Spaces:
Runtime error
Runtime error
File size: 3,083 Bytes
7572555 1242299 7572555 60f71bf 7572555 6b8c3fc 1e7779c 6b8c3fc 1e7779c 7572555 6b8c3fc 7572555 2c65526 7572555 2c65526 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 |
import gradio as gr
from gradio_client import Client
def get_speech(text, voice):
client = Client("https://collabora-whisperspeech.hf.space/")
result = client.predict(
text, # str in 'Enter multilingual text💬📝' Textbox component
voice, # filepath in 'Upload or Record Speaker Audio (optional)🌬️💬' Audio component
"", # str in 'alternatively, you can paste in an audio file URL:' Textbox component
14, # float (numeric value between 10 and 15) in 'Tempo (in characters per second)' Slider component
api_name="/whisper_speech_demo"
)
print(result)
return result
def get_dreamtalk(image_in, speech):
client = Client("https://fffiloni-dreamtalk.hf.space/")
result = client.predict(
speech, # filepath in 'Audio input' Audio component
image_in, # filepath in 'Image' Image component
"M030_front_neutral_level1_001.mat", # Literal['M030_front_angry_level3_001.mat', 'M030_front_contempt_level3_001.mat', 'M030_front_disgusted_level3_001.mat', 'M030_front_fear_level3_001.mat', 'M030_front_happy_level3_001.mat', 'M030_front_neutral_level1_001.mat', 'M030_front_sad_level3_001.mat', 'M030_front_surprised_level3_001.mat', 'W009_front_angry_level3_001.mat', 'W009_front_contempt_level3_001.mat', 'W009_front_disgusted_level3_001.mat', 'W009_front_fear_level3_001.mat', 'W009_front_happy_level3_001.mat', 'W009_front_neutral_level1_001.mat', 'W009_front_sad_level3_001.mat', 'W009_front_surprised_level3_001.mat', 'W011_front_angry_level3_001.mat', 'W011_front_contempt_level3_001.mat', 'W011_front_disgusted_level3_001.mat', 'W011_front_fear_level3_001.mat', 'W011_front_happy_level3_001.mat', 'W011_front_neutral_level1_001.mat', 'W011_front_sad_level3_001.mat', 'W011_front_surprised_level3_001.mat'] in 'emotional style' Dropdown component
api_name="/infer"
)
print(result)
return result['video']
def pipe (text, voice, image_in):
speech = get_speech(text, voice)
try:
video = get_dreamtalk(image_in, speech)
except:
raise gr.Error('Could not load DreamTalk, please try again later')
return video
with gr.Blocks() as demo:
with gr.Column():
gr.HTML("""
<h2 style="text-align: center;">
Whisper Speech X Dreamtalk
</h2>
<p style="text-align: center;"></p>
""")
with gr.Row():
with gr.Column():
image_in = gr.Image(label="Portrait IN", type="filepath", value="einstein.jpg")
with gr.Column():
voice = gr.Audio(type="filepath", label="Upload or Record Speaker audio (Optional)")
text = gr.Textbox(label="text")
submit_btn = gr.Button('Submit')
with gr.Column():
video_o = gr.Video(label="Video result")
submit_btn.click(
fn = pipe,
inputs = [
text, voice, image_in
],
outputs = [
video_o
],
concurrency_limit = 3
)
demo.queue(max_size=10).launch(show_error=True, show_api=False) |