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strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar tslib_1 = require(\"tslib\");\r\ntslib_1.__exportStar(require(\"./convLayer\"), exports);\r\ntslib_1.__exportStar(require(\"./depthwiseSeparableConv\"), exports);\r\ntslib_1.__exportStar(require(\"./disposeUnusedWeightTensors\"), exports);\r\ntslib_1.__exportStar(require(\"./extractConvParamsFactory\"), exports);\r\ntslib_1.__exportStar(require(\"./extractFCParamsFactory\"), exports);\r\ntslib_1.__exportStar(require(\"./extractSeparableConvParamsFactory\"), exports);\r\ntslib_1.__exportStar(require(\"./extractWeightEntryFactory\"), exports);\r\ntslib_1.__exportStar(require(\"./extractWeightsFactory\"), exports);\r\ntslib_1.__exportStar(require(\"./getModelUris\"), exports);\r\ntslib_1.__exportStar(require(\"./types\"), exports);\r\n//# sourceMappingURL=index.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar tslib_1 = require(\"tslib\");\r\ntslib_1.__exportStar(require(\"./BoundingBox\"), exports);\r\ntslib_1.__exportStar(require(\"./Box\"), exports);\r\ntslib_1.__exportStar(require(\"./Dimensions\"), exports);\r\ntslib_1.__exportStar(require(\"./FaceDetection\"), exports);\r\ntslib_1.__exportStar(require(\"./FaceLandmarks\"), exports);\r\ntslib_1.__exportStar(require(\"./FaceLandmarks5\"), exports);\r\ntslib_1.__exportStar(require(\"./FaceLandmarks68\"), exports);\r\ntslib_1.__exportStar(require(\"./FaceMatch\"), exports);\r\ntslib_1.__exportStar(require(\"./LabeledBox\"), exports);\r\ntslib_1.__exportStar(require(\"./LabeledFaceDescriptors\"), exports);\r\ntslib_1.__exportStar(require(\"./ObjectDetection\"), exports);\r\ntslib_1.__exportStar(require(\"./Point\"), exports);\r\ntslib_1.__exportStar(require(\"./PredictedBox\"), exports);\r\ntslib_1.__exportStar(require(\"./Rect\"), exports);\r\n//# sourceMappingURL=index.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar tslib_1 = require(\"tslib\");\r\nvar utils_1 = require(\"../utils\");\r\nvar FaceLandmarks_1 = require(\"./FaceLandmarks\");\r\nvar FaceLandmarks68 = /** @class */ (function (_super) {\r\n    tslib_1.__extends(FaceLandmarks68, _super);\r\n    function FaceLandmarks68() {\r\n        return _super !== null && _super.apply(this, arguments) || this;\r\n    }\r\n    FaceLandmarks68.prototype.getJawOutline = function () {\r\n        return this.positions.slice(0, 17);\r\n    };\r\n    FaceLandmarks68.prototype.getLeftEyeBrow = function () {\r\n        return this.positions.slice(17, 22);\r\n    };\r\n    FaceLandmarks68.prototype.getRightEyeBrow = function () {\r\n        return this.positions.slice(22, 27);\r\n    };\r\n    FaceLandmarks68.prototype.getNose = function () {\r\n        return this.positions.slice(27, 36);\r\n    };\r\n    FaceLandmarks68.prototype.getLeftEye = function () {\r\n        return this.positions.slice(36, 42);\r\n    };\r\n    FaceLandmarks68.prototype.getRightEye = function () {\r\n        return this.positions.slice(42, 48);\r\n    };\r\n    FaceLandmarks68.prototype.getMouth = function () {\r\n        return this.positions.slice(48, 68);\r\n    };\r\n    FaceLandmarks68.prototype.getRefPointsForAlignment = function () {\r\n        return [\r\n            this.getLeftEye(),\r\n            this.getRightEye(),\r\n            this.getMouth()\r\n        ].map(utils_1.getCenterPoint);\r\n    };\r\n    return FaceLandmarks68;\r\n}(FaceLandmarks_1.FaceLandmarks));\r\nexports.FaceLandmarks68 = FaceLandmarks68;\r\n//# sourceMappingURL=FaceLandmarks68.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nfunction extractWeightsFactory(weights) {\r\n    var remainingWeights = weights;\r\n    function extractWeights(numWeights) {\r\n        var ret = remainingWeights.slice(0, numWeights);\r\n        remainingWeights = remainingWeights.slice(numWeights);\r\n        return ret;\r\n    }\r\n    function getRemainingWeights() {\r\n        return remainingWeights;\r\n    }\r\n    return {\r\n        extractWeights: extractWeights,\r\n        getRemainingWeights: getRemainingWeights\r\n    };\r\n}\r\nexports.extractWeightsFactory = extractWeightsFactory;\r\n//# sourceMappingURL=extractWeightsFactory.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar tf = require(\"@tensorflow/tfjs-core\");\r\nvar types_1 = require(\"./types\");\r\nfunction extractSeparableConvParamsFactory(extractWeights, paramMappings) {\r\n    return function (channelsIn, channelsOut, mappedPrefix) {\r\n        var depthwise_filter = tf.tensor4d(extractWeights(3 * 3 * channelsIn), [3, 3, channelsIn, 1]);\r\n        var pointwise_filter = tf.tensor4d(extractWeights(channelsIn * channelsOut), [1, 1, channelsIn, channelsOut]);\r\n        var bias = tf.tensor1d(extractWeights(channelsOut));\r\n        paramMappings.push({ paramPath: mappedPrefix + \"/depthwise_filter\" }, { paramPath: mappedPrefix + \"/pointwise_filter\" }, { paramPath: mappedPrefix + \"/bias\" });\r\n        return new types_1.SeparableConvParams(depthwise_filter, pointwise_filter, bias);\r\n    };\r\n}\r\nexports.extractSeparableConvParamsFactory = extractSeparableConvParamsFactory;\r\nfunction loadSeparableConvParamsFactory(extractWeightEntry) {\r\n    return function (prefix) {\r\n        var depthwise_filter = extractWeightEntry(prefix + \"/depthwise_filter\", 4);\r\n        var pointwise_filter = extractWeightEntry(prefix + \"/pointwise_filter\", 4);\r\n        var bias = extractWeightEntry(prefix + \"/bias\", 1);\r\n        return new types_1.SeparableConvParams(depthwise_filter, pointwise_filter, bias);\r\n    };\r\n}\r\nexports.loadSeparableConvParamsFactory = loadSeparableConvParamsFactory;\r\n//# sourceMappingURL=extractSeparableConvParamsFactory.