Source code for datumaro.components.validator

# Copyright (C) 2021 Intel Corporation
#
# SPDX-License-Identifier: MIT

from enum import Enum, auto
from typing import Dict, List

from datumaro.components.cli_plugin import CliPlugin
from datumaro.components.dataset import IDataset


[docs]class Severity(Enum): info = auto() warning = auto() error = auto()
[docs]class TaskType(Enum): classification = auto() detection = auto() segmentation = auto()
[docs]class Validator(CliPlugin):
[docs] def validate(self, dataset: IDataset) -> Dict: """ Returns the validation results of a dataset based on task type. Args: dataset (IDataset): Dataset to be validated Raises: ValueError Returns: validation_results (dict): Dict with validation statistics, reports and summary. """ validation_results = {} if not isinstance(dataset, IDataset): raise TypeError("Invalid dataset type '%s'" % type(dataset)) # generate statistics stats = self.compute_statistics(dataset) validation_results["statistics"] = stats # generate validation reports and summary reports = self.generate_reports(stats) reports = list(map(lambda r: r.to_dict(), reports)) summary = { "errors": sum(map(lambda r: r["severity"] == "error", reports)), "warnings": sum(map(lambda r: r["severity"] == "warning", reports)), "infos": sum(map(lambda r: r["severity"] == "info", reports)), } validation_results["validation_reports"] = reports validation_results["summary"] = summary return validation_results
[docs] def compute_statistics(self, dataset: IDataset) -> Dict: """ Computes statistics of the dataset based on task type. Args: dataset (IDataset): a dataset to be validated Returns: stats (dict): A dict object containing statistics of the dataset. """ raise NotImplementedError("Must be implemented in a subclass")
[docs] def generate_reports(self, stats: Dict) -> List[Dict]: raise NotImplementedError("Must be implemented in a subclass")