@vizzly-testing/honeydiff

Blazingly fast image comparison for visual regression testing in Node.js. Built with Rust for native performance.

npm install @vizzly-testing/honeydiff

Requires Node.js 22+. Pre-built binaries included for macOS (ARM64), Linux (x64/ARM64), and Windows (x64).

Why Honeydiff?

6x faster than odiff - Processes 230M+ pixels/sec with multi-core parallelization
Smart anti-aliasing - Filters out rendering artifacts, not actual changes
Accessibility built-in - WCAG contrast analysis for catching accessibility violations
Flexible inputs - Works with file paths or Buffers
Full TypeScript support - Complete type definitions included
Advanced analytics - SSIM perceptual scoring, spatial clustering, intensity stats

Built for production visual regression testing at scale.

Quick Start

Basic Comparison

const { compare, quickCompare } = require('@vizzly-testing/honeydiff');

// Quick boolean check - are these images different?
if (await quickCompare('baseline.png', 'current.png')) {
  console.log('Visual regression detected!');
}

// Detailed comparison with tolerance
const result = await compare('baseline.png', 'current.png', {
  pixelTolerance: 10,  // Ignore tiny differences
  includeSSIM: true    // Perceptual similarity score
});

console.log(`Diff: ${result.diffPercentage.toFixed(2)}%`);
console.log(`SSIM: ${result.perceptualScore}`);
// Output: Diff: 3.55%, SSIM: 0.9234

TypeScript

import { compare, CompareOptions, DiffResult } from '@vizzly-testing/honeydiff';

const options: CompareOptions = {
  pixelTolerance: 5,
  includeSSIM: true,
  includeClusters: true
};

const result: DiffResult = await compare('img1.png', 'img2.png', options);

if (result.diffClusters) {
  console.log(`Found ${result.diffClusters.length} different regions`);
}

Test Integration

Jest/Vitest

import { quickCompare } from '@vizzly-testing/honeydiff';

test('homepage should match baseline', async () => {
  let screenshot = await page.screenshot();
  let isDifferent = await quickCompare('baseline.png', screenshot);
  expect(isDifferent).toBe(false);
});

Playwright

const { compare } = require('@vizzly-testing/honeydiff');

test('button hover state', async () => {
  await page.hover('[data-testid="submit-button"]');
  let screenshot = await page.screenshot();

  let result = await compare('baseline.png', screenshot, {
    pixelTolerance: 10,
    diffPath: './artifacts/diff.png'
  });

  expect(result.diffPercentage).toBeLessThan(1.0);
});

Core Features

1. Performance at Scale

Process 230M pixels/second with automatic multi-core parallelization. Perfect for CI/CD pipelines.

// 18.3M pixel screenshot compared in ~79ms
const result = await compare('full-page-baseline.png', 'full-page-current.png');

2. Smart Anti-Aliasing Detection

Automatically filters out rendering artifacts (font smoothing, sub-pixel differences) while catching real visual changes.

const result = await compare('img1.png', 'img2.png', {
  antialiasing: true  // Default: true
});

console.log(`Ignored ${result.aaPixelsIgnored} AA pixels`);
// Output: Ignored 1952904 AA pixels

Disable for pixel-perfect matching:

const result = await compare('img1.png', 'img2.png', {
  antialiasing: false  // Strict pixel matching
});

3. Variable Height Screenshots

Perfect for scrollable content - compare full-page screenshots with different heights.

// 24,162px vs 24,412px tall images
const result = await compare('full-page-v1.png', 'full-page-v2.png');

if (result.heightDiff) {
  console.log(`Height difference: ${result.heightDiff.height1} vs ${result.heightDiff.height2}`);
  console.log(`Extra pixels: ${result.heightDiff.extraPixels}`);
}

4. Visual Diff Artifacts

Generate highlighted diff images, binary masks, and overlays for debugging.

const result = await compare('baseline.png', 'current.png', {
  diffPath: './artifacts/diff.png',      // Highlighted differences
  maskPath: './artifacts/mask.png',      // Binary diff mask
  overlayPath: './artifacts/overlay.png', // Side-by-side comparison
  overwrite: true
});

console.log('Artifacts saved to ./artifacts/');

5. Spatial Clustering & Noise Filtering

Group nearby differences into regions and filter out single-pixel noise from rendering variance.

