2020-08-20 02:05:34 +02:00
|
|
|
"use strict";
|
|
|
|
|
Object.defineProperty(exports, "__esModule", { value: true });
|
|
|
|
|
exports.normalize = void 0;
|
|
|
|
|
const tf = require("@tensorflow/tfjs-core");
|
|
|
|
|
function normalize(x, meanRgb) {
|
2020-08-18 14:04:33 +02:00
|
|
|
return tf.tidy(() => {
|
|
|
|
|
const [r, g, b] = meanRgb;
|
|
|
|
|
const avg_r = tf.fill([...x.shape.slice(0, 3), 1], r);
|
|
|
|
|
const avg_g = tf.fill([...x.shape.slice(0, 3), 1], g);
|
|
|
|
|
const avg_b = tf.fill([...x.shape.slice(0, 3), 1], b);
|
|
|
|
|
const avg_rgb = tf.concat([avg_r, avg_g, avg_b], 3);
|
|
|
|
|
return tf.sub(x, avg_rgb);
|
|
|
|
|
});
|
|
|
|
|
}
|
2020-08-20 02:05:34 +02:00
|
|
|
exports.normalize = normalize;
|
2020-08-18 14:04:33 +02:00
|
|
|
//# sourceMappingURL=normalize.js.map
|
