I'm trying to decode the dataset from this source: http://yann.lecun.com/exdb/mnist/
There is a description of the "very simple" IDX file type in the bottom, but I cannot figure it out.
What I'm trying to achieve is something like:
var imagesFileBuffer = fs.readFileSync(__dirname + '/train-images-idx3-ubyte');
var labelFileBuffer = fs.readFileSync(__dirname + '/train-labels-idx1-ubyte');
var pixelValues = {};
Do magic
pixelValues are now like:
// {
// "0": [0,0,200,190,79,0... for all 784 pixels ... ],
// "4": [0,0,200,190,79,0... for all 784 pixels ... ],
etc for all image entries in the dataset. I've tried to figure out the structure of the binary files, but failed.
I realized there would be duplicate keys in my structure of the pixelValues object, so I made an array of objects of it instaed. The following code will create the structure I'm after:
var dataFileBuffer = fs.readFileSync(__dirname + '/train-images-idx3-ubyte');
var labelFileBuffer = fs.readFileSync(__dirname + '/train-labels-idx1-ubyte');
var pixelValues = [];
// It would be nice with a checker instead of a hard coded 60000 limit here
for (var image = 0; image <= 59999; image++) {
var pixels = [];
for (var x = 0; x <= 27; x++) {
for (var y = 0; y <= 27; y++) {
pixels.push(dataFileBuffer[(image * 28 * 28) + (x + (y * 28)) + 15]);
}
}
var imageData = {};
imageData[JSON.stringify(labelFileBuffer[image + 8])] = pixels;
pixelValues.push(imageData);
}
The structure of pixelValues is now something like this:
[
{5: [28,0,0,0,0,0,0,0,0,0...]},
{0: [0,0,0,0,0,0,0,0,0,0...]},
...
]
There are 28x28=784 pixel values, all varying from 0 to 255.
To render the pixels, use my for loops like I did above, rendering the first pixel in the upper left corner, then working towards the right.
Just a small improvement:
for (var image = 0; image <= 59999; image++) {
with 60000 there is an "entry" with null's at the very end of your pixelValues.
EDIT:
I got a little obsessed with details because I wanted to convert the MNIST dataset back to real and separate image files. So I have found more mistakes in your code.
it is definitely +16 because you have to skip the 16 Bytes of header data. This little mistake is reflected in your answer where the first pixel value of the first digit (with is a 5) is '28'. Which is actually the value that tells how many columns the image has - not the first pixel of the image.
Your nested for loops has to be turned inside-out to get you the right pixel order - asuming you will "rebuild" your image from the upper left corner down to the lower right corner. With your code the image will be flipped along the axis that goes from the upper left to the lower right corner.
So your code should be:
var dataFileBuffer = fs.readFileSync(__dirname + '/train-images-idx3-ubyte');
var labelFileBuffer = fs.readFileSync(__dirname + '/train-labels-idx1-ubyte');
var pixelValues = [];
// It would be nice with a checker instead of a hard coded 60000 limit here
for (var image = 0; image <= 59999; image++) {
var pixels = [];
for (var y = 0; y <= 27; y++) {
for (var x = 0; x <= 27; x++) {
pixels.push(dataFileBuffer[(image * 28 * 28) + (x + (y * 28)) + 16]);
}
}
var imageData = {};
imageData[JSON.stringify(labelFileBuffer[image + 8])] = pixels;
pixelValues.push(imageData);
}
Those little details wouldn't be an issue if you stay consistent and use those extracted data to -for example- train neural networks, because you will do the same with the testing dataset. But if you want to take that MNIST trained neural network and try to verify it with real life hand written digits, you will get bad results because the real images are not flipped.
