Rocky_Mountain_Vending/.pnpm-store/v10/files/9d/90ec29f1a0731a83d45b90996dfc1fe020af0342c52a8a2947d25dd89252e656eaec57fb7bb9b21c75e1a035b93d533eb81dedf8a3bc9eea6700492db4955f
DMleadgen 46d973904b
Initial commit: Rocky Mountain Vending website
Next.js website for Rocky Mountain Vending company featuring:
- Product catalog with Stripe integration
- Service areas and parts pages
- Admin dashboard with Clerk authentication
- SEO optimized pages with JSON-LD structured data

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-02-12 16:22:15 -07:00

143 lines
6.6 KiB
Text

/**
* @preserve
* Copyright 2015 Igor Bezkrovny
* All rights reserved. (MIT Licensed)
*
* ssim.ts - part of Image Quantization Library
*/
/**
* - Original TypeScript implementation:
* https://github.com/igor-bezkrovny/image-quantization/blob/9f62764ac047c3e53accdf1d7e4e424b0ef2fb60/src/quality/ssim.ts
* - Based on Java implementation: https://github.com/rhys-e/structural-similarity
* - For more information see: http://en.wikipedia.org/wiki/Structural_similarity
*/
var ImageSSIM;
(function (ImageSSIM) {
'use strict';
/**
* Grey = 1, GreyAlpha = 2, RGB = 3, RGBAlpha = 4
*/
(function (Channels) {
Channels[Channels["Grey"] = 1] = "Grey";
Channels[Channels["GreyAlpha"] = 2] = "GreyAlpha";
Channels[Channels["RGB"] = 3] = "RGB";
Channels[Channels["RGBAlpha"] = 4] = "RGBAlpha";
})(ImageSSIM.Channels || (ImageSSIM.Channels = {}));
var Channels = ImageSSIM.Channels;
/**
* Entry point.
* @throws new Error('Images have different sizes!')
*/
function compare(image1, image2, windowSize, K1, K2, luminance, bitsPerComponent) {
if (windowSize === void 0) { windowSize = 8; }
if (K1 === void 0) { K1 = 0.01; }
if (K2 === void 0) { K2 = 0.03; }
if (luminance === void 0) { luminance = true; }
if (bitsPerComponent === void 0) { bitsPerComponent = 8; }
if (image1.width !== image2.width || image1.height !== image2.height) {
throw new Error('Images have different sizes!');
}
/* tslint:disable:no-bitwise */
var L = (1 << bitsPerComponent) - 1;
/* tslint:enable:no-bitwise */
var c1 = Math.pow((K1 * L), 2), c2 = Math.pow((K2 * L), 2), numWindows = 0, mssim = 0.0;
var mcs = 0.0;
function iteration(lumaValues1, lumaValues2, averageLumaValue1, averageLumaValue2) {
// calculate variance and covariance
var sigxy, sigsqx, sigsqy;
sigxy = sigsqx = sigsqy = 0.0;
for (var i = 0; i < lumaValues1.length; i++) {
sigsqx += Math.pow((lumaValues1[i] - averageLumaValue1), 2);
sigsqy += Math.pow((lumaValues2[i] - averageLumaValue2), 2);
sigxy += (lumaValues1[i] - averageLumaValue1) * (lumaValues2[i] - averageLumaValue2);
}
var numPixelsInWin = lumaValues1.length - 1;
sigsqx /= numPixelsInWin;
sigsqy /= numPixelsInWin;
sigxy /= numPixelsInWin;
// perform ssim calculation on window
var numerator = (2 * averageLumaValue1 * averageLumaValue2 + c1) * (2 * sigxy + c2);
var denominator = (Math.pow(averageLumaValue1, 2) + Math.pow(averageLumaValue2, 2) + c1) * (sigsqx + sigsqy + c2);
mssim += numerator / denominator;
mcs += (2 * sigxy + c2) / (sigsqx + sigsqy + c2);
numWindows++;
}
// calculate SSIM for each window
Internals._iterate(image1, image2, windowSize, luminance, iteration);
return { ssim: mssim / numWindows, mcs: mcs / numWindows };
}
ImageSSIM.compare = compare;
/**
* Internal functions.
*/
var Internals;
(function (Internals) {
function _iterate(image1, image2, windowSize, luminance, callback) {
var width = image1.width, height = image1.height;
for (var y = 0; y < height; y += windowSize) {
for (var x = 0; x < width; x += windowSize) {
// avoid out-of-width/height
var windowWidth = Math.min(windowSize, width - x), windowHeight = Math.min(windowSize, height - y);
var lumaValues1 = _lumaValuesForWindow(image1, x, y, windowWidth, windowHeight, luminance), lumaValues2 = _lumaValuesForWindow(image2, x, y, windowWidth, windowHeight, luminance), averageLuma1 = _averageLuma(lumaValues1), averageLuma2 = _averageLuma(lumaValues2);
callback(lumaValues1, lumaValues2, averageLuma1, averageLuma2);
}
}
}
Internals._iterate = _iterate;
function _lumaValuesForWindow(image, x, y, width, height, luminance) {
var array = image.data, lumaValues = new Float32Array(new ArrayBuffer(width * height * 4)), counter = 0;
var maxj = y + height;
for (var j = y; j < maxj; j++) {
var offset = j * image.width;
var i = (offset + x) * image.channels;
var maxi = (offset + x + width) * image.channels;
switch (image.channels) {
case 1 /* Grey */:
while (i < maxi) {
// (0.212655 + 0.715158 + 0.072187) === 1
lumaValues[counter++] = array[i++];
}
break;
case 2 /* GreyAlpha */:
while (i < maxi) {
lumaValues[counter++] = array[i++] * (array[i++] / 255);
}
break;
case 3 /* RGB */:
if (luminance) {
while (i < maxi) {
lumaValues[counter++] = (array[i++] * 0.212655 + array[i++] * 0.715158 + array[i++] * 0.072187);
}
}
else {
while (i < maxi) {
lumaValues[counter++] = (array[i++] + array[i++] + array[i++]);
}
}
break;
case 4 /* RGBAlpha */:
if (luminance) {
while (i < maxi) {
lumaValues[counter++] = (array[i++] * 0.212655 + array[i++] * 0.715158 + array[i++] * 0.072187) * (array[i++] / 255);
}
}
else {
while (i < maxi) {
lumaValues[counter++] = (array[i++] + array[i++] + array[i++]) * (array[i++] / 255);
}
}
break;
}
}
return lumaValues;
}
function _averageLuma(lumaValues) {
var sumLuma = 0.0;
for (var i = 0; i < lumaValues.length; i++) {
sumLuma += lumaValues[i];
}
return sumLuma / lumaValues.length;
}
})(Internals || (Internals = {}));
})(ImageSSIM || (ImageSSIM = {}));
module.exports = ImageSSIM;