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import os, sys
sys.path.append('./')
import argparse
import gradio as gr
from inference.real3d_infer import GeneFace2Infer
from utils.commons.hparams import hparams
class Inferer(GeneFace2Infer):
def infer_once_args(self, *args, **kargs):
assert len(kargs) == 0
keys = [
'src_image_name',
'drv_audio_name',
'drv_pose_name',
'bg_image_name',
'blink_mode',
'temperature',
'mouth_amp',
'out_mode',
'map_to_init_pose',
'low_memory_usage',
'hold_eye_opened',
'a2m_ckpt',
'head_ckpt',
'torso_ckpt',
'min_face_area_percent',
]
inp = {}
out_name = None
info = ""
try: # try to catch errors and jump to return
for key_index in range(len(keys)):
key = keys[key_index]
inp[key] = args[key_index]
if '_name' in key:
inp[key] = inp[key] if inp[key] is not None else ''
if inp['src_image_name'] == '':
info = "Input Error: Source image is REQUIRED!"
raise ValueError
if inp['drv_audio_name'] == '' and inp['drv_pose_name'] == '':
info = "Input Error: At least one of driving audio or video is REQUIRED!"
raise ValueError
if inp['drv_audio_name'] == '' and inp['drv_pose_name'] != '':
inp['drv_audio_name'] = inp['drv_pose_name']
print("No audio input, we use driving pose video for video driving")
if inp['drv_pose_name'] == '':
inp['drv_pose_name'] = 'static'
reload_flag = False
if inp['a2m_ckpt'] != self.audio2secc_dir:
print("Changes of a2m_ckpt detected, reloading model")
reload_flag = True
if inp['head_ckpt'] != self.head_model_dir:
print("Changes of head_ckpt detected, reloading model")
reload_flag = True
if inp['torso_ckpt'] != self.torso_model_dir:
print("Changes of torso_ckpt detected, reloading model")
reload_flag = True
inp['out_name'] = ''
inp['seed'] = 42
print(f"infer inputs : {inp}")
try:
if reload_flag:
self.__init__(inp['a2m_ckpt'], inp['head_ckpt'], inp['torso_ckpt'], inp=inp, device=self.device)
except Exception as e:
content = f"{e}"
info = f"Reload ERROR: {content}"
raise ValueError
try:
out_name = self.infer_once(inp)
except Exception as e:
content = f"{e}"
info = f"Inference ERROR: {content}"
raise ValueError
except Exception as e:
if info == "": # unexpected errors
content = f"{e}"
info = f"WebUI ERROR: {content}"
# output part
if len(info) > 0 : # there is errors
print(info)
info_gr = gr.update(visible=True, value=info)
else: # no errors
info_gr = gr.update(visible=False, value=info)
if out_name is not None and len(out_name) > 0 and os.path.exists(out_name): # good output
print(f"Succefully generated in {out_name}")
video_gr = gr.update(visible=True, value=out_name)
else:
print(f"Failed to generate")
video_gr = gr.update(visible=True, value=out_name)
return video_gr, info_gr
def toggle_audio_file(choice):
if choice == False:
return gr.update(visible=True), gr.update(visible=False)
else:
return gr.update(visible=False), gr.update(visible=True)
def ref_video_fn(path_of_ref_video):
if path_of_ref_video is not None:
return gr.update(value=True)
else:
return gr.update(value=False)
def real3dportrait_demo(
audio2secc_dir,
head_model_dir,
torso_model_dir,
device = 'cuda',
warpfn = None,
):
sep_line = "-" * 40
infer_obj = Inferer(
audio2secc_dir=audio2secc_dir,
head_model_dir=head_model_dir,
torso_model_dir=torso_model_dir,
device=device,
)
print(sep_line)
print("Model loading is finished.")
