54 lines
No EOL
2.4 KiB
JavaScript
54 lines
No EOL
2.4 KiB
JavaScript
import * as tslib_1 from "tslib";
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import * as tf from '@tensorflow/tfjs-core';
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import { NeuralNetwork, normalize, toNetInput } from 'tfjs-image-recognition-base';
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import { denseBlock4 } from './denseBlock';
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import { extractParams } from './extractParams';
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import { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';
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var FaceFeatureExtractor = /** @class */ (function (_super) {
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tslib_1.__extends(FaceFeatureExtractor, _super);
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function FaceFeatureExtractor() {
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return _super.call(this, 'FaceFeatureExtractor') || this;
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}
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FaceFeatureExtractor.prototype.forwardInput = function (input) {
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var params = this.params;
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if (!params) {
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throw new Error('FaceFeatureExtractor - load model before inference');
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}
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return tf.tidy(function () {
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var batchTensor = input.toBatchTensor(112, true);
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var meanRgb = [122.782, 117.001, 104.298];
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var normalized = normalize(batchTensor, meanRgb).div(tf.scalar(255));
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var out = denseBlock4(normalized, params.dense0, true);
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out = denseBlock4(out, params.dense1);
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out = denseBlock4(out, params.dense2);
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out = denseBlock4(out, params.dense3);
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out = tf.avgPool(out, [7, 7], [2, 2], 'valid');
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return out;
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});
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};
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FaceFeatureExtractor.prototype.forward = function (input) {
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return tslib_1.__awaiter(this, void 0, void 0, function () {
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var _a;
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return tslib_1.__generator(this, function (_b) {
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switch (_b.label) {
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case 0:
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_a = this.forwardInput;
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return [4 /*yield*/, toNetInput(input)];
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case 1: return [2 /*return*/, _a.apply(this, [_b.sent()])];
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}
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});
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});
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};
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FaceFeatureExtractor.prototype.getDefaultModelName = function () {
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return 'face_feature_extractor_model';
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};
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FaceFeatureExtractor.prototype.extractParamsFromWeigthMap = function (weightMap) {
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return extractParamsFromWeigthMap(weightMap);
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};
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FaceFeatureExtractor.prototype.extractParams = function (weights) {
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return extractParams(weights);
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};
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return FaceFeatureExtractor;
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}(NeuralNetwork));
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export { FaceFeatureExtractor };
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//# sourceMappingURL=FaceFeatureExtractor.js.map
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