Novus Examples, Real, documented example files for testing

Denoise Input: gradient-sky, Multiplicative speckle

Multiplicative speckle applied to the gradient-sky base plate with seed 9102. Multiplicative rather than additive noise, so its amplitude scales with local brightness: the pattern seen in ultrasound and radar. Additive-noise models systematically under-correct highlights. Paired with the clean ground truth in this group, so denoiser output can be scored numerically. Encoded at CRF 24 rather than 19: random noise is incompressible, and at this amplitude the codec's own artefacts sit far below the noise floor, so a coarser quantiser saves several megabytes without affecting any measurement.

File: MP4 · Denoise · 640x360
Use case: Video denoiseVideo QA· Conversion set

Denoise Input: gradient-sky, Poisson shot noise

Poisson shot noise applied to the gradient-sky base plate with seed 9119. Photon shot noise, signal-dependent and the physically correct model for low-light capture. Dark regions are proportionally far noisier than bright ones. Paired with the clean ground truth in this group, so denoiser output can be scored numerically. Encoded at CRF 24 rather than 19: random noise is incompressible, and at this amplitude the codec's own artefacts sit far below the noise floor, so a coarser quantiser saves several megabytes without affecting any measurement.

File: MP4 · Denoise · 640x360
Use case: Video denoiseVideo QA· Conversion set

Denoise Input: gradient-sky, Salt and pepper 2%

Salt and pepper 2% applied to the gradient-sky base plate with seed 9068. Two per cent of pixels forced to pure black or white: impulse noise from sensor faults and transmission errors. Defeats Gaussian-assuming filters, which smear each spike instead of rejecting it. Paired with the clean ground truth in this group, so denoiser output can be scored numerically. Encoded at CRF 19, where the light noise could otherwise be confused with compression artefacts.

File: MP4 · Denoise · 640x360
Use case: Video denoiseVideo QA· Conversion set

Denoise Input: gradient-sky, Salt and pepper 8%

Salt and pepper 8% applied to the gradient-sky base plate with seed 9085. Dense impulse noise. A median filter handles this trivially and a Gaussian one cannot, so it separates the two families of denoiser immediately. Paired with the clean ground truth in this group, so denoiser output can be scored numerically. Encoded at CRF 24 rather than 19: random noise is incompressible, and at this amplitude the codec's own artefacts sit far below the noise floor, so a coarser quantiser saves several megabytes without affecting any measurement.

File: MP4 · Denoise · 640x360
Use case: Video denoiseVideo QA· Conversion set

Denoise Input: pan-city, Gaussian σ=15

Gaussian σ=15 applied to the pan-city base plate with seed 9017. Moderate Gaussian noise, roughly a mid-ISO handheld shot. The level most denoise benchmarks use. Paired with the clean ground truth in this group, so denoiser output can be scored numerically. Encoded at CRF 19, where the light noise could otherwise be confused with compression artefacts.

File: MP4 · Denoise · 640x360
Use case: Video denoiseVideo QA· Conversion set

Denoise Input: pan-city, Gaussian σ=30

Gaussian σ=30 applied to the pan-city base plate with seed 9034. Heavy Gaussian noise where fine detail and noise overlap in amplitude, so recovery requires temporal information rather than spatial smoothing alone. Paired with the clean ground truth in this group, so denoiser output can be scored numerically. Encoded at CRF 24 rather than 19: random noise is incompressible, and at this amplitude the codec's own artefacts sit far below the noise floor, so a coarser quantiser saves several megabytes without affecting any measurement.

File: MP4 · Denoise · 640x360
Use case: Video denoiseVideo QA· Conversion set

Denoise Input: pan-city, Gaussian σ=5

Gaussian σ=5 applied to the pan-city base plate with seed 9000. Light sensor noise: the level a modern camera produces at base ISO. Subtle enough that an over-aggressive denoiser does more damage than the noise did. Paired with the clean ground truth in this group, so denoiser output can be scored numerically. Encoded at CRF 19, where the light noise could otherwise be confused with compression artefacts.

