check in latest build

README.md

@@ -368,7 +368,7 @@ const result = await faceapi.detectSingleFace(input).withFaceLandmarks().withFac
 
 ### Recognizing Face Expressions
 
-**Face expressions recognition can be performed for detected faces as follows:**
+**Face expression recognition can be performed for detected faces as follows:**
 
 Detect all faces in an image + recognize face expressions. Returns **Array<[WithFaceExpressions<WithFaceDetection<{}>>](#usage-utility-classes)>**:
 

build/commonjs/classes/FaceDetection.d.ts

@@ -5,4 +5,5 @@ export interface IFaceDetecion {
 }
 export declare class FaceDetection extends ObjectDetection implements IFaceDetecion {
     constructor(score: number, relativeBox: Rect, imageDims: IDimensions);
+    forSize(width: number, height: number): FaceDetection;
 }

build/commonjs/classes/FaceDetection.js

@@ -7,6 +7,9 @@ var FaceDetection = /** @class */ (function (_super) {
     function FaceDetection(score, relativeBox, imageDims) {
         return _super.call(this, score, score, '', relativeBox, imageDims) || this;
     }
+    FaceDetection.prototype.forSize = function (width, height) {
+        return _super.prototype.forSize.call(this, width, height);
+    };
     return FaceDetection;
 }(tfjs_image_recognition_base_1.ObjectDetection));
 exports.FaceDetection = FaceDetection;

build/commonjs/classes/FaceDetection.js.map

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+{"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"}
\ No newline at end of file

build/commonjs/classes/FaceDetectionWithLandmarks.d.ts

-import { FaceDetection } from './FaceDetection';
-import { FaceLandmarks } from './FaceLandmarks';
-import { FaceLandmarks68 } from './FaceLandmarks68';
-export interface IFaceDetectionWithLandmarks<TFaceLandmarks extends FaceLandmarks = FaceLandmarks68> {
-    detection: FaceDetection;
-    landmarks: TFaceLandmarks;
-}
-export declare class FaceDetectionWithLandmarks<TFaceLandmarks extends FaceLandmarks = FaceLandmarks68> implements IFaceDetectionWithLandmarks<TFaceLandmarks> {
-    private _detection;
-    private _unshiftedLandmarks;
-    constructor(detection: FaceDetection, unshiftedLandmarks: TFaceLandmarks);
-    readonly detection: FaceDetection;
-    readonly unshiftedLandmarks: TFaceLandmarks;
-    readonly alignedRect: FaceDetection;
-    readonly landmarks: TFaceLandmarks;
-    readonly faceDetection: FaceDetection;
-    readonly faceLandmarks: TFaceLandmarks;
-    forSize(width: number, height: number): FaceDetectionWithLandmarks<TFaceLandmarks>;
-}

build/commonjs/classes/FaceDetectionWithLandmarks.js

-"use strict";
-Object.defineProperty(exports, "__esModule", { value: true });
-var FaceDetection_1 = require("./FaceDetection");
-var FaceDetectionWithLandmarks = /** @class */ (function () {
-    function FaceDetectionWithLandmarks(detection, unshiftedLandmarks) {
-        this._detection = detection;
-        this._unshiftedLandmarks = unshiftedLandmarks;
-    }
-    Object.defineProperty(FaceDetectionWithLandmarks.prototype, "detection", {
-        get: function () { return this._detection; },
-        enumerable: true,
-        configurable: true
-    });
-    Object.defineProperty(FaceDetectionWithLandmarks.prototype, "unshiftedLandmarks", {
-        get: function () { return this._unshiftedLandmarks; },
-        enumerable: true,
-        configurable: true
-    });
-    Object.defineProperty(FaceDetectionWithLandmarks.prototype, "alignedRect", {
-        get: function () {
-            var rect = this.landmarks.align();
-            var imageDims = this.detection.imageDims;
-            return new FaceDetection_1.FaceDetection(this._detection.score, rect.rescale(imageDims.reverse()), imageDims);
-        },
-        enumerable: true,
-        configurable: true
-    });
-    Object.defineProperty(FaceDetectionWithLandmarks.prototype, "landmarks", {
-        get: function () {
-            var _a = this.detection.box, x = _a.x, y = _a.y;
-            return this._unshiftedLandmarks.shiftBy(x, y);
-        },
-        enumerable: true,
-        configurable: true
-    });
-    Object.defineProperty(FaceDetectionWithLandmarks.prototype, "faceDetection", {
-        // aliases for backward compatibily
-        get: function () { return this.detection; },
-        enumerable: true,
-        configurable: true
-    });
-    Object.defineProperty(FaceDetectionWithLandmarks.prototype, "faceLandmarks", {
-        get: function () { return this.landmarks; },
-        enumerable: true,
-        configurable: true
-    });
-    FaceDetectionWithLandmarks.prototype.forSize = function (width, height) {
-        var resizedDetection = this._detection.forSize(width, height);
-        var resizedLandmarks = this._unshiftedLandmarks.forSize(resizedDetection.box.width, resizedDetection.box.height);
-        return new FaceDetectionWithLandmarks(resizedDetection, resizedLandmarks);
-    };
-    return FaceDetectionWithLandmarks;
-}());
-exports.FaceDetectionWithLandmarks = FaceDetectionWithLandmarks;
-//# sourceMappingURL=FaceDetectionWithLandmarks.js.map
\ No newline at end of file

build/commonjs/classes/FaceDetectionWithLandmarks.js.map

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\ No newline at end of file

build/commonjs/classes/FullFaceDescription.d.ts

-import { FaceDetection } from './FaceDetection';
-import { FaceDetectionWithLandmarks, IFaceDetectionWithLandmarks } from './FaceDetectionWithLandmarks';
-import { FaceLandmarks } from './FaceLandmarks';
-import { FaceLandmarks68 } from './FaceLandmarks68';
-export interface IFullFaceDescription<TFaceLandmarks extends FaceLandmarks = FaceLandmarks68> extends IFaceDetectionWithLandmarks<TFaceLandmarks> {
-    detection: FaceDetection;
-    landmarks: TFaceLandmarks;
-    descriptor: Float32Array;
-}
-export declare class FullFaceDescription<TFaceLandmarks extends FaceLandmarks = FaceLandmarks68> extends FaceDetectionWithLandmarks<TFaceLandmarks> implements IFullFaceDescription<TFaceLandmarks> {
-    private _descriptor;
-    constructor(detection: FaceDetection, unshiftedLandmarks: TFaceLandmarks, descriptor: Float32Array);
-    readonly descriptor: Float32Array;
-    forSize(width: number, height: number): FullFaceDescription<TFaceLandmarks>;
-}

build/commonjs/classes/FullFaceDescription.js

-"use strict";
-Object.defineProperty(exports, "__esModule", { value: true });
-var tslib_1 = require("tslib");
-var FaceDetectionWithLandmarks_1 = require("./FaceDetectionWithLandmarks");
-var FullFaceDescription = /** @class */ (function (_super) {
-    tslib_1.__extends(FullFaceDescription, _super);
-    function FullFaceDescription(detection, unshiftedLandmarks, descriptor) {
-        var _this = _super.call(this, detection, unshiftedLandmarks) || this;
-        _this._descriptor = descriptor;
-        return _this;
-    }
-    Object.defineProperty(FullFaceDescription.prototype, "descriptor", {
-        get: function () {
-            return this._descriptor;
-        },
-        enumerable: true,
-        configurable: true
-    });
-    FullFaceDescription.prototype.forSize = function (width, height) {
-        var _a = _super.prototype.forSize.call(this, width, height), detection = _a.detection, landmarks = _a.landmarks;
-        return new FullFaceDescription(detection, landmarks, this.descriptor);
-    };
-    return FullFaceDescription;
-}(FaceDetectionWithLandmarks_1.FaceDetectionWithLandmarks));
-exports.FullFaceDescription = FullFaceDescription;
-//# sourceMappingURL=FullFaceDescription.js.map
\ No newline at end of file

build/commonjs/classes/FullFaceDescription.js.map

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\ No newline at end of file

build/commonjs/classes/index.d.ts

 export * from './FaceDetection';
-export * from './FaceDetectionWithLandmarks';
 export * from './FaceLandmarks';
 export * from './FaceLandmarks5';
 export * from './FaceLandmarks68';
 export * from './FaceMatch';
-export * from './FullFaceDescription';
 export * from './LabeledFaceDescriptors';

build/commonjs/classes/index.js

@@ -2,11 +2,9 @@
 Object.defineProperty(exports, "__esModule", { value: true });
 var tslib_1 = require("tslib");
 tslib_1.__exportStar(require("./FaceDetection"), exports);
-tslib_1.__exportStar(require("./FaceDetectionWithLandmarks"), exports);
 tslib_1.__exportStar(require("./FaceLandmarks"), exports);
 tslib_1.__exportStar(require("./FaceLandmarks5"), exports);
 tslib_1.__exportStar(require("./FaceLandmarks68"), exports);
 tslib_1.__exportStar(require("./FaceMatch"), exports);
-tslib_1.__exportStar(require("./FullFaceDescription"), exports);
 tslib_1.__exportStar(require("./LabeledFaceDescriptors"), exports);
 //# sourceMappingURL=index.js.map
\ No newline at end of file

build/commonjs/classes/index.js.map

-{"version":3,"file":"index.js","sourceRoot":"","sources":["../../../src/classes/index.ts"],"names":[],"mappings":";;;AAAA,0DAAgC;AAChC,uEAA6C;AAC7C,0DAAgC;AAChC,2DAAiC;AACjC,4DAAkC;AAClC,sDAA4B;AAC5B,gEAAsC;AACtC,mEAAyC"}
+{"version":3,"file":"index.js","sourceRoot":"","sources":["../../../src/classes/index.ts"],"names":[],"mappings":";;;AAAA,0DAAgC;AAChC,0DAAgC;AAChC,2DAAiC;AACjC,4DAAkC;AAClC,sDAA4B;AAC5B,mEAAyC"}
\ No newline at end of file

build/commonjs/common/fullyConnectedLayer.js.map

+{"version":3,"file":"fullyConnectedLayer.js","sourceRoot":"","sources":["../../../src/common/fullyConnectedLayer.ts"],"names":[],"mappings":";;AAAA,0CAA4C;AAG5C,6BACE,CAAc,EACd,MAAgB;IAEhB,OAAO,EAAE,CAAC,IAAI,CAAC;QACb,OAAA,EAAE,CAAC,GAAG,CACJ,EAAE,CAAC,MAAM,CAAC,CAAC,EAAE,MAAM,CAAC,OAAO,CAAC,EAC5B,MAAM,CAAC,IAAI,CACZ;IAHD,CAGC,CACF,CAAA;AACH,CAAC;AAVD,kDAUC"}
\ 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

