<!DOCTYPE html>
<meta name="viewport" content="width=device-width, initial-scale=1.0"> body {
font-family: Arial, sans-serif;
background-color: #f0f0f0;
display: flex;
flex-direction: column;
align-items: center;
padding: 20px;
text-align: center;
}
h1 {
color: #333;
margin: auto;
margin-bottom: 0;
}
h2 {
color: #333;
margin: auto;
margin-top: 0;
}
img:not(#example, .exampleheads, .preview) {
width: 30vw;
height: 30vw;
max-width: 300px;
max-height: 300px;
}
.example-container {
margin: auto;
display: flex;
justify-content: space-around;
width: 100%;
max-width: 600px;
}
#example {
display: inline-block;
height: 40vw;
max-height: 200px;
}
.exampleheads {
display: inline-block;
height: 100px;
margin-top: 50px;
width: 20vw;
height: 20vw;
max-width: 100px;
max-height: 100px;
}
legend {
background: white;
color: #333;
font-weight: bold;
border-radius: 3px;
border: 1px solid #aaa;
padding: 1px 3px;
}
.input-container {
background: white;
padding: 15px;
border-radius: 8px;
box-shadow: 0 2px 10px rgba(0,0,0,0.1);
margin-bottom: 20px;
width: calc(100% - 40px);
max-width: 680px;
display: flex;
flex-wrap: wrap;
justify-content: space-between;
align-items: center;
}
input[type="text"] {
padding: 10px;
border: 1px solid #ccc;
border-radius: 5px;
flex-grow: 1;
margin-right: 10px;
width: 30%;
}
.upload_label {
background-color: #007BFF;
color: white;
padding: 10px;
border-radius: 5px;
cursor: pointer;
transition: background-color 0.3s ease;
}
.upload_label:hover {
background-color: #0056b3;
}
input[type="file"] {
display: none;
}
.checkbox-group {
display: flex;
align-items: center;
gap: 10px;
margin-left: 10px;
}
.checkbox-group label {
background: none;
color: #333;
padding: 0;
}
.checkbox-group input[type="checkbox"] {
accent-color: #007BFF;
}
canvas {
display: none;
}
.images-container {
margin: auto;
display: flex;
justify-content: space-around;
width: 100%;
max-width: 1000px;
}
.images-container img {
border: 1px solid #333;
image-rendering: pixelated;
}
#result-preview {
margin: auto;
margin-top: 50px;
}
@media screen and (max-width: 750px) {
body {
padding: 0;
}
.break {
flex-basis: 100%;
height: 0;
}
.checkbox-group {
margin-left: 0;
margin-top: 10px;
}
input[type="text"] {
width: 20vw;
}
}
<h1>Mini-Skin Generator
</h1> <p id="credits">by
<a href="https://leroch.net">Christian
</a> (
<a href="https://73.nu/donation">Donate
</a>❤️) |
<a href="https://pb.73.nu/miniskin">Sourcecode
</a> |
<a href="https://pb.73.nu/miniskin-info/fullscreen">Info
</a> |
<a href="https://github.com/nirastich/miniskin">GitHub
</a></p> <div class="example-container"> <img class="exampleheads" src="data:image/png;base64,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"> 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"> <input type="text" id="username1" placeholder="Username"> <label class="upload_label" for="upload1">Upload
File
</label> <input type="file" id="upload1" accept="image/png"> <div class="checkbox-group"> <label><input type="checkbox" id="skin1_jacket"><abbr title="Second skin layer for body and pants ignoring head">Show Jacket
</abbr></label> <label><input type="checkbox" id="fix_eyes"><abbr title="Check this box if eyes are not showing correctly">Fix Eyes
</abbr></label> <input type="text" id="username2" placeholder="Username"> <label class="upload_label" for="upload2">Upload
File
</label> <input type="file" id="upload2" accept="image/png"> <div class="checkbox-group"> <div class="images-container"> <img id="img1" width="128" height="128"> <img id="img2" width="128" height="128"> <img id="combinedImg" width="128" height="128"> <div id="result-preview" style="display: none;"> <img class="preview" id="full-body-preview" src="" alt="Full body preview"> <img class="preview" id="head-preview" src="" alt="head preview"> <p>Search
& Preview powered by <a href="https://vzge.me">vzge.me</a> API</p> <script>
function getUsersFromUrl() {
const params = new URLSearchParams(window.location.search);
const headskin = params.get('head') || '';
const carrierskin = params.get('carrier') || '';
const skin1_64x32 = params.get('s1x32') == 'true';
const skin1_jacket = params.get('jacket') == 'true';
const skin2_64x32 = params.get('s2x32') == 'true';
const skin2_slim = params.get('slim') == 'true';
const fix_eyes = params.get('eyes') == 'true';
let img1Loaded = false;
let img2Loaded = false;
// Set tickbox states based on URL parameters
document.getElementById('skin1_64x32').checked = skin1_64x32;
document.getElementById('skin1_jacket').checked = skin1_jacket;
document.getElementById('skin2_64x32').checked = skin2_64x32;
