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import torch | |
import requests | |
from PIL import Image | |
from diffusers import DiffusionPipeline, EulerAncestralDiscreteScheduler | |
# Load the pipeline | |
pipeline = DiffusionPipeline.from_pretrained( | |
"sudo-ai/zero123plus-v1.1", custom_pipeline="sudo-ai/zero123plus-pipeline", | |
torch_dtype=torch.float16 | |
) | |
# Feel free to tune the scheduler | |
pipeline.scheduler = EulerAncestralDiscreteScheduler.from_config( | |
pipeline.scheduler.config, timestep_spacing='trailing' | |
) | |
pipeline.to('cuda:0') | |
# Run the pipeline | |
cond = Image.open(requests.get("https://d.skis.ltd/nrp/sample-data/lysol.png", stream=True).raw) | |
result = pipeline(cond, num_inference_steps=75).images[0] | |
result.show() | |
result.save("output.png") | |