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Novus Examples
webp8.6 KB

Smooth abstract gradient, deep (WebP q85)

The same plate as WebP at quality 85, for format-handling coverage beside the PNG and JPEG encodings of identical pixels Plate t-grad-cool.

Preview of Smooth abstract gradient, deep (WebP q85)

Specifications

Width
1280
Height
853
Quality
85
Role
format-variant
Derived From
t-grad-cool.png
Synthetic
true
Disclosure
AI-generated / synthetic. Not a photograph of a real person, place or event.
Family
gradient
Schema Version
1
Alt Text
Smooth abstract gradient, deep teal to midnight blue, subtle noise
Alt Text Source
prompt

Testing contract

Expected to pass
Scenario
Decode this file and the lossless PNG in the same group, then compare dimensions and pixel count before comparing pixels.
Expected result
Both decode to 1280x853. This copy was encoded as WebP at quality 85, so the PIXELS differ from the reference and the GEOMETRY does not: a decoder returning different dimensions or a different pixel count has lost something rather than merely produced a smaller file.

What is a .webp file?

WebP is a modern raster format from Google offering both lossy (VP8-based) and lossless compression, with alpha transparency and animation support. It typically produces smaller files than JPEG or PNG at comparable quality. It is widely supported by current browsers.

How to use this file

Use an example WebP to test decoder support, fallback logic for older clients, and converters that translate between WebP and JPEG, PNG, or GIF while preserving alpha and animation.

How to use this file for testing

“Smooth abstract gradient, deep (WebP q85)” is a deterministic Novus Examples fixture for Media handling. Generated stills, clips and audio published in several encodings of identical content, so a media pipeline can be tested on format handling, quality loss and frame or sample extraction against a reference that is known rather than assumed.

Documented properties for this file: 1280×853 · format-variant. Compare results against paired or grouped companions on this page when present (clean↔damaged, searchable↔scanned, or format twins) so scores stay reproducible across runs.

Download the file once, keep the path stable in CI or local scripts, and treat the spec table as the contract: dimensions, seeds, field lists, and roles are intentional. Corrupt or invalid samples are labelled as such, expect parsers to fail loudly rather than silently accept them.

For image AI or enhancement tools, run the model or filter on this file and diff against the clean or ground-truth companion in the same group when available. Keep seeds and documented damage parameters in your evaluation notes so regressions are attributable.

Code examples

<img src="t-grad-cool.webp" alt="Example image" width="640" loading="lazy">

Generated by generation/comfy_media_wave.py. Free for any use, no attribution required, license.