[Feature Request] Save defaults for extras & keep image parameters after using extras #251
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AUTOMATIC
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2e6153e343
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f185874418
4 changed files with 94 additions and 83 deletions
87
modules/extras.py
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87
modules/extras.py
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@ -0,0 +1,87 @@
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import numpy as np
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from PIL import Image
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from modules import processing, shared, images
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from modules.shared import opts
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import modules.gfpgan_model
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from modules.ui import plaintext_to_html
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import modules.codeformer_model
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cached_images = {}
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def run_extras(image, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility):
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processing.torch_gc()
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image = image.convert("RGB")
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info = ""
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outpath = opts.outdir_samples or opts.outdir_extras_samples
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if gfpgan_visibility > 0:
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restored_img = modules.gfpgan_model.gfpgan_fix_faces(np.array(image, dtype=np.uint8))
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res = Image.fromarray(restored_img)
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if gfpgan_visibility < 1.0:
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res = Image.blend(image, res, gfpgan_visibility)
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info += f"GFPGAN visibility:{round(gfpgan_visibility, 2)}\n"
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image = res
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if codeformer_visibility > 0:
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restored_img = modules.codeformer_model.codeformer.restore(np.array(image, 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(image, res, codeformer_visibility)
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info += f"CodeFormer w: {round(codeformer_weight, 2)}, CodeFormer visibility:{round(codeformer_visibility)}\n"
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image = res
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if upscaling_resize != 1.0:
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def upscale(image, scaler_index, resize):
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small = image.crop((image.width // 2, image.height // 2, image.width // 2 + 10, image.height // 2 + 10))
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pixels = tuple(np.array(small).flatten().tolist())
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key = (resize, scaler_index, image.width, image.height, gfpgan_visibility, codeformer_visibility, codeformer_weight) + pixels
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c = cached_images.get(key)
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if c is None:
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upscaler = shared.sd_upscalers[scaler_index]
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c = upscaler.upscale(image, image.width * resize, image.height * resize)
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cached_images[key] = c
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return c
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info += f"Upscale: {round(upscaling_resize, 3)}, model:{shared.sd_upscalers[extras_upscaler_1].name}\n"
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res = upscale(image, extras_upscaler_1, upscaling_resize)
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if extras_upscaler_2 != 0 and extras_upscaler_2_visibility > 0:
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res2 = upscale(image, extras_upscaler_2, upscaling_resize)
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info += f"Upscale: {round(upscaling_resize, 3)}, visibility: {round(extras_upscaler_2_visibility, 3)}, model:{shared.sd_upscalers[extras_upscaler_2].name}\n"
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res = Image.blend(res, res2, extras_upscaler_2_visibility)
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image = res
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while len(cached_images) > 2:
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del cached_images[next(iter(cached_images.keys()))]
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images.save_image(image, outpath, "", None, info=info, extension=opts.samples_format, short_filename=True, no_prompt=True, pnginfo_section_name="extras")
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return image, plaintext_to_html(info), ''
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def run_pnginfo(image):
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info = ''
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for key, text in image.info.items():
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info += f"""
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<div>
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<p><b>{plaintext_to_html(str(key))}</b></p>
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<p>{plaintext_to_html(str(text))}</p>
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</div>
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""".strip()+"\n"
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if len(info) == 0:
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message = "Nothing found in the image."
