Source code for detectron2.evaluation.testing

# Copyright (c) Facebook, Inc. and its affiliates.
import logging
import numpy as np
import pprint
import sys
from collections.abc import Mapping





[docs]def verify_results(cfg, results): """ Args: results (OrderedDict[dict]): task_name -> {metric -> score} Returns: bool: whether the verification succeeds or not """ expected_results = cfg.TEST.EXPECTED_RESULTS if not len(expected_results): return True ok = True for task, metric, expected, tolerance in expected_results: actual = results[task].get(metric, None) if actual is None: ok = False continue if not np.isfinite(actual): ok = False continue diff = abs(actual - expected) if diff > tolerance: ok = False logger = logging.getLogger(__name__) if not ok: logger.error("Result verification failed!") logger.error("Expected Results: " + str(expected_results)) logger.error("Actual Results: " + pprint.pformat(results)) sys.exit(1) else: logger.info("Results verification passed.") return ok
def flatten_results_dict(results): """ Expand a hierarchical dict of scalars into a flat dict of scalars. If results[k1][k2][k3] = v, the returned dict will have the entry {"k1/k2/k3": v}. Args: results (dict): """ r = {} for k, v in results.items(): if isinstance(v, Mapping): v = flatten_results_dict(v) for kk, vv in v.items(): r[k + "/" + kk] = vv else: r[k] = v return r