67 lines
1.4 KiB
Python
67 lines
1.4 KiB
Python
from diffusers import (
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OnnxStableDiffusionPipeline,
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)
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from PIL import Image
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from typing import Callable
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from ..diffusion import (
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get_latents_from_seed,
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load_pipeline,
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)
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from ..image import (
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expand_image,
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mask_filter_none,
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noise_source_histogram,
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)
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from ..params import (
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Border,
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ImageParams,
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Size,
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StageParams,
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)
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from ..utils import (
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base_join,
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is_debug,
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ServerContext,
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)
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from .utils import (
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process_tiles,
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)
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import numpy as np
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def generate_txt2img(
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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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size: Size,
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) -> Image:
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print('generating image using txt2img', params.prompt)
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if source_image is not None:
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print('a source image was passed to a txt2img stage, but will be discarded')
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pipe = load_pipeline(OnnxStableDiffusionPipeline,
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params.model, params.provider, params.scheduler)
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latents = get_latents_from_seed(params.seed, size)
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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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height=size.height,
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width=size.width,
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generator=rng,
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guidance_scale=params.cfg,
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latents=latents,
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negative_prompt=params.negative_prompt,
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num_inference_steps=params.steps,
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)
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output = result.images[0]
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print('final output image size', output.size)
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return output
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