53 lines
No EOL
2.4 KiB
JavaScript
53 lines
No EOL
2.4 KiB
JavaScript
import * as tslib_1 from "tslib";
|
|
import * as tf from '@tensorflow/tfjs-core';
|
|
import { NeuralNetwork, normalize, toNetInput } from 'tfjs-image-recognition-base';
|
|
import { denseBlock3 } from './denseBlock';
|
|
import { extractParamsFromWeigthMapTiny } from './extractParamsFromWeigthMapTiny';
|
|
import { extractParamsTiny } from './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 = normalize(batchTensor, meanRgb).div(tf.scalar(255));
|
|
var out = denseBlock3(normalized, params.dense0, true);
|
|
out = denseBlock3(out, params.dense1);
|
|
out = 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*/, 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(weightMap);
|
|
};
|
|
TinyFaceFeatureExtractor.prototype.extractParams = function (weights) {
|
|
return extractParamsTiny(weights);
|
|
};
|
|
return TinyFaceFeatureExtractor;
|
|
}(NeuralNetwork));
|
|
export { TinyFaceFeatureExtractor };
|
|
//# sourceMappingURL=TinyFaceFeatureExtractor.js.map
|