+{"version":3,"file":"drawFaceExpressions.js","sourceRoot":"","sources":["../../../src/dom/drawFaceExpressions.ts"],"names":[],"mappings":";;AAAA,2EAA6H;AAK7H,6BACE,SAAqC,EACrC,eAAsE,EACtE,OAAoC;IAEpC,IAAM,MAAM,GAAG,0CAAY,CAAC,SAAS,CAAC,CAAA;IACtC,IAAI,CAAC,CAAC,MAAM,YAAY,iCAAG,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,mDAAqB,CAAC,OAAO,CAAC,EAC9B,CAAC,OAAO,IAAI,EAAE,CAAC,CAChB,CAAA;IAED,IAAM,GAAG,GAAG,iDAAmB,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,mCAAK,CAAC,IAAI,CAAC,WAAW,CAAC,MAAG,CAAA;YAC9D,sCAAQ,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;AArDD,kDAqDC"}
\ 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

@@ -3,6 +3,7 @@ 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

-{"version":3,"file":"index.js","sourceRoot":"","sources":["../../../src/dom/index.ts"],"names":[],"mappings":";;;AAAA,wDAA6B;AAC7B,0DAA+B;AAC/B,yDAA8B;AAC9B,+DAAoC"}
+{"version":3,"file":"index.js","sourceRoot":"","sources":["../../../src/dom/index.ts"],"names":[],"mappings":";;;AAAA,wDAA6B;AAC7B,0DAA+B;AAC/B,gEAAqC;AACrC,yDAA8B;AAC9B,+DAAoC"}
\ No newline at end of file

build/commonjs/dom/types.d.ts

+import { IPoint, IRect } from 'tfjs-tiny-yolov2';
+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/faceExpressionNet/FaceExpressionNet.d.ts

+import * as tf from '@tensorflow/tfjs-core';
+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';
+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[][]>;
+    protected getDefaultModelName(): string;
+    protected getClassifierChannelsIn(): number;
+    protected getClassifierChannelsOut(): number;
+}

build/commonjs/faceExpressionNet/FaceExpressionNet.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 FaceFeatureExtractor_1 = require("../faceFeatureExtractor/FaceFeatureExtractor");
+var FaceProcessor_1 = require("../faceProcessor/FaceProcessor");
+var types_1 = require("./types");
+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)); });
+    };
+    FaceExpressionNet.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()])];
+                }
+            });
+        });
+    };
+    FaceExpressionNet.prototype.predictExpressions = function (input) {
+        return tslib_1.__awaiter(this, void 0, void 0, function () {
+            var _this = this;
+            var netInput, out, probabilitesByBatch, predictionsByBatch;
+            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();
+                        return [4 /*yield*/, Promise.all(tf.unstack(out).map(function (t) { return tslib_1.__awaiter(_this, void 0, void 0, function () {
+                                var data;
+                                return tslib_1.__generator(this, function (_a) {
+                                    switch (_a.label) {
+                                        case 0: return [4 /*yield*/, t.data()];
+                                        case 1:
+                                            data = _a.sent();
+                                            t.dispose();
+                                            return [2 /*return*/, data];
+                                    }
+                                });
+                            }); }))];
+                    case 3:
+                        probabilitesByBatch = _a.sent();
+                        out.dispose();
+                        predictionsByBatch = probabilitesByBatch
+                            .map(function (propablities) { return FaceExpressionNet.decodeProbabilites(propablities); });
+                        return [2 /*return*/, netInput.isBatchInput
+                                ? predictionsByBatch
+                                : predictionsByBatch[0]];
+                }
+            });
+        });
+    };
+    FaceExpressionNet.prototype.getDefaultModelName = function () {
+        return 'face_expression_model';
+    };
+    FaceExpressionNet.prototype.getClassifierChannelsIn = function () {
+        return 256;
+    };
+    FaceExpressionNet.prototype.getClassifierChannelsOut = function () {
+        return 7;
+    };
+    return FaceExpressionNet;
+}(FaceProcessor_1.FaceProcessor));
+exports.FaceExpressionNet = FaceExpressionNet;
+//# sourceMappingURL=FaceExpressionNet.js.map
\ No newline at end of file

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"}
\ No newline at end of file

build/commonjs/faceExpressionNet/index.d.ts

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

build/commonjs/faceExpressionNet/index.js

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

build/commonjs/faceExpressionNet/types.d.ts

+export declare const faceExpressionLabels: {
+    neutral: number;
+    happy: number;
+    sad: number;
+    angry: number;
+    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;
+};

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

+{"version":3,"file":"types.js","sourceRoot":"","sources":["../../../src/faceExpressionNet/types.ts"],"names":[],"mappings":";;AAAa,QAAA,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/commonjs/faceFeatureExtractor/FaceFeatureExtractor.d.ts

+import * as tf from '@tensorflow/tfjs-core';
+import { NetInput, NeuralNetwork, TNetInput } from 'tfjs-image-recognition-base';
+import { FaceFeatureExtractorParams, IFaceFeatureExtractor } from './types';
+export declare class FaceFeatureExtractor extends NeuralNetwork<FaceFeatureExtractorParams> implements IFaceFeatureExtractor<FaceFeatureExtractorParams> {
+    constructor();
+    forwardInput(input: NetInput): tf.Tensor4D;
+    forward(input: TNetInput): Promise<tf.Tensor4D>;
+    protected getDefaultModelName(): string;
+    protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap): {
+        params: FaceFeatureExtractorParams;
+        paramMappings: {
+            originalPath?: string | undefined;
+            paramPath: string;
+        }[];
+    };
+    protected extractParams(weights: Float32Array): {
+        params: FaceFeatureExtractorParams;
+        paramMappings: {
+            originalPath?: string | undefined;
+            paramPath: string;
+        }[];
+    };
+}

build/commonjs/faceFeatureExtractor/FaceFeatureExtractor.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 denseBlock_1 = require("./denseBlock");
+var extractParams_1 = require("./extractParams");
+var extractParamsFromWeigthMap_1 = require("./extractParamsFromWeigthMap");
+var FaceFeatureExtractor = /** @class */ (function (_super) {
+    tslib_1.__extends(FaceFeatureExtractor, _super);
+    function FaceFeatureExtractor() {
+        return _super.call(this, 'FaceFeatureExtractor') || this;
+    }
+    FaceFeatureExtractor.prototype.forwardInput = function (input) {
+        var params = this.params;
+        if (!params) {
+            throw new Error('FaceFeatureExtractor - 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(255));
+            var out = denseBlock_1.denseBlock4(normalized, params.dense0, true);
+            out = denseBlock_1.denseBlock4(out, params.dense1);
+            out = denseBlock_1.denseBlock4(out, params.dense2);
+            out = denseBlock_1.denseBlock4(out, params.dense3);
+            out = tf.avgPool(out, [7, 7], [2, 2], 'valid');
+            return out;
+        });
+    };
+    FaceFeatureExtractor.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()])];
+                }
+            });
+        });
+    };
+    FaceFeatureExtractor.prototype.getDefaultModelName = function () {
+        return 'face_feature_extractor_model';
+    };
+    FaceFeatureExtractor.prototype.extractParamsFromWeigthMap = function (weightMap) {
+        return extractParamsFromWeigthMap_1.extractParamsFromWeigthMap(weightMap);
+    };
+    FaceFeatureExtractor.prototype.extractParams = function (weights) {
+        return extractParams_1.extractParams(weights);
+    };
+    return FaceFeatureExtractor;
+}(tfjs_image_recognition_base_1.NeuralNetwork));
+exports.FaceFeatureExtractor = FaceFeatureExtractor;
+//# sourceMappingURL=FaceFeatureExtractor.js.map
\ No newline at end of file

build/commonjs/faceFeatureExtractor/FaceFeatureExtractor.js.map

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\ No newline at end of file

build/commonjs/faceFeatureExtractor/TinyFaceFeatureExtractor.d.ts

+import * as tf from '@tensorflow/tfjs-core';
+import { NetInput, NeuralNetwork, TNetInput } from 'tfjs-image-recognition-base';
+import { IFaceFeatureExtractor, TinyFaceFeatureExtractorParams } from './types';
+export declare class TinyFaceFeatureExtractor extends NeuralNetwork<TinyFaceFeatureExtractorParams> implements IFaceFeatureExtractor<TinyFaceFeatureExtractorParams> {
+    constructor();
+    forwardInput(input: NetInput): tf.Tensor4D;
+    forward(input: TNetInput): Promise<tf.Tensor4D>;
+    protected getDefaultModelName(): string;
+    protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap): {
+        params: TinyFaceFeatureExtractorParams;
+        paramMappings: {
+            originalPath?: string | undefined;
+            paramPath: string;
+        }[];
+    };
+    protected extractParams(weights: Float32Array): {
+        params: TinyFaceFeatureExtractorParams;
+        paramMappings: {
+            originalPath?: string | undefined;
+            paramPath: string;
+        }[];
+    };
+}

build/commonjs/faceFeatureExtractor/TinyFaceFeatureExtractor.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 denseBlock_1 = require("./denseBlock");
+var extractParamsFromWeigthMapTiny_1 = require("./extractParamsFromWeigthMapTiny");
+var extractParamsTiny_1 = require("./extractParamsTiny");
+var TinyFaceFeatureExtractor = /** @class */ (function (_super) {
+    tslib_1.__extends(TinyFaceFeatureExtractor, _super);
+    function TinyFaceFeatureExtractor() {
+        return _super.call(this, 'TinyFaceFeatureExtractor') || this;
+    }
+    TinyFaceFeatureExtractor.prototype.forwardInput = function (input) {
+        var params = this.params;
+        if (!params) {
+            throw new Error('TinyFaceFeatureExtractor - 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(255));
+            var out = denseBlock_1.denseBlock3(normalized, params.dense0, true);
+            out = denseBlock_1.denseBlock3(out, params.dense1);
+            out = denseBlock_1.denseBlock3(out, params.dense2);
+            out = tf.avgPool(out, [14, 14], [2, 2], 'valid');
+            return out;
+        });
+    };
+    TinyFaceFeatureExtractor.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()])];
+                }
+            });
+        });
+    };
+    TinyFaceFeatureExtractor.prototype.getDefaultModelName = function () {
+        return 'face_feature_extractor_tiny_model';
+    };
+    TinyFaceFeatureExtractor.prototype.extractParamsFromWeigthMap = function (weightMap) {
+        return extractParamsFromWeigthMapTiny_1.extractParamsFromWeigthMapTiny(weightMap);
+    };
+    TinyFaceFeatureExtractor.prototype.extractParams = function (weights) {
+        return extractParamsTiny_1.extractParamsTiny(weights);
+    };
+    return TinyFaceFeatureExtractor;
+}(tfjs_image_recognition_base_1.NeuralNetwork));
+exports.TinyFaceFeatureExtractor = TinyFaceFeatureExtractor;
+//# sourceMappingURL=TinyFaceFeatureExtractor.js.map
\ No newline at end of file

