PixelDiff

A visual image comparison tool for pixel-perfect difference detection. Designed for use with Screenshot tests.

Overview

PixelDiff is an open source GUI application for comparing two images side-by-side and highlighting pixel-level differences. It's designed for developers, designers, and QA professionals who need to visually validate changes between image versions.

Features

• Side by Side Comparison: View original and updated images simultaneously
• Difference Highlighting: Visual overlay showing exactly which pixels have changed
• Interactive Navigation: Pan and zoom to examine differences in detail
• Multiple View Modes: Toggle between previous image, updated image, and difference overlay
• Zoom to Changes: Automatically focus on areas with detected differences
• Pixel-Level Analysis: Hover over pixels to see exact color values and changes
• Transparency Support: Proper handling of images with alpha channels

Usage

Currently, you can pass in two arguments, which are two files and it compares the two:

pixel-diff file-before.png file-after.png

For example, in this repository we have two sample images to try this against:

pixel-diff src/pixel-diff/examples/image1.png src/pixel-diff/examples/image2.png

In a future version, we'll provide you the ability to compare two git branches.

View Modes

• Previous: Shows only the original image
• Diff: Highlights changed pixels in red overlay (default)
• Updated: Shows only the new image

Controls

Mouse Controls

• Click & Drag: Pan around the image
• Mouse Hover: Display pixel color information

Keyboard Shortcuts

• V: Toggle between Previous/Updated views
• + / -: Zoom in/out at cursor position

Interface Elements

• View Radio Panel: Switch between Previous, Diff, and Updated modes
• Zoom to Change Button: Automatically center on first detected difference
• Status Bar: Shows pixel information and color values

Implementation

PixelDiff is implemented in Common Lisp using the CAPI (Common Application Programmer Interface) for cross-platform GUI functionality. The core comparison algorithm performs pixel-by-pixel analysis to detect and highlight differences with sub-pixel accuracy.

License

Open source - see LICENSE file for details.