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import gradio as gr
import os
import datetime
import inference
import spaces
example1 = ["sample_data/ref1.jpg", "sample_data/ano.mp3"]
example2 = ["sample_data/ref2.jpg", "sample_data/ano.mp3"]
@spaces.GPU(duration=120)
def fix_face_video(input_image, input_audio):
dt = datetime.datetime.now() + datetime.timedelta(hours=9)
fol_name = dt.strftime("%Y%m%d")
file_name = dt.strftime("%H%M%S")
out_video = "./output/" + fol_name+ "/fix_face_" + file_name + ".mp4"
inference.fix_face(input_image, input_audio, out_video)
return out_video
image = gr.Image(label="画像(image)", type="filepath")
audio = gr.File(label="音声(audio)", file_types=[".mp3", ".MP3"])
out_video = gr.Video(label="Fix Face Video")
btn = gr.Button("送信", variant="primary")
title = "V_Express"
description = "<div style='text-align: center;'><h3>画像と音声だけで生成できます。(Using only images and audio.)"
description += "<br>This uses the following V-Express \"https://github.com/tencent-ailab/V-Express\""
description += "<br><br>※GPU ZERO制限のため短い音声しか生成できません。(Can only generate short sounds.)</h3></div>"
demo = gr.Interface(
fn=fix_face_video,
inputs=[image, audio],
examples=[example1, example2],
outputs=[out_video],
title=title,
submit_btn=btn,
clear_btn=None,
description=description,
allow_flagging="never",
cache_examples=False
)
demo.queue()
demo.launch(share=True, debug=True)