const result = await compare('img1.png', 'img2.png', {
  includeClusters: true,
  minClusterSize: 2  // Default: filter single isolated pixels as noise
});

if (result.diffClusters) {
  result.diffClusters.forEach((cluster, i) => {
    console.log(`Region ${i + 1}:`);
    console.log(`  - ${cluster.pixelCount} pixels changed`);
    console.log(`  - Center at (${cluster.centerOfMass[0]}, ${cluster.centerOfMass[1]})`);
    console.log(`  - Bounding box: ${cluster.boundingBox.width}x${cluster.boundingBox.height}`);
    console.log(`  - Average intensity: ${cluster.avgIntensity}`);
  });
}
// Output:
// Region 1:
//   - 12450 pixels changed
//   - Center at (245, 189)
//   - Bounding box: 124x89
//   - Average intensity: 127.3

Noise filtering values:

Value	Behavior
1	Exact matching - any different pixel counts
2	Default - filters single isolated pixels as rendering noise
3+	More permissive - only larger clusters detected

6. Perceptual Similarity (SSIM)

Beyond pixel counting - measure structural similarity from a human perception perspective.

const result = await compare('img1.png', 'img2.png', {
  includeSSIM: true  // Note: Can be slow on large images
});

if (result.perceptualScore !== null) {
  console.log(`SSIM: ${result.perceptualScore.toFixed(3)}`);
  // Output: SSIM: 0.923 (0.0 = different, 1.0 = identical)

  if (result.perceptualScore > 0.95) {
    console.log('Images are perceptually very similar');
  }
}

7. Tolerance & Color Spaces

RGB Mode (default) - Exact matching with pixel tolerance:

const result = await compare('img1.png', 'img2.png', {
  pixelTolerance: 10  // Ignore differences below threshold (0-255)
});

YIQ Mode - Perceptual color matching weighted for human vision:

const result = await compare('img1.png', 'img2.png', {
  colorThreshold: 0.1  // YIQ mode (odiff-compatible)
});

Brightness-only Mode - Ignore color, compare structure:

const result = await compare('img1.png', 'img2.png', {
  ignoreColors: true  // Compare brightness/luminance only
});

8. Buffer Support

Work with in-memory images from screenshots or API responses.

const fs = require('fs');

// Compare buffers directly
let img1 = fs.readFileSync('image1.png');
let img2 = fs.readFileSync('image2.png');
let result = await compare(img1, img2, { pixelTolerance: 5 });

// Mix paths and buffers
let screenshot = await page.screenshot();  // Returns Buffer
let result = await compare('baseline.png', screenshot);

9. Image Dimensions

Fast utility to get image dimensions without loading full image data.

const { getDimensions } = require('@vizzly-testing/honeydiff');

let dims = await getDimensions('screenshot.png');
console.log(`Image is ${dims.width}x${dims.height} pixels`);
// Output: Image is 1920x1080 pixels

// Works with buffers too
let buffer = fs.readFileSync('image.png');
let dims = await getDimensions(buffer);

10. Image Metadata

Get image dimensions, file size, and format detection - useful for storage tracking and billing.

const { getImageMetadata, getImageMetadataFromFile } = require('@vizzly-testing/honeydiff');

// From buffer
let buffer = fs.readFileSync('screenshot.png');
let metadata = await getImageMetadata(buffer);
console.log(`Image: ${metadata.width}x${metadata.height}`);
console.log(`Size: ${metadata.fileSizeBytes} bytes`);
console.log(`Format: ${metadata.format}`);
// Output: Image: 1920x1080
//         Size: 245760 bytes
//         Format: png

// From file (gets accurate file size from disk)
let metadata = await getImageMetadataFromFile('screenshot.png');
console.log(`${metadata.width}x${metadata.height}, ${metadata.fileSizeBytes} bytes`);

Accessibility Features

Built-in WCAG color contrast analysis and color blindness simulation to catch accessibility violations in screenshots and UI designs.

