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tiff459.4 KB

Single running shoe on a plain white (tiff lzw)

The same 512x512 photograph written as tiff lzw. LZW, the TIFF compression most readers assume. Every member of this group is identical pixels, so a decoder returning different dimensions or a different pixel count has lost something rather than simply produced a different file; the 24-bit PNG in this group is lossless and is the reference the lossy members are measured against Source plate pr-shoe.

Preview of Single running shoe on a plain white (tiff lzw)

Specifications

Compression
lzw
Lossless
true
Width
512
Height
512
Variant
tiff-lzw
Source Plate
pr-shoe.png
Synthetic
true
Disclosure
AI-generated / synthetic. Not a photograph of a real person, place or event.
Schema Version
1
Alt Text
Single running shoe on a plain white studio background, soft light
Alt Text Source
prompt

Testing contract

Expected to pass
Scenario
Decode this file and the 24-bit PNG in the same group, compare dimensions and pixel count, then check the decoded properties against the ones declared in its specs.
Expected result
It decodes to 512x512 with lzw compression. The encode is lossless, so it must decode to the reference pixel for pixel. Every member of this group is the same source image, so a reader that returns different dimensions has demonstrably lost something rather than read a different file.

What is a .tiff file?

TIFF (Tagged Image File Format) is a flexible container that stores one or more raster images with a rich tag-based header describing layout, compression, and color. It supports uncompressed, LZW, and other codecs, high bit depths, multiple pages, and CMYK, making it common in publishing, scanning, and archival workflows. Its flexibility means reader support varies.

How to use this file

Use an example TIFF to test multi-page and high-bit-depth handling, tag parsing, and document-imaging or archival pipelines that must read varied compression and color models.

How to use this file for testing

“Single running shoe on a plain white (tiff lzw)” 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: 512×512. 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="pr-shoe-tiff-lzw.tiff" alt="Example image" width="640" loading="lazy">

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