE,CAAC,CAAC,CAAA;QACjE,OAAO,EAAE,OAAO,SAAA,EAAE,IAAI,MAAA,EAAE,CAAA;IAC1B,CAAC;IAED,IAAM,MAAM,GAAG;QACb,EAAE,EAAE;YACF,GAAG,EAAE,eAAe,CAAC,QAAQ,CAAC;YAC9B,MAAM,EAAE,eAAe,CAAC,WAAW,CAAC;SACrC;KACF,CAAA;IAED,wBAAwB,CAAC,0BAA0B,CAAC,SAAS,EAAE,aAAa,CAAC,CAAA;IAE7E,OAAO,EAAE,MAAM,QAAA,EAAE,aAAa,eAAA,EAAE,CAAA;AAClC,CAAC"}
\ No newline at end of file

build/es6/ageGenderNet/index.d.ts

+export * from './AgeGenderNet';
+export * from './types';

build/es6/ageGenderNet/index.js

+export * from './AgeGenderNet';
+export * from './types';
+//# sourceMappingURL=index.js.map
\ No newline at end of file

build/es6/ageGenderNet/index.js.map

+{"version":3,"file":"index.js","sourceRoot":"","sources":["../../../src/ageGenderNet/index.ts"],"names":[],"mappings":"AAAA,cAAc,gBAAgB,CAAC;AAC/B,cAAc,SAAS,CAAC"}
\ No newline at end of file

build/es6/ageGenderNet/types.d.ts

+import * as tf from '@tensorflow/tfjs-core';
+import { TfjsImageRecognitionBase } from 'tfjs-image-recognition-base';
+export declare type AgeAndGenderPrediction = {
+    age: number;
+    gender: Gender;
+    genderProbability: number;
+};
+export declare enum Gender {
+    FEMALE = "female",
+    MALE = "male"
+}
+export declare type NetOutput = {
+    age: tf.Tensor1D;
+    gender: tf.Tensor2D;
+};
+export declare type NetParams = {
+    fc: {
+        age: TfjsImageRecognitionBase.FCParams;
+        gender: TfjsImageRecognitionBase.FCParams;
+    };
+};

build/es6/ageGenderNet/types.js

+export var Gender;
+(function (Gender) {
+    Gender["FEMALE"] = "female";
+    Gender["MALE"] = "male";
+})(Gender || (Gender = {}));
+//# sourceMappingURL=types.js.map
\ No newline at end of file

build/es6/ageGenderNet/types.js.map

+{"version":3,"file":"types.js","sourceRoot":"","sources":["../../../src/ageGenderNet/types.ts"],"names":[],"mappings":"AASA,MAAM,CAAN,IAAY,MAGX;AAHD,WAAY,MAAM;IAChB,2BAAiB,CAAA;IACjB,uBAAa,CAAA;AACf,CAAC,EAHW,MAAM,KAAN,MAAM,QAGjB"}
\ No newline at end of file

build/es6/classes/FaceDetection.js

@@ -6,7 +6,8 @@ var FaceDetection = /** @class */ (function (_super) {
         return _super.call(this, score, score, '', relativeBox, imageDims) || this;
     }
     FaceDetection.prototype.forSize = function (width, height) {
-        return _super.prototype.forSize.call(this, width, height);
+        var _a = _super.prototype.forSize.call(this, width, height), score = _a.score, relativeBox = _a.relativeBox, imageDims = _a.imageDims;
+        return new FaceDetection(score, relativeBox, imageDims);
     };
     return FaceDetection;
 }(ObjectDetection));

build/es6/classes/FaceDetection.js.map

-{"version":3,"file":"FaceDetection.js","sourceRoot":"","sources":["../../../src/classes/FaceDetection.ts"],"names":[],"mappings":";AAAA,OAAO,EAAoB,eAAe,EAAQ,MAAM,6BAA6B,CAAC;AAOtF;IAAmC,yCAAe;IAChD,uBACE,KAAa,EACb,WAAiB,EACjB,SAAsB;eAEtB,kBAAM,KAAK,EAAE,KAAK,EAAE,EAAE,EAAE,WAAW,EAAE,SAAS,CAAC;IACjD,CAAC;IAEM,+BAAO,GAAd,UAAe,KAAa,EAAE,MAAc;QAC1C,OAAO,iBAAM,OAAO,YAAC,KAAK,EAAE,MAAM,CAAC,CAAA;IACrC,CAAC;IACH,oBAAC;AAAD,CAAC,AAZD,CAAmC,eAAe,GAYjD"}
+{"version":3,"file":"FaceDetection.js","sourceRoot":"","sources":["../../../src/classes/FaceDetection.ts"],"names":[],"mappings":";AAAA,OAAO,EAAoB,eAAe,EAAQ,MAAM,6BAA6B,CAAC;AAOtF;IAAmC,yCAAe;IAChD,uBACE,KAAa,EACb,WAAiB,EACjB,SAAsB;eAEtB,kBAAM,KAAK,EAAE,KAAK,EAAE,EAAE,EAAE,WAAW,EAAE,SAAS,CAAC;IACjD,CAAC;IAEM,+BAAO,GAAd,UAAe,KAAa,EAAE,MAAc;QACpC,IAAA,uDAAgE,EAA9D,gBAAK,EAAE,4BAAW,EAAE,wBAA0C,CAAA;QACtE,OAAO,IAAI,aAAa,CAAC,KAAK,EAAE,WAAW,EAAE,SAAS,CAAC,CAAA;IACzD,CAAC;IACH,oBAAC;AAAD,CAAC,AAbD,CAAmC,eAAe,GAajD"}
\ No newline at end of file

build/es6/classes/FaceLandmarks.d.ts

-import { Dimensions, IDimensions, Point, Rect } from 'tfjs-image-recognition-base';
+import { Box, Dimensions, IBoundingBox, IDimensions, IRect, Point } from 'tfjs-image-recognition-base';
 import { FaceDetection } from './FaceDetection';
 export interface IFaceLandmarks {
     positions: Point[];
@@ -28,6 +28,11 @@ export declare class FaceLandmarks implements IFaceLandmarks {
      * it's current shift.
      * @returns The bounding box of the aligned face.
      */
-    align(detection?: FaceDetection | Rect): Rect;
+    align(detection?: FaceDetection | IRect | IBoundingBox | null, options?: {
+        useDlibAlignment?: boolean;
+        minBoxPadding?: number;
+    }): Box;
+    private alignDlib;
+    private alignMinBbox;
     protected getRefPointsForAlignment(): Point[];
 }

build/es6/classes/FaceLandmarks.js

-import { Dimensions, getCenterPoint, Point, Rect } from 'tfjs-image-recognition-base';
+import { Box, Dimensions, getCenterPoint, Point, Rect } from 'tfjs-image-recognition-base';
+import { minBbox } from '../minBbox';
 import { FaceDetection } from './FaceDetection';
 // face alignment constants
 var relX = 0.5;
@@ -60,13 +61,21 @@ var FaceLandmarks = /** @class */ (function () {
      * it's current shift.
      * @returns The bounding box of the aligned face.
      */
-    FaceLandmarks.prototype.align = function (detection) {
+    FaceLandmarks.prototype.align = function (detection, options) {
+        if (options === void 0) { options = {}; }
         if (detection) {
             var box = detection instanceof FaceDetection
                 ? detection.box.floor()
-                : detection;
-            return this.shiftBy(box.x, box.y).align();
+                : new Box(detection);
+            return this.shiftBy(box.x, box.y).align(null, options);
         }
+        var _a = Object.assign({}, { useDlibAlignment: false, minBoxPadding: 0.2 }, options), useDlibAlignment = _a.useDlibAlignment, minBoxPadding = _a.minBoxPadding;
+        if (useDlibAlignment) {
+            return this.alignDlib();
+        }
+        return this.alignMinBbox(minBoxPadding);
+    };
+    FaceLandmarks.prototype.alignDlib = function () {
         var centers = this.getRefPointsForAlignment();
         var leftEyeCenter = centers[0], rightEyeCenter = centers[1], mouthCenter = centers[2];
         var distToMouth = function (pt) { return mouthCenter.sub(pt).magnitude(); };
@@ -78,6 +87,10 @@ var FaceLandmarks = /** @class */ (function () {
         var y = Math.floor(Math.max(0, refPoint.y - (relY * size)));
         return new Rect(x, y, Math.min(size, this.imageWidth + x), Math.min(size, this.imageHeight + y));
     };
+    FaceLandmarks.prototype.alignMinBbox = function (padding) {
+        var box = minBbox(this.positions);
+        return box.pad(box.width * padding, box.height * padding);
+    };
     FaceLandmarks.prototype.getRefPointsForAlignment = function () {
         throw new Error('getRefPointsForAlignment not implemented by base class');
     };

build/es6/classes/FaceLandmarks.js.map

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+{"version":3,"file":"FaceLandmarks.js","sourceRoot":"","sources":["../../../src/classes/FaceLandmarks.ts"],"names":[],"mappings":"AAAA,OAAO,EAAE,GAAG,EAAE,UAAU,EAAE,cAAc,EAAoC,KAAK,EAAE,IAAI,EAAE,MAAM,6BAA6B,CAAC;AAE7H,OAAO,EAAE,OAAO,EAAE,MAAM,YAAY,CAAC;AACrC,OAAO,EAAE,aAAa,EAAE,MAAM,iBAAiB,CAAC;AAEhD,2BAA2B;AAC3B,IAAM,IAAI,GAAG,GAAG,CAAA;AAChB,IAAM,IAAI,GAAG,IAAI,CAAA;AACjB,IAAM,QAAQ,GAAG,IAAI,CAAA;AAOrB;IAKE,uBACE,6BAAsC,EACtC,OAAoB,EACpB,KAA8B;QAA9B,sBAAA,EAAA,YAAmB,KAAK,CAAC,CAAC,EAAE,CAAC,CAAC;QAEtB,IAAA,qBAAK,EAAE,uBAAM,CAAY;QACjC,IAAI,CAAC,QAAQ,GAAG,IAAI,UAAU,CAAC,KAAK,EAAE,MAAM,CAAC,CAAA;QAC7C,IAAI,CAAC,MAAM,GAAG,KAAK,CAAA;QACnB,IAAI,CAAC,UAAU,GAAG,6BAA6B,CAAC,GAAG,CACjD,UAAA,EAAE,IAAI,OAAA,EAAE,CAAC,GAAG,CAAC,IAAI,KAAK,CAAC,KAAK,EAAE,MAAM,CAAC,CAAC,CAAC,GAAG,CAAC,KAAK,CAAC,EAA3C,CAA2C,CAClD,CAAA;IACH,CAAC;IAED,sBAAW,gCAAK;aAAhB,cAA4B,OAAO,IAAI,KAAK,CAAC,IAAI,CAAC,MAAM,CAAC,CAAC,EAAE,IAAI,CAAC,MAAM,CAAC,CAAC,CAAC,CAAA,CAAC,CAAC;;;OAAA;IAC5E,sBAAW,qCAAU;aAArB,cAAkC,OAAO,IAAI,CAAC,QAAQ,CAAC,KAAK,CAAA,CAAC,CAAC;;;OAAA;IAC9D,sBAAW,sCAAW;aAAtB,cAAmC,OAAO,IAAI,CAAC,QAAQ,CAAC,MAAM,CAAA,CAAC,CAAC;;;OAAA;IAChE,sBAAW,oCAAS;aAApB,cAAkC,OAAO,IAAI,CAAC,UAAU,CAAA,CAAC,CAAC;;;OAAA;IAC1D,sBAAW,4CAAiB;aAA5B;YAAA,iBAIC;YAHC,OAAO,IAAI,CAAC,UAAU,CAAC,GAAG,CACxB,UAAA,EAAE,IAAI,OAAA,EAAE,CAAC,GAAG,CAAC,KAAI,CAAC,MAAM,CAAC,CAAC,GAAG,CAAC,IAAI,KAAK,CAAC,KAAI,CAAC,UAAU,EAAE,KAAI,CAAC,WAAW,CAAC,CAAC,EAArE,CAAqE,CAC5E,CAAA;QACH,CAAC;;;OAAA;IAEM,+BAAO,GAAd,UAAwC,KAAa,EAAE,MAAc;QACnE,OAAO,IAAK,IAAI,CAAC,WAAmB,CAClC,IAAI,CAAC,iBAAiB,EACtB,EAAE,KAAK,OAAA,EAAE,MAAM,QAAA,EAAE,CAClB,CAAA;IACH,CAAC;IAEM,+BAAO,GAAd,UAAwC,CAAS,EAAE,CAAS;QAC1D,OAAO,IAAK,IAAI,CAAC,WAAmB,CAClC,IAAI,CAAC,iBAAiB,EACtB,IAAI,CAAC,QAAQ,EACb,IAAI,KAAK,CAAC,CAAC,EAAE,CAAC,CAAC,CAChB,CAAA;IACH,CAAC;IAEM,oCAAY,GAAnB,UAA6C,EAAS;QACpD,OAAO,IAAI,CAAC,OAAO,CAAC,EAAE,CAAC,CAAC,EAAE,EAAE,CAAC,CAAC,CAAC,CAAA;IACjC,CAAC;IAED;;;;;;;;;;OAUG;IACI,6BAAK,GAAZ,UACE,SAAuD,EACvD,OAAqE;QAArE,wBAAA,EAAA,YAAqE;QAErE,IAAI,SAAS,EAAE;YACb,IAAM,GAAG,GAAG,SAAS,YAAY,aAAa;gBAC5C,CAAC,CAAC,SAAS,CAAC,GAAG,CAAC,KAAK,EAAE;gBACvB,CAAC,CAAC,IAAI,GAAG,CAAC,SAAS,CAAC,CAAA;YAEtB,OAAO,IAAI,CAAC,OAAO,CAAC,GAAG,CAAC,CAAC,EAAE,GAAG,CAAC,CAAC,CAAC,CAAC,KAAK,CAAC,IAAI,EAAE,OAAO,CAAC,CAAA;SACvD;QAEK,IAAA,gFAAiH,EAA/G,sCAAgB,EAAE,gCAA6F,CAAA;QAEvH,IAAI,gBAAgB,EAAE;YACpB,OAAO,IAAI,CAAC,SAAS,EAAE,CAAA;SACxB;QAED,OAAO,IAAI,CAAC,YAAY,CAAC,aAAa,CAAC,CAAA;IACzC,CAAC;IAEO,iCAAS,GAAjB;QAEE,IAAM,OAAO,GAAG,IAAI,CAAC,wBAAwB,EAAE,CAAA;QAExC,IAAA,0BAAa,EAAE,2BAAc,EAAE,wBAAW,CAAW;QAC5D,IAAM,WAAW,GAAG,UAAC,EAAS,IAAK,OAAA,WAAW,CAAC,GAAG,CAAC,EAAE,CAAC,CAAC,SAAS,EAAE,EAA/B,CAA+B,CAAA;QAClE,IAAM,cAAc,GAAG,CAAC,WAAW,CAAC,aAAa,CAAC,GAAG,WAAW,CAAC,cAAc,CAAC,CAAC,GAAG,CAAC,CAAA;QAErF,IAAM,IAAI,GAAG,IAAI,CAAC,KAAK,CAAC,cAAc,GAAG,QAAQ,CAAC,CAAA;QAElD,IAAM,QAAQ,GAAG,cAAc,CAAC,OAAO,CAAC,CAAA;QACxC,qDAAqD;QACrD,IAAM,CAAC,GAAG,IAAI,CAAC,KAAK,CAAC,IAAI,CAAC,GAAG,CAAC,CAAC,EAAE,QAAQ,CAAC,CAAC,GAAG,CAAC,IAAI,GAAG,IAAI,CAAC,CAAC,CAAC,CAAA;QAC7D,IAAM,CAAC,GAAG,IAAI,CAAC,KAAK,CAAC,IAAI,CAAC,GAAG,CAAC,CAAC,EAAE,QAAQ,CAAC,CAAC,GAAG,CAAC,IAAI,GAAG,IAAI,CAAC,CAAC,CAAC,CAAA;QAE7D,OAAO,IAAI,IAAI,CAAC,CAAC,EAAE,CAAC,EAAE,IAAI,CAAC,GAAG,CAAC,IAAI,EAAE,IAAI,CAAC,UAAU,GAAG,CAAC,CAAC,EAAE,IAAI,CAAC,GAAG,CAAC,IAAI,EAAE,IAAI,CAAC,WAAW,GAAG,CAAC,CAAC,CAAC,CAAA;IAClG,CAAC;IAEO,oCAAY,GAApB,UAAqB,OAAe;QAClC,IAAM,GAAG,GAAG,OAAO,CAAC,IAAI,CAAC,SAAS,CAAC,CAAA;QACnC,OAAO,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,KAAK,GAAG,OAAO,EAAE,GAAG,CAAC,MAAM,GAAG,OAAO,CAAC,CAAA;IAC3D,CAAC;IAES,gDAAwB,GAAlC;QACE,MAAM,IAAI,KAAK,CAAC,wDAAwD,CAAC,CAAA;IAC3E,CAAC;IACH,oBAAC;AAAD,CAAC,AAzGD,IAyGC"}
\ No newline at end of file

build/es6/common/depthwiseSeparableConv.js.map

+{"version":3,"file":"depthwiseSeparableConv.js","sourceRoot":"","sources":["../../../src/common/depthwiseSeparableConv.ts"],"names":[],"mappings":"AAAA,OAAO,KAAK,EAAE,MAAM,uBAAuB,CAAC;AAG5C,MAAM,UAAU,sBAAsB,CACpC,CAAc,EACd,MAAoD,EACpD,MAAwB;IAExB,OAAO,EAAE,CAAC,IAAI,CAAC;QACb,IAAI,GAAG,GAAG,EAAE,CAAC,eAAe,CAAC,CAAC,EAAE,MAAM,CAAC,gBAAgB,EAAE,MAAM,CAAC,gBAAgB,EAAE,MAAM,EAAE,MAAM,CAAC,CAAA;QACjG,GAAG,GAAG,EAAE,CAAC,GAAG,CAAC,GAAG,EAAE,MAAM,CAAC,IAAI,CAAC,CAAA;QAC9B,OAAO,GAAG,CAAA;IACZ,CAAC,CAAC,CAAA;AACJ,CAAC"}
\ No newline at end of file

build/es6/common/loadConvParamsFactory.d.ts

+import { TfjsImageRecognitionBase } from 'tfjs-image-recognition-base';
+export declare function loadConvParamsFactory(extractWeightEntry: <T>(originalPath: string, paramRank: number) => T): (prefix: string) => TfjsImageRecognitionBase.ConvParams;

build/es6/common/loadConvParamsFactory.js

+export function loadConvParamsFactory(extractWeightEntry) {
+    return function (prefix) {
+        var filters = extractWeightEntry(prefix + "/filters", 4);
+        var bias = extractWeightEntry(prefix + "/bias", 1);
+        return { filters: filters, bias: bias };
+    };
+}
+//# sourceMappingURL=loadConvParamsFactory.js.map
\ No newline at end of file

build/es6/common/loadConvParamsFactory.js.map

+{"version":3,"file":"loadConvParamsFactory.js","sourceRoot":"","sources":["../../../src/common/loadConvParamsFactory.ts"],"names":[],"mappings":"AAGA,MAAM,UAAU,qBAAqB,CAAC,kBAAqE;IACzG,OAAO,UAAS,MAAc;QAC5B,IAAM,OAAO,GAAG,kBAAkB,CAAiB,MAAM,aAAU,EAAE,CAAC,CAAC,CAAA;QACvE,IAAM,IAAI,GAAG,kBAAkB,CAAiB,MAAM,UAAO,EAAE,CAAC,CAAC,CAAA;QAEjE,OAAO,EAAE,OAAO,SAAA,EAAE,IAAI,MAAA,EAAE,CAAA;IAC1B,CAAC,CAAA;AACH,CAAC"}
\ No newline at end of file

