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import os, sys
import tempfile
import gradio as gr
from modules.text2speech import text2speech
from modules.gfpgan_inference import gfpgan
from modules.sadtalker_test import SadTalker
def get_driven_audio(audio):
if os.path.isfile(audio):
return audio
else:
save_path = tempfile.NamedTemporaryFile(
delete=False,
suffix=("." + "wav"),
)
gen_audio = text2speech(audio, save_path.name)
return gen_audio, gen_audio
def get_source_image(image):
return image
def sadtalker_demo(result_dir):
sad_talker = SadTalker()
with gr.Blocks(analytics_enabled=False) as sadtalker_interface:
with gr.Row().style(equal_height=False):
with gr.Column(variant='panel'):
with gr.Tabs(elem_id="sadtalker_source_image"):
with gr.TabItem('Upload image'):
with gr.Row():
source_image = gr.Image(label="Source image", source="upload", type="filepath").style(height=256,width=256)
with gr.Tabs(elem_id="sadtalker_driven_audio"):
with gr.TabItem('Upload audio'):
with gr.Column(variant='panel'):
driven_audio = gr.Audio(label="Input audio", source="upload", type="filepath")
# submit_audio_1 = gr.Button('Submit', variant='primary')
# submit_audio_1.click(fn=get_driven_audio, inputs=input_audio1, outputs=driven_audio)
with gr.Tabs(elem_id="sadtalker_checkbox"):
with gr.TabItem('Settings'):
with gr.Column(variant='panel'):
is_still_mode = gr.Checkbox(label="w/ Still Mode")
enhancer = gr.Checkbox(label="w/ GFPGAN as Face enhancer")
with gr.Column(variant='panel'):
gen_video = gr.Video(label="Generated video", format="mp4").style(height=256,width=256)
gen_text = gr.Textbox(visible=False)
submit = gr.Button('Generate', elem_id="sadtalker_generate", variant='primary')
submit.click(
fn=sad_talker.test,
inputs=[source_image,
driven_audio,
is_still_mode,
enhancer,
gr.Textbox(value=result_dir, visible=False)],
outputs=[gen_video, gen_text]
)
return sadtalker_interface
if __name__ == "__main__":
current_code_path = sys.argv[0]
current_root_dir = os.path.split(current_code_path)[0]
sadtalker_result_dir = os.path.join(current_root_dir, 'results', 'sadtalker')
demo = sadtalker_demo(sadtalker_result_dir)
demo.launch()
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