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tsup.config.ts	tsup.config.ts

@blazediff/core-native

The fastest single-threaded image diff in the world. Native Rust implementation with SIMD optimization, 3-4x faster and 3x smaller than odiff.

Features:

PNG, JPEG & QOI support - auto-detected by file extension
SIMD-accelerated (NEON on ARM, SSE4.1 on x86)
Block-based two-pass optimization
YIQ perceptual color difference
Anti-aliasing detection
Cross-platform pre-built binaries (~700KB-900KB, no compilation required)

Vendored Libraries:

libspng - Fast PNG decoding/encoding with SIMD
libjpeg-turbo - High-performance JPEG codec with SIMD
qoi - QOI (Quite OK Image) format for fast lossless compression

Note: This package was previously published as @blazediff/bin, which is now deprecated. Please use @blazediff/core-native instead.

Installation

npm install @blazediff/core-native

Also available as a Rust crate: cargo install blazediff

Pre-built binaries are included via platform-specific packages:

@blazediff/core-native-darwin-arm64 - macOS ARM64 (Apple Silicon)
@blazediff/core-native-darwin-x64 - macOS x64 (Intel)
@blazediff/core-native-linux-arm64 - Linux ARM64
@blazediff/core-native-linux-x64 - Linux x64
@blazediff/core-native-win32-arm64 - Windows ARM64
@blazediff/core-native-win32-x64 - Windows x64

API

compare(basePath, comparePath, diffOutput, options?)

Compare two images (PNG or JPEG) and generate a diff image. Format is auto-detected from file extension.

Parameter	Type	Description
`basePath`	string	Path to the base/expected image
`comparePath`	string	Path to the comparison/actual image
`diffOutput`	string	Path where the diff image will be saved
`options`	BlazeDiffOptions	Comparison options (optional)

Returns: Promise<BlazeDiffResult>

Option	Type	Default	Description
`threshold`	number	0.1	Color difference threshold (0.0-1.0). Lower = more strict
`antialiasing`	boolean	false	Enable anti-aliasing detection to exclude AA pixels from diff count
`diffMask`	boolean	false	Output only differences with transparent background
`interpret`	boolean	false	Run structured interpretation after diff — adds `interpretation` to the result with detected change regions, classification, and a human-readable summary
`outputFormat`	"png" \| "html"	"png"	Output format for diff. Use `"html"` to generate an interpret report (implies `interpret: true`)

interpret(image1Path, image2Path, options?)

Convenience wrapper that calls compare with interpret: true and returns the InterpretResult directly. No diff image output — purely analytical.

Parameter	Type	Description
`image1Path`	string	Path to the first image
`image2Path`	string	Path to the second image
`options`	Pick<BlazeDiffOptions, "threshold" \| "antialiasing">	Comparison options (optional)

Returns: Promise<InterpretResult>

Result Types

type BlazeDiffResult =
  | { match: true; interpretation?: InterpretResult }
  | { match: false; reason: "layout-diff" }
  | { match: false; reason: "pixel-diff"; diffCount: number; diffPercentage: number; interpretation?: InterpretResult }
  | { match: false; reason: "file-not-exists"; file: string };

interface InterpretResult {
  summary: string;          // Human-readable summary of the diff
  diffCount: number;        // Total number of differing pixels
  totalRegions: number;     // Number of detected change regions
  regions: ChangeRegion[];  // Detailed per-region analysis
  severity: string;         // Overall severity level
  diffPercentage: number;   // Percentage of pixels that differ
  width: number;            // Image width
  height: number;           // Image height
}

interface ChangeRegion {
  bbox: BoundingBox;               // Bounding box of the region
  pixelCount: number;              // Number of changed pixels in this region
  percentage: number;              // Percentage of image this region covers
  position: string;                // Spatial position descriptor
  shape: string;                   // Shape classification
  shapeStats: ShapeStats;          // Shape statistical analysis
  changeType: string;              // Type of change detected
  signals: ClassificationSignals;  // Classification signal details
  confidence: number;              // Confidence level of classification
  colorDelta: ColorDeltaStats;     // Color difference statistics
  gradient: GradientStats;         // Gradient analysis statistics
}

Usage

Programmatic API

import { compare } from '@blazediff/core-native';

const result = await compare('expected.png', 'actual.png', 'diff.png', {
  threshold: 0.1,
  antialiasing: true,
});

if (result.match) {
  console.log('Images are identical!');
} else if (result.reason === 'pixel-diff') {
  console.log(`${result.diffCount} pixels differ (${result.diffPercentage.toFixed(2)}%)`);
} else if (result.reason === 'layout-diff') {
  console.log('Images have different dimensions');
}

Compare with Interpretation

import { compare } from '@blazediff/core-native';

const result = await compare('expected.png', 'actual.png', 'diff.png', {
  threshold: 0.1,
  interpret: true,
});

if (!result.match && result.reason === 'pixel-diff') {
  const { interpretation } = result;
  console.log(interpretation.summary);
  for (const region of interpretation.regions) {
    console.log(`${region.position}: ${region.changeType} (${region.percentage.toFixed(2)}%)`);
  }
}