Hopefully this helps someone out, I have added the ability to save the images to a png. Please note you will need to have an images directory
var fs = require('fs');
const {createCanvas} = require('canvas');
function readMNIST(start, end)
{
var dataFileBuffer = fs.readFileSync(__dirname + '\\test_images_10k.idx3-ubyte');
var labelFileBuffer = fs.readFileSync(__dirname + '\\test_labels_10k.idx1-ubyte');
var pixelValues = [];
for (var image = start; image < end; image++)
{
var pixels = [];
for (var y = 0; y <= 27; y++)
{
for (var x = 0; x <= 27; x++)
{
pixels.push(dataFileBuffer[(image * 28 * 28) + (x + (y * 28)) + 16]);
}
}
var imageData = {};
imageData["index"] = image;
imageData["label"] = labelFileBuffer[image + 8];
imageData["pixels"] = pixels;
pixelValues.push(imageData);
}
return pixelValues;
}
function saveMNIST(start, end)
{
const canvas = createCanvas(28, 28);
const ctx = canvas.getContext('2d');
var pixelValues = readMNIST(start, end);
pixelValues.forEach(function(image)
{
ctx.clearRect(0, 0, canvas.width, canvas.height);
for (var y = 0; y <= 27; y++)
{
for (var x = 0; x <= 27; x++)
{
var pixel = image.pixels[x + (y * 28)];
var colour = 255 - pixel;
ctx.fillStyle = `rgb(${colour}, ${colour}, ${colour})`;
ctx.fillRect(x, y, 1, 1);
}
}
const buffer = canvas.toBuffer('image/png')
fs.writeFileSync(__dirname + `\\images\\image${image.index}-${image.label}.png`, buffer)
})
}
saveMNIST(0, 5);
Related
I'm trying to create a little simulation with the help of HTML5 and Javascript using a canvas. My problem however is, I can't really think of a way to control the behavior of my pixels, without making every single pixel an object, which leads to an awful slowdown of my simulation.
Heres the code so far:
var pixels = [];
class Pixel{
constructor(color){
this.color=color;
}
}
window.onload=function(){
canv = document.getElementById("canv");
ctx = canv.getContext("2d");
createMap();
setInterval(game,1000/60);
};
function createMap(){
pixels=[];
for(i = 0; i <= 800; i++){
pixels.push(sub_pixels = []);
for(j = 0; j <= 800; j++){
pixels[i].push(new Pixel("green"));
}
}
pixels[400][400].color="red";
}
function game(){
ctx.fillStyle = "white";
ctx.fillRect(0,0,canv.width,canv.height);
for(i = 0; i <= 800; i++){
for(j = 0; j <= 800; j++){
ctx.fillStyle=pixels[i][j].color;
ctx.fillRect(i,j,1,1);
}
}
for(i = 0; i <= 800; i++){
for(j = 0; j <= 800; j++){
if(pixels[i][j].color == "red"){
direction = Math.floor((Math.random() * 4) + 1);
switch(direction){
case 1:
pixels[i][j-1].color= "red";
break;
case 2:
pixels[i+1][j].color= "red";
break;
case 3:
pixels[i][j+1].color= "red";
break;
case 4:
pixels[i-1][j].color= "red";
break;
}
}
}
}
}
function retPos(){
return Math.floor((Math.random() * 800) + 1);
}
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<script language="javascript" type="text/javascript" src="game.js"></script>
</head>
<body>
<canvas width="800px" height="800px" id="canv"></canvas>
</body>
</html>
So my two big questions are, what better way of controlling those pixels is there? And how can I speed up the pixel generation?
Hope you can help me.
Optimizing pixel manipulation
There are many options to speed up your code
Pixels as 32bit ints
The following will slug most machines with too much work.
// I removed fixed 800 and replaced with const size
for(i = 0; i <= size; i++){
for(j = 0; j <= size; j++){
ctx.fillStyle=pixels[i][j].color;
ctx.fillRect(i,j,1,1);
}
}
Don't write each pixel via a rect. Use the pixel data you can get from the canvas API via createImageData and associated functions. It uses typed arrays that are a little quicker than arrays and can have multiple view on the same content.
You can write all the pixels to the canvas in a single call. Not blindingly fast but a zillion times faster than what you are doing.
const size = 800;
const imageData = ctx.createImageData(size,size);
// get a 32 bit view
const data32 = new Uint32Array(imageData.data.buffer);
// To set a single pixel
data32[x+y*size] = 0xFF0000FF; // set pixel to red
// to set all pixels
data32.fill(0xFF00FF00); // set all to green
To get a pixel at a pixel coord
const pixel = data32[x + y * imageData.width];
See Accessing pixel data for more on using the image data.
