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Reference validator for the VIDS (Verified Imaging Dataset Standard) specification

Project description

VIDS Validator

PyPI Python License

Reference validator for the VIDS (Verified Imaging Dataset Standard) specification.

Zero dependencies. Python 3.8+. One command.

Install

pip install vids-validator

Usage

Command line

# Validate a dataset (auto-detects profile from .vids marker)
vids-validate /path/to/dataset

# Explicit Full profile validation
vids-validate /path/to/dataset --profile full

# JSON output (for CI pipelines)
vids-validate /path/to/dataset --json

# Save report to file
vids-validate /path/to/dataset --output report.json

Python API

from vids_validator import VIDSValidator

validator = VIDSValidator("/path/to/dataset", profile="auto")
report = validator.validate()

print(report["Summary"]["Status"])  # "PASS" or "FAIL"
print(report["Summary"]["Passed"])  # number of rules passed

As a module

python -m vids_validator /path/to/dataset

What it checks

21 validation rules across 6 categories:

Category Rules Scope
Structure (S001–S006) .vids marker, dataset_description.json, participants, README, subject/session dirs All profiles
Imaging (I001–I004) NIfTI files, sidecar JSONs, valid JSON, naming convention All profiles
Annotation (A001–A005) Annotation directory, segmentation files, sidecars, provenance fields All profiles
Quality (Q001–Q003) Quality directory, quality summary, annotation agreement Full only
ML (M001–M002) ML directory, splits.json Full only
Metadata (D001) CHANGES.md All (WARN)

A dataset is compliant if and only if zero rules have FAIL status.

Profiles

  • POC (15 rules) — quick prototypes, pilots, internal research
  • Full (21 rules) — production, publications, regulatory submissions

The profile is declared in the .vids marker file at the dataset root.

Exit codes

  • 0 — validation passed
  • 1 — validation failed

Links

License

Apache License 2.0 — see LICENSE.

VIDS was created by Princeton Medical Systems and is maintained as an open community standard.

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