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V boat harbour: clean plate (ground truth)

A clean 512x512 crop of small fishing boat moored in a harbour, morning light, taken from the published plate v-boat-harbour.png before anything was added to it. This is the ANSWER KEY for its group: the object in the source file was composited onto this image, so this is exactly what was behind it. Nothing else in the group came from a second tool's guess.

Preview of V boat harbour: clean plate (ground truth)

Specifications

Width
512
Height
512
Role
reference
Removal Kind
blob
Mask Coverage
0.05614
Source Plate
nss-v-boat-harbour_00001_.png
Crop Box
279,288,791,800
Group Members
4
Synthetic
true
Disclosure
Derived from an AI-generated plate. Synthetic, not a photograph of a real scene.
Schema Version
1
Alt Text
Small fishing boat moored in a harbour, morning light

Testing contract

Reference control
Scenario
Decode this file and the source file in the same group, then compare them pixel for pixel OUTSIDE the mask.
Expected result
They are identical outside the mask, byte for byte, because the object was composited onto this image and nothing else was touched. This is the answer key for the group: a difference here is the reader's, since there is none in the files. It is 512x512.

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

“V boat harbour: clean plate (ground truth)” is a deterministic Novus Examples fixture for Inpainting. Images with cut-out regions (rects, circles, corners, strips, irregular tears) and matching masks for testing inpainting, generative fill, content-aware fill, and object-removal pipelines.

Documented properties for this file: 512×512 · reference. 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.

Run your enhancement model on the degraded input and diff against the clean ground-truth companion in the same group; keep the documented degradation parameters and seed in your eval notes so scores are reproducible.

Code examples

<img src="v-boat-harbour-plate.png" alt="Example image" width="640" loading="lazy">

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