The pixel data is not displayed until you put it onto the canvas
ctx.putImageData(imageData,0,0);
That will give you a major improvement.
Better data organization.
When performance is critical you sacrifice memory and simplicity to get more CPU cycles doing what you want and less doing a lot of nothing.
You have red pixels randomly expanding into the scene, you read every pixel and check (via a slow string comparison) if it is red. When you find one you add a random red pixel besides it.
Checking the green pixels is a waste and can be avoided. Expanding red pixels that are completely surrounded by other reds is also pointless. They do nothing.
The only pixels you are interested in are the red pixels that are next to green pixels.
Thus you can create a buffer that holds the location of all active red pixels, An active red has at least one green. Each frame you check all the active reds, spawning new ones if they can, and killing them if they are surrounded in red.
We don't need to store the x,y coordinate of each red, just the memory address so we can use a flat array.
const reds = new Uint32Array(size * size); // max size way over kill but you may need it some time.
You dont want to have to search for reds in your reds array so you need to keep track of how many active reds there are. You want all the active reds to be at the bottom of the array. You need to check each active red only once per frame. If a red is dead than all above it must move down one array index. But you only want to move each red only once per frame.
Bubble array
I dont know what this type of array is called its like a separation tank, dead stuff slowly moves up and live stuff moves down. Or unused items bubble up used items settle to the bottom.
I will show it as functional because it will be easier to understand. but is better implemented as one brute force function
// data32 is the pixel data
const size = 800; // width and height
const red = 0xFF0000FF; // value of a red pixel
const green = 0xFF00FF00; // value of a green pixel
const reds = new Uint32Array(size * size); // max size way over kill but you var count = 0; // total active reds
var head = 0; // index of current red we are processing
var tail = 0; // after a red has been process it is move to the tail
var arrayOfSpawnS = [] // for each neighbor that is green you want
// to select randomly to spawn to. You dont want
// to spend time processing so this is a lookup
// that has all the possible neighbor combinations
for(let i = 0; i < 16; i ++){
let j = 0;
const combo = [];
i & 1 && (combo[j++] = 1); // right
i & 2 && (combo[j++] = -1); // left
i & 4 && (combo[j++] = -size); // top
i & 5 && (combo[j++] = size); // bottom
arrayOfSpawnS.push(combo);
}
function addARed(x,y){ // add a new red
const pixelIndex = x + y * size;
if(data32[pixelIndex] === green) { // check if the red can go there
reds[count++] = pixelIndex; // add the red with the pixel index
data32[pixelIndex] = red; // and set the pixel
}
}
function safeAddRed(pixelIndex) { // you know that some reds are safe at the new pos so a little bit faster
reds[count++] = pixelIndex; // add the red with the pixel index
data32[pixelIndex] = red; // and set the pixel
}
// a frame in the life of a red. Returns false if red is dead
function processARed(indexOfRed) {
// get the pixel index
var pixelIndex = reds[indexOfRed];
// check reds neighbors right left top and bottom
// we fill a bit value with each bit on if there is a green
var n = data32[pixelIndex + 1] === green ? 1 : 0;
n += data32[pixelIndex - 1] === green ? 2 : 0;
n += data32[pixelIndex - size] === green ? 4 : 0;
n += data32[pixelIndex + size] === green ? 8 : 0;
if(n === 0){ // no room to spawn so die
return false;
}
// has room to spawn so pick a random
var nCount = arrayOfSpawnS[n].length;
// if only one spawn point then rather than spawn we move
// this red to the new pos.
if(nCount === 1){
reds[indexOfRed] += arrayOfSpawnS[n][0]; // move to next pos
}else{ // there are several spawn points
safeAddRed(pixelIndex + arrayOfSpawnS[n][(Math.random() * nCount)|0]);
}
// reds frame is done so return still alive to spawn another frame
return true;
}
Now to process all the reds.