build/commonjs/faceFeatureExtractor/TinyFaceFeatureExtractor.js.map

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\ No newline at end of file

build/commonjs/faceFeatureExtractor/denseBlock.d.ts

+import * as tf from '@tensorflow/tfjs-core';
+import { DenseBlock3Params, DenseBlock4Params } from './types';
+export declare function denseBlock3(x: tf.Tensor4D, denseBlockParams: DenseBlock3Params, isFirstLayer?: boolean): tf.Tensor4D;
+export declare function denseBlock4(x: tf.Tensor4D, denseBlockParams: DenseBlock4Params, isFirstLayer?: boolean, isScaleDown?: boolean): tf.Tensor4D;

build/commonjs/faceFeatureExtractor/denseBlock.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+var tf = require("@tensorflow/tfjs-core");
+var depthwiseSeparableConv_1 = require("./depthwiseSeparableConv");
+function denseBlock3(x, denseBlockParams, isFirstLayer) {
+    if (isFirstLayer === void 0) { isFirstLayer = false; }
+    return tf.tidy(function () {
+        var out1 = tf.relu(isFirstLayer
+            ? tf.add(tf.conv2d(x, denseBlockParams.conv0.filters, [2, 2], 'same'), denseBlockParams.conv0.bias)
+            : depthwiseSeparableConv_1.depthwiseSeparableConv(x, denseBlockParams.conv0, [2, 2]));
+        var out2 = depthwiseSeparableConv_1.depthwiseSeparableConv(out1, denseBlockParams.conv1, [1, 1]);
+        var in3 = tf.relu(tf.add(out1, out2));
+        var out3 = depthwiseSeparableConv_1.depthwiseSeparableConv(in3, denseBlockParams.conv2, [1, 1]);
+        return tf.relu(tf.add(out1, tf.add(out2, out3)));
+    });
+}
+exports.denseBlock3 = denseBlock3;
+function denseBlock4(x, denseBlockParams, isFirstLayer, isScaleDown) {
+    if (isFirstLayer === void 0) { isFirstLayer = false; }
+    if (isScaleDown === void 0) { isScaleDown = true; }
+    return tf.tidy(function () {
+        var out1 = tf.relu(isFirstLayer
+            ? tf.add(tf.conv2d(x, denseBlockParams.conv0.filters, isScaleDown ? [2, 2] : [1, 1], 'same'), denseBlockParams.conv0.bias)
+            : depthwiseSeparableConv_1.depthwiseSeparableConv(x, denseBlockParams.conv0, isScaleDown ? [2, 2] : [1, 1]));
+        var out2 = depthwiseSeparableConv_1.depthwiseSeparableConv(out1, denseBlockParams.conv1, [1, 1]);
+        var in3 = tf.relu(tf.add(out1, out2));
+        var out3 = depthwiseSeparableConv_1.depthwiseSeparableConv(in3, denseBlockParams.conv2, [1, 1]);
+        var in4 = tf.relu(tf.add(out1, tf.add(out2, out3)));
+        var out4 = depthwiseSeparableConv_1.depthwiseSeparableConv(in4, denseBlockParams.conv3, [1, 1]);
+        return tf.relu(tf.add(out1, tf.add(out2, tf.add(out3, out4))));
+    });
+}
+exports.denseBlock4 = denseBlock4;
+//# sourceMappingURL=denseBlock.js.map
\ No newline at end of file

build/commonjs/faceFeatureExtractor/denseBlock.js.map

+{"version":3,"file":"denseBlock.js","sourceRoot":"","sources":["../../../src/faceFeatureExtractor/denseBlock.ts"],"names":[],"mappings":";;AAAA,0CAA4C;AAG5C,mEAAkE;AAGlE,qBACE,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,KAAoB,CAAC,OAAO,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,MAAM,CAAC,EAC5E,gBAAgB,CAAC,KAAK,CAAC,IAAI,CAC5B;YACD,CAAC,CAAC,+CAAsB,CAAC,CAAC,EAAE,gBAAgB,CAAC,KAA4B,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CACtE,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,qBACE,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,KAAoB,CAAC,OAAO,EAAE,WAAW,CAAC,CAAC,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,MAAM,CAAC,EACnG,gBAAgB,CAAC,KAAK,CAAC,IAAI,CAC5B;YACD,CAAC,CAAC,+CAAsB,CAAC,CAAC,EAAE,gBAAgB,CAAC,KAA4B,EAAE,WAAW,CAAC,CAAC,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAC7F,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,gCACE,CAAc,EACd,MAA2B,EAC3B,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/extractParams.d.ts

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

build/commonjs/faceLandmarkNet/extractParams.js → build/commonjs/faceFeatureExtractor/extractParams.js

@@ -5,18 +5,17 @@ var extractorsFactory_1 = require("./extractorsFactory");
 function extractParams(weights) {
     var paramMappings = [];
     var _a = tfjs_image_recognition_base_1.extractWeightsFactory(weights), extractWeights = _a.extractWeights, getRemainingWeights = _a.getRemainingWeights;
-    var _b = extractorsFactory_1.extractorsFactory(extractWeights, paramMappings), extractDenseBlock4Params = _b.extractDenseBlock4Params, extractFCParams = _b.extractFCParams;
+    var extractDenseBlock4Params = extractorsFactory_1.extractorsFactory(extractWeights, paramMappings).extractDenseBlock4Params;
     var dense0 = extractDenseBlock4Params(3, 32, 'dense0', true);
     var dense1 = extractDenseBlock4Params(32, 64, 'dense1');
     var dense2 = extractDenseBlock4Params(64, 128, 'dense2');
     var dense3 = extractDenseBlock4Params(128, 256, 'dense3');
-    var fc = extractFCParams(256, 136, 'fc');
     if (getRemainingWeights().length !== 0) {
         throw new Error("weights remaing after extract: " + getRemainingWeights().length);
     }
     return {
         paramMappings: paramMappings,
-        params: { dense0: dense0, dense1: dense1, dense2: dense2, dense3: dense3, fc: fc }
+        params: { dense0: dense0, dense1: dense1, dense2: dense2, dense3: dense3 }
     };
 }
 exports.extractParams = extractParams;

build/commonjs/faceFeatureExtractor/extractParams.js.map

+{"version":3,"file":"extractParams.js","sourceRoot":"","sources":["../../../src/faceFeatureExtractor/extractParams.ts"],"names":[],"mappings":";;AAAA,2EAAkF;AAElF,yDAAwD;AAGxD,uBAA8B,OAAqB;IAEjD,IAAM,aAAa,GAAmB,EAAE,CAAA;IAElC,IAAA,iEAG4B,EAFhC,kCAAc,EACd,4CAAmB,CACa;IAGhC,IAAA,wHAAwB,CAC0B;IAEpD,IAAM,MAAM,GAAG,wBAAwB,CAAC,CAAC,EAAE,EAAE,EAAE,QAAQ,EAAE,IAAI,CAAC,CAAA;IAC9D,IAAM,MAAM,GAAG,wBAAwB,CAAC,EAAE,EAAE,EAAE,EAAE,QAAQ,CAAC,CAAA;IACzD,IAAM,MAAM,GAAG,wBAAwB,CAAC,EAAE,EAAE,GAAG,EAAE,QAAQ,CAAC,CAAA;IAC1D,IAAM,MAAM,GAAG,wBAAwB,CAAC,GAAG,EAAE,GAAG,EAAE,QAAQ,CAAC,CAAA;IAE3D,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,MAAM,QAAA,EAAE,MAAM,QAAA,EAAE,MAAM,QAAA,EAAE,MAAM,QAAA,EAAE;KAC3C,CAAA;AACH,CAAC;AA1BD,sCA0BC"}
\ No newline at end of file

build/commonjs/faceFeatureExtractor/extractParamsFromWeigthMap.d.ts

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

build/commonjs/faceLandmarkNet/extractParamsFromWeigthMap.js → build/commonjs/faceFeatureExtractor/extractParamsFromWeigthMap.js

@@ -4,13 +4,12 @@ var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
 var loadParamsFactory_1 = require("./loadParamsFactory");
 function extractParamsFromWeigthMap(weightMap) {
     var paramMappings = [];
-    var _a = loadParamsFactory_1.loadParamsFactory(weightMap, paramMappings), extractDenseBlock4Params = _a.extractDenseBlock4Params, extractFcParams = _a.extractFcParams;
+    var extractDenseBlock4Params = loadParamsFactory_1.loadParamsFactory(weightMap, paramMappings).extractDenseBlock4Params;
     var params = {
         dense0: extractDenseBlock4Params('dense0', true),
         dense1: extractDenseBlock4Params('dense1'),
         dense2: extractDenseBlock4Params('dense2'),
-        dense3: extractDenseBlock4Params('dense3'),
-        fc: extractFcParams('fc')
+        dense3: extractDenseBlock4Params('dense3')
     };
     tfjs_image_recognition_base_1.disposeUnusedWeightTensors(weightMap, paramMappings);
     return { params: params, paramMappings: paramMappings };

build/commonjs/faceFeatureExtractor/extractParamsFromWeigthMap.js.map

+{"version":3,"file":"extractParamsFromWeigthMap.js","sourceRoot":"","sources":["../../../src/faceFeatureExtractor/extractParamsFromWeigthMap.ts"],"names":[],"mappings":";;AACA,2EAAuF;AAEvF,yDAAwD;AAGxD,oCACE,SAA4B;IAG5B,IAAM,aAAa,GAAmB,EAAE,CAAA;IAGtC,IAAA,mHAAwB,CACqB;IAE/C,IAAM,MAAM,GAAG;QACb,MAAM,EAAE,wBAAwB,CAAC,QAAQ,EAAE,IAAI,CAAC;QAChD,MAAM,EAAE,wBAAwB,CAAC,QAAQ,CAAC;QAC1C,MAAM,EAAE,wBAAwB,CAAC,QAAQ,CAAC;QAC1C,MAAM,EAAE,wBAAwB,CAAC,QAAQ,CAAC;KAC3C,CAAA;IAED,wDAA0B,CAAC,SAAS,EAAE,aAAa,CAAC,CAAA;IAEpD,OAAO,EAAE,MAAM,QAAA,EAAE,aAAa,eAAA,EAAE,CAAA;AAClC,CAAC;AApBD,gEAoBC"}
\ No newline at end of file

build/commonjs/faceLandmarkNet/extractParamsFromWeigthMapTiny.d.ts → build/commonjs/faceFeatureExtractor/extractParamsFromWeigthMapTiny.d.ts

