Medix-AI/coqui-tts
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coqui-tts
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Uses tabs instead of columns

This commit is contained in:
Edresson Casanova 2023-11-23 17:50:41 -03:00
parent cc4f37e1b0
commit 7cc348ed76
2 changed files with 115 additions and 115 deletions
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1
TTS/demos/xtts_ft_demo/requirements.txt Normal file
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@ -0,0 +1 @@
faster_whisper

229
TTS/demos/xtts_ft_demo/xtts_demo.py
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@ -95,123 +95,46 @@ def read_logs():
with gr.Blocks() as demo:
with gr.Tab("XTTS"):
state_vars = gr.State(
state_vars = gr.State()
with gr.Tab("Data processing"):
upload_file = gr.Audio(
sources="upload",
label="Select here the audio files that you want to use for XTTS trainining !",
type="filepath",
)
with gr.Row():
with gr.Column() as col1:
upload_file = gr.Audio(
sources="upload",
label="Select here the audio files that you want to use for XTTS trainining !",
type="filepath",
)
lang = gr.Dropdown(
label="Dataset Language",
value="en",
choices=[
"en",
"es",
"fr",
"de",
"it",
"pt",
"pl",
"tr",
"ru",
"nl",
"cs",
"ar",
"zh",
"hu",
"ko",
"ja"
],
)
progress_data = gr.Label(
label="Progress:"
)
logs = gr.Textbox(
label="Logs:",
interactive=False,
)
demo.load(read_logs, None, logs, every=1)
prompt_compute_btn = gr.Button(value="Step 1 - Create dataset.")
with gr.Column() as col2:
num_epochs = gr.Slider(
label="num_epochs",
minimum=1,
maximum=100,
step=1,
value=2,# 15
)
batch_size = gr.Slider(
label="batch_size",
minimum=2,
maximum=512,
step=1,
value=15,
)
progress_train = gr.Label(
label="Progress:"
)
logs_tts_train = gr.Textbox(
label="Logs:",
interactive=False,
)
demo.load(read_logs, None, logs_tts_train, every=1)
train_btn = gr.Button(value="Step 2 - Run the training")
with gr.Column() as col3:
xtts_checkpoint = gr.Textbox(
label="XTTS checkpoint path:",
value="",
)
xtts_config = gr.Textbox(
label="XTTS config path:",
value="",
)
xtts_vocab = gr.Textbox(
label="XTTS config path:",
value="",
)
speaker_reference_audio = gr.Textbox(
label="Speaker reference audio:",
value="",
)
tts_language = gr.Dropdown(
label="Language",
value="en",
choices=[
"en",
"es",
"fr",
"de",
"it",
"pt",
"pl",
"tr",
"ru",
"nl",
"cs",
"ar",
"zh",
"hu",
"ko",
"ja",
]
)
tts_text = gr.Textbox(
label="Input Text.",
value="This model sounds really good and above all, it's reasonably fast.",
)
tts_btn = gr.Button(value="Step 3 - Inference XTTS model")
tts_output_audio = gr.Audio(label="Generated Audio.")
reference_audio = gr.Audio(label="Reference audio used.")
lang = gr.Dropdown(
label="Dataset Language",
value="en",
choices=[
"en",
"es",
"fr",
"de",
"it",
"pt",
"pl",
"tr",
"ru",
"nl",
"cs",
"ar",
"zh",
"hu",
"ko",
"ja"
],
)
progress_data = gr.Label(
label="Progress:"
)
logs = gr.Textbox(
label="Logs:",
interactive=False,
)
demo.load(read_logs, None, logs, every=1)
prompt_compute_btn = gr.Button(value="Step 1 - Create dataset.")
def preprocess_dataset(audio_path, language, state_vars, progress=gr.Progress(track_tqdm=True)):
# create a temp directory to save the dataset
out_path = tempfile.TemporaryDirectory().name
@ -240,6 +163,32 @@ with gr.Blocks() as demo:
],
)
with gr.Tab("Fine-tuning XTTS"):
num_epochs = gr.Slider(
label="num_epochs",
minimum=1,
maximum=100,
step=1,
value=2,# 15
)
batch_size = gr.Slider(
label="batch_size",
minimum=2,
maximum=512,
step=1,
value=15,
)
progress_train = gr.Label(
label="Progress:"
)
logs_tts_train = gr.Textbox(
label="Logs:",
interactive=False,
)
demo.load(read_logs, None, logs_tts_train, every=1)
train_btn = gr.Button(value="Step 2 - Run the training")
def train_model(language, num_epochs, batch_size, state_vars, output_path="./", progress=gr.Progress(track_tqdm=True)):
# state_vars = {'train_csv': '/tmp/tmprh4k_vou/metadata_train.csv', 'eval_csv': '/tmp/tmprh4k_vou/metadata_eval.csv'}
@ -257,6 +206,55 @@ with gr.Blocks() as demo:
return "Model training done!", state_vars, config_path, vocab_file, ft_xtts_checkpoint, speaker_wav
with gr.Tab("Inference"):
xtts_checkpoint = gr.Textbox(
label="XTTS checkpoint path:",
value="",
)
xtts_config = gr.Textbox(
label="XTTS config path:",
value="",
)
xtts_vocab = gr.Textbox(
label="XTTS config path:",
value="",
)
speaker_reference_audio = gr.Textbox(
label="Speaker reference audio:",
value="",
)
tts_language = gr.Dropdown(
label="Language",
value="en",
choices=[
"en",
"es",
"fr",
"de",
"it",
"pt",
"pl",
"tr",
"ru",
"nl",
"cs",
"ar",
"zh",
"hu",
"ko",
"ja",
]
)
tts_text = gr.Textbox(
label="Input Text.",
value="This model sounds really good and above all, it's reasonably fast.",
)
tts_btn = gr.Button(value="Step 3 - Inference XTTS model")
tts_output_audio = gr.Audio(label="Generated Audio.")
reference_audio = gr.Audio(label="Reference audio used.")
train_btn.click(
fn=train_model,
inputs=[
@ -268,6 +266,7 @@ with gr.Blocks() as demo:
outputs=[progress_train, state_vars, xtts_config, xtts_vocab, xtts_checkpoint, speaker_reference_audio],
)
tts_btn.click(
fn=run_tts,
inputs=[