"Data modules, datasets, dataclasses, model registry, constructors,
Scanned 9/8/2026
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---
name: "data-and-models"
description: "Data modules, datasets, dataclasses, model registry, constructors,
feature extraction, and custom data-layout guidance."
metadata:
disco-role: operating
disable-model-invocation: true
license: Apache 2.0
---
# Data and Models
Use this sub-skill for anomalib questions about choosing, configuring, and debugging data or model entry points.
## Use this when the user asks about
- Image datamodules: `MVTecAD`, `Folder`, `Tabular`, `PredictDataset`
- Video datamodules: `Avenue`, `ShanghaiTech`, `UCSDped`
- Depth datamodules: `MVTec3D`, `Folder3D`, `ADAM3D`
- Dataclasses and batch shapes: `ImageItem`, `VideoItem`, `DepthItem`, and their batch types
- Model registry and lookup: `get_model`, `list_models`, `get_datamodule`
- Core model constructors: `Padim`, `Patchcore`, `EfficientAd`, `AiVad`, `Fuvas`
- Backbone / layer selection and feature extraction with `TimmFeatureExtractor`
- Custom folder, tabular, video, or depth data layouts
- Unknown model names, registry lookup errors, or feature-layer mismatches
## Do not use this when the user asks about
- Engine fit / validate / test / predict execution
- Export, deployment, or inference packaging
- Pipeline orchestration or benchmark automation
- CLI install mechanics
- Studio application content
## Fast routing
- Data layout, dataclasses, and config shapes: [references/data-and-models.md](references/data-and-models.md)
- Model selection, constructors, and feature extraction: [references/model-overview.md](references/model-overview.md)
- Failure modes, optional dependencies, and lookup errors: [references/troubleshooting.md](references/troubleshooting.md)
- Lightweight discovery / validation helper: [scripts/inspect_data_models.py](scripts/inspect_data_models.py)
## Primary source surfaces
- `src/anomalib/data/**`
- `src/anomalib/models/**`
- `docs/source/markdown/guides/how_to/data/**`
- `docs/source/markdown/guides/how_to/models/**`
- `docs/source/markdown/guides/reference/data/index.md`
- `docs/source/markdown/guides/reference/models/index.md`
- `examples/api/02_data/**`
- `examples/api/03_models/**`
- `tests/unit/data/**`
- `tests/unit/models/**`
- `tests/integration/model/test_models.py`
## Helpful mental model
1. Choose the data family first: image, video, depth, custom folder, or tabular.
2. Confirm the datamodule layout and split mode before choosing a model.
3. For backbone-based image models, confirm the backbone / layer names before instantiating.
4. For video models, confirm clip length and target frame semantics.
5. If the user needs a quick sanity check, use the bundled inspection script instead of guessing.
## Discovery and validation script
The bundled script can:
- list key datamodule and model constructors
- print the current `list_models()` registry
- validate custom folder layouts by calling anomalib's own folder parser
- validate custom tabular layouts with anomalib-style rules
Example invocations:
```bash
python scripts/inspect_data_models.py list
python scripts/inspect_data_models.py check-folder --help
python scripts/inspect_data_models.py check-tabular --help
```
## Notes
- Prefer the exact public constructors and helpers documented in the bundled references.
- Keep training, export, and pipeline questions routed to the other sub-skills.
- Use the bundled references for exact argument defaults, path rules, and dependency caveats.
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
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