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@seangeleno

seangeleno/help-me-down.markdown

Created September 11, 2023 10:27
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help me down
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" alt="">
Raw
script.js
"use strict";
{
////////////////////////////////////////////////////////////////
const canvas = {
init() {
this.elem = document.querySelector("canvas");
const gl = this.elem.getContext("webgl", { alpha: false });
const vertexShader = gl.createShader(gl.VERTEX_SHADER);
const fragmentShader = gl.createShader(gl.FRAGMENT_SHADER);
gl.shaderSource(vertexShader, `
uniform mat4 camProj, camView;
attribute vec3 aPosition, aNormal, aColor;
varying vec3 vColor;
const vec3 lightDir = vec3(0, 0, 1);
void main(void) {
vec3 normal = mat3(camView) * aNormal;
vec4 pos = camView * vec4(aPosition, 1.0);
vColor = aColor * max(dot(normal, normalize(lightDir - pos.xyz)), 0.2);
gl_Position = camProj * pos;
}
`);
gl.shaderSource(fragmentShader, `
precision highp float;
varying vec3 vColor;
void main(void) {
gl_FragColor = vec4(vColor, 1.0);
}
`);
gl.compileShader(vertexShader);
gl.compileShader(fragmentShader);
this.program = gl.createProgram();
gl.attachShader(this.program, vertexShader);
gl.attachShader(this.program, fragmentShader);
gl.linkProgram(this.program);
gl.useProgram(this.program);
return gl;
},
resize() {
this.width = this.elem.width = this.elem.offsetWidth;
this.height = this.elem.height = this.elem.offsetHeight;
camera.proj.perspective(60, this.width / this.height).load();
gl.viewport(0, 0, gl.drawingBufferWidth, gl.drawingBufferHeight);
}
};
////////////////////////////////////////////////////////////////
const Mat4 = class {
constructor(program, uName) {
this.u = gl.getUniformLocation(program, uName);
this.data = new Float32Array([
1, 0, 0, 0,
0, 1, 0, 0,
0, 0, 1, 0,
0, 0, 0, 1
]);
}
identity() {
const d = this.data;
d[0] = 1;
d[1] = 0;
d[2] = 0;
d[3] = 0;
d[4] = 0;
d[5] = 1;
d[6] = 0;
d[7] = 0;
d[8] = 0;
d[9] = 0;
d[10] = 1;
d[11] = 0;
d[12] = 0;
d[13] = 0;
d[14] = 0;
d[15] = 1;
return this;
}
translate(x, y, z) {
const d = this.data;
d[12] = d[0] * x + d[4] * y + d[8] * z + d[12];
d[13] = d[1] * x + d[5] * y + d[9] * z + d[13];
d[14] = d[2] * x + d[6] * y + d[10] * z + d[14];
d[15] = d[3] * x + d[7] * y + d[11] * z + d[15];
return this;
}
rotateX(angle) {
const d = this.data;
const s = Math.sin(angle);
const c = Math.cos(angle);
const a10 = d[4];
const a11 = d[5];
const a12 = d[6];
const a13 = d[7];
const a20 = d[8];
const a21 = d[9];
const a22 = d[10];
const a23 = d[11];
d[4] = a10 * c + a20 * s;
d[5] = a11 * c + a21 * s;
d[6] = a12 * c + a22 * s;
d[7] = a13 * c + a23 * s;
d[8] = a10 * -s + a20 * c;
d[9] = a11 * -s + a21 * c;
d[10] = a12 * -s + a22 * c;
d[11] = a13 * -s + a23 * c;
return this;
}
rotateY(angle) {
const d = this.data;
const s = Math.sin(angle);
const c = Math.cos(angle);
const a00 = d[0];
const a01 = d[1];
const a02 = d[2];
const a03 = d[3];
const a20 = d[8];
const a21 = d[9];
const a22 = d[10];
const a23 = d[11];
d[0] = a00 * c + a20 * -s;
d[1] = a01 * c + a21 * -s;
d[2] = a02 * c + a22 * -s;
d[3] = a03 * c + a23 * -s;
d[8] = a00 * s + a20 * c;
d[9] = a01 * s + a21 * c;
d[10] = a02 * s + a22 * c;