This is the heart of the bubble array. head is used to index each active red. tail is the index of where to move the current head if no deaths have been encountered tail is equal to head. If however a dead item is encountered the head move up one while the tail remains pointing to the dead item. This moves all the active items to the bottom.
When head === count all active items have been checked. The value of tail now contains the new count which is set after the iteration.
If you were using an object rather than a Integer, instead of moving the active item down you swap the head and tail items. This effectively creates a pool of available objects that can be used when adding new items. This type of array management incurs not GC or Allocation overhead and is hence very quick when compared to stacks and object pools.
function doAllReds(){
head = tail = 0; // start at the bottom
while(head < count){
if(processARed(head)){ // is red not dead
reds[tail++] = reds[head++]; // move red down to the tail
}else{ // red is dead so this creates a gap in the array
// Move the head up but dont move the tail,
// The tail is only for alive reds
head++;
}
}
// All reads done. The tail is now the new count
count = tail;
}
The Demo.
The demo will show you the speed improvement. I used the functional version and there could be some other tweaks.
You can also consider webWorkers to get event more speed. Web worker run on a separate javascript context and provides true concurrent processing.
For the ultimate speed use WebGL. All the logic can be done via a fragment shader on the GPU. This type of task is very well suited to parallel processing for which the GPU is designed.
Will be back later to clean up this answer (got a little too long)
I have also added a boundary to the pixel array as the reds were spawning off the pixel array.
const size = canvas.width;
canvas.height = canvas.width;
const ctx = canvas.getContext("2d");
const red = 0xFF0000FF;
const green = 0xFF00FF00;
const reds = new Uint32Array(size * size);
const wall = 0xFF000000;
var count = 0;
var head = 0;
var tail = 0;
var arrayOfSpawnS = []
for(let i = 0; i < 16; i ++){
let j = 0;
const combo = [];
i & 1 && (combo[j++] = 1); // right
i & 2 && (combo[j++] = -1); // left
i & 4 && (combo[j++] = -size); // top
i & 5 && (combo[j++] = size); // bottom
arrayOfSpawnS.push(combo);
}
const imageData = ctx.createImageData(size,size);
const data32 = new Uint32Array(imageData.data.buffer);
function createWall(){//need to keep the reds walled up so they dont run free
for(let j = 0; j < size; j ++){
data32[j] = wall;
data32[j * size] = wall;
data32[j * size + size - 1] = wall;
data32[size * (size - 1) +j] = wall;
}
}
function addARed(x,y){
const pixelIndex = x + y * size;
if (data32[pixelIndex] === green) {
reds[count++] = pixelIndex;
data32[pixelIndex] = red;
}
}
function processARed(indexOfRed) {
var pixelIndex = reds[indexOfRed];
var n = data32[pixelIndex + 1] === green ? 1 : 0;
n += data32[pixelIndex - 1] === green ? 2 : 0;
n += data32[pixelIndex - size] === green ? 4 : 0;
n += data32[pixelIndex + size] === green ? 8 : 0;
if(n === 0) { return false }
var nCount = arrayOfSpawnS[n].length;
if (nCount === 1) { reds[indexOfRed] += arrayOfSpawnS[n][0] }
else {
pixelIndex += arrayOfSpawnS[n][(Math.random() * nCount)|0]
reds[count++] = pixelIndex;
data32[pixelIndex] = red;
}
return true;
}
function doAllReds(){
head = tail = 0;
while(head < count) {
if(processARed(head)) { reds[tail++] = reds[head++] }
else { head++ }
}
count = tail;
}
function start(){
data32.fill(green);
createWall();
var startRedCount = (Math.random() * 5 + 1) | 0;
for(let i = 0; i < startRedCount; i ++) { addARed((Math.random() * size-2+1) | 0, (Math.random() * size-2+1) | 0) }
ctx.putImageData(imageData,0,0);
setTimeout(doItTillAllDead,1000);
countSameCount = 0;
}
var countSameCount;
var lastCount;
function doItTillAllDead(){
doAllReds();
ctx.putImageData(imageData,0,0);
if(count === 0 || countSameCount === 100){ // all dead
setTimeout(start,1000);
}else{
countSameCount += count === lastCount ? 1 : 0;
lastCount = count; //
requestAnimationFrame(doItTillAllDead);
}
}
start();
<canvas width="800" height="800" id="canvas"></canvas>
The main cause of your slow down is your assumption that you need to loop over every pixel for every operation. You do not do this, as that would be 640,000 iterations for every operation you need to do.