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

build/commonjs/faceLandmarkNet/extractParamsFromWeigthMapTiny.js → build/commonjs/faceFeatureExtractor/extractParamsFromWeigthMapTiny.js

@@ -4,12 +4,11 @@ var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
 var loadParamsFactory_1 = require("./loadParamsFactory");
 function extractParamsFromWeigthMapTiny(weightMap) {
     var paramMappings = [];
-    var _a = loadParamsFactory_1.loadParamsFactory(weightMap, paramMappings), extractDenseBlock3Params = _a.extractDenseBlock3Params, extractFcParams = _a.extractFcParams;
+    var extractDenseBlock3Params = loadParamsFactory_1.loadParamsFactory(weightMap, paramMappings).extractDenseBlock3Params;
     var params = {
         dense0: extractDenseBlock3Params('dense0', true),
         dense1: extractDenseBlock3Params('dense1'),
-        dense2: extractDenseBlock3Params('dense2'),
-        fc: extractFcParams('fc')
+        dense2: extractDenseBlock3Params('dense2')
     };
     tfjs_image_recognition_base_1.disposeUnusedWeightTensors(weightMap, paramMappings);
     return { params: params, paramMappings: paramMappings };

build/commonjs/faceFeatureExtractor/extractParamsFromWeigthMapTiny.js.map

+{"version":3,"file":"extractParamsFromWeigthMapTiny.js","sourceRoot":"","sources":["../../../src/faceFeatureExtractor/extractParamsFromWeigthMapTiny.ts"],"names":[],"mappings":";;AACA,2EAAuF;AAEvF,yDAAwD;AAGxD,wCACE,SAA4B;IAG5B,IAAM,aAAa,GAAmB,EAAE,CAAA;IAGtC,IAAA,mHAAwB,CACqB;IAE/C,IAAM,MAAM,GAAG;QACb,MAAM,EAAE,wBAAwB,CAAC,QAAQ,EAAE,IAAI,CAAC;QAChD,MAAM,EAAE,wBAAwB,CAAC,QAAQ,CAAC;QAC1C,MAAM,EAAE,wBAAwB,CAAC,QAAQ,CAAC;KAC3C,CAAA;IAED,wDAA0B,CAAC,SAAS,EAAE,aAAa,CAAC,CAAA;IAEpD,OAAO,EAAE,MAAM,QAAA,EAAE,aAAa,eAAA,EAAE,CAAA;AAClC,CAAC;AAnBD,wEAmBC"}
\ No newline at end of file

build/commonjs/faceLandmarkNet/extractParamsTiny.d.ts → build/commonjs/faceFeatureExtractor/extractParamsTiny.d.ts

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

build/commonjs/faceLandmarkNet/extractParamsTiny.js → build/commonjs/faceFeatureExtractor/extractParamsTiny.js

@@ -5,17 +5,16 @@ var extractorsFactory_1 = require("./extractorsFactory");
 function extractParamsTiny(weights) {
     var paramMappings = [];
     var _a = tfjs_image_recognition_base_1.extractWeightsFactory(weights), extractWeights = _a.extractWeights, getRemainingWeights = _a.getRemainingWeights;
-    var _b = extractorsFactory_1.extractorsFactory(extractWeights, paramMappings), extractDenseBlock3Params = _b.extractDenseBlock3Params, extractFCParams = _b.extractFCParams;
+    var extractDenseBlock3Params = extractorsFactory_1.extractorsFactory(extractWeights, paramMappings).extractDenseBlock3Params;
     var dense0 = extractDenseBlock3Params(3, 32, 'dense0', true);
     var dense1 = extractDenseBlock3Params(32, 64, 'dense1');
     var dense2 = extractDenseBlock3Params(64, 128, 'dense2');
-    var fc = extractFCParams(128, 136, 'fc');
     if (getRemainingWeights().length !== 0) {
         throw new Error("weights remaing after extract: " + getRemainingWeights().length);
     }
     return {
         paramMappings: paramMappings,
-        params: { dense0: dense0, dense1: dense1, dense2: dense2, fc: fc }
+        params: { dense0: dense0, dense1: dense1, dense2: dense2 }
     };
 }
 exports.extractParamsTiny = extractParamsTiny;

build/commonjs/faceFeatureExtractor/extractParamsTiny.js.map

+{"version":3,"file":"extractParamsTiny.js","sourceRoot":"","sources":["../../../src/faceFeatureExtractor/extractParamsTiny.ts"],"names":[],"mappings":";;AAAA,2EAAkF;AAElF,yDAAwD;AAGxD,2BAAkC,OAAqB;IAErD,IAAM,aAAa,GAAmB,EAAE,CAAA;IAElC,IAAA,iEAG4B,EAFhC,kCAAc,EACd,4CAAmB,CACa;IAGhC,IAAA,wHAAwB,CAC0B;IAEpD,IAAM,MAAM,GAAG,wBAAwB,CAAC,CAAC,EAAE,EAAE,EAAE,QAAQ,EAAE,IAAI,CAAC,CAAA;IAC9D,IAAM,MAAM,GAAG,wBAAwB,CAAC,EAAE,EAAE,EAAE,EAAE,QAAQ,CAAC,CAAA;IACzD,IAAM,MAAM,GAAG,wBAAwB,CAAC,EAAE,EAAE,GAAG,EAAE,QAAQ,CAAC,CAAA;IAE1D,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,MAAM,QAAA,EAAE,MAAM,QAAA,EAAE,MAAM,QAAA,EAAE;KACnC,CAAA;AACH,CAAC;AAzBD,8CAyBC"}
\ No newline at end of file

build/commonjs/faceLandmarkNet/extractorsFactory.d.ts → build/commonjs/faceFeatureExtractor/extractorsFactory.d.ts

 import { ExtractWeightsFunction, ParamMapping } from 'tfjs-image-recognition-base';
-import { FCParams } from 'tfjs-tiny-yolov2';
 import { DenseBlock3Params, DenseBlock4Params } from './types';
 export declare function extractorsFactory(extractWeights: ExtractWeightsFunction, paramMappings: ParamMapping[]): {
     extractDenseBlock3Params: (channelsIn: number, channelsOut: number, mappedPrefix: string, isFirstLayer?: boolean) => DenseBlock3Params;
     extractDenseBlock4Params: (channelsIn: number, channelsOut: number, mappedPrefix: string, isFirstLayer?: boolean) => DenseBlock4Params;
-    extractFCParams: (channelsIn: number, channelsOut: number, mappedPrefix: string) => FCParams;
 };

build/commonjs/faceLandmarkNet/extractorsFactory.js → build/commonjs/faceFeatureExtractor/extractorsFactory.js

@@ -10,15 +10,6 @@ function extractorsFactory(extractWeights, paramMappings) {
         paramMappings.push({ paramPath: mappedPrefix + "/depthwise_filter" }, { paramPath: mappedPrefix + "/pointwise_filter" }, { paramPath: mappedPrefix + "/bias" });
         return new tfjs_tiny_yolov2_1.SeparableConvParams(depthwise_filter, pointwise_filter, bias);
     }
-    function extractFCParams(channelsIn, channelsOut, mappedPrefix) {
-        var weights = tf.tensor2d(extractWeights(channelsIn * channelsOut), [channelsIn, channelsOut]);
-        var bias = tf.tensor1d(extractWeights(channelsOut));
-        paramMappings.push({ paramPath: mappedPrefix + "/weights" }, { paramPath: mappedPrefix + "/bias" });
-        return {
-            weights: weights,
-            bias: bias
-        };
-    }
     var extractConvParams = tfjs_tiny_yolov2_1.extractConvParamsFactory(extractWeights, paramMappings);
     function extractDenseBlock3Params(channelsIn, channelsOut, mappedPrefix, isFirstLayer) {
         if (isFirstLayer === void 0) { isFirstLayer = false; }
@@ -37,8 +28,7 @@ function extractorsFactory(extractWeights, paramMappings) {
     }
     return {
         extractDenseBlock3Params: extractDenseBlock3Params,
-        extractDenseBlock4Params: extractDenseBlock4Params,
-        extractFCParams: extractFCParams
+        extractDenseBlock4Params: extractDenseBlock4Params
     };
 }
 exports.extractorsFactory = extractorsFactory;

build/commonjs/faceFeatureExtractor/extractorsFactory.js.map

+{"version":3,"file":"extractorsFactory.js","sourceRoot":"","sources":["../../../src/faceFeatureExtractor/extractorsFactory.ts"],"names":[],"mappings":";;AAAA,0CAA4C;AAE5C,qDAA2F;AAI3F,2BAAkC,cAAsC,EAAE,aAA6B;IAErG,oCAAoC,UAAkB,EAAE,WAAmB,EAAE,YAAoB;QAC/F,IAAM,gBAAgB,GAAG,EAAE,CAAC,QAAQ,CAAC,cAAc,CAAC,CAAC,GAAG,CAAC,GAAG,UAAU,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,EAAE,UAAU,EAAE,CAAC,CAAC,CAAC,CAAA;QAC/F,IAAM,gBAAgB,GAAG,EAAE,CAAC,QAAQ,CAAC,cAAc,CAAC,UAAU,GAAG,WAAW,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,EAAE,UAAU,EAAE,WAAW,CAAC,CAAC,CAAA;QAC/G,IAAM,IAAI,GAAG,EAAE,CAAC,QAAQ,CAAC,cAAc,CAAC,WAAW,CAAC,CAAC,CAAA;QAErD,aAAa,CAAC,IAAI,CAChB,EAAE,SAAS,EAAK,YAAY,sBAAmB,EAAE,EACjD,EAAE,SAAS,EAAK,YAAY,sBAAmB,EAAE,EACjD,EAAE,SAAS,EAAK,YAAY,UAAO,EAAE,CACtC,CAAA;QAED,OAAO,IAAI,sCAAmB,CAC5B,gBAAgB,EAChB,gBAAgB,EAChB,IAAI,CACL,CAAA;IACH,CAAC;IAED,IAAM,iBAAiB,GAAG,2CAAwB,CAAC,cAAc,EAAE,aAAa,CAAC,CAAA;IAEjF,kCAAkC,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,kCAAkC,UAAkB,EAAE,WAAmB,EAAE,YAAoB,EAAE,YAA6B;QAA7B,6BAAA,EAAA,oBAA6B;QAEtH,IAAA,kFAAuG,EAArG,gBAAK,EAAE,gBAAK,EAAE,gBAAK,CAAkF;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;AA9CD,8CA8CC"}
\ No newline at end of file

