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Fix import_cv2.py binary file + permissions

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This commit is contained in:
Quentin Brunet 2019-03-03 17:27:50 +01:00
parent 3c3401ec60
commit 179ba1b533
1 changed files with 11 additions and 9 deletions
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20
bin/import_cv2.py Normal file → Executable file
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@ -20,16 +20,16 @@ from util.downloader import SIMPLE_BAR
'''
Broadly speaking, this script takes the audio downloaded from Common Voice
for a certain language, in addition to the *.tsv files output by CorporaCeator,
for a certain language, in addition to the *.tsv files output by CorporaCreator,
and the script formats the data and transcripts to be in a state usable by
DeepSpeech.py
Usage:
$ python3 import_cv2.py /path/to/audio/data_dir /path/to/tsv_dir
Input:
Input:
(1) audio_dir (string) path to dir of audio downloaded from Common Voice
(2) tsv_dir (string) path to dir containing {train,test,dev}.tsv files
(2) tsv_dir (string) path to dir containing {train,test,dev}.tsv files
which were generated by CorporaCreator
Ouput:
@ -53,23 +53,25 @@ def _preprocess_data(audio_dir, tsv_dir):
def _maybe_convert_set(audio_dir, input_tsv):
output_csv = path.join(audio_dir,os.path.split(input_tsv)[-1].replace('tsv', 'csv'))
print("Saving new DeepSpeech-formatted CSV file to: ", output_csv)
# Get audiofile path and transcript for each sentence in tsv
samples = []
with open(input_tsv) as input_tsv_file:
reader = csv.DictReader(input_tsv_file, delimiter='\t')
for row in reader:
samples.append((row['path'], row['sentence']))
# Keep track of how many samples are good vs. problematic
counter = { 'all': 0, 'too_short': 0, 'too_long': 0 }
lock = RLock()
num_samples = len(samples)
rows = []
def one_sample(sample):
""" Take a audio file, and optionally convert it to 16kHz WAV """
mp3_filename = path.join(audio_dir, sample[0])
if not path.splitext(mp3_filename.lower())[1] == '.mp3':
mp3_filename += ".mp3"
# Storing wav files next to the mp3 ones - just with a different suffix
wav_filename = path.splitext(mp3_filename)[0] + ".wav"
_maybe_convert_wav(mp3_filename, wav_filename)
@ -86,7 +88,7 @@ def _maybe_convert_set(audio_dir, input_tsv):
# This one is good - keep it for the target CSV
rows.append((wav_filename, file_size, sample[1]))
counter['all'] += 1
print("Importing mp3 files...")
pool = Pool(cpu_count())
bar = progressbar.ProgressBar(max_value=num_samples, widgets=SIMPLE_BAR)
@ -95,7 +97,7 @@ def _maybe_convert_set(audio_dir, input_tsv):
bar.update(num_samples)
pool.close()
pool.join()
with open(output_csv, 'w') as output_csv_file:
print('Writing CSV file for DeepSpeech.py as: ', output_csv)
writer = csv.DictWriter(output_csv_file, fieldnames=FIELDNAMES)
@ -103,7 +105,7 @@ def _maybe_convert_set(audio_dir, input_tsv):
bar = progressbar.ProgressBar(max_value=len(rows), widgets=SIMPLE_BAR)
for filename, file_size, transcript in bar(rows):
writer.writerow({ 'wav_filename': filename, 'wav_filesize': file_size, 'transcript': transcript })
print('Imported %d samples.' % (counter['all'] - counter['too_short'] - counter['too_long']))
if counter['too_short'] > 0:
print('Skipped %d samples that were too short to match the transcript.' % counter['too_short'])