You also shouldn't be doing any manipulation logic within the render loop. The only thing that should be there is drawing code. So this should be moved out to preferably a separate thread (Web Workers). If unable to use those a setTimeout/Interval call.
So first a couple of small changes:
Make Pixel class contain the pixel's coordinates along with the color:
class Pixel{
constructor(color,x,y){
this.color=color;
this.x = x;
this.y = y;
}
}
Keep an array of pixels that will end up creating new red pixels. And another one to keep track of what pixels have been updated so we know which ones need drawn.
var pixels = [];
var infectedPixesl = [];
var updatedPixels = [];
Now the easiest part of the code to change is the render loop. Since the only thing that it needs to do is draw the pixels it will be only a couple lines.
function render(){
var numUpdatedPixels = updatedPixels.length;
for(let i=0; i<numUpdatedPixels; i++){
let pixel = updatedPixels[i];
ctx.fillStyle = pixel.color;
ctx.fillRect(pixel.x,pixel.y,1,1);
}
//clear out the updatedPixels as they should no longer be considered updated.
updatedPixels = [];
//better method than setTimeout/Interval for drawing
requestAnimationFrame(render);
}
From there we can move on to the logic. We will loop over the infectedPixels array, and with each pixel we decide a random direction and get that pixel. If this selected pixel is red we do nothing and continue on. Otherwise we change it's color and add it to a temporary array affectedPixels. After which we test to see if all the pixels around the original pixel are all red, if so we can remove it from the infectedPixels as there is no need to check it again. Then add all the pixels from affectedPixels onto the infectedPixels as these are now new pixels that need to be checked. And the last step is to also add affectedPixels onto updatedPixels so that the render loop draws the changes.
function update(){
var affectedPixels = [];
//needed as we shouldn't change an array while looping over it
var stillInfectedPixels = [];
var numInfected = infectedPixels.length;
for(let i=0; i<numInfected; i++){
let pixel = infectedPixels[i];
let x = pixel.x;
let y = pixel.y;
//instead of using a switch statement, use the random number as the index
//into a surroundingPixels array
let surroundingPixels = [
(pixels[x] ? pixels[x][y - 1] : null),
(pixels[x + 1] ? pixels[x + 1][y] : null),
(pixels[x] ? pixels[x][y + 1] : null),
(pixels[x - 1] ? pixels[x - 1][y] : null)
].filter(p => p);
//filter used above to remove nulls, in the cases of edge pixels
var rand = Math.floor((Math.random() * surroundingPixels.length));
let selectedPixel = surroundingPixels[rand];
if(selectedPixel.color == "green"){
selectedPixel.color = "red";
affectedPixels.push(selectedPixel);
}
if(!surroundingPixels.every(p=>p.color=="red")){
stillInfectedPixels.push(pixel);
}
}
infectedPixels = stillInfectedPixel.concat( affectedPixels );
updatedPixels.push(...affectedPixels);
}
Demo
var pixels = [],
infectedPixels = [],
updatedPixels = [],
canv, ctx;
window.onload = function() {
canv = document.getElementById("canv");
ctx = canv.getContext("2d");
createMap();
render();
setInterval(() => {
update();
}, 16);
};
function createMap() {
for (let y = 0; y < 800; y++) {
pixels.push([]);
for (x = 0; x < 800; x++) {
pixels[y].push(new Pixel("green",x,y));
}
}
pixels[400][400].color = "red";
updatedPixels = [].concat(...pixels);
infectedPixels.push(pixels[400][400]);
}
class Pixel {
constructor(color, x, y) {
this.color = color;
this.x = x;
this.y = y;
}
}
function update() {
var affectedPixels = [];
var stillInfectedPixels = [];
var numInfected = infectedPixels.length;
for (let i = 0; i < numInfected; i++) {
let pixel = infectedPixels[i];