build/commonjs/faceFeatureExtractor/index.d.ts

+export * from './FaceFeatureExtractor';
+export * from './TinyFaceFeatureExtractor';

build/commonjs/faceFeatureExtractor/index.js

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

build/commonjs/faceFeatureExtractor/index.js.map

+{"version":3,"file":"index.js","sourceRoot":"","sources":["../../../src/faceFeatureExtractor/index.ts"],"names":[],"mappings":";;;AAAA,iEAAuC;AACvC,qEAA2C"}
\ No newline at end of file

build/commonjs/faceLandmarkNet/loadParamsFactory.d.ts → build/commonjs/faceFeatureExtractor/loadParamsFactory.d.ts

 import { ParamMapping } from 'tfjs-image-recognition-base';
-import { FCParams } from 'tfjs-tiny-yolov2';
 import { DenseBlock3Params, DenseBlock4Params } from './types';
 export declare function loadParamsFactory(weightMap: any, paramMappings: ParamMapping[]): {
     extractDenseBlock3Params: (prefix: string, isFirstLayer?: boolean) => DenseBlock3Params;
     extractDenseBlock4Params: (prefix: string, isFirstLayer?: boolean) => DenseBlock4Params;
-    extractFcParams: (prefix: string) => FCParams;
 };

build/commonjs/faceLandmarkNet/loadParamsFactory.js → build/commonjs/faceFeatureExtractor/loadParamsFactory.js

@@ -34,15 +34,9 @@ function loadParamsFactory(weightMap, paramMappings) {
         var conv3 = extractSeparableConvParams(prefix + "/conv3");
         return { conv0: conv0, conv1: conv1, conv2: conv2, conv3: conv3 };
     }
-    function extractFcParams(prefix) {
-        var weights = extractWeightEntry(prefix + "/weights", 2);
-        var bias = extractWeightEntry(prefix + "/bias", 1);
-        return { weights: weights, bias: bias };
-    }
     return {
         extractDenseBlock3Params: extractDenseBlock3Params,
-        extractDenseBlock4Params: extractDenseBlock4Params,
-        extractFcParams: extractFcParams
+        extractDenseBlock4Params: extractDenseBlock4Params
     };
 }
 exports.loadParamsFactory = loadParamsFactory;

build/commonjs/faceFeatureExtractor/loadParamsFactory.js.map

+{"version":3,"file":"loadParamsFactory.js","sourceRoot":"","sources":["../../../src/faceFeatureExtractor/loadParamsFactory.ts"],"names":[],"mappings":";;AACA,2EAAsF;AACtF,qDAAmE;AAInE,2BAAkC,SAAc,EAAE,aAA6B;IAE7E,IAAM,kBAAkB,GAAG,uDAAyB,CAAC,SAAS,EAAE,aAAa,CAAC,CAAA;IAE9E,2BAA2B,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,oCAAoC,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,sCAAmB,CAC5B,gBAAgB,EAChB,gBAAgB,EAChB,IAAI,CACL,CAAA;IACH,CAAC;IAED,kCAAkC,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,kCAAkC,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"}
\ No newline at end of file

build/commonjs/faceLandmarkNet/types.d.ts → build/commonjs/faceFeatureExtractor/types.d.ts

 import * as tf from '@tensorflow/tfjs-core';
-import { ConvParams, FCParams, SeparableConvParams } from 'tfjs-tiny-yolov2';
+import { NetInput, NeuralNetwork, TNetInput } from 'tfjs-image-recognition-base';
+import { ConvParams, SeparableConvParams } from 'tfjs-tiny-yolov2';
 export declare type ConvWithBatchNormParams = BatchNormParams & {
     filter: tf.Tensor4D;
 };
@@ -13,9 +14,6 @@ export declare type SeparableConvWithBatchNormParams = {
     depthwise: ConvWithBatchNormParams;
     pointwise: ConvWithBatchNormParams;
 };
-export declare type FCWithBatchNormParams = BatchNormParams & {
-    weights: tf.Tensor2D;
-};
 export declare type DenseBlock3Params = {
     conv0: SeparableConvParams | ConvParams;
     conv1: SeparableConvParams;
@@ -24,16 +22,18 @@ export declare type DenseBlock3Params = {
 export declare type DenseBlock4Params = DenseBlock3Params & {
     conv3: SeparableConvParams;
 };
-export declare type TinyNetParams = {
+export declare type TinyFaceFeatureExtractorParams = {
     dense0: DenseBlock3Params;
     dense1: DenseBlock3Params;
     dense2: DenseBlock3Params;
-    fc: FCParams;
 };
-export declare type NetParams = {
+export declare type FaceFeatureExtractorParams = {
     dense0: DenseBlock4Params;
     dense1: DenseBlock4Params;
     dense2: DenseBlock4Params;
     dense3: DenseBlock4Params;
-    fc: FCParams;
 };
+export interface IFaceFeatureExtractor<TNetParams extends TinyFaceFeatureExtractorParams | FaceFeatureExtractorParams> extends NeuralNetwork<TNetParams> {
+    forwardInput(input: NetInput): tf.Tensor4D;
+    forward(input: TNetInput): Promise<tf.Tensor4D>;
+}

build/commonjs/faceFeatureExtractor/types.js.map

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

build/commonjs/faceLandmarkNet/FaceLandmark68Net.d.ts

-import * as tf from '@tensorflow/tfjs-core';
-import { NetInput } from 'tfjs-image-recognition-base';
+import { FaceFeatureExtractor } from '../faceFeatureExtractor/FaceFeatureExtractor';
+import { FaceFeatureExtractorParams } from '../faceFeatureExtractor/types';
 import { FaceLandmark68NetBase } from './FaceLandmark68NetBase';
-import { NetParams } from './types';
-export declare class FaceLandmark68Net extends FaceLandmark68NetBase<NetParams> {
-    constructor();
-    runNet(input: NetInput): tf.Tensor2D;
+export declare class FaceLandmark68Net extends FaceLandmark68NetBase<FaceFeatureExtractorParams> {
+    constructor(faceFeatureExtractor?: FaceFeatureExtractor);
     protected getDefaultModelName(): string;
-    protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap): {
-        params: NetParams;
-        paramMappings: {
-            originalPath?: string | undefined;
-            paramPath: string;
-        }[];
-    };
-    protected extractParams(weights: Float32Array): {
-        params: NetParams;
-        paramMappings: {
-            originalPath?: string | undefined;
-            paramPath: string;
-        }[];
-    };
+    protected getClassifierChannelsIn(): number;
 }

build/commonjs/faceLandmarkNet/FaceLandmark68Net.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("./depthwiseSeparableConv");
-var extractParams_1 = require("./extractParams");
-var extractParamsFromWeigthMap_1 = require("./extractParamsFromWeigthMap");
+var FaceFeatureExtractor_1 = require("../faceFeatureExtractor/FaceFeatureExtractor");
 var FaceLandmark68NetBase_1 = require("./FaceLandmark68NetBase");
-var fullyConnectedLayer_1 = require("./fullyConnectedLayer");
-function denseBlock(x, denseBlockParams, isFirstLayer) {
-    if (isFirstLayer === void 0) { isFirstLayer = false; }
-    return tf.tidy(function () {
-        var out1 = tf.relu(isFirstLayer
-            ? tf.add(tf.conv2d(x, denseBlockParams.conv0.filters, [2, 2], 'same'), denseBlockParams.conv0.bias)
-            : depthwiseSeparableConv_1.depthwiseSeparableConv(x, denseBlockParams.conv0, [2, 2]));
-        var out2 = depthwiseSeparableConv_1.depthwiseSeparableConv(out1, denseBlockParams.conv1, [1, 1]);
-        var in3 = tf.relu(tf.add(out1, out2));
-        var out3 = depthwiseSeparableConv_1.depthwiseSeparableConv(in3, denseBlockParams.conv2, [1, 1]);
-        var in4 = tf.relu(tf.add(out1, tf.add(out2, out3)));
-        var out4 = depthwiseSeparableConv_1.depthwiseSeparableConv(in4, denseBlockParams.conv3, [1, 1]);
-        return tf.relu(tf.add(out1, tf.add(out2, tf.add(out3, out4))));
-    });
-}
 var FaceLandmark68Net = /** @class */ (function (_super) {
     tslib_1.__extends(FaceLandmark68Net, _super);
-    function FaceLandmark68Net() {
-        return _super.call(this, 'FaceLandmark68Net') || this;
+    function FaceLandmark68Net(faceFeatureExtractor) {
+        if (faceFeatureExtractor === void 0) { faceFeatureExtractor = new FaceFeatureExtractor_1.FaceFeatureExtractor(); }
+        return _super.call(this, 'FaceLandmark68Net', faceFeatureExtractor) || this;
     }
-    FaceLandmark68Net.prototype.runNet = function (input) {
-        var params = this.params;
-        if (!params) {
-            throw new Error('FaceLandmark68Net - 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(255));
-            var out = denseBlock(normalized, params.dense0, true);
-            out = denseBlock(out, params.dense1);
-            out = denseBlock(out, params.dense2);
-            out = denseBlock(out, params.dense3);
-            out = tf.avgPool(out, [7, 7], [2, 2], 'valid');
-            return fullyConnectedLayer_1.fullyConnectedLayer(out.as2D(out.shape[0], -1), params.fc);
-        });
-    };
     FaceLandmark68Net.prototype.getDefaultModelName = function () {
         return 'face_landmark_68_model';
     };
-    FaceLandmark68Net.prototype.extractParamsFromWeigthMap = function (weightMap) {
-        return extractParamsFromWeigthMap_1.extractParamsFromWeigthMap(weightMap);
-    };
-    FaceLandmark68Net.prototype.extractParams = function (weights) {
-        return extractParams_1.extractParams(weights);
+    FaceLandmark68Net.prototype.getClassifierChannelsIn = function () {
+        return 256;
     };
     return FaceLandmark68Net;
 }(FaceLandmark68NetBase_1.FaceLandmark68NetBase));

