Matting — Soft Edge Blob Soft Alpha (288px)
Soft-alpha cut-out (soft edges: soft-edge-blob) for alpha-matting / background-removal quality tests.
Specifications
- Width
- 288
- Height
- 288
- Mode
- RGBA
- Edge
- soft
- Role
- soft alpha
- Seed
- 1803
Testing contract
Expected to pass- Scenario
- Exercise Matting — Soft Edge Blob Soft Alpha (288px) in its matting set workflow. Soft-alpha cut-out (soft edges: soft-edge-blob) for alpha-matting / background-removal quality tests.
- Expected result
- Decoded geometry is 288×288 pixels in RGBA mode; frame count is 1. Declared feature checks: mode=RGBA; edge=soft; role=soft alpha. The declared comparison counterpart is img-we-matte-soft-edge-blob-rgb; preserve the stated difference instead of expecting the container bytes to match.
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
“Matting — Soft Edge Blob Soft Alpha (288px)” is a deterministic Novus Examples fixture for Image matting, Computer vision. Hair/fur-like soft alpha composites and trimap-style inputs for matting and refined background-removal tools.
Documented properties for this file: 288×288 · seed 1803 · soft alpha. 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.
Use the RGB input with its mask or soft-alpha companion. Class IDs and edge kinds are documented in specs, score IoU or boundary error against that ground truth, not a hand label.
Code examples
<img src="soft-edge-blob-alpha.png" alt="Example image" width="640" loading="lazy">Related files
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Generated by generation/images_wave_e.py. Free for any use, no attribution required, license.