experiments/STT
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Rename dataset param.

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Daniel 2020-02-06 14:47:59 +01:00
parent 8cc91fafb2
commit 726cc20586
1 changed files with 4 additions and 4 deletions
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8
util/evaluate_tools.py
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@ -55,7 +55,7 @@ def process_decode_result(item):
}) })
def calculate_and_print_report(wav_filenames, labels, decodings, losses, dataset): def calculate_and_print_report(wav_filenames, labels, decodings, losses, dataset_name):
r''' r'''
This routine will calculate and print a WER report. This routine will calculate and print a WER report.
It'll compute the `mean` WER and create ``Sample`` objects of the ``report_count`` top lowest It'll compute the `mean` WER and create ``Sample`` objects of the ``report_count`` top lowest
@ -77,17 +77,17 @@ def calculate_and_print_report(wav_filenames, labels, decodings, losses, dataset
samples.sort(key=lambda s: s.wer) samples.sort(key=lambda s: s.wer)
# Print the report # Print the report
print_report(samples, losses, samples_wer, samples_cer, dataset) print_report(samples, losses, samples_wer, samples_cer, dataset_name)
return samples return samples
def print_report(samples, losses, wer, cer, dataset): def print_report(samples, losses, wer, cer, dataset_name):
""" Print a report summary and samples of best, median and worst results """ """ Print a report summary and samples of best, median and worst results """
# Print summary # Print summary
mean_loss = np.mean(losses) mean_loss = np.mean(losses)
print('Test on %s - WER: %f, CER: %f, loss: %f' % (dataset, wer, cer, mean_loss)) print('Test on %s - WER: %f, CER: %f, loss: %f' % (dataset_name, wer, cer, mean_loss))
print('-' * 80) print('-' * 80)
best_samples = samples[:FLAGS.report_count] best_samples = samples[:FLAGS.report_count]