print(sep_line)
with gr.Blocks(analytics_enabled=False) as real3dportrait_interface:
gr.Markdown("\
<div align='center'> <h2> Real3D-Portrait: One-shot Realistic 3D Talking Portrait Synthesis (ICLR 2024 Spotlight) </span> </h2> \
<a style='font-size:18px;color: #a0a0a0' href='https://arxiv.org/pdf/2401.08503.pdf'>Arxiv</a> \
<a style='font-size:18px;color: #a0a0a0' href='https://real3dportrait.github.io/'>Homepage</a> \
<a style='font-size:18px;color: #a0a0a0' href='https://github.com/yerfor/Real3DPortrait/'> Github </div>")
sources = None
with gr.Row():
with gr.Column(variant='panel'):
with gr.Tabs(elem_id="source_image"):
with gr.TabItem('Upload image'):
with gr.Row():
src_image_name = gr.Image(label="Source image (required)", sources=sources, type="filepath", value="data/raw/examples/Macron.png")
with gr.Tabs(elem_id="driven_audio"):
with gr.TabItem('Upload audio'):
with gr.Column(variant='panel'):
drv_audio_name = gr.Audio(label="Input audio (required for audio-driven)", sources=sources, type="filepath", value="data/raw/examples/Obama_5s.wav")
with gr.Tabs(elem_id="driven_pose"):
with gr.TabItem('Upload video'):
with gr.Column(variant='panel'):
drv_pose_name = gr.Video(label="Driven Pose (required for video-driven, optional for audio-driven)", sources=sources, value="data/raw/examples/May_5s.mp4")
with gr.Tabs(elem_id="bg_image"):
with gr.TabItem('Upload image'):
with gr.Row():
bg_image_name = gr.Image(label="Background image (optional)", sources=sources, type="filepath", value="data/raw/examples/bg.png")
with gr.Column(variant='panel'):
with gr.Tabs(elem_id="checkbox"):
with gr.TabItem('General Settings'):
with gr.Column(variant='panel'):
blink_mode = gr.Radio(['none', 'period'], value='period', label='blink mode', info="whether to blink periodly") #
min_face_area_percent = gr.Slider(minimum=0.15, maximum=0.5, step=0.01, label="min_face_area_percent", value=0.2, info='The minimum face area percent in the output frame, to prevent bad cases caused by a too small face.',)
temperature = gr.Slider(minimum=0.0, maximum=1.0, step=0.025, label="temperature", value=0.2, info='audio to secc temperature',)
mouth_amp = gr.Slider(minimum=0.0, maximum=1.0, step=0.025, label="mouth amplitude", value=0.45, info='higher -> mouth will open wider, default to be 0.4',)
out_mode = gr.Radio(['final', 'concat_debug'], value='concat_debug', label='output layout', info="final: only final output ; concat_debug: final output concated with internel features")
low_memory_usage = gr.Checkbox(label="Low Memory Usage Mode: save memory at the expense of lower inference speed. Useful when running a low audio (minutes-long).", value=False)
map_to_init_pose = gr.Checkbox(label="Whether to map pose of first frame to initial pose", value=True)
hold_eye_opened = gr.Checkbox(label="Whether to maintain eyes always open")
submit = gr.Button('Generate', elem_id="generate", variant='primary')
with gr.Tabs(elem_id="genearted_video"):
info_box = gr.Textbox(label="Error", interactive=False, visible=False)
gen_video = gr.Video(label="Generated video", format="mp4", visible=True)
with gr.Column(variant='panel'):
with gr.Tabs(elem_id="checkbox"):
with gr.TabItem('Checkpoints'):
with gr.Column(variant='panel'):
ckpt_info_box = gr.Textbox(value="Please select \"ckpt\" under the checkpoint folder ", interactive=False, visible=True, show_label=False)
audio2secc_dir = gr.FileExplorer(glob="checkpoints/**/*.ckpt", value=audio2secc_dir, file_count='single', label='audio2secc model ckpt path or directory')
head_model_dir = gr.FileExplorer(glob="checkpoints/**/*.ckpt", value=head_model_dir, file_count='single', label='head model ckpt path or directory (will be ignored if torso model is set)')
torso_model_dir = gr.FileExplorer(glob="checkpoints/**/*.ckpt", value=torso_model_dir, file_count='single', label='torso model ckpt path or directory')
# audio2secc_dir = gr.Textbox(audio2secc_dir, max_lines=1, label='audio2secc model ckpt path or directory (will be ignored if torso model is set)')
# head_model_dir = gr.Textbox(head_model_dir, max_lines=1, label='head model ckpt path or directory (will be ignored if torso model is set)')
# torso_model_dir = gr.Textbox(torso_model_dir, max_lines=1, label='torso model ckpt path or directory')
fn = infer_obj.infer_once_args
if warpfn:
fn = warpfn(fn)
submit.click(
fn=fn,
inputs=[
src_image_name,
drv_audio_name,
drv_pose_name,
bg_image_name,
blink_mode,
temperature,
mouth_amp,
out_mode,
map_to_init_pose,
low_memory_usage,
hold_eye_opened,
audio2secc_dir,
head_model_dir,
torso_model_dir,
min_face_area_percent,
],
outputs=[
gen_video,
info_box,
],
)
print(sep_line)
print("Gradio page is constructed.")
print(sep_line)
return real3dportrait_interface
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--a2m_ckpt", type=str, default='checkpoints/240210_real3dportrait_orig/audio2secc_vae/model_ckpt_steps_400000.ckpt')
parser.add_argument("--head_ckpt", type=str, default='')
parser.add_argument("--torso_ckpt", type=str, default='checkpoints/240210_real3dportrait_orig/secc2plane_torso_orig/model_ckpt_steps_100000.ckpt')
parser.add_argument("--port", type=int, default=None)
parser.add_argument("--server", type=str, default='127.0.0.1')
parser.add_argument("--share", action='store_true', dest='share', help='share srever to Internet')
args = parser.parse_args()
demo = real3dportrait_demo(
audio2secc_dir=args.a2m_ckpt,
head_model_dir=args.head_ckpt,
torso_model_dir=args.torso_ckpt,
device='cuda:0',
warpfn=None,
)
demo.queue()
demo.launch(share=args.share, server_name=args.server, server_port=args.port)
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