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diffusion_webui/__init__.py
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__version__ = "
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__version__ = "2.0.1"
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diffusion_webui/diffusion_models/stable_diffusion/text2img_app.py
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from diffusers import StableDiffusionPipeline
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from diffusion_webui.utils.model_list import stable_model_list
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from diffusion_webui.utils.scheduler_list import
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class StableDiffusionText2ImageGenerator:
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with gr.Column():
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text2image_scheduler = gr.Dropdown(
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choices=
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"EulerA",
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"Euler",
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"LMS",
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"Heun",
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],
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value="DDIM",
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label="Scheduler",
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)
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from diffusers import StableDiffusionPipeline
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from diffusion_webui.utils.model_list import stable_model_list
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from diffusion_webui.utils.scheduler_list import (
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SCHEDULER_LIST,
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get_scheduler_list,
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)
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class StableDiffusionText2ImageGenerator:
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with gr.Column():
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text2image_scheduler = gr.Dropdown(
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choices=SCHEDULER_LIST,
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value=SCHEDULER_LIST[0],
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label="Scheduler",
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)
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diffusion_webui/upscaler_models/codeformer_upscaler.py
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upscale: int,
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codeformer_fidelity: int,
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):
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pipe = inference_app(
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return [pipe]
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upscale: int,
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codeformer_fidelity: int,
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):
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pipe = inference_app(
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image=image_path,
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background_enhance=background_enhance,
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face_upsample=face_upsample,
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upscale=upscale,
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codeformer_fidelity=codeformer_fidelity,
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)
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return [pipe]
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diffusion_webui/utils/data_utils.py
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from PIL import Image
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def image_grid(imgs, rows, cols):
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assert len(imgs) == rows * cols
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w, h = imgs[0].size
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grid = Image.new("RGB", size=(cols * w, rows * h))
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for i, img in enumerate(imgs):
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grid.paste(img, box=(i % cols * w, i // cols * h))
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return grid
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diffusion_webui/utils/model_list.py
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"runwayml/stable-diffusion-v1-5",
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"stabilityai/stable-diffusion-2-1",
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"prompthero/openjourney-v4",
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]
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controlnet_canny_model_list = [
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"runwayml/stable-diffusion-v1-5",
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"stabilityai/stable-diffusion-2-1",
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"prompthero/openjourney-v4",
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"wavymulder/Analog-Diffusion",
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"dreamlike-art/dreamlike-diffusion-1.0",
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"gsdf/Counterfeit-V2.5",
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"dreamlike-art/dreamlike-photoreal-2.0"
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]
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controlnet_canny_model_list = [
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