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feat(evaluator): calculate average of metric result across all dataset #1947

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feat(evaluator): calculate average of metric result across all dataset #1947

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058d3bd
feat(evaluator): calculate average of metric overall dataset.
Jul 5, 2023
2b20d39
fix(tests): fix the tests.
Jul 5, 2023
6faeb6f
fix(multi_datasets-evaluator): return single dict.
Jul 27, 2023
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fix(multi_datasets-evaluator): return single dict.
  • Loading branch information
Sharad committed Jul 27, 2023
commit 6faeb6fb7f871449f2d8681a5fd8d7bf96acd188
11 changes: 7 additions & 4 deletions mmocr/evaluation/evaluator/multi_datasets_evaluator.py
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Original file line number Diff line number Diff line change
@@ -92,15 +92,18 @@ def evaluate(self, size: int) -> dict:
metrics_results.update(metric_results)
metric.results.clear()
if is_main_process():
averaged_results = self.average_results(metrics_results)
averaged_results = [self.average_results(metrics_results)]
else:
averaged_results = None
averaged_results = [None]

metrics_results = [metrics_results]
broadcast_object_list(metrics_results)
broadcast_object_list([averaged_results])

return metrics_results[0], averaged_results
results = {
'metric_results': metrics_results[0],
'averaged_results': averaged_results
}
return results

def average_results(self, metrics_results):
"""Compute the average of metric results across all datasets.