vectorize
Development benchmark

Five logos. Fifteen controlled inputs. Failures included.

This test asks a narrow question: how closely does the Vectorize prototype recover the color regions and topology of clean logo rasterizations at two sizes, plus a lightly shaded variant?

Run
Runner snapshot
344ddaf
Cases
5 logos · 15 inputs
Dataset role
Development, not independent
Method

The tracer sees only pixels.

Reference vectors are used to create and evaluate each test. They are never passed to the reconstruction pipeline.

01Raster input
Controlled Slack PNG input

Pixels only. The reference SVG is not passed to the tracer.

02Detect regions
Automatically detected color regions

Connected areas become a compact, automatic color palette.

03Trace paths
SVG paths reconstructed from the detected regionsSVG

Each region is rebuilt as scalable geometry and flat fills.

04Render & measure
99.34%region IoU Topology matched

The SVG is rendered back to pixels for the same comparison.

One clean 512px Slack run shown. The same automatic pipeline is applied to every benchmark input without manual path editing.
Visual results

Resolution is part of the result.

The left panel is the controlled raster input. The two output panels embed the generated SVG files directly—not screenshots of them—and let you download the same vectors. The 128px trace is enlarged so lost geometry remains easy to inspect.

Adidas

Lettering, sharp corners and counters

Reference source
Adidas controlled 512-pixel PNG input
Input · 512pxPNG
Adidas rendered vector output traced from the 512-pixel input
Output · 512px sourceSVG
Adidas rendered vector output traced from the 128-pixel input
Output · 128px sourceSVG

Good at 512px. At 128px the mark remains recognizable, but corners soften and the lettering loses precision.

Slack

Four colors, separated parts and curves

Reference source
Slack controlled 512-pixel PNG input
Input · 512pxPNG
Slack rendered vector output traced from the 512-pixel input
Output · 512px sourceSVG
Slack rendered vector output traced from the 128-pixel input
Output · 128px sourceSVG

Good in both clean sizes. The four regions stay separated, with less regular curves in the smaller trace.

Wikimedia

Circles, symmetry and three colors

Reference source
Wikimedia controlled 512-pixel PNG input
Input · 512pxPNG
Wikimedia rendered vector output traced from the 512-pixel input
Output · 512px sourceSVG
Wikimedia rendered vector output traced from the 128-pixel input
Output · 128px sourceSVG

Good in both sizes. At 128px, circles and hard corners show a small visible approximation.

Starbucks

Thin details and enclosed white regions

Reference source
Starbucks controlled 512-pixel PNG input
Input · 512pxPNG
Starbucks rendered vector output traced from the 512-pixel input
Output · 512px sourceSVG
Starbucks rendered vector output traced from the 128-pixel input
Output · 128px sourceSVG

The 512px result is similar but needs work in internal details. The 128px trace is not suitable for professional use.

Google 2015

Multicolor lettering and open counters

Reference source
Google 2015 controlled 512-pixel PNG input
Input · 512pxPNG
Google 2015 rendered vector output traced from the 512-pixel input
Output · 512px sourceSVG
Google 2015 rendered vector output traced from the 128-pixel input
Output · 128px sourceSVG

Good at 512px. The 128px trace stays recognizable, while stroke weight and letter geometry become less precise.

Measured results

Region overlap is a diagnostic, not a grade.

Mean color-region IoU is the intersection divided by the union of each rendered color region, averaged across colors. It is not an overall quality percentage and does not replace visual review.

Clean-input measurements by logo and source size
LogoColorsRegion IoU · 512Region IoU · 128TopologySVG · 512
Adidas198.74%94.52%Matched4,940 B
Slack499.34%97.38%Matched3,763 B
Wikimedia399.49%98.12%Matched2,269 B
Starbucks297.75%89.44%Did not match26,179 B
Google 2015496.71%88.69%Matched4,424 B

Geometry and rendering

Across clean 512px inputs, mean region IoU ranges from 96.71% to 99.49%. At 128px the range widens to 88.69%–98.12%. A high silhouette score can still conceal incorrect internal detail.

Topology

Components and holes match the reference for four of five logo families at both clean sizes. Starbucks does not match in either size; features smaller than four pixels in the 4× evaluation are ignored.

Color

Clean-input palettes are recovered exactly in these cases. On shaded inputs, the correct number of colors remains, but several representative colors become darker and white can become gray.

Complexity

The clean 512px SVGs range from 2,269 to 26,179 bytes and from 4 to 36 traced regions. This is descriptive complexity, not a smaller-is-always-better target.

What changed

The failed cases shaped the product.

The first experiment forced two colors, which failed on the one-color Adidas case and distorted multicolor palettes. The revised prototype estimates its palette, seeds disconnected regions, treats flat artwork separately and exports disconnected color shapes without a global base layer.

Starbucks at 128px improved from 71.03% to 89.44% mean region IoU, yet the face, star, hair and trademark detail remain visibly unreliable. The correct product response is to warn and review, not to call that result professional.

Decision

Promising for simple logos, incomplete for small detail.

The independent evaluation protocol is now frozen separately from this development set. The next run must use unseen source families and add real JPEG compression, opaque backgrounds and more low-resolution lettering. Until those results exist, Vectorize should keep its narrow promise and require human review.

Try the converterAbout the maker and method

The Adidas, Slack, Wikimedia, Starbucks and Google marks remain the property of their respective owners. They appear here only as attributed benchmark samples, not as Vectorize branding or endorsement.