document.getElementById('skin2_slim').checked = skin2_slim;
document.getElementById('fix_eyes').checked = fix_eyes;
if (headskin) {
username1.value = headskin;
handleInput(username1, function(img) {
img1Element.src = img.src;
img1Data = getImageData(img);
img1Loaded = true;
if (img1Loaded && img2Loaded) combineSkins();
});
}
if (carrierskin) {
username2.value = carrierskin;
handleInput(username2, function(img) {
img2Element.src = img.src;
img2Data = getImageData(img);
img2Loaded = true;
if (img1Loaded && img2Loaded) combineSkins();
});
}
return {
headskin,
carrierskin,
skin1_64x32,
skin1_jacket,
skin2_64x32,
skin2_slim,
fix_eyes
};
}
function setNamesInUrl(headskin, carrierskin) {
const params = new URLSearchParams();
const skin1_64x32 = document.getElementById('skin1_64x32').checked;
const skin1_jacket = document.getElementById('skin1_jacket').checked;
const skin2_64x32 = document.getElementById('skin2_64x32').checked;
const skin2_slim = document.getElementById('skin2_slim').checked;
const fix_eyes = document.getElementById('fix_eyes').checked;
params.set('head', headskin);
params.set('carrier', carrierskin);
params.set('s1x32', skin1_64x32);
params.set('jacket', skin1_jacket);
params.set('s2x32', skin2_64x32);
params.set('slim', skin2_slim);
params.set('eyes', fix_eyes);
window.history.replaceState({}, '', `${window.location.pathname}?${params}`);
}
const upload1 = document.getElementById('upload1');
const upload2 = document.getElementById('upload2');
const username1 = document.getElementById('username1');
const username2 = document.getElementById('username2');
const canvas = document.getElementById('canvas');
const ctx = canvas.getContext('2d');
const img1Element = document.getElementById('img1');
const img2Element = document.getElementById('img2');
const combinedImgElement = document.getElementById('combinedImg');
const downloadBtn = document.getElementById('downloadBtn');
let img1Data = null;
let img2Data = null;
function loadImage(fileOrUrl, callback) {
const img = new Image();
img.crossOrigin = "Anonymous";
img.onload = function() {
callback(img);
}
if (fileOrUrl instanceof File) {
const reader = new FileReader();
reader.onload = function(event) {
img.src = event.target.result;
}
reader.readAsDataURL(fileOrUrl);
} else {
img.src = fileOrUrl;
}
}
function getImageData(img) {
const tempCanvas = document.createElement('canvas');
const tempCtx = tempCanvas.getContext('2d');
tempCanvas.width = 64;
tempCanvas.height = 64;
tempCtx.clearRect(0, 0, 64, 64);
tempCtx.drawImage(img, 0, 0, img.width, img.height);
return tempCtx.getImageData(0, 0, 64, 64);
}
function copyArea(srcData, srcX, srcY, width, height, destX, destY, destData, rotate = false) {
for (let y = 0; y < height; y++) {
for (let x = 0; x < width; x++) {
const srcIndex = ((srcY + y) * 64 + (srcX + x)) * 4;
let destIndex;
if (rotate) {
const rotatedX = width - 1 - x;
const rotatedY = height - 1 - y;
destIndex = ((destY + rotatedY) * 64 + (destX + rotatedX)) * 4;
} else {
destIndex = ((destY + y) * 64 + (destX + x)) * 4;
}
for (let i = 0; i < 4; i++) {
destData[destIndex + i] = srcData[srcIndex + i];
}
}
}
}
function setPixel(destData, x, y, color) {
const index = ((y * 64) + x) * 4;
destData[index + 0] = color[0]; // Red
destData[index + 1] = color[1]; // Green
destData[index + 2] = color[2]; // Blue
destData[index + 3] = color[3]; // Alpha
}
function combineSkins() {
const skin1_64x32 = document.getElementById('skin1_64x32').checked;
const skin1_jacket = document.getElementById('skin1_jacket').checked;
const skin2_64x32 = document.getElementById('skin2_64x32').checked;
const skin2_slim = document.getElementById('skin2_slim').checked;
const fix_eyes = document.getElementById('fix_eyes').checked;
const headskin = document.getElementById('username1').value;
const carrierskin = document.getElementById('username2').value;
if (headskin !== "" && carrierskin !== "") {
setNamesInUrl(headskin,carrierskin);
}
const combinedData = ctx.createImageData(64, 64);
const data = combinedData.data;
// watermark 73.nu/MS
// 7
setPixel(data, 62, 46, [0, 0, 0, 255]);
setPixel(data, 61, 46, [0, 0, 0, 255]);
setPixel(data, 60, 46, [0, 0, 0, 255]);
setPixel(data, 59, 45, [0, 0, 0, 255]);
setPixel(data, 58, 45, [0, 0, 0, 255]);
setPixel(data, 58, 46, [0, 0, 0, 255]);
setPixel(data, 58, 47, [0, 0, 0, 255]);
// 3
setPixel(data, 62, 43, [0, 0, 0, 255]);
setPixel(data, 62, 42, [0, 0, 0, 255]);
setPixel(data, 61, 41, [0, 0, 0, 255]);
setPixel(data, 60, 42, [0, 0, 0, 255]);
setPixel(data, 59, 41, [0, 0, 0, 255]);
setPixel(data, 58, 42, [0, 0, 0, 255]);
setPixel(data, 58, 43, [0, 0, 0, 255]);
// .
