Spaces:
Runtime error
Runtime error
File size: 4,372 Bytes
1028ed7 |
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 |
import gradio as gr
from model import Model
from functools import partial
from bs4 import BeautifulSoup
import requests
examples = [
["an astronaut waving the arm on the moon"],
["a sloth surfing on a wakeboard"],
["an astronaut walking on a street"],
["a cute cat walking on grass"],
["a horse is galloping on a street"],
["an astronaut is skiing down the hill"],
["a gorilla walking alone down the street"],
["a gorilla dancing on times square"],
["A panda dancing dancing like crazy on Times Square"],
]
def model_url_list():
url_list = []
for i in range(0, 5):
url_list.append(f"https://huggingface.co/models?p={i}&sort=downloads&search=dreambooth")
return url_list
def data_scraping(url_list):
model_list = []
for url in url_list:
response = requests.get(url)
soup = BeautifulSoup(response.text, "html.parser")
div_class = 'grid grid-cols-1 gap-5 2xl:grid-cols-2'
div = soup.find('div', {'class': div_class})
for a in div.find_all('a', href=True):
model_list.append(a['href'])
return model_list
model_list = data_scraping(model_url_list())
for i in range(len(model_list)):
model_list[i] = model_list[i][1:]
best_model_list = [
"dreamlike-art/dreamlike-photoreal-2.0",
"dreamlike-art/dreamlike-diffusion-1.0",
"runwayml/stable-diffusion-v1-5",
"CompVis/stable-diffusion-v1-4",
"prompthero/openjourney",
]
model_list = best_model_list + model_list
def create_demo(model: Model):
with gr.Blocks() as demo:
with gr.Row():
gr.Markdown('## Text2Video-Zero: Video Generation')
with gr.Row():
gr.HTML(
"""
<div style="text-align: left; auto;">
<h2 style="font-weight: 450; font-size: 1rem; margin: 0rem">
Description: Simply input <b>any textual prompt</b> to generate videos right away and unleash your creativity and imagination! You can also select from the examples below. For performance purposes, our current preview release by default generates only 8 output frames and output 4s videos, but you can increase it from Advanced Options.
</h3>
</div>
""")
with gr.Row():
with gr.Column():
model_name = gr.Dropdown(
label="Model",
choices=model_list,
value="dreamlike-art/dreamlike-photoreal-2.0",
)
prompt = gr.Textbox(label='Prompt')
run_button = gr.Button(label='Run')
with gr.Accordion('Advanced options', open=False):
watermark = gr.Radio(["Picsart AI Research", "Text2Video-Zero", "None"], label="Watermark", value='Picsart AI Research')
video_length = gr.Number(label="Video length", value=8, min=2, precision=0)
chunk_size = gr.Slider(label="Chunk size", minimum=2, maximum=32, value=8, step=1)
motion_field_strength_x = gr.Slider(label='Global Translation $\delta_{x}$', minimum=-20, maximum=20, value=12, step=1)
motion_field_strength_y = gr.Slider(label='Global Translation $\delta_{y}$', minimum=-20, maximum=20, value=12, step=1)
t0 = gr.Slider(label="Timestep t0", minimum=0, maximum=49, value=44, step=1)
t1 = gr.Slider(label="Timestep t1", minimum=0, maximum=49, value=47, step=1)
n_prompt = gr.Textbox(label="Optional Negative Prompt", value='')
with gr.Column():
result = gr.Video(label="Generated Video")
inputs = [
prompt,
model_name,
motion_field_strength_x,
motion_field_strength_y,
t0,
t1,
n_prompt,
chunk_size,
video_length,
watermark,
]
gr.Examples(examples=examples,
inputs=inputs,
outputs=result,
fn=model.process_text2video,
# cache_examples=True,
run_on_click=False,
)
run_button.click(fn=model.process_text2video,
inputs=inputs,
outputs=result,)
return demo
|