Spaces:
Runtime error
Runtime error
File size: 7,076 Bytes
c50a2e8 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 |
#!/usr/bin/env python
from __future__ import annotations
import os
import gradio as gr
from inference import InferencePipeline
class InferenceUtil:
def __init__(self, hf_token: str | None):
self.hf_token = hf_token
def load_model_info(self, model_id: str) -> tuple[str, str]:
try:
card = InferencePipeline.get_model_card(model_id, self.hf_token)
except Exception:
return '', ''
base_model = getattr(card.data, 'base_model', '')
training_prompt = getattr(card.data, 'training_prompt', '')
return base_model, training_prompt
TITLE = '# [Tune-A-Video](https://tuneavideo.github.io/)'
HF_TOKEN = os.getenv('HF_TOKEN')
pipe = InferencePipeline(HF_TOKEN)
app = InferenceUtil(HF_TOKEN)
with gr.Blocks(css='style.css') as demo:
gr.Markdown(TITLE)
with gr.Row():
with gr.Column():
with gr.Box():
model_id = gr.Dropdown(
label='Model ID',
choices=[
'Tune-A-Video-library/a-man-is-surfing',
'Tune-A-Video-library/mo-di-bear-guitar',
'Tune-A-Video-library/redshift-man-skiing',
],
value='Tune-A-Video-library/a-man-is-surfing')
with gr.Accordion(
label=
'Model info (Base model and prompt used for training)',
open=False):
with gr.Row():
base_model_used_for_training = gr.Text(
label='Base model', interactive=False)
prompt_used_for_training = gr.Text(
label='Training prompt', interactive=False)
prompt = gr.Textbox(label='Prompt',
max_lines=1,
placeholder='Example: "A panda is surfing"')
video_length = gr.Slider(label='Video length',
minimum=4,
maximum=12,
step=1,
value=8)
fps = gr.Slider(label='FPS',
minimum=1,
maximum=12,
step=1,
value=1)
seed = gr.Slider(label='Seed',
minimum=0,
maximum=100000,
step=1,
value=0)
with gr.Accordion('Other Parameters', open=False):
num_steps = gr.Slider(label='Number of Steps',
minimum=0,
maximum=100,
step=1,
value=50)
guidance_scale = gr.Slider(label='CFG Scale',
minimum=0,
maximum=50,
step=0.1,
value=7.5)
run_button = gr.Button('Generate')
gr.Markdown('''
- It takes a few minutes to download model first.
- Expected time to generate an 8-frame video: 70 seconds with T4, 24 seconds with A10G, (10 seconds with A100)
''')
with gr.Column():
result = gr.Video(label='Result')
with gr.Row():
examples = [
[
'Tune-A-Video-library/a-man-is-surfing',
'A panda is surfing.',
8,
1,
3,
50,
7.5,
],
[
'Tune-A-Video-library/a-man-is-surfing',
'A racoon is surfing, cartoon style.',
8,
1,
3,
50,
7.5,
],
[
'Tune-A-Video-library/mo-di-bear-guitar',
'a handsome prince is playing guitar, modern disney style.',
8,
1,
123,
50,
7.5,
],
[
'Tune-A-Video-library/mo-di-bear-guitar',
'a magical princess is playing guitar, modern disney style.',
8,
1,
123,
50,
7.5,
],
[
'Tune-A-Video-library/mo-di-bear-guitar',
'a rabbit is playing guitar, modern disney style.',
8,
1,
123,
50,
7.5,
],
[
'Tune-A-Video-library/mo-di-bear-guitar',
'a baby is playing guitar, modern disney style.',
8,
1,
123,
50,
7.5,
],
[
'Tune-A-Video-library/redshift-man-skiing',
'(redshift style) spider man is skiing.',
8,
1,
123,
50,
7.5,
],
[
'Tune-A-Video-library/redshift-man-skiing',
'(redshift style) black widow is skiing.',
8,
1,
123,
50,
7.5,
],
[
'Tune-A-Video-library/redshift-man-skiing',
'(redshift style) batman is skiing.',
8,
1,
123,
50,
7.5,
],
[
'Tune-A-Video-library/redshift-man-skiing',
'(redshift style) hulk is skiing.',
8,
1,
123,
50,
7.5,
],
]
gr.Examples(examples=examples,
inputs=[
model_id,
prompt,
video_length,
fps,
seed,
num_steps,
guidance_scale,
],
outputs=result,
fn=pipe.run,
cache_examples=os.getenv('SYSTEM') == 'spaces')
model_id.change(fn=app.load_model_info,
inputs=model_id,
outputs=[
base_model_used_for_training,
prompt_used_for_training,
])
inputs = [
model_id,
prompt,
video_length,
fps,
seed,
num_steps,
guidance_scale,
]
prompt.submit(fn=pipe.run, inputs=inputs, outputs=result)
run_button.click(fn=pipe.run, inputs=inputs, outputs=result)
demo.queue().launch()
|