build/es6/dom/drawContour.js.map

-{"version":3,"file":"drawContour.js","sourceRoot":"","sources":["../../../src/dom/drawContour.ts"],"names":[],"mappings":"AAEA,MAAM,UAAU,WAAW,CACzB,GAA6B,EAC7B,MAAe,EACf,QAAyB;IAAzB,yBAAA,EAAA,gBAAyB;IAEzB,GAAG,CAAC,SAAS,EAAE,CAAA;IAEf,MAAM,CAAC,KAAK,CAAC,CAAC,CAAC,CAAC,OAAO,CAAC,UAAC,EAAQ,EAAE,OAAO;YAAf,QAAC,EAAE,QAAC;QAC7B,IAAM,IAAI,GAAG,MAAM,CAAC,OAAO,CAAC,CAAA;QAC5B,GAAG,CAAC,MAAM,CAAC,IAAI,CAAC,CAAC,EAAE,IAAI,CAAC,CAAC,CAAC,CAAA;QAC1B,GAAG,CAAC,MAAM,CAAC,CAAC,EAAE,CAAC,CAAC,CAAA;IAClB,CAAC,CAAC,CAAA;IAEF,IAAI,QAAQ,EAAE;QACZ,IAAM,IAAI,GAAG,MAAM,CAAC,MAAM,CAAC,MAAM,GAAG,CAAC,CAAC,CAAA;QACtC,IAAM,EAAE,GAAG,MAAM,CAAC,CAAC,CAAC,CAAA;QACpB,IAAI,CAAC,IAAI,IAAI,CAAC,EAAE,EAAE;YAChB,OAAM;SACP;QAED,GAAG,CAAC,MAAM,CAAC,IAAI,CAAC,CAAC,EAAE,IAAI,CAAC,CAAC,CAAC,CAAA;QAC1B,GAAG,CAAC,MAAM,CAAC,EAAE,CAAC,CAAC,EAAE,EAAE,CAAC,CAAC,CAAC,CAAA;KACvB;IAED,GAAG,CAAC,MAAM,EAAE,CAAA;AACd,CAAC"}
\ No newline at end of file

build/es6/dom/drawFaceExpressions.d.ts

-import { DrawFaceExpressionsInput, DrawFaceExpressionsOptions } from './types';
-export declare function drawFaceExpressions(canvasArg: string | HTMLCanvasElement, faceExpressions: DrawFaceExpressionsInput | DrawFaceExpressionsInput[], options?: DrawFaceExpressionsOptions): void;

build/es6/dom/drawFaceExpressions.js

-import { drawText, env, getContext2dOrThrow, getDefaultDrawOptions, resolveInput, round } from 'tfjs-image-recognition-base';
-export function drawFaceExpressions(canvasArg, faceExpressions, options) {
-    var canvas = resolveInput(canvasArg);
-    if (!(canvas instanceof env.getEnv().Canvas)) {
-        throw new Error('drawFaceExpressions - expected canvas to be of type: HTMLCanvasElement');
-    }
-    var drawOptions = Object.assign(getDefaultDrawOptions(options), (options || {}));
-    var ctx = getContext2dOrThrow(canvas);
-    var _a = drawOptions.primaryColor, primaryColor = _a === void 0 ? 'red' : _a, _b = drawOptions.secondaryColor, secondaryColor = _b === void 0 ? 'blue' : _b, _c = drawOptions.primaryFontSize, primaryFontSize = _c === void 0 ? 22 : _c, _d = drawOptions.secondaryFontSize, secondaryFontSize = _d === void 0 ? 16 : _d, _e = drawOptions.minConfidence, minConfidence = _e === void 0 ? 0.2 : _e;
-    var faceExpressionsArray = Array.isArray(faceExpressions)
-        ? faceExpressions
-        : [faceExpressions];
-    faceExpressionsArray.forEach(function (_a) {
-        var position = _a.position, expressions = _a.expressions;
-        var x = position.x, y = position.y;
-        var height = position.height || 0;
-        var sorted = expressions.sort(function (a, b) { return b.probability - a.probability; });
-        var resultsToDisplay = sorted.filter(function (expr) { return expr.probability > minConfidence; });
-        var offset = (y + height + resultsToDisplay.length * primaryFontSize) > canvas.height
-            ? -(resultsToDisplay.length * primaryFontSize)
-            : 0;
-        resultsToDisplay.forEach(function (expr, i) {
-            var text = expr.expression + " (" + round(expr.probability) + ")";
-            drawText(ctx, x, y + height + (i * primaryFontSize) + offset, text, {
-                textColor: i === 0 ? primaryColor : secondaryColor,
-                fontSize: i === 0 ? primaryFontSize : secondaryFontSize
-            });
-        });
-    });
-}
-//# sourceMappingURL=drawFaceExpressions.js.map
\ No newline at end of file

build/es6/dom/drawFaceExpressions.js.map

-{"version":3,"file":"drawFaceExpressions.js","sourceRoot":"","sources":["../../../src/dom/drawFaceExpressions.ts"],"names":[],"mappings":"AAAA,OAAO,EAAE,QAAQ,EAAE,GAAG,EAAE,mBAAmB,EAAE,qBAAqB,EAAE,YAAY,EAAE,KAAK,EAAE,MAAM,6BAA6B,CAAC;AAK7H,MAAM,UAAU,mBAAmB,CACjC,SAAqC,EACrC,eAAsE,EACtE,OAAoC;IAEpC,IAAM,MAAM,GAAG,YAAY,CAAC,SAAS,CAAC,CAAA;IACtC,IAAI,CAAC,CAAC,MAAM,YAAY,GAAG,CAAC,MAAM,EAAE,CAAC,MAAM,CAAC,EAAE;QAC5C,MAAM,IAAI,KAAK,CAAC,wEAAwE,CAAC,CAAA;KAC1F;IAED,IAAM,WAAW,GAAG,MAAM,CAAC,MAAM,CAC/B,qBAAqB,CAAC,OAAO,CAAC,EAC9B,CAAC,OAAO,IAAI,EAAE,CAAC,CAChB,CAAA;IAED,IAAM,GAAG,GAAG,mBAAmB,CAAC,MAAM,CAAC,CAAA;IAErC,IAAA,6BAAoB,EAApB,yCAAoB,EACpB,+BAAuB,EAAvB,4CAAuB,EACvB,gCAAoB,EAApB,yCAAoB,EACpB,kCAAsB,EAAtB,2CAAsB,EACtB,8BAAmB,EAAnB,wCAAmB,CACN;IAEf,IAAM,oBAAoB,GAAG,KAAK,CAAC,OAAO,CAAC,eAAe,CAAC;QACzD,CAAC,CAAC,eAAe;QACjB,CAAC,CAAC,CAAC,eAAe,CAAC,CAAA;IAErB,oBAAoB,CAAC,OAAO,CAAC,UAAC,EAAyB;YAAvB,sBAAQ,EAAE,4BAAW;QAC3C,IAAA,cAAC,EAAE,cAAC,CAAa;QACzB,IAAM,MAAM,GAAI,QAAkB,CAAC,MAAM,IAAI,CAAC,CAAA;QAC9C,IAAM,MAAM,GAAG,WAAW,CAAC,IAAI,CAAC,UAAC,CAAC,EAAE,CAAC,IAAK,OAAA,CAAC,CAAC,WAAW,GAAG,CAAC,CAAC,WAAW,EAA7B,CAA6B,CAAC,CAAA;QACxE,IAAM,gBAAgB,GAAG,MAAM,CAAC,MAAM,CAAC,UAAA,IAAI,IAAI,OAAA,IAAI,CAAC,WAAW,GAAG,aAAa,EAAhC,CAAgC,CAAC,CAAA;QAEhF,IAAI,MAAM,GAAG,CAAC,CAAC,GAAG,MAAM,GAAG,gBAAgB,CAAC,MAAM,GAAG,eAAe,CAAC,GAAG,MAAM,CAAC,MAAM;YACnF,CAAC,CAAC,CAAC,CAAC,gBAAgB,CAAC,MAAM,GAAG,eAAe,CAAC;YAC9C,CAAC,CAAC,CAAC,CAAA;QACL,gBAAgB,CAAC,OAAO,CAAC,UAAC,IAAI,EAAE,CAAC;YAC/B,IAAM,IAAI,GAAM,IAAI,CAAC,UAAU,UAAK,KAAK,CAAC,IAAI,CAAC,WAAW,CAAC,MAAG,CAAA;YAC9D,QAAQ,CACN,GAAG,EACH,CAAC,EACD,CAAC,GAAG,MAAM,GAAG,CAAC,CAAC,GAAG,eAAe,CAAC,GAAG,MAAM,EAC3C,IAAI,EACJ;gBACE,SAAS,EAAE,CAAC,KAAK,CAAC,CAAC,CAAC,CAAC,YAAY,CAAC,CAAC,CAAC,cAAc;gBAClD,QAAQ,EAAE,CAAC,KAAK,CAAC,CAAC,CAAC,CAAC,eAAe,CAAC,CAAC,CAAC,iBAAiB;aACxD,CACF,CAAA;QACH,CAAC,CAAC,CAAA;IACJ,CAAC,CAAC,CAAA;AAGJ,CAAC"}
\ No newline at end of file

build/es6/dom/drawLandmarks.d.ts

-import { FaceLandmarks } from '../classes/FaceLandmarks';
-import { DrawLandmarksOptions } from './types';
-export declare function drawLandmarks(canvasArg: string | HTMLCanvasElement, faceLandmarks: FaceLandmarks | FaceLandmarks[], options?: DrawLandmarksOptions): void;

build/es6/dom/drawLandmarks.js

-import { env, getContext2dOrThrow, getDefaultDrawOptions, resolveInput } from 'tfjs-image-recognition-base';
-import { FaceLandmarks68 } from '../classes/FaceLandmarks68';
-import { drawContour } from './drawContour';
-export function drawLandmarks(canvasArg, faceLandmarks, options) {
-    var canvas = resolveInput(canvasArg);
-    if (!(canvas instanceof env.getEnv().Canvas)) {
-        throw new Error('drawLandmarks - expected canvas to be of type: HTMLCanvasElement');
-    }
-    var drawOptions = Object.assign(getDefaultDrawOptions(options), (options || {}));
-    var drawLines = Object.assign({ drawLines: false }, (options || {})).drawLines;
-    var ctx = getContext2dOrThrow(canvas);
-    var lineWidth = drawOptions.lineWidth, _a = drawOptions.color, color = _a === void 0 ? 'blue' : _a;
-    var faceLandmarksArray = Array.isArray(faceLandmarks) ? faceLandmarks : [faceLandmarks];
-    faceLandmarksArray.forEach(function (landmarks) {
-        if (drawLines && landmarks instanceof FaceLandmarks68) {
-            ctx.strokeStyle = color;
-            ctx.lineWidth = lineWidth;
-            drawContour(ctx, landmarks.getJawOutline());
-            drawContour(ctx, landmarks.getLeftEyeBrow());
-            drawContour(ctx, landmarks.getRightEyeBrow());
-            drawContour(ctx, landmarks.getNose());
-            drawContour(ctx, landmarks.getLeftEye(), true);
-            drawContour(ctx, landmarks.getRightEye(), true);
-            drawContour(ctx, landmarks.getMouth(), true);
-            return;
-        }
-        // else draw points
-        var ptOffset = lineWidth / 2;
-        ctx.fillStyle = color;
-        landmarks.positions.forEach(function (pt) { return ctx.fillRect(pt.x - ptOffset, pt.y - ptOffset, lineWidth, lineWidth); });
-    });
-}
-//# sourceMappingURL=drawLandmarks.js.map
\ No newline at end of file

build/es6/dom/drawLandmarks.js.map

-{"version":3,"file":"drawLandmarks.js","sourceRoot":"","sources":["../../../src/dom/drawLandmarks.ts"],"names":[],"mappings":"AAAA,OAAO,EAAE,GAAG,EAAE,mBAAmB,EAAE,qBAAqB,EAAE,YAAY,EAAE,MAAM,6BAA6B,CAAC;AAG5G,OAAO,EAAE,eAAe,EAAE,MAAM,4BAA4B,CAAC;AAC7D,OAAO,EAAE,WAAW,EAAE,MAAM,eAAe,CAAC;AAG5C,MAAM,UAAU,aAAa,CAC3B,SAAqC,EACrC,aAA8C,EAC9C,OAA8B;IAE9B,IAAM,MAAM,GAAG,YAAY,CAAC,SAAS,CAAC,CAAA;IACtC,IAAI,CAAC,CAAC,MAAM,YAAY,GAAG,CAAC,MAAM,EAAE,CAAC,MAAM,CAAC,EAAE;QAC5C,MAAM,IAAI,KAAK,CAAC,kEAAkE,CAAC,CAAA;KACpF;IAED,IAAM,WAAW,GAAG,MAAM,CAAC,MAAM,CAC/B,qBAAqB,CAAC,OAAO,CAAC,EAC9B,CAAC,OAAO,IAAI,EAAE,CAAC,CAChB,CAAA;IAEO,IAAA,0EAAS,CAAyD;IAE1E,IAAM,GAAG,GAAG,mBAAmB,CAAC,MAAM,CAAC,CAAA;IAC/B,IAAA,iCAAS,EAAE,sBAAc,EAAd,mCAAc,CAAgB;IAEjD,IAAM,kBAAkB,GAAG,KAAK,CAAC,OAAO,CAAC,aAAa,CAAC,CAAC,CAAC,CAAC,aAAa,CAAC,CAAC,CAAC,CAAC,aAAa,CAAC,CAAA;IAEzF,kBAAkB,CAAC,OAAO,CAAC,UAAA,SAAS;QAClC,IAAI,SAAS,IAAI,SAAS,YAAY,eAAe,EAAE;YACrD,GAAG,CAAC,WAAW,GAAG,KAAK,CAAA;YACvB,GAAG,CAAC,SAAS,GAAG,SAAS,CAAA;YACzB,WAAW,CAAC,GAAG,EAAE,SAAS,CAAC,aAAa,EAAE,CAAC,CAAA;YAC3C,WAAW,CAAC,GAAG,EAAE,SAAS,CAAC,cAAc,EAAE,CAAC,CAAA;YAC5C,WAAW,CAAC,GAAG,EAAE,SAAS,CAAC,eAAe,EAAE,CAAC,CAAA;YAC7C,WAAW,CAAC,GAAG,EAAE,SAAS,CAAC,OAAO,EAAE,CAAC,CAAA;YACrC,WAAW,CAAC,GAAG,EAAE,SAAS,CAAC,UAAU,EAAE,EAAE,IAAI,CAAC,CAAA;YAC9C,WAAW,CAAC,GAAG,EAAE,SAAS,CAAC,WAAW,EAAE,EAAE,IAAI,CAAC,CAAA;YAC/C,WAAW,CAAC,GAAG,EAAE,SAAS,CAAC,QAAQ,EAAE,EAAE,IAAI,CAAC,CAAA;YAC5C,OAAM;SACP;QAED,mBAAmB;QACnB,IAAM,QAAQ,GAAG,SAAS,GAAG,CAAC,CAAA;QAC9B,GAAG,CAAC,SAAS,GAAG,KAAK,CAAA;QACrB,SAAS,CAAC,SAAS,CAAC,OAAO,CAAC,UAAA,EAAE,IAAI,OAAA,GAAG,CAAC,QAAQ,CAAC,EAAE,CAAC,CAAC,GAAG,QAAQ,EAAE,EAAE,CAAC,CAAC,GAAG,QAAQ,EAAE,SAAS,EAAE,SAAS,CAAC,EAApE,CAAoE,CAAC,CAAA;IACzG,CAAC,CAAC,CAAA;AACJ,CAAC"}
\ No newline at end of file

build/es6/dom/index.d.ts

-export * from './drawContour';
-export * from './drawLandmarks';
-export * from './drawFaceExpressions';
 export * from './extractFaces';
 export * from './extractFaceTensors';
-export * from './types';

build/es6/dom/index.js

-export * from './drawContour';
-export * from './drawLandmarks';
-export * from './drawFaceExpressions';
 export * from './extractFaces';
 export * from './extractFaceTensors';
 //# sourceMappingURL=index.js.map
\ No newline at end of file

build/es6/dom/index.js.map

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+{"version":3,"file":"index.js","sourceRoot":"","sources":["../../../src/dom/index.ts"],"names":[],"mappings":"AAAA,cAAc,gBAAgB,CAAA;AAC9B,cAAc,sBAAsB,CAAA"}
\ No newline at end of file

build/es6/dom/types.d.ts

-import { IPoint, IRect } from 'tfjs-image-recognition-base';
-import { WithFaceExpressions } from '../factories/WithFaceExpressions';
-export declare type DrawLandmarksOptions = {
-    lineWidth?: number;
-    color?: string;
-    drawLines?: boolean;
-};
-export declare type DrawFaceExpressionsOptions = {
-    primaryColor?: string;
-    secondaryColor?: string;
-    primaryFontSize?: number;
-    secondaryFontSize?: number;
-    minConfidence?: number;
-};
-export declare type DrawFaceExpressionsInput = WithFaceExpressions<{
-    position: IPoint | IRect;
-}>;

build/es6/dom/types.js.map

-{"version":3,"file":"types.js","sourceRoot":"","sources":["../../../src/dom/types.ts"],"names":[],"mappings":""}
\ No newline at end of file

build/es6/draw/DrawFaceLandmarks.d.ts

+import { FaceLandmarks } from '../classes/FaceLandmarks';
+import { WithFaceDetection } from '../factories/WithFaceDetection';
+import { WithFaceLandmarks } from '../factories/WithFaceLandmarks';
+export interface IDrawFaceLandmarksOptions {
+    drawLines?: boolean;
+    drawPoints?: boolean;
+    lineWidth?: number;
+    pointSize?: number;
+    lineColor?: string;
+    pointColor?: string;
+}
+export declare class DrawFaceLandmarksOptions {
+    drawLines: boolean;
+    drawPoints: boolean;
+    lineWidth: number;
+    pointSize: number;
+    lineColor: string;
+    pointColor: string;
+    constructor(options?: IDrawFaceLandmarksOptions);
+}
+export declare class DrawFaceLandmarks {
+    faceLandmarks: FaceLandmarks;
+    options: DrawFaceLandmarksOptions;
+    constructor(faceLandmarks: FaceLandmarks, options?: IDrawFaceLandmarksOptions);
+    draw(canvasArg: string | HTMLCanvasElement | CanvasRenderingContext2D): void;
+}
+export declare type DrawFaceLandmarksInput = FaceLandmarks | WithFaceLandmarks<WithFaceDetection<{}>>;
+export declare function drawFaceLandmarks(canvasArg: string | HTMLCanvasElement, faceLandmarks: DrawFaceLandmarksInput | Array<DrawFaceLandmarksInput>): void;

build/es6/draw/DrawFaceLandmarks.js

+import { getContext2dOrThrow } from 'tfjs-image-recognition-base';
+import { FaceLandmarks } from '../classes/FaceLandmarks';
+import { FaceLandmarks68 } from '../classes/FaceLandmarks68';
+import { isWithFaceLandmarks } from '../factories/WithFaceLandmarks';
+import { drawContour } from './drawContour';
+var DrawFaceLandmarksOptions = /** @class */ (function () {
+    function DrawFaceLandmarksOptions(options) {
+        if (options === void 0) { options = {}; }
+        var _a = options.drawLines, drawLines = _a === void 0 ? true : _a, _b = options.drawPoints, drawPoints = _b === void 0 ? true : _b, lineWidth = options.lineWidth, lineColor = options.lineColor, pointSize = options.pointSize, pointColor = options.pointColor;
+        this.drawLines = drawLines;
+        this.drawPoints = drawPoints;
+        this.lineWidth = lineWidth || 1;
+        this.pointSize = pointSize || 2;
+        this.lineColor = lineColor || 'rgba(0, 255, 255, 1)';
+        this.pointColor = pointColor || 'rgba(255, 0, 255, 1)';
+    }
+    return DrawFaceLandmarksOptions;
+}());
+export { DrawFaceLandmarksOptions };
+var DrawFaceLandmarks = /** @class */ (function () {
+    function DrawFaceLandmarks(faceLandmarks, options) {
+        if (options === void 0) { options = {}; }
+        this.faceLandmarks = faceLandmarks;
+        this.options = new DrawFaceLandmarksOptions(options);
+    }
+    DrawFaceLandmarks.prototype.draw = function (canvasArg) {
+        var ctx = getContext2dOrThrow(canvasArg);
+        var _a = this.options, drawLines = _a.drawLines, drawPoints = _a.drawPoints, lineWidth = _a.lineWidth, lineColor = _a.lineColor, pointSize = _a.pointSize, pointColor = _a.pointColor;
+        if (drawLines && this.faceLandmarks instanceof FaceLandmarks68) {
+            ctx.strokeStyle = lineColor;
+            ctx.lineWidth = lineWidth;
+            drawContour(ctx, this.faceLandmarks.getJawOutline());
+            drawContour(ctx, this.faceLandmarks.getLeftEyeBrow());
+            drawContour(ctx, this.faceLandmarks.getRightEyeBrow());
+            drawContour(ctx, this.faceLandmarks.getNose());
+            drawContour(ctx, this.faceLandmarks.getLeftEye(), true);
+            drawContour(ctx, this.faceLandmarks.getRightEye(), true);
+            drawContour(ctx, this.faceLandmarks.getMouth(), true);
+        }
+        if (drawPoints) {
+            ctx.strokeStyle = pointColor;
+            ctx.fillStyle = pointColor;
+            var drawPoint = function (pt) {
+                ctx.beginPath();
+                ctx.arc(pt.x, pt.y, pointSize, 0, 2 * Math.PI);
+                ctx.fill();
+            };
+            this.faceLandmarks.positions.forEach(drawPoint);
+        }
+    };
+    return DrawFaceLandmarks;
+}());
+export { DrawFaceLandmarks };
+export function drawFaceLandmarks(canvasArg, faceLandmarks) {
+    var faceLandmarksArray = Array.isArray(faceLandmarks) ? faceLandmarks : [faceLandmarks];
+    faceLandmarksArray.forEach(function (f) {
+        var landmarks = f instanceof FaceLandmarks
+            ? f
+            : (isWithFaceLandmarks(f) ? f.landmarks : undefined);
+        if (!landmarks) {
+            throw new Error('drawFaceLandmarks - expected faceExpressions to be FaceLandmarks | WithFaceLandmarks<WithFaceDetection<{}>> or array thereof');
+        }
+        new DrawFaceLandmarks(landmarks).draw(canvasArg);
+    });
+}
+//# sourceMappingURL=DrawFaceLandmarks.js.map
\ No newline at end of file

