Related
I have found similar questions to mine on SO, but have not yet come across an answer to this problem. I have a rgb8 encoded image that I am trying to display in-browser, either in an img or canvas element. I am unsure how to convert this pixel data into an image properly, and was looking for any insight.
For context, the source of this rgb8 data is from a ROS topic with type sensor_msgs/Image. When subscribing to this topic using roslibjs, I am given the following object:
{
data: “MT4+CR…”, (of length 1228800)
encoding: "rgb8",
header: {
frame_id: “camera_color_optical_frame”,
seq: 1455,
stamp: ...timestamp info
},
height: 480,
is_bigendian: 0,
step: 1920,
width: 640
}
With the data string, I have tried displaying it on canvas, converting it to base64, etc. but have not been able to. I know about web_video_server in ROS to help send these images over a port, but that is not an option for me unfortunately - I need to work directly with the data.
Is there a way I can go about displaying this rgb8 data in the browser? Based on the documentation on here, data should be represented as a uint8[] (if that helps).
Thank you so much!
First create a canvas of the correct size and obtain a CanvasRenderingContext2D
// Assuming that imgMes is the image message as linked in question
const can = document.createElement("canvas");
can.width = imgMes.width;
can.height = imgMes.height;
const ctx = can.getcontext("2d");
Then create an image buffer to hold the pixels
const imgData = ctx.createImageData(0, 0, imgMes.width, imgMes.height);
const data = imgData.data;
const inData = imgMes.data;
Then read the data from the image message. Making sure to use the correct order as defined in the flag is_bigendian
var i = 0, j, y = 0, x;
while (y < imgMes.height) {
j = y * imgMes.step;
for (x = 0; x < imgMes.width; x ++) {
if (imgMes.is_bigendian) {
data[i] = inData[j]; // red
data[i + 1] = inData[j + 1]; // green
data[i + 2] = inData[j + 2]; // blue
} else {
data[i + 2] = inData[j]; // blue
data[i + 1] = inData[j + 1]; // green
data[i] = inData[j + 2]; // red
}
data[i + 3] = 255; // alpha
i += 4;
j += 3;
}
y++;
}
The put the pixel data into the canvas;
ctx.putImageData(imgData, 0, 0);
And add the canvas to your HTML
document.body.appendChild(can);
And you are done.
Note that I may have is_bigendian the wrong way around. If so just change the line if (imgMes.is_bigendian) { to if (!imgMes.is_bigendian) {
UPDATE
With more information regarding the data format i was able to extract the image.
I used atob to decode the Base64 string. This returns another string. I then iterated each character in the string, getting the character code to add to each pixel.
It is unclear where the endianess is. My guess is that it is in the decoded string and thus the code swaps bytes for each char code as it makes no sense to have endianess on multiples of 3 bytes
const can = document.createElement("canvas");
can.width = imgMes.width;
can.height = imgMes.height;
const ctx = can.getContext("2d");
const imgData = ctx.createImageData(imgMes.width, imgMes.height);
const data = imgData.data;
const inData = atob(imgMes.data);
var j = 0; i = 4; // j data in , i data out
while( j < inData.length) {
const w1 = inData.charCodeAt(j++); // read 3 16 bit words represent 1 pixel
const w2 = inData.charCodeAt(j++);
const w3 = inData.charCodeAt(j++);
if (!imgMes.is_bigendian) {
data[i++] = w1; // red
data[i++] = w2; // green
data[i++] = w3; // blue
} else {
data[i++] = (w1 >> 8) + ((w1 & 0xFF) << 8);
data[i++] = (w2 >> 8) + ((w2 & 0xFF) << 8);
data[i++] = (w3 >> 8) + ((w3 & 0xFF) << 8);
}
data[i++] = 255; // alpha
}
ctx.putImageData(imgData, 0, 0);
document.body.appendChild(can);
From the example data I got an image of some paving near a road.
How would you manually calculate RGB multipliers and offsets to adjust the brightness of a color so that an argument of -1 was all black and 1 was all white?
If it's less than 1, it's easy. R, G, and B are just multiplied by (1 + brightness).