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar tf = require(\"@tensorflow/tfjs-core\");\r\nfunction convLayer(x, params, padding, withRelu) {\r\n    if (padding === void 0) { padding = 'same'; }\r\n    if (withRelu === void 0) { withRelu = false; }\r\n    return tf.tidy(function () {\r\n        var out = tf.add(tf.conv2d(x, params.filters, [1, 1], padding), params.bias);\r\n        return withRelu ? tf.relu(out) : out;\r\n    });\r\n}\r\nexports.convLayer = convLayer;\r\n//# sourceMappingURL=convLayer.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar LabeledFaceDescriptors = /** @class */ (function () {\r\n    function LabeledFaceDescriptors(label, descriptors) {\r\n        if (!(typeof label === 'string')) {\r\n            throw new Error('LabeledFaceDescriptors - constructor expected label to be a string');\r\n        }\r\n        if (!Array.isArray(descriptors) || descriptors.some(function (desc) { return !(desc instanceof Float32Array); })) {\r\n            throw new Error('LabeledFaceDescriptors - constructor expected descriptors to be an array of Float32Array');\r\n        }\r\n        this._label = label;\r\n        this._descriptors = descriptors;\r\n    }\r\n    Object.defineProperty(LabeledFaceDescriptors.prototype, \"label\", {\r\n        get: function () { return this._label; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(LabeledFaceDescriptors.prototype, \"descriptors\", {\r\n        get: function () { return this._descriptors; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    LabeledFaceDescriptors.prototype.toJSON = function () {\r\n        return {\r\n            label: this.label,\r\n            descriptors: this.descriptors.map(function (d) { return Array.from(d); })\r\n        };\r\n    };\r\n    LabeledFaceDescriptors.fromJSON = function (json) {\r\n        var descriptors = json.descriptors.map(function (d) {\r\n            return new Float32Array(d);\r\n        });\r\n        return new LabeledFaceDescriptors(json.label, descriptors);\r\n    };\r\n    return LabeledFaceDescriptors;\r\n}());\r\nexports.LabeledFaceDescriptors = LabeledFaceDescriptors;\r\n//# sourceMappingURL=LabeledFaceDescriptors.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nfunction disposeUnusedWeightTensors(weightMap, paramMappings) {\r\n    Object.keys(weightMap).forEach(function (path) {\r\n        if (!paramMappings.some(function (pm) { return pm.originalPath === path; })) {\r\n            weightMap[path].dispose();\r\n        }\r\n    });\r\n}\r\nexports.disposeUnusedWeightTensors = disposeUnusedWeightTensors;\r\n//# sourceMappingURL=disposeUnusedWeightTensors.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar tslib_1 = require(\"tslib\");\r\nvar utils_1 = require(\"../utils\");\r\nvar Box_1 = require(\"./Box\");\r\nvar LabeledBox = /** @class */ (function (_super) {\r\n    tslib_1.__extends(LabeledBox, _super);\r\n    function LabeledBox(box, label) {\r\n        var _this = _super.call(this, box) || this;\r\n        _this._label = label;\r\n        return _this;\r\n    }\r\n    LabeledBox.assertIsValidLabeledBox = function (box, callee) {\r\n        Box_1.Box.assertIsValidBox(box, callee);\r\n        if (!utils_1.isValidNumber(box.label)) {\r\n            throw new Error(callee + \" - expected property label (\" + box.label + \") to be a number\");\r\n        }\r\n    };\r\n    Object.defineProperty(LabeledBox.prototype, \"label\", {\r\n        get: function () { return this._label; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    return LabeledBox;\r\n}(Box_1.Box));\r\nexports.LabeledBox = LabeledBox;\r\n//# sourceMappingURL=LabeledBox.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar utils_1 = require(\"../utils\");\r\nfunction extractWeightEntryFactory(weightMap, paramMappings) {\r\n    return function (originalPath, paramRank, mappedPath) {\r\n        var tensor = weightMap[originalPath];\r\n        if (!utils_1.isTensor(tensor, paramRank)) {\r\n            throw new Error(\"expected weightMap[\" + originalPath + \"] to be a Tensor\" + paramRank + \"D, instead have \" + tensor);\r\n        }\r\n        paramMappings.push({ originalPath: originalPath, paramPath: mappedPath || originalPath });\r\n        return tensor;\r\n    };\r\n}\r\nexports.extractWeightEntryFactory = extractWeightEntryFactory;\r\n//# sourceMappingURL=extractWeightEntryFactory.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar tslib_1 = require(\"tslib\");\r\nvar Box_1 = require(\"./Box\");\r\nvar Rect = /** @class */ (function (_super) {\r\n    tslib_1.__extends(Rect, _super);\r\n    function Rect(x, y, width, height, allowNegativeDimensions) {\r\n        if (allowNegativeDimensions === void 0) { allowNegativeDimensions = false; }\r\n        return _super.call(this, { x: x, y: y, width: width, height: height }, allowNegativeDimensions) || this;\r\n    }\r\n    return Rect;\r\n}(Box_1.Box));\r\nexports.Rect = Rect;\r\n//# sourceMappingURL=Rect.