Spaces:
Runtime error
Runtime error
File size: 12,020 Bytes
f41d114 21d4393 0e406cc f41d114 9c88c69 2aca82a 0e406cc 1bd26d7 0e406cc 1bd26d7 2aca82a 1bd26d7 2aca82a 0e406cc 2aca82a 789c5b7 0e406cc 789c5b7 0e406cc 2aca82a 9c88c69 feb87be 0e406cc feb87be 789c5b7 1bd26d7 feb87be 789c5b7 feb87be 2aca82a feb87be 2aca82a feb87be 2aca82a feb87be 789c5b7 2aca82a feb87be 16d4e4c 2aca82a feb87be 0e406cc 1bd26d7 0e406cc 1bd26d7 0e406cc 789c5b7 0e406cc 789c5b7 0e406cc feb87be 3b4ef39 f41d114 9c88c69 feb87be bbc3e9e 8132e49 f41d114 9c88c69 feb87be f41d114 83a8130 f41d114 9c88c69 f41d114 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 |
import gradio as gr
import requests
import time
import json
from contextlib import closing
from websocket import create_connection
from deep_translator import GoogleTranslator
from langdetect import detect
import os
from PIL import Image
import io
import base64
import os
import random
import tempfile
import re
from gradio_client import Client
def animate_img(encoded_string):
try:
r = requests.post("https://stable-video-diffusion.com/api/upload", files={"file": open(encoded_string, 'rb')})
hash_ = r.json()['hash']
time.sleep(10)
c = 0
while c < 10:
r2 = requests.get(f"https://stable-video-diffusion.com/result?hash={hash_}")
source_string = r2.text
if "Generation has been in progress for" in source_string:
time.sleep(15)
c += 1
continue
if "Generation has been in progress for" not in source_string:
pattern = r'https://storage.stable-video-diffusion.com/([a-f0-9]{32})\.mp4'
matches = re.findall(pattern, source_string)
sd_video = []
for match in matches:
sd_video.append(f"https://storage.stable-video-diffusion.com/{match}.mp4")
if len(sd_video) != 0:
print("s_1")
return sd_video[0]
else:
_ = 1/0
print("f_1")
except:
print("2")
client1 = Client("https://emmadrex-stable-video-diffusion.hf.space")
result1 = client1.predict(encoded_string, api_name="/resize_image")
client = Client("https://emmadrex-stable-video-diffusion.hf.space")
result = client.predict(result1, 0, True, 1, 15, api_name="/video")
res = result[0]['video']
print("s_2")
return res
def create_video(prompt):
url_sd3 = os.getenv("url_sd3")
url_sd4 = os.getenv("url_sd4")
try:
with closing(create_connection(f"{url_sd3}", timeout=120)) as conn:
conn.send('{"fn_index":3,"session_hash":""}')
conn.send(f'{{"data":["{prompt}","[deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry",7.5,"(No style)"],"event_data":null,"fn_index":3,"session_hash":""}}')
c = 0
while c < 60:
status = json.loads(conn.recv())['msg']
if status == 'estimation':
c += 1
time.sleep(1)
continue
if status == 'process_starts':
break
photo = json.loads(conn.recv())['output']['data'][0][0]
base64_string = photo.replace('data:image/jpeg;base64,', '').replace('data:image/png;base64,', '')
image_bytes = base64.b64decode(base64_string)
with tempfile.NamedTemporaryFile(delete=False) as temp:
temp.write(image_bytes)
temp_file_path = temp.name
print("cs_1")
except:
print("c_2")
with closing(create_connection(f"{url_sd4}", timeout=120)) as conn:
conn.send('{"fn_index":0,"session_hash":""}')
conn.send(f'{{"data":["{prompt}","[deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry","dreamshaperXL10_alpha2.safetensors [c8afe2ef]",30,"DPM++ 2M Karras",7,1024,1024,-1],"event_data":null,"fn_index":0,"session_hash":""}}')
conn.recv()
conn.recv()
conn.recv()
conn.recv()
photo = json.loads(conn.recv())['output']['data'][0]
base64_string = photo.replace('data:image/jpeg;base64,', '').replace('data:image/png;base64,', '')
image_bytes = base64.b64decode(base64_string)
with tempfile.NamedTemporaryFile(delete=False) as temp:
temp.write(image_bytes)
temp_file_path = temp.name
print("cs_2")
try:
r = requests.post("https://stable-video-diffusion.com/api/upload", files={"file": open(temp_file_path, 'rb')})
print(r.text)
hash_ = r.json()['hash']
time.sleep(10)
c = 0
while c < 10:
r2 = requests.get(f"https://stable-video-diffusion.com/result?hash={hash_}")
source_string = r2.text
if "Generation has been in progress for" in source_string:
time.sleep(15)
c += 1
continue
if "Generation has been in progress for" not in source_string:
pattern = r'https://storage.stable-video-diffusion.com/([a-f0-9]{32})\.mp4'
matches = re.findall(pattern, source_string)
sd_video = []
for match in matches:
sd_video.append(f"https://storage.stable-video-diffusion.com/{match}.mp4")
print(sd_video[0])
if len(sd_video) != 0:
return sd_video[0]
else:
_ = 1/0
except:
client1 = Client("https://emmadrex-stable-video-diffusion.hf.space")
result1 = client1.predict(encoded_string, api_name="/resize_image")
client = Client("https://emmadrex-stable-video-diffusion.hf.space")