But how would you calculate the offsets for brightness values greater than 0?
It is simple channel per channel interpolation math. It does not look simple only because there are three channels and they need de/serialization for various purposes.
// Usage.
acoolor:uint = parseRGB(200, 150, 100);
trace(colorToRGB(brightNess(acoolor, 0.5)));
trace(colorToRGB(brightNess(acoolor, -0.5)));
// Implementation.
function parseRGB(ared:uint, agreen:uint, ablue:uint):uint
{
var result:uint;
result += (ared << 16) & 0xFF0000;
result += (agreen << 8) & 0xFF00;
result += (ablue) & 0xFF;
return result;
}
function colorToRGB(acolor:uint):Array
{
result = new Array;
result[0] = (acolor >> 16) & 0xFF;
result[1] = (acolor >> 8) & 0xFF;
result[2] = (acolor) & 0xFF;
return result;
}
function RGBToColor(anrgb:Array):uint
{
return parseRGB.apply(this, anrgb);
}
function brightChannel(achannel:uint, adjust:Number):uint
{
if (adjust <= -1) return 0;
if (adjust >= 1) return 255;
if (adjust < 0) return achannel * (1 + adjust);
if (adjust > 0) return achannel + (255 - achannel) * adjust;
// If adjust == 0
return achannel;
}
function brightNess(acolor:uint, adjust:Number):uint
{
var anrgb:Array = colorToRGB(acolor);
for (var i:int = 0; i < 3; i++)
anrgb[i] = brightChannel(anrgb[i], adjust);
return RGBToColor(anrgb);
}
I need to check if an image exists in another image using JavaScript, I need to know what are the best approaches (algorithm) and solutions (ex: librarie) to do this operations
I explained what I need to do in this image:
Using the GPU to help in image processing.
Using the 2D API and some simple tricks you can exploit the GPUs power to speed up Javascript.
Difference
To find an image you need to compare the pixels you are looking for (A) against the pixels in the image (B). If the difference between the Math.abs(A-B) === 0 then the pixels are the same.
A function to do this may look like the following
function findDif(imageDataSource, imageDataDest, xx,yy)
const ds = imageDataSource.data;
const dd = imageDataDest.data;
const w = imageDataSource.width;
const h = imageDataSource.height;
var x,y;
var dif = 0;
for(y = 0; y < h; y += 1){
for(x = 0; x < w; x += 1){
var indexS = (x + y * w) * 4;
var indexD = (x + xx + (y + yy) * imageDataDest.width) * 4;
dif += Math.abs(ds[indexS]-dd[indexD]);
dif += Math.abs(ds[indexS + 1]-dd[indexD + 1]);
dif += Math.abs(ds[indexS + 2]-dd[indexD + 2]);
}
}
return dif;
}
var source = sourceCanvas.getContext("2d").getImageData(0,0,sourceCanvas.width,sourceCanvas.height);
var dest = destinationCanvas.getContext("2d").getImageData(0,0,destinationCanvas.width,destinationCanvas.height);
if(findDif(source,dest,100,100)){ // is the image at 100,100?
// Yes image is very similar
}
Where the source is the image we are looking for and the dest is the image we want to find it in. We run the function for every location that the image may be and if the result is under a level then its a good chance we have found it.
But this is very very slow in JS. This is where the GPU can help.
Using the ctx.globalCompositeOperation = "difference"; operation we can speed up the process as it will do the difference calculation for us
When you render with the comp operation "difference" the resulting pixels are the difference between the pixels you are drawing and those that are already on the canvas. Thus if you draw on something that is the same the result is all pixels are black (no difference)
To find a similar image in the image you render the image you are testing for at each location on the canvas that you want to test for. Then you get the sum of all the pixels you just rendered on, if the result is under a threshold that you have set then the image under that area is very similar to the image you are testing for.
But we still need to count all the pixels one by one.
A GPU mean function
The comp op "difference" already does the pixel difference calculation for you, but to get the sum you can use the inbuilt image smoothing.
After you have rendered to find the difference you take that area and render it at a smaller scale with ctx.imageSmoothingEnabled = true the default setting. The GPU will do something similar to an average and can reduce the amount of work JS has to do by several orders of magnitude.