setPixel(data, 62, 39, [90, 90, 90, 255]);
// n
setPixel(data, 62, 37, [0, 0, 0, 255]);
setPixel(data, 61, 37, [0, 0, 0, 255]);
setPixel(data, 60, 37, [0, 0, 0, 255]);
setPixel(data, 60, 36, [0, 0, 0, 255]);
setPixel(data, 61, 35, [0, 0, 0, 255]);
setPixel(data, 62, 35, [0, 0, 0, 255]);
// u
setPixel(data, 60, 31, [0, 0, 0, 255]);
setPixel(data, 61, 33, [0, 0, 0, 255]);
setPixel(data, 60, 33, [0, 0, 0, 255]);
setPixel(data, 62, 32, [0, 0, 0, 255]);
setPixel(data, 61, 31, [0, 0, 0, 255]);
setPixel(data, 62, 31, [0, 0, 0, 255]);
// /
setPixel(data, 62, 29, [90, 90, 90, 255]);
setPixel(data, 61, 29, [90, 90, 90, 255]);
setPixel(data, 60, 28, [90, 90, 90, 255]);
setPixel(data, 59, 28, [90, 90, 90, 255]);
setPixel(data, 58, 27, [90, 90, 90, 255]);
setPixel(data, 57, 27, [90, 90, 90, 255]);
// M
setPixel(data, 62, 25, [0, 0, 0, 255]);
setPixel(data, 61, 25, [0, 0, 0, 255]);
setPixel(data, 60, 25, [0, 0, 0, 255]);
setPixel(data, 59, 25, [0, 0, 0, 255]);
setPixel(data, 58, 25, [0, 0, 0, 255]);
setPixel(data, 59, 24, [0, 0, 0, 255]);
setPixel(data, 60, 23, [0, 0, 0, 255]);
setPixel(data, 59, 22, [0, 0, 0, 255]);
setPixel(data, 62, 21, [0, 0, 0, 255]);
setPixel(data, 61, 21, [0, 0, 0, 255]);
setPixel(data, 60, 21, [0, 0, 0, 255]);
setPixel(data, 59, 21, [0, 0, 0, 255]);
setPixel(data, 58, 21, [0, 0, 0, 255]);
// S
setPixel(data, 62, 19, [0, 0, 0, 255]);
setPixel(data, 62, 18, [0, 0, 0, 255]);
setPixel(data, 62, 17, [0, 0, 0, 255]);
setPixel(data, 61, 16, [0, 0, 0, 255]);
setPixel(data, 60, 17, [0, 0, 0, 255]);
setPixel(data, 60, 18, [0, 0, 0, 255]);
setPixel(data, 59, 19, [0, 0, 0, 255]);
setPixel(data, 58, 18, [0, 0, 0, 255]);
setPixel(data, 58, 17, [0, 0, 0, 255]);
setPixel(data, 58, 16, [0, 0, 0, 255]);
// base
//copyArea(img1Data.data, 0, 0, 64, 64, 0, 0, data);
// head top
copyArea(img1Data.data, 8, 0, 8, 8, 8, 0, data);
// head underside
copyArea(img1Data.data, 4, 16, 4, 4, 16, 0, data);
copyArea(img1Data.data, 4, 16, 4, 4, 20, 4, data);
if (skin1_64x32) {
copyArea(img1Data.data, 4, 16, 4, 4, 20, 0, data);
copyArea(img1Data.data, 4, 16, 4, 4, 16, 4, data);
} else {
copyArea(img1Data.data, 20, 48, 4, 4, 20, 0, data);
copyArea(img1Data.data, 20, 48, 4, 4, 16, 4, data);
}
// head front
copyArea(img1Data.data, 8, 9, 8, 2, 8, 8, data);
if (fix_eyes) {
copyArea(img1Data.data, 8, 11, 8, 4, 8, 10, data);
} else {
copyArea(img1Data.data, 8, 12, 8, 4, 8, 10, data);
}
copyArea(img1Data.data, 4, 20, 4, 1, 12, 15, data);
copyArea(img1Data.data, 20, 21, 3, 1, 8, 13, data);
copyArea(img1Data.data, 25, 21, 3, 1, 13, 13, data);
copyArea(img1Data.data, 20, 22, 8, 1, 8, 14, data);
copyArea(img1Data.data, 4, 20, 4, 1, 8, 15, data);
if (skin1_64x32) {
copyArea(img1Data.data, 4, 20, 4, 1, 12, 15, data);
} else {
copyArea(img1Data.data, 20, 52, 4, 1, 12, 15, data);
}
// head back
copyArea(img1Data.data, 24, 9, 8, 2, 24, 8, data);
copyArea(img1Data.data, 24, 12, 8, 4, 24, 10, data);
copyArea(img1Data.data, 32, 21, 8, 1, 24, 13, data);
copyArea(img1Data.data, 32, 22, 8, 1, 24, 14, data);
copyArea(img1Data.data, 12, 20, 4, 1, 24, 15, data);
if (skin1_64x32) {
copyArea(img1Data.data, 12, 20, 4, 1, 28, 15, data);
} else {
copyArea(img1Data.data, 28, 52, 4, 1, 28, 15, data);
}
// head left
copyArea(img1Data.data, 0, 9, 8, 2, 0, 8, data);
copyArea(img1Data.data, 0, 12, 8, 4, 0, 10, data);
copyArea(img1Data.data, 16, 21, 1, 2, 0, 13, data);
copyArea(img1Data.data, 16, 21, 1, 2, 1, 13, data);