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info = f"<div><p>{message}<p></div>"
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return '', '', info
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@ -243,7 +243,7 @@ def sanitize_filename_part(text):
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return text.replace(' ', '_').translate({ord(x): '' for x in invalid_filename_chars})[:128]
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def save_image(image, path, basename, seed=None, prompt=None, extension='png', info=None, short_filename=False, no_prompt=False):
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def save_image(image, path, basename, seed=None, prompt=None, extension='png', info=None, short_filename=False, no_prompt=False, pnginfo_section_name='parameters'):
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# would be better to add this as an argument in future, but will do for now
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is_a_grid = basename != ""
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@ -256,7 +256,7 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i
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if extension == 'png' and opts.enable_pnginfo and info is not None:
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pnginfo = PngImagePlugin.PngInfo()
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pnginfo.add_text("parameters", info)
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pnginfo.add_text(pnginfo_section_name, info)
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else:
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pnginfo = None
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@ -797,6 +797,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
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visit(txt2img_interface, loadsave, "txt2img")
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visit(img2img_interface, loadsave, "img2img")
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visit(extras_interface, loadsave, "extras")
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if not error_loading and (not os.path.exists(ui_config_file) or settings_count != len(ui_settings)):
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with open(ui_config_file, "w", encoding="utf8") as file:
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85
webui.py
85
webui.py
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@ -4,9 +4,7 @@ import threading
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from modules.paths import script_path
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import torch
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import numpy as np
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from omegaconf import OmegaConf
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from PIL import Image
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import signal
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@ -15,16 +13,14 @@ from ldm.util import instantiate_from_config
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from modules.shared import opts, cmd_opts, state
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import modules.shared as shared
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import modules.ui
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from modules.ui import plaintext_to_html
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import modules.scripts
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import modules.processing as processing
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import modules.sd_hijack
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import modules.codeformer_model
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import modules.gfpgan_model
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import modules.face_restoration
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import modules.realesrgan_model as realesrgan
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import modules.esrgan_model as esrgan
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import modules.images as images
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import modules.extras
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import modules.lowvram
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import modules.txt2img
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import modules.img2img
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@ -56,80 +52,6 @@ def load_model_from_config(config, ckpt, verbose=False):
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model.eval()
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return model
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cached_images = {}
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def run_extras(image, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility):
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processing.torch_gc()
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image = image.convert("RGB")
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outpath = opts.outdir_samples or opts.outdir_extras_samples
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if gfpgan_visibility > 0:
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restored_img = modules.gfpgan_model.gfpgan_fix_faces(np.array(image, dtype=np.uint8))
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res = Image.fromarray(restored_img)
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if gfpgan_visibility < 1.0:
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res = Image.blend(image, res, gfpgan_visibility)
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image = res
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if codeformer_visibility > 0:
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restored_img = modules.codeformer_model.codeformer.restore(np.array(image, 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(image, res, codeformer_visibility)
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image = res
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if upscaling_resize != 1.0:
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def upscale(image, scaler_index, resize):
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small = image.crop((image.width // 2, image.height // 2, image.width // 2 + 10, image.height // 2 + 10))
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pixels = tuple(np.array(small).flatten().tolist())
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key = (resize, scaler_index, image.width, image.height, gfpgan_visibility, codeformer_visibility, codeformer_weight) + pixels
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c = cached_images.get(key)
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if c is None:
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upscaler = shared.sd_upscalers[scaler_index]
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c = upscaler.upscale(image, image.width * resize, image.height * resize)
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cached_images[key] = c
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return c
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res = upscale(image, extras_upscaler_1, upscaling_resize)
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if extras_upscaler_2 != 0 and extras_upscaler_2_visibility>0:
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res2 = upscale(image, extras_upscaler_2, upscaling_resize)
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res = Image.blend(res, res2, extras_upscaler_2_visibility)
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image = res
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while len(cached_images) > 2:
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del cached_images[next(iter(cached_images.keys()))]
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images.save_image(image, outpath, "", None, '', opts.samples_format, short_filename=True, no_prompt=True)
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return image, '', ''
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def run_pnginfo(image):
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info = ''
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for key, text in image.info.items():
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info += f"""
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<div>
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<p><b>{plaintext_to_html(str(key))}</b></p>
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<p>{plaintext_to_html(str(text))}</p>
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</div>
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""".strip()+"\n"
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if len(info) == 0:
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message = "Nothing found in the image."
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info = f"<div><p>{message}<p></div>"
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return '', '', info
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queue_lock = threading.Lock()
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@ -153,6 +75,7 @@ def wrap_gradio_gpu_call(func):
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return modules.ui.wrap_gradio_call(f)
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modules.scripts.load_scripts(os.path.join(script_path, "scripts"))
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try:
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@ -187,8 +110,8 @@ def webui():
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demo = modules.ui.create_ui(
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txt2img=wrap_gradio_gpu_call(modules.txt2img.txt2img),
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img2img=wrap_gradio_gpu_call(modules.img2img.img2img),
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run_extras=wrap_gradio_gpu_call(run_extras),
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run_pnginfo=run_pnginfo
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run_extras=wrap_gradio_gpu_call(modules.extras.run_extras),
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run_pnginfo=modules.extras.run_pnginfo
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)
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demo.launch(share=cmd_opts.share, server_name="0.0.0.0" if cmd_opts.listen else None, server_port=cmd_opts.port)
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