diff --git a/tortoise/do_tts.py b/tortoise/do_tts.py index e35be36..6f2bd88 100644 --- a/tortoise/do_tts.py +++ b/tortoise/do_tts.py @@ -16,10 +16,12 @@ if __name__ == '__main__': help='How to balance vocal diversity with the quality/intelligibility of the spoken text. 0 means highly diverse voice (not recommended), 1 means maximize intellibility', default=.5) parser.add_argument('--output_path', type=str, help='Where to store outputs.', default='results/') + parser.add_argument('--model_dir', type=str, help='Where to find pretrained model checkpoints. Tortoise automatically downloads these to .models, so this' + 'should only be specified if you have custom checkpoints.', default='.models') args = parser.parse_args() os.makedirs(args.output_path, exist_ok=True) - tts = TextToSpeech() + tts = TextToSpeech(models_dir=args.model_dir) selected_voices = args.voice.split(',') for voice in selected_voices: diff --git a/tortoise/read.py b/tortoise/read.py index ce65c05..b22f62e 100644 --- a/tortoise/read.py +++ b/tortoise/read.py @@ -37,13 +37,17 @@ if __name__ == '__main__': parser.add_argument('--voice_diversity_intelligibility_slider', type=float, help='How to balance vocal diversity with the quality/intelligibility of the spoken text. 0 means highly diverse voice (not recommended), 1 means maximize intellibility', default=.5) + parser.add_argument('--model_dir', type=str, help='Where to find pretrained model checkpoints. Tortoise automatically downloads these to .models, so this' + 'should only be specified if you have custom checkpoints.', default='.models') args = parser.parse_args() + tts = TextToSpeech(models_dir=args.model_dir) outpath = args.output_path selected_voices = args.voice.split(',') regenerate = args.regenerate if regenerate is not None: regenerate = [int(e) for e in regenerate.split(',')] + for selected_voice in selected_voices: voice_outpath = os.path.join(outpath, selected_voice) os.makedirs(voice_outpath, exist_ok=True) @@ -51,7 +55,6 @@ if __name__ == '__main__': with open(args.textfile, 'r', encoding='utf-8') as f: text = ''.join([l for l in f.readlines()]) texts = split_and_recombine_text(text) - tts = TextToSpeech() if '&' in selected_voice: voice_sel = selected_voice.split('&')