build/es6/draw/DrawFaceLandmarks.js.map

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\ No newline at end of file

build/es6/draw/drawContour.js.map

+{"version":3,"file":"drawContour.js","sourceRoot":"","sources":["../../../src/draw/drawContour.ts"],"names":[],"mappings":"AAEA,MAAM,UAAU,WAAW,CACzB,GAA6B,EAC7B,MAAe,EACf,QAAyB;IAAzB,yBAAA,EAAA,gBAAyB;IAEzB,GAAG,CAAC,SAAS,EAAE,CAAA;IAEf,MAAM,CAAC,KAAK,CAAC,CAAC,CAAC,CAAC,OAAO,CAAC,UAAC,EAAQ,EAAE,OAAO;YAAf,QAAC,EAAE,QAAC;QAC7B,IAAM,IAAI,GAAG,MAAM,CAAC,OAAO,CAAC,CAAA;QAC5B,GAAG,CAAC,MAAM,CAAC,IAAI,CAAC,CAAC,EAAE,IAAI,CAAC,CAAC,CAAC,CAAA;QAC1B,GAAG,CAAC,MAAM,CAAC,CAAC,EAAE,CAAC,CAAC,CAAA;IAClB,CAAC,CAAC,CAAA;IAEF,IAAI,QAAQ,EAAE;QACZ,IAAM,IAAI,GAAG,MAAM,CAAC,MAAM,CAAC,MAAM,GAAG,CAAC,CAAC,CAAA;QACtC,IAAM,EAAE,GAAG,MAAM,CAAC,CAAC,CAAC,CAAA;QACpB,IAAI,CAAC,IAAI,IAAI,CAAC,EAAE,EAAE;YAChB,OAAM;SACP;QAED,GAAG,CAAC,MAAM,CAAC,IAAI,CAAC,CAAC,EAAE,IAAI,CAAC,CAAC,CAAC,CAAA;QAC1B,GAAG,CAAC,MAAM,CAAC,EAAE,CAAC,CAAC,EAAE,EAAE,CAAC,CAAC,CAAC,CAAA;KACvB;IAED,GAAG,CAAC,MAAM,EAAE,CAAA;AACd,CAAC"}
\ No newline at end of file

build/es6/draw/drawDetections.d.ts

+import { IBoundingBox, IRect } from 'tfjs-image-recognition-base';
+import { FaceDetection } from '../classes/FaceDetection';
+import { WithFaceDetection } from '../factories/WithFaceDetection';
+export declare type TDrawDetectionsInput = IRect | IBoundingBox | FaceDetection | WithFaceDetection<{}>;
+export declare function drawDetections(canvasArg: string | HTMLCanvasElement, detections: TDrawDetectionsInput | Array<TDrawDetectionsInput>): void;

build/es6/draw/drawDetections.js

+import { Box, draw, round } from 'tfjs-image-recognition-base';
+import { FaceDetection } from '../classes/FaceDetection';
+import { isWithFaceDetection } from '../factories/WithFaceDetection';
+export function drawDetections(canvasArg, detections) {
+    var detectionsArray = Array.isArray(detections) ? detections : [detections];
+    detectionsArray.forEach(function (det) {
+        var score = det instanceof FaceDetection
+            ? det.score
+            : (isWithFaceDetection(det) ? det.detection.score : undefined);
+        var box = det instanceof FaceDetection
+            ? det.box
+            : (isWithFaceDetection(det) ? det.detection.box : new Box(det));
+        var label = score ? "" + round(score) : undefined;
+        new draw.DrawBox(box, { label: label }).draw(canvasArg);
+    });
+}
+//# sourceMappingURL=drawDetections.js.map
\ No newline at end of file

build/es6/draw/drawDetections.js.map

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\ No newline at end of file

build/es6/draw/drawFaceExpressions.d.ts

+import { IPoint } from 'tfjs-image-recognition-base';
+import { FaceExpressions } from '../faceExpressionNet';
+import { WithFaceExpressions } from '../factories/WithFaceExpressions';
+export declare type DrawFaceExpressionsInput = FaceExpressions | WithFaceExpressions<{}>;
+export declare function drawFaceExpressions(canvasArg: string | HTMLCanvasElement, faceExpressions: DrawFaceExpressionsInput | Array<DrawFaceExpressionsInput>, minConfidence?: number, textFieldAnchor?: IPoint): void;

build/es6/draw/drawFaceExpressions.js

+import { draw, Point, round } from 'tfjs-image-recognition-base';
+import { FaceExpressions } from '../faceExpressionNet';
+import { isWithFaceDetection } from '../factories/WithFaceDetection';
+import { isWithFaceExpressions } from '../factories/WithFaceExpressions';
+export function drawFaceExpressions(canvasArg, faceExpressions, minConfidence, textFieldAnchor) {
+    if (minConfidence === void 0) { minConfidence = 0.1; }
+    var faceExpressionsArray = Array.isArray(faceExpressions) ? faceExpressions : [faceExpressions];
+    faceExpressionsArray.forEach(function (e) {
+        var expr = e instanceof FaceExpressions
+            ? e
+            : (isWithFaceExpressions(e) ? e.expressions : undefined);
+        if (!expr) {
+            throw new Error('drawFaceExpressions - expected faceExpressions to be FaceExpressions | WithFaceExpressions<{}> or array thereof');
+        }
+        var sorted = expr.asSortedArray();
+        var resultsToDisplay = sorted.filter(function (expr) { return expr.probability > minConfidence; });
+        var anchor = isWithFaceDetection(e)
+            ? e.detection.box.bottomLeft
+            : (textFieldAnchor || new Point(0, 0));
+        var drawTextField = new draw.DrawTextField(resultsToDisplay.map(function (expr) { return expr.expression + " (" + round(expr.probability) + ")"; }), anchor);
+        drawTextField.draw(canvasArg);
+    });
+}
+//# sourceMappingURL=drawFaceExpressions.js.map
\ No newline at end of file

build/es6/draw/drawFaceExpressions.js.map

+{"version":3,"file":"drawFaceExpressions.js","sourceRoot":"","sources":["../../../src/draw/drawFaceExpressions.ts"],"names":[],"mappings":"AAAA,OAAO,EAAE,IAAI,EAAU,KAAK,EAAE,KAAK,EAAE,MAAM,6BAA6B,CAAC;AAEzE,OAAO,EAAE,eAAe,EAAE,MAAM,sBAAsB,CAAC;AACvD,OAAO,EAAE,mBAAmB,EAAE,MAAM,gCAAgC,CAAC;AACrE,OAAO,EAAE,qBAAqB,EAAuB,MAAM,kCAAkC,CAAC;AAI9F,MAAM,UAAU,mBAAmB,CACjC,SAAqC,EACrC,eAA2E,EAC3E,aAAmB,EACnB,eAAwB;IADxB,8BAAA,EAAA,mBAAmB;IAGnB,IAAM,oBAAoB,GAAG,KAAK,CAAC,OAAO,CAAC,eAAe,CAAC,CAAC,CAAC,CAAC,eAAe,CAAC,CAAC,CAAC,CAAC,eAAe,CAAC,CAAA;IAEjG,oBAAoB,CAAC,OAAO,CAAC,UAAA,CAAC;QAC5B,IAAM,IAAI,GAAG,CAAC,YAAY,eAAe;YACvC,CAAC,CAAC,CAAC;YACH,CAAC,CAAC,CAAC,qBAAqB,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,WAAW,CAAC,CAAC,CAAC,SAAS,CAAC,CAAA;QAC1D,IAAI,CAAC,IAAI,EAAE;YACT,MAAM,IAAI,KAAK,CAAC,iHAAiH,CAAC,CAAA;SACnI;QAED,IAAM,MAAM,GAAG,IAAI,CAAC,aAAa,EAAE,CAAA;QACnC,IAAM,gBAAgB,GAAG,MAAM,CAAC,MAAM,CAAC,UAAA,IAAI,IAAI,OAAA,IAAI,CAAC,WAAW,GAAG,aAAa,EAAhC,CAAgC,CAAC,CAAA;QAEhF,IAAM,MAAM,GAAG,mBAAmB,CAAC,CAAC,CAAC;YACnC,CAAC,CAAC,CAAC,CAAC,SAAS,CAAC,GAAG,CAAC,UAAU;YAC5B,CAAC,CAAC,CAAC,eAAe,IAAI,IAAI,KAAK,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAA;QAExC,IAAM,aAAa,GAAG,IAAI,IAAI,CAAC,aAAa,CAC1C,gBAAgB,CAAC,GAAG,CAAC,UAAA,IAAI,IAAI,OAAG,IAAI,CAAC,UAAU,UAAK,KAAK,CAAC,IAAI,CAAC,WAAW,CAAC,MAAG,EAAjD,CAAiD,CAAC,EAC/E,MAAM,CACP,CAAA;QACD,aAAa,CAAC,IAAI,CAAC,SAAS,CAAC,CAAA;IAC/B,CAAC,CAAC,CAAA;AACJ,CAAC"}
\ No newline at end of file

build/es6/draw/index.d.ts

+export * from './drawContour';
+export * from './drawDetections';
+export * from './drawFaceExpressions';
+export * from './DrawFaceLandmarks';

build/es6/draw/index.js

+export * from './drawContour';
+export * from './drawDetections';
+export * from './drawFaceExpressions';
+export * from './DrawFaceLandmarks';
+//# sourceMappingURL=index.js.map
\ No newline at end of file

build/es6/draw/index.js.map

+{"version":3,"file":"index.js","sourceRoot":"","sources":["../../../src/draw/index.ts"],"names":[],"mappings":"AAAA,cAAc,eAAe,CAAA;AAC7B,cAAc,kBAAkB,CAAA;AAChC,cAAc,uBAAuB,CAAA;AACrC,cAAc,qBAAqB,CAAA"}
\ No newline at end of file

build/es6/faceExpressionNet/FaceExpressionNet.d.ts

@@ -3,14 +3,12 @@ import { NetInput, TNetInput } from 'tfjs-image-recognition-base';
 import { FaceFeatureExtractor } from '../faceFeatureExtractor/FaceFeatureExtractor';
 import { FaceFeatureExtractorParams } from '../faceFeatureExtractor/types';
 import { FaceProcessor } from '../faceProcessor/FaceProcessor';
-import { FaceExpressionPrediction } from './types';
+import { FaceExpressions } from './FaceExpressions';
 export declare class FaceExpressionNet extends FaceProcessor<FaceFeatureExtractorParams> {
-    static getFaceExpressionLabel(faceExpression: string): number;
-    static decodeProbabilites(probabilities: number[] | Float32Array): FaceExpressionPrediction[];
     constructor(faceFeatureExtractor?: FaceFeatureExtractor);
     forwardInput(input: NetInput | tf.Tensor4D): tf.Tensor2D;
     forward(input: TNetInput): Promise<tf.Tensor2D>;
-    predictExpressions(input: TNetInput): Promise<FaceExpressionPrediction[] | FaceExpressionPrediction[][]>;
+    predictExpressions(input: TNetInput): Promise<FaceExpressions | FaceExpressions[]>;
     protected getDefaultModelName(): string;
     protected getClassifierChannelsIn(): number;
     protected getClassifierChannelsOut(): number;

build/es6/faceExpressionNet/FaceExpressionNet.js

@@ -3,27 +3,13 @@ import * as tf from '@tensorflow/tfjs-core';
 import { toNetInput } from 'tfjs-image-recognition-base';
 import { FaceFeatureExtractor } from '../faceFeatureExtractor/FaceFeatureExtractor';
 import { FaceProcessor } from '../faceProcessor/FaceProcessor';
-import { faceExpressionLabels } from './types';
+import { FaceExpressions } from './FaceExpressions';
 var FaceExpressionNet = /** @class */ (function (_super) {
     tslib_1.__extends(FaceExpressionNet, _super);
     function FaceExpressionNet(faceFeatureExtractor) {
         if (faceFeatureExtractor === void 0) { faceFeatureExtractor = new FaceFeatureExtractor(); }
         return _super.call(this, 'FaceExpressionNet', faceFeatureExtractor) || this;
     }
-    FaceExpressionNet.getFaceExpressionLabel = function (faceExpression) {
-        var label = faceExpressionLabels[faceExpression];
-        if (typeof label !== 'number') {
-            throw new Error("getFaceExpressionLabel - no label for faceExpression: " + faceExpression);
-        }
-        return label;
-    };
-    FaceExpressionNet.decodeProbabilites = function (probabilities) {
-        if (probabilities.length !== 7) {
-            throw new Error("decodeProbabilites - expected probabilities.length to be 7, have: " + probabilities.length);
-        }
-        return Object.keys(faceExpressionLabels)
-            .map(function (expression) { return ({ expression: expression, probability: probabilities[faceExpressionLabels[expression]] }); });
-    };
     FaceExpressionNet.prototype.forwardInput = function (input) {
         var _this = this;
         return tf.tidy(function () { return tf.softmax(_this.runNet(input)); });
@@ -69,7 +55,7 @@ var FaceExpressionNet = /** @class */ (function (_super) {
                         probabilitesByBatch = _a.sent();
                         out.dispose();
                         predictionsByBatch = probabilitesByBatch
-                            .map(function (propablities) { return FaceExpressionNet.decodeProbabilites(propablities); });
+                            .map(function (probabilites) { return new FaceExpressions(probabilites); });
                         return [2 /*return*/, netInput.isBatchInput
                                 ? predictionsByBatch
                                 : predictionsByBatch[0]];

build/es6/faceExpressionNet/FaceExpressionNet.js.map

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+{"version":3,"file":"FaceExpressionNet.js","sourceRoot":"","sources":["../../../src/faceExpressionNet/FaceExpressionNet.ts"],"names":[],"mappings":";AAAA,OAAO,KAAK,EAAE,MAAM,uBAAuB,CAAC;AAC5C,OAAO,EAAuB,UAAU,EAAE,MAAM,6BAA6B,CAAC;AAE9E,OAAO,EAAE,oBAAoB,EAAE,MAAM,8CAA8C,CAAC;AAEpF,OAAO,EAAE,aAAa,EAAE,MAAM,gCAAgC,CAAC;AAC/D,OAAO,EAAE,eAAe,EAAE,MAAM,mBAAmB,CAAC;AAEpD;IAAuC,6CAAyC;IAE9E,2BAAY,oBAAuE;QAAvE,qCAAA,EAAA,2BAAiD,oBAAoB,EAAE;eACjF,kBAAM,mBAAmB,EAAE,oBAAoB,CAAC;IAClD,CAAC;IAEM,wCAAY,GAAnB,UAAoB,KAA6B;QAAjD,iBAEC;QADC,OAAO,EAAE,CAAC,IAAI,CAAC,cAAM,OAAA,EAAE,CAAC,OAAO,CAAC,KAAI,CAAC,MAAM,CAAC,KAAK,CAAC,CAAC,EAA9B,CAA8B,CAAC,CAAA;IACtD,CAAC;IAEY,mCAAO,GAApB,UAAqB,KAAgB;;;;;;wBAC5B,KAAA,IAAI,CAAC,YAAY,CAAA;wBAAC,qBAAM,UAAU,CAAC,KAAK,CAAC,EAAA;4BAAhD,sBAAO,SAAA,IAAI,GAAc,SAAuB,EAAC,EAAA;;;;KAClD;IAEY,8CAAkB,GAA/B,UAAgC,KAAgB;;;;;;4BAC7B,qBAAM,UAAU,CAAC,KAAK,CAAC,EAAA;;wBAAlC,QAAQ,GAAG,SAAuB;wBAC5B,qBAAM,IAAI,CAAC,YAAY,CAAC,QAAQ,CAAC,EAAA;;wBAAvC,GAAG,GAAG,SAAiC;wBACjB,qBAAM,OAAO,CAAC,GAAG,CAAC,EAAE,CAAC,OAAO,CAAC,GAAG,CAAC,CAAC,GAAG,CAAC,UAAM,CAAC;;;;gDAC1D,qBAAM,CAAC,CAAC,IAAI,EAAE,EAAA;;4CAArB,IAAI,GAAG,SAAc;4CAC3B,CAAC,CAAC,OAAO,EAAE,CAAA;4CACX,sBAAO,IAAI,EAAA;;;iCACZ,CAAC,CAAC,EAAA;;wBAJG,mBAAmB,GAAG,SAIzB;wBACH,GAAG,CAAC,OAAO,EAAE,CAAA;wBAEP,kBAAkB,GAAG,mBAAmB;6BAC3C,GAAG,CAAC,UAAA,YAAY,IAAI,OAAA,IAAI,eAAe,CAAC,YAA4B,CAAC,EAAjD,CAAiD,CAAC,CAAA;wBAEzE,sBAAO,QAAQ,CAAC,YAAY;gCAC1B,CAAC,CAAC,kBAAkB;gCACpB,CAAC,CAAC,kBAAkB,CAAC,CAAC,CAAC,EAAA;;;;KAC1B;IAES,+CAAmB,GAA7B;QACE,OAAO,uBAAuB,CAAA;IAChC,CAAC;IAES,mDAAuB,GAAjC;QACE,OAAO,GAAG,CAAA;IACZ,CAAC;IAES,oDAAwB,GAAlC;QACE,OAAO,CAAC,CAAA;IACV,CAAC;IACH,wBAAC;AAAD,CAAC,AA3CD,CAAuC,aAAa,GA2CnD"}
\ No newline at end of file

build/es6/faceExpressionNet/types.d.ts → build/es6/faceExpressionNet/FaceExpressions.d.ts

