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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('An error occurred while loading: Image may not contain any face')
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="./einstein1.jpg")
with gr.Column():
voice = gr.Audio(type="filepath", label="Upload or Record Speaker audio (Optional voice cloning)")
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) |