Interpret Only (no diff image)

import { interpret } from '@blazediff/core-native';

const result = await interpret('expected.png', 'actual.png');
console.log(result.summary);
console.log(`Severity: ${result.severity}, ${result.diffPercentage.toFixed(2)}% changed`);

CLI Usage

# Compare two PNG images
npx blazediff expected.png actual.png diff.png

# Compare two JPEG images
npx blazediff expected.jpg actual.jpg diff.jpg

# Compare two QOI images
npx blazediff expected.qoi actual.qoi diff.qoi

# Mixed formats (PNG input, QOI output - recommended for smallest diff files)
npx blazediff expected.png actual.png diff.qoi

# With options
npx blazediff expected.png actual.png diff.png --threshold 0.05 --antialiasing

# With higher PNG compression (smaller output file, slower)
npx blazediff expected.png actual.png diff.png -c 6

# With JPEG quality setting
npx blazediff expected.jpg actual.jpg diff.jpg -q 85

# Output as JSON
npx blazediff expected.png actual.png diff.png --output-format json

CLI Options

Usage: blazediff [OPTIONS] <IMAGE1> <IMAGE2> [OUTPUT]

Arguments:
  <IMAGE1>  First image path (PNG, JPEG, or QOI)
  <IMAGE2>  Second image path (PNG, JPEG, or QOI)
  [OUTPUT]  Output diff image path (optional, format detected from extension)

Options:
  -t, --threshold <THRESHOLD>  Color difference threshold (0.0-1.0) [default: 0.1]
  -a, --antialiasing           Enable anti-aliasing detection
      --diff-mask              Output only differences (transparent background)
  -c, --compression <LEVEL>    PNG compression level (0-9, 0=fastest, 9=smallest) [default: 0]
  -q, --quality <QUALITY>      JPEG quality (1-100) [default: 90]
      --output-format <FORMAT> Output format (json or text) [default: json]
  -h, --help                   Print help
  -V, --version                Print version

Supported Formats

Format	Extensions	Notes
PNG	`.png`	Lossless, supports transparency
JPEG	`.jpg`, `.jpeg`	Lossy, smaller file sizes
QOI	`.qoi`	Fast lossless, ideal for diff outputs (12x smaller than uncompressed PNG)

Input images can be mixed formats (e.g., compare PNG to JPEG). Output format is determined by the output file extension.

QOI for diff outputs: QOI excels at encoding diff images with large uniform areas, producing files 12x smaller than PNG (level 0) while being faster to encode.

Exit Codes

0 - Images are identical
1 - Images differ (includes layout/size mismatch)
2 - Error (file not found, invalid format, etc.)

Performance

Benchmarked on Apple M1 Pro with 5600x3200 4K PNG images:

Tool	Benchmark Time	vs blazediff
blazediff	~327ms	-
odiff	~1215ms	3.4x slower

Binary sizes (stripped, LTO optimized) - ~3x smaller than odiff:

Platform	blazediff	odiff
macOS ARM64	702 KB	2.2 MB
macOS x64	773 KB	2.6 MB
Linux ARM64	753 KB	2.3 MB
Linux x64	869 KB	2.9 MB
Windows ARM64	580 KB	2.4 MB
Windows x64	915 KB	3.0 MB

Algorithm

BlazeDiff uses a two-pass block-based approach with SIMD acceleration:

Cold Pass: Scans image in 8x8 blocks using 32-bit integer comparison to identify changed regions
Hot Pass: Only processes blocks marked as changed, applying YIQ perceptual color difference
SIMD: Uses NEON (ARM) or SSE4.1 (x86) for parallel pixel processing
Anti-aliasing: Implements Vysniauskas (2009) algorithm to detect AA artifacts

References

YIQ Color Space: Kotsarenko & Ramos (2009) - "Measuring perceived color difference using YIQ NTSC transmission color space"
Anti-Aliasing Detection: Vysniauskas (2009) - "Anti-aliased Pixel and Intensity Slope Detector"
Inspiration: odiff - Fast image comparison tool written in Zig

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README.md

@blazediff/core-native

Installation

API

compare(basePath, comparePath, diffOutput, options?)

interpret(image1Path, image2Path, options?)

Result Types

Usage

Programmatic API

Compare with Interpretation

Interpret Only (no diff image)

CLI Usage

CLI Options

Supported Formats

Exit Codes

Performance

Algorithm

References

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README.md

@blazediff/core-native

Installation

API

compare(basePath, comparePath, diffOutput, options?)

interpret(image1Path, image2Path, options?)

Result Types

Usage

Programmatic API

Compare with Interpretation

Interpret Only (no diff image)

CLI Usage

CLI Options

Supported Formats

Exit Codes

Performance

Algorithm

References