File: MP4 · Denoise · 640x360
Use case: Video denoiseVideo QA· Conversion set

Denoise Input: pan-city, Gaussian σ=50

Gaussian σ=50 applied to the pan-city base plate with seed 9051. Severe noise approaching the signal level. Included as the failure case: most denoisers hallucinate structure here, which is exactly what the paired reference exposes. Paired with the clean ground truth in this group, so denoiser output can be scored numerically. Encoded at CRF 24 rather than 19: random noise is incompressible, and at this amplitude the codec's own artefacts sit far below the noise floor, so a coarser quantiser saves several megabytes without affecting any measurement.

File: MP4 · Denoise · 640x360
Use case: Video denoiseVideo QA· Conversion set

Denoise Input: pan-city, Multiplicative speckle

Multiplicative speckle applied to the pan-city base plate with seed 9102. Multiplicative rather than additive noise, so its amplitude scales with local brightness: the pattern seen in ultrasound and radar. Additive-noise models systematically under-correct highlights. Paired with the clean ground truth in this group, so denoiser output can be scored numerically. Encoded at CRF 24 rather than 19: random noise is incompressible, and at this amplitude the codec's own artefacts sit far below the noise floor, so a coarser quantiser saves several megabytes without affecting any measurement.

File: MP4 · Denoise · 640x360
Use case: Video denoiseVideo QA· Conversion set

Denoise Input: pan-city, Poisson shot noise

Poisson shot noise applied to the pan-city base plate with seed 9119. Photon shot noise, signal-dependent and the physically correct model for low-light capture. Dark regions are proportionally far noisier than bright ones. Paired with the clean ground truth in this group, so denoiser output can be scored numerically. Encoded at CRF 24 rather than 19: random noise is incompressible, and at this amplitude the codec's own artefacts sit far below the noise floor, so a coarser quantiser saves several megabytes without affecting any measurement.

File: MP4 · Denoise · 640x360
Use case: Video denoiseVideo QA· Conversion set

Denoise Input: pan-city, Salt and pepper 2%

Salt and pepper 2% applied to the pan-city base plate with seed 9068. Two per cent of pixels forced to pure black or white: impulse noise from sensor faults and transmission errors. Defeats Gaussian-assuming filters, which smear each spike instead of rejecting it. Paired with the clean ground truth in this group, so denoiser output can be scored numerically. Encoded at CRF 19, where the light noise could otherwise be confused with compression artefacts.

File: MP4 · Denoise · 640x360
Use case: Video denoiseVideo QA· Conversion set

Denoise Input: pan-city, Salt and pepper 8%

Salt and pepper 8% applied to the pan-city base plate with seed 9085. Dense impulse noise. A median filter handles this trivially and a Gaussian one cannot, so it separates the two families of denoiser immediately. Paired with the clean ground truth in this group, so denoiser output can be scored numerically. Encoded at CRF 24 rather than 19: random noise is incompressible, and at this amplitude the codec's own artefacts sit far below the noise floor, so a coarser quantiser saves several megabytes without affecting any measurement.

File: MP4 · Denoise · 640x360
Use case: Video denoiseVideo QA· Conversion set

Dependency Alerts Feed (JSON)

The shape a hosted dependency-alert API returns: alerts with lifecycle state, a nested advisory, a patched-version pointer and an explicitly null dismissed_reason on the alerts that were not dismissed. Advisory identifiers use the invented NOVUS-SAMPLE namespace with SAMPLE-CVE aliases; no identifier here refers to a published CVE, GHSA or OSV record, and no package named exists.

File: JSON · Vulnerability
Use case: JSON parsingAPI testing+1· Conversion set

Dependency Graph (GraphML)

The dependency graph in GraphML, with typed attribute keys for node version, licence and depth and for edge range: the interchange format graph databases and analysis tools import. Every package, version, hash and licence is fictional: the tree describes nothing real.