d[11] = a03 * s + a23 * c;
return this;
}
rotateZ(angle) {
const d = this.data;
const s = Math.sin(angle);
const c = Math.cos(angle);
const a00 = d[0];
const a01 = d[1];
const a02 = d[2];
const a03 = d[3];
const a10 = d[4];
const a11 = d[5];
const a12 = d[6];
const a13 = d[7];
d[0] = a00 * c + a10 * s;
d[1] = a01 * c + a11 * s;
d[2] = a02 * c + a12 * s;
d[3] = a03 * c + a13 * s;
d[4] = a00 * -s + a10 * c;
d[5] = a01 * -s + a11 * c;
d[6] = a02 * -s + a12 * c;
d[7] = a03 * -s + a13 * c;
return this;
}
perspective(fov, aspect) {
const d = this.data;
const near = 0.01;
const far = 100;
const top = near * Math.tan(fov * Math.PI / 360);
const right = top * aspect;
const left = -right;
const bottom = -top;
d[0] = 2 * near / (right - left);
d[1] = 0;
d[2] = 0;
d[3] = 0;
d[4] = 0;
d[5] = 2 * near / (top - bottom);
d[6] = 0;
d[7] = 0;
d[8] = (right + left) / (right - left);
d[9] = (top + bottom) / (top - bottom);
d[10] = -(far + near) / (far - near);
d[11] = -1;
d[12] = 0;
d[13] = 0;
d[14] = -(2 * far * near) / (far - near);
d[15] = 0;
return this;
}
load() {
gl.uniformMatrix4fv(this.u, gl.FALSE, this.data);
return this;
}
};
////////////////////////////////////////////////////////////////
const gl = canvas.init();
gl.enable(gl.DEPTH_TEST);
gl.enable(gl.CULL_FACE);
const camera = {
proj: new Mat4(canvas.program, "camProj").load(),
view: new Mat4(canvas.program, "camView").load()
};
canvas.resize();
window.addEventListener("resize", () => canvas.resize(), false);
////////////////////////////////////////////////////////////////
const decode = () => {
const img = document.getElementById("heightmap");
const width = img.width;
const height = img.height;
const cmap = document.createElement("canvas");
cmap.width = width;
cmap.height = height;
const cty = cmap.getContext("2d");
cty.drawImage(img, 0, 0);
const hmap = cty.getImageData(0, 0, width, height).data;
// brillance
for (let i = 0; i < width * height * 4; i += 4) {
hmap[i + 3] = 0.34 * hmap[i] + 0.5 * hmap[i + 1] + 0.16 * hmap[i + 2];
}
let vertices = new Float32Array(6000000);
let iV = 0;
const cube = (x, z, l, h, w, r, g, b) => [
x,h,z,0,1,0,r,g,b,x,h,z+w,0,1,0,r,g,b,x+l,h,z+w,0,1,0,r,g,b,x,h,z,0,1,0,r,g,b,x+l,h,z+w,0,1,0,r,g,b,x+l,h,z,0,1,0,r,g,b,
x,0,z,-1,0,0,r,g,b,x,0,z+w,-1,0,0,r,g,b,x,h,z+w,-1,0,0,r,g,b,x,0,z,-1,0,0,r,g,b,x,h,z+w,-1,0,0,r,g,b,x,h,z,-1,0,0,r,g,b,
x+l,0,z,1,0,0,r,g,b,x+l,h,z,1,0,0,r,g,b,x+l,h,z+w,1,0,0,r,g,b,x+l,0,z,1,0,0,r,g,b,x+l,h,z+w,1,0,0,r,g,b,x+l,0,z+w,1,0,0,r,g,b,
x,0,z,0,0,-1,r,g,b,x,h,z,0,0,-1,r,g,b,x+l,h,z,0,0,-1,r,g,b,x,0,z,0,0,-1,r,g,b,x+l,h,z,0,0,-1,r,g,b,x+l,0,z,0,0,-1,r,g,b,
x,0,z+w,0,0,1,r,g,b,x+l,0,z+w,0,0,1,r,g,b,x+l,h,z+w,0,0,1,r,g,b,x,0,z+w,0,0,1,r,g,b,x+l,h,z+w,0,0,1,r,g,b,x,h,z+w,0,0,1,r,g,b
];
const attribute = (program, name, data, size, stride, offset) => {
if (data !== null) {
const buffer = gl.createBuffer();
gl.bindBuffer(gl.ARRAY_BUFFER, buffer);
gl.bufferData(gl.ARRAY_BUFFER, data, gl.STATIC_DRAW);
}
const index = gl.getAttribLocation(program, name);
gl.enableVertexAttribArray(index);
gl.vertexAttribPointer(index, size, gl.FLOAT, false, stride, offset);
};
const increaseArray = (oldArray) => {
const newArray = new Float32Array(oldArray.length * 1.25);
newArray.set(oldArray);
