Medix-AI/coqui-tts
Medix-AI
/
coqui-tts
mirror of https://github.com/coqui-ai/TTS.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

add save audio option

This commit is contained in:
Edresson 2021-04-23 15:00:00 -03:00
parent 8228091f92
commit 20e42a3381
1 changed files with 15 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

22
TTS/bin/extract_tts_spectrograms.py
View File

@ -66,10 +66,12 @@ def set_filename(wav_path, out_path):
os.makedirs(os.path.join(out_path, "quant"), exist_ok=True)
os.makedirs(os.path.join(out_path, "mel"), exist_ok=True)
os.makedirs(os.path.join(out_path, "wav_gl"), exist_ok=True)
os.makedirs(os.path.join(out_path, "wav"), exist_ok=True)
wavq_path = os.path.join(out_path, "quant", file_name)
mel_path = os.path.join(out_path, "mel", file_name)
wav_path = os.path.join(out_path, "wav_gl", file_name+'.wav')
return file_name, wavq_path, mel_path, wav_path
wav_gl_path = os.path.join(out_path, "wav_gl", file_name+'.wav')
wav_path = os.path.join(out_path, "wav", file_name+'.wav')
return file_name, wavq_path, mel_path, wav_gl_path, wav_path
def format_data(data):
# setup input data
@ -122,7 +124,7 @@ def format_data(data):
)
@torch.no_grad()
def extract_spectrograms(data_loader, model, ap, output_path, quantized_wav=False, debug=False, metada_name="metada.txt"):
def extract_spectrograms(data_loader, model, ap, output_path, quantized_wav=False, save_audio=False, debug=False, metada_name="metada.txt"):
model.eval()
export_metadata = []
for _, data in tqdm(enumerate(data_loader), total=len(data_loader)):
@ -185,7 +187,7 @@ def extract_spectrograms(data_loader, model, ap, output_path, quantized_wav=Fals
for idx in range(text_input.shape[0]):
wav_file_path = item_idx[idx]
wav = ap.load_wav(wav_file_path)
_, wavq_path, mel_path, wav_path = set_filename(wav_file_path, output_path)
_, wavq_path, mel_path, wav_gl_path, wav_path = set_filename(wav_file_path, output_path)
# quantize and save wav
if quantized_wav:
@ -199,11 +201,13 @@ def extract_spectrograms(data_loader, model, ap, output_path, quantized_wav=Fals
np.save(mel_path, mel)
export_metadata.append([wav_file_path, mel_path])
if save_audio:
ap.save_wav(wav, wav_path)
if debug:
print("Audio for debug saved at:", wav_path)
print("Audio for debug saved at:", wav_gl_path)
wav = ap.inv_melspectrogram(mel)
ap.save_wav(wav, wav_path)
ap.save_wav(wav, wav_gl_path)
with open(os.path.join(output_path, metada_name), "w") as f:
for data in export_metadata:
@ -247,7 +251,7 @@ def main(args): # pylint: disable=redefined-outer-name
r = 1 if c.model.lower() == "glow_tts" else model.decoder.r
own_loader = setup_loader(ap, r, verbose=True)
extract_spectrograms(own_loader, model, ap, args.output_path, quantized_wav=args.quantized, debug=args.debug, metada_name="metada.txt")
extract_spectrograms(own_loader, model, ap, args.output_path, quantized_wav=args.quantized, save_audio=args.save_audio, debug=args.debug, metada_name="metada.txt")
if __name__ == "__main__":
@ -271,6 +275,10 @@ if __name__ == "__main__":
default=False,
action='store_true',
help='Save audio files for debug')
parser.add_argument('--save_audio',
default=False,
action='store_true',
help='Save audio files')
parser.add_argument('--quantized',
action='store_true',
help='Save quantized audio files')