copyArea(img1Data.data, 17, 21, 1, 2, 2, 13, data);
copyArea(img1Data.data, 17, 21, 1, 2, 3, 13, data);
copyArea(img1Data.data, 18, 21, 1, 2, 4, 13, data);
copyArea(img1Data.data, 18, 21, 1, 2, 5, 13, data);
copyArea(img1Data.data, 19, 21, 1, 2, 6, 13, data);
copyArea(img1Data.data, 19, 21, 1, 2, 7, 13, data);
copyArea(img1Data.data, 0, 20, 4, 1, 0, 15, data);
copyArea(img1Data.data, 12, 20, 4, 1, 4, 15, data);
// head right
copyArea(img1Data.data, 16, 9, 8, 2, 16, 8, data);
copyArea(img1Data.data, 16, 12, 8, 4, 16, 10, data);
copyArea(img1Data.data, 28, 21, 1, 2, 16, 13, data);
copyArea(img1Data.data, 28, 21, 1, 2, 17, 13, data);
copyArea(img1Data.data, 29, 21, 1, 2, 18, 13, data);
copyArea(img1Data.data, 29, 21, 1, 2, 19, 13, data);
copyArea(img1Data.data, 30, 21, 1, 2, 20, 13, data);
copyArea(img1Data.data, 30, 21, 1, 2, 21, 13, data);
copyArea(img1Data.data, 31, 21, 1, 2, 22, 13, data);
copyArea(img1Data.data, 31, 21, 1, 2, 23, 13, data);
copyArea(img1Data.data, 0, 20, 4, 1, 16, 15, data);
copyArea(img1Data.data, 12, 20, 4, 1, 20, 15, data);
// 2nd layer head top
copyArea(img1Data.data, 40, 0, 8, 8, 40, 0, data);
// 2nd layer head front
copyArea(img1Data.data, 40, 9, 8, 2, 40, 8, data);
if (fix_eyes) {
copyArea(img1Data.data, 40, 11, 8, 4, 40, 10, data);
} else {
copyArea(img1Data.data, 40, 12, 8, 4, 40, 10, data);
}
if (skin1_jacket) {
copyArea(img1Data.data, 20, 37, 3, 1, 40, 13, data);
copyArea(img1Data.data, 25, 37, 3, 1, 45, 13, data);
copyArea(img1Data.data, 20, 38, 8, 1, 40, 14, data);
copyArea(img1Data.data, 4, 36, 4, 1, 40, 15, data);
copyArea(img1Data.data, 4, 52, 4, 1, 44, 15, data);
}
// 2nd layer head back
copyArea(img1Data.data, 56, 9, 8, 2, 56, 8, data);
copyArea(img1Data.data, 56, 12, 8, 4, 56, 10, data);
if (skin1_jacket) {
copyArea(img1Data.data, 32, 36, 8, 1, 56, 13, data);
copyArea(img1Data.data, 32, 37, 8, 1, 56, 14, data);
copyArea(img1Data.data, 12, 36, 4, 1, 56, 15, data);
copyArea(img1Data.data, 12, 52, 4, 1, 60, 15, data);
}
// 2nd layer head left
copyArea(img1Data.data, 32, 9, 8, 2, 32, 8, data);
copyArea(img1Data.data, 32, 12, 8, 4, 32, 10, data);
if (skin1_jacket) {
copyArea(img1Data.data, 16, 37, 1, 2, 32, 13, data);
copyArea(img1Data.data, 16, 37, 1, 2, 33, 13, data);
copyArea(img1Data.data, 17, 37, 1, 2, 34, 13, data);
copyArea(img1Data.data, 17, 37, 1, 2, 35, 13, data);
copyArea(img1Data.data, 18, 37, 1, 2, 36, 13, data);
copyArea(img1Data.data, 18, 37, 1, 2, 37, 13, data);
copyArea(img1Data.data, 19, 37, 1, 2, 38, 13, data);
copyArea(img1Data.data, 19, 37, 1, 2, 39, 13, data);
copyArea(img1Data.data, 0, 37, 1, 1, 32, 15, data);
copyArea(img1Data.data, 0, 37, 1, 1, 33, 15, data);
copyArea(img1Data.data, 1, 37, 1, 1, 34, 15, data);
copyArea(img1Data.data, 1, 37, 1, 1, 35, 15, data);
copyArea(img1Data.data, 2, 37, 1, 1, 36, 15, data);
copyArea(img1Data.data, 2, 37, 1, 1, 37, 15, data);
copyArea(img1Data.data, 3, 37, 1, 1, 38, 15, data);
copyArea(img1Data.data, 3, 37, 1, 1, 39, 15, data);
}
// 2nd layer head right
copyArea(img1Data.data, 48, 9, 8, 2, 48, 8, data);
copyArea(img1Data.data, 48, 12, 8, 4, 48, 10, data);
if (skin1_jacket) {
copyArea(img1Data.data, 28, 37, 1, 2, 48, 13, data);
copyArea(img1Data.data, 28, 37, 1, 2, 49, 13, data);
copyArea(img1Data.data, 29, 37, 1, 2, 50, 13, data);
copyArea(img1Data.data, 29, 37, 1, 2, 51, 13, data);
copyArea(img1Data.data, 30, 37, 1, 2, 52, 13, data);