-export declare const faceExpressionLabels: {
+export declare const FACE_EXPRESSION_LABELS: string[];
+export declare class FaceExpressions {
     neutral: number;
     happy: number;
     sad: number;
@@ -6,9 +7,9 @@ export declare const faceExpressionLabels: {
     fearful: number;
     disgusted: number;
     surprised: number;
-};
-export declare type FaceExpression = 'neutral' | 'happy' | 'sad' | 'angry' | 'fearful' | 'disgusted' | 'surprised';
-export declare type FaceExpressionPrediction = {
-    expression: FaceExpression;
-    probability: number;
-};
+    constructor(probabilities: number[] | Float32Array);
+    asSortedArray(): {
+        expression: string;
+        probability: number;
+    }[];
+}

build/es6/faceExpressionNet/FaceExpressions.js

+export var FACE_EXPRESSION_LABELS = ['neutral', 'happy', 'sad', 'angry', 'fearful', 'disgusted', 'surprised'];
+var FaceExpressions = /** @class */ (function () {
+    function FaceExpressions(probabilities) {
+        var _this = this;
+        if (probabilities.length !== 7) {
+            throw new Error("FaceExpressions.constructor - expected probabilities.length to be 7, have: " + probabilities.length);
+        }
+        FACE_EXPRESSION_LABELS.forEach(function (expression, idx) {
+            _this[expression] = probabilities[idx];
+        });
+    }
+    FaceExpressions.prototype.asSortedArray = function () {
+        var _this = this;
+        return FACE_EXPRESSION_LABELS
+            .map(function (expression) { return ({ expression: expression, probability: _this[expression] }); })
+            .sort(function (e0, e1) { return e1.probability - e0.probability; });
+    };
+    return FaceExpressions;
+}());
+export { FaceExpressions };
+//# sourceMappingURL=FaceExpressions.js.map
\ No newline at end of file

build/es6/faceExpressionNet/FaceExpressions.js.map

+{"version":3,"file":"FaceExpressions.js","sourceRoot":"","sources":["../../../src/faceExpressionNet/FaceExpressions.ts"],"names":[],"mappings":"AAAA,MAAM,CAAC,IAAM,sBAAsB,GAAG,CAAC,SAAS,EAAE,OAAO,EAAE,KAAK,EAAE,OAAO,EAAE,SAAS,EAAE,WAAW,EAAE,WAAW,CAAC,CAAA;AAE/G;IASE,yBAAY,aAAsC;QAAlD,iBAQC;QAPC,IAAI,aAAa,CAAC,MAAM,KAAK,CAAC,EAAE;YAC9B,MAAM,IAAI,KAAK,CAAC,gFAA8E,aAAa,CAAC,MAAQ,CAAC,CAAA;SACtH;QAED,sBAAsB,CAAC,OAAO,CAAC,UAAC,UAAU,EAAE,GAAG;YAC7C,KAAI,CAAC,UAAU,CAAC,GAAG,aAAa,CAAC,GAAG,CAAC,CAAA;QACvC,CAAC,CAAC,CAAA;IACJ,CAAC;IAED,uCAAa,GAAb;QAAA,iBAIC;QAHC,OAAO,sBAAsB;aAC1B,GAAG,CAAC,UAAA,UAAU,IAAI,OAAA,CAAC,EAAE,UAAU,YAAA,EAAE,WAAW,EAAE,KAAI,CAAC,UAAU,CAAW,EAAE,CAAC,EAAzD,CAAyD,CAAC;aAC5E,IAAI,CAAC,UAAC,EAAE,EAAE,EAAE,IAAK,OAAA,EAAE,CAAC,WAAW,GAAG,EAAE,CAAC,WAAW,EAA/B,CAA+B,CAAC,CAAA;IACtD,CAAC;IACH,sBAAC;AAAD,CAAC,AAxBD,IAwBC"}
\ No newline at end of file

build/es6/faceExpressionNet/index.d.ts

 export * from './FaceExpressionNet';
-export * from './types';
+export * from './FaceExpressions';

build/es6/faceExpressionNet/index.js

 export * from './FaceExpressionNet';
-export * from './types';
+export * from './FaceExpressions';
 //# sourceMappingURL=index.js.map
\ No newline at end of file

build/es6/faceExpressionNet/index.js.map

-{"version":3,"file":"index.js","sourceRoot":"","sources":["../../../src/faceExpressionNet/index.ts"],"names":[],"mappings":"AAAA,cAAc,qBAAqB,CAAC;AACpC,cAAc,SAAS,CAAC"}
+{"version":3,"file":"index.js","sourceRoot":"","sources":["../../../src/faceExpressionNet/index.ts"],"names":[],"mappings":"AAAA,cAAc,qBAAqB,CAAC;AACpC,cAAc,mBAAmB,CAAC"}
\ No newline at end of file

build/es6/faceExpressionNet/types.js

-export var faceExpressionLabels = {
-    neutral: 0,
-    happy: 1,
-    sad: 2,
-    angry: 3,
-    fearful: 4,
-    disgusted: 5,
-    surprised: 6
-};
-//# sourceMappingURL=types.js.map
\ No newline at end of file

build/es6/faceExpressionNet/types.js.map

-{"version":3,"file":"types.js","sourceRoot":"","sources":["../../../src/faceExpressionNet/types.ts"],"names":[],"mappings":"AAAA,MAAM,CAAC,IAAM,oBAAoB,GAAG;IAClC,OAAO,EAAE,CAAC;IACV,KAAK,EAAE,CAAC;IACR,GAAG,EAAE,CAAC;IACN,KAAK,EAAE,CAAC;IACR,OAAO,EAAE,CAAC;IACV,SAAS,EAAE,CAAC;IACZ,SAAS,EAAC,CAAC;CACZ,CAAA"}
\ No newline at end of file

build/es6/faceFeatureExtractor/denseBlock.js

 import * as tf from '@tensorflow/tfjs-core';
-import { depthwiseSeparableConv } from './depthwiseSeparableConv';
+import { depthwiseSeparableConv } from '../common/depthwiseSeparableConv';
 export function denseBlock3(x, denseBlockParams, isFirstLayer) {
     if (isFirstLayer === void 0) { isFirstLayer = false; }
     return tf.tidy(function () {

build/es6/faceFeatureExtractor/denseBlock.js.map

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\ No newline at end of file

build/es6/faceFeatureExtractor/depthwiseSeparableConv.js.map

-{"version":3,"file":"depthwiseSeparableConv.js","sourceRoot":"","sources":["../../../src/faceFeatureExtractor/depthwiseSeparableConv.ts"],"names":[],"mappings":"AAAA,OAAO,KAAK,EAAE,MAAM,uBAAuB,CAAC;AAG5C,MAAM,UAAU,sBAAsB,CACpC,CAAc,EACd,MAAoD,EACpD,MAAwB;IAExB,OAAO,EAAE,CAAC,IAAI,CAAC;QACb,IAAI,GAAG,GAAG,EAAE,CAAC,eAAe,CAAC,CAAC,EAAE,MAAM,CAAC,gBAAgB,EAAE,MAAM,CAAC,gBAAgB,EAAE,MAAM,EAAE,MAAM,CAAC,CAAA;QACjG,GAAG,GAAG,EAAE,CAAC,GAAG,CAAC,GAAG,EAAE,MAAM,CAAC,IAAI,CAAC,CAAA;QAC9B,OAAO,GAAG,CAAA;IACZ,CAAC,CAAC,CAAA;AACJ,CAAC"}
\ No newline at end of file

build/es6/faceFeatureExtractor/extractorsFactory.js

-import * as tf from '@tensorflow/tfjs-core';
 import { TfjsImageRecognitionBase } from 'tfjs-image-recognition-base';
 export function extractorsFactory(extractWeights, paramMappings) {
-    function extractSeparableConvParams(channelsIn, channelsOut, mappedPrefix) {
-        var depthwise_filter = tf.tensor4d(extractWeights(3 * 3 * channelsIn), [3, 3, channelsIn, 1]);
-        var pointwise_filter = tf.tensor4d(extractWeights(channelsIn * channelsOut), [1, 1, channelsIn, channelsOut]);
-        var bias = tf.tensor1d(extractWeights(channelsOut));
-        paramMappings.push({ paramPath: mappedPrefix + "/depthwise_filter" }, { paramPath: mappedPrefix + "/pointwise_filter" }, { paramPath: mappedPrefix + "/bias" });
-        return new TfjsImageRecognitionBase.SeparableConvParams(depthwise_filter, pointwise_filter, bias);
-    }
     var extractConvParams = TfjsImageRecognitionBase.extractConvParamsFactory(extractWeights, paramMappings);
+    var extractSeparableConvParams = TfjsImageRecognitionBase.extractSeparableConvParamsFactory(extractWeights, paramMappings);
     function extractDenseBlock3Params(channelsIn, channelsOut, mappedPrefix, isFirstLayer) {
         if (isFirstLayer === void 0) { isFirstLayer = false; }
         var conv0 = isFirstLayer

build/es6/faceFeatureExtractor/extractorsFactory.js.map

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\ No newline at end of file

build/es6/faceFeatureExtractor/loadParamsFactory.js

 import { TfjsImageRecognitionBase } from 'tfjs-image-recognition-base';
+import { loadConvParamsFactory } from '../common/loadConvParamsFactory';
 export function loadParamsFactory(weightMap, paramMappings) {
     var extractWeightEntry = TfjsImageRecognitionBase.extractWeightEntryFactory(weightMap, paramMappings);
-    function extractConvParams(prefix) {
-        var filters = extractWeightEntry(prefix + "/filters", 4);
-        var bias = extractWeightEntry(prefix + "/bias", 1);
-        return { filters: filters, bias: bias };
-    }
-    function extractSeparableConvParams(prefix) {
-        var depthwise_filter = extractWeightEntry(prefix + "/depthwise_filter", 4);
-        var pointwise_filter = extractWeightEntry(prefix + "/pointwise_filter", 4);
-        var bias = extractWeightEntry(prefix + "/bias", 1);
-        return new TfjsImageRecognitionBase.SeparableConvParams(depthwise_filter, pointwise_filter, bias);
-    }
+    var extractConvParams = loadConvParamsFactory(extractWeightEntry);
+    var extractSeparableConvParams = TfjsImageRecognitionBase.loadSeparableConvParamsFactory(extractWeightEntry);
     function extractDenseBlock3Params(prefix, isFirstLayer) {
         if (isFirstLayer === void 0) { isFirstLayer = false; }
         var conv0 = isFirstLayer

build/es6/faceFeatureExtractor/loadParamsFactory.js.map

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+{"version":3,"file":"loadParamsFactory.js","sourceRoot":"","sources":["../../../src/faceFeatureExtractor/loadParamsFactory.ts"],"names":[],"mappings":"AAAA,OAAO,EAAE,wBAAwB,EAAE,MAAM,6BAA6B,CAAC;AAEvE,OAAO,EAAE,qBAAqB,EAAE,MAAM,iCAAiC,CAAC;AAGxE,MAAM,UAAU,iBAAiB,CAAC,SAAc,EAAE,aAAsD;IAEtG,IAAM,kBAAkB,GAAG,wBAAwB,CAAC,yBAAyB,CAAC,SAAS,EAAE,aAAa,CAAC,CAAA;IAEvG,IAAM,iBAAiB,GAAG,qBAAqB,CAAC,kBAAkB,CAAC,CAAA;IACnE,IAAM,0BAA0B,GAAG,wBAAwB,CAAC,8BAA8B,CAAC,kBAAkB,CAAC,CAAA;IAE9G,SAAS,wBAAwB,CAAC,MAAc,EAAE,YAA6B;QAA7B,6BAAA,EAAA,oBAA6B;QAC7E,IAAM,KAAK,GAAG,YAAY;YACxB,CAAC,CAAC,iBAAiB,CAAI,MAAM,WAAQ,CAAC;YACtC,CAAC,CAAC,0BAA0B,CAAI,MAAM,WAAQ,CAAC,CAAA;QACjD,IAAM,KAAK,GAAG,0BAA0B,CAAI,MAAM,WAAQ,CAAC,CAAA;QAC3D,IAAM,KAAK,GAAG,0BAA0B,CAAI,MAAM,WAAQ,CAAC,CAAA;QAE3D,OAAO,EAAE,KAAK,OAAA,EAAE,KAAK,OAAA,EAAE,KAAK,OAAA,EAAE,CAAA;IAChC,CAAC;IAED,SAAS,wBAAwB,CAAC,MAAc,EAAE,YAA6B;QAA7B,6BAAA,EAAA,oBAA6B;QAC7E,IAAM,KAAK,GAAG,YAAY;YACxB,CAAC,CAAC,iBAAiB,CAAI,MAAM,WAAQ,CAAC;YACtC,CAAC,CAAC,0BAA0B,CAAI,MAAM,WAAQ,CAAC,CAAA;QACjD,IAAM,KAAK,GAAG,0BAA0B,CAAI,MAAM,WAAQ,CAAC,CAAA;QAC3D,IAAM,KAAK,GAAG,0BAA0B,CAAI,MAAM,WAAQ,CAAC,CAAA;QAC3D,IAAM,KAAK,GAAG,0BAA0B,CAAI,MAAM,WAAQ,CAAC,CAAA;QAE3D,OAAO,EAAE,KAAK,OAAA,EAAE,KAAK,OAAA,EAAE,KAAK,OAAA,EAAE,KAAK,OAAA,EAAE,CAAA;IACvC,CAAC;IAED,OAAO;QACL,wBAAwB,0BAAA;QACxB,wBAAwB,0BAAA;KACzB,CAAA;AACH,CAAC"}
\ No newline at end of file

build/es6/factories/WithAge.d.ts

+export declare type WithAge<TSource> = TSource & {
+    age: number;
+};
+export declare function isWithAge(obj: any): obj is WithAge<{}>;
+export declare function extendWithAge<TSource>(sourceObj: TSource, age: number): WithAge<TSource>;

build/es6/factories/WithAge.js

+export function isWithAge(obj) {
+    return typeof obj['age'] === 'number';
+}
+export function extendWithAge(sourceObj, age) {
+    var extension = { age: age };
+    return Object.assign({}, sourceObj, extension);
+}
+//# sourceMappingURL=WithAge.js.map
\ No newline at end of file

build/es6/factories/WithAge.js.map

+{"version":3,"file":"WithAge.js","sourceRoot":"","sources":["../../../src/factories/WithAge.ts"],"names":[],"mappings":"AAIA,MAAM,UAAU,SAAS,CAAC,GAAQ;IAChC,OAAO,OAAO,GAAG,CAAC,KAAK,CAAC,KAAK,QAAQ,CAAA;AACvC,CAAC;AAED,MAAM,UAAU,aAAa,CAG3B,SAAkB,EAClB,GAAW;IAGX,IAAM,SAAS,GAAG,EAAE,GAAG,KAAA,EAAE,CAAA;IACzB,OAAO,MAAM,CAAC,MAAM,CAAC,EAAE,EAAE,SAAS,EAAE,SAAS,CAAC,CAAA;AAChD,CAAC"}
\ No newline at end of file

build/es6/factories/WithFaceDetection.d.ts

@@ -2,4 +2,5 @@ import { FaceDetection } from '../classes/FaceDetection';
 export declare type WithFaceDetection<TSource> = TSource & {
     detection: FaceDetection;
 };
+export declare function isWithFaceDetection(obj: any): obj is WithFaceDetection<{}>;
 export declare function extendWithFaceDetection<TSource>(sourceObj: TSource, detection: FaceDetection): WithFaceDetection<TSource>;

build/es6/factories/WithFaceDetection.js

+import { FaceDetection } from '../classes/FaceDetection';
+export function isWithFaceDetection(obj) {
+    return obj['detection'] instanceof FaceDetection;
+}
 export function extendWithFaceDetection(sourceObj, detection) {
     var extension = { detection: detection };
     return Object.assign({}, sourceObj, extension);

build/es6/factories/WithFaceDetection.js.map

-{"version":3,"file":"WithFaceDetection.js","sourceRoot":"","sources":["../../../src/factories/WithFaceDetection.ts"],"names":[],"mappings":"AAMA,MAAM,UAAU,uBAAuB,CAGrC,SAAkB,EAClB,SAAwB;IAGxB,IAAM,SAAS,GAAG,EAAE,SAAS,WAAA,EAAE,CAAA;IAC/B,OAAO,MAAM,CAAC,MAAM,CAAC,EAAE,EAAE,SAAS,EAAE,SAAS,CAAC,CAAA;AAChD,CAAC"}
+{"version":3,"file":"WithFaceDetection.js","sourceRoot":"","sources":["../../../src/factories/WithFaceDetection.ts"],"names":[],"mappings":"AAAA,OAAO,EAAE,aAAa,EAAE,MAAM,0BAA0B,CAAC;AAMzD,MAAM,UAAU,mBAAmB,CAAC,GAAQ;IAC1C,OAAO,GAAG,CAAC,WAAW,CAAC,YAAY,aAAa,CAAA;AAClD,CAAC;AAED,MAAM,UAAU,uBAAuB,CAGrC,SAAkB,EAClB,SAAwB;IAGxB,IAAM,SAAS,GAAG,EAAE,SAAS,WAAA,EAAE,CAAA;IAC/B,OAAO,MAAM,CAAC,MAAM,CAAC,EAAE,EAAE,SAAS,EAAE,SAAS,CAAC,CAAA;AAChD,CAAC"}
\ No newline at end of file

build/es6/factories/WithFaceExpressions.d.ts

-import { FaceExpressionPrediction } from '../faceExpressionNet/types';
+import { FaceExpressions } from '../faceExpressionNet/FaceExpressions';
 export declare type WithFaceExpressions<TSource> = TSource & {
-    expressions: FaceExpressionPrediction[];
+    expressions: FaceExpressions;
 };
-export declare function extendWithFaceExpressions<TSource>(sourceObj: TSource, expressions: FaceExpressionPrediction[]): WithFaceExpressions<TSource>;
+export declare function isWithFaceExpressions(obj: any): obj is WithFaceExpressions<{}>;
+export declare function extendWithFaceExpressions<TSource>(sourceObj: TSource, expressions: FaceExpressions): WithFaceExpressions<TSource>;

build/es6/factories/WithFaceExpressions.js

+import { FaceExpressions } from '../faceExpressionNet/FaceExpressions';
+export function isWithFaceExpressions(obj) {
+    return obj['expressions'] instanceof FaceExpressions;
+}
 export function extendWithFaceExpressions(sourceObj, expressions) {
     var extension = { expressions: expressions };
     return Object.assign({}, sourceObj, extension);

build/es6/factories/WithFaceExpressions.js.map

-{"version":3,"file":"WithFaceExpressions.js","sourceRoot":"","sources":["../../../src/factories/WithFaceExpressions.ts"],"names":[],"mappings":"AAMA,MAAM,UAAU,yBAAyB,CAGvC,SAAkB,EAClB,WAAuC;IAGvC,IAAM,SAAS,GAAG,EAAE,WAAW,aAAA,EAAE,CAAA;IACjC,OAAO,MAAM,CAAC,MAAM,CAAC,EAAE,EAAE,SAAS,EAAE,SAAS,CAAC,CAAA;AAChD,CAAC"}
+{"version":3,"file":"WithFaceExpressions.js","sourceRoot":"","sources":["../../../src/factories/WithFaceExpressions.ts"],"names":[],"mappings":"AAAA,OAAO,EAAE,eAAe,EAAE,MAAM,sCAAsC,CAAC;AAMvE,MAAM,UAAU,qBAAqB,CAAC,GAAQ;IAC5C,OAAO,GAAG,CAAC,aAAa,CAAC,YAAY,eAAe,CAAA;AACtD,CAAC;AAED,MAAM,UAAU,yBAAyB,CAGvC,SAAkB,EAClB,WAA4B;IAG5B,IAAM,SAAS,GAAG,EAAE,WAAW,aAAA,EAAE,CAAA;IACjC,OAAO,MAAM,CAAC,MAAM,CAAC,EAAE,EAAE,SAAS,EAAE,SAAS,CAAC,CAAA;AAChD,CAAC"}
\ No newline at end of file

build/es6/factories/WithFaceLandmarks.d.ts

@@ -7,4 +7,5 @@ export declare type WithFaceLandmarks<TSource extends WithFaceDetection<{}>, TFa
     unshiftedLandmarks: TFaceLandmarks;
     alignedRect: FaceDetection;
 };
+export declare function isWithFaceLandmarks(obj: any): obj is WithFaceLandmarks<WithFaceDetection<{}>, FaceLandmarks>;
 export declare function extendWithFaceLandmarks<TSource extends WithFaceDetection<{}>, TFaceLandmarks extends FaceLandmarks = FaceLandmarks68>(sourceObj: TSource, unshiftedLandmarks: TFaceLandmarks): WithFaceLandmarks<TSource, TFaceLandmarks>;

build/es6/factories/WithFaceLandmarks.js

 import { FaceDetection } from '../classes/FaceDetection';
+import { FaceLandmarks } from '../classes/FaceLandmarks';
+import { isWithFaceDetection } from './WithFaceDetection';
+export function isWithFaceLandmarks(obj) {
+    return isWithFaceDetection(obj)
+        && obj['landmarks'] instanceof FaceLandmarks
+        && obj['unshiftedLandmarks'] instanceof FaceLandmarks
+        && obj['alignedRect'] instanceof FaceDetection;
+}
 export function extendWithFaceLandmarks(sourceObj, unshiftedLandmarks) {
     var shift = sourceObj.detection.box;
     var landmarks = unshiftedLandmarks.shiftBy(shift.x, shift.y);