WCAG Contrast Analysis

Analyze entire images for WCAG color contrast violations - perfect for catching accessibility issues in screenshots and UI designs.

const { analyzeWcagContrast, saveWcagOverlay } = require('@vizzly-testing/honeydiff');

// Analyze a screenshot for accessibility violations
let analysis = await analyzeWcagContrast('screenshot.png', {
  edgeThreshold: 60,      // Edge detection sensitivity (0-255)
  minRegionSize: 50,      // Minimum violation region size (pixels)
  checkAA: true,          // Check WCAG AA (4.5:1 normal, 3.0:1 large)
  checkAAA: true          // Check WCAG AAA (7.0:1 normal, 4.5:1 large)
});

console.log(`Total edges analyzed: ${analysis.totalEdges}`);
console.log(`AA normal text pass rate: ${analysis.aaNormalPassPercentage.toFixed(1)}%`);
console.log(`Found ${analysis.violations.length} violations`);

// Examine violations
analysis.violations.forEach((violation, i) => {
  console.log(`\nViolation ${i + 1}:`);
  console.log(`  Location: (${violation.boundingBox.x}, ${violation.boundingBox.y})`);
  console.log(`  Contrast ratio: ${violation.contrastRatio.toFixed(2)}:1`);
  console.log(`  Foreground: rgb(${violation.foregroundColor.slice(0,3).join(', ')})`);
  console.log(`  Background: rgb(${violation.backgroundColor.slice(0,3).join(', ')})`);
  console.log(`  Fails AA normal: ${violation.failsAaNormal}`);
  console.log(`  Fails AAA normal: ${violation.failsAaaNormal}`);
});

// Generate visual overlay showing violations
await saveWcagOverlay('screenshot.png', analysis, 'violations.png', {
  highlightColor: [255, 0, 0, 180]  // Semi-transparent red
});

Advanced filtering:

let analysis = await analyzeWcagContrast('screenshot.png', {
  edgeThreshold: 80,           // Higher = fewer false positives
  minRegionSize: 100,          // Ignore tiny regions
  maxContrastThreshold: 3.5,   // Only flag severe violations
  checkAA: true,
  checkAAA: false
});

console.log(`AA pass rate: ${analysis.aaNormalPassPercentage.toFixed(1)}%`);

Color Blindness Simulation

Simulate how your UI appears to users with color vision deficiencies. Uses the scientifically accurate Brettel, Viénot & Mollon 1997 algorithm.

Supported CVD types:

protanopia - Red-blind (~1% of males)
deuteranopia - Green-blind (~1% of males, most common)
tritanopia - Blue-blind (~0.003% of population)
achromatopsia - Complete color blindness (grayscale only)

const {
  simulateColorBlindness,
  saveColorBlindnessSimulation,
  saveAllColorBlindnessSimulations,
  getColorBlindnessTypes
} = require('@vizzly-testing/honeydiff');

// Get CVD type information
let types = getColorBlindnessTypes();
types.forEach(cvd => {
  console.log(`${cvd.name}: ${cvd.description} (${cvd.prevalence})`);
});

// Simulate and get buffer (useful for in-memory operations)
let simulated = await simulateColorBlindness('chart.png', 'deuteranopia');
fs.writeFileSync('chart-deuteranopia.png', simulated);

// Or save directly to file
await saveColorBlindnessSimulation('ui.png', 'protanopia', 'ui-protanopia.png');

// Generate all simulations at once
// Creates: dashboard_protanopia.png, dashboard_deuteranopia.png,
//          dashboard_tritanopia.png, dashboard_achromatopsia.png
await saveAllColorBlindnessSimulations('dashboard.png', 'dashboard', 'png');

CVD-Aware WCAG Analysis

Analyze contrast accessibility specifically for colorblind users. This catches issues that only appear when colors are perceived differently.

const { analyzeWcagForCvd, analyzeWcagAllCvd } = require('@vizzly-testing/honeydiff');

// Analyze for a specific CVD type
let analysis = await analyzeWcagForCvd('ui.png', 'deuteranopia', {
  checkAA: true,
  checkAAA: false
});

if (analysis.violations.length > 0) {
  console.log(`Found ${analysis.violations.length} contrast issues for red-green colorblind users`);
}

// Comprehensive report for all CVD types
let report = await analyzeWcagAllCvd('dashboard.png', {
  checkAA: true,
  checkAAA: true
});

console.log('Accessibility Report:');
console.log(`Normal vision:  ${report.normalVision.violations.length} violations`);
console.log(`Protanopia:     ${report.protanopia.violations.length} violations`);
console.log(`Deuteranopia:   ${report.deuteranopia.violations.length} violations`);
console.log(`Tritanopia:     ${report.tritanopia.violations.length} violations`);
console.log(`Total: ${report.totalViolations} violations`);
console.log(`CVD-only issues: ~${report.cvdOnlyViolationCount}`);

if (report.hasAnyViolations) {
  console.log('Accessibility issues detected!');
}

