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Portrait-Animation
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import gradio as gr
import os
import numpy as np
from pydub import AudioSegment
import hashlib
from sonic import Sonic

cmd = 'python3 -m pip install "huggingface_hub[cli]"; \
huggingface-cli download LeonJoe13/Sonic --local-dir  checkpoints; \
huggingface-cli download stabilityai/stable-video-diffusion-img2vid-xt --local-dir  checkpoints/stable-video-diffusion-img2vid-xt; \
huggingface-cli download openai/whisper-tiny --local-dir checkpoints/whisper-tiny'
os.system(cmd)


pipe = Sonic(0)

def get_md5(content):
    md5hash = hashlib.md5(content)
    md5 = md5hash.hexdigest()
    return md5

def get_video_res(img_path, audio_path, res_video_path, dynamic_scale=1.0):

    expand_ratio = 0.5
    min_resolution = 512
    inference_steps = 25

    face_info = pipe.preprocess(img_path, expand_ratio=expand_ratio)
    print(face_info)
    if face_info['face_num'] > 0:
        crop_image_path = img_path + '.crop.png'
        pipe.crop_image(img_path, crop_image_path, face_info['crop_bbox'])
        img_path = crop_image_path
        os.makedirs(os.path.dirname(res_video_path), exist_ok=True)
        pipe.process(img_path, audio_path, res_video_path, min_resolution=min_resolution, inference_steps=inference_steps, dynamic_scale=dynamic_scale)
    else:
        return -1
tmp_path = './tmp_path/'
res_path = './res_path/'
os.makedirs(tmp_path,exist_ok=1)
os.makedirs(res_path,exist_ok=1)

def process_sonic(image,audio,s0):
    img_md5= get_md5(np.array(image))
    audio_md5 = get_md5(audio[1])
    print(img_md5,audio_md5)
    sampling_rate, arr = audio[:2]
    if len(arr.shape)==1:
        arr = arr[:,None]
    audio = AudioSegment(
        arr.tobytes(),
        frame_rate=sampling_rate,
        sample_width=arr.dtype.itemsize,
        channels=arr.shape[1]
    )
    audio = audio.set_frame_rate(sampling_rate)
    image_path = os.path.abspath(tmp_path+'{0}.png'.format(img_md5))
    audio_path = os.path.abspath(tmp_path+'{0}.wav'.format(audio_md5))
    if not os.path.exists(image_path):
        image.save(image_path)
    if not os.path.exists(audio_path):
        audio.export(audio_path, format="wav")
    res_video_path = os.path.abspath(res_path+f'{img_md5}_{audio_md5}_{s0}.mp4')
    if os.path.exists(res_video_path):
        return res_video_path
    else:
        get_video_res(image_path, audio_path, res_video_path,s0)
    return res_video_path
    
inputs = [
    gr.Image(type='pil',label="Upload Image"),
    gr.Audio(label="Upload Audio"),
    gr.Slider(0.5, 2.0, value=1.0, step=0.1, label="Dynamic scale", info="Increase/decrease to obtain more/less movements"),
]
outputs = gr.Video(label="output.mp4")


html_description = """
<div style="display: flex; justify-content: center; align-items: center;">
  <a href="https://github.com/jixiaozhong/Sonic.git" style="margin: 0 2px;">
    <img src='https://img.shields.io/badge/GitHub-Repo-blue?style=flat&logo=GitHub' alt='GitHub'>
  </a>
  <a href="https://arxiv.org/pdf/2411.16331" style="margin: 0 2px;">
    <img src='https://img.shields.io/badge/arXiv-2411.16331-red?style=flat&logo=arXiv&logoColor=red' alt='arxiv'>
  </a>
  <a href='https://jixiaozhong.github.io/Sonic/' style="margin: 0 2px;">
    <img src='https://img.shields.io/badge/Webpage-Project-silver?style=flat&logo=&logoColor=orange' alt='webpage'>
  </a>
  <a href="https://github.com/jixiaozhong/Sonic/blob/main/LICENSE" style="margin: 0 2px;">
    <img src='https://img.shields.io/badge/License-CC BY--NC--SA--4.0-lightgreen?style=flat&logo=Lisence' alt='License'>
  </a>
</div>

The demo can only be used for <b>Non-commercial Use</b>.
<br>If you like our work, please star <a href='https://jixiaozhong.github.io/Sonic/' style="margin: 0 2px;">Sonic</a>.
<br>Note: Audio longer than 10s will be truncated due to computing resources.
"""
TAIL = """
<div style="display: flex; justify-content: center; align-items: center;">
<a href="https://clustrmaps.com/site/1c38t"  title="ClustrMaps"><img src="//www.clustrmaps.com/map_v2.png?d=BI2nzSldyixPC88l8Kev4wjjqsU4IOk7gcvpOijolGI&cl=ffffff" /></a>
</div>
"""

def get_example():
    return [
        ["examples/image/female_diaosu.png", "examples/wav/sing_female_rap_10s.MP3", 1.0],
        ["examples/image/hair.png", "examples/wav/sing_female_10s.wav", 1.0],
        ["examples/image/anime1.png", "examples/wav/talk_female_english_10s.MP3", 1.0],
        ["examples/image/leonnado.jpg", "examples/wav/talk_male_law_10s.wav", 1.0],
        
    ]

with gr.Blocks(title="Sonic") as demo:
    gr.Interface(fn=process_sonic, inputs=inputs, outputs=outputs, title="Sonic: Shifting Focus to Global Audio Perception in Portrait Animation", description=html_description)
    gr.Examples(
        examples=get_example(),
        fn=process_sonic,
        inputs=inputs,
        outputs=outputs,
        cache_examples=False,)
    gr.Markdown(TAIL)
    
demo.launch(server_name='0.0.0.0', server_port=8081, share=True, enable_queue=True)