build/es6/factories/WithFaceLandmarks.js.map

-{"version":3,"file":"WithFaceLandmarks.js","sourceRoot":"","sources":["../../../src/factories/WithFaceLandmarks.ts"],"names":[],"mappings":"AAAA,OAAO,EAAE,aAAa,EAAE,MAAM,0BAA0B,CAAC;AAczD,MAAM,UAAU,uBAAuB,CAIrC,SAAkB,EAClB,kBAAkC;IAG1B,IAAA,+BAAU,CAAwB;IAC1C,IAAM,SAAS,GAAG,kBAAkB,CAAC,OAAO,CAAiB,KAAK,CAAC,CAAC,EAAE,KAAK,CAAC,CAAC,CAAC,CAAA;IAE9E,IAAM,IAAI,GAAG,SAAS,CAAC,KAAK,EAAE,CAAA;IACtB,IAAA,yCAAS,CAAwB;IACzC,IAAM,WAAW,GAAG,IAAI,aAAa,CAAC,SAAS,CAAC,SAAS,CAAC,KAAK,EAAE,IAAI,CAAC,OAAO,CAAC,SAAS,CAAC,OAAO,EAAE,CAAC,EAAE,SAAS,CAAC,CAAA;IAE9G,IAAM,SAAS,GAAG;QAChB,SAAS,WAAA;QACT,kBAAkB,oBAAA;QAClB,WAAW,aAAA;KACZ,CAAA;IAED,OAAO,MAAM,CAAC,MAAM,CAAC,EAAE,EAAE,SAAS,EAAE,SAAS,CAAC,CAAA;AAChD,CAAC"}
+{"version":3,"file":"WithFaceLandmarks.js","sourceRoot":"","sources":["../../../src/factories/WithFaceLandmarks.ts"],"names":[],"mappings":"AAAA,OAAO,EAAE,aAAa,EAAE,MAAM,0BAA0B,CAAC;AACzD,OAAO,EAAE,aAAa,EAAE,MAAM,0BAA0B,CAAC;AAEzD,OAAO,EAAE,mBAAmB,EAAqB,MAAM,qBAAqB,CAAC;AAW7E,MAAM,UAAU,mBAAmB,CAAC,GAAQ;IAC1C,OAAO,mBAAmB,CAAC,GAAG,CAAC;WAC1B,GAAG,CAAC,WAAW,CAAC,YAAY,aAAa;WACzC,GAAG,CAAC,oBAAoB,CAAC,YAAY,aAAa;WAClD,GAAG,CAAC,aAAa,CAAC,YAAY,aAAa,CAAA;AAClD,CAAC;AAED,MAAM,UAAU,uBAAuB,CAIrC,SAAkB,EAClB,kBAAkC;IAG1B,IAAA,+BAAU,CAAwB;IAC1C,IAAM,SAAS,GAAG,kBAAkB,CAAC,OAAO,CAAiB,KAAK,CAAC,CAAC,EAAE,KAAK,CAAC,CAAC,CAAC,CAAA;IAE9E,IAAM,IAAI,GAAG,SAAS,CAAC,KAAK,EAAE,CAAA;IACtB,IAAA,yCAAS,CAAwB;IACzC,IAAM,WAAW,GAAG,IAAI,aAAa,CAAC,SAAS,CAAC,SAAS,CAAC,KAAK,EAAE,IAAI,CAAC,OAAO,CAAC,SAAS,CAAC,OAAO,EAAE,CAAC,EAAE,SAAS,CAAC,CAAA;IAE9G,IAAM,SAAS,GAAG;QAChB,SAAS,WAAA;QACT,kBAAkB,oBAAA;QAClB,WAAW,aAAA;KACZ,CAAA;IAED,OAAO,MAAM,CAAC,MAAM,CAAC,EAAE,EAAE,SAAS,EAAE,SAAS,CAAC,CAAA;AAChD,CAAC"}
\ No newline at end of file

build/es6/factories/WithGender.d.ts

+import { Gender } from '../ageGenderNet/types';
+export declare type WithGender<TSource> = TSource & {
+    gender: Gender;
+    genderProbability: number;
+};
+export declare function isWithGender(obj: any): obj is WithGender<{}>;
+export declare function extendWithGender<TSource>(sourceObj: TSource, gender: Gender, genderProbability: number): WithGender<TSource>;

build/es6/factories/WithGender.js

+import { isValidProbablitiy } from 'tfjs-image-recognition-base';
+import { Gender } from '../ageGenderNet/types';
+export function isWithGender(obj) {
+    return (obj['gender'] === Gender.MALE || obj['gender'] === Gender.FEMALE)
+        && isValidProbablitiy(obj['genderProbability']);
+}
+export function extendWithGender(sourceObj, gender, genderProbability) {
+    var extension = { gender: gender, genderProbability: genderProbability };
+    return Object.assign({}, sourceObj, extension);
+}
+//# sourceMappingURL=WithGender.js.map
\ No newline at end of file

build/es6/factories/WithGender.js.map

+{"version":3,"file":"WithGender.js","sourceRoot":"","sources":["../../../src/factories/WithGender.ts"],"names":[],"mappings":"AAAA,OAAO,EAAE,kBAAkB,EAAE,MAAM,6BAA6B,CAAC;AAEjE,OAAO,EAAE,MAAM,EAAE,MAAM,uBAAuB,CAAC;AAO/C,MAAM,UAAU,YAAY,CAAC,GAAQ;IACnC,OAAO,CAAC,GAAG,CAAC,QAAQ,CAAC,KAAK,MAAM,CAAC,IAAI,IAAI,GAAG,CAAC,QAAQ,CAAC,KAAK,MAAM,CAAC,MAAM,CAAC;WACpE,kBAAkB,CAAC,GAAG,CAAC,mBAAmB,CAAC,CAAC,CAAA;AACnD,CAAC;AAED,MAAM,UAAU,gBAAgB,CAG9B,SAAkB,EAClB,MAAc,EACd,iBAAyB;IAGzB,IAAM,SAAS,GAAG,EAAE,MAAM,QAAA,EAAE,iBAAiB,mBAAA,EAAE,CAAA;IAC/C,OAAO,MAAM,CAAC,MAAM,CAAC,EAAE,EAAE,SAAS,EAAE,SAAS,CAAC,CAAA;AAChD,CAAC"}
\ No newline at end of file

build/es6/globalApi/ComputeFaceDescriptorsTasks.d.ts

@@ -3,6 +3,8 @@ import { WithFaceDescriptor } from '../factories/WithFaceDescriptor';
 import { WithFaceDetection } from '../factories/WithFaceDetection';
 import { WithFaceLandmarks } from '../factories/WithFaceLandmarks';
 import { ComposableTask } from './ComposableTask';
+import { PredictAllAgeAndGenderWithFaceAlignmentTask, PredictSingleAgeAndGenderWithFaceAlignmentTask } from './PredictAgeAndGenderTask';
+import { PredictAllFaceExpressionsWithFaceAlignmentTask, PredictSingleFaceExpressionsWithFaceAlignmentTask } from './PredictFaceExpressionsTask';
 export declare class ComputeFaceDescriptorsTaskBase<TReturn, TParentReturn> extends ComposableTask<TReturn> {
     protected parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>;
     protected input: TNetInput;
@@ -10,7 +12,11 @@ export declare class ComputeFaceDescriptorsTaskBase<TReturn, TParentReturn> exte
 }
 export declare class ComputeAllFaceDescriptorsTask<TSource extends WithFaceLandmarks<WithFaceDetection<{}>>> extends ComputeFaceDescriptorsTaskBase<WithFaceDescriptor<TSource>[], TSource[]> {
     run(): Promise<WithFaceDescriptor<TSource>[]>;
+    withFaceExpressions(): PredictAllFaceExpressionsWithFaceAlignmentTask<WithFaceDescriptor<TSource>>;
+    withAgeAndGender(): PredictAllAgeAndGenderWithFaceAlignmentTask<WithFaceDescriptor<TSource>>;
 }
 export declare class ComputeSingleFaceDescriptorTask<TSource extends WithFaceLandmarks<WithFaceDetection<{}>>> extends ComputeFaceDescriptorsTaskBase<WithFaceDescriptor<TSource> | undefined, TSource | undefined> {
     run(): Promise<WithFaceDescriptor<TSource> | undefined>;
+    withFaceExpressions(): PredictSingleFaceExpressionsWithFaceAlignmentTask<WithFaceDescriptor<TSource>>;
+    withAgeAndGender(): PredictSingleAgeAndGenderWithFaceAlignmentTask<WithFaceDescriptor<TSource>>;
 }

build/es6/globalApi/ComputeFaceDescriptorsTasks.js

 import * as tslib_1 from "tslib";
-import * as tf from '@tensorflow/tfjs-core';
-import { extractFaces, extractFaceTensors } from '../dom';
 import { extendWithFaceDescriptor } from '../factories/WithFaceDescriptor';
 import { ComposableTask } from './ComposableTask';
+import { extractAllFacesAndComputeResults, extractSingleFaceAndComputeResult } from './extractFacesAndComputeResults';
 import { nets } from './nets';
+import { PredictAllAgeAndGenderWithFaceAlignmentTask, PredictSingleAgeAndGenderWithFaceAlignmentTask, } from './PredictAgeAndGenderTask';
+import { PredictAllFaceExpressionsWithFaceAlignmentTask, PredictSingleFaceExpressionsWithFaceAlignmentTask, } from './PredictFaceExpressionsTask';
 var ComputeFaceDescriptorsTaskBase = /** @class */ (function (_super) {
     tslib_1.__extends(ComputeFaceDescriptorsTaskBase, _super);
     function ComputeFaceDescriptorsTaskBase(parentTask, input) {
@@ -22,47 +23,28 @@ var ComputeAllFaceDescriptorsTask = /** @class */ (function (_super) {
     }
     ComputeAllFaceDescriptorsTask.prototype.run = function () {
         return tslib_1.__awaiter(this, void 0, void 0, function () {
-            var parentResults, alignedRects, alignedFaces, _a, results;
-            var _this = this;
-            return tslib_1.__generator(this, function (_b) {
-                switch (_b.label) {
+            var parentResults, descriptors;
+            return tslib_1.__generator(this, function (_a) {
+                switch (_a.label) {
                     case 0: return [4 /*yield*/, this.parentTask];
                     case 1:
-                        parentResults = _b.sent();
-                        alignedRects = parentResults.map(function (_a) {
-                            var alignedRect = _a.alignedRect;
-                            return alignedRect;
-                        });
-                        if (!(this.input instanceof tf.Tensor)) return [3 /*break*/, 3];
-                        return [4 /*yield*/, extractFaceTensors(this.input, alignedRects)];
+                        parentResults = _a.sent();
+                        return [4 /*yield*/, extractAllFacesAndComputeResults(parentResults, this.input, function (faces) { return Promise.all(faces.map(function (face) {
+                                return nets.faceRecognitionNet.computeFaceDescriptor(face);
+                            })); }, null, function (parentResult) { return parentResult.landmarks.align(null, { useDlibAlignment: true }); })];
                     case 2:
-                        _a = _b.sent();
-                        return [3 /*break*/, 5];
-                    case 3: return [4 /*yield*/, extractFaces(this.input, alignedRects)];
-                    case 4:
-                        _a = _b.sent();
-                        _b.label = 5;
-                    case 5:
-                        alignedFaces = _a;
-                        return [4 /*yield*/, Promise.all(parentResults.map(function (parentResult, i) { return tslib_1.__awaiter(_this, void 0, void 0, function () {
-                                var descriptor;
-                                return tslib_1.__generator(this, function (_a) {
-                                    switch (_a.label) {
-                                        case 0: return [4 /*yield*/, nets.faceRecognitionNet.computeFaceDescriptor(alignedFaces[i])];
-                                        case 1:
-                                            descriptor = _a.sent();
-                                            return [2 /*return*/, extendWithFaceDescriptor(parentResult, descriptor)];
-                                    }
-                                });
-                            }); }))];
-                    case 6:
-                        results = _b.sent();
-                        alignedFaces.forEach(function (f) { return f instanceof tf.Tensor && f.dispose(); });
-                        return [2 /*return*/, results];
+                        descriptors = _a.sent();
+                        return [2 /*return*/, descriptors.map(function (descriptor, i) { return extendWithFaceDescriptor(parentResults[i], descriptor); })];
                 }
             });
         });
     };
+    ComputeAllFaceDescriptorsTask.prototype.withFaceExpressions = function () {
+        return new PredictAllFaceExpressionsWithFaceAlignmentTask(this, this.input);
+    };
+    ComputeAllFaceDescriptorsTask.prototype.withAgeAndGender = function () {
+        return new PredictAllAgeAndGenderWithFaceAlignmentTask(this, this.input);
+    };
     return ComputeAllFaceDescriptorsTask;
 }(ComputeFaceDescriptorsTaskBase));
 export { ComputeAllFaceDescriptorsTask };
@@ -73,36 +55,29 @@ var ComputeSingleFaceDescriptorTask = /** @class */ (function (_super) {
     }
     ComputeSingleFaceDescriptorTask.prototype.run = function () {
         return tslib_1.__awaiter(this, void 0, void 0, function () {
-            var parentResult, alignedRect, alignedFaces, _a, descriptor;
-            return tslib_1.__generator(this, function (_b) {
-                switch (_b.label) {
+            var parentResult, descriptor;
+            return tslib_1.__generator(this, function (_a) {
+                switch (_a.label) {
                     case 0: return [4 /*yield*/, this.parentTask];
                     case 1:
-                        parentResult = _b.sent();
+                        parentResult = _a.sent();
                         if (!parentResult) {
                             return [2 /*return*/];
                         }
-                        alignedRect = parentResult.alignedRect;
-                        if (!(this.input instanceof tf.Tensor)) return [3 /*break*/, 3];
-                        return [4 /*yield*/, extractFaceTensors(this.input, [alignedRect])];
+                        return [4 /*yield*/, extractSingleFaceAndComputeResult(parentResult, this.input, function (face) { return nets.faceRecognitionNet.computeFaceDescriptor(face); }, null, function (parentResult) { return parentResult.landmarks.align(null, { useDlibAlignment: true }); })];
                     case 2:
-                        _a = _b.sent();
-                        return [3 /*break*/, 5];
-                    case 3: return [4 /*yield*/, extractFaces(this.input, [alignedRect])];
-                    case 4:
-                        _a = _b.sent();
-                        _b.label = 5;
-                    case 5:
-                        alignedFaces = _a;
-                        return [4 /*yield*/, nets.faceRecognitionNet.computeFaceDescriptor(alignedFaces[0])];
-                    case 6:
-                        descriptor = _b.sent();
-                        alignedFaces.forEach(function (f) { return f instanceof tf.Tensor && f.dispose(); });
+                        descriptor = _a.sent();
                         return [2 /*return*/, extendWithFaceDescriptor(parentResult, descriptor)];
                 }
             });
         });
     };
+    ComputeSingleFaceDescriptorTask.prototype.withFaceExpressions = function () {
+        return new PredictSingleFaceExpressionsWithFaceAlignmentTask(this, this.input);
+    };
+    ComputeSingleFaceDescriptorTask.prototype.withAgeAndGender = function () {
+        return new PredictSingleAgeAndGenderWithFaceAlignmentTask(this, this.input);
+    };
     return ComputeSingleFaceDescriptorTask;
 }(ComputeFaceDescriptorsTaskBase));
 export { ComputeSingleFaceDescriptorTask };

build/es6/globalApi/ComputeFaceDescriptorsTasks.js.map

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\ No newline at end of file

build/es6/globalApi/DetectFaceLandmarksTasks.d.ts

 import { TNetInput } from 'tfjs-image-recognition-base';
+import { FaceLandmarks68 } from '../classes/FaceLandmarks68';
 import { FaceLandmark68Net } from '../faceLandmarkNet/FaceLandmark68Net';
 import { FaceLandmark68TinyNet } from '../faceLandmarkNet/FaceLandmark68TinyNet';
 import { WithFaceDetection } from '../factories/WithFaceDetection';
 import { WithFaceLandmarks } from '../factories/WithFaceLandmarks';
 import { ComposableTask } from './ComposableTask';
 import { ComputeAllFaceDescriptorsTask, ComputeSingleFaceDescriptorTask } from './ComputeFaceDescriptorsTasks';
+import { PredictAllAgeAndGenderWithFaceAlignmentTask, PredictSingleAgeAndGenderWithFaceAlignmentTask } from './PredictAgeAndGenderTask';
+import { PredictAllFaceExpressionsWithFaceAlignmentTask, PredictSingleFaceExpressionsWithFaceAlignmentTask } from './PredictFaceExpressionsTask';
 export declare class DetectFaceLandmarksTaskBase<TReturn, TParentReturn> extends ComposableTask<TReturn> {
     protected parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>;
     protected input: TNetInput;
@@ -14,9 +17,13 @@ export declare class DetectFaceLandmarksTaskBase<TReturn, TParentReturn> extends
 }
 export declare class DetectAllFaceLandmarksTask<TSource extends WithFaceDetection<{}>> extends DetectFaceLandmarksTaskBase<WithFaceLandmarks<TSource>[], TSource[]> {
     run(): Promise<WithFaceLandmarks<TSource>[]>;
-    withFaceDescriptors(): ComputeAllFaceDescriptorsTask<WithFaceLandmarks<TSource>>;
+    withFaceExpressions(): PredictAllFaceExpressionsWithFaceAlignmentTask<WithFaceLandmarks<TSource, FaceLandmarks68>>;
+    withAgeAndGender(): PredictAllAgeAndGenderWithFaceAlignmentTask<WithFaceLandmarks<TSource, FaceLandmarks68>>;
+    withFaceDescriptors(): ComputeAllFaceDescriptorsTask<WithFaceLandmarks<TSource, FaceLandmarks68>>;
 }
 export declare class DetectSingleFaceLandmarksTask<TSource extends WithFaceDetection<{}>> extends DetectFaceLandmarksTaskBase<WithFaceLandmarks<TSource> | undefined, TSource | undefined> {
     run(): Promise<WithFaceLandmarks<TSource> | undefined>;
-    withFaceDescriptor(): ComputeSingleFaceDescriptorTask<WithFaceLandmarks<TSource>>;
+    withFaceExpressions(): PredictSingleFaceExpressionsWithFaceAlignmentTask<WithFaceLandmarks<TSource, FaceLandmarks68>>;
+    withAgeAndGender(): PredictSingleAgeAndGenderWithFaceAlignmentTask<WithFaceLandmarks<TSource, FaceLandmarks68>>;
+    withFaceDescriptor(): ComputeSingleFaceDescriptorTask<WithFaceLandmarks<TSource, FaceLandmarks68>>;
 }

build/es6/globalApi/DetectFaceLandmarksTasks.js

@@ -5,6 +5,8 @@ import { extendWithFaceLandmarks } from '../factories/WithFaceLandmarks';
 import { ComposableTask } from './ComposableTask';
 import { ComputeAllFaceDescriptorsTask, ComputeSingleFaceDescriptorTask } from './ComputeFaceDescriptorsTasks';
 import { nets } from './nets';
+import { PredictAllAgeAndGenderWithFaceAlignmentTask, PredictSingleAgeAndGenderWithFaceAlignmentTask, } from './PredictAgeAndGenderTask';
+import { PredictAllFaceExpressionsWithFaceAlignmentTask, PredictSingleFaceExpressionsWithFaceAlignmentTask, } from './PredictFaceExpressionsTask';
 var DetectFaceLandmarksTaskBase = /** @class */ (function (_super) {
     tslib_1.__extends(DetectFaceLandmarksTaskBase, _super);
     function DetectFaceLandmarksTaskBase(parentTask, input, useTinyLandmarkNet) {
@@ -63,6 +65,12 @@ var DetectAllFaceLandmarksTask = /** @class */ (function (_super) {
             });
         });
     };
+    DetectAllFaceLandmarksTask.prototype.withFaceExpressions = function () {
+        return new PredictAllFaceExpressionsWithFaceAlignmentTask(this, this.input);
+    };
+    DetectAllFaceLandmarksTask.prototype.withAgeAndGender = function () {
+        return new PredictAllAgeAndGenderWithFaceAlignmentTask(this, this.input);
+    };
     DetectAllFaceLandmarksTask.prototype.withFaceDescriptors = function () {
         return new ComputeAllFaceDescriptorsTask(this, this.input);
     };
@@ -106,6 +114,12 @@ var DetectSingleFaceLandmarksTask = /** @class */ (function (_super) {
             });
         });
     };
+    DetectSingleFaceLandmarksTask.prototype.withFaceExpressions = function () {
+        return new PredictSingleFaceExpressionsWithFaceAlignmentTask(this, this.input);
+    };
+    DetectSingleFaceLandmarksTask.prototype.withAgeAndGender = function () {
+        return new PredictSingleAgeAndGenderWithFaceAlignmentTask(this, this.input);
+    };
     DetectSingleFaceLandmarksTask.prototype.withFaceDescriptor = function () {
         return new ComputeSingleFaceDescriptorTask(this, this.input);
     };

build/es6/globalApi/DetectFaceLandmarksTasks.js.map

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\ No newline at end of file

build/es6/globalApi/DetectFacesTasks.d.ts

 import { TNetInput } from 'tfjs-image-recognition-base';
 import { FaceDetection } from '../classes/FaceDetection';
-import { WithFaceDetection } from '../factories/WithFaceDetection';
 import { ComposableTask } from './ComposableTask';
 import { DetectAllFaceLandmarksTask, DetectSingleFaceLandmarksTask } from './DetectFaceLandmarksTasks';
-import { PredictAllFaceExpressionsTask, PredictSingleFaceExpressionTask } from './PredictFaceExpressionsTask';
+import { PredictAllAgeAndGenderTask, PredictSingleAgeAndGenderTask } from './PredictAgeAndGenderTask';
+import { PredictAllFaceExpressionsTask, PredictSingleFaceExpressionsTask } from './PredictFaceExpressionsTask';
 import { FaceDetectionOptions } from './types';
 export declare class DetectFacesTaskBase<TReturn> extends ComposableTask<TReturn> {
     protected input: TNetInput;
@@ -13,12 +13,26 @@ export declare class DetectFacesTaskBase<TReturn> extends ComposableTask<TReturn
 export declare class DetectAllFacesTask extends DetectFacesTaskBase<FaceDetection[]> {
     run(): Promise<FaceDetection[]>;
     private runAndExtendWithFaceDetections;
-    withFaceLandmarks(useTinyLandmarkNet?: boolean): DetectAllFaceLandmarksTask<WithFaceDetection<{}>>;
-    withFaceExpressions(): PredictAllFaceExpressionsTask<WithFaceDetection<{}>>;
+    withFaceLandmarks(useTinyLandmarkNet?: boolean): DetectAllFaceLandmarksTask<{
+        detection: FaceDetection;
+    }>;
+    withFaceExpressions(): PredictAllFaceExpressionsTask<{
+        detection: FaceDetection;
+    }>;
+    withAgeAndGender(): PredictAllAgeAndGenderTask<{
+        detection: FaceDetection;
+    }>;
 }
 export declare class DetectSingleFaceTask extends DetectFacesTaskBase<FaceDetection | undefined> {
     run(): Promise<FaceDetection | undefined>;
     private runAndExtendWithFaceDetection;
-    withFaceLandmarks(useTinyLandmarkNet?: boolean): DetectSingleFaceLandmarksTask<WithFaceDetection<{}>>;
-    withFaceExpressions(): PredictSingleFaceExpressionTask<WithFaceDetection<{}>>;
+    withFaceLandmarks(useTinyLandmarkNet?: boolean): DetectSingleFaceLandmarksTask<{
+        detection: FaceDetection;
+    }>;
+    withFaceExpressions(): PredictSingleFaceExpressionsTask<{
+        detection: FaceDetection;
+    }>;
+    withAgeAndGender(): PredictSingleAgeAndGenderTask<{
+        detection: FaceDetection;
+    }>;
 }

