Validate a COCO-style dataset directory — validate

Performs existence checks for expected splits and annotations, then runs annotation diagnostics (counts, size distribution, potential issues) for each split.

Usage

validate_dataset(data_dir, quiet = FALSE)

Arguments

data_dir: Directory containing 'train' and 'valid' subdirectories, or a .tar.gz / .tgz archive thereof (e.g. the path returned by get_training_dataset()). Archives are transparently extracted into a session-scoped cache.
quiet: If TRUE, suppress CLI output while still returning diagnostics

Value

A list with validation flags, counts, size metrics, and diagnostics