let x = pixel.x;
let y = pixel.y;
let surroundingPixels = [
(pixels[x] ? pixels[x][y - 1] : null),
(pixels[x + 1] ? pixels[x + 1][y] : null),
(pixels[x] ? pixels[x][y + 1] : null),
(pixels[x - 1] ? pixels[x - 1][y] : null)
].filter(p => p);
var rand = Math.floor((Math.random() * surroundingPixels.length));
let selectedPixel = surroundingPixels[rand];
if (selectedPixel.color == "green") {
selectedPixel.color = "red";
affectedPixels.push(selectedPixel);
}
if (!surroundingPixels.every(p => p.color == "red")) {
stillInfectedPixels.push(pixel);
}
}
infectedPixels = stillInfectedPixels.concat(affectedPixels);
updatedPixels.push(...affectedPixels);
}
function render() {
var numUpdatedPixels = updatedPixels.length;
for (let i = 0; i < numUpdatedPixels; i++) {
let pixel = updatedPixels[i];
ctx.fillStyle = pixel.color;
ctx.fillRect(pixel.x, pixel.y, 1, 1);
}
updatedPixels = [];
requestAnimationFrame(render);
}
<canvas id="canv" width="800" height="800"></canvas>
How to count transperent pixels of the area at image canvas, i wrote this function, but i guess there is something like a another method
ctx = getCanvasImg();
for (var x = selection.x2 * zoom; x > selection.x1 * zoom; x--) {
for (var y = selection.y2 * zoom; y > selection.y1 * zoom; y--) {
var pixel = ctx.getImageData(x, y, 1, 1);
var data = pixel.data;
var rgba = 'rgba(' + data[0] + ',' + data[1] + ',' + data[2] + ',' + (data[3] / 255) + ')';
if (data[0] == 0) {
countWhite++;
}
}
}
Just grab the area in need once:
var idata = ctx.getImageData(startX, startY, widthOfArea, heightOfArea);
To count all opaque pixels, you can iterate using a Uint32Array instead:
var data = new Uint32Array(idata.data.buffer);
// little-endian byte order
for(var i = 0, len = data.length, count = 0; i < len;) {
if (data[i++] >>> 24 === 255) count++; // shifts AABBGGRR to 000000AA, then =255?
}
// count = number of opaque pixels
Update: Just to clarify in regards to comments: this do assume little-endian CPU architecture. Most mainstream/consumer devices nowadays uses this CPU architecture and this is usually not a problem. However, if you suspect your code will come across big-endian systems you have to check for this in advance and reverse the byte-order in the check (for anything using typed arrays views wider than 8-bits as they will use the native systems's architecture).
To check for endianess on a system you can do this:
function isLittleEndian() {
return new Uint16Array(new Uint8Array([255,0]).buffer)[0] === 255
}
And if big-endian, check this way instead using a and mask instead of bit-shift:
// big-endian byte order
for(var i = 0, len = data.length, count = 0; i < len;) {
if (data[i++] & 0xff === 255) count++; // masks RRGGBBAA to 000000AA, then =255?
}
You can always use DataViews and specify endianess, however in this case that is of no benefit due to the slight overhead.
This is a bit complicated to describe, so please bear with me.
I'm using the HTML5 canvas to extend a diagramming tool (Diagramo). It implements multiple types of line, straight, jagged (right angle) and curved (cubic or quadratic). These lines can be solid, dotted or dashed.
The new feature I am implementing is a "squiggly" line, where instead of following a constant path, the line zigzags back and forth across the desired target path in smooth arcs.
Below is an example of this that is correct. This works in most cases, however, in certain edge cases it does not.
The implementation is to take the curve, use the quadratic or cubic functions to estimate equidistance points along the line, and draw squiggles along these straight lines by placing control points on either side of the straight line (alternating) and drawing multiple cubic curves.
