52 lines
1.1 KiB
Python
52 lines
1.1 KiB
Python
from diffusers import (
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OnnxStableDiffusionImg2ImgPipeline,
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)
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from logging import getLogger
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from PIL import Image
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from ..diffusion import (
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load_pipeline,
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)
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from ..params import (
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ImageParams,
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StageParams,
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)
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from ..utils import (
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ServerContext,
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)
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import numpy as np
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logger = getLogger(__name__)
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def blend_img2img(
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_ctx: ServerContext,
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_stage: StageParams,
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params: ImageParams,
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source_image: Image.Image,
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*,
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strength: float,
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) -> Image.Image:
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logger.info('generating image using img2img', params.prompt)
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pipe = load_pipeline(OnnxStableDiffusionImg2ImgPipeline,
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params.model, params.provider, params.scheduler)
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rng = np.random.RandomState(params.seed)
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result = pipe(
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params.prompt,
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generator=rng,
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guidance_scale=params.cfg,
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image=source_image,
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negative_prompt=params.negative_prompt,
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num_inference_steps=params.steps,
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strength=strength,
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)
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output = result.images[0]
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logger.info('final output image size', output.size)
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return output
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