return newArray;
};
const concat = (a1, a2, index) => {
if (index + a2.length > vertices.length) vertices = increaseArray(vertices);
for (let i = 0, l = a2.length; i < l; i++) {
a1[index++] = a2[i];
}
return index;
};
const Rect = class {
constructor(x0, y0, w0, h0) {
this.x = x0;
this.y = y0;
this.w = w0;
this.h = h0;
x0 = Math.floor(x0);
y0 = Math.floor(y0);
w0 = Math.ceil(w0);
h0 = Math.ceil(h0);
const n = w0 * h0;
let r = 0, g = 0, b = 0, l = 0;
for (let x = x0; x < x0 + w0; x++) {
for (let y = y0; y < y0 + h0; y++) {
const p = (y * width + x) * 4;
r += hmap[p + 0];
g += hmap[p + 1];
b += hmap[p + 2];
l += hmap[p + 3];
}
}
// average colors
this.r = (r / n)|0;
this.g = (g / n)|0;
this.b = (b / n)|0;
this.l = (l / n)|0;
// standard deviation
let sd = 0;
for (let x = x0; x < x0 + w0; x++) {
for (let y = y0; y < y0 + h0; y++) {
const l = hmap[(y * width + x) * 4 + 3] - this.l;
sd += (l * l);
}
}
this.sd = Math.sqrt(sd / n);
}
draw() {
if (this.l > 1) iV = concat(vertices, cube(
(this.x - width * 0.5) * 0.1,
(this.y - height * 0.5) * 0.1,
this.w * 0.1,
this.l * 0.02,
this.h * 0.1,
this.r / 256,
this.g / 256,
this.b / 256
), iV);
}
};
const rect = new Rect(0, 0, width, height);
const divide = (rect) => {
if (rect.w > 1 || rect.h > 1) {
if (rect.sd > 8) {
const hw = rect.w * 0.5;
const hh = rect.h * 0.5;
divide(new Rect(rect.x, rect.y, hw, hh));
divide(new Rect(rect.x + hw, rect.y, hw, hh));
divide(new Rect(rect.x, rect.y + hh, hw, hh));
divide(new Rect(rect.x + hw, rect.y + hh, hw, hh));
} else {
rect.draw();
}
} else {
rect.draw();
}
}
divide(rect);
attribute(canvas.program, "aPosition", vertices, 3, 36, 0);
attribute(canvas.program, "aNormal", null, 3, 36, 12);
attribute(canvas.program, "aColor", null, 3, 36, 24);
return iV / 9;
}
const pointer = {
init(canvas) {
this.x = canvas.width * 0.5;
this.y = canvas.height * 0.5;
this.ex = this.x;
this.ey = this.y * 2;
["mousemove", "touchstart", "touchmove"].forEach((event, touch) => {
canvas.elem.addEventListener(
event,
e => {
if (touch) {
e.preventDefault();
this.x = e.targetTouches[0].clientX;
this.y = e.targetTouches[0].clientY;
} else {
this.x = e.clientX;
this.y = e.clientY;
}
},
false
);
});
},
ease(step) {
this.ex += (this.x - this.ex) * step;
this.ey += (this.y - this.ey) * step;
}
};
pointer.init(canvas);
////////////////////////////////////////////////////////////////
const run = () => {
requestAnimationFrame(run);
pointer.ease(0.02);
const rx = (pointer.ex - canvas.width * 0.5) / (canvas.width * 0.35);
const ry = (-pointer.ey + canvas.height * 0.5) / (canvas.height * 0.35);
camera.view
.identity()
.translate(0, ry * 4, -50 + Math.sqrt(rx * rx + ry * ry) * 30)
.rotateX(Math.PI/2)
.rotateZ(rx)
.rotateX(ry)
.load();
gl.drawArrays(gl.TRIANGLES, 0, numElements);
};
let numElements = 0;
const start = () => {
numElements = decode();
run();
};
requestAnimationFrame(start);
}
Raw
style.css
body, html {
touch-action: none;
content-zooming: none;
position: absolute;
margin: 0;
padding: 0;
width: 100%;
height: 100%;
overflow: hidden;
}
canvas {
position: absolute;
display: block;
width: 100%;
height: 100%;
background:#000;
cursor: crosshair;
}
img {visibility: hidden;}
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