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face-api.js

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JavaScript API for face detection and face recognition in the browser with tensorflow.js

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import { __extends } from "tslib"; import * as tf from '@tensorflow/tfjs-core'; import { fullyConnectedLayer } from '../common/fullyConnectedLayer'; import { NetInput } from '../dom'; import { NeuralNetwork } from '../NeuralNetwork'; import { extractParams } from './extractParams'; import { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap'; import { seperateWeightMaps } from './util'; var FaceProcessor = /** @class */ (function (_super) { __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 NetInput ? _this.faceFeatureExtractor.forwardInput(input) : input; return 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(weights, this.getClassifierChannelsIn(), this.getClassifierChannelsOut()); }; FaceProcessor.prototype.extractParamsFromWeigthMap = function (weightMap) { var _a = seperateWeightMaps(weightMap), featureExtractorMap = _a.featureExtractorMap, classifierMap = _a.classifierMap; this.faceFeatureExtractor.loadFromWeightMap(featureExtractorMap); return 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; }(NeuralNetwork)); export { FaceProcessor }; //# sourceMappingURL=FaceProcessor.js.map