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L street eu: object composited in

The same view of narrow european old town street, cobbles, receding , daylight, with a foreign object composited over 9.47% of the frame as a region touching the frame, so the inpainter has no surrounding context on one side. This is the file an object-removal tool is given. Outside the mask it is byte-identical to the clean plate beside it, so any difference a tool leaves there is damage it did rather than content it was handed.

Preview of L street eu: object composited in

Specifications

Width
512
Height
512
Role
source
Removal Kind
edge
Mask Coverage
0.09467
Source Plate
nss-l-street-eu_00001_.png
Crop Box
134,171,646,683
Group Members
4
Synthetic
true
Disclosure
Derived from an AI-generated plate. Synthetic, not a photograph of a real scene.
Schema Version
1
Donor Plate
t-mesh-grad
Outside Mask Mad Vs Truth
0
Alt Text
Narrow european old town street, cobbles, receding , daylight

Testing contract

Expected to pass
Scenario
Feed this file and the mask to an object-removal tool, then compare its output against the clean plate in the same group.
Expected result
The object covers 9.47% of the frame and the clean plate is exactly what is behind it, so the removal can be SCORED rather than eyeballed. Outside the mask this file is byte-identical to that plate, which means any difference a tool leaves there is damage it did and not content it was given.

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

“L street eu: object composited in” 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 · source. 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="l-street-eu-source.png" alt="Example image" width="640" loading="lazy">

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