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar Box_1 = require(\"./Box\");\r\nvar Dimensions_1 = require(\"./Dimensions\");\r\nvar ObjectDetection = /** @class */ (function () {\r\n    function ObjectDetection(score, classScore, className, relativeBox, imageDims) {\r\n        this._imageDims = new Dimensions_1.Dimensions(imageDims.width, imageDims.height);\r\n        this._score = score;\r\n        this._classScore = classScore;\r\n        this._className = className;\r\n        this._box = new Box_1.Box(relativeBox).rescale(this._imageDims);\r\n    }\r\n    Object.defineProperty(ObjectDetection.prototype, \"score\", {\r\n        get: function () { return this._score; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(ObjectDetection.prototype, \"classScore\", {\r\n        get: function () { return this._classScore; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(ObjectDetection.prototype, \"className\", {\r\n        get: function () { return this._className; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(ObjectDetection.prototype, \"box\", {\r\n        get: function () { return this._box; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(ObjectDetection.prototype, \"imageDims\", {\r\n        get: function () { return this._imageDims; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(ObjectDetection.prototype, \"imageWidth\", {\r\n        get: function () { return this.imageDims.width; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(ObjectDetection.prototype, \"imageHeight\", {\r\n        get: function () { return this.imageDims.height; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(ObjectDetection.prototype, \"relativeBox\", {\r\n        get: function () { return new Box_1.Box(this._box).rescale(this.imageDims.reverse()); },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    ObjectDetection.prototype.forSize = function (width, height) {\r\n        return new ObjectDetection(this.score, this.classScore, this.className, this.relativeBox, { width: width, height: height });\r\n    };\r\n    return ObjectDetection;\r\n}());\r\nexports.ObjectDetection = ObjectDetection;\r\n//# sourceMappingURL=ObjectDetection.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nfunction iou(box1, box2, isIOU) {\r\n    if (isIOU === void 0) { isIOU = true; }\r\n    var width = Math.max(0.0, Math.min(box1.right, box2.right) - Math.max(box1.left, box2.left));\r\n    var height = Math.max(0.0, Math.min(box1.bottom, box2.bottom) - Math.max(box1.top, box2.top));\r\n    var interSection = width * height;\r\n    return isIOU\r\n        ? interSection / (box1.area + box2.area - interSection)\r\n        : interSection / Math.min(box1.area, box2.area);\r\n}\r\nexports.iou = iou;\r\n//# sourceMappingURL=iou.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar ops_1 = require(\"../ops\");\r\nvar utils_1 = require(\"../utils\");\r\nvar Box_1 = require(\"./Box\");\r\nvar Dimensions_1 = require(\"./Dimensions\");\r\nvar FaceDetection_1 = require(\"./FaceDetection\");\r\nvar Point_1 = require(\"./Point\");\r\nvar Rect_1 = require(\"./Rect\");\r\n// face alignment constants\r\nvar relX = 0.5;\r\nvar relY = 0.43;\r\nvar relScale = 0.45;\r\nvar FaceLandmarks = /** @class */ (function () {\r\n    function FaceLandmarks(relativeFaceLandmarkPositions, imgDims, shift) {\r\n        if (shift === void 0) { shift = new Point_1.Point(0, 0); }\r\n        var width = imgDims.width, height = imgDims.height;\r\n        this._imgDims = new Dimensions_1.Dimensions(width, height);\r\n        this._shift = shift;\r\n        this._positions = relativeFaceLandmarkPositions.map(function (pt) { return pt.mul(new Point_1.Point(width, height)).add(shift); });\r\n    }\r\n    Object.defineProperty(FaceLandmarks.prototype, \"shift\", {\r\n        get: function () { return new Point_1.Point(this._shift.x, this._shift.y); },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(FaceLandmarks.prototype, \"imageWidth\", {\r\n        get: function () { return this._imgDims.width; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(FaceLandmarks.prototype, \"imageHeight\", {\r\n        get: function () { return this._imgDims.height; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(FaceLandmarks.prototype, \"positions\", {\r\n        get: function () { return this._positions; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(FaceLandmarks.prototype, \"relativePositions\", {\r\n        get: function () {\r\n            var _this = this;\r\n            return this._positions.map(function (pt) { return pt.sub(_this._shift).div(new Point_1.Point(_this.imageWidth, _this.imageHeight)); });\r\n        },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    FaceLandmarks.prototype.forSize = function (width, height) {\r\n        return new this.constructor(this.relativePositions, { width: width, height: height });\r\n    };\r\n    FaceLandmarks.prototype.shiftBy = function (x, y) {\r\n        return new this.constructor(this.relativePositions, this._imgDims, new Point_1.Point(x, y));\r\n    };\r\n    FaceLandmarks.prototype.shiftByPoint = function (pt) {\r\n        return this.shiftBy(pt.x, pt.y);\r\n    };\r\n    /**\r\n     * Aligns the face landmarks after face detection from the relative positions of the faces\r\n     * bounding box, or it's current shift. This function should be used to align the face images\r\n     * after face detection has been performed, before they are passed to the face recognition net.\r\n     * This will make the computed face descriptor more accurate.\r\n     *\r\n     * @param detection (optional) The bounding box of the face or the face detection result. If\r\n     * no argument was passed the position of the face landmarks are assumed to be relative to\r\n     * it's current shift.\r\n     * @returns The bounding box of the aligned face.