aiavatartest / scripts /extension.py
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import os, sys
from pathlib import Path
import tempfile
import gradio as gr
from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call
from modules.shared import opts, OptionInfo
from modules import shared, paths, script_callbacks
import launch
import glob
from huggingface_hub import snapshot_download
def check_all_files(current_dir):
kv = {
"auido2exp_00300-model.pth": "audio2exp",
"auido2pose_00140-model.pth": "audio2pose",
"epoch_20.pth": "face_recon",
"facevid2vid_00189-model.pth.tar": "face-render",
"mapping_00109-model.pth.tar" : "mapping-109" ,
"mapping_00229-model.pth.tar" : "mapping-229" ,
"wav2lip.pth": "wav2lip",
"shape_predictor_68_face_landmarks.dat": "dlib",
}
if not os.path.isdir(current_dir):
return False
dirs = os.listdir(current_dir)
for f in dirs:
if f in kv.keys():
del kv[f]
return len(kv.keys()) == 0
def download_model(local_dir='./checkpoints'):
REPO_ID = 'vinthony/SadTalker'
snapshot_download(repo_id=REPO_ID, local_dir=local_dir, local_dir_use_symlinks=False)
def get_source_image(image):
return image
def get_img_from_txt2img(x):
talker_path = Path(paths.script_path) / "outputs"
imgs_from_txt_dir = str(talker_path / "txt2img-images/")
imgs = glob.glob(imgs_from_txt_dir+'/*/*.png')
imgs.sort(key=lambda x:os.path.getmtime(os.path.join(imgs_from_txt_dir, x)))
img_from_txt_path = os.path.join(imgs_from_txt_dir, imgs[-1])
return img_from_txt_path, img_from_txt_path
def get_img_from_img2img(x):
talker_path = Path(paths.script_path) / "outputs"
imgs_from_img_dir = str(talker_path / "img2img-images/")
imgs = glob.glob(imgs_from_img_dir+'/*/*.png')
imgs.sort(key=lambda x:os.path.getmtime(os.path.join(imgs_from_img_dir, x)))
img_from_img_path = os.path.join(imgs_from_img_dir, imgs[-1])
return img_from_img_path, img_from_img_path
def get_default_checkpoint_path():
# check the path of models/checkpoints and extensions/
checkpoint_path = Path(paths.script_path) / "models"/ "SadTalker"
extension_checkpoint_path = Path(paths.script_path) / "extensions"/ "SadTalker" / "checkpoints"
if check_all_files(checkpoint_path):
# print('founding sadtalker checkpoint in ' + str(checkpoint_path))
return checkpoint_path
if check_all_files(extension_checkpoint_path):
# print('founding sadtalker checkpoint in ' + str(extension_checkpoint_path))
return extension_checkpoint_path
return None
def install():
kv = {
"face_alignment": "face-alignment==1.3.5",
"imageio": "imageio==2.19.3",
"imageio_ffmpeg": "imageio-ffmpeg==0.4.7",
"librosa":"librosa==0.8.0",
"pydub":"pydub==0.25.1",
"scipy":"scipy==1.8.1",
"tqdm": "tqdm",
"yacs":"yacs==0.1.8",
"yaml": "pyyaml",
"av":"av",
"gfpgan": "gfpgan",
}
if 'darwin' in sys.platform:
kv['dlib'] = "dlib"
else:
kv['dlib'] = 'dlib-bin'
for k,v in kv.items():
if not launch.is_installed(k):
print(k, launch.is_installed(k))
launch.run_pip("install "+ v, "requirements for SadTalker")
if os.getenv('SADTALKER_CHECKPOINTS'):
print('load Sadtalker Checkpoints from '+ os.getenv('SADTALKER_CHECKPOINTS'))
elif get_default_checkpoint_path() is not None:
os.environ['SADTALKER_CHECKPOINTS'] = str(get_default_checkpoint_path())
else:
print(
""""
SadTalker will not support download all the files from hugging face, which will take a long time.