Now instead of 100s or 1000s of pixels you can reduce it down to as little at 4 or 16 depending on the accuracy you need.
An example.
Using these methods you can get a near realtime image in image search with just the basic numerical analysis.
Click to start a test. Results are shown plus the time it took. The image that is being searched for is in the top right.
//------------------------------------------------------------------------
// Some helper functions
var imageTools = (function () {
var tools = {
canvas(width, height) { // create a blank image (canvas)
var c = document.createElement("canvas");
c.width = width;
c.height = height;
return c;
},
createImage : function (width, height) {
var i = this.canvas(width, height);
i.ctx = i.getContext("2d");
return i;
},
image2Canvas(img) {
var i = this.canvas(img.width, img.height);
i.ctx = i.getContext("2d");
i.ctx.drawImage(img, 0, 0);
return i;
},
copyImage(img){ // just a named stub
return this.image2Canvas(img);
},
};
return tools;
})();
const U = undefined;
const doFor = (count, callback) => {var i = 0; while (i < count && callback(i ++) !== true ); };
const setOf = (count, callback) => {var a = [],i = 0; while (i < count) { a.push(callback(i ++)) } return a };
const randI = (min, max = min + (min = 0)) => (Math.random() * (max - min) + min) | 0;
const rand = (min, max = min + (min = 0)) => Math.random() * (max - min) + min;
const randA = (array) => array[(Math.random() * array.length) | 0];
const randG = (min, max = min + (min = 0)) => Math.random() * Math.random() * Math.random() * Math.random() * (max - min) + min;
// end of helper functions
//------------------------------------------------------------------------
function doit(){
document.body.innerHTML = ""; // clear the page;
var canvas = document.createElement("canvas");
document.body.appendChild(canvas);
var ctx = canvas.getContext("2d");
// a grid of 36 images
canvas.width = 6 * 64;
canvas.height = 6 * 64;
console.log("test");
// get a random character to look for
const digit = String.fromCharCode("A".charCodeAt(0) + randI(26));
// get some characters we dont want
const randomDigits = setOf(6,i=>{
return String.fromCharCode("A".charCodeAt(0) + randI(26));
})
randomDigits.push(digit); // add the image we are looking for
var w = canvas.width;
var h = canvas.height;
// create a canvas for the image we are looking for
const imageToFind = imageTools.createImage(64,64);
// and a larger one to cover pixels on the sides
const imageToFindExtend = imageTools.createImage(128,128);
// Draw the character onto the image with a white background and scaled to fit
imageToFindExtend.ctx.fillStyle = imageToFind.ctx.fillStyle = "White";
imageToFind.ctx.fillRect(0,0,64,64);
imageToFindExtend.ctx.fillRect(0,0,128,128);
ctx.font = imageToFind.ctx.font = "64px arial black";
ctx.textAlign = imageToFind.ctx.textAlign = "center";
ctx.textBaseline = imageToFind.ctx.textBaseline = "middle";
const digWidth = imageToFind.ctx.measureText(digit).width+8;
const scale = Math.min(1,64/digWidth);
imageToFind.ctx.fillStyle = "black";
imageToFind.ctx.setTransform(scale,0,0,scale,32,32);
imageToFind.ctx.fillText(digit,0,0);
imageToFind.ctx.setTransform(1,0,0,1,0,0);
imageToFindExtend.ctx.drawImage(imageToFind,32,32);
imageToFind.extendedImage = imageToFindExtend;
// Now fill the canvas with images of other characters
ctx.fillStyle = "white";
ctx.setTransform(1,0,0,1,0,0);
ctx.fillRect(0,0,w,h);
ctx.fillStyle = "black";
ctx.strokeStyle = "white";
ctx.lineJoin = "round";
ctx.lineWidth = 12;
// some characters will be rotated 90,180,-90 deg
const dirs = [
[1,0,0,1,0,0],
[0,1,-1,0,1,0],
[-1,0,0,-1,1,1],
[0,-1,1,0,0,1],
]
// draw random characters at random directions
doFor(h / 64, y => {