\r\n     */\r\n    FaceLandmarks.prototype.align = function (detection, options) {\r\n        if (options === void 0) { options = {}; }\r\n        if (detection) {\r\n            var box = detection instanceof FaceDetection_1.FaceDetection\r\n                ? detection.box.floor()\r\n                : new Box_1.Box(detection);\r\n            return this.shiftBy(box.x, box.y).align(null, options);\r\n        }\r\n        var _a = Object.assign({}, { useDlibAlignment: false, minBoxPadding: 0.2 }, options), useDlibAlignment = _a.useDlibAlignment, minBoxPadding = _a.minBoxPadding;\r\n        if (useDlibAlignment) {\r\n            return this.alignDlib();\r\n        }\r\n        return this.alignMinBbox(minBoxPadding);\r\n    };\r\n    FaceLandmarks.prototype.alignDlib = function () {\r\n        var centers = this.getRefPointsForAlignment();\r\n        var leftEyeCenter = centers[0], rightEyeCenter = centers[1], mouthCenter = centers[2];\r\n        var distToMouth = function (pt) { return mouthCenter.sub(pt).magnitude(); };\r\n        var eyeToMouthDist = (distToMouth(leftEyeCenter) + distToMouth(rightEyeCenter)) / 2;\r\n        var size = Math.floor(eyeToMouthDist / relScale);\r\n        var refPoint = utils_1.getCenterPoint(centers);\r\n        // TODO: pad in case rectangle is out of image bounds\r\n        var x = Math.floor(Math.max(0, refPoint.x - (relX * size)));\r\n        var y = Math.floor(Math.max(0, refPoint.y - (relY * size)));\r\n        return new Rect_1.Rect(x, y, Math.min(size, this.imageWidth + x), Math.min(size, this.imageHeight + y));\r\n    };\r\n    FaceLandmarks.prototype.alignMinBbox = function (padding) {\r\n        var box = ops_1.minBbox(this.positions);\r\n        return box.pad(box.width * padding, box.height * padding);\r\n    };\r\n    FaceLandmarks.prototype.getRefPointsForAlignment = function () {\r\n        throw new Error('getRefPointsForAlignment not implemented by base class');\r\n    };\r\n    return FaceLandmarks;\r\n}());\r\nexports.FaceLandmarks = FaceLandmarks;\r\n//# sourceMappingURL=FaceLandmarks.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar tf = require(\"@tensorflow/tfjs-core\");\r\nfunction extractConvParamsFactory(extractWeights, paramMappings) {\r\n    return function (channelsIn, channelsOut, filterSize, mappedPrefix) {\r\n        var filters = tf.tensor4d(extractWeights(channelsIn * channelsOut * filterSize * filterSize), [filterSize, filterSize, channelsIn, channelsOut]);\r\n        var bias = tf.tensor1d(extractWeights(channelsOut));\r\n        paramMappings.push({ paramPath: mappedPrefix + \"/filters\" }, { paramPath: mappedPrefix + \"/bias\" });\r\n        return { filters: filters, bias: bias };\r\n    };\r\n}\r\nexports.extractConvParamsFactory = extractConvParamsFactory;\r\n//# sourceMappingURL=extractConvParamsFactory.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar utils_1 = require(\"../utils\");\r\nvar Dimensions = /** @class */ (function () {\r\n    function Dimensions(width, height) {\r\n        if (!utils_1.isValidNumber(width) || !utils_1.isValidNumber(height)) {\r\n            throw new Error(\"Dimensions.constructor - expected width and height to be valid numbers, instead have \" + JSON.stringify({ width: width, height: height }));\r\n        }\r\n        this._width = width;\r\n        this._height = height;\r\n    }\r\n    Object.defineProperty(Dimensions.prototype, \"width\", {\r\n        get: function () { return this._width; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(Dimensions.prototype, \"height\", {\r\n        get: function () { return this._height; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Dimensions.prototype.reverse = function () {\r\n        return new Dimensions(1 / this.width, 1 / this.height);\r\n    };\r\n    return Dimensions;\r\n}());\r\nexports.Dimensions = Dimensions;\r\n//# sourceMappingURL=Dimensions.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nfunction getModelUris(uri, defaultModelName) {\r\n    var defaultManifestFilename = defaultModelName + \"-weights_manifest.json\";\r\n    if (!uri) {\r\n        return {\r\n            modelBaseUri: '',\r\n            manifestUri: defaultManifestFilename\r\n        };\r\n    }\r\n    if (uri === '/') {\r\n        return {\r\n            modelBaseUri: '/',\r\n            manifestUri: \"/\" + defaultManifestFilename\r\n        };\r\n    }\r\n    var protocol = uri.startsWith('http://') ? 'http://' : uri.startsWith('https://') ? 'https://' : '';\r\n    uri = uri.replace(protocol, '');\r\n    var parts = uri.split('/').filter(function (s) { return s; });\r\n    var manifestFile = uri.endsWith('.json')\r\n        ? parts[parts.length - 1]\r\n        : defaultManifestFilename;\r\n    var modelBaseUri = protocol + (uri.endsWith('.json') ? parts.slice(0, parts.length - 1) : parts).join('/');\r\n    modelBaseUri = uri.startsWith('/') ? \"/\" + modelBaseUri : modelBaseUri;\r\n    return {\r\n        modelBaseUri: modelBaseUri,\r\n        manifestUri: modelBaseUri === '/' ? \"/\" + manifestFile : modelBaseUri + \"/\" + manifestFile\r\n    };\r\n}\r\nexports.getModelUris = getModelUris;\r\n//# sourceMappingURL=getModelUris.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar tslib_1 = require(\"tslib\");\r\nvar ObjectDetection_1 = require(\"./ObjectDetection\");\r\nvar FaceDetection = /** @class */ (function (_super) {\r\n    tslib_1.__extends(FaceDetection, _super);\r\n    function FaceDetection(score, relativeBox, imageDims) {\r\n        return _super.call(this, score, score, '', relativeBox, imageDims) || this;\r\n    }\r\n    FaceDetection.prototype.forSize = function (width, height) {\r\n        var _a = _super.prototype.forSize.call(this, width, height), score = _a.score, relativeBox = _a.relativeBox, imageDims = _a.imageDims;\r\n        return new FaceDetection(score, relativeBox, imageDims);\r\n    };\r\n    return FaceDetection;\r\n}(ObjectDetection_1.ObjectDetection));\r\nexports.FaceDetection = FaceDetection;\r\n//# sourceMappingURL=FaceDetection.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar tslib_1 = require(\"tslib\");\r\nvar utils_1 = require(\"../utils\");\r\nvar FaceLandmarks_1 = require(\"./FaceLandmarks\");\r\nvar FaceLandmarks5 = /** @class */ (function (_super) {\r\n    tslib_1.