copyArea(img1Data.data, 30, 37, 1, 2, 53, 13, data);
copyArea(img1Data.data, 31, 37, 1, 2, 54, 13, data);
copyArea(img1Data.data, 31, 37, 1, 2, 55, 13, data);
copyArea(img1Data.data, 8, 37, 1, 1, 48, 15, data);
copyArea(img1Data.data, 8, 37, 1, 1, 49, 15, data);
copyArea(img1Data.data, 9, 37, 1, 1, 50, 15, data);
copyArea(img1Data.data, 9, 37, 1, 1, 51, 15, data);
copyArea(img1Data.data, 10, 37, 1, 1, 52, 15, data);
copyArea(img1Data.data, 10, 37, 1, 1, 53, 15, data);
copyArea(img1Data.data, 11, 37, 1, 1, 54, 15, data);
copyArea(img1Data.data, 11, 37, 1, 1, 55, 15, data);
}
// arms
copyArea(img1Data.data, 45, 20, 2, 1, 39, 13, data);
copyArea(img1Data.data, 45, 31, 2, 1, 39, 14, data);
if (skin1_64x32) {
copyArea(img1Data.data, 45, 20, 2, 1, 47, 13, data);
copyArea(img1Data.data, 45, 31, 2, 1, 47, 14, data);
} else {
copyArea(img1Data.data, 37, 52, 2, 1, 47, 13, data);
copyArea(img1Data.data, 37, 63, 2, 1, 47, 14, data);
}
if (skin1_jacket) {
copyArea(img1Data.data, 45, 36, 2, 1, 39, 13, data);
if (skin1_64x32) {
copyArea(img1Data.data, 45, 36, 2, 1, 47, 13, data);
} else {
copyArea(img1Data.data, 53, 52, 2, 1, 47, 13, data);
}
}
// shoes
copyArea(img1Data.data, 5, 31, 2, 1, 41, 15, data);
copyArea(img1Data.data, 9, 17, 2, 1, 49, 7, data);
if (skin1_64x32) {
copyArea(img1Data.data, 5, 31, 2, 1, 45, 15, data);
copyArea(img1Data.data, 9, 17, 2, 1, 53, 7, data);
} else {
copyArea(img1Data.data, 21, 63, 2, 1, 45, 15, data);
copyArea(img1Data.data, 25, 49, 2, 1, 53, 7, data);
}
// body front
copyArea(img2Data.data, 8, 8, 8, 8, 20, 20, data);
copyArea(img2Data.data, 20, 20, 8, 1, 20, 28, data);
copyArea(img2Data.data, 20, 22, 8, 1, 20, 29, data);
copyArea(img2Data.data, 20, 24, 8, 1, 20, 30, data);
copyArea(img2Data.data, 20, 26, 8, 1, 20, 31, data);
// body top
copyArea(img2Data.data, 8, 2, 8, 4, 20, 16, data);
// body back
copyArea(img2Data.data, 24, 8, 8, 8, 32, 20, data);
copyArea(img2Data.data, 32, 20, 8, 1, 32, 28, data);
copyArea(img2Data.data, 32, 22, 8, 1, 32, 29, data);
copyArea(img2Data.data, 32, 24, 8, 1, 32, 30, data);
copyArea(img2Data.data, 32, 26, 8, 1, 32, 31, data);
// body left
copyArea(img2Data.data, 2, 8, 1, 8, 16, 20, data);
copyArea(img2Data.data, 4, 8, 1, 8, 17, 20, data);
copyArea(img2Data.data, 6, 8, 1, 8, 18, 20, data);
copyArea(img2Data.data, 7, 8, 1, 8, 19, 20, data);
copyArea(img2Data.data, 16, 20, 4, 1, 16, 28, data);
copyArea(img2Data.data, 16, 22, 4, 1, 16, 29, data);
copyArea(img2Data.data, 16, 24, 4, 1, 16, 30, data);
copyArea(img2Data.data, 16, 26, 4, 1, 16, 31, data);
// body right
copyArea(img2Data.data, 16, 8, 1, 8, 28, 20, data);
copyArea(img2Data.data, 17, 8, 1, 8, 29, 20, data);
copyArea(img2Data.data, 19, 8, 1, 8, 30, 20, data);
copyArea(img2Data.data, 21, 8, 1, 8, 31, 20, data);
copyArea(img2Data.data, 28, 20, 4, 1, 28, 28, data);
copyArea(img2Data.data, 28, 22, 4, 1, 28, 29, data);
copyArea(img2Data.data, 28, 24, 4, 1, 28, 30, data);
copyArea(img2Data.data, 28, 26, 4, 1, 28, 31, data);
// 2nd layer body front
copyArea(img2Data.data, 40, 8, 8, 8, 20, 36, data);
if (!skin2_64x32) {
copyArea(img2Data.data, 20, 36, 8, 1, 20, 44, data);
copyArea(img2Data.data, 20, 38, 8, 1, 20, 45, data);
copyArea(img2Data.data, 20, 40, 8, 1, 20, 46, data);
copyArea(img2Data.data, 20, 42, 8, 1, 20, 47, data);
}
// 2nd layer body top
copyArea(img2Data.data, 40, 2, 8, 4, 20, 32, data);
// 2nd layer body back