doFor(w / 64, x => {
const dir = randA(dirs)
ctx.setTransform(dir[0] * scale,dir[1] * scale,dir[2] * scale,dir[3] * scale,x * 64 + 32, y * 64 + 32);
const d = randA(randomDigits);
ctx.strokeText(d,0,0);
ctx.fillText(d,0,0);
});
});
ctx.setTransform(1,0,0,1,0,0);
// get a copy of the canvas
const saveCan = imageTools.copyImage(ctx.canvas);
// function that finds the images
// image is the image to find
// dir is the matrix direction to find
// smapleSize is the mean sampling size samller numbers are quicker
function checkFor(image,dir,sampleSize){
const can = imageTools.copyImage(saveCan);
const c = can.ctx;
const stepx = 64;
const stepy = 64;
// the image that will contain the reduced means of the differences
const results = imageTools.createImage(Math.ceil(w / stepx) * sampleSize,Math.ceil(h / stepy) * sampleSize);
const e = image.extendedImage;
// for each potencial image location
// set a clip area and draw the source image on it with
// comp mode "difference";
for(var y = 0 ; y < h; y += stepy ){
for(var x = 0 ; x < w; x += stepx ){
c.save();
c.beginPath();
c.rect(x,y,stepx,stepy);
c.clip();
c.globalCompositeOperation = "difference";
c.setTransform(dir[0],dir[1],dir[2],dir[3],x +32 ,y +32 );
c.drawImage(e,-64,-64);
c.restore();
}
}
// Apply the mean (reducing nnumber of pixels to check
results.ctx.drawImage(can,0,0,results.width,results.height);
// get the pixel data
var dat = new Uint32Array(results.ctx.getImageData(0,0,results.width,results.height).data.buffer);
// for each area get the sum of the difference
for(var y = 0; y < results.height; y += sampleSize){
for(var x = 0; x < results.width; x += sampleSize){
var val = 0;
for(var yy = 0; yy < sampleSize && y+yy < results.height; yy += 1){
var i = x + (y+yy)*results.width;
for(var xx = 0; xx < sampleSize && x + xx < results.width ; xx += 1){
val += dat[i++] & 0xFF;
}
}
// if the sum is under the threshold we have found an image
// and we mark it
if(val < sampleSize * sampleSize * 5){
ctx.strokeStyle = "red";
ctx.fillStyle = "rgba(255,0,0,0.5)";
ctx.lineWidth = 2;
ctx.strokeRect(x * (64/sampleSize),y * (64/sampleSize),64,64);
ctx.fillRect(x * (64/sampleSize),y * (64/sampleSize),64,64);
foundCount += 1;
}
}
}
}
var foundCount = 0;
// find the images at different orientations
var now = performance.now();
checkFor(imageToFind,dirs[0],4);
checkFor(imageToFind,dirs[1],6); // rotated images need larger sample size
checkFor(imageToFind,dirs[2],6);
checkFor(imageToFind,dirs[3],6);
var time = performance.now() - now;
var result = document.createElement("div");
result.textContent = "Found "+foundCount +" matching images in "+time.toFixed(3)+"ms. Click to try again.";
document.body.appendChild(result);
// show the image we are looking for
imageToFind.style.left = (64*6 + 16) + "px";
imageToFind.id = "lookingFor";
document.body.appendChild(imageToFind);
}
document.addEventListener("click",doit);
canvas {
border : 2px solid black;
position : absolute;
top : 28px;
left : 2px;
}
#lookingFor {
border : 4px solid red;
}
div {
border : 2px solid black;
position : absolute;
top : 2px;
left : 2px;
}
Click to start test.
Not perfect
The example is not perfect and will sometimes make mistakes. There is a huge amount of room for improving both the accuracy and the speed. This is just something I threw together as an example to show how to use the GPU via the 2D API. Some further maths will be needed to find the statistically good results.
This method can also work for different scales, and rotations, you can even use some of the other comp modes to remove colour and normalize contrast. I have used a very similar approch to stabilize webcam by tracking points from one frame to the next, and a veriaty of other image tracking uses.
