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import gradio as gr | |
import subprocess | |
import spaces | |
def greet(name): | |
cmd = ["lsb_release", "-a"] | |
result = subprocess.run(cmd, capture_output=True) | |
print(result.stdout.decode("utf-8")) | |
cmd = ["python", "-V"] | |
result = subprocess.run(cmd, capture_output=True) | |
print(result.stdout.decode("utf-8")) | |
cmd = ["pip", "list"] | |
result = subprocess.run(cmd, capture_output=True) | |
print(result.stdout.decode("utf-8")) | |
cmd = ["nvcc", "-V"] | |
result = subprocess.run(cmd, capture_output=True) | |
print(result.stdout.decode("utf-8")) | |
return "Hello " + name + "!!" | |
demo = gr.Interface(fn=greet, inputs="text", outputs="text") | |
demo.launch() | |
def fix_face_video(input_image, input_audio): | |
# θͺΏζ»η¨ | |
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="η»ε(image)", type="filepath") | |
audio = gr.File(label="ι³ε£°(audio)", file_types=[".mp3", ".MP3"]) | |
out_video = gr.Video(label="Fix Face Video") | |
btn = gr.Button("ιδΏ‘", variant="primary") | |
title = "V_Express" | |
description = "<div style='text-align: center;'><h3>η»εγ¨ι³ε£°γ γγ§ηζγ§γγΎγγ(Using only images and audio)" | |
description += "<br>This uses the following V-Express \"https://github.com/tencent-ailab/V-Express\"</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" | |
) | |
demo.queue() | |
demo.launch(share=True, debug=True) |