build/commonjs/faceLandmarkNet/FaceLandmark68Net.js.map

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+{"version":3,"file":"FaceLandmark68Net.js","sourceRoot":"","sources":["../../../src/faceLandmarkNet/FaceLandmark68Net.ts"],"names":[],"mappings":";;;AAAA,qFAAoF;AAEpF,iEAAgE;AAEhE;IAAuC,6CAAiD;IAEtF,2BAAY,oBAAuE;QAAvE,qCAAA,EAAA,2BAAiD,2CAAoB,EAAE;eACjF,kBAAM,mBAAmB,EAAE,oBAAoB,CAAC;IAClD,CAAC;IAES,+CAAmB,GAA7B;QACE,OAAO,wBAAwB,CAAA;IACjC,CAAC;IAES,mDAAuB,GAAjC;QACE,OAAO,GAAG,CAAA;IACZ,CAAC;IACH,wBAAC;AAAD,CAAC,AAbD,CAAuC,6CAAqB,GAa3D;AAbY,8CAAiB"}
\ No newline at end of file

build/commonjs/faceLandmarkNet/FaceLandmark68NetBase.d.ts

 import * as tf from '@tensorflow/tfjs-core';
-import { IDimensions, NetInput, NeuralNetwork, TNetInput } from 'tfjs-image-recognition-base';
+import { IDimensions, NetInput, TNetInput } from 'tfjs-image-recognition-base';
 import { FaceLandmarks68 } from '../classes/FaceLandmarks68';
-export declare abstract class FaceLandmark68NetBase<NetParams> extends NeuralNetwork<NetParams> {
-    private __name;
-    constructor(_name: string);
-    abstract runNet(netInput: NetInput): tf.Tensor2D;
+import { FaceFeatureExtractorParams, TinyFaceFeatureExtractorParams } from '../faceFeatureExtractor/types';
+import { FaceProcessor } from '../faceProcessor/FaceProcessor';
+export declare abstract class FaceLandmark68NetBase<TExtractorParams extends FaceFeatureExtractorParams | TinyFaceFeatureExtractorParams> extends FaceProcessor<TExtractorParams> {
     postProcess(output: tf.Tensor2D, inputSize: number, originalDimensions: IDimensions[]): tf.Tensor2D;
     forwardInput(input: NetInput): tf.Tensor2D;
     forward(input: TNetInput): Promise<tf.Tensor2D>;
     detectLandmarks(input: TNetInput): Promise<FaceLandmarks68 | FaceLandmarks68[]>;
+    protected getClassifierChannelsOut(): number;
 }

build/commonjs/faceLandmarkNet/FaceLandmark68NetBase.js

@@ -4,12 +4,11 @@ var tslib_1 = require("tslib");
 var tf = require("@tensorflow/tfjs-core");
 var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
 var FaceLandmarks68_1 = require("../classes/FaceLandmarks68");
+var FaceProcessor_1 = require("../faceProcessor/FaceProcessor");
 var FaceLandmark68NetBase = /** @class */ (function (_super) {
     tslib_1.__extends(FaceLandmark68NetBase, _super);
-    function FaceLandmark68NetBase(_name) {
-        var _this = _super.call(this, _name) || this;
-        _this.__name = _name;
-        return _this;
+    function FaceLandmark68NetBase() {
+        return _super !== null && _super.apply(this, arguments) || this;
     }
     FaceLandmark68NetBase.prototype.postProcess = function (output, inputSize, originalDimensions) {
         var inputDimensions = originalDimensions.map(function (_a) {
@@ -106,7 +105,10 @@ var FaceLandmark68NetBase = /** @class */ (function (_super) {
             });
         });
     };
+    FaceLandmark68NetBase.prototype.getClassifierChannelsOut = function () {
+        return 136;
+    };
     return FaceLandmark68NetBase;
-}(tfjs_image_recognition_base_1.NeuralNetwork));
+}(FaceProcessor_1.FaceProcessor));
 exports.FaceLandmark68NetBase = FaceLandmark68NetBase;
 //# sourceMappingURL=FaceLandmark68NetBase.js.map
\ No newline at end of file

build/commonjs/faceLandmarkNet/FaceLandmark68NetBase.js.map

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\ No newline at end of file

build/commonjs/faceLandmarkNet/FaceLandmark68TinyNet.d.ts

-import * as tf from '@tensorflow/tfjs-core';
-import { NetInput } from 'tfjs-image-recognition-base';
+import { TinyFaceFeatureExtractorParams } from 'src/faceFeatureExtractor/types';
+import { TinyFaceFeatureExtractor } from '../faceFeatureExtractor/TinyFaceFeatureExtractor';
 import { FaceLandmark68NetBase } from './FaceLandmark68NetBase';
-import { TinyNetParams } from './types';
-export declare class FaceLandmark68TinyNet extends FaceLandmark68NetBase<TinyNetParams> {
-    constructor();
-    runNet(input: NetInput): tf.Tensor2D;
+export declare class FaceLandmark68TinyNet extends FaceLandmark68NetBase<TinyFaceFeatureExtractorParams> {
+    constructor(faceFeatureExtractor?: TinyFaceFeatureExtractor);
     protected getDefaultModelName(): string;
-    protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap): {
-        params: TinyNetParams;
-        paramMappings: {
-            originalPath?: string | undefined;
-            paramPath: string;
-        }[];
-    };
-    protected extractParams(weights: Float32Array): {
-        params: TinyNetParams;
-        paramMappings: {
-            originalPath?: string | undefined;
-            paramPath: string;
-        }[];
-    };
+    protected getClassifierChannelsIn(): number;
 }

build/commonjs/faceLandmarkNet/FaceLandmark68TinyNet.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("./depthwiseSeparableConv");
-var extractParamsTiny_1 = require("./extractParamsTiny");
+var TinyFaceFeatureExtractor_1 = require("../faceFeatureExtractor/TinyFaceFeatureExtractor");
 var FaceLandmark68NetBase_1 = require("./FaceLandmark68NetBase");
-var fullyConnectedLayer_1 = require("./fullyConnectedLayer");
-var extractParamsFromWeigthMapTiny_1 = require("./extractParamsFromWeigthMapTiny");
-function denseBlock(x, denseBlockParams, isFirstLayer) {
-    if (isFirstLayer === void 0) { isFirstLayer = false; }
-    return tf.tidy(function () {
-        var out1 = tf.relu(isFirstLayer
-            ? tf.add(tf.conv2d(x, denseBlockParams.conv0.filters, [2, 2], 'same'), denseBlockParams.conv0.bias)
-            : depthwiseSeparableConv_1.depthwiseSeparableConv(x, denseBlockParams.conv0, [2, 2]));
-        var out2 = depthwiseSeparableConv_1.depthwiseSeparableConv(out1, denseBlockParams.conv1, [1, 1]);
-        var in3 = tf.relu(tf.add(out1, out2));
-        var out3 = depthwiseSeparableConv_1.depthwiseSeparableConv(in3, denseBlockParams.conv2, [1, 1]);
-        return tf.relu(tf.add(out1, tf.add(out2, out3)));
-    });
-}
 var FaceLandmark68TinyNet = /** @class */ (function (_super) {
     tslib_1.__extends(FaceLandmark68TinyNet, _super);
-    function FaceLandmark68TinyNet() {
-        return _super.call(this, 'FaceLandmark68TinyNet') || this;
+    function FaceLandmark68TinyNet(faceFeatureExtractor) {
+        if (faceFeatureExtractor === void 0) { faceFeatureExtractor = new TinyFaceFeatureExtractor_1.TinyFaceFeatureExtractor(); }
+        return _super.call(this, 'FaceLandmark68TinyNet', faceFeatureExtractor) || this;
     }
-    FaceLandmark68TinyNet.prototype.runNet = function (input) {
-        var params = this.params;
-        if (!params) {
-            throw new Error('FaceLandmark68TinyNet - 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(255));
-            var out = denseBlock(normalized, params.dense0, true);
-            out = denseBlock(out, params.dense1);
-            out = denseBlock(out, params.dense2);
-            out = tf.avgPool(out, [14, 14], [2, 2], 'valid');
-            return fullyConnectedLayer_1.fullyConnectedLayer(out.as2D(out.shape[0], -1), params.fc);
-        });
-    };
     FaceLandmark68TinyNet.prototype.getDefaultModelName = function () {
         return 'face_landmark_68_tiny_model';
     };
-    FaceLandmark68TinyNet.prototype.extractParamsFromWeigthMap = function (weightMap) {
-        return extractParamsFromWeigthMapTiny_1.extractParamsFromWeigthMapTiny(weightMap);
-    };
-    FaceLandmark68TinyNet.prototype.extractParams = function (weights) {
-        return extractParamsTiny_1.extractParamsTiny(weights);
+    FaceLandmark68TinyNet.prototype.getClassifierChannelsIn = function () {
+        return 128;
     };
     return FaceLandmark68TinyNet;
 }(FaceLandmark68NetBase_1.FaceLandmark68NetBase));

build/commonjs/faceLandmarkNet/FaceLandmark68TinyNet.js.map

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+{"version":3,"file":"FaceLandmark68TinyNet.js","sourceRoot":"","sources":["../../../src/faceLandmarkNet/FaceLandmark68TinyNet.ts"],"names":[],"mappings":";;;AAEA,6FAA4F;AAC5F,iEAAgE;AAEhE;IAA2C,iDAAqD;IAE9F,+BAAY,oBAA+E;QAA/E,qCAAA,EAAA,2BAAqD,mDAAwB,EAAE;eACzF,kBAAM,uBAAuB,EAAE,oBAAoB,CAAC;IACtD,CAAC;IAES,mDAAmB,GAA7B;QACE,OAAO,6BAA6B,CAAA;IACtC,CAAC;IAES,uDAAuB,GAAjC;QACE,OAAO,GAAG,CAAA;IACZ,CAAC;IACH,4BAAC;AAAD,CAAC,AAbD,CAA2C,6CAAqB,GAa/D;AAbY,sDAAqB"}
\ No newline at end of file

build/commonjs/faceLandmarkNet/depthwiseSeparableConv.js.map

-{"version":3,"file":"depthwiseSeparableConv.js","sourceRoot":"","sources":["../../../src/faceLandmarkNet/depthwiseSeparableConv.ts"],"names":[],"mappings":";;AAAA,0CAA4C;AAG5C,gCACE,CAAc,EACd,MAA2B,EAC3B,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/faceLandmarkNet/extractParams.js.map