I am trying to add text on an image using the <canvas> element. First the image is drawn and on the image the text is drawn. So far so good.
But where I am facing a problem is that if the text is too long, it gets cut off in the start and end by the canvas. I don't plan to resize the canvas, but I was wondering how to wrap the long text into multiple lines so that all of it gets displayed. Can anyone point me at the right direction?
Updated version of #mizar's answer, with one severe and one minor bug fixed.
function getLines(ctx, text, maxWidth) {
var words = text.split(" ");
var lines = [];
var currentLine = words[0];
for (var i = 1; i < words.length; i++) {
var word = words[i];
var width = ctx.measureText(currentLine + " " + word).width;
if (width < maxWidth) {
currentLine += " " + word;
} else {
lines.push(currentLine);
currentLine = word;
}
}
lines.push(currentLine);
return lines;
}
We've been using this code for some time, but today we were trying to figure out why some text wasn't drawing, and we found a bug!
It turns out that if you give a single word (without any spaces) to the getLines() function, it will return an empty array, rather than an array with a single line.
While we were investigating that, we found another (much more subtle) bug, where lines can end up slightly longer than they should be, since the original code didn't account for spaces when measuring the length of a line.
Our updated version, which works for everything we've thrown at it, is above. Let me know if you find any bugs!
A possible method (not completely tested, but as for now it worked perfectly)
/**
* Divide an entire phrase in an array of phrases, all with the max pixel length given.
* The words are initially separated by the space char.
* #param phrase
* #param length
* #return
*/
function getLines(ctx,phrase,maxPxLength,textStyle) {
var wa=phrase.split(" "),
phraseArray=[],
lastPhrase=wa[0],
measure=0,
splitChar=" ";
if (wa.length <= 1) {
return wa
}
ctx.font = textStyle;
for (var i=1;i<wa.length;i++) {
var w=wa[i];
measure=ctx.measureText(lastPhrase+splitChar+w).width;
if (measure<maxPxLength) {
lastPhrase+=(splitChar+w);
} else {
phraseArray.push(lastPhrase);
lastPhrase=w;
}
if (i===wa.length-1) {
phraseArray.push(lastPhrase);
break;
}
}
return phraseArray;
}
Here was my spin on it... I read #mizar's answer and made some alterations to it... and with a little assistance I Was able to get this.
code removed, see fiddle.
Here is example usage. http://jsfiddle.net/9PvMU/1/ - this script can also be seen here and ended up being what I used in the end... this function assumes ctx is available in the parent scope... if not you can always pass it in.
edit
the post was old and had my version of the function that I was still tinkering with. This version seems to have met my needs thus far and I hope it can help anyone else.
edit
It was brought to my attention there was a small bug in this code. It took me some time to get around to fixing it but here it is updated. I have tested it myself and it seems to work as expected now.
function fragmentText(text, maxWidth) {
var words = text.split(' '),
lines = [],
line = "";
if (ctx.measureText(text).width < maxWidth) {
return [text];
}
while (words.length > 0) {
var split = false;
while (ctx.measureText(words[0]).width >= maxWidth) {
var tmp = words[0];
words[0] = tmp.slice(0, -1);
if (!split) {
split = true;
words.splice(1, 0, tmp.slice(-1));
} else {
words[1] = tmp.slice(-1) + words[1];
}
}
if (ctx.measureText(line + words[0]).width < maxWidth) {
line += words.shift() + " ";
} else {
lines.push(line);
line = "";
}
if (words.length === 0) {
lines.push(line);
}
}
return lines;
}
context.measureText(text).width is what you're looking for...
Try this script to wrap the text on a canvas.
