update
After Width: | Height: | Size: 2.3 MiB |
After Width: | Height: | Size: 2.8 MiB |
After Width: | Height: | Size: 3.3 MiB |
After Width: | Height: | Size: 2.4 MiB |
After Width: | Height: | Size: 3.5 MiB |
After Width: | Height: | Size: 467 KiB |
After Width: | Height: | Size: 556 KiB |
After Width: | Height: | Size: 581 KiB |
After Width: | Height: | Size: 529 KiB |
After Width: | Height: | Size: 609 KiB |
After Width: | Height: | Size: 542 KiB |
After Width: | Height: | Size: 625 KiB |
Before Width: | Height: | Size: 24 MiB After Width: | Height: | Size: 42 MiB |
@ -0,0 +1,201 @@
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Beyoncé
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Taylor Swift
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Rihanna
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Ariana Grande
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Angelina Jolie
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Jennifer Lawrence
|
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Emma Watson
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Katy Perry
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Scarlett Johansson
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Lady Gaga
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Gal Gadot
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Selena Gomez
|
||||
Sandra Bullock
|
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Ellen DeGeneres
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Mila Kunis
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Jennifer Aniston
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||||
Margot Robbie
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||||
Blake Lively
|
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Miley Cyrus
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Charlize Theron
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Emma Stone
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Sofia Vergara
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Halle Berry
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Zendaya
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Dwayne Johnson
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Lady Amelia Windsor
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Brie Larson
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Adele
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Janelle Monae
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Shakira
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Priyanka Chopra
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Betty White
|
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Nina Dobrev
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Meghan Markle
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Lupita Nyong'o
|
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Emilia Clarke
|
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Kate Middleton
|
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Zooey Deschanel
|
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Sienna Miller
|
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Christina Aguilera
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Kate Hudson
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Gina Rodriguez
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Cardi B
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Yara Shahidi
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Michelle Obama
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Kourtney Kardashian
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Portia de Rossi
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Kerry Washington
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Jada Pinkett Smith
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Lucy Liu
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Victoria Beckham
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Gwyneth Paltrow
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Kim Kardashian
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Ellen Page
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Kerry Washington
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Maya Rudolph
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Alicia Keys
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Oprah Winfrey
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Tracee Ellis Ross
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Jennifer Lopez
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Rachel McAdams
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Pink
|
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Cameron Diaz
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Lily Collins
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Anne Hathaway
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Tyra Banks
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Ashley Tisdale
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Amanda Seyfried
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Jessica Alba
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Demi Lovato
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Keira Knightley
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Bella Hadid
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Kendall Jenner
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Emma Roberts
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Vanessa Hudgens
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Sofia Richie
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Hailey Bieber
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Gisele Bündchen
|
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Taylor Hill
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Kiki Layne
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Cate Blanchett
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Kate Winslet
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Gal Gadot
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Salma Hayek
|
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Julia Roberts
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Mariah Carey
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Scarlett Johansson
|
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Rosie Huntington-Whitely
|
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Marjane Satrapi
|
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Halle Berry