__extends(FaceLandmarks5, _super);\r\n    function FaceLandmarks5() {\r\n        return _super !== null && _super.apply(this, arguments) || this;\r\n    }\r\n    FaceLandmarks5.prototype.getRefPointsForAlignment = function () {\r\n        var pts = this.positions;\r\n        return [\r\n            pts[0],\r\n            pts[1],\r\n            utils_1.getCenterPoint([pts[3], pts[4]])\r\n        ];\r\n    };\r\n    return FaceLandmarks5;\r\n}(FaceLandmarks_1.FaceLandmarks));\r\nexports.FaceLandmarks5 = FaceLandmarks5;\r\n//# sourceMappingURL=FaceLandmarks5.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar iou_1 = require(\"./iou\");\r\nfunction nonMaxSuppression(boxes, scores, iouThreshold, isIOU) {\r\n    if (isIOU === void 0) { isIOU = true; }\r\n    var indicesSortedByScore = scores\r\n        .map(function (score, boxIndex) { return ({ score: score, boxIndex: boxIndex }); })\r\n        .sort(function (c1, c2) { return c1.score - c2.score; })\r\n        .map(function (c) { return c.boxIndex; });\r\n    var pick = [];\r\n    var _loop_1 = function () {\r\n        var curr = indicesSortedByScore.pop();\r\n        pick.push(curr);\r\n        var indices = indicesSortedByScore;\r\n        var outputs = [];\r\n        for (var i = 0; i < indices.length; i++) {\r\n            var idx = indices[i];\r\n            var currBox = boxes[curr];\r\n            var idxBox = boxes[idx];\r\n            outputs.push(iou_1.iou(currBox, idxBox, isIOU));\r\n        }\r\n        indicesSortedByScore = indicesSortedByScore.filter(function (_, j) { return outputs[j] <= iouThreshold; });\r\n    };\r\n    while (indicesSortedByScore.length > 0) {\r\n        _loop_1();\r\n    }\r\n    return pick;\r\n}\r\nexports.nonMaxSuppression = nonMaxSuppression;\r\n//# sourceMappingURL=nonMaxSuppression.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar tf = require(\"@tensorflow/tfjs-core\");\r\nfunction extractFCParamsFactory(extractWeights, paramMappings) {\r\n    return function (channelsIn, channelsOut, mappedPrefix) {\r\n        var fc_weights = tf.tensor2d(extractWeights(channelsIn * channelsOut), [channelsIn, channelsOut]);\r\n        var fc_bias = tf.tensor1d(extractWeights(channelsOut));\r\n        paramMappings.push({ paramPath: mappedPrefix + \"/weights\" }, { paramPath: mappedPrefix + \"/bias\" });\r\n        return {\r\n            weights: fc_weights,\r\n            bias: fc_bias\r\n        };\r\n    };\r\n}\r\nexports.extractFCParamsFactory = extractFCParamsFactory;\r\n//# sourceMappingURL=extractFCParamsFactory.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar SeparableConvParams = /** @class */ (function () {\r\n    function SeparableConvParams(depthwise_filter, pointwise_filter, bias) {\r\n        this.depthwise_filter = depthwise_filter;\r\n        this.pointwise_filter = pointwise_filter;\r\n        this.bias = bias;\r\n    }\r\n    return SeparableConvParams;\r\n}());\r\nexports.SeparableConvParams = SeparableConvParams;\r\n//# sourceMappingURL=types.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar classes_1 = require(\"../classes\");\r\nfunction minBbox(pts) {\r\n    var xs = pts.map(function (pt) { return pt.x; });\r\n    var ys = pts.map(function (pt) { return pt.y; });\r\n    var minX = xs.reduce(function (min, x) { return x < min ? x : min; }, Infinity);\r\n    var minY = ys.reduce(function (min, y) { return y < min ? y : min; }, Infinity);\r\n    var maxX = xs.reduce(function (max, x) { return max < x ? x : max; }, 0);\r\n    var maxY = ys.reduce(function (max, y) { return max < y ? y : max; }, 0);\r\n    return new classes_1.BoundingBox(minX, minY, maxX, maxY);\r\n}\r\nexports.minBbox = minBbox;\r\n//# sourceMappingURL=minBbox.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar tslib_1 = require(\"tslib\");\r\nvar Box_1 = require(\"./Box\");\r\nvar BoundingBox = /** @class */ (function (_super) {\r\n    tslib_1.__extends(BoundingBox, _super);\r\n    function BoundingBox(left, top, right, bottom, allowNegativeDimensions) {\r\n        if (allowNegativeDimensions === void 0) { allowNegativeDimensions = false; }\r\n        return _super.call(this, { left: left, top: top, right: right, bottom: bottom }, allowNegativeDimensions) || this;\r\n    }\r\n    return BoundingBox;\r\n}(Box_1.Box));\r\nexports.BoundingBox = BoundingBox;\r\n//# sourceMappingURL=BoundingBox.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar Point = /** @class */ (function () {\r\n    function Point(x, y) {\r\n        this._x = x;\r\n        this._y = y;\r\n    }\r\n    Object.defineProperty(Point.prototype, \"x\", {\r\n        get: function () { return this._x; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(Point.prototype, \"y\", {\r\n        get: function () { return this._y; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Point.prototype.add = function (pt) {\r\n        return new Point(this.x + pt.x, this.y + pt.y);\r\n    };\r\n    Point.prototype.sub = function (pt) {\r\n        return new Point(this.x - pt.x, this.y - pt.y);\r\n    };\r\n    Point.prototype.mul = function (pt) {\r\n        return new Point(this.x * pt.x, this.y * pt.y);\r\n    };\r\n    Point.prototype.div = function (pt) {\r\n        return new Point(this.x / pt.x, this.y / pt.y);\r\n    };\r\n    Point.prototype.abs = function () {\r\n        return new Point(Math.abs(this.x), Math.abs(this.y));\r\n    };\r\n    Point.prototype.magnitude = function () {\r\n        return Math.sqrt(Math.pow(this.x, 2) + Math.pow(this.y, 2));\r\n    };\r\n    Point.prototype.floor = function () {\r\n        return new Point(Math.floor(this.x), Math.floor(this.y));\r\n    };\r\n    return Point;\r\n}());\r\nexports.Point = Point;\r\n//# sourceMappingURL=Point.