Test integration:

test('UI colors work for colorblind users', async () => {
  let screenshot = await page.screenshot();

  // Comprehensive CVD accessibility check
  let report = await analyzeWcagAllCvd(screenshot, { checkAA: true });

  expect(report.hasAnyViolations).toBe(false);
  expect(report.deuteranopia.aaNormalPassPercentage).toBeGreaterThan(95);
});

Complete API Reference

Async Functions (Recommended)

compare(img1, img2, options?): Promise<DiffResult>

Full comparison with detailed results.

quickCompare(img1, img2): Promise<boolean>

Fast boolean check - returns true if different, false if identical.

getDimensions(img): Promise<{ width: number, height: number }>

Get image dimensions without loading full image data.

getImageMetadata(buffer): Promise<ImageMetadata>

Get image metadata (dimensions, file size, format) from a buffer.

getImageMetadataFromFile(path): Promise<ImageMetadata>

Get image metadata from a file path. File size is read from disk for accuracy.

Sync Functions (Blocks Event Loop)

compareSync(img1, img2, options?): DiffResult

Synchronous comparison. Use only when blocking behavior is required.

quickCompareSync(img1, img2): boolean

Synchronous boolean check.

getDimensionsSync(img): { width: number, height: number }

Synchronous dimension retrieval.

getImageMetadataSync(buffer): ImageMetadata

Synchronous metadata retrieval from buffer.

getImageMetadataFromFileSync(path): ImageMetadata

Synchronous metadata retrieval from file.

Input Types

All functions accept:

string - File path to PNG image
Buffer - Image data in memory

CompareOptions

interface CompareOptions {
  // Basic options
  pixelTolerance?: number;              // 0-255, ignore diffs below threshold (default: 0)
  colorThreshold?: number;              // 0.0-1.0, YIQ mode threshold (default: 0.0 = RGB)
  antialiasing?: boolean;               // Ignore AA artifacts (default: true)
  ignoreColors?: boolean;               // Brightness only (default: false)
  maxDiffs?: number;                    // Stop after N diffs (default: unlimited)

  // Analysis options
  includeDiffPixels?: boolean;          // List all diff pixels (memory intensive, default: false)
  includeClusters?: boolean;            // Spatial clustering (default: false)
  includeSSIM?: boolean;                // SSIM perceptual score (slow, default: false)
  minClusterSize?: number;              // Filter clusters smaller than this (default: 2)

  // Accessibility options
  includeAccessibilityData?: boolean;   // RGB, luminance, WCAG (default: false)
  checkColorBlindness?: boolean;        // Color blindness simulation (default: false)
  colorBlindnessThreshold?: number;     // Visibility threshold 0-255 (default: 30.0)

  // Output options
  diffPath?: string;                    // Save diff image path
  maskPath?: string;                    // Save mask image path
  overlayPath?: string;                 // Save overlay image path
  overwrite?: boolean;                  // Overwrite existing files (default: false)
  diffMaskColor?: string | number[];    // Highlight color: hex or [r,g,b,a] (default: "ff0000")
}

DiffResult

interface DiffResult {
  // Basic metrics
  isDifferent: boolean;                 // Are images different? (respects minClusterSize filtering)
  diffPercentage: number;               // 0.0-100.0
  totalPixels: number;
  diffPixels: number;                   // Raw count (unaffected by minClusterSize filtering)

  // Anti-aliasing
  aaPixelsIgnored: number;
  aaPercentage: number;                 // 0.0-100.0

  // Spatial info
  boundingBox: BoundingBox | null;      // Rectangle containing all diffs
  heightDiff: HeightDiff | null;        // Height difference info

  // Advanced analysis
  diffPixelsList: DiffPixel[] | null;   // Null unless includeDiffPixels enabled
  diffClusters: DiffCluster[] | null;   // Null unless includeClusters enabled
  intensityStats: IntensityStats | null; // Null unless includeDiffPixels enabled
  perceptualScore: number | null;       // 0.0-1.0, null unless includeSSIM enabled
}

See index.d.ts for complete type definitions.

