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onnx-web/api/onnx_web/diffusion/run.py

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from diffusers import (
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OnnxStableDiffusionPipeline,
OnnxStableDiffusionImg2ImgPipeline,
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)
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from logging import getLogger
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from PIL import Image, ImageChops
from typing import Any
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from ..chain import (
upscale_outpaint,
)
from ..params import (
ImageParams,
Border,
Size,
StageParams,
)
from ..output import (
save_image,
save_params,
)
from ..upscale import (
run_upscale_correction,
UpscaleParams,
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)
from ..utils import (
run_gc,
ServerContext,
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)
from .load import (
get_latents_from_seed,
load_pipeline,
)
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import numpy as np
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logger = getLogger(__name__)
def run_txt2img_pipeline(
ctx: ServerContext,
params: ImageParams,
size: Size,
output: str,
upscale: UpscaleParams
) -> None:
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pipe = load_pipeline(OnnxStableDiffusionPipeline,
params.model, params.provider, params.scheduler)
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latents = get_latents_from_seed(params.seed, size)
rng = np.random.RandomState(params.seed)
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result = pipe(
params.prompt,
height=size.height,
width=size.width,
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generator=rng,
guidance_scale=params.cfg,
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latents=latents,
negative_prompt=params.negative_prompt,
num_inference_steps=params.steps,
)
image = result.images[0]
image = run_upscale_correction(
ctx, StageParams(), params, image, upscale=upscale)
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dest = save_image(ctx, output, image)
save_params(ctx, output, params, size, upscale=upscale)
del image
del result
run_gc()
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logger.info('finished txt2img job: %s', dest)
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def run_img2img_pipeline(
ctx: ServerContext,
params: ImageParams,
output: str,
upscale: UpscaleParams,
source_image: Image.Image,
strength: float,
) -> None:
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pipe = load_pipeline(OnnxStableDiffusionImg2ImgPipeline,
params.model, params.provider, params.scheduler)
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rng = np.random.RandomState(params.seed)
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result = pipe(
params.prompt,
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generator=rng,
guidance_scale=params.cfg,
image=source_image,
negative_prompt=params.negative_prompt,
num_inference_steps=params.steps,
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strength=strength,
)
image = result.images[0]
image = run_upscale_correction(
ctx, StageParams(), params, image, upscale=upscale)
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dest = save_image(ctx, output, image)
size = Size(*source_image.size)
save_params(ctx, output, params, size, upscale=upscale)
del image
del result
run_gc()
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logger.info('finished img2img job: %s', dest)
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def run_inpaint_pipeline(
ctx: ServerContext,
params: ImageParams,
size: Size,
output: str,
upscale: UpscaleParams,
source_image: Image.Image,
mask_image: Image.Image,
border: Border,
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noise_source: Any,
mask_filter: Any,
strength: float,
fill_color: str,
) -> None:
stage = StageParams()
image = upscale_outpaint(
ctx,
stage,
params,
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source_image,
border=border,
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mask_image=mask_image,
fill_color=fill_color,
mask_filter=mask_filter,
noise_source=noise_source,
)
logger.info('applying mask filter and generating noise source')
if image.size == source_image.size:
image = ImageChops.blend(source_image, image, strength)
else:
logger.info(
'output image size does not match source, skipping post-blend')
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image = run_upscale_correction(
ctx, stage, params, image, upscale=upscale)
dest = save_image(ctx, output, image)
save_params(ctx, output, params, size, upscale=upscale, border=border)
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del image
run_gc()
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logger.info('finished inpaint job: %s', dest)
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def run_upscale_pipeline(
ctx: ServerContext,
params: ImageParams,
size: Size,
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output: str,
upscale: UpscaleParams,
source_image: Image.Image,
) -> None:
image = run_upscale_correction(
ctx, StageParams(), params, source_image, upscale=upscale)
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dest = save_image(ctx, output, image)
save_params(ctx, output, params, size, upscale=upscale)
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del image
run_gc()
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logger.info('finished upscale job: %s', dest)