47 lines
2.0 KiB
JavaScript
47 lines
2.0 KiB
JavaScript
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import * as tf from '@tensorflow/tfjs-core';
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function getCenterCoordinatesAndSizesLayer(x) {
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const vec = tf.unstack(tf.transpose(x, [1, 0]));
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const sizes = [
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tf.sub(vec[2], vec[0]),
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tf.sub(vec[3], vec[1])
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];
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const centers = [
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tf.add(vec[0], tf.div(sizes[0], tf.scalar(2))),
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tf.add(vec[1], tf.div(sizes[1], tf.scalar(2)))
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];
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return {
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sizes,
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centers
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};
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}
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function decodeBoxesLayer(x0, x1) {
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const { sizes, centers } = getCenterCoordinatesAndSizesLayer(x0);
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const vec = tf.unstack(tf.transpose(x1, [1, 0]));
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const div0_out = tf.div(tf.mul(tf.exp(tf.div(vec[2], tf.scalar(5))), sizes[0]), tf.scalar(2));
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const add0_out = tf.add(tf.mul(tf.div(vec[0], tf.scalar(10)), sizes[0]), centers[0]);
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const div1_out = tf.div(tf.mul(tf.exp(tf.div(vec[3], tf.scalar(5))), sizes[1]), tf.scalar(2));
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const add1_out = tf.add(tf.mul(tf.div(vec[1], tf.scalar(10)), sizes[1]), centers[1]);
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return tf.transpose(tf.stack([
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tf.sub(add0_out, div0_out),
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tf.sub(add1_out, div1_out),
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tf.add(add0_out, div0_out),
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tf.add(add1_out, div1_out)
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]), [1, 0]);
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}
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export function outputLayer(boxPredictions, classPredictions, params) {
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return tf.tidy(() => {
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const batchSize = boxPredictions.shape[0];
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let boxes = decodeBoxesLayer(tf.reshape(tf.tile(params.extra_dim, [batchSize, 1, 1]), [-1, 4]), tf.reshape(boxPredictions, [-1, 4]));
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boxes = tf.reshape(boxes, [batchSize, (boxes.shape[0] / batchSize), 4]);
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const scoresAndClasses = tf.sigmoid(tf.slice(classPredictions, [0, 0, 1], [-1, -1, -1]));
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let scores = tf.slice(scoresAndClasses, [0, 0, 0], [-1, -1, 1]);
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scores = tf.reshape(scores, [batchSize, scores.shape[1]]);
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const boxesByBatch = tf.unstack(boxes);
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const scoresByBatch = tf.unstack(scores);
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return {
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boxes: boxesByBatch,
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scores: scoresByBatch
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};
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});
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}
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//# sourceMappingURL=outputLayer.js.map
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