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from PIL import Image | |
import numpy as np | |
from modules import scripts_postprocessing, codeformer_model, ui_components | |
import gradio as gr | |
class ScriptPostprocessingCodeFormer(scripts_postprocessing.ScriptPostprocessing): | |
name = "CodeFormer" | |
order = 3000 | |
def ui(self): | |
with ui_components.InputAccordion(False, label="CodeFormer") as enable: | |
with gr.Row(): | |
codeformer_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Visibility", value=1.0, elem_id="extras_codeformer_visibility") | |
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") | |
return { | |
"enable": enable, | |
"codeformer_visibility": codeformer_visibility, | |
"codeformer_weight": codeformer_weight, | |
} | |
def process(self, pp: scripts_postprocessing.PostprocessedImage, enable, codeformer_visibility, codeformer_weight): | |
if codeformer_visibility == 0 or not enable: | |
return | |
restored_img = codeformer_model.codeformer.restore(np.array(pp.image, dtype=np.uint8), w=codeformer_weight) | |
res = Image.fromarray(restored_img) | |
if codeformer_visibility < 1.0: | |
res = Image.blend(pp.image, res, codeformer_visibility) | |
pp.image = res | |
pp.info["CodeFormer visibility"] = round(codeformer_visibility, 3) | |
pp.info["CodeFormer weight"] = round(codeformer_weight, 3) | |