Performance

Benchmarked on 18.3M pixel screenshots (750 x 24,162 px):

Operation	Time	Throughput
Basic RGB comparison	~79ms	231.8M pixels/sec
With anti-aliasing	~88ms	208M pixels/sec
YIQ color space	~89ms	206M pixels/sec
With artifacts (diff/mask/overlay)	~432ms	42.4M pixels/sec

vs odiff: 6.0x faster (79ms vs 474ms)

Multi-core parallelization: 215-309% CPU utilization across cores.

Benchmarked on Apple M-series Mac.

Common Patterns

CI/CD Integration

const { compare } = require('@vizzly-testing/honeydiff');

async function visualRegressionTest() {
  let result = await compare('baseline.png', 'current.png', {
    pixelTolerance: 10,
    maxDiffs: 1000,  // Early exit for fast failure
    diffPath: process.env.CI ? './artifacts/diff.png' : undefined
  });

  if (result.isDifferent && result.diffPercentage > 1.0) {
    console.error(`Visual regression: ${result.diffPercentage.toFixed(2)}% changed`);
    process.exit(1);
  }
}

Progressive Enhancement

// Start with quick check
if (await quickCompare('baseline.png', 'current.png')) {
  // Only run expensive analysis if different
  let result = await compare('baseline.png', 'current.png', {
    includeClusters: true,
    includeSSIM: true,
    diffPath: './diff.png'
  });

  // Detailed analysis and reporting
  reportVisualRegression(result);
}

Tolerance Thresholds

const result = await compare('baseline.png', 'current.png', {
  pixelTolerance: 10
});

if (result.diffPercentage > 5.0) {
  console.error('FAIL: Major visual regression');
  process.exit(1);
} else if (result.diffPercentage > 1.0) {
  console.warn('WARN: Minor visual changes detected');
} else {
  console.log('PASS: Visual test passed');
}

Troubleshooting

Module not found errors

Ensure Node.js 22+ is installed
Verify your platform is supported (macOS ARM64, Linux x64/ARM64, Windows x64)
Try npm install again to download pre-built binaries

Large memory usage with includeDiffPixels

This option stores every different pixel's position and intensity
Disable for large images with many differences
Only enable if you need detailed pixel-level data

Slow performance with includeSSIM

SSIM calculation is O(width × height × window²)
Only enable when perceptual scoring is needed
Consider running SSIM only on failed comparisons

Anti-aliasing too aggressive

Set antialiasing: false for stricter pixel matching
Adjust pixelTolerance instead for controlled flexibility

Use Cases

Visual Regression Testing - Catch unintended UI changes in CI/CD
Screenshot Validation - Compare generated screenshots against baselines
Accessibility Testing - Validate WCAG contrast and color blindness visibility
Design QA - Ensure implementations match design specifications
Cross-browser Testing - Detect rendering differences across browsers
A/B Testing - Measure visual differences between variants
Responsive Design - Compare layouts across viewports

Examples

See examples/ directory:

basic.js - Core features and comparison options
buffers.js - Working with in-memory images
typescript.ts - TypeScript integration
wcag.js - WCAG contrast analysis
color-blindness.js - CVD simulation and accessibility

License

MIT License

Built with native Rust for maximum performance.

Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
.github/ISSUE_TEMPLATE		.github/ISSUE_TEMPLATE
CHANGELOG.md		CHANGELOG.md
LICENSE		LICENSE
README.md		README.md
index.d.ts		index.d.ts
index.js		index.js
load-platform.cjs		load-platform.cjs
package.json		package.json

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@vizzly-testing/honeydiff

Why Honeydiff?

Quick Start

Basic Comparison

TypeScript

Test Integration

Core Features

1. Performance at Scale

2. Smart Anti-Aliasing Detection

3. Variable Height Screenshots

4. Visual Diff Artifacts

5. Spatial Clustering & Noise Filtering

6. Perceptual Similarity (SSIM)

7. Tolerance & Color Spaces

8. Buffer Support

9. Image Dimensions

10. Image Metadata

Accessibility Features

WCAG Contrast Analysis

Color Blindness Simulation

CVD-Aware WCAG Analysis

Complete API Reference

Async Functions (Recommended)

Sync Functions (Blocks Event Loop)

Input Types

CompareOptions

DiffResult

Performance

Common Patterns

CI/CD Integration

Progressive Enhancement

Tolerance Thresholds

Troubleshooting

Use Cases

Examples

License

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