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar utils_1 = require(\"../utils\");\r\nvar Point_1 = require(\"./Point\");\r\nvar Box = /** @class */ (function () {\r\n    function Box(_box, allowNegativeDimensions) {\r\n        if (allowNegativeDimensions === void 0) { allowNegativeDimensions = true; }\r\n        var box = (_box || {});\r\n        var isBbox = [box.left, box.top, box.right, box.bottom].every(utils_1.isValidNumber);\r\n        var isRect = [box.x, box.y, box.width, box.height].every(utils_1.isValidNumber);\r\n        if (!isRect && !isBbox) {\r\n            throw new Error(\"Box.constructor - expected box to be IBoundingBox | IRect, instead have \" + JSON.stringify(box));\r\n        }\r\n        var _a = isRect\r\n            ? [box.x, box.y, box.width, box.height]\r\n            : [box.left, box.top, box.right - box.left, box.bottom - box.top], x = _a[0], y = _a[1], width = _a[2], height = _a[3];\r\n        Box.assertIsValidBox({ x: x, y: y, width: width, height: height }, 'Box.constructor', allowNegativeDimensions);\r\n        this._x = x;\r\n        this._y = y;\r\n        this._width = width;\r\n        this._height = height;\r\n    }\r\n    Box.isRect = function (rect) {\r\n        return !!rect && [rect.x, rect.y, rect.width, rect.height].every(utils_1.isValidNumber);\r\n    };\r\n    Box.assertIsValidBox = function (box, callee, allowNegativeDimensions) {\r\n        if (allowNegativeDimensions === void 0) { allowNegativeDimensions = false; }\r\n        if (!Box.isRect(box)) {\r\n            throw new Error(callee + \" - invalid box: \" + JSON.stringify(box) + \", expected object with properties x, y, width, height\");\r\n        }\r\n        if (!allowNegativeDimensions && (box.width < 0 || box.height < 0)) {\r\n            throw new Error(callee + \" - width (\" + box.width + \") and height (\" + box.height + \") must be positive numbers\");\r\n        }\r\n    };\r\n    Object.defineProperty(Box.prototype, \"x\", {\r\n        get: function () { return this._x; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(Box.prototype, \"y\", {\r\n        get: function () { return this._y; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(Box.prototype, \"width\", {\r\n        get: function () { return this._width; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(Box.prototype, \"height\", {\r\n        get: function () { return this._height; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(Box.prototype, \"left\", {\r\n        get: function () { return this.x; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(Box.prototype, \"top\", {\r\n        get: function () { return this.y; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(Box.prototype, \"right\", {\r\n        get: function () { return this.x + this.width; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(Box.prototype, \"bottom\", {\r\n        get: function () { return this.y + this.height; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(Box.prototype, \"area\", {\r\n        get: function () { return this.width * this.height; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(Box.prototype, \"topLeft\", {\r\n        get: function () { return new Point_1.Point(this.left, this.top); },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(Box.prototype, \"topRight\", {\r\n        get: function () { return new Point_1.Point(this.right, this.top); },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(Box.prototype, \"bottomLeft\", {\r\n        get: function () { return new Point_1.Point(this.left, this.bottom); },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(Box.prototype, \"bottomRight\", {\r\n        get: function () { return new Point_1.Point(this.right, this.bottom); },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Box.prototype.round = function () {\r\n        var _a = [this.x, this.y, this.width, this.height]\r\n            .map(function (val) { return Math.round(val); }), x = _a[0], y = _a[1], width = _a[2], height = _a[3];\r\n        return new Box({ x: x, y: y, width: width, height: height });\r\n    };\r\n    Box.prototype.floor = function () {\r\n        var _a = [this.x, this.y, this.width, this.height]\r\n            .map(function (val) { return Math.floor(val); }), x = _a[0], y = _a[1], width = _a[2], height = _a[3];\r\n        return new Box({ x: x, y: y, width: width, height: height });\r\n    };\r\n    Box.prototype.toSquare = function () {\r\n        var _a = this, x = _a.x, y = _a.y, width = _a.width, height = _a.height;\r\n        var diff = Math.abs(width - height);\r\n        if (width < height) {\r\n            x -= (diff / 2);\r\n            width += diff;\r\n        }\r\n        if (height < width) {\r\n            y -= (diff / 2);\r\n            height += diff;\r\n        }\r\n        return new Box({ x: x, y: y, width: width, height: height });\r\n    };\r\n    Box.prototype.rescale = function (s) {\r\n        var scaleX = utils_1.isDimensions(s) ? s.width : s;\r\n        var scaleY = utils_1.isDimensions(s) ? s.height : s;\r\n        return new Box({\r\n            x: this.x * scaleX,\r\n            y: this.y * scaleY,\r\n            width: this.width * scaleX,\r\n            height: this.height * scaleY\r\n        });\r\n    };\r\n    Box.prototype.pad = function (padX, padY) {\r\n        var _a = [\r\n            this.x - (padX / 2),\r\n            this.y - (padY / 2),\r\n            this.width + padX,\r\n            this.height + padY\r\n        ], x = _a[0], y = _a[1], width = _a[2], height = _a[3];\r\n        return new Box({ x: x, y: y, width: width, height: height });\r\n    };\r\n    Box.prototype.clipAtImageBorders = function (imgWidth, imgHeight) {\r\n        var _a = this, x = _a.x, y = _a.y, right = _a.right, bottom = _a.bottom;\r\n        var clippedX = Math.max(x, 0);\r\n        var clippedY = Math.max(y, 0);\r\n        var newWidth = right - clippedX;\r\n        var newHeight = bottom - clippedY;\r\n        var clippedWidth = Math.min(newWidth, imgWidth - clippedX);\r\n        var clippedHeight = Math.min(newHeight, imgHeight - clippedY);\r\n        return (new Box({ x: clippedX, y: clippedY, width: clippedWidth, height: clippedHeight })).floor();\r\n    };\r\n    Box.prototype.shift = function (sx, sy) {\r\n        var _a = this, width = _a.width, height = _a.height;\r\n        var x = this.x + sx;\r\n        var y = this.y + sy;\r\n        return new Box({ x: x, y: y, width: width, height: height });\r\n    };\r\n    Box.prototype.padAtBorders = function (imageHeight, imageWidth) {\r\n        var w = this.width + 1;\r\n        var h = this.height + 1;\r\n        var dx = 1;\r\n        var dy = 1;\r\n        var edx = w;\r\n        var edy = h;\r\n        var x = this.left;\r\n        var y = this.top;\r\n        var ex = this.right;\r\n        var ey = this.bottom;\r\n        if (ex > imageWidth) {\r\n            edx = -ex + imageWidth + w;\r\n            ex = imageWidth;\r\n        }\r\n        if (ey > imageHeight) {\r\n            edy = -ey + imageHeight + h;\r\n            ey = imageHeight;\r\n        }\r\n        if (x < 1) {\r\n            edy = 2 - x;\r\n            x = 1;\r\n        }\r\n        if (y < 1) {\r\n            edy = 2 - y;\r\n            y = 1;\r\n        }\r\n        return { dy: dy, edy: edy, dx: dx, edx: edx, y: y, ey: ey, x: x, ex: ex, w: w, h: h };\r\n    };\r\n    Box.prototype.calibrate = function (region) {\r\n        return new Box({\r\n            left: this.left + (region.left * this.width),\r\n            top: this.top + (region.top * this.height),\r\n            right: this.right + (region.right * this.width),\r\n            bottom: this.bottom + (region.bottom * this.height)\r\n        }).toSquare().round();\r\n    };\r\n    return Box;\r\n}());\r\nexports.Box = Box;\r\n//# sourceMappingURL=Box.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar utils_1 = require(\"../utils\");\r\nvar FaceMatch = /** @class */ (function () {\r\n    function FaceMatch(label, distance) {\r\n        this._label = label;\r\n        this._distance = distance;\r\n    }\r\n    Object.defineProperty(FaceMatch.prototype, \"label\", {\r\n        get: function () { return this._label; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(FaceMatch.prototype, \"distance\", {\r\n        get: function () { return this._distance; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    FaceMatch.prototype.toString = function (withDistance) {\r\n        if (withDistance === void 0) { withDistance = true; }\r\n        return \"\" + this.label + (withDistance ? \" (\" + utils_1.round(this.distance) + \")\" : '');\r\n    };\r\n    return FaceMatch;\r\n}());\r\nexports.FaceMatch = FaceMatch;\r\n//# sourceMappingURL=FaceMatch.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nfunction shuffleArray(inputArray) {\r\n    var array = inputArray.slice();\r\n    for (var i = array.length - 1; i > 0; i--) {\r\n        var j = Math.floor(Math.random() * (i + 1));\r\n        var x = array[i];\r\n        array[i] = array[j];\r\n        array[j] = x;\r\n    }\r\n    return array;\r\n}\r\nexports.shuffleArray = shuffleArray;\r\n//# sourceMappingURL=shuffleArray.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar tslib_1 = require(\"tslib\");\r\nvar utils_1 = require(\"../utils\");\r\nvar LabeledBox_1 = require(\"./LabeledBox\");\r\nvar PredictedBox = /** @class */ (function (_super) {\r\n    tslib_1.__extends(PredictedBox, _super);\r\n    function PredictedBox(box, label, score, classScore) {\r\n        var _this = _super.call(this, box, label) || this;\r\n        _this._score = score;\r\n        _this._classScore = classScore;\r\n        return _this;\r\n    }\r\n    PredictedBox.assertIsValidPredictedBox = function (box, callee) {\r\n        LabeledBox_1.LabeledBox.assertIsValidLabeledBox(box, callee);\r\n        if (!utils_1.isValidProbablitiy(box.score)\r\n            || !utils_1.isValidProbablitiy(box.classScore)) {\r\n            throw new Error(callee + \" - expected properties score (\" + box.score + \") and (\" + box.classScore + \") to be a number between [0, 1]\");\r\n        }\r\n    };\r\n    Object.defineProperty(PredictedBox.prototype, \"score\", {\r\n        get: function () { return this._score; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    Object.defineProperty(PredictedBox.prototype, \"classScore\", {\r\n        get: function () { return this._classScore; },\r\n        enumerable: true,\r\n        configurable: true\r\n    });\r\n    return PredictedBox;\r\n}(LabeledBox_1.LabeledBox));\r\nexports.PredictedBox = PredictedBox;\r\n//# sourceMappingURL=PredictedBox.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar tslib_1 = require(\"tslib\");\r\nvar tf = require(\"@tensorflow/tfjs-core\");\r\nfunction normalize(x, meanRgb) {\r\n    return tf.tidy(function () {\r\n        var r = meanRgb[0], g = meanRgb[1], b = meanRgb[2];\r\n        var avg_r = tf.fill(tslib_1.__spreadArrays(x.shape.slice(0, 3), [1]), r);\r\n        var avg_g = tf.fill(tslib_1.__spreadArrays(x.shape.slice(0, 3), [1]), g);\r\n        var avg_b = tf.fill(tslib_1.