The issues occur when the line is relatively short, and doubles back on itself close to the origin. An example is below, this happens on longer lines too - the critical point is that there is a very small sharp curve immediately after the origin. In this situation the algorithm picks the first point after the sharp curve, in some cases immediately next to the origin, and considers that the first segment.
Each squiggle has a minimum/maximum pixel length of 8px/14px (which I can change, but much below that and it becomes too sharp, and above becomes too wavy) the code tries to find the right sized squiggle for the line segment to fit with the minimum empty space, which is then filled by a straight line.
I'm hoping there is a solution to this that can account for sharply curved lines, if I know all points along a line can I choose control points that alternate either side of the line, perpendicular too it?
Would one option be to consider a point i and the points i-1 and i+1 and use that to determine the orientation of the line, and thus pick control points?
Code follows below
//fragment is either Cubic or Quadratic curve.
paint(fragment){
var length = fragment.getLength();
var points = Util.equidistancePoints(fragment, length < 100 ? (length < 50 ? 3: 5): 11);
points.splice(0, 1); //remove origin as that is the initial point of the delegate.
//points.splice(0, 1);
delegate.paint(context, points);
}
/**
*
* #param {QuadCurve} or {CubicCurbe} curve
* #param {Number} m the number of points
* #return [Point] a set of equidistance points along the polyline of points
* #author Zack
* #href http://math.stackexchange.com/questions/321293/find-coordinates-of-equidistant-points-in-bezier-curve
*/
equidistancePoints: function(curve, m){
var points = curve.getPoints(0.001);
// Get fractional arclengths along polyline
var n = points.length;
var s = 1.0/(n-1);
var dd = [];
var cc = [];
var QQ = [];
function findIndex(dd, d){
var i = 0;
for (var j = 0 ; j < dd.length ; j++){
if (d > dd[j]) {
i = j;
}
else{
return i;
}
}
return i;
};
dd.push(0);
cc.push(0);
for (var i = 0; i < n; i++){
if(i >0) {
cc.push(Util.distance(points[i], points[i - 1]));
}
}
for (var i = 1 ; i < n ; i++) {
dd.push(dd[i-1] + cc[i]);
}
for (var i = 1 ; i < n ; i++) {
dd[i] = dd[i]/dd[n-1];
}
var step = 1.0/(m-1);
for (var r = 0 ; r < m ; r++){
var d = parseFloat(r)*step;
var i = findIndex(dd, d);
var u = (d - dd[i]) / (dd[i+1] - dd[i]);
var t = (i + u)*s;
QQ[r] = curve.getPoint(t);
}
return QQ;
}
SquigglyLineDelegate.prototype = {
constructor: SquigglyLineDelegate,
paint: function(context, points){
var squiggles = 0;
var STEP = 0.1;
var useStart = false;
var bestSquiggles = -1;
var bestA = 0;
var distance = Util.distance(points[0], this.start);
for(var a = SquigglyLineDelegate.MIN_SQUIGGLE_LENGTH; a < SquigglyLineDelegate.MAX_SQUIGGLE_LENGTH; a += STEP){
squiggles = distance / a;
var diff = Math.abs(Math.floor(squiggles) - squiggles);
if(diff < bestSquiggles || bestSquiggles == -1){
bestA = a;
bestSquiggles = diff;
}
}
squiggles = distance / bestA;
for(var i = 0; i < points.length; i++){
context.beginPath();
var point = points[i];
for(var s = 0; s < squiggles-1; s++){
var start = Util.point_on_segment(this.start, point, s * bestA);
var end = Util.point_on_segment(this.start, point, (s + 1) * bestA);
var mid = Util.point_on_segment(this.start, point, (s + 0.5) * bestA);
end.style.lineWidth = 1;
var line1 = new Line(Util.point_on_segment(mid, end, -this.squiggleWidth), Util.point_on_segment(mid, end, this.squiggleWidth));
var mid1 = Util.getMiddle(line1.startPoint, line1.endPoint);
line1.transform(Matrix.translationMatrix(-mid1.x, -mid1.y));
line1.transform(Matrix.rotationMatrix(radians = 90 * (Math.PI/180)));
line1.transform(Matrix.translationMatrix(mid1.x, mid1.y));
var control1 = useStart ? line1.startPoint : line1.endPoint;
var curve = new QuadCurve(start, control1, end);
curve.style = null;
curve.paint(context);
useStart = !useStart;
}
this.start = point;
context.lineTo(point.x, point.y);
context.stroke();
}
}
}
I have a matrix of values representing an 8-bit grayscale image (values range from 0 to 255). I would like to display this image on the web. How can I do so? The image is coming from a C program, would this require converting the image in the C program?