build/es6/globalApi/DetectFacesTasks.js

@@ -7,7 +7,8 @@ import { TinyFaceDetectorOptions } from '../tinyFaceDetector/TinyFaceDetectorOpt
 import { ComposableTask } from './ComposableTask';
 import { DetectAllFaceLandmarksTask, DetectSingleFaceLandmarksTask } from './DetectFaceLandmarksTasks';
 import { nets } from './nets';
-import { PredictAllFaceExpressionsTask, PredictSingleFaceExpressionTask } from './PredictFaceExpressionsTask';
+import { PredictAllAgeAndGenderTask, PredictSingleAgeAndGenderTask } from './PredictAgeAndGenderTask';
+import { PredictAllFaceExpressionsTask, PredictSingleFaceExpressionsTask } from './PredictFaceExpressionsTask';
 var DetectFacesTaskBase = /** @class */ (function (_super) {
     tslib_1.__extends(DetectFacesTaskBase, _super);
     function DetectFacesTaskBase(input, options) {
@@ -73,6 +74,9 @@ var DetectAllFacesTask = /** @class */ (function (_super) {
     DetectAllFacesTask.prototype.withFaceExpressions = function () {
         return new PredictAllFaceExpressionsTask(this.runAndExtendWithFaceDetections(), this.input);
     };
+    DetectAllFacesTask.prototype.withAgeAndGender = function () {
+        return new PredictAllAgeAndGenderTask(this.runAndExtendWithFaceDetections(), this.input);
+    };
     return DetectAllFacesTask;
 }(DetectFacesTaskBase));
 export { DetectAllFacesTask };
@@ -119,7 +123,10 @@ var DetectSingleFaceTask = /** @class */ (function (_super) {
         return new DetectSingleFaceLandmarksTask(this.runAndExtendWithFaceDetection(), this.input, useTinyLandmarkNet);
     };
     DetectSingleFaceTask.prototype.withFaceExpressions = function () {
-        return new PredictSingleFaceExpressionTask(this.runAndExtendWithFaceDetection(), this.input);
+        return new PredictSingleFaceExpressionsTask(this.runAndExtendWithFaceDetection(), this.input);
+    };
+    DetectSingleFaceTask.prototype.withAgeAndGender = function () {
+        return new PredictSingleAgeAndGenderTask(this.runAndExtendWithFaceDetection(), this.input);
     };
     return DetectSingleFaceTask;
 }(DetectFacesTaskBase));

build/es6/globalApi/DetectFacesTasks.js.map

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build/es6/globalApi/PredictAgeAndGenderTask.d.ts

+import * as tf from '@tensorflow/tfjs-core';
+import { TNetInput } from 'tfjs-image-recognition-base';
+import { WithAge } from '../factories/WithAge';
+import { WithFaceDetection } from '../factories/WithFaceDetection';
+import { WithFaceLandmarks } from '../factories/WithFaceLandmarks';
+import { WithGender } from '../factories/WithGender';
+import { ComposableTask } from './ComposableTask';
+import { ComputeAllFaceDescriptorsTask, ComputeSingleFaceDescriptorTask } from './ComputeFaceDescriptorsTasks';
+import { PredictAllFaceExpressionsTask, PredictAllFaceExpressionsWithFaceAlignmentTask, PredictSingleFaceExpressionsTask, PredictSingleFaceExpressionsWithFaceAlignmentTask } from './PredictFaceExpressionsTask';
+export declare class PredictAgeAndGenderTaskBase<TReturn, TParentReturn> extends ComposableTask<TReturn> {
+    protected parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>;
+    protected input: TNetInput;
+    protected extractedFaces?: (HTMLCanvasElement | tf.Tensor<tf.Rank.R3>)[] | undefined;
+    constructor(parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>, input: TNetInput, extractedFaces?: (HTMLCanvasElement | tf.Tensor<tf.Rank.R3>)[] | undefined);
+}
+export declare class PredictAllAgeAndGenderTask<TSource extends WithFaceDetection<{}>> extends PredictAgeAndGenderTaskBase<WithAge<WithGender<TSource>>[], TSource[]> {
+    run(): Promise<WithAge<WithGender<TSource>>[]>;
+    withFaceExpressions(): PredictAllFaceExpressionsTask<WithAge<WithGender<TSource>>>;
+}
+export declare class PredictSingleAgeAndGenderTask<TSource extends WithFaceDetection<{}>> extends PredictAgeAndGenderTaskBase<WithAge<WithGender<TSource>> | undefined, TSource | undefined> {
+    run(): Promise<WithAge<WithGender<TSource>> | undefined>;
+    withFaceExpressions(): PredictSingleFaceExpressionsTask<WithAge<WithGender<TSource>>>;
+}
+export declare class PredictAllAgeAndGenderWithFaceAlignmentTask<TSource extends WithFaceLandmarks<WithFaceDetection<{}>>> extends PredictAllAgeAndGenderTask<TSource> {
+    withFaceExpressions(): PredictAllFaceExpressionsWithFaceAlignmentTask<WithAge<WithGender<TSource>>>;
+    withFaceDescriptors(): ComputeAllFaceDescriptorsTask<WithAge<WithGender<TSource>>>;
+}
+export declare class PredictSingleAgeAndGenderWithFaceAlignmentTask<TSource extends WithFaceLandmarks<WithFaceDetection<{}>>> extends PredictSingleAgeAndGenderTask<TSource> {
+    withFaceExpressions(): PredictSingleFaceExpressionsWithFaceAlignmentTask<WithAge<WithGender<TSource>>>;
+    withFaceDescriptor(): ComputeSingleFaceDescriptorTask<WithAge<WithGender<TSource>>>;
+}

build/es6/globalApi/PredictAgeAndGenderTask.js

+import * as tslib_1 from "tslib";
+import { extendWithAge } from '../factories/WithAge';
+import { extendWithGender } from '../factories/WithGender';
+import { ComposableTask } from './ComposableTask';
+import { ComputeAllFaceDescriptorsTask, ComputeSingleFaceDescriptorTask } from './ComputeFaceDescriptorsTasks';
+import { extractAllFacesAndComputeResults, extractSingleFaceAndComputeResult } from './extractFacesAndComputeResults';
+import { nets } from './nets';
+import { PredictAllFaceExpressionsTask, PredictAllFaceExpressionsWithFaceAlignmentTask, PredictSingleFaceExpressionsTask, PredictSingleFaceExpressionsWithFaceAlignmentTask, } from './PredictFaceExpressionsTask';
+var PredictAgeAndGenderTaskBase = /** @class */ (function (_super) {
+    tslib_1.__extends(PredictAgeAndGenderTaskBase, _super);
+    function PredictAgeAndGenderTaskBase(parentTask, input, extractedFaces) {
+        var _this = _super.call(this) || this;
+        _this.parentTask = parentTask;
+        _this.input = input;
+        _this.extractedFaces = extractedFaces;
+        return _this;
+    }
+    return PredictAgeAndGenderTaskBase;
+}(ComposableTask));
+export { PredictAgeAndGenderTaskBase };
+var PredictAllAgeAndGenderTask = /** @class */ (function (_super) {
+    tslib_1.__extends(PredictAllAgeAndGenderTask, _super);
+    function PredictAllAgeAndGenderTask() {
+        return _super !== null && _super.apply(this, arguments) || this;
+    }
+    PredictAllAgeAndGenderTask.prototype.run = function () {
+        return tslib_1.__awaiter(this, void 0, void 0, function () {
+            var parentResults, ageAndGenderByFace;
+            var _this = this;
+            return tslib_1.__generator(this, function (_a) {
+                switch (_a.label) {
+                    case 0: return [4 /*yield*/, this.parentTask];
+                    case 1:
+                        parentResults = _a.sent();
+                        return [4 /*yield*/, extractAllFacesAndComputeResults(parentResults, this.input, function (faces) { return tslib_1.__awaiter(_this, void 0, void 0, function () {
+                                return tslib_1.__generator(this, function (_a) {
+                                    switch (_a.label) {
+                                        case 0: return [4 /*yield*/, Promise.all(faces.map(function (face) { return nets.ageGenderNet.predictAgeAndGender(face); }))];
+                                        case 1: return [2 /*return*/, _a.sent()];
+                                    }
+                                });
+                            }); }, this.extractedFaces)];
+                    case 2:
+                        ageAndGenderByFace = _a.sent();
+                        return [2 /*return*/, parentResults.map(function (parentResult, i) {
+                                var _a = ageAndGenderByFace[i], age = _a.age, gender = _a.gender, genderProbability = _a.genderProbability;
+                                return extendWithAge(extendWithGender(parentResult, gender, genderProbability), age);
+                            })];
+                }
+            });
+        });
+    };
+    PredictAllAgeAndGenderTask.prototype.withFaceExpressions = function () {
+        return new PredictAllFaceExpressionsTask(this, this.input);
+    };
+    return PredictAllAgeAndGenderTask;
+}(PredictAgeAndGenderTaskBase));
+export { PredictAllAgeAndGenderTask };
+var PredictSingleAgeAndGenderTask = /** @class */ (function (_super) {
+    tslib_1.__extends(PredictSingleAgeAndGenderTask, _super);
+    function PredictSingleAgeAndGenderTask() {
+        return _super !== null && _super.apply(this, arguments) || this;
+    }
+    PredictSingleAgeAndGenderTask.prototype.run = function () {
+        return tslib_1.__awaiter(this, void 0, void 0, function () {
+            var parentResult, _a, age, gender, genderProbability;
+            return tslib_1.__generator(this, function (_b) {
+                switch (_b.label) {
+                    case 0: return [4 /*yield*/, this.parentTask];
+                    case 1:
+                        parentResult = _b.sent();
+                        if (!parentResult) {
+                            return [2 /*return*/];
+                        }
+                        return [4 /*yield*/, extractSingleFaceAndComputeResult(parentResult, this.input, function (face) { return nets.ageGenderNet.predictAgeAndGender(face); }, this.extractedFaces)];
+                    case 2:
+                        _a = _b.sent(), age = _a.age, gender = _a.gender, genderProbability = _a.genderProbability;
+                        return [2 /*return*/, extendWithAge(extendWithGender(parentResult, gender, genderProbability), age)];
+                }
+            });
+        });
+    };
+    PredictSingleAgeAndGenderTask.prototype.withFaceExpressions = function () {
+        return new PredictSingleFaceExpressionsTask(this, this.input);
+    };
+    return PredictSingleAgeAndGenderTask;
+}(PredictAgeAndGenderTaskBase));
+export { PredictSingleAgeAndGenderTask };
+var PredictAllAgeAndGenderWithFaceAlignmentTask = /** @class */ (function (_super) {
+    tslib_1.__extends(PredictAllAgeAndGenderWithFaceAlignmentTask, _super);
+    function PredictAllAgeAndGenderWithFaceAlignmentTask() {
+        return _super !== null && _super.apply(this, arguments) || this;
+    }
+    PredictAllAgeAndGenderWithFaceAlignmentTask.prototype.withFaceExpressions = function () {
+        return new PredictAllFaceExpressionsWithFaceAlignmentTask(this, this.input);
+    };
+    PredictAllAgeAndGenderWithFaceAlignmentTask.prototype.withFaceDescriptors = function () {
+        return new ComputeAllFaceDescriptorsTask(this, this.input);
+    };
+    return PredictAllAgeAndGenderWithFaceAlignmentTask;
+}(PredictAllAgeAndGenderTask));
+export { PredictAllAgeAndGenderWithFaceAlignmentTask };
+var PredictSingleAgeAndGenderWithFaceAlignmentTask = /** @class */ (function (_super) {
+    tslib_1.__extends(PredictSingleAgeAndGenderWithFaceAlignmentTask, _super);
+    function PredictSingleAgeAndGenderWithFaceAlignmentTask() {
+        return _super !== null && _super.apply(this, arguments) || this;
+    }
+    PredictSingleAgeAndGenderWithFaceAlignmentTask.prototype.withFaceExpressions = function () {
+        return new PredictSingleFaceExpressionsWithFaceAlignmentTask(this, this.input);
+    };
+    PredictSingleAgeAndGenderWithFaceAlignmentTask.prototype.withFaceDescriptor = function () {
+        return new ComputeSingleFaceDescriptorTask(this, this.input);
+    };
+    return PredictSingleAgeAndGenderWithFaceAlignmentTask;
+}(PredictSingleAgeAndGenderTask));
+export { PredictSingleAgeAndGenderWithFaceAlignmentTask };
+//# sourceMappingURL=PredictAgeAndGenderTask.js.map
\ No newline at end of file

build/es6/globalApi/PredictAgeAndGenderTask.js.map

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build/es6/globalApi/PredictFaceExpressionsTask.d.ts

+import * as tf from '@tensorflow/tfjs-core';
 import { TNetInput } from 'tfjs-image-recognition-base';
 import { WithFaceDetection } from '../factories/WithFaceDetection';
 import { WithFaceExpressions } from '../factories/WithFaceExpressions';
+import { WithFaceLandmarks } from '../factories/WithFaceLandmarks';
 import { ComposableTask } from './ComposableTask';
-import { DetectAllFaceLandmarksTask, DetectSingleFaceLandmarksTask } from './DetectFaceLandmarksTasks';
+import { ComputeAllFaceDescriptorsTask, ComputeSingleFaceDescriptorTask } from './ComputeFaceDescriptorsTasks';
+import { PredictAllAgeAndGenderTask, PredictAllAgeAndGenderWithFaceAlignmentTask, PredictSingleAgeAndGenderTask, PredictSingleAgeAndGenderWithFaceAlignmentTask } from './PredictAgeAndGenderTask';
 export declare class PredictFaceExpressionsTaskBase<TReturn, TParentReturn> extends ComposableTask<TReturn> {
     protected parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>;
     protected input: TNetInput;
-    constructor(parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>, input: TNetInput);
+    protected extractedFaces?: (HTMLCanvasElement | tf.Tensor<tf.Rank.R3>)[] | undefined;
+    constructor(parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>, input: TNetInput, extractedFaces?: (HTMLCanvasElement | tf.Tensor<tf.Rank.R3>)[] | undefined);
 }
 export declare class PredictAllFaceExpressionsTask<TSource extends WithFaceDetection<{}>> extends PredictFaceExpressionsTaskBase<WithFaceExpressions<TSource>[], TSource[]> {
     run(): Promise<WithFaceExpressions<TSource>[]>;
-    withFaceLandmarks(): DetectAllFaceLandmarksTask<WithFaceExpressions<TSource>>;
+    withAgeAndGender(): PredictAllAgeAndGenderTask<WithFaceExpressions<TSource>>;
 }
-export declare class PredictSingleFaceExpressionTask<TSource extends WithFaceDetection<{}>> extends PredictFaceExpressionsTaskBase<WithFaceExpressions<TSource> | undefined, TSource | undefined> {
+export declare class PredictSingleFaceExpressionsTask<TSource extends WithFaceDetection<{}>> extends PredictFaceExpressionsTaskBase<WithFaceExpressions<TSource> | undefined, TSource | undefined> {
     run(): Promise<WithFaceExpressions<TSource> | undefined>;
-    withFaceLandmarks(): DetectSingleFaceLandmarksTask<WithFaceExpressions<TSource>>;
+    withAgeAndGender(): PredictSingleAgeAndGenderTask<WithFaceExpressions<TSource>>;
+}
+export declare class PredictAllFaceExpressionsWithFaceAlignmentTask<TSource extends WithFaceLandmarks<WithFaceDetection<{}>>> extends PredictAllFaceExpressionsTask<TSource> {
+    withAgeAndGender(): PredictAllAgeAndGenderWithFaceAlignmentTask<WithFaceExpressions<TSource>>;
+    withFaceDescriptors(): ComputeAllFaceDescriptorsTask<WithFaceExpressions<TSource>>;
+}
+export declare class PredictSingleFaceExpressionsWithFaceAlignmentTask<TSource extends WithFaceLandmarks<WithFaceDetection<{}>>> extends PredictSingleFaceExpressionsTask<TSource> {
+    withAgeAndGender(): PredictSingleAgeAndGenderWithFaceAlignmentTask<WithFaceExpressions<TSource>>;
+    withFaceDescriptor(): ComputeSingleFaceDescriptorTask<WithFaceExpressions<TSource>>;
 }

