File size: 7,006 Bytes
cff9535
 
 
416263d
 
0ce42bd
cff9535
 
 
 
0ce42bd
 
 
416263d
 
cff9535
0ce42bd
 
 
416263d
 
cff9535
416263d
cff9535
 
416263d
2299694
ed7bb0b
 
 
 
 
 
416263d
cff9535
 
 
 
416263d
cff9535
 
d7e9ac0
cff9535
d7e9ac0
416263d
 
 
 
 
 
cff9535
9beb764
 
 
 
0ce42bd
 
416263d
9beb764
 
 
a86a2b8
416263d
cff9535
 
 
416263d
 
0ce42bd
cff9535
 
a86a2b8
 
416263d
0ce42bd
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a86a2b8
416263d
 
 
 
 
0ce42bd
a86a2b8
 
 
 
416263d
 
0ce42bd
 
416263d
 
0ce42bd
 
 
 
 
 
 
cff9535
 
 
 
 
0ce42bd
cff9535
416263d
 
cff9535
ed7bb0b
cff9535
 
 
 
 
0ce42bd
cff9535
416263d
 
cff9535
 
 
a22eb82
 
cff9535
a22eb82
416263d
ed7bb0b
 
a22eb82
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
import os, sys
import tempfile
import gradio as gr
from src.gradio_demo import SadTalker  
from src.utils.text2speech import TTSTalker
from huggingface_hub import snapshot_download

def get_source_image(image):   
        return image

def download_model():
    REPO_ID = 'vinthony/SadTalker'
    snapshot_download(repo_id=REPO_ID, local_dir='./checkpoints', local_dir_use_symlinks=True)

def sadtalker_demo():

    download_model()

    sad_talker = SadTalker(lazy_load=True)
    tts_talker = TTSTalker()

    with gr.Blocks(analytics_enabled=False) as sadtalker_interface:
        gr.Markdown("<div align='center'> <h2> 😭 SadTalker: Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation (CVPR 2023) </span> </h2> \
                    <a style='font-size:18px;color: #efefef' href='https://arxiv.org/abs/2211.12194'>Arxiv</a> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp; \
                    <a style='font-size:18px;color: #efefef' href='https://sadtalker.github.io'>Homepage</a>  &nbsp;&nbsp;&nbsp;&nbsp;&nbsp; \
                     <a style='font-size:18px;color: #efefef' href='https://github.com/Winfredy/SadTalker'> Github </div>")
        
        
        gr.Markdown("""
        <b>You may duplicate the space and upgrade to GPU in settings for better performance and faster inference without waiting in the queue. <a style='display:inline-block' href="https://huggingface.co/spaces/vinthony/SadTalker?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a></b> \
        <br/><b>Alternatively, try our GitHub <a href=https://github.com/Winfredy/SadTalker> code </a> on your own GPU. </b> <a style='display:inline-block' href="https://github.com/Winfredy/SadTalker"><img src="https://img.shields.io/github/stars/Winfredy/SadTalker?style=social"/></a> \
        """)
        
        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():
                            source_image = gr.Image(label="Source image", source="upload", type="filepath").style(height=256,width=256)
 
                with gr.Tabs(elem_id="sadtalker_driven_audio"):
                    with gr.TabItem('Upload or Generating from TTS'):
                        with gr.Column(variant='panel'):
                            driven_audio = gr.Audio(label="Input audio(.wav/.mp3)", source="upload", type="filepath")
                    
                        with gr.Column(variant='panel'):
                            input_text = gr.Textbox(label="Generating audio from text", lines=5, placeholder="Alternatively, you can genreate the audio from text using @Coqui.ai TTS.")
                            tts = gr.Button('Generate audio',elem_id="sadtalker_audio_generate", variant='primary')
                            tts.click(fn=tts_talker.test, inputs=[input_text], outputs=[driven_audio])
                        

            with gr.Column(variant='panel'): 
                with gr.Tabs(elem_id="sadtalker_checkbox"):
                    with gr.TabItem('Settings'):
                        with gr.Column(variant='panel'):
                            preprocess_type = gr.Radio(['crop','resize','full'], value='crop', label='preprocess', info="How to handle input image?")
                            is_still_mode = gr.Checkbox(label="w/ Still Mode (fewer hand motion, works with preprocess `full`)")
                            enhancer = gr.Checkbox(label="w/ GFPGAN as Face enhancer")
                            submit = gr.Button('Generate', elem_id="sadtalker_generate", variant='primary')

                with gr.Tabs(elem_id="sadtalker_genearted"):
                        gen_video = gr.Video(label="Generated video", format="mp4").style(width=256)

        with gr.Row():
            examples = [
                [
                    'examples/source_image/full_body_1.png',
                    'examples/driven_audio/bus_chinese.wav',
                    'crop',
                    True,
                    False
                ],
                [
                    'examples/source_image/full_body_2.png',
                    'examples/driven_audio/japanese.wav',
                    'crop',
                    False,
                    False
                ],
                [
                    'examples/source_image/full3.png',
                    'examples/driven_audio/deyu.wav',
                    'crop',
                    False,
                    True
                ],
                [
                    'examples/source_image/full4.jpeg',
                    'examples/driven_audio/eluosi.wav',
                    'full',
                    False,
                    True
                ],
                [
                    'examples/source_image/full4.jpeg',
                    'examples/driven_audio/imagine.wav',
                    'full',
                    True,
                    True
                ],
                [
                    'examples/source_image/full_body_1.png',
                    'examples/driven_audio/bus_chinese.wav',
                    'full',
                    True,
                    False
                ],
                [
                    'examples/source_image/art_13.png',
                    'examples/driven_audio/fayu.wav',
                    'resize',
                    True,
                    False
                ],
                [
                    'examples/source_image/art_5.png',
                    'examples/driven_audio/chinese_news.wav',
                    'resize',
                    False,
                    False
                ],
                [
                    'examples/source_image/art_5.png',
                    'examples/driven_audio/RD_Radio31_000.wav',
                    'resize',
                    True,
                    True
                ],
            ]
            gr.Examples(examples=examples,
                        inputs=[
                            source_image,
                            driven_audio,
                            preprocess_type,
                            is_still_mode,
                            enhancer], 
                        outputs=[gen_video],
                        fn=sad_talker.test,
                        cache_examples=os.getenv('SYSTEM') == 'spaces') # 

        submit.click(
                    fn=sad_talker.test, 
                    inputs=[source_image,
                            driven_audio,
                            preprocess_type,
                            is_still_mode,
                            enhancer], 
                    outputs=[gen_video]
                    )

    return sadtalker_interface
 

if __name__ == "__main__":

    demo = sadtalker_demo()
    demo.queue(max_size=10)
    demo.launch(debug=True)