please manually set the SADTALKER_CHECKPOINTS in `webui_user.bat`(windows) or `webui_user.sh`(linux)
"""
)
# python = sys.executable
# launch.run(f'"{python}" -m pip uninstall -y huggingface_hub', live=True)
# launch.run(f'"{python}" -m pip install --upgrade git+https://github.com/huggingface/huggingface_hub@main', live=True)
# ### run the scripts to downlod models to correct localtion.
# # print('download models for SadTalker')
# # launch.run("cd " + paths.script_path+"/extensions/SadTalker && bash ./scripts/download_models.sh", live=True)
# # print('SadTalker is successfully installed!')
# download_model(paths.script_path+'/extensions/SadTalker/checkpoints')
def on_ui_tabs():
install()
sys.path.extend([paths.script_path+'/extensions/SadTalker'])
repo_dir = paths.script_path+'/extensions/SadTalker/'
result_dir = opts.sadtalker_result_dir
os.makedirs(result_dir, exist_ok=True)
from src.gradio_demo import SadTalker
if os.getenv('SADTALKER_CHECKPOINTS'):
checkpoint_path = os.getenv('SADTALKER_CHECKPOINTS')
else:
checkpoint_path = repo_dir+'checkpoints/'
sad_talker = SadTalker(checkpoint_path=checkpoint_path, config_path=repo_dir+'src/config', lazy_load=True)
with gr.Blocks(analytics_enabled=False) as audio_to_video:
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():
input_image = gr.Image(label="Source image", source="upload", type="filepath").style(height=256,width=256)
with gr.Row():
submit_image2 = gr.Button('load From txt2img', variant='primary')
submit_image2.click(fn=get_img_from_txt2img, inputs=input_image, outputs=[input_image, input_image])
submit_image3 = gr.Button('load from img2img', variant='primary')
submit_image3.click(fn=get_img_from_img2img, inputs=input_image, outputs=[input_image, input_image])
with gr.Tabs(elem_id="sadtalker_driven_audio"):
with gr.TabItem('Upload'):
with gr.Column(variant='panel'):
with gr.Row():
driven_audio = gr.Audio(label="Input audio", source="upload", type="filepath")
with gr.Column(variant='panel'):
with gr.Tabs(elem_id="sadtalker_checkbox"):
with gr.TabItem('Settings'):
with gr.Column(variant='panel'):
gr.Markdown("Please visit [**[here]**](https://github.com/Winfredy/SadTalker/blob/main/docs/best_practice.md) if you don't know how to choose these configurations.")
preprocess_type = gr.Radio(['crop','resize','full'], value='crop', label='preprocess', info="How to handle input image?")
is_still_mode = gr.Checkbox(label="Remove head motion (works better with preprocess `full`)")
enhancer = gr.Checkbox(label="Face enhancement")
submit = gr.Button('Generate', elem_id="sadtalker_generate", variant='primary')
path_to_save = gr.Text(Path(paths.script_path) / "outputs/SadTalker/", visible=False)
with gr.Tabs(elem_id="sadtalker_genearted"):
gen_video = gr.Video(label="Generated video", format="mp4").style(width=256)
### gradio gpu call will always return the html,
submit.click(
fn=wrap_queued_call(sad_talker.test),
inputs=[input_image,
driven_audio,
preprocess_type,
is_still_mode,
enhancer,
path_to_save
],
outputs=[gen_video, ]
)
return [(audio_to_video, "SadTalker", "extension")]
def on_ui_settings():
talker_path = Path(paths.script_path) / "outputs"
section = ('extension', "SadTalker")
opts.add_option("sadtalker_result_dir", OptionInfo(str(talker_path / "SadTalker/"), "Path to save results of sadtalker", section=section))
script_callbacks.on_ui_settings(on_ui_settings)
script_callbacks.on_ui_tabs(on_ui_tabs)