24 lines
653 B
Python
24 lines
653 B
Python
from diffusers import OnnxStableDiffusionPipeline
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from os import path
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import cv2
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import numpy as np
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import onnxruntime as ort
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import torch
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import time
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cfg = 8
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steps = 22
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height = 512
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width = 512
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model = path.join('..', 'models', 'stable-diffusion-onnx-v1-5')
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prompt = 'an astronaut eating a hamburger'
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output = path.join('..', 'outputs', 'test.png')
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print('generating test image...')
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pipe = OnnxStableDiffusionPipeline.from_pretrained(model, provider='DmlExecutionProvider', safety_checker=None)
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image = pipe(prompt, height, width, num_inference_steps=steps, guidance_scale=cfg).images[0]
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image.save(output)
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print('saved test image to %s' % output)
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