| 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) | |