Update app.py
Browse files
app.py
CHANGED
|
@@ -13,15 +13,15 @@ model_ids = [
|
|
| 13 |
for model_id in model_ids:
|
| 14 |
model_name = model_id.split('/')[-1]
|
| 15 |
snapshot_download(model_id, local_dir=f'checkpoints/{model_name}')
|
| 16 |
-
"""
|
| 17 |
-
#from TTS.tts.configs.bark_config import BarkConfig
|
| 18 |
-
#from TTS.tts.models.bark import Bark
|
| 19 |
|
| 20 |
-
|
| 21 |
-
|
| 22 |
-
#model = Bark.init_from_config(config)
|
| 23 |
-
#model.load_checkpoint(config, checkpoint_dir="checkpoints/bark", eval=True)
|
| 24 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 25 |
from TTS.api import TTS
|
| 26 |
tts = TTS("tts_models/multilingual/multi-dataset/bark", gpu=True)
|
| 27 |
|
|
@@ -87,25 +87,34 @@ def infer(prompt, input_wav_file):
|
|
| 87 |
|
| 88 |
# Print the contents
|
| 89 |
for item in contents:
|
| 90 |
-
print(item)
|
|
|
|
|
|
|
| 91 |
|
| 92 |
-
return "output.wav", f"bark_voices/{file_name}/{contents[1]}"
|
| 93 |
|
| 94 |
|
| 95 |
css = """
|
| 96 |
#col-container {max-width: 580px; margin-left: auto; margin-right: auto;}
|
|
|
|
|
|
|
|
|
|
|
|
|
| 97 |
"""
|
| 98 |
|
| 99 |
with gr.Blocks(css=css) as demo:
|
| 100 |
with gr.Column(elem_id="col-container"):
|
| 101 |
|
| 102 |
-
gr.
|
| 103 |
<h1 style="text-align: center;">Instant Voice Cloning</h1>
|
| 104 |
<p style="text-align: center;">
|
| 105 |
Clone any voice in less than 2 minutes with this <a href="https://tts.readthedocs.io/en/dev/models/bark.html" target="_blank">Coqui TSS + Bark</a> demo ! <br />
|
| 106 |
Upload a clean 20 seconds WAV file of the voice you want to clone, <br />
|
| 107 |
type your text-to-speech prompt and hit submit ! <br />
|
| 108 |
</p>
|
|
|
|
|
|
|
|
|
|
| 109 |
""")
|
| 110 |
|
| 111 |
prompt = gr.Textbox(
|
|
@@ -124,6 +133,10 @@ with gr.Blocks(css=css) as demo:
|
|
| 124 |
cloned_out = gr.Audio(
|
| 125 |
label="Text to speech output"
|
| 126 |
)
|
|
|
|
|
|
|
|
|
|
|
|
|
| 127 |
|
| 128 |
npz_file = gr.File(
|
| 129 |
label=".npz file"
|
|
@@ -137,6 +150,7 @@ with gr.Blocks(css=css) as demo:
|
|
| 137 |
],
|
| 138 |
outputs = [
|
| 139 |
cloned_out,
|
|
|
|
| 140 |
npz_file
|
| 141 |
]
|
| 142 |
)
|
|
|
|
| 13 |
for model_id in model_ids:
|
| 14 |
model_name = model_id.split('/')[-1]
|
| 15 |
snapshot_download(model_id, local_dir=f'checkpoints/{model_name}')
|
|
|
|
|
|
|
|
|
|
| 16 |
|
| 17 |
+
from TTS.tts.configs.bark_config import BarkConfig
|
| 18 |
+
from TTS.tts.models.bark import Bark
|
|
|
|
|
|
|
| 19 |
|
| 20 |
+
#os.environ['CUDA_VISIBLE_DEVICES'] = '1'
|
| 21 |
+
config = BarkConfig()
|
| 22 |
+
model = Bark.init_from_config(config)
|
| 23 |
+
model.load_checkpoint(config, checkpoint_dir="checkpoints/bark", eval=True)
|
| 24 |
+
"""
|
| 25 |
from TTS.api import TTS
|
| 26 |
tts = TTS("tts_models/multilingual/multi-dataset/bark", gpu=True)
|
| 27 |
|
|
|
|
| 87 |
|
| 88 |
# Print the contents
|
| 89 |
for item in contents:
|
| 90 |
+
print(item)
|
| 91 |
+
|
| 92 |
+
tts_video = gr.make_waveform(audio="output.wav")
|
| 93 |
|
| 94 |
+
return "output.wav", tts_video, f"bark_voices/{file_name}/{contents[1]}"
|
| 95 |
|
| 96 |
|
| 97 |
css = """
|
| 98 |
#col-container {max-width: 580px; margin-left: auto; margin-right: auto;}
|
| 99 |
+
img[src*='#center'] {
|
| 100 |
+
display: block;
|
| 101 |
+
margin: auto;
|
| 102 |
+
}
|
| 103 |
"""
|
| 104 |
|
| 105 |
with gr.Blocks(css=css) as demo:
|
| 106 |
with gr.Column(elem_id="col-container"):
|
| 107 |
|
| 108 |
+
gr.Markdown("""
|
| 109 |
<h1 style="text-align: center;">Instant Voice Cloning</h1>
|
| 110 |
<p style="text-align: center;">
|
| 111 |
Clone any voice in less than 2 minutes with this <a href="https://tts.readthedocs.io/en/dev/models/bark.html" target="_blank">Coqui TSS + Bark</a> demo ! <br />
|
| 112 |
Upload a clean 20 seconds WAV file of the voice you want to clone, <br />
|
| 113 |
type your text-to-speech prompt and hit submit ! <br />
|
| 114 |
</p>
|
| 115 |
+
|
| 116 |
+
[](https://huggingface.co/spaces/fffiloni/instant-TTS-Bark-cloning?duplicate=true)
|
| 117 |
+
|
| 118 |
""")
|
| 119 |
|
| 120 |
prompt = gr.Textbox(
|
|
|
|
| 133 |
cloned_out = gr.Audio(
|
| 134 |
label="Text to speech output"
|
| 135 |
)
|
| 136 |
+
|
| 137 |
+
video_out = gr.Video(
|
| 138 |
+
label = "Waveform video"
|
| 139 |
+
)
|
| 140 |
|
| 141 |
npz_file = gr.File(
|
| 142 |
label=".npz file"
|
|
|
|
| 150 |
],
|
| 151 |
outputs = [
|
| 152 |
cloned_out,
|
| 153 |
+
video_out,
|
| 154 |
npz_file
|
| 155 |
]
|
| 156 |
)
|