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from PIL import Image
import numpy as np
from diffusers import DEISMultistepScheduler
from pipeline_onnx_stable_diffusion_controlnet import OnnxStableDiffusionControlNetPipeline
import onnxruntime as ort
pose_image = Image.open(r"dance_pose.png")
opts = ort.SessionOptions()
opts.enable_cpu_mem_arena = False
opts.enable_mem_pattern = False
pipe = OnnxStableDiffusionControlNetPipeline.from_pretrained(
"model/anyv3-fp16-autoslicing-cn_openpose",
sess_options=opts,
provider="DmlExecutionProvider",
)
pipe.scheduler = DEISMultistepScheduler.from_config(pipe.scheduler.config)
prompt = "1girl, blonde, long dress, dancing, best quality"
seed=25
generator = np.random.RandomState(seed)
images = pipe(
prompt,
pose_image,
width=512,
height=512,
negative_prompt="monochrome, lowres, bad anatomy, worst quality, low quality",
num_inference_steps=30,
generator=generator,
).images[0]
images.save("controlnet-openpose-test.png")
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