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index.js
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index.js
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/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
import * as tf from '@tensorflow/tfjs';
import {antirectifier} from './custom_layer';
function customLayerDemo() {
let imgElement = document.getElementById('cat');
// Layer expects first dimension to be batch, therefore expandDims.
const img = tf.browser.fromPixels(imgElement).toFloat().expandDims(0);
const layer = antirectifier();
const [posTensor, negTensor] = tf.split(layer.apply(img), 2, 3);
const posCanvas = document.createElement('canvas');
tensorToCanvas(posTensor, posCanvas);
document.getElementById('output_image_1').appendChild(posCanvas);
const negCanvas = document.createElement('canvas');
tensorToCanvas(negTensor, negCanvas);
document.getElementById('output_image_2').appendChild(negCanvas);
}
function tensorToCanvas(tensor, canvas) {
const ctx = canvas.getContext('2d');
const [batch, height, width, nChan] = tensor.shape;
console.assert(nChan == 3);
console.assert(batch == 1);
canvas.width = width;
canvas.height = height;
const imageData = new ImageData(width, height);
const data = tensor.dataSync();
for (let i = 0; i < height * width; ++i) {
const i4 = i * 4;
const i3 = i * 3;
imageData.data[i4 + 0] = data[i3 + 0] * 2;
imageData.data[i4 + 1] = data[i3 + 1] * 2;
imageData.data[i4 + 2] = data[i3 + 2] * 2;
imageData.data[i4 + 3] = 255;
}
ctx.putImageData(imageData, 0, 0);
};
customLayerDemo();