result = client.predict(result1, 0, True, 1, 15, api_name="/video")
return result[0]['video']
def flip_text1(prompt, motion):
try:
language = detect(prompt)
if language == 'ru':
prompt = GoogleTranslator(source='ru', target='en').translate(prompt)
print(prompt)
except:
prompt = 'video'
url_video_g = os.getenv("url_video_g")
url_video_c = os.getenv("url_video_c")
if motion == "Приближение →←":
motion = 'zoom in'
if motion == "Отдаление ←→":
motion = 'zoom out'
if motion == "Вверх ↑":
motion = 'up'
if motion == "Вниз ↓":
motion = 'down'
if motion == "Влево ←":
motion = 'left'
if motion == "Вправо →":
motion = 'right'
if motion == "По часовой стрелке ⟳":
motion = 'rotate cw'
if motion == "Против часовой стрелки ⟲":
motion = 'rotate ccw'
data = {"prompt": f"{prompt}","image": "null", "denoise": 0.75,"motion": motion}
r = requests.post(f"{url_video_g}", json=data)
while True:
data2 = {"task_id": f"{r.json()['task_id']}"}
r2 = requests.post(f"{url_video_c}", json=data2)
time.sleep(3)
try:
if r2.json()['status'] == "QUEUED":
continue
if r2.json()['status'] == "PROCESSING":
continue
except:
try:
n_im2 = f"{time.time()}"
with tempfile.NamedTemporaryFile(prefix=f'aaafff{n_im2}', suffix='.mp4', delete=False) as file:
for chunk in r2.iter_content(chunk_size=1024):
if chunk:
file.write(chunk)
return file.name
except Exception as e:
print(e)
break
def flip_text2(encoded_string, prompt, motion):
url_video_g = os.getenv("url_video_g")
url_video_c = os.getenv("url_video_c")
try:
language = detect(prompt)
if language == 'ru':
prompt = GoogleTranslator(source='ru', target='en').translate(prompt)
print(prompt)
except:
pass
if motion == "Приближение →←":
motion = 'zoom in'
if motion == "Отдаление ←→":
motion = 'zoom out'
if motion == "Вверх ↑":
motion = 'up'
if motion == "Вниз ↓":
motion = 'down'
if motion == "Влево ←":
motion = 'left'
if motion == "Вправо →":
motion = 'right'
if motion == "По часовой стрелке ⟳":
motion = 'rotate cw'
if motion == "Против часовой стрелки ⟲":
motion = 'rotate ccw'
with open(encoded_string, "rb") as image_file:
encoded_string2 = base64.b64encode(image_file.read())
encoded_string2 = str(encoded_string2).replace("b'", '')
data = {"prompt": f"{prompt}","image": f"{encoded_string2}","denoise":0.75,"motion": motion}
r = requests.post(f"{url_video_g}", json=data)
while True:
data2 = {"task_id": f"{r.json()['task_id']}"}
r2 = requests.post(f"{url_video_c}", json=data2)
time.sleep(3)
try:
if r2.json()['status'] == "QUEUED":
continue
if r2.json()['status'] == "PROCESSING":
continue
except:
try:
n_im2 = f"{time.time()}"
with tempfile.NamedTemporaryFile(prefix=f'aaafff{n_im2}', suffix='.mp4', delete=False) as file:
for chunk in r2.iter_content(chunk_size=1024):
if chunk:
file.write(chunk)
return file.name
except Exception as e:
print(e)
break
css = """
#generate {
width: 100%;
background: #e253dd !important;
border: none;
border-radius: 50px;
outline: none !important;
color: white;
}
#generate:hover {
background: #de6bda !important;
outline: none !important;
color: #fff;
}
footer {visibility: hidden !important;}
"""
with gr.Blocks(css=css) as demo:
with gr.Tab("Сгенерировать видео"):
with gr.Column():
prompt = gr.Textbox(placeholder="Введите описание видео...", show_label=True, label='Описание:', lines=3)
motion1 = gr.Dropdown(value="Приближение →←", interactive=True, show_label=True, label="Движение камеры:", choices=[
"Приближение →←", "Отдаление ←→", "Вверх ↑", "Вниз ↓", "Влево ←", "Вправо →", "По часовой стрелке ⟳", "Против часовой стрелки ⟲"])
with gr.Column():
text_button = gr.Button("Сгенерировать видео", variant='primary', elem_id="generate")
with gr.Column():
video_output = gr.Video(show_label=True, label='Результат:', type="file")
text_button.click(create_video, inputs=[prompt], outputs=video_output)
with gr.Tab("Анимировать изображение"):
with gr.Column():
prompt2 = gr.Image(show_label=True, interactive=True, type='filepath', label='Исходное изображение:')
prompt12 = gr.Textbox(placeholder="Введите описание видео...", show_label=True, label='Описание видео (опционально):', lines=3)
motion2 = gr.Dropdown(value="Приближение →←", interactive=True, show_label=True, label="Движение камеры:", choices=[
"Приближение →←", "Отдаление ←→", "Вверх ↑", "Вниз ↓", "Влево ←", "Вправо →", "По часовой стрелке ⟳", "Против часовой стрелки ⟲"])
with gr.Column():
text_button2 = gr.Button("Анимировать изображение", variant='primary', elem_id="generate")
with gr.Column():
video_output2 = gr.Video(show_label=True, label='Результат:', type="file")
text_button2.click(animate_img, inputs=[prompt2], outputs=video_output2)
demo.queue(concurrency_count=12)
demo.launch() |