-{"version":3,"file":"extractParams.js","sourceRoot":"","sources":["../../../src/faceLandmarkNet/extractParams.ts"],"names":[],"mappings":";;AAAA,2EAAkF;AAElF,yDAAwD;AAGxD,uBAA8B,OAAqB;IAEjD,IAAM,aAAa,GAAmB,EAAE,CAAA;IAElC,IAAA,iEAG4B,EAFhC,kCAAc,EACd,4CAAmB,CACa;IAE5B,IAAA,yEAG8C,EAFlD,sDAAwB,EACxB,oCAAe,CACmC;IAEpD,IAAM,MAAM,GAAG,wBAAwB,CAAC,CAAC,EAAE,EAAE,EAAE,QAAQ,EAAE,IAAI,CAAC,CAAA;IAC9D,IAAM,MAAM,GAAG,wBAAwB,CAAC,EAAE,EAAE,EAAE,EAAE,QAAQ,CAAC,CAAA;IACzD,IAAM,MAAM,GAAG,wBAAwB,CAAC,EAAE,EAAE,GAAG,EAAE,QAAQ,CAAC,CAAA;IAC1D,IAAM,MAAM,GAAG,wBAAwB,CAAC,GAAG,EAAE,GAAG,EAAE,QAAQ,CAAC,CAAA;IAC3D,IAAM,EAAE,GAAG,eAAe,CAAC,GAAG,EAAE,GAAG,EAAE,IAAI,CAAC,CAAA;IAE1C,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,MAAM,QAAA,EAAE,MAAM,QAAA,EAAE,MAAM,QAAA,EAAE,MAAM,QAAA,EAAE,EAAE,IAAA,EAAE;KAC/C,CAAA;AACH,CAAC;AA5BD,sCA4BC"}
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build/commonjs/faceLandmarkNet/extractParamsFromWeigthMap.js.map

-{"version":3,"file":"extractParamsFromWeigthMap.js","sourceRoot":"","sources":["../../../src/faceLandmarkNet/extractParamsFromWeigthMap.ts"],"names":[],"mappings":";;AACA,2EAAuF;AAEvF,yDAAwD;AAGxD,oCACE,SAA4B;IAG5B,IAAM,aAAa,GAAmB,EAAE,CAAA;IAElC,IAAA,oEAGyC,EAF7C,sDAAwB,EACxB,oCAAe,CAC8B;IAE/C,IAAM,MAAM,GAAG;QACb,MAAM,EAAE,wBAAwB,CAAC,QAAQ,EAAE,IAAI,CAAC;QAChD,MAAM,EAAE,wBAAwB,CAAC,QAAQ,CAAC;QAC1C,MAAM,EAAE,wBAAwB,CAAC,QAAQ,CAAC;QAC1C,MAAM,EAAE,wBAAwB,CAAC,QAAQ,CAAC;QAC1C,EAAE,EAAE,eAAe,CAAC,IAAI,CAAC;KAC1B,CAAA;IAED,wDAA0B,CAAC,SAAS,EAAE,aAAa,CAAC,CAAA;IAEpD,OAAO,EAAE,MAAM,QAAA,EAAE,aAAa,eAAA,EAAE,CAAA;AAClC,CAAC;AAtBD,gEAsBC"}
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build/commonjs/faceLandmarkNet/extractParamsFromWeigthMapTiny.js.map

-{"version":3,"file":"extractParamsFromWeigthMapTiny.js","sourceRoot":"","sources":["../../../src/faceLandmarkNet/extractParamsFromWeigthMapTiny.ts"],"names":[],"mappings":";;AACA,2EAAuF;AAEvF,yDAAwD;AAGxD,wCACE,SAA4B;IAG5B,IAAM,aAAa,GAAmB,EAAE,CAAA;IAElC,IAAA,oEAGyC,EAF7C,sDAAwB,EACxB,oCAAe,CAC8B;IAE/C,IAAM,MAAM,GAAG;QACb,MAAM,EAAE,wBAAwB,CAAC,QAAQ,EAAE,IAAI,CAAC;QAChD,MAAM,EAAE,wBAAwB,CAAC,QAAQ,CAAC;QAC1C,MAAM,EAAE,wBAAwB,CAAC,QAAQ,CAAC;QAC1C,EAAE,EAAE,eAAe,CAAC,IAAI,CAAC;KAC1B,CAAA;IAED,wDAA0B,CAAC,SAAS,EAAE,aAAa,CAAC,CAAA;IAEpD,OAAO,EAAE,MAAM,QAAA,EAAE,aAAa,eAAA,EAAE,CAAA;AAClC,CAAC;AArBD,wEAqBC"}
\ No newline at end of file

build/commonjs/faceLandmarkNet/extractParamsTiny.js.map

-{"version":3,"file":"extractParamsTiny.js","sourceRoot":"","sources":["../../../src/faceLandmarkNet/extractParamsTiny.ts"],"names":[],"mappings":";;AAAA,2EAAkF;AAElF,yDAAwD;AAGxD,2BAAkC,OAAqB;IAErD,IAAM,aAAa,GAAmB,EAAE,CAAA;IAElC,IAAA,iEAG4B,EAFhC,kCAAc,EACd,4CAAmB,CACa;IAE5B,IAAA,yEAG8C,EAFlD,sDAAwB,EACxB,oCAAe,CACmC;IAEpD,IAAM,MAAM,GAAG,wBAAwB,CAAC,CAAC,EAAE,EAAE,EAAE,QAAQ,EAAE,IAAI,CAAC,CAAA;IAC9D,IAAM,MAAM,GAAG,wBAAwB,CAAC,EAAE,EAAE,EAAE,EAAE,QAAQ,CAAC,CAAA;IACzD,IAAM,MAAM,GAAG,wBAAwB,CAAC,EAAE,EAAE,GAAG,EAAE,QAAQ,CAAC,CAAA;IAC1D,IAAM,EAAE,GAAG,eAAe,CAAC,GAAG,EAAE,GAAG,EAAE,IAAI,CAAC,CAAA;IAE1C,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,MAAM,QAAA,EAAE,MAAM,QAAA,EAAE,MAAM,QAAA,EAAE,EAAE,IAAA,EAAE;KACvC,CAAA;AACH,CAAC;AA3BD,8CA2BC"}
\ No newline at end of file

build/commonjs/faceLandmarkNet/extractorsFactory.js.map

-{"version":3,"file":"extractorsFactory.js","sourceRoot":"","sources":["../../../src/faceLandmarkNet/extractorsFactory.ts"],"names":[],"mappings":";;AAAA,0CAA4C;AAE5C,qDAA2F;AAI3F,2BAAkC,cAAsC,EAAE,aAA6B;IAErG,oCAAoC,UAAkB,EAAE,WAAmB,EAAE,YAAoB;QAC/F,IAAM,gBAAgB,GAAG,EAAE,CAAC,QAAQ,CAAC,cAAc,CAAC,CAAC,GAAG,CAAC,GAAG,UAAU,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,EAAE,UAAU,EAAE,CAAC,CAAC,CAAC,CAAA;QAC/F,IAAM,gBAAgB,GAAG,EAAE,CAAC,QAAQ,CAAC,cAAc,CAAC,UAAU,GAAG,WAAW,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,EAAE,UAAU,EAAE,WAAW,CAAC,CAAC,CAAA;QAC/G,IAAM,IAAI,GAAG,EAAE,CAAC,QAAQ,CAAC,cAAc,CAAC,WAAW,CAAC,CAAC,CAAA;QAErD,aAAa,CAAC,IAAI,CAChB,EAAE,SAAS,EAAK,YAAY,sBAAmB,EAAE,EACjD,EAAE,SAAS,EAAK,YAAY,sBAAmB,EAAE,EACjD,EAAE,SAAS,EAAK,YAAY,UAAO,EAAE,CACtC,CAAA;QAED,OAAO,IAAI,sCAAmB,CAC5B,gBAAgB,EAChB,gBAAgB,EAChB,IAAI,CACL,CAAA;IACH,CAAC;IAED,yBAAyB,UAAkB,EAAE,WAAmB,EAAE,YAAoB;QACpF,IAAM,OAAO,GAAG,EAAE,CAAC,QAAQ,CAAC,cAAc,CAAC,UAAU,GAAG,WAAW,CAAC,EAAE,CAAC,UAAU,EAAE,WAAW,CAAC,CAAC,CAAA;QAChG,IAAM,IAAI,GAAG,EAAE,CAAC,QAAQ,CAAC,cAAc,CAAC,WAAW,CAAC,CAAC,CAAA;QAErD,aAAa,CAAC,IAAI,CAChB,EAAE,SAAS,EAAK,YAAY,aAAU,EAAE,EACxC,EAAE,SAAS,EAAK,YAAY,UAAO,EAAE,CACtC,CAAA;QAED,OAAO;YACL,OAAO,SAAA;YACP,IAAI,MAAA;SACL,CAAA;IACH,CAAC;IAED,IAAM,iBAAiB,GAAG,2CAAwB,CAAC,cAAc,EAAE,aAAa,CAAC,CAAA;IAEjF,kCAAkC,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,kCAAkC,UAAkB,EAAE,WAAmB,EAAE,YAAoB,EAAE,YAA6B;QAA7B,6BAAA,EAAA,oBAA6B;QAEtH,IAAA,kFAAuG,EAArG,gBAAK,EAAE,gBAAK,EAAE,gBAAK,CAAkF;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;QACxB,eAAe,iBAAA;KAChB,CAAA;AAEH,CAAC;AA9DD,8CA8DC"}
\ No newline at end of file

build/commonjs/faceLandmarkNet/fullyConnectedLayer.js.map

-{"version":3,"file":"fullyConnectedLayer.js","sourceRoot":"","sources":["../../../src/faceLandmarkNet/fullyConnectedLayer.ts"],"names":[],"mappings":";;AAAA,0CAA4C;AAG5C,6BACE,CAAc,EACd,MAAgB;IAEhB,OAAO,EAAE,CAAC,IAAI,CAAC;QACb,OAAA,EAAE,CAAC,GAAG,CACJ,EAAE,CAAC,MAAM,CAAC,CAAC,EAAE,MAAM,CAAC,OAAO,CAAC,EAC5B,MAAM,CAAC,IAAI,CACZ;IAHD,CAGC,CACF,CAAA;AACH,CAAC;AAVD,kDAUC"}
\ No newline at end of file

build/commonjs/faceLandmarkNet/index.d.ts

@@ -3,4 +3,3 @@ export * from './FaceLandmark68Net';
 export * from './FaceLandmark68TinyNet';
 export declare class FaceLandmarkNet extends FaceLandmark68Net {
 }
-export declare function createFaceLandmarkNet(weights: Float32Array): FaceLandmarkNet;

