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- import * as tf from '@tensorflow/tfjs-core';
- import { convLayer } from '../common';
- import { fullyConnectedLayer } from '../common/fullyConnectedLayer';
- import { prelu } from './prelu';
- import { sharedLayer } from './sharedLayers';
- export function ONet(x, params) {
- return tf.tidy(function () {
- var out = sharedLayer(x, params);
- out = tf.maxPool(out, [2, 2], [2, 2], 'same');
- out = convLayer(out, params.conv4, 'valid');
- out = prelu(out, params.prelu4_alpha);
- var vectorized = tf.reshape(out, [out.shape[0], params.fc1.weights.shape[0]]);
- var fc1 = fullyConnectedLayer(vectorized, params.fc1);
- var prelu5 = prelu(fc1, params.prelu5_alpha);
- var fc2_1 = fullyConnectedLayer(prelu5, params.fc2_1);
- var max = tf.expandDims(tf.max(fc2_1, 1), 1);
- var prob = tf.softmax(tf.sub(fc2_1, max), 1);
- var regions = fullyConnectedLayer(prelu5, params.fc2_2);
- var points = fullyConnectedLayer(prelu5, params.fc2_3);
- var scores = tf.unstack(prob, 1)[1];
- return { scores: scores, regions: regions, points: points };
- });
- }
- //# sourceMappingURL=ONet.js.map
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