Everything PixellPeep can do

Powerful comparison engines, reports that actually make sense, and CI that slots into the way you already work — all in one place.

What visual regression testing catches

Functional tests answer “does the button still work?” They stay green when the button is invisible, overlapping the footer, or rendered in the wrong brand colour. Visual regression testing closes that gap: it compares a screenshot of your interface against a known-good baseline and flags what changed, so layout damage is caught before a user sees it.

That matters most when the change didn’t come from your own pull request — a dependency bump, a CSS framework upgrade, a third-party widget, or a CMS plugin update. There’s no diff to review in those cases, which is exactly when an automated screenshot check earns its keep.

How the workflow fits together

  1. Capture. Take a screenshot from your existing Playwright, Cypress or Puppeteer test, from the CLI, or by uploading images directly.
  2. Compare. The image is checked against the stored baseline using whichever algorithm suits that screen.
  3. Review. Differences are highlighted in a shared report, with an AI summary describing what actually changed.
  4. Gate. The build fails when a difference exceeds your tolerance — so regressions stop at CI, not in production.
  5. Approve. When a change is intentional, accept it and it becomes the new baseline.

Drops into the tests you already have

You don’t rewrite your suite. Install the SDK for your framework and add a snapshot call where you want a visual check — your selectors, fixtures and test logic stay exactly as they are.

import { test } from '@pixellpeep/playwright';

test('checkout page', async ({ page, pixellpeep }) => {
  await page.goto('/checkout');
  await pixellpeep.snapshot('checkout');
});

Baselines are stored centrally rather than committed to your repository, so there are no screenshots bloating git and no drift between a developer’s machine and the CI runner — the failure mode that sinks most self-hosted visual testing setups.

6 ways to compare

“Did this change?” isn’t one question. A dense data table and a marketing hero need different definitions of “different”, so you pick the engine per screen instead of compromising on a single global threshold.

1

Speed Compare

Lightning-fast exact matching - Performs pixel-by-pixel comparison for exact matching.

2

Visual Match

Human-perception based comparison - Uses Structural Similarity Index to compare images based on how humans perceive visual quality.

3

Layout Match

Structural diff with less anti-alias noise - Uses color-distribution comparison tuned for layout shifts.

4

Precision Analysis

Statistical accuracy measurement - Calculates Mean Squared Error and PSNR for precise statistical analysis.

5

Smart Detect

Intelligent duplicate detection - Uses perceptual hashing to identify similar images even with minor modifications like resizing, compression, or color adjustments.

6

Color Insight

Color distribution analysis - Analyzes and compares color distribution patterns.

6 ways to see what changed

Highlight differences however makes the most sense to you

Color Overlay - Paint differences with a colour
Bounding Boxes - Draw rectangles around changes
Heatmap - Hot = more different, cool = same
Side by Side - Both images placed next to each other
Grayscale Highlight - Grey background, coloured differences
Binary Mask - Pure black and white difference map

The full toolkit

Everything you need for serious visual testing, in one place

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Frequently asked questions

What comparison algorithms does PixellPeep offer?

PixellPeep offers 6 comparison algorithms — Speed Compare, Visual Match, Precision Analysis, Smart Detect, Color Insight, and Layout Compare — so you can tune detection between fast pixel diffs and perceptual or structural comparison.

How does PixellPeep integrate with CI/CD pipelines?

PixellPeep provides a CLI, a REST API, and native SDKs for Playwright, Cypress, and Puppeteer, so it can automatically fail builds when visual regressions are detected in GitHub Actions, GitLab CI, Jenkins, and other CI systems.

Can PixellPeep compare many images at once?

Yes. PixellPeep supports bulk CSV comparison, letting you upload hundreds of baseline/candidate image pairs and run them in a single batch.

Does PixellPeep explain visual differences?

Yes. PixellPeep includes AI-powered diff explanations that describe what changed, assign a severity rating, and suppress noise such as anti-aliasing and minor rendering differences.

See it for yourself

Spin up your first comparison in minutes and let PixellPeep handle the visual checks for you.