"use strict";
|
Object.defineProperty(exports, "__esModule", { value: true });
|
var tslib_1 = require("tslib");
|
var tf = require("@tensorflow/tfjs-core");
|
var fullyConnectedLayer_1 = require("../common/fullyConnectedLayer");
|
var dom_1 = require("../dom");
|
var NeuralNetwork_1 = require("../NeuralNetwork");
|
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 dom_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;
|
}(NeuralNetwork_1.NeuralNetwork));
|
exports.FaceProcessor = FaceProcessor;
|
//# sourceMappingURL=FaceProcessor.js.map
|