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https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
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37 lines
1.5 KiB
Python
37 lines
1.5 KiB
Python
from PIL import Image
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import numpy as np
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from modules import scripts_postprocessing, codeformer_model, ui_components
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import gradio as gr
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class ScriptPostprocessingCodeFormer(scripts_postprocessing.ScriptPostprocessing):
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name = "CodeFormer"
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order = 3000
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def ui(self):
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with ui_components.InputAccordion(False, label="CodeFormer") as enable:
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with gr.Row():
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codeformer_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Visibility", value=1.0, elem_id="extras_codeformer_visibility")
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codeformer_weight = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Weight (0 = maximum effect, 1 = minimum effect)", value=0, elem_id="extras_codeformer_weight")
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return {
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"enable": enable,
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"codeformer_visibility": codeformer_visibility,
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"codeformer_weight": codeformer_weight,
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}
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def process(self, pp: scripts_postprocessing.PostprocessedImage, enable, codeformer_visibility, codeformer_weight):
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if codeformer_visibility == 0 or not enable:
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return
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restored_img = codeformer_model.codeformer.restore(np.array(pp.image.convert("RGB"), dtype=np.uint8), w=codeformer_weight)
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res = Image.fromarray(restored_img)
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if codeformer_visibility < 1.0:
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res = Image.blend(pp.image, res, codeformer_visibility)
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pp.image = res
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pp.info["CodeFormer visibility"] = round(codeformer_visibility, 3)
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pp.info["CodeFormer weight"] = round(codeformer_weight, 3)
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