def model_check():
new_path = model_path
new_model = current_model
tools.printer(11, 'training', new_model)
if os.path.isdir(new_path) == True:
tools.printer(8, 'already trainings file for', new_model)
u_input = tools.get_inputs([['d', 'delete and recreate', 0],
['c', 'choose another trainings name', 0]],
'', True, True)
if u_input == 'd':
tools.delete_all(new_path)
elif u_input == 'c':
while True:
new_model = input(" new name for training\n\n--:")
new_path = current_dir + '/languages/' + str(
language_data[0]) + '/training/' + new_model + '/'
if os.path.isdir(new_path) == False:
break
elif new_model in ['q', 'Q']:
return [False]
print()
tools.printer(8, 'already trainings file for', new_model)
elif new_model in ['q', 'Q']:
return [False]
else:
return [False]
tools.create_folder(current_dir, new_model, 'create', language_data[0])
tools.printer(-3, '', '', True, new_path + 'info/training.txt', True,
False)
return [True, new_model, new_path]
def error_flag():
if sec_input == '':
tools.printer(8, 'no audio path')
array = [
tools.get_inputs([['wav_path', 'audio path from db', 1],
['audios_id', 'audio id from db', 5]], '', True,
True)
]
else:
array = [sec_input]
try:
sql_test = "select audios_id from audios where audios_id=" + str(
int(array[0])) + ""
sql = "update audios set errors=9 where wav_path=" + str(int(
array[0])) + ""
except:
sql_test = "select audios_id from audios where wav_path='" + str(
array[0]) + "'"
sql = "update audios set errors=9 where wav_path='" + str(
array[0]) + "'"
if str(array[0]) == 'unflag':
tools.printer(22, 'all errors are unflagged', array[0])
main_db[1].execute('update audios set errors=0')
main_db[0].commit()
else:
main_db[1].execute(sql_test)
test = main_db[1].fetchall()
if len(test) > 0:
tools.printer(22, 'error flagged', array[0])
main_db[1].execute(sql)
main_db[0].commit()
else:
tools.printer(9, 'not found', array[0])
def test_sentences():
if sec_input == '':
tools.printer(8, 'no test input')
array = [
tools.get_inputs([['', 'sentences or path', -1]], '', True, True)
]
if os.path.isfile(sec_input) == True:
array = tools.get_file(sec_input, True)
elif sec_input != '':
array = [sec_input]
print()
for arr in array:
cleaned = alphabet.sentences_cleaner(prepare, str(arr),
language_data[0], args.upper,
num_activ, args.lower)
if cleaned == False:
tools.printer(8, arr + '\n')
else:
tools.printer(2, arr)
tools.printer(22, cleaned + '\n')
model_path + 'info/training.txt', deepspeech_dir[1])
language_data[4].commit()
create_train_files()
elif mode == 'error':
error_flag()
elif mode == 'insert':
tools.printer(-3)
tools.printer(1, 'Inserter\n')
if sec_input == '':
tools.printer(8, 'no path selected', '')
corpus_path = tools.get_inputs([['', '', 2]], 'enter corpus path',
True, True)
else:
corpus_path = sec_input
if corpus_path != False:
tools.printer(2, 'found path', str(corpus_path))
downloader.insert_corpora(corpus_path, True, main_db,
language_data[0])
else:
tools.printer(9, 'path not found', str(corpus_path))
elif mode == 'test' or mode == 'testing':
tools.printer(-3)
tools.printer(1, 'Replacement Tester\n')
test_sentences()