copyArea(img2Data.data, 56, 8, 8, 8, 32, 36, data);
if (!skin2_64x32) {
copyArea(img2Data.data, 32, 36, 8, 1, 32, 44, data);
copyArea(img2Data.data, 32, 38, 8, 1, 32, 45, data);
copyArea(img2Data.data, 32, 40, 8, 1, 32, 46, data);
copyArea(img2Data.data, 32, 42, 8, 1, 32, 47, data);
}
// 2nd layer body left
copyArea(img2Data.data, 34, 8, 1, 8, 16, 36, data);
copyArea(img2Data.data, 36, 8, 1, 8, 17, 36, data);
copyArea(img2Data.data, 38, 8, 1, 8, 18, 36, data);
copyArea(img2Data.data, 39, 8, 1, 8, 19, 36, data);
if (!skin2_64x32) {
copyArea(img2Data.data, 16, 36, 4, 1, 16, 44, data);
copyArea(img2Data.data, 16, 38, 4, 1, 16, 45, data);
copyArea(img2Data.data, 16, 40, 4, 1, 16, 46, data);
copyArea(img2Data.data, 16, 42, 4, 1, 16, 47, data);
}
// 2nd layer body right
copyArea(img2Data.data, 48, 8, 1, 8, 28, 36, data);
copyArea(img2Data.data, 49, 8, 1, 8, 29, 36, data);
copyArea(img2Data.data, 51, 8, 1, 8, 30, 36, data);
copyArea(img2Data.data, 53, 8, 1, 8, 31, 36, data);
if (!skin2_64x32) {
copyArea(img2Data.data, 28, 36, 4, 1, 28, 44, data);
copyArea(img2Data.data, 28, 38, 4, 1, 28, 45, data);
copyArea(img2Data.data, 28, 40, 4, 1, 28, 46, data);
copyArea(img2Data.data, 28, 42, 4, 1, 28, 47, data);
}
// left leg
copyArea(img2Data.data, 8, 16, 4, 4, 8, 16, data);
copyArea(img2Data.data, 28, 16, 4, 4, 4, 16, data);
copyArea(img2Data.data, 20, 28, 4, 1, 4, 20, data);
copyArea(img2Data.data, 20, 30, 4, 1, 4, 21, data);
copyArea(img2Data.data, 36, 28, 4, 1, 12, 20, data);
copyArea(img2Data.data, 36, 30, 4, 1, 12, 21, data);
copyArea(img2Data.data, 30, 17, 4, 2, 8, 20, data);
copyArea(img2Data.data, 16, 28, 4, 1, 0, 20, data);
copyArea(img2Data.data, 16, 30, 4, 1, 0, 21, data);
copyArea(img2Data.data, 0, 20, 16, 1, 0, 22, data);
copyArea(img2Data.data, 0, 22, 16, 1, 0, 23, data);
copyArea(img2Data.data, 0, 24, 16, 1, 0, 24, data);
copyArea(img2Data.data, 0, 25, 16, 7, 0, 25, data);
// right leg
if (skin2_64x32) {
copyArea(data, 0, 16, 16, 4, 16, 48, data);
copyArea(data, 12, 20, 1, 12, 31, 52, data);
copyArea(data, 13, 20, 1, 12, 30, 52, data);
copyArea(data, 14, 20, 1, 12, 29, 52, data);
copyArea(data, 15, 20, 1, 12, 28, 52, data);
copyArea(data, 0, 20, 1, 12, 27, 52, data);
copyArea(data, 1, 20, 1, 12, 26, 52, data);
copyArea(data, 2, 20, 1, 12, 25, 52, data);
copyArea(data, 3, 20, 1, 12, 24, 52, data);
copyArea(data, 4, 20, 1, 12, 23, 52, data);
copyArea(data, 5, 20, 1, 12, 22, 52, data);
copyArea(data, 6, 20, 1, 12, 21, 52, data);
copyArea(data, 7, 20, 1, 12, 20, 52, data);
copyArea(data, 8, 20, 1, 12, 19, 52, data);
copyArea(data, 9, 20, 1, 12, 18, 52, data);
copyArea(data, 10, 20, 1, 12, 17, 52, data);
copyArea(data, 11, 20, 1, 12, 16, 52, data);
} else {
copyArea(img2Data.data, 24, 48, 4, 4, 24, 48, data);
copyArea(img2Data.data, 32, 16, 4, 4, 20, 48, data);
copyArea(img2Data.data, 24, 28, 4, 1, 20, 52, data);
copyArea(img2Data.data, 24, 30, 4, 1, 20, 53, data);
copyArea(img2Data.data, 32, 28, 4, 1, 28, 52, data);
copyArea(img2Data.data, 32, 30, 4, 1, 28, 53, data);
copyArea(img2Data.data, 30, 17, 4, 2, 24, 52, data);
copyArea(img2Data.data, 28, 28, 4, 1, 16, 52, data);
copyArea(img2Data.data, 28, 30, 4, 1, 16, 53, data);
copyArea(img2Data.data, 16, 52, 16, 1, 16, 54, data);
copyArea(img2Data.data, 16, 54, 16, 1, 16, 55, data);
copyArea(img2Data.data, 16, 56, 16, 1, 16, 56, data);
copyArea(img2Data.data, 16, 57, 16, 7, 16, 57, data);
}
if (!skin2_64x32) {