build/es6/globalApi/PredictFaceExpressionsTask.js

 import * as tslib_1 from "tslib";
-import * as tf from '@tensorflow/tfjs-core';
-import { extractFaces, extractFaceTensors } from '../dom';
 import { extendWithFaceExpressions } from '../factories/WithFaceExpressions';
 import { ComposableTask } from './ComposableTask';
-import { DetectAllFaceLandmarksTask, DetectSingleFaceLandmarksTask } from './DetectFaceLandmarksTasks';
+import { ComputeAllFaceDescriptorsTask, ComputeSingleFaceDescriptorTask } from './ComputeFaceDescriptorsTasks';
+import { extractAllFacesAndComputeResults, extractSingleFaceAndComputeResult } from './extractFacesAndComputeResults';
 import { nets } from './nets';
+import { PredictAllAgeAndGenderTask, PredictAllAgeAndGenderWithFaceAlignmentTask, PredictSingleAgeAndGenderTask, PredictSingleAgeAndGenderWithFaceAlignmentTask, } from './PredictAgeAndGenderTask';
 var PredictFaceExpressionsTaskBase = /** @class */ (function (_super) {
     tslib_1.__extends(PredictFaceExpressionsTaskBase, _super);
-    function PredictFaceExpressionsTaskBase(parentTask, input) {
+    function PredictFaceExpressionsTaskBase(parentTask, input, extractedFaces) {
         var _this = _super.call(this) || this;
         _this.parentTask = parentTask;
         _this.input = input;
+        _this.extractedFaces = extractedFaces;
         return _this;
     }
     return PredictFaceExpressionsTaskBase;
@@ -23,80 +24,90 @@ var PredictAllFaceExpressionsTask = /** @class */ (function (_super) {
     }
     PredictAllFaceExpressionsTask.prototype.run = function () {
         return tslib_1.__awaiter(this, void 0, void 0, function () {
-            var parentResults, detections, faces, _a, faceExpressionsByFace;
-            return tslib_1.__generator(this, function (_b) {
-                switch (_b.label) {
+            var parentResults, faceExpressionsByFace;
+            var _this = this;
+            return tslib_1.__generator(this, function (_a) {
+                switch (_a.label) {
                     case 0: return [4 /*yield*/, this.parentTask];
                     case 1:
-                        parentResults = _b.sent();
-                        detections = parentResults.map(function (parentResult) { return parentResult.detection; });
-                        if (!(this.input instanceof tf.Tensor)) return [3 /*break*/, 3];
-                        return [4 /*yield*/, extractFaceTensors(this.input, detections)];
+                        parentResults = _a.sent();
+                        return [4 /*yield*/, extractAllFacesAndComputeResults(parentResults, this.input, function (faces) { return tslib_1.__awaiter(_this, void 0, void 0, function () {
+                                return tslib_1.__generator(this, function (_a) {
+                                    switch (_a.label) {
+                                        case 0: return [4 /*yield*/, Promise.all(faces.map(function (face) { return nets.faceExpressionNet.predictExpressions(face); }))];
+                                        case 1: return [2 /*return*/, _a.sent()];
+                                    }
+                                });
+                            }); }, this.extractedFaces)];
                     case 2:
-                        _a = _b.sent();
-                        return [3 /*break*/, 5];
-                    case 3: return [4 /*yield*/, extractFaces(this.input, detections)];
-                    case 4:
-                        _a = _b.sent();
-                        _b.label = 5;
-                    case 5:
-                        faces = _a;
-                        return [4 /*yield*/, Promise.all(faces.map(function (face) { return nets.faceExpressionNet.predictExpressions(face); }))];
-                    case 6:
-                        faceExpressionsByFace = _b.sent();
-                        faces.forEach(function (f) { return f instanceof tf.Tensor && f.dispose(); });
+                        faceExpressionsByFace = _a.sent();
                         return [2 /*return*/, parentResults.map(function (parentResult, i) { return extendWithFaceExpressions(parentResult, faceExpressionsByFace[i]); })];
                 }
             });
         });
     };
-    PredictAllFaceExpressionsTask.prototype.withFaceLandmarks = function () {
-        return new DetectAllFaceLandmarksTask(this, this.input, false);
+    PredictAllFaceExpressionsTask.prototype.withAgeAndGender = function () {
+        return new PredictAllAgeAndGenderTask(this, this.input);
     };
     return PredictAllFaceExpressionsTask;
 }(PredictFaceExpressionsTaskBase));
 export { PredictAllFaceExpressionsTask };
-var PredictSingleFaceExpressionTask = /** @class */ (function (_super) {
-    tslib_1.__extends(PredictSingleFaceExpressionTask, _super);
-    function PredictSingleFaceExpressionTask() {
+var PredictSingleFaceExpressionsTask = /** @class */ (function (_super) {
+    tslib_1.__extends(PredictSingleFaceExpressionsTask, _super);
+    function PredictSingleFaceExpressionsTask() {
         return _super !== null && _super.apply(this, arguments) || this;
     }
-    PredictSingleFaceExpressionTask.prototype.run = function () {
+    PredictSingleFaceExpressionsTask.prototype.run = function () {
         return tslib_1.__awaiter(this, void 0, void 0, function () {
-            var parentResult, detection, faces, _a, faceExpressions;
-            return tslib_1.__generator(this, function (_b) {
-                switch (_b.label) {
+            var parentResult, faceExpressions;
+            return tslib_1.__generator(this, function (_a) {
+                switch (_a.label) {
                     case 0: return [4 /*yield*/, this.parentTask];
                     case 1:
-                        parentResult = _b.sent();
+                        parentResult = _a.sent();
                         if (!parentResult) {
                             return [2 /*return*/];
                         }
-                        detection = parentResult.detection;
-                        if (!(this.input instanceof tf.Tensor)) return [3 /*break*/, 3];
-                        return [4 /*yield*/, extractFaceTensors(this.input, [detection])];
+                        return [4 /*yield*/, extractSingleFaceAndComputeResult(parentResult, this.input, function (face) { return nets.faceExpressionNet.predictExpressions(face); }, this.extractedFaces)];
                     case 2:
-                        _a = _b.sent();
-                        return [3 /*break*/, 5];
-                    case 3: return [4 /*yield*/, extractFaces(this.input, [detection])];
-                    case 4:
-                        _a = _b.sent();
-                        _b.label = 5;
-                    case 5:
-                        faces = _a;
-                        return [4 /*yield*/, nets.faceExpressionNet.predictExpressions(faces[0])];
-                    case 6:
-                        faceExpressions = _b.sent();
-                        faces.forEach(function (f) { return f instanceof tf.Tensor && f.dispose(); });
+                        faceExpressions = _a.sent();
                         return [2 /*return*/, extendWithFaceExpressions(parentResult, faceExpressions)];
                 }
             });
         });
     };
-    PredictSingleFaceExpressionTask.prototype.withFaceLandmarks = function () {
-        return new DetectSingleFaceLandmarksTask(this, this.input, false);
+    PredictSingleFaceExpressionsTask.prototype.withAgeAndGender = function () {
+        return new PredictSingleAgeAndGenderTask(this, this.input);
     };
-    return PredictSingleFaceExpressionTask;
+    return PredictSingleFaceExpressionsTask;
 }(PredictFaceExpressionsTaskBase));
-export { PredictSingleFaceExpressionTask };
+export { PredictSingleFaceExpressionsTask };
+var PredictAllFaceExpressionsWithFaceAlignmentTask = /** @class */ (function (_super) {
+    tslib_1.__extends(PredictAllFaceExpressionsWithFaceAlignmentTask, _super);
+    function PredictAllFaceExpressionsWithFaceAlignmentTask() {
+        return _super !== null && _super.apply(this, arguments) || this;
+    }
+    PredictAllFaceExpressionsWithFaceAlignmentTask.prototype.withAgeAndGender = function () {
+        return new PredictAllAgeAndGenderWithFaceAlignmentTask(this, this.input);
+    };
+    PredictAllFaceExpressionsWithFaceAlignmentTask.prototype.withFaceDescriptors = function () {
+        return new ComputeAllFaceDescriptorsTask(this, this.input);
+    };
+    return PredictAllFaceExpressionsWithFaceAlignmentTask;
+}(PredictAllFaceExpressionsTask));
+export { PredictAllFaceExpressionsWithFaceAlignmentTask };
+var PredictSingleFaceExpressionsWithFaceAlignmentTask = /** @class */ (function (_super) {
+    tslib_1.__extends(PredictSingleFaceExpressionsWithFaceAlignmentTask, _super);
+    function PredictSingleFaceExpressionsWithFaceAlignmentTask() {
+        return _super !== null && _super.apply(this, arguments) || this;
+    }
+    PredictSingleFaceExpressionsWithFaceAlignmentTask.prototype.withAgeAndGender = function () {
+        return new PredictSingleAgeAndGenderWithFaceAlignmentTask(this, this.input);
+    };
+    PredictSingleFaceExpressionsWithFaceAlignmentTask.prototype.withFaceDescriptor = function () {
+        return new ComputeSingleFaceDescriptorTask(this, this.input);
+    };
+    return PredictSingleFaceExpressionsWithFaceAlignmentTask;
+}(PredictSingleFaceExpressionsTask));
+export { PredictSingleFaceExpressionsWithFaceAlignmentTask };
 //# sourceMappingURL=PredictFaceExpressionsTask.js.map
\ No newline at end of file

build/es6/globalApi/PredictFaceExpressionsTask.js.map

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\ No newline at end of file

build/es6/globalApi/extractFacesAndComputeResults.d.ts

+import * as tf from '@tensorflow/tfjs-core';
+import { TNetInput } from 'tfjs-image-recognition-base';
+import { FaceDetection } from '../classes/FaceDetection';
+import { WithFaceDetection } from '../factories/WithFaceDetection';
+import { WithFaceLandmarks } from '../factories/WithFaceLandmarks';
+export declare function extractAllFacesAndComputeResults<TSource extends WithFaceDetection<{}>, TResult>(parentResults: TSource[], input: TNetInput, computeResults: (faces: Array<HTMLCanvasElement | tf.Tensor3D>) => Promise<TResult>, extractedFaces?: Array<HTMLCanvasElement | tf.Tensor3D> | null, getRectForAlignment?: (parentResult: WithFaceLandmarks<TSource, any>) => FaceDetection): Promise<TResult>;
+export declare function extractSingleFaceAndComputeResult<TSource extends WithFaceDetection<{}>, TResult>(parentResult: TSource, input: TNetInput, computeResult: (face: HTMLCanvasElement | tf.Tensor3D) => Promise<TResult>, extractedFaces?: Array<HTMLCanvasElement | tf.Tensor3D> | null, getRectForAlignment?: (parentResult: WithFaceLandmarks<TSource, any>) => FaceDetection): Promise<TResult>;

build/es6/globalApi/extractFacesAndComputeResults.js

+import * as tslib_1 from "tslib";
+import * as tf from '@tensorflow/tfjs-core';
+import { extractFaces, extractFaceTensors } from '../dom';
+import { isWithFaceLandmarks } from '../factories/WithFaceLandmarks';
+export function extractAllFacesAndComputeResults(parentResults, input, computeResults, extractedFaces, getRectForAlignment) {
+    if (getRectForAlignment === void 0) { getRectForAlignment = function (_a) {
+        var alignedRect = _a.alignedRect;
+        return alignedRect;
+    }; }
+    return tslib_1.__awaiter(this, void 0, void 0, function () {
+        var faceBoxes, faces, _a, _b, results;
+        return tslib_1.__generator(this, function (_c) {
+            switch (_c.label) {
+                case 0:
+                    faceBoxes = parentResults.map(function (parentResult) {
+                        return isWithFaceLandmarks(parentResult)
+                            ? getRectForAlignment(parentResult)
+                            : parentResult.detection;
+                    });
+                    _a = extractedFaces;
+                    if (_a) return [3 /*break*/, 5];
+                    if (!(input instanceof tf.Tensor)) return [3 /*break*/, 2];
+                    return [4 /*yield*/, extractFaceTensors(input, faceBoxes)];
+                case 1:
+                    _b = _c.sent();
+                    return [3 /*break*/, 4];
+                case 2: return [4 /*yield*/, extractFaces(input, faceBoxes)];
+                case 3:
+                    _b = _c.sent();
+                    _c.label = 4;
+                case 4:
+                    _a = (_b);
+                    _c.label = 5;
+                case 5:
+                    faces = _a;
+                    return [4 /*yield*/, computeResults(faces)];
+                case 6:
+                    results = _c.sent();
+                    faces.forEach(function (f) { return f instanceof tf.Tensor && f.dispose(); });
+                    return [2 /*return*/, results];
+            }
+        });
+    });
+}
+export function extractSingleFaceAndComputeResult(parentResult, input, computeResult, extractedFaces, getRectForAlignment) {
+    return tslib_1.__awaiter(this, void 0, void 0, function () {
+        var _this = this;
+        return tslib_1.__generator(this, function (_a) {
+            return [2 /*return*/, extractAllFacesAndComputeResults([parentResult], input, function (faces) { return tslib_1.__awaiter(_this, void 0, void 0, function () { return tslib_1.__generator(this, function (_a) {
+                    return [2 /*return*/, computeResult(faces[0])];
+                }); }); }, extractedFaces, getRectForAlignment)];
+        });
+    });
+}
+//# sourceMappingURL=extractFacesAndComputeResults.js.map
\ No newline at end of file

build/es6/globalApi/extractFacesAndComputeResults.js.map

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\ No newline at end of file

build/es6/globalApi/nets.d.ts

 import { TfjsImageRecognitionBase, TNetInput } from 'tfjs-image-recognition-base';
+import { AgeGenderNet } from '../ageGenderNet/AgeGenderNet';
+import { AgeAndGenderPrediction } from '../ageGenderNet/types';
 import { FaceDetection } from '../classes/FaceDetection';
 import { FaceLandmarks5 } from '../classes/FaceLandmarks5';
 import { FaceLandmarks68 } from '../classes/FaceLandmarks68';
 import { FaceExpressionNet } from '../faceExpressionNet/FaceExpressionNet';
-import { FaceExpressionPrediction } from '../faceExpressionNet/types';
+import { FaceExpressions } from '../faceExpressionNet/FaceExpressions';
 import { FaceLandmark68Net } from '../faceLandmarkNet/FaceLandmark68Net';
 import { FaceLandmark68TinyNet } from '../faceLandmarkNet/FaceLandmark68TinyNet';
 import { FaceRecognitionNet } from '../faceRecognitionNet/FaceRecognitionNet';
@@ -24,6 +26,7 @@ export declare const nets: {
     faceLandmark68TinyNet: FaceLandmark68TinyNet;
     faceRecognitionNet: FaceRecognitionNet;
     faceExpressionNet: FaceExpressionNet;
+    ageGenderNet: AgeGenderNet;
 };
 /**
  * Attempts to detect all faces in an image using SSD Mobilenetv1 Network.
@@ -90,14 +93,21 @@ export declare const detectFaceLandmarksTiny: (input: TNetInput) => Promise<Face
  */
 export declare const computeFaceDescriptor: (input: TNetInput) => Promise<Float32Array | Float32Array[]>;
 /**
- * Recognizes the facial expressions of a face and returns the likelyhood of
- * each facial expression.
+ * Recognizes the facial expressions from a face image.
  *
  * @param inputs The face image extracted from the bounding box of a face. Can
  * also be an array of input images, which will be batch processed.
- * @returns An array of facial expressions with corresponding probabilities or array thereof in case of batch input.
+ * @returns Facial expressions with corresponding probabilities or array thereof in case of batch input.
  */
-export declare const recognizeFaceExpressions: (input: TNetInput) => Promise<FaceExpressionPrediction[] | FaceExpressionPrediction[][]>;
+export declare const recognizeFaceExpressions: (input: TNetInput) => Promise<FaceExpressions | FaceExpressions[]>;
+/**
+ * Predicts age and gender from a face image.
+ *
+ * @param inputs The face image extracted from the bounding box of a face. Can
+ * also be an array of input images, which will be batch processed.
+ * @returns Predictions with age, gender and gender probability or array thereof in case of batch input.
+ */
+export declare const predictAgeAndGender: (input: TNetInput) => Promise<AgeAndGenderPrediction | AgeAndGenderPrediction[]>;
 export declare const loadSsdMobilenetv1Model: (url: string) => Promise<void>;
 export declare const loadTinyFaceDetectorModel: (url: string) => Promise<void>;
 export declare const loadMtcnnModel: (url: string) => Promise<void>;
@@ -106,6 +116,7 @@ export declare const loadFaceLandmarkModel: (url: string) => Promise<void>;
 export declare const loadFaceLandmarkTinyModel: (url: string) => Promise<void>;
 export declare const loadFaceRecognitionModel: (url: string) => Promise<void>;
 export declare const loadFaceExpressionModel: (url: string) => Promise<void>;
+export declare const loadAgeGenderModel: (url: string) => Promise<void>;
 export declare const loadFaceDetectionModel: (url: string) => Promise<void>;
 export declare const locateFaces: (input: TNetInput, options: SsdMobilenetv1Options) => Promise<FaceDetection[]>;
 export declare const detectLandmarks: (input: TNetInput) => Promise<FaceLandmarks68 | FaceLandmarks68[]>;

build/es6/globalApi/nets.js

+import { AgeGenderNet } from '../ageGenderNet/AgeGenderNet';
 import { FaceExpressionNet } from '../faceExpressionNet/FaceExpressionNet';
 import { FaceLandmark68Net } from '../faceLandmarkNet/FaceLandmark68Net';
 import { FaceLandmark68TinyNet } from '../faceLandmarkNet/FaceLandmark68TinyNet';
@@ -14,7 +15,8 @@ export var nets = {
     faceLandmark68Net: new FaceLandmark68Net(),
     faceLandmark68TinyNet: new FaceLandmark68TinyNet(),
     faceRecognitionNet: new FaceRecognitionNet(),
-    faceExpressionNet: new FaceExpressionNet()
+    faceExpressionNet: new FaceExpressionNet(),
+    ageGenderNet: new AgeGenderNet()
 };
 /**
  * Attempts to detect all faces in an image using SSD Mobilenetv1 Network.
@@ -93,16 +95,25 @@ export var computeFaceDescriptor = function (input) {
     return nets.faceRecognitionNet.computeFaceDescriptor(input);
 };
 /**
- * Recognizes the facial expressions of a face and returns the likelyhood of
- * each facial expression.
+ * Recognizes the facial expressions from a face image.
  *
  * @param inputs The face image extracted from the bounding box of a face. Can
  * also be an array of input images, which will be batch processed.
- * @returns An array of facial expressions with corresponding probabilities or array thereof in case of batch input.
+ * @returns Facial expressions with corresponding probabilities or array thereof in case of batch input.
  */
 export var recognizeFaceExpressions = function (input) {
     return nets.faceExpressionNet.predictExpressions(input);
 };
+/**
+ * Predicts age and gender from a face image.
+ *
+ * @param inputs The face image extracted from the bounding box of a face. Can
+ * also be an array of input images, which will be batch processed.
+ * @returns Predictions with age, gender and gender probability or array thereof in case of batch input.
+ */
+export var predictAgeAndGender = function (input) {
+    return nets.ageGenderNet.predictAgeAndGender(input);
+};
 export var loadSsdMobilenetv1Model = function (url) { return nets.ssdMobilenetv1.load(url); };
 export var loadTinyFaceDetectorModel = function (url) { return nets.tinyFaceDetector.load(url); };
 export var loadMtcnnModel = function (url) { return nets.mtcnn.load(url); };
@@ -111,6 +122,7 @@ export var loadFaceLandmarkModel = function (url) { return nets.faceLandmark68Ne
 export var loadFaceLandmarkTinyModel = function (url) { return nets.faceLandmark68TinyNet.load(url); };
 export var loadFaceRecognitionModel = function (url) { return nets.faceRecognitionNet.load(url); };
 export var loadFaceExpressionModel = function (url) { return nets.faceExpressionNet.load(url); };
+export var loadAgeGenderModel = function (url) { return nets.ageGenderNet.load(url); };
 // backward compatibility
 export var loadFaceDetectionModel = loadSsdMobilenetv1Model;
 export var locateFaces = ssdMobilenetv1;

build/es6/globalApi/nets.js.map

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\ No newline at end of file

build/es6/index.d.ts

 import * as tf from '@tensorflow/tfjs-core';
+import { draw as drawBase } from 'tfjs-image-recognition-base';
+import * as drawExtended from './draw';
 export { tf };
 export * from 'tfjs-image-recognition-base';
+export * from './ageGenderNet/index';
+declare const draw: {
+    drawContour(ctx: CanvasRenderingContext2D, points: import("tfjs-image-recognition-base").Point[], isClosed?: boolean): void;
+    drawDetections(canvasArg: string | HTMLCanvasElement, detections: import("tfjs-image-recognition-base").IRect | import("tfjs-image-recognition-base").IBoundingBox | import("./classes").FaceDetection | {
+        detection: import("./classes").FaceDetection;
+    } | drawExtended.TDrawDetectionsInput[]): void;
+    drawFaceExpressions(canvasArg: string | HTMLCanvasElement, faceExpressions: import("./faceExpressionNet").FaceExpressions | {
+        expressions: import("./faceExpressionNet").FaceExpressions;
+    } | drawExtended.DrawFaceExpressionsInput[], minConfidence?: number, textFieldAnchor?: import("tfjs-image-recognition-base").IPoint | undefined): void;
+    drawFaceLandmarks(canvasArg: string | HTMLCanvasElement, faceLandmarks: import("./classes").FaceLandmarks | import("./factories").WithFaceLandmarks<{
+        detection: import("./classes").FaceDetection;
+    }, import("./classes").FaceLandmarks68> | drawExtended.DrawFaceLandmarksInput[]): void;
+    DrawFaceLandmarksOptions: typeof drawExtended.DrawFaceLandmarksOptions;
+    DrawFaceLandmarks: typeof drawExtended.DrawFaceLandmarks;
+    DrawBoxOptions: typeof drawBase.DrawBoxOptions;
+    DrawBox: typeof drawBase.DrawBox;
+    AnchorPosition: typeof drawBase.AnchorPosition;
+    DrawTextFieldOptions: typeof drawBase.DrawTextFieldOptions;
+    DrawTextField: typeof drawBase.DrawTextField;
+};
+export { draw };
 export * from './classes/index';
 export * from './dom/index';
 export * from './faceExpressionNet/index';

build/es6/index.js

+import * as tslib_1 from "tslib";
 import * as tf from '@tensorflow/tfjs-core';
+import { draw as drawBase } from 'tfjs-image-recognition-base';
+import * as drawExtended from './draw';
 export { tf };
 export * from 'tfjs-image-recognition-base';
+export * from './ageGenderNet/index';
+var draw = tslib_1.__assign({}, drawBase, drawExtended);
+export { draw };
 export * from './classes/index';
 export * from './dom/index';
 export * from './faceExpressionNet/index';

build/es6/index.js.map

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+{"version":3,"file":"index.js","sourceRoot":"","sources":["../../src/index.ts"],"names":[],"mappings":";AAAA,OAAO,KAAK,EAAE,MAAM,uBAAuB,CAAC;AAC5C,OAAO,EAAE,IAAI,IAAI,QAAQ,EAAE,MAAM,6BAA6B,CAAC;AAE/D,OAAO,KAAK,YAAY,MAAM,QAAQ,CAAC;AAEvC,OAAO,EACL,EAAE,EACH,CAAA;AAED,cAAc,6BAA6B,CAAC;AAE5C,cAAc,sBAAsB,CAAC;AACrC,IAAM,IAAI,wBAAO,QAAQ,EAAK,YAAY,CAAE,CAAA;AAC5C,OAAO,EAAE,IAAI,EAAE,CAAA;AAEf,cAAc,iBAAiB,CAAC;AAChC,cAAc,aAAa,CAAA;AAC3B,cAAc,2BAA2B,CAAC;AAC1C,cAAc,yBAAyB,CAAC;AACxC,cAAc,4BAA4B,CAAC;AAC3C,cAAc,mBAAmB,CAAC;AAClC,cAAc,mBAAmB,CAAC;AAClC,cAAc,eAAe,CAAC;AAC9B,cAAc,wBAAwB,CAAC;AACvC,cAAc,0BAA0B,CAAC;AACzC,cAAc,oBAAoB,CAAC;AAEnC,cAAc,qBAAqB,CAAC;AACpC,cAAc,iBAAiB,CAAC"}
\ No newline at end of file