build/commonjs/faceLandmarkNet/index.js

@@ -12,10 +12,4 @@ var FaceLandmarkNet = /** @class */ (function (_super) {
     return FaceLandmarkNet;
 }(FaceLandmark68Net_1.FaceLandmark68Net));
 exports.FaceLandmarkNet = FaceLandmarkNet;
-function createFaceLandmarkNet(weights) {
-    var net = new FaceLandmarkNet();
-    net.extractWeights(weights);
-    return net;
-}
-exports.createFaceLandmarkNet = createFaceLandmarkNet;
 //# sourceMappingURL=index.js.map
\ No newline at end of file

build/commonjs/faceLandmarkNet/index.js.map

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+{"version":3,"file":"index.js","sourceRoot":"","sources":["../../../src/faceLandmarkNet/index.ts"],"names":[],"mappings":";;;AAAA,yDAAwD;AAExD,8DAAoC;AACpC,kEAAwC;AAExC;IAAqC,2CAAiB;IAAtD;;IAAwD,CAAC;IAAD,sBAAC;AAAD,CAAC,AAAzD,CAAqC,qCAAiB,GAAG;AAA5C,0CAAe"}
\ No newline at end of file

build/commonjs/faceLandmarkNet/loadParamsFactory.js.map

-{"version":3,"file":"loadParamsFactory.js","sourceRoot":"","sources":["../../../src/faceLandmarkNet/loadParamsFactory.ts"],"names":[],"mappings":";;AACA,2EAAsF;AACtF,qDAA6E;AAI7E,2BAAkC,SAAc,EAAE,aAA6B;IAE7E,IAAM,kBAAkB,GAAG,uDAAyB,CAAC,SAAS,EAAE,aAAa,CAAC,CAAA;IAE9E,2BAA2B,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,oCAAoC,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,sCAAmB,CAC5B,gBAAgB,EAChB,gBAAgB,EAChB,IAAI,CACL,CAAA;IACH,CAAC;IAED,kCAAkC,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,kCAAkC,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,yBAAyB,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;QAEjE,OAAO,EAAE,OAAO,SAAA,EAAE,IAAI,MAAA,EAAE,CAAA;IAC1B,CAAC;IAED,OAAO;QACL,wBAAwB,0BAAA;QACxB,wBAAwB,0BAAA;QACxB,eAAe,iBAAA;KAChB,CAAA;AACH,CAAC;AAxDD,8CAwDC"}
\ No newline at end of file

build/commonjs/faceLandmarkNet/types.js.map

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

build/commonjs/faceProcessor/FaceProcessor.d.ts

+import * as tf from '@tensorflow/tfjs-core';
+import { NetInput, NeuralNetwork } from 'tfjs-image-recognition-base';
+import { FaceFeatureExtractorParams, IFaceFeatureExtractor, TinyFaceFeatureExtractorParams } from '../faceFeatureExtractor/types';
+import { NetParams } from './types';
+export declare abstract class FaceProcessor<TExtractorParams extends FaceFeatureExtractorParams | TinyFaceFeatureExtractorParams> extends NeuralNetwork<NetParams> {
+    protected _faceFeatureExtractor: IFaceFeatureExtractor<TExtractorParams>;
+    constructor(_name: string, faceFeatureExtractor: IFaceFeatureExtractor<TExtractorParams>);
+    readonly faceFeatureExtractor: IFaceFeatureExtractor<TExtractorParams>;
+    protected abstract getDefaultModelName(): string;
+    protected abstract getClassifierChannelsIn(): number;
+    protected abstract getClassifierChannelsOut(): number;
+    runNet(input: NetInput | tf.Tensor4D): tf.Tensor2D;
+    dispose(throwOnRedispose?: boolean): void;
+    loadClassifierParams(weights: Float32Array): void;
+    extractClassifierParams(weights: Float32Array): {
+        params: NetParams;
+        paramMappings: {
+            originalPath?: string | undefined;
+            paramPath: string;
+        }[];
+    };
+    protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap): {
+        params: NetParams;
+        paramMappings: {
+            originalPath?: string | undefined;
+            paramPath: string;
+        }[];
+    };
+    protected extractParams(weights: Float32Array): {
+        params: NetParams;
+        paramMappings: {
+            originalPath?: string | undefined;
+            paramPath: string;
+        }[];
+    };
+}

build/commonjs/faceProcessor/FaceProcessor.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 extractParams_1 = require("./extractParams");
+var extractParamsFromWeigthMap_1 = require("./extractParamsFromWeigthMap");
+var util_1 = require("./util");
+var FaceProcessor = /** @class */ (function (_super) {
+    tslib_1.__extends(FaceProcessor, _super);
+    function FaceProcessor(_name, faceFeatureExtractor) {
+        var _this = _super.call(this, _name) || this;
+        _this._faceFeatureExtractor = faceFeatureExtractor;
+        return _this;
+    }
+    Object.defineProperty(FaceProcessor.prototype, "faceFeatureExtractor", {
+        get: function () {
+            return this._faceFeatureExtractor;
+        },
+        enumerable: true,
+        configurable: true
+    });
+    FaceProcessor.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;
+            return fullyConnectedLayer_1.fullyConnectedLayer(bottleneckFeatures.as2D(bottleneckFeatures.shape[0], -1), params.fc);
+        });
+    };
+    FaceProcessor.prototype.dispose = function (throwOnRedispose) {
+        if (throwOnRedispose === void 0) { throwOnRedispose = true; }
+        this.faceFeatureExtractor.dispose(throwOnRedispose);
+        _super.prototype.dispose.call(this, throwOnRedispose);
+    };
+    FaceProcessor.prototype.loadClassifierParams = function (weights) {
+        var _a = this.extractClassifierParams(weights), params = _a.params, paramMappings = _a.paramMappings;
+        this._params = params;
+        this._paramMappings = paramMappings;
+    };
+    FaceProcessor.prototype.extractClassifierParams = function (weights) {
+        return extractParams_1.extractParams(weights, this.getClassifierChannelsIn(), this.getClassifierChannelsOut());
+    };
+    FaceProcessor.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);
+    };
+    FaceProcessor.prototype.extractParams = function (weights) {
+        var cIn = this.getClassifierChannelsIn();
+        var cOut = this.getClassifierChannelsOut();
+        var classifierWeightSize = (cOut * cIn) + cOut;
+        var featureExtractorWeights = weights.slice(0, weights.length - classifierWeightSize);
+        var classifierWeights = weights.slice(weights.length - classifierWeightSize);
+        this.faceFeatureExtractor.extractWeights(featureExtractorWeights);
+        return this.extractClassifierParams(classifierWeights);
+    };
+    return FaceProcessor;
+}(tfjs_image_recognition_base_1.NeuralNetwork));
+exports.FaceProcessor = FaceProcessor;
+//# sourceMappingURL=FaceProcessor.js.map
\ No newline at end of file

build/commonjs/faceProcessor/FaceProcessor.js.map

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\ No newline at end of file

build/commonjs/faceLandmarkNet/extractParams.d.ts → build/commonjs/faceProcessor/extractParams.d.ts

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

build/commonjs/faceProcessor/extractParams.js

+"use strict";
+Object.defineProperty(exports, "__esModule", { value: true });
+var tfjs_image_recognition_base_1 = require("tfjs-image-recognition-base");
+var tfjs_tiny_yolov2_1 = require("tfjs-tiny-yolov2");
+function extractParams(weights, channelsIn, channelsOut) {
+    var paramMappings = [];
+    var _a = tfjs_image_recognition_base_1.extractWeightsFactory(weights), extractWeights = _a.extractWeights, getRemainingWeights = _a.getRemainingWeights;
+    var extractFCParams = tfjs_tiny_yolov2_1.extractFCParamsFactory(extractWeights, paramMappings);
+    var fc = extractFCParams(channelsIn, channelsOut, 'fc');
+    if (getRemainingWeights().length !== 0) {
+        throw new Error("weights remaing after extract: " + getRemainingWeights().length);
+    }
+    return {
+        paramMappings: paramMappings,
+        params: { fc: fc }
+    };
+}
+exports.extractParams = extractParams;
+//# sourceMappingURL=extractParams.js.map
\ No newline at end of file

build/commonjs/faceProcessor/extractParams.js.map

+{"version":3,"file":"extractParams.js","sourceRoot":"","sources":["../../../src/faceProcessor/extractParams.ts"],"names":[],"mappings":";;AAAA,2EAAkF;AAClF,qDAA0D;AAI1D,uBAA8B,OAAqB,EAAE,UAAkB,EAAE,WAAmB;IAE1F,IAAM,aAAa,GAAmB,EAAE,CAAA;IAElC,IAAA,iEAG4B,EAFhC,kCAAc,EACd,4CAAmB,CACa;IAElC,IAAM,eAAe,GAAG,yCAAsB,CAAC,cAAc,EAAE,aAAa,CAAC,CAAA;IAE7E,IAAM,EAAE,GAAG,eAAe,CAAC,UAAU,EAAE,WAAW,EAAE,IAAI,CAAC,CAAA;IAEzD,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,IAAA,EAAE;KACf,CAAA;AACH,CAAC;AArBD,sCAqBC"}
\ No newline at end of file

build/commonjs/faceProcessor/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.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: extractFcParams('fc')
+    };
+    tfjs_image_recognition_base_1.disposeUnusedWeightTensors(weightMap, paramMappings);
+    return { params: params, paramMappings: paramMappings };
+}
+exports.extractParamsFromWeigthMap = extractParamsFromWeigthMap;
+//# sourceMappingURL=extractParamsFromWeigthMap.js.map
\ No newline at end of file

build/commonjs/faceProcessor/extractParamsFromWeigthMap.js.map

+{"version":3,"file":"extractParamsFromWeigthMap.js","sourceRoot":"","sources":["../../../src/faceProcessor/extractParamsFromWeigthMap.ts"],"names":[],"mappings":";;AACA,2EAAkH;AAKlH,oCACE,SAA4B;IAG5B,IAAM,aAAa,GAAmB,EAAE,CAAA;IAExC,IAAM,kBAAkB,GAAG,uDAAyB,CAAC,SAAS,EAAE,aAAa,CAAC,CAAA;IAE9E,yBAAyB,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,eAAe,CAAC,IAAI,CAAC;KAC1B,CAAA;IAED,wDAA0B,CAAC,SAAS,EAAE,aAAa,CAAC,CAAA;IAEpD,OAAO,EAAE,MAAM,QAAA,EAAE,aAAa,eAAA,EAAE,CAAA;AAClC,CAAC;AArBD,gEAqBC"}
\ No newline at end of file

build/commonjs/faceProcessor/index.d.ts

+export * from './FaceProcessor';

build/commonjs/faceProcessor/index.js

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