speedy-vision
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GPU-accelerated Computer Vision for JavaScript
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HTML
<!--
speedy-vision.js
GPU-accelerated Computer Vision for JavaScript
Copyright 2020-2022 Alexandre Martins <alemartf(at)gmail.com>
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.
convolution.html
Image convolution
-->
<html>
<head>
<meta charset="utf-8">
<meta name="description" content="speedy-vision.js: GPU-accelerated Computer Vision for JavaScript">
<meta name="author" content="Alexandre Martins">
<title>Cool effects with image convolutions</title>
<script src="../dist/speedy-vision.js"></script>
<link href="style.css" rel="stylesheet">
</head>
<body>
<h1>Image convolution</h1>
<form>
<div>
Select the
<select id="template"></select>
convolution kernel or edit the fields below:
</div>
<div class="separator"></div>
<div>
<table>
<tr>
<td><input type="text" id="kernel-0" value="0"></td>
<td><input type="text" id="kernel-3" value="0"></td>
<td><input type="text" id="kernel-6" value="0"></td>
</tr>
<tr>
<td><input type="text" id="kernel-1" value="0"></td>
<td><input type="text" id="kernel-4" value="1"></td>
<td><input type="text" id="kernel-7" value="0"></td>
</tr>
<tr>
<td><input type="text" id="kernel-2" value="0"></td>
<td><input type="text" id="kernel-5" value="0"></td>
<td><input type="text" id="kernel-8" value="0"></td>
</tr>
</table>
</div>
</form>
<div>
<span id="status"></span>
<canvas id="canvas-demo"></canvas>
</div>
<div>
<button id="play">Play / pause</button>
</div>
<video
src="../assets/jelly.webm"
poster="../assets/loading.jpg"
width="426" height="240"
preload="auto"
loop muted hidden
title="Free video by Chris Munnik from https://www.pexels.com/pt-br/video/3297379/">
</video>
<script>
// Convolution kernels written in column-major format (3x3)
const template = {
"Original":
[
0, 0, 0,
0, 1, 0,
0, 0, 0,
],
"Brighten":
[
0, 0, 0,
0, 2, 0,
0, 0, 0,
],
"Simple blur":
[
0.11111, 0.11111, 0.11111,
0.11111, 0.11111, 0.11111,
0.11111, 0.11111, 0.11111,
],
"Gaussian blur":
[
0.0625, 0.125, 0.0625,
0.125, 0.25, 0.125,
0.0625, 0.125, 0.0625,
],
"Sharpen":
[
0,-1, 0,
-1, 5,-1,
0,-1, 0,
],
"Emboss":
[
-2,-1, 0,
-1, 1, 1,
0, 1, 2,
],
"Edges":
[
1, 1, 1,
1,-8, 1,
1, 1, 1,
],
"Horizontal lines":
[
-1, 2,-1,
-1, 2,-1,
-1, 2,-1,
],
"Vertical lines":
[
-1,-1,-1,
2, 2, 2,
-1,-1,-1,
],
"Scharr (X)":
[
-3,-10,-3,
0, 0, 0,
3, 10, 3,
],
"Scharr (Y)":
[
-3, 0, 3,
-10, 0, 10,
-3, 0, 3,
],
"Laplacian":
[
0, 1, 0,
1,-4, 1,
0, 1, 0,
],
};
window.onload = async function()
{
// input fields
const kernelElement = [...(new Array(9)).keys()].map(k => document.getElementById('kernel-' + k));
// setup the <select> element
const templateSelector = document.getElementById('template');
for(let templateName in template) {
const option = document.createElement('option');
const text = document.createTextNode(templateName);
option.value = templateName;
option.selected = (option.value == 'Original');
option.appendChild(text);
templateSelector.appendChild(option);
}
templateSelector.onchange = () => {
const name = templateSelector.value;
kernelElement.forEach((inputField, i) => inputField.value = template[name][i]);
updatePipeline();
};
// update the pipeline as soon as a text field is changed
for(let inputField of kernelElement)
inputField.oninput = updatePipeline;
// load the video
const video = document.querySelector('video');
const media = await Speedy.load(video);
video.play();
// play/pause
const playButton = document.getElementById('play');
playButton.onclick = () => video.paused ? video.play() : video.pause();
// create a pipeline
const pipeline = Speedy.Pipeline();
const source = Speedy.Image.Source();
const sink = Speedy.Image.Sink();
const convolution = Speedy.Filter.Convolution();
source.media = media;
source.output().connectTo(convolution.input());
convolution.output().connectTo(sink.input());
pipeline.init(source, sink, convolution);
// update the pipeline
function updatePipeline()
{
const entries = kernelElement.map(field => Number(field.value));
convolution.kernel = Speedy.Matrix(3, 3, entries);
}
// Main loop
(function() {
const canvas = createCanvas(media.width, media.height, video.title);
let image = null, frameReady = false;
async function update()
{
const result = await pipeline.run();
image = result.image;
frameReady = true;
setTimeout(update, 1000 / 60);
}
update();
function render()
{
if(frameReady) {
draw(image, canvas);
}
frameReady = false;
requestAnimationFrame(render);
}
render();
setInterval(renderStatus, 200);
})();
}
function createCanvas(width, height, title)
{
const canvas = document.getElementById('canvas-demo') || document.createElement('canvas');
canvas.width = width;
canvas.height = height;
canvas.title = title;
if(!document.body.contains(canvas))
document.body.appendChild(canvas);
return canvas;
}
function renderStatus()
{
const status = document.getElementById('status');
status.innerText = `FPS: ${Speedy.fps}`;
}
function draw(media, canvas, x = 0, y = 0, width = media.width, height = media.height)
{
const ctx = canvas.getContext('2d');
ctx.drawImage(media.source, x, y, width, height);
}
</script>
<mark>Powered by <a href="https://github.com/alemart/speedy-vision">speedy-vision.js</a></mark>
</body>
</html>