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from PIL import Image | |
from deepfloyd_if.modules import IFStageI, IFStageII | |
from deepfloyd_if.modules.t5 import T5Embedder | |
from deepfloyd_if.pipelines import style_transfer | |
# Run locally | |
device = 'cuda' | |
cache_dir = "/path/to/storage/IF" | |
if_I = IFStageI('IF-I-XL-v1.0', device=device, cache_dir=cache_dir) | |
if_II = IFStageII('IF-II-L-v1.0', device=device, cache_dir=cache_dir) | |
t5 = T5Embedder(device=device, cache_dir=cache_dir) | |
# Style generate from GPT-4 | |
style_prompt = [ | |
"in style of colorful and cute kawaii art", | |
"in style of boho-chic textile patterns", | |
] | |
raw_pil_image = Image.open("/path/to/image") | |
result = style_transfer( | |
t5=t5, if_I=if_I, if_II=if_II, | |
support_pil_img=raw_pil_image, | |
style_prompt=style_prompt, | |
seed=42, | |
if_I_kwargs={ | |
"guidance_scale": 10.0, | |
"sample_timestep_respacing": "10,10,10,10,10,10,10,10,0,0", | |
'support_noise_less_qsample_steps': 5, | |
}, | |
if_II_kwargs={ | |
"guidance_scale": 4.0, | |
"sample_timestep_respacing": 'smart50', | |
"support_noise_less_qsample_steps": 5, | |
}, | |
) | |
# save all the images generated in StageII | |
for i, image in enumerate(result["II"]): | |
image.save("./style_transfer_{}.jpg".format(i)) | |