<script>
function wrapText(ctx, text, x, y, maxWidth, lineHeight) {
var words = text.split(' ');
var line = '';
for(var n = 0; n < words.length; n++) {
var testLine = line + words[n] + ' ';
var metrics = ctx.measureText(testLine);
var testWidth = metrics.width;
if (testWidth > maxWidth && n > 0) {
ctx.fillText(line, x, y);
line = words[n] + ' ';
y += lineHeight;
}
else {
line = testLine;
}
}
ctx.fillText(line, x, y);
}
var canvas = document.getElementById('Canvas01');
var ctx = canvas.getContext('2d');
var maxWidth = 400;
var lineHeight = 24;
var x = (canvas.width - maxWidth) / 2;
var y = 70;
var text = 'HTML is the language for describing the structure of Web pages. HTML stands for HyperText Markup Language. Web pages consist of markup tags and plain text. HTML is written in the form of HTML elements consisting of tags enclosed in angle brackets (like <html>). HTML tags most commonly come in pairs like <h1> and </h1>, although some tags represent empty elements and so are unpaired, for example <img>..';
ctx.font = '15pt Calibri';
ctx.fillStyle = '#555555';
wrapText(ctx, text, x, y, maxWidth, lineHeight);
</script>
</body>
See demo here http://codetutorial.com/examples-canvas/canvas-examples-text-wrap.
From the script here: http://www.html5canvastutorials.com/tutorials/html5-canvas-wrap-text-tutorial/
I've extended to include paragraph support. Use \n for new line.
function wrapText(context, text, x, y, line_width, line_height)
{
var line = '';
var paragraphs = text.split('\n');
for (var i = 0; i < paragraphs.length; i++)
{
var words = paragraphs[i].split(' ');
for (var n = 0; n < words.length; n++)
{
var testLine = line + words[n] + ' ';
var metrics = context.measureText(testLine);
var testWidth = metrics.width;
if (testWidth > line_width && n > 0)
{
context.fillText(line, x, y);
line = words[n] + ' ';
y += line_height;
}
else
{
line = testLine;
}
}
context.fillText(line, x, y);
y += line_height;
line = '';
}
}
Text can be formatted like so:
var text =
[
"Paragraph 1.",
"\n\n",
"Paragraph 2."
].join("");
Use:
wrapText(context, text, x, y, line_width, line_height);
in place of
context.fillText(text, x, y);
I am posting my own version used here since answers here weren't sufficient for me. The first word needed to be measured in my case, to be able to deny too long words from small canvas areas. And I needed support for 'break+space, 'space+break' or double-break/paragraph-break combos.
wrapLines: function(ctx, text, maxWidth) {
var lines = [],
words = text.replace(/\n\n/g,' ` ').replace(/(\n\s|\s\n)/g,'\r')
.replace(/\s\s/g,' ').replace('`',' ').replace(/(\r|\n)/g,' '+' ').split(' '),
space = ctx.measureText(' ').width,
width = 0,
line = '',
word = '',
len = words.length,
w = 0,
i;
for (i = 0; i < len; i++) {
word = words[i];
w = word ? ctx.measureText(word).width : 0;
if (w) {
width = width + space + w;
}
if (w > maxWidth) {
return [];
} else if (w && width < maxWidth) {
line += (i ? ' ' : '') + word;
} else {
!i || lines.push(line !== '' ? line.trim() : '');
line = word;
width = w;
}
}
if (len !== i || line !== '') {
lines.push(line);
}
return lines;
}
It supports any variants of lines breaks, or paragraph breaks, removes double spaces, as well as leading or trailing paragraph breaks. It returns either an empty array if the text doesn't fit. Or an array of lines ready to draw.
look at https://developer.mozilla.org/en/Drawing_text_using_a_canvas#measureText%28%29
If you can see the selected text, and see its wider than your canvas, you can remove words, until the text is short enough. With the removed words, you can start at the second line and do the same.
Of course, this will not be very efficient, so you can improve it by not removing one word, but multiple words if you see the text is much wider than the canvas width.