I ended up using the pngjs library to do the job thanks to stdob's suggestion https://www.npmjs.com/package/pngjs. Heres the code I used:
var fs = require('fs'),
PNG = require('pngjs').PNG;
var png = new PNG({
width: 100,
height: 100,
filterType: -1
});
for (var y = 0; y < png.height; y++) {
for (var x = 0; x < png.width; x++) {
var idx = (png.width * y + x) << 2;
png.data[idx ] = 255;
png.data[idx+1] = 218;
png.data[idx+2] = 185;
png.data[idx+3] = 255;
}
}
png.pack().pipe(fs.createWriteStream('newOut.png'));
I'm into a 2D/3D graphic project and I'm facing a performance problem.
My algorithm takes two images: a picture and the relative grayscale depth map.
I have also an array of 10 canvases ("layers") initally blank. A note: all the images have the same dimension.
I need to check every pixel X;Y of the depth map and, depending on its color value, access one of the 10 canvases and draw the X;Y pixel of the original image on it.
Resulting algorithm is someting like:
for (var y = 0; y < totalHeight; ++y) {
for (var x = 0; x < totalWidth; ++x) {
var index = (y * totalWidth + x) * 4; // index of the current pixel
// parse depth level using luminosity method
var depthLevel = Math.round(
0.21 * depthData[index] +
0.71 * depthData[index + 1] +
0.07 * depthData[index + 2]
);
// get the proper layer to modify
var layerIndex = Math.floor((layersCount / 256) * depthLevel);
var layerContext = layers[layerIndex].getContext("2d");
var layerData = layerContext.getImageData(0, 0, totalWidth, totalHeight);
layerData.data[index] = originalData[index];
layerData.data[index + 1] = originalData[index + 1];
layerData.data[index + 2] = originalData[index + 2];
layerData.data[index + 3] = originalData[index + 3];
layerContext.putImageData(layerData, 0, 0);
}
A loop like that takes around 3 minutes to complete on a 200x200 image! I'm pretty sure that the slowness is caused by the last function, putImageData. Is there a faster way to draw pixels in the way I need? Thank you
Don't set your image data in every iteration of the loop. That's a heavy operation, and you're executing it 40.000 (200*200) times.
This should save you a bit of processing power:
var contexts = [];
var data = [];
// Save your contexts and data to 2 arrays.
for (var i = 0; i < layers.length; i++) {
contexts[i] = layers[i].getContext("2d");
data[i] = contexts[i].getImageData(0, 0, totalWidth, totalHeight);
}
for (var y = 0; y < totalHeight; ++y) {
for (var x = 0; x < totalWidth; ++x) {
var index = (y * totalWidth + x) * 4; // index of the current pixel
// parse depth level using luminosity method
var depthLevel = Math.round(
0.21 * depthData[index]
+ 0.71 * depthData[index + 1]
+ 0.07 * depthData[index + 2]);
// get the proper layer to modify
var layerIndex = Math.floor((layersCount / 256) * depthLevel);
data[layerIndex].data[index] = originalData[index];
data[layerIndex].data[index + 1] = originalData[index + 1];
data[layerIndex].data[index + 2] = originalData[index + 2];
data[layerIndex].data[index + 3] = originalData[index + 3];
}
}
// Apply your new data to the contexts.
for (var i = 0; i < layers.length; i++) {
contexts[i].putImageData(data[i]);
}
I haven't tested it, but this should give you a bit of an idea of how to do it.