__spreadArrays(x.shape.slice(0, 3), [1]), b);\r\n        var avg_rgb = tf.concat([avg_r, avg_g, avg_b], 3);\r\n        return tf.sub(x, avg_rgb);\r\n    });\r\n}\r\nexports.normalize = normalize;\r\n//# sourceMappingURL=normalize.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar tf = require(\"@tensorflow/tfjs-core\");\r\nvar classes_1 = require(\"../classes\");\r\nvar Dimensions_1 = require(\"../classes/Dimensions\");\r\nfunction isTensor(tensor, dim) {\r\n    return tensor instanceof tf.Tensor && tensor.shape.length === dim;\r\n}\r\nexports.isTensor = isTensor;\r\nfunction isTensor1D(tensor) {\r\n    return isTensor(tensor, 1);\r\n}\r\nexports.isTensor1D = isTensor1D;\r\nfunction isTensor2D(tensor) {\r\n    return isTensor(tensor, 2);\r\n}\r\nexports.isTensor2D = isTensor2D;\r\nfunction isTensor3D(tensor) {\r\n    return isTensor(tensor, 3);\r\n}\r\nexports.isTensor3D = isTensor3D;\r\nfunction isTensor4D(tensor) {\r\n    return isTensor(tensor, 4);\r\n}\r\nexports.isTensor4D = isTensor4D;\r\nfunction isFloat(num) {\r\n    return num % 1 !== 0;\r\n}\r\nexports.isFloat = isFloat;\r\nfunction isEven(num) {\r\n    return num % 2 === 0;\r\n}\r\nexports.isEven = isEven;\r\nfunction round(num, prec) {\r\n    if (prec === void 0) { prec = 2; }\r\n    var f = Math.pow(10, prec);\r\n    return Math.floor(num * f) / f;\r\n}\r\nexports.round = round;\r\nfunction isDimensions(obj) {\r\n    return obj && obj.width && obj.height;\r\n}\r\nexports.isDimensions = isDimensions;\r\nfunction computeReshapedDimensions(_a, inputSize) {\r\n    var width = _a.width, height = _a.height;\r\n    var scale = inputSize / Math.max(height, width);\r\n    return new Dimensions_1.Dimensions(Math.round(width * scale), Math.round(height * scale));\r\n}\r\nexports.computeReshapedDimensions = computeReshapedDimensions;\r\nfunction getCenterPoint(pts) {\r\n    return pts.reduce(function (sum, pt) { return sum.add(pt); }, new classes_1.Point(0, 0))\r\n        .div(new classes_1.Point(pts.length, pts.length));\r\n}\r\nexports.getCenterPoint = getCenterPoint;\r\nfunction range(num, start, step) {\r\n    return Array(num).fill(0).map(function (_, i) { return start + (i * step); });\r\n}\r\nexports.range = range;\r\nfunction isValidNumber(num) {\r\n    return !!num && num !== Infinity && num !== -Infinity && !isNaN(num) || num === 0;\r\n}\r\nexports.isValidNumber = isValidNumber;\r\nfunction isValidProbablitiy(num) {\r\n    return isValidNumber(num) && 0 <= num && num <= 1.0;\r\n}\r\nexports.isValidProbablitiy = isValidProbablitiy;\r\n//# sourceMappingURL=index.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar tslib_1 = require(\"tslib\");\r\ntslib_1.__exportStar(require(\"./iou\"), exports);\r\ntslib_1.__exportStar(require(\"./minBbox\"), exports);\r\ntslib_1.__exportStar(require(\"./nonMaxSuppression\"), exports);\r\ntslib_1.__exportStar(require(\"./normalize\"), exports);\r\ntslib_1.__exportStar(require(\"./padToSquare\"), exports);\r\ntslib_1.__exportStar(require(\"./shuffleArray\"), exports);\r\nfunction sigmoid(x) {\r\n    return 1 / (1 + Math.exp(-x));\r\n}\r\nexports.sigmoid = sigmoid;\r\nfunction inverseSigmoid(x) {\r\n    return Math.log(x / (1 - x));\r\n}\r\nexports.inverseSigmoid = inverseSigmoid;\r\n//# sourceMappingURL=index.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar tf = require(\"@tensorflow/tfjs-core\");\r\nfunction depthwiseSeparableConv(x, params, stride) {\r\n    return tf.tidy(function () {\r\n        var out = tf.separableConv2d(x, params.depthwise_filter, params.pointwise_filter, stride, 'same');\r\n        out = tf.add(out, params.bias);\r\n        return out;\r\n    });\r\n}\r\nexports.depthwiseSeparableConv = depthwiseSeparableConv;\r\n//# sourceMappingURL=depthwiseSeparableConv.js.map","\"use strict\";\r\nObject.defineProperty(exports, \"__esModule\", { value: true });\r\nvar tf = require(\"@tensorflow/tfjs-core\");\r\n/**\r\n * Pads the smaller dimension of an image tensor with zeros, such that width === height.\r\n *\r\n * @param imgTensor The image tensor.\r\n * @param isCenterImage (optional, default: false) If true, add an equal amount of padding on\r\n * both sides of the minor dimension oof the image.\r\n * @returns The padded tensor with width === height.\r\n */\r\nfunction padToSquare(imgTensor, isCenterImage) {\r\n    if (isCenterImage === void 0) { isCenterImage = false; }\r\n    return tf.tidy(function () {\r\n        var _a = imgTensor.shape.slice(1), height = _a[0], width = _a[1];\r\n        if (height === width) {\r\n            return imgTensor;\r\n        }\r\n        var dimDiff = Math.abs(height - width);\r\n        var paddingAmount = Math.round(dimDiff * (isCenterImage ? 0.5 : 1));\r\n        var paddingAxis = height > width ? 2 : 1;\r\n        var createPaddingTensor = function (paddingAmount) {\r\n            var paddingTensorShape = imgTensor.shape.slice();\r\n            paddingTensorShape[paddingAxis] = paddingAmount;\r\n            return tf.fill(paddingTensorShape, 0);\r\n        };\r\n        var paddingTensorAppend = createPaddingTensor(paddingAmount);\r\n        var remainingPaddingAmount = dimDiff - paddingTensorAppend.shape[paddingAxis];\r\n        var paddingTensorPrepend = isCenterImage && remainingPaddingAmount\r\n            ? createPaddingTensor(remainingPaddingAmount)\r\n            : null;\r\n        var tensorsToStack = [\r\n            paddingTensorPrepend,\r\n            imgTensor,\r\n            paddingTensorAppend\r\n        ]\r\n            .filter(function (t) { return !!t; })\r\n            .map(function (t) { return t.toFloat(); });\r\n        return tf.concat(tensorsToStack, paddingAxis);\r\n    });\r\n}\r\nexports.padToSquare = padToSquare;\r\n//# sourceMappingURL=padToSquare.js.map"],"sourceRoot":""}