I did not research, but maybe their are even javascript libraries that do this for you
I modified it using the code from here http://miteshmaheta.blogspot.sg/2012/07/html5-wrap-text-in-canvas.html
http://jsfiddle.net/wizztjh/kDy2U/41/
This should bring the lines correctly from the textbox:-
function fragmentText(text, maxWidth) {
var lines = text.split("\n");
var fittingLines = [];
for (var i = 0; i < lines.length; i++) {
if (canvasContext.measureText(lines[i]).width <= maxWidth) {
fittingLines.push(lines[i]);
}
else {
var tmp = lines[i];
while (canvasContext.measureText(tmp).width > maxWidth) {
tmp = tmp.slice(0, tmp.length - 1);
}
if (tmp.length >= 1) {
var regex = new RegExp(".{1," + tmp.length + "}", "g");
var thisLineSplitted = lines[i].match(regex);
for (var j = 0; j < thisLineSplitted.length; j++) {
fittingLines.push(thisLineSplitted[j]);
}
}
}
}
return fittingLines;
And then get draw the fetched lines on the canvas :-
var lines = fragmentText(textBoxText, (rect.w - 10)); //rect.w = canvas width, rect.h = canvas height
for (var showLines = 0; showLines < lines.length; showLines++) { // do not show lines that go beyond the height
if ((showLines * resultFont.height) >= (rect.h - 10)) { // of the canvas
break;
}
}
for (var i = 1; i <= showLines; i++) {
canvasContext.fillText(lines[i-1], rect.clientX +5 , rect.clientY + 10 + (i * (resultFont.height))); // resultfont = get the font height using some sort of calculation
}
This is a typescript version of #JBelfort's answer.
(By the way, thanks for this brilliant code)
As he mentioned in his answer this code can simulate html element such as textarea,and also the CSS property
word-break: break-all
I added canvas location parameters (x, y and lineHeight)
function wrapText(
ctx: CanvasRenderingContext2D,
text: string,
maxWidth: number,
x: number,
y: number,
lineHeight: number
) {
const xOffset = x;
let yOffset = y;
const lines = text.split('\n');
const fittingLines: [string, number, number][] = [];
for (let i = 0; i < lines.length; i++) {
if (ctx.measureText(lines[i]).width <= maxWidth) {
fittingLines.push([lines[i], xOffset, yOffset]);
yOffset += lineHeight;
} else {
let tmp = lines[i];
while (ctx.measureText(tmp).width > maxWidth) {
tmp = tmp.slice(0, tmp.length - 1);
}
if (tmp.length >= 1) {
const regex = new RegExp(`.{1,${tmp.length}}`, 'g');
const thisLineSplitted = lines[i].match(regex);
for (let j = 0; j < thisLineSplitted!.length; j++) {
fittingLines.push([thisLineSplitted![j], xOffset, yOffset]);
yOffset += lineHeight;
}
}
}
}
return fittingLines;
}
and you can just use this like
const wrappedText = wrapText(ctx, dialog, 200, 100, 200, 50);
wrappedText.forEach(function (text) {
ctx.fillText(...text);
});
}
UPDATE: Once I got this demo working... holy smokes, it's SLOW, like 12-16 seconds for only a level 2 render (when image is around 1000x2000 pixels). This is not even worth bothering with.
I found this really awesome and hopeful looking code in the top answer here: Resizing an image in an HTML5 canvas
//returns a function that calculates lanczos weight
function lanczosCreate(lobes){
return function(x){
if (x > lobes)
return 0;
x *= Math.PI;
if (Math.abs(x) < 1e-16)
return 1
var xx = x / lobes;
return Math.sin(x) * Math.sin(xx) / x / xx;
}
}
//elem: canvas element, img: image element, sx: scaled width, lobes: kernel radius
function thumbnailer(elem, img, sx, lobes){
this.canvas = elem;
elem.width = img.width;
elem.height = img.height;
elem.style.display = "none";
this.ctx = elem.getContext("2d");
this.ctx.drawImage(img, 0, 0);
this.img = img;
this.src = this.ctx.getImageData(0, 0, img.width, img.height);
this.dest = {
width: sx,
height: Math.round(img.height * sx / img.width),
};
this.dest.data = new Array(this.dest.width * this.dest.height * 3);
this.lanczos = lanczosCreate(lobes);
this.ratio = img.width / sx;
this.rcp_ratio = 2 / this.ratio;
