Black-to-White Tonal Ramp
A continuous linear greyscale ramp from black to white, useful for spotting banding and gamma issues.
Specifications
- Width
- 512
- Height
- 64
- Mode
- L (8-bit greyscale)
- Gradient
- linear 0–255
- Alt Text
- A continuous linear greyscale ramp from black to white, useful for spotting banding and gamma issues
- Alt Text Source
- description
Testing contract
Expected to pass- Scenario
- Exercise Black-to-White Tonal Ramp in its greyscale set workflow. A continuous linear greyscale ramp from black to white, useful for spotting banding and gamma issues.
- Expected result
- Decoded geometry is 512×64 pixels in L mode; frame count is 1. Declared feature checks: mode=L (8-bit greyscale); gradient=linear 0–255.
What is a .png file?
PNG (Portable Network Graphics) is a raster image format using lossless DEFLATE compression. It supports full 8- or 16-bit-per-channel truecolor, palette, and greyscale modes with an optional alpha channel, but no animation. It is the standard choice for screenshots, logos, and graphics with sharp edges or transparency.
How to use this file
Use an example PNG to test image decoders, alpha-compositing, thumbnail generators, and format converters, or to verify that a pipeline preserves transparency and color depth on round-trip.
How to use this file for testing
“Black-to-White Tonal Ramp” is a deterministic Testaroo fixture for Greyscale testing. Colour originals paired with true-greyscale conversions, grey wedges, and gradient ramps for testing desaturation and tone handling.
Documented properties for this file: 512×64. 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="tonal-ramp.png" alt="Example image" width="640" loading="lazy">Generated by generation/images_greyscale.py. Free for any use, no attribution required, license.
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