md`# gpu.js laser detection v2`
GPU = (await require('gpu.js@2.15.2')).GPU
canvas = document.createElement('canvas');
canvas2 = document.createElement('canvas');
gpu = new GPU({ mode: 'gpu', canvas })
function rgb2hsv(r, g, b) {
let rr = 0, gg = 0, bb = 0,
h = 0, s = 0;
let v = Math.max(r, g);
v = Math.max(v, b);
let minv = Math.min(r, g);
minv = Math.min(minv, b);
let diff = v - minv;
function diffc(c, v, diff) {
return (v - c) / 6 / diff + 1 / 2;
}
if (diff == 0) {
h = s = 0;
} else {
s = diff / v;
rr = diffc(r, v, diff);
gg = diffc(g, v, diff);
bb = diffc(b, v, diff);
if (r === v) {
h = bb - gg;
} else if (g === v) {
h = (1 / 3) + rr - bb;
} else if (b === v) {
h = (2 / 3) + gg - rr;
}
if (h < 0) {
h += 1;
} else if (h > 1) {
h -= 1;
}
}
return [Math.round(h * 360), Math.round(s * 100), Math.round(v * 100)];
}
gpu.addFunction(rgb2hsv, { returnType: 'Array(3)' }); // { returnType: 'Array(3)' }
function imageKernel(width, height) {
let kernel = gpu.createKernel(function(image) {
const pixel = image[this.thread.y][this.thread.x];
const hsv = rgb2hsv(pixel[0], pixel[1], pixel[2])
const h = hsv[0];
const s = hsv[1];
const v = hsv[2];
// if (this.thread.x >= 419 && this.thread.x <= 438 &&
// this.thread.y >= 510 && this.thread.y <= 526)
if (this.thread.x >= 309 && this.thread.x <= 328 && this.thread.y >= 335 && this.thread.y <= 355) {
// this.color(1, 1, 0, 1);
// console.log(pixel[0] * 255, pixel[1] * 255, pixel[2] * 255)
// console.log([pixel[0], pixel[1], pixel[2], pixel[3]]);
// console.log(h, s, v);
}
// hue_min=20, hue_max=160,
// sat_min=100, sat_max=255, val_min=200, val_max=256,
if (
// h >= 20 && h <= 160 &&
s >= 0 && s <= 100 &&
v >= 78 && v <= 100 &&
h >= 318
) {
// this.color(pixel[0], pixel[1], pixel[2], pixel[3]);
this.color(0, 1, 0, 1);
// } else if (this.thread.x >= 309 && this.thread.x <= 328 && this.thread.y >= 335 && this.thread.y <= 355) {
// this.color(1, 1, 0, 1);
return 1;
} else {
this.color(pixel[0], pixel[1], pixel[2], pixel[3]);
return 0;
}
})
// .setGraphical(true)
.setOutput([width, height]);
return kernel;
}
function boxKernel(width, height) {
let kernel = gpu.createKernel(function(image) {
})
.setOutput([width, height]);
return kernel;
}
{
let img = document.createElement('img');
let canvas
img.crossOrigin = ""
img.onload = function() {
// Scale down image
// img.height = parseInt(img.height / 2, 10);
// img.width = parseInt(img.width / 2, 10); // Comment out if returning below
console.log(img.width, img.height)
let kernel = imageKernel(img.width, img.height)
// let kernel2 = boxKernel(img.width, img.height)
console.log('running!')
let start = window.performance.now()
let out = kernel(img)
// console.log(out);
console.log('Size', out.length, out[0].length);
// Out is an array of Float32Arrays that is height x width (height first, i.e. Array is `height` in length)
const dots = [];
let minx = img.width;
let miny = img.height;
let maxx = 0;
let maxy = 0;
for (let y = 0; y <= out.length-1; y++) {
const arr = out[y];
for (let x = 0; x <= arr.length-1; x++) {
if (arr[x] == 1) {
if (x < minx) minx = x;
if (x > maxx) maxx = x;
if (y < miny) miny = y;
if (y > maxy) maxy = y;
}
}
}
// Inverse
miny = img.height - miny;
maxy = img.height - maxy;
console.log([minx, miny], [maxx, maxy]);
let boxSize = Math.max(maxx - minx, maxy - miny);
let stop = window.performance.now()
console.log('Took', stop - start);
canvas2.width = img.width;
canvas2.height = img.height;
const ctx = canvas2.getContext("2d");
ctx.drawImage(img, 0, 0);
console.log(canvas);
ctx.beginPath();
const mid = (a, b) => ((b - a) / 2) + a;
ctx.arc(mid(minx, maxx), mid(miny, maxy), boxSize, 0, 2 * Math.PI);
ctx.strokeStyle = 'yellow';
ctx.stroke();
}
// img.src = 'https://i.imgur.com/qb1ywMq.jpg'
// img.src = 'https://i.imgur.com/eLpI3sN.jpg'
// img.src = 'https://i.imgur.com/q4t1tgb.jpg'
// img.src = 'https://i.imgur.com/QKgG5vT.jpg'
img.src = 'https://i.imgur.com/QOyFPcN.jpg'
// return img
}
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.