File: GRAPHML · Graphs
Use case: Graph dataConversion testing+1· Conversion set

Dependency Graph (Mermaid Flowchart)

The dependency graph as Mermaid, for embedding in Markdown documentation, labelled edges carry the declared range and a classDef highlights the two diamond joins. Every package, version, hash and licence is fictional: the tree describes nothing real.

File: MMD · Graphs
Use case: Graph dataConversion testing+1· Conversion set

Dependency Graph With a Cycle (Graphviz DOT)

The cyclic plugin graph as DOT, with the three cycle edges highlighted. Graphviz renders it happily, which is exactly why a topological sort must be the thing that rejects it. Every package, version, hash and licence is fictional: the tree describes nothing real.

File: DOT · Graphs
Use case: Graph dataError handling+1· Paired fixture

Dependency Graph With a Cycle (JSON)

A dependency graph containing a genuine three-node cycle between fictional plugins: the fixture that makes a naive recursive walker hang or blow the stack, with the cycle path stated so the expected answer is unambiguous. Every package, version, hash and licence is fictional: the tree describes nothing real.

File: JSON · Graphs
Use case: JSON parsingGraph data+1· Paired fixture

Dependency Graph With Diamond Dependencies (JSON)

An explicit node/edge dependency graph with in-degree, out-degree and depth precomputed, plus a diamonds array naming the two shared nodes and their parents: the reference answer for any graph builder run against the SBOMs and lockfiles here. Every package, version, hash and licence is fictional: the tree describes nothing real.

File: JSON · Graphs
Use case: JSON parsingGraph data+1· Paired fixture

Dependency Graph With Diamonds (Graphviz DOT)

The same diamond graph as Graphviz DOT, with edge labels carrying the declared semver range and the two diamond joins filled, renderable to SVG and diffable against the JSON twin. Every package, version, hash and licence is fictional: the tree describes nothing real.

File: DOT · Graphs
Use case: Graph dataConversion testing+1· Paired fixture

Dependent Select Lists (HTML)

A country list that rewrites a region list in the browser. The regions live in a script rather than the markup, so a scraper that reads the shipped HTML sees an empty second list and one that drives a real browser sees four options.

File: HTML · Shipping · 4 fields
Use case: Form testingForm parsing+3

Depth Ground Truth: Layer Depth Map

The depth map for the parallax plate, encoded brighter-is-nearer across three layers. These values are not an estimate: they are derived from the layer velocities the generator used, so the depth ordering is exact by construction. Relative depth is what matters here: the layers move at 0.6, 2.4 and 6.0 pixels per frame, a 1 : 4 : 10 ratio.

File: MP4 · Depth · 640x360
Use case: Depth from videoVideo QA· Conversion set

Depth Input: Three-Layer Parallax Scene

Three planes translating at 0.6, 2.4 and 6.0 pixels per frame, a 1 : 4 : 10 velocity ratio that defines their relative depth by motion alone. There are no pictorial depth cues to fall back on: no perspective convergence, no shading, no familiar object sizes. A monocular depth model that has learned pictorial cues rather than motion parallax will do poorly here, which is precisely what makes the fixture informative.

File: MP4 · Depth · 640x360
Use case: Depth from videoFrame interpolation+1· Conversion set

Detached Signature, ASCII Armor: SAMPLE Shape

An ASCII-armored detached signature block of the shape that accompanies a SHA256SUMS file. It is a SAMPLE placeholder, not a valid OpenPGP signature: armor detectors will find it, verifiers must reject it. Signatures, key ids and certificates here are SAMPLE placeholders: the base64 decodes to the words 'SAMPLE SIGNATURE', so verification must fail. Nothing here is cryptographically valid and no key material is real.

File: TXT · Provenance
Use case: Config parsingCertificate & key testing+1· Conversion set

Detection Annotations: Aerial COCO (JSON)

COCO JSON with bounding boxes and polygon segmentation for the aerial scene.

File: JSON · Vision
Use case: Computer visionML training data+1

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