build/es6/minBbox.d.ts

+import { BoundingBox, IPoint } from 'tfjs-image-recognition-base';
+export declare function minBbox(pts: IPoint[]): BoundingBox;

build/es6/minBbox.js

+import { BoundingBox } from 'tfjs-image-recognition-base';
+export function minBbox(pts) {
+    var xs = pts.map(function (pt) { return pt.x; });
+    var ys = pts.map(function (pt) { return pt.y; });
+    var minX = xs.reduce(function (min, x) { return x < min ? x : min; }, Infinity);
+    var minY = ys.reduce(function (min, y) { return y < min ? y : min; }, Infinity);
+    var maxX = xs.reduce(function (max, x) { return max < x ? x : max; }, 0);
+    var maxY = ys.reduce(function (max, y) { return max < y ? y : max; }, 0);
+    return new BoundingBox(minX, minY, maxX, maxY);
+}
+//# sourceMappingURL=minBbox.js.map
\ No newline at end of file

build/es6/minBbox.js.map

+{"version":3,"file":"minBbox.js","sourceRoot":"","sources":["../../src/minBbox.ts"],"names":[],"mappings":"AAAA,OAAO,EAAE,WAAW,EAAU,MAAM,6BAA6B,CAAC;AAElE,MAAM,UAAU,OAAO,CAAC,GAAa;IACnC,IAAM,EAAE,GAAG,GAAG,CAAC,GAAG,CAAC,UAAA,EAAE,IAAI,OAAA,EAAE,CAAC,CAAC,EAAJ,CAAI,CAAC,CAAA;IAC9B,IAAM,EAAE,GAAG,GAAG,CAAC,GAAG,CAAC,UAAA,EAAE,IAAI,OAAA,EAAE,CAAC,CAAC,EAAJ,CAAI,CAAC,CAAA;IAC9B,IAAM,IAAI,GAAG,EAAE,CAAC,MAAM,CAAC,UAAC,GAAG,EAAE,CAAC,IAAK,OAAA,CAAC,GAAG,GAAG,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,GAAG,EAAjB,CAAiB,EAAE,QAAQ,CAAC,CAAA;IAC/D,IAAM,IAAI,GAAG,EAAE,CAAC,MAAM,CAAC,UAAC,GAAG,EAAE,CAAC,IAAK,OAAA,CAAC,GAAG,GAAG,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,GAAG,EAAjB,CAAiB,EAAE,QAAQ,CAAC,CAAA;IAC/D,IAAM,IAAI,GAAG,EAAE,CAAC,MAAM,CAAC,UAAC,GAAG,EAAE,CAAC,IAAK,OAAA,GAAG,GAAG,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,GAAG,EAAjB,CAAiB,EAAE,CAAC,CAAC,CAAA;IACxD,IAAM,IAAI,GAAG,EAAE,CAAC,MAAM,CAAC,UAAC,GAAG,EAAE,CAAC,IAAK,OAAA,GAAG,GAAG,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,GAAG,EAAjB,CAAiB,EAAE,CAAC,CAAC,CAAA;IAExD,OAAO,IAAI,WAAW,CAAC,IAAI,EAAE,IAAI,EAAE,IAAI,EAAE,IAAI,CAAC,CAAA;AAChD,CAAC"}
\ No newline at end of file

build/es6/resizeResults.d.ts

 import { IDimensions } from 'tfjs-image-recognition-base';
-export declare function resizeResults<T>(results: T, { width, height }: IDimensions): T;
+export declare function resizeResults<T>(results: T, dimensions: IDimensions): T;

build/es6/resizeResults.js

+import { Dimensions } from 'tfjs-image-recognition-base';
 import { FaceDetection } from './classes/FaceDetection';
 import { FaceLandmarks } from './classes/FaceLandmarks';
-import { extendWithFaceDetection } from './factories/WithFaceDetection';
-import { extendWithFaceLandmarks } from './factories/WithFaceLandmarks';
-export function resizeResults(results, _a) {
-    var width = _a.width, height = _a.height;
+import { extendWithFaceDetection, isWithFaceDetection } from './factories/WithFaceDetection';
+import { extendWithFaceLandmarks, isWithFaceLandmarks } from './factories/WithFaceLandmarks';
+export function resizeResults(results, dimensions) {
+    var _a = new Dimensions(dimensions.width, dimensions.height), width = _a.width, height = _a.height;
+    if (width <= 0 || height <= 0) {
+        throw new Error("resizeResults - invalid dimensions: " + JSON.stringify({ width: width, height: height }));
+    }
     if (Array.isArray(results)) {
         return results.map(function (obj) { return resizeResults(obj, { width: width, height: height }); });
     }
-    var hasLandmarks = results['unshiftedLandmarks'] && results['unshiftedLandmarks'] instanceof FaceLandmarks;
-    var hasDetection = results['detection'] && results['detection'] instanceof FaceDetection;
-    if (hasLandmarks) {
-        var resizedDetection = results['detection'].forSize(width, height);
-        var resizedLandmarks = results['unshiftedLandmarks'].forSize(resizedDetection.box.width, resizedDetection.box.height);
+    if (isWithFaceLandmarks(results)) {
+        var resizedDetection = results.detection.forSize(width, height);
+        var resizedLandmarks = results.unshiftedLandmarks.forSize(resizedDetection.box.width, resizedDetection.box.height);
         return extendWithFaceLandmarks(extendWithFaceDetection(results, resizedDetection), resizedLandmarks);
     }
-    if (hasDetection) {
-        return extendWithFaceDetection(results, results['detection'].forSize(width, height));
+    if (isWithFaceDetection(results)) {
+        return extendWithFaceDetection(results, results.detection.forSize(width, height));
     }
     if (results instanceof FaceLandmarks || results instanceof FaceDetection) {
         return results.forSize(width, height);

build/es6/resizeResults.js.map

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\ No newline at end of file

build/es6/xception/TinyXception.d.ts

+import * as tf from '@tensorflow/tfjs-core';
+import { NetInput, NeuralNetwork, TfjsImageRecognitionBase, TNetInput } from 'tfjs-image-recognition-base';
+import { TinyXceptionParams } from './types';
+export declare class TinyXception extends NeuralNetwork<TinyXceptionParams> {
+    private _numMainBlocks;
+    constructor(numMainBlocks: number);
+    forwardInput(input: NetInput): tf.Tensor4D;
+    forward(input: TNetInput): Promise<tf.Tensor4D>;
+    protected getDefaultModelName(): string;
+    protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap): {
+        params: TinyXceptionParams;
+        paramMappings: TfjsImageRecognitionBase.ParamMapping[];
+    };
+    protected extractParams(weights: Float32Array): {
+        params: TinyXceptionParams;
+        paramMappings: TfjsImageRecognitionBase.ParamMapping[];
+    };
+}

build/es6/xception/TinyXception.js

+import * as tslib_1 from "tslib";
+import * as tf from '@tensorflow/tfjs-core';
+import { NeuralNetwork, normalize, range, toNetInput, } from 'tfjs-image-recognition-base';
+import { depthwiseSeparableConv } from '../common/depthwiseSeparableConv';
+import { extractParams } from './extractParams';
+import { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';
+function conv(x, params, stride) {
+    return tf.add(tf.conv2d(x, params.filters, stride, 'same'), params.bias);
+}
+function reductionBlock(x, params, isActivateInput) {
+    if (isActivateInput === void 0) { isActivateInput = true; }
+    var out = isActivateInput ? tf.relu(x) : x;
+    out = depthwiseSeparableConv(out, params.separable_conv0, [1, 1]);
+    out = depthwiseSeparableConv(tf.relu(out), params.separable_conv1, [1, 1]);
+    out = tf.maxPool(out, [3, 3], [2, 2], 'same');
+    out = tf.add(out, conv(x, params.expansion_conv, [2, 2]));
+    return out;
+}
+function mainBlock(x, params) {
+    var out = depthwiseSeparableConv(tf.relu(x), params.separable_conv0, [1, 1]);
+    out = depthwiseSeparableConv(tf.relu(out), params.separable_conv1, [1, 1]);
+    out = depthwiseSeparableConv(tf.relu(out), params.separable_conv2, [1, 1]);
+    out = tf.add(out, x);
+    return out;
+}
+var TinyXception = /** @class */ (function (_super) {
+    tslib_1.__extends(TinyXception, _super);
+    function TinyXception(numMainBlocks) {
+        var _this = _super.call(this, 'TinyXception') || this;
+        _this._numMainBlocks = numMainBlocks;
+        return _this;
+    }
+    TinyXception.prototype.forwardInput = function (input) {
+        var _this = this;
+        var params = this.params;
+        if (!params) {
+            throw new Error('TinyXception - load model before inference');
+        }
+        return tf.tidy(function () {
+            var batchTensor = input.toBatchTensor(112, true);
+            var meanRgb = [122.782, 117.001, 104.298];
+            var normalized = normalize(batchTensor, meanRgb).div(tf.scalar(256));
+            var out = tf.relu(conv(normalized, params.entry_flow.conv_in, [2, 2]));
+            out = reductionBlock(out, params.entry_flow.reduction_block_0, false);
+            out = reductionBlock(out, params.entry_flow.reduction_block_1);
+            range(_this._numMainBlocks, 0, 1).forEach(function (idx) {
+                out = mainBlock(out, params.middle_flow["main_block_" + idx]);
+            });
+            out = reductionBlock(out, params.exit_flow.reduction_block);
+            out = tf.relu(depthwiseSeparableConv(out, params.exit_flow.separable_conv, [1, 1]));
+            return out;
+        });
+    };
+    TinyXception.prototype.forward = function (input) {
+        return tslib_1.__awaiter(this, void 0, void 0, function () {
+            var _a;
+            return tslib_1.__generator(this, function (_b) {
+                switch (_b.label) {
+                    case 0:
+                        _a = this.forwardInput;
+                        return [4 /*yield*/, toNetInput(input)];
+                    case 1: return [2 /*return*/, _a.apply(this, [_b.sent()])];
+                }
+            });
+        });
+    };
+    TinyXception.prototype.getDefaultModelName = function () {
+        return 'tiny_xception_model';
+    };
+    TinyXception.prototype.extractParamsFromWeigthMap = function (weightMap) {
+        return extractParamsFromWeigthMap(weightMap, this._numMainBlocks);
+    };
+    TinyXception.prototype.extractParams = function (weights) {
+        return extractParams(weights, this._numMainBlocks);
+    };
+    return TinyXception;
+}(NeuralNetwork));
+export { TinyXception };
+//# sourceMappingURL=TinyXception.js.map
\ No newline at end of file

build/es6/xception/TinyXception.js.map

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\ No newline at end of file

build/es6/xception/extractParams.d.ts

+import { TfjsImageRecognitionBase } from 'tfjs-image-recognition-base';
+import { TinyXceptionParams } from './types';
+export declare function extractParams(weights: Float32Array, numMainBlocks: number): {
+    params: TinyXceptionParams;
+    paramMappings: TfjsImageRecognitionBase.ParamMapping[];
+};

build/es6/xception/extractParams.js

+import { range, TfjsImageRecognitionBase } from 'tfjs-image-recognition-base';
+function extractorsFactory(extractWeights, paramMappings) {
+    var extractConvParams = TfjsImageRecognitionBase.extractConvParamsFactory(extractWeights, paramMappings);
+    var extractSeparableConvParams = TfjsImageRecognitionBase.extractSeparableConvParamsFactory(extractWeights, paramMappings);
+    function extractReductionBlockParams(channelsIn, channelsOut, mappedPrefix) {
+        var separable_conv0 = extractSeparableConvParams(channelsIn, channelsOut, mappedPrefix + "/separable_conv0");
+        var separable_conv1 = extractSeparableConvParams(channelsOut, channelsOut, mappedPrefix + "/separable_conv1");
+        var expansion_conv = extractConvParams(channelsIn, channelsOut, 1, mappedPrefix + "/expansion_conv");
+        return { separable_conv0: separable_conv0, separable_conv1: separable_conv1, expansion_conv: expansion_conv };
+    }
+    function extractMainBlockParams(channels, mappedPrefix) {
+        var separable_conv0 = extractSeparableConvParams(channels, channels, mappedPrefix + "/separable_conv0");
+        var separable_conv1 = extractSeparableConvParams(channels, channels, mappedPrefix + "/separable_conv1");
+        var separable_conv2 = extractSeparableConvParams(channels, channels, mappedPrefix + "/separable_conv2");
+        return { separable_conv0: separable_conv0, separable_conv1: separable_conv1, separable_conv2: separable_conv2 };
+    }
+    return {
+        extractConvParams: extractConvParams,
+        extractSeparableConvParams: extractSeparableConvParams,
+        extractReductionBlockParams: extractReductionBlockParams,
+        extractMainBlockParams: extractMainBlockParams
+    };
+}
+export function extractParams(weights, numMainBlocks) {
+    var paramMappings = [];
+    var _a = TfjsImageRecognitionBase.extractWeightsFactory(weights), extractWeights = _a.extractWeights, getRemainingWeights = _a.getRemainingWeights;
+    var _b = extractorsFactory(extractWeights, paramMappings), extractConvParams = _b.extractConvParams, extractSeparableConvParams = _b.extractSeparableConvParams, extractReductionBlockParams = _b.extractReductionBlockParams, extractMainBlockParams = _b.extractMainBlockParams;
+    var entry_flow_conv_in = extractConvParams(3, 32, 3, 'entry_flow/conv_in');
+    var entry_flow_reduction_block_0 = extractReductionBlockParams(32, 64, 'entry_flow/reduction_block_0');
+    var entry_flow_reduction_block_1 = extractReductionBlockParams(64, 128, 'entry_flow/reduction_block_1');
+    var entry_flow = {
+        conv_in: entry_flow_conv_in,
+        reduction_block_0: entry_flow_reduction_block_0,
+        reduction_block_1: entry_flow_reduction_block_1
+    };
+    var middle_flow = {};
+    range(numMainBlocks, 0, 1).forEach(function (idx) {
+        middle_flow["main_block_" + idx] = extractMainBlockParams(128, "middle_flow/main_block_" + idx);
+    });
+    var exit_flow_reduction_block = extractReductionBlockParams(128, 256, 'exit_flow/reduction_block');
+    var exit_flow_separable_conv = extractSeparableConvParams(256, 512, 'exit_flow/separable_conv');
+    var exit_flow = {
+        reduction_block: exit_flow_reduction_block,
+        separable_conv: exit_flow_separable_conv
+    };
+    if (getRemainingWeights().length !== 0) {
+        throw new Error("weights remaing after extract: " + getRemainingWeights().length);
+    }
+    return {
+        paramMappings: paramMappings,
+        params: { entry_flow: entry_flow, middle_flow: middle_flow, exit_flow: exit_flow }
+    };
+}
+//# sourceMappingURL=extractParams.js.map
\ No newline at end of file

build/es6/xception/extractParams.js.map

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\ No newline at end of file

build/es6/xception/extractParamsFromWeigthMap.d.ts

+import * as tf from '@tensorflow/tfjs-core';
+import { TfjsImageRecognitionBase } from 'tfjs-image-recognition-base';
+import { TinyXceptionParams } from './types';
+export declare function extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap, numMainBlocks: number): {
+    params: TinyXceptionParams;
+    paramMappings: TfjsImageRecognitionBase.ParamMapping[];
+};

build/es6/xception/extractParamsFromWeigthMap.js

+import { TfjsImageRecognitionBase, range } from 'tfjs-image-recognition-base';
+import { loadConvParamsFactory } from '../common/loadConvParamsFactory';
+function loadParamsFactory(weightMap, paramMappings) {
+    var extractWeightEntry = TfjsImageRecognitionBase.extractWeightEntryFactory(weightMap, paramMappings);
+    var extractConvParams = loadConvParamsFactory(extractWeightEntry);
+    var extractSeparableConvParams = TfjsImageRecognitionBase.loadSeparableConvParamsFactory(extractWeightEntry);
+    function extractReductionBlockParams(mappedPrefix) {
+        var separable_conv0 = extractSeparableConvParams(mappedPrefix + "/separable_conv0");
+        var separable_conv1 = extractSeparableConvParams(mappedPrefix + "/separable_conv1");
+        var expansion_conv = extractConvParams(mappedPrefix + "/expansion_conv");
+        return { separable_conv0: separable_conv0, separable_conv1: separable_conv1, expansion_conv: expansion_conv };
+    }
+    function extractMainBlockParams(mappedPrefix) {
+        var separable_conv0 = extractSeparableConvParams(mappedPrefix + "/separable_conv0");
+        var separable_conv1 = extractSeparableConvParams(mappedPrefix + "/separable_conv1");
+        var separable_conv2 = extractSeparableConvParams(mappedPrefix + "/separable_conv2");
+        return { separable_conv0: separable_conv0, separable_conv1: separable_conv1, separable_conv2: separable_conv2 };
+    }
+    return {
+        extractConvParams: extractConvParams,
+        extractSeparableConvParams: extractSeparableConvParams,
+        extractReductionBlockParams: extractReductionBlockParams,
+        extractMainBlockParams: extractMainBlockParams
+    };
+}
+export function extractParamsFromWeigthMap(weightMap, numMainBlocks) {
+    var paramMappings = [];
+    var _a = loadParamsFactory(weightMap, paramMappings), extractConvParams = _a.extractConvParams, extractSeparableConvParams = _a.extractSeparableConvParams, extractReductionBlockParams = _a.extractReductionBlockParams, extractMainBlockParams = _a.extractMainBlockParams;
+    var entry_flow_conv_in = extractConvParams('entry_flow/conv_in');
+    var entry_flow_reduction_block_0 = extractReductionBlockParams('entry_flow/reduction_block_0');
+    var entry_flow_reduction_block_1 = extractReductionBlockParams('entry_flow/reduction_block_1');
+    var entry_flow = {
+        conv_in: entry_flow_conv_in,
+        reduction_block_0: entry_flow_reduction_block_0,
+        reduction_block_1: entry_flow_reduction_block_1
+    };
+    var middle_flow = {};
+    range(numMainBlocks, 0, 1).forEach(function (idx) {
+        middle_flow["main_block_" + idx] = extractMainBlockParams("middle_flow/main_block_" + idx);
+    });
+    var exit_flow_reduction_block = extractReductionBlockParams('exit_flow/reduction_block');
+    var exit_flow_separable_conv = extractSeparableConvParams('exit_flow/separable_conv');
+    var exit_flow = {
+        reduction_block: exit_flow_reduction_block,
+        separable_conv: exit_flow_separable_conv
+    };
+    TfjsImageRecognitionBase.disposeUnusedWeightTensors(weightMap, paramMappings);
+    return { params: { entry_flow: entry_flow, middle_flow: middle_flow, exit_flow: exit_flow }, paramMappings: paramMappings };
+}
+//# sourceMappingURL=extractParamsFromWeigthMap.js.map
\ No newline at end of file

build/es6/xception/extractParamsFromWeigthMap.js.map

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\ No newline at end of file

build/es6/xception/index.d.ts

+export * from './TinyXception';

build/es6/xception/index.js

+export * from './TinyXception';
+//# sourceMappingURL=index.js.map
\ No newline at end of file

build/es6/xception/index.js.map

+{"version":3,"file":"index.js","sourceRoot":"","sources":["../../../src/xception/index.ts"],"names":[],"mappings":"AAAA,cAAc,gBAAgB,CAAC"}
\ No newline at end of file

build/es6/xception/types.d.ts

+import { TfjsImageRecognitionBase } from "tfjs-image-recognition-base";
+export declare type ReductionBlockParams = {
+    separable_conv0: TfjsImageRecognitionBase.SeparableConvParams;
+    separable_conv1: TfjsImageRecognitionBase.SeparableConvParams;
+    expansion_conv: TfjsImageRecognitionBase.ConvParams;
+};
+export declare type MainBlockParams = {
+    separable_conv0: TfjsImageRecognitionBase.SeparableConvParams;
+    separable_conv1: TfjsImageRecognitionBase.SeparableConvParams;
+    separable_conv2: TfjsImageRecognitionBase.SeparableConvParams;
+};
+export declare type TinyXceptionParams = {
+    entry_flow: {
+        conv_in: TfjsImageRecognitionBase.ConvParams;
+        reduction_block_0: ReductionBlockParams;
+        reduction_block_1: ReductionBlockParams;
+    };
+    middle_flow: any;
+    exit_flow: {
+        reduction_block: ReductionBlockParams;
+        separable_conv: TfjsImageRecognitionBase.SeparableConvParams;
+    };
+};

build/es6/xception/types.js.map

+{"version":3,"file":"types.js","sourceRoot":"","sources":["../../../src/xception/types.ts"],"names":[],"mappings":""}
\ No newline at end of file