// 2nd layer left leg
copyArea(img2Data.data, 8, 32, 4, 4, 8, 32, data);
copyArea(img2Data.data, 20, 44, 4, 1, 4, 36, data);
copyArea(img2Data.data, 20, 46, 4, 1, 4, 37, data);
copyArea(img2Data.data, 36, 44, 4, 1, 12, 36, data);
copyArea(img2Data.data, 36, 46, 4, 1, 12, 37, data);
copyArea(img2Data.data, 30, 32, 4, 2, 8, 36, data);
copyArea(img2Data.data, 16, 44, 4, 1, 0, 36, data);
copyArea(img2Data.data, 16, 46, 4, 1, 0, 37, data);
copyArea(img2Data.data, 0, 36, 16, 1, 0, 38, data);
copyArea(img2Data.data, 0, 38, 16, 1, 0, 39, data);
copyArea(img2Data.data, 0, 40, 16, 1, 0, 40, data);
copyArea(img2Data.data, 0, 41, 16, 7, 0, 41, data);
// 2nd layer right leg
copyArea(img2Data.data, 8, 48, 4, 4, 8, 48, data);
copyArea(img2Data.data, 24, 44, 4, 1, 4, 52, data);
copyArea(img2Data.data, 24, 46, 4, 1, 4, 53, data);
copyArea(img2Data.data, 32, 44, 4, 1, 12, 52, data);
copyArea(img2Data.data, 32, 46, 4, 1, 12, 53, data);
copyArea(img2Data.data, 30, 32, 4, 2, 0, 52, data);
copyArea(img2Data.data, 28, 44, 4, 1, 8, 52, data);
copyArea(img2Data.data, 28, 46, 4, 1, 8, 53, data);
copyArea(img2Data.data, 0, 52, 16, 1, 0, 54, data);
copyArea(img2Data.data, 0, 54, 16, 1, 0, 55, data);
copyArea(img2Data.data, 0, 56, 16, 1, 0, 56, data);
copyArea(img2Data.data, 0, 57, 16, 7, 0, 57, data);
}
// left arm
if (skin2_slim) {
copyArea(img2Data.data, 44, 16, 6, 4, 44, 16, data, true);
copyArea(img2Data.data, 40, 20, 4, 12, 40, 20, data, true);
copyArea(img2Data.data, 44, 20, 3, 12, 51, 20, data, true);
copyArea(img2Data.data, 47, 20, 4, 12, 47, 20, data, true);
copyArea(img2Data.data, 51, 20, 3, 12, 44, 20, data, true);
} else {
copyArea(img2Data.data, 44, 16, 8, 4, 44, 16, data, true);
copyArea(img2Data.data, 48, 20, 4, 12, 48, 20, data, true);
copyArea(img2Data.data, 52, 20, 4, 12, 44, 20, data, true);
copyArea(img2Data.data, 40, 20, 4, 12, 40, 20, data, true);
copyArea(img2Data.data, 44, 20, 4, 12, 52, 20, data, true);
}
// right arm
if (skin2_64x32) {
copyArea(data, 40, 16, 16, 4, 32, 48, data);
copyArea(data, 52, 20, 1, 12, 47, 52, data);
copyArea(data, 53, 20, 1, 12, 46, 52, data);
copyArea(data, 54, 20, 1, 12, 45, 52, data);
copyArea(data, 55, 20, 1, 12, 44, 52, data);
copyArea(data, 40, 20, 1, 12, 43, 52, data);
copyArea(data, 41, 20, 1, 12, 42, 52, data);
copyArea(data, 42, 20, 1, 12, 41, 52, data);
copyArea(data, 43, 20, 1, 12, 40, 52, data);
copyArea(data, 44, 20, 1, 12, 39, 52, data);
copyArea(data, 45, 20, 1, 12, 38, 52, data);
copyArea(data, 46, 20, 1, 12, 37, 52, data);
copyArea(data, 47, 20, 1, 12, 36, 52, data);
copyArea(data, 48, 20, 1, 12, 35, 52, data);
copyArea(data, 49, 20, 1, 12, 34, 52, data);
copyArea(data, 50, 20, 1, 12, 33, 52, data);
copyArea(data, 51, 20, 1, 12, 32, 52, data);
} else {
if (skin2_slim) {
copyArea(img2Data.data, 36, 48, 6, 4, 36, 48, data, true);
copyArea(img2Data.data, 32, 52, 4, 12, 32, 52, data, true);
copyArea(img2Data.data, 36, 52, 3, 12, 43, 52, data, true);
copyArea(img2Data.data, 39, 52, 4, 12, 39, 52, data, true);
copyArea(img2Data.data, 43, 52, 3, 12, 36, 52, data, true);
} else {
copyArea(img2Data.data, 36, 48, 8, 4, 36, 48, data, true);
copyArea(img2Data.data, 32, 52, 4, 12, 32, 52, data, true);
copyArea(img2Data.data, 36, 52, 4, 12, 44, 52, data, true);
copyArea(img2Data.data, 40, 52, 4, 12, 40, 52, data, true);
copyArea(img2Data.data, 44, 52, 4, 12, 36, 52, data, true);
}
}
if (!skin2_64x32) {