this.range2 = Math.ceil(this.ratio * lobes / 2);
this.cacheLanc = {};
this.center = {};
this.icenter = {};
setTimeout(this.process1, 0, this, 0);
}
thumbnailer.prototype.process1 = function(self, u){
self.center.x = (u + 0.5) * self.ratio;
self.icenter.x = Math.floor(self.center.x);
for (var v = 0; v < self.dest.height; v++) {
self.center.y = (v + 0.5) * self.ratio;
self.icenter.y = Math.floor(self.center.y);
var a, r, g, b;
a = r = g = b = 0;
for (var i = self.icenter.x - self.range2; i <= self.icenter.x + self.range2; i++) {
if (i < 0 || i >= self.src.width)
continue;
var f_x = Math.floor(1000 * Math.abs(i - self.center.x));
if (!self.cacheLanc[f_x])
self.cacheLanc[f_x] = {};
for (var j = self.icenter.y - self.range2; j <= self.icenter.y + self.range2; j++) {
if (j < 0 || j >= self.src.height)
continue;
var f_y = Math.floor(1000 * Math.abs(j - self.center.y));
if (self.cacheLanc[f_x][f_y] == undefined)
self.cacheLanc[f_x][f_y] = self.lanczos(Math.sqrt(Math.pow(f_x * self.rcp_ratio, 2) + Math.pow(f_y * self.rcp_ratio, 2)) / 1000);
weight = self.cacheLanc[f_x][f_y];
if (weight > 0) {
var idx = (j * self.src.width + i) * 4;
a += weight;
r += weight * self.src.data[idx];
g += weight * self.src.data[idx + 1];
b += weight * self.src.data[idx + 2];
}
}
}
var idx = (v * self.dest.width + u) * 3;
self.dest.data[idx] = r / a;
self.dest.data[idx + 1] = g / a;
self.dest.data[idx + 2] = b / a;
}
if (++u < self.dest.width)
setTimeout(self.process1, 0, self, u);
else
setTimeout(self.process2, 0, self);
};
thumbnailer.prototype.process2 = function(self){
self.canvas.width = self.dest.width;
self.canvas.height = self.dest.height;
self.ctx.drawImage(self.img, 0, 0);
self.src = self.ctx.getImageData(0, 0, self.dest.width, self.dest.height);
var idx, idx2;
for (var i = 0; i < self.dest.width; i++) {
for (var j = 0; j < self.dest.height; j++) {
idx = (j * self.dest.width + i) * 3;
idx2 = (j * self.dest.width + i) * 4;
self.src.data[idx2] = self.dest.data[idx];
self.src.data[idx2 + 1] = self.dest.data[idx + 1];
self.src.data[idx2 + 2] = self.dest.data[idx + 2];
}
}
self.ctx.putImageData(self.src, 0, 0);
self.canvas.style.display = "block";
}
...
img.onload = function() {
var canvas = document.createElement("canvas");
new thumbnailer(canvas, img, 188, 3); //this produces lanczos3
//but feel free to raise it up to 8. Your client will appreciate
//that the program makes full use of his machine.
document.body.appendChild(canvas);
}
However, this implementation loads an image and renders it, end of story.
I have been trying to re-implement this code so that it does the filtering every time an existing canvas is scaled (think, zooming in and out of an image or document) without having to load a new image or create a new canvas.
How can I adapt it to work this way? Or is that even possible?
What you want to do is something like a singleton to reuse your canvas object. This will let you save the cost of create a new canvas object each time and you will reuse the same object
function getCanvas(){
var canvas;
if (typeof canvas === "undefined"){ canvas = document.createElement("canvas");}
return canvas;
}
img.onload = function() {
var canvas = getCanvas("canvas");
.... THE REST OF YOUR CODE .......
}
.
However this is not what slows your code, image scaling Algorithms are really heavy algorithms with intensive cpu use "usually make use of gpu acceleration at a really low level", and use advanced techniques like multiple bufferr and so others. here is a interesting tutorial in java.net on how image scaling works, it is in java but you can interpolate to any language.
Javascript is not ready for this techniques, so I recommend you to use the transformations available in the canvas api, as in the tutorial you read the efficient way is using the canvas2Dcontext.
var ctx = canvas.getContext("2d");
ctx.scale(2,2);