|
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Mariah Carey
|
||||
Selena Gomez
|
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Emma Watson
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||||
Jennifer Aniston
|
||||
Rihanna
|
||||
Blake Lively
|
||||
Ariana Grande
|
||||
Angelina Jolie
|
||||
Lady Gaga
|
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Taylor Swift
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|
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Robert Downey Jr.
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Tom Cruise
|
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George Clooney
|
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Brad Pitt
|
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Dwayne Johnson
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Leonardo DiCaprio
|
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Will Smith
|
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Johnny Depp
|
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Chris Evans
|
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Ryan Reynolds
|
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Tom Hanks
|
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Matt Damon
|
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Denzel Washington
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Hugh Jackman
|
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Chris Hemsworth
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Chris Pratt
|
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Idris Elba
|
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Daniel Craig
|
||||
Samuel L. Jackson
|
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Jeremy Renner
|
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Chris Pine
|
||||
Robert Pattinson
|
||||
Sebastian Stan
|
||||
Benedict Cumberbatch
|
||||
Paul Rudd
|
||||
Mark Wahlberg
|
||||
Zac Efron
|
||||
Jason Statham
|
||||
Michael Fassbender
|
||||
Joel Kinnaman
|
||||
Keanu Reeves
|
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Scarlett Johansson
|
||||
Vin Diesel
|
||||
Angelina Jolie
|
||||
Emma Watson
|
||||
Jennifer Lawrence
|
||||
Gal Gadot
|
||||
Margot Robbie
|
||||
Brie Larson
|
||||
Sofia Vergara
|
||||
Mila Kunis
|
||||
Emily Blunt
|
||||
Sandra Bullock
|
||||
Kate Winslet
|
||||
Nicole Kidman
|
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Charlize Theron
|
||||
Anne Hathaway
|
||||
Cate Blanchett
|
||||
Emma Stone
|
||||
Lupita Nyong'o
|
||||
Jennifer Aniston
|
||||
Halle Berry
|
||||
Rihanna
|
||||
Lady Gaga
|
||||
Beyoncé
|
||||
Taylor Swift
|
||||
Miley Cyrus
|
||||
Ariana Grande
|
||||
Meghan Markle
|
||||
Kate Middleton
|
||||
Angelina Jolie
|
||||
Jennifer Lopez
|
||||
Shakira
|
||||
Katy Perry
|
||||
Lady Gaga
|
||||
Britney Spears
|
||||
Adele
|
||||
Mariah Carey
|
||||
Madonna
|
||||
Janet Jackson
|
||||
Whitney Houston
|
||||
Tina Turner
|
||||
Celine Dion
|
||||
Barbra Streisand
|
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Cher
|
||||
Gloria Estefan
|
||||
Diana Ross
|
||||
Julie Andrews
|
||||
Liza Minnelli
|
||||
Bette Midler
|
||||
Elton John
|
||||
Freddie Mercury
|
||||
Paul McCartney
|
||||
Elvis Presley
|
||||
Michael Jackson
|
||||
Prince
|
||||
Madonna
|
||||
Mariah Carey
|
||||
Janet Jackson
|
||||
Whitney Houston
|
||||
Tina Turner
|
||||
Celine Dion
|
||||
Barbra Streisand
|
||||
Cher
|
||||
Gloria Estefan
|
||||
Diana Ross
|
||||
Julie Andrews
|
||||
Liza Minnelli
|
||||
Bette Midler
|
||||
Elton John
|
@ -1,4 +1,13 @@
|
||||
from modelscope.hub.snapshot_download import snapshot_download
|
||||
# pre-trained models in different style
|
||||
model_dir = snapshot_download('damo/cv_unet_person-image-cartoon_compound-models', cache_dir='.')
|
||||
model_dir = snapshot_download('damo/cv_unet_person-image-cartoon-3d_compound-models', cache_dir='.')
|
||||
model_dir = snapshot_download('damo/cv_unet_person-image-cartoon-handdrawn_compound-models', cache_dir='.')
|
||||
model_dir = snapshot_download('damo/cv_unet_person-image-cartoon-sketch_compound-models', cache_dir='.')
|
||||
model_dir = snapshot_download('damo/cv_unet_person-image-cartoon-artstyle_compound-models', cache_dir='.')
|
||||
|
||||
# pre-trained models trained with DCT-Net + Stable-Diffusion
|
||||
model_dir = snapshot_download('damo/cv_unet_person-image-cartoon-sd-design_compound-models', revision='v1.0.0', cache_dir='.')
|
||||
model_dir = snapshot_download('damo/cv_unet_person-image-cartoon-sd-illustration_compound-models', revision='v1.0.0', cache_dir='.')
|
||||
|
||||
|
||||
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@ -0,0 +1,59 @@
|
||||
from modelscope.pipelines import pipeline
|
||||
from modelscope.utils.constant import Tasks
|
||||
import torch
|
||||
import os, cv2
|
||||
import argparse
|
||||
|
||||
def load_cele_txt(celeb_file='celeb.txt'):
|
||||
celeb = open(celeb_file, 'r')
|
||||
lines = celeb.readlines()
|
||||
name_list = []
|
||||
for line in lines:
|
||||
name = line.strip('\n')
|
||||
if name != '':
|
||||
name_list.append(name)
|
||||
return name_list
|
||||
|
||||
|
||||
def main(args):
|
||||
style = args.style
|
||||
repeat_num = 5
|
||||
|
||||
model_id = 'damo/cv_cartoon_stable_diffusion_' + style
|
||||
pipe = pipeline(Tasks.text_to_image_synthesis, model=model_id,
|
||||
model_revision='v1.0.0', torch_dtype=torch.float16)
|
||||
from diffusers.schedulers import EulerAncestralDiscreteScheduler
|
||||
pipe.pipeline.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.pipeline.scheduler.config)
|
||||
print('model init finished!')
|
||||
|
||||
|
||||
save_dir = 'res_style_%s/syn_celeb' % (style)
|
||||
if not os.path.exists(save_dir):
|
||||
os.makedirs(save_dir)
|
||||
|
||||
name_list = load_cele_txt('celeb.txt')
|
||||
person_num = len(name_list)
|
||||
for i in range(person_num):
|
||||
name = name_list[i]
|
||||
print('process %s' % name)
|
||||
|
||||
if style == "clipart":
|
||||
prompt = 'archer style, a portrait painting of %s' % (name)
|
||||
else:
|
||||
prompt = 'sks style, a painting of a %s, no text' % (name)
|
||||
|
||||
images = pipe({'text': prompt, 'num_images_per_prompt': repeat_num})['output_imgs']
|
||||
idx = 0
|
||||
for image in images:
|
||||
outpath = os.path.join(save_dir, '%s_%d.png' % (name, idx))
|
||||
cv2.imwrite(outpath, image)
|
||||
idx += 1
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument('--style', type=str, default='clipart')
|
||||
|
||||
args = parser.parse_args()
|
||||
main(args)
|
||||
|