// 2nd layer left arm
if (skin2_slim) {
copyArea(img2Data.data, 44, 32, 6, 4, 44, 32, data, true);
copyArea(img2Data.data, 40, 36, 4, 12, 40, 36, data, true);
copyArea(img2Data.data, 44, 36, 3, 12, 51, 36, data, true);
copyArea(img2Data.data, 47, 36, 4, 12, 47, 36, data, true);
copyArea(img2Data.data, 51, 36, 3, 12, 44, 36, data, true);
} else {
copyArea(img2Data.data, 44, 32, 8, 4, 44, 32, data, true);
copyArea(img2Data.data, 48, 36, 4, 12, 48, 36, data, true);
copyArea(img2Data.data, 52, 36, 4, 12, 44, 36, data, true);
copyArea(img2Data.data, 40, 36, 4, 12, 40, 36, data, true);
copyArea(img2Data.data, 44, 36, 4, 12, 52, 36, data, true);
}
// 2nd layer right arm
if (skin2_slim) {
copyArea(img2Data.data, 52, 48, 6, 4, 52, 48, data, true);
copyArea(img2Data.data, 48, 52, 4, 12, 48, 52, data, true);
copyArea(img2Data.data, 52, 52, 3, 12, 59, 52, data, true);
copyArea(img2Data.data, 55, 52, 4, 12, 55, 52, data, true);
copyArea(img2Data.data, 59, 52, 3, 12, 52, 52, data, true);
} else {
copyArea(img2Data.data, 52, 48, 8, 4, 52, 48, data, true);
copyArea(img2Data.data, 48, 52, 4, 12, 48, 52, data, true);
copyArea(img2Data.data, 52, 52, 4, 12, 60, 52, data, true);
copyArea(img2Data.data, 56, 52, 4, 12, 56, 52, data, true);
copyArea(img2Data.data, 60, 52, 4, 12, 52, 52, data, true);
}
}
ctx.putImageData(combinedData, 0, 0);
combinedImgElement.src = canvas.toDataURL();
const resultPreview = document.getElementById('result-preview');
resultPreview.style.display = 'block';
const base64 = combinedImgElement.src.split(',')[1]
.replace(/\+/g, '-')
.replace(/\//g, '_')
.replace(/=+$/, '');
var slimquery = skin2_slim ? "?slim" : "";
document.getElementById('full-body-preview').src = `https://vzge.me/frontfull/384/${base64}` + slimquery;
document.getElementById('head-preview').src = `https://vzge.me/head/256/${base64}`;
}
function handleInput(input, callback) {
if (input.files && input.files[0]) {
loadImage(input.files[0], callback);
} else if (input.value) {
const username = input.value.trim();
const url = `https://vzge.me/processedskin/${username}`;
loadImage(url, callback);
}
}
upload1.addEventListener('change', function() {
handleInput(upload1, function(img) {
img1Element.src = img.src;
img1Data = getImageData(img);
if (img2Data) combineSkins();
});
});
upload2.addEventListener('change', function() {
handleInput(upload2, function(img) {
img2Element.src = img.src;
img2Data = getImageData(img);
if (img1Data) combineSkins();
});
});
username1.addEventListener('change', function() {
handleInput(username1, function(img) {
img1Element.src = img.src;
img1Data = getImageData(img);
if (img2Data) combineSkins();
});
});
username2.addEventListener('change', function() {
handleInput(username2, function(img) {
img2Element.src = img.src;
img2Data = getImageData(img);
if (img1Data) combineSkins();
});
});
document.getElementById('skin1_64x32').addEventListener('change', function() {
if (img2Data) combineSkins();
});
document.getElementById('skin1_jacket').addEventListener('change', function() {
if (img2Data) combineSkins();
});
document.getElementById('skin2_64x32').addEventListener('change', function() {
if (img2Data) combineSkins();
});
document.getElementById('skin2_slim').addEventListener('change', function() {
if (img2Data) combineSkins();
});
document.getElementById('fix_eyes').addEventListener('change', function() {
if (img2Data) combineSkins();
});
getUsersFromUrl();