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S workshop: expanded canvas

The same view of a cluttered joinery workshop bench with hand tools and sawdust, window light from the left, expanded to 704x512 - 192 pixels added to the right alone, so the original is no longer centred - so 27.3% of this frame is invented canvas. The original sits at pixels 0,0 to 512,512. Compare it INSET by 40 pixels: over that core it differs from the original by only 6.862/255, the VAE round trip, but over the whole rectangle by 7.908/255, because the pad deliberately feathers the original's outer edge into the new area. A test that expects the whole rectangle untouched fails on a correct tool.

Preview of S workshop: expanded canvas

Specifications

Pad Name
right-only
Pad Left
0
Pad Top
0
Pad Right
192
Pad Bottom
0
Original Rect
0,0,512,512
Feather Px
40
Source Plate
nss-s-workshop_00001_.png
Crop Box
374,297,886,809
Added Share
0.27273
Synthetic
true
Disclosure
Derived from an AI-generated plate. Synthetic, not a photograph of a real scene.
Schema Version
1
Width
704
Height
512
Role
result
Model
Stable Diffusion 1.5 (v1-5-pruned-emaonly-fp16)
Sampler
dpmpp_2m / karras, 25 steps, CFG 7.0, denoise 1.0
Seed
2993498715
Grow Mask By
16
Core Mad
6.862
Whole Original Mad
7.908
Alt Text
A cluttered joinery workshop bench with hand tools and sawdust, window light from the left

Testing contract

Expected to pass
Scenario
Crop this frame to the rectangle in the boundary record and compare it with the original TWICE: once over the whole rectangle, once inset by the feather.
Expected result
It is 704x512 with 27.3% of it invented canvas, and the original sits at 0,0,512,512. Inset by 40 pixels the difference is 6.862/255 - the VAE round trip, nothing else. Over the WHOLE rectangle it is 7.908/255, because the pad feathers the original's outer edge into the new area by design. A test that expects the whole rectangle untouched fails on a correct tool, and that is what these two numbers are here to prevent.

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

“S workshop: expanded canvas” 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: 704×512 · seed 2993498715 · result. 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="s-workshop-expanded.png" alt="Example image" width="640" loading="lazy">

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