657 lines
24 KiB
Python
657 lines
24 KiB
Python
import base64
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import html
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import io
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import json
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import mimetypes
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import os
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import random
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import sys
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import time
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import traceback
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from PIL import Image
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import gradio as gr
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import gradio.utils
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import gradio.routes
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from modules.paths import script_path
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from modules.shared import opts, cmd_opts
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import modules.shared as shared
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from modules.sd_samplers import samplers, samplers_for_img2img
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import modules.gfpgan_model as gfpgan
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import modules.realesrgan_model as realesrgan
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import modules.scripts
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# this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the bowser will not show any UI
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mimetypes.init()
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mimetypes.add_type('application/javascript', '.js')
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if not cmd_opts.share and not cmd_opts.listen:
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# fix gradio phoning home
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gradio.utils.version_check = lambda: None
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gradio.utils.get_local_ip_address = lambda: '127.0.0.1'
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def gr_show(visible=True):
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return {"visible": visible, "__type__": "update"}
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sample_img2img = "assets/stable-samples/img2img/sketch-mountains-input.jpg"
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sample_img2img = sample_img2img if os.path.exists(sample_img2img) else None
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css_hide_progressbar = """
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.wrap .m-12 svg { display:none!important; }
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.wrap .m-12::before { content:"Loading..." }
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.progress-bar { display:none!important; }
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.meta-text { display:none!important; }
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"""
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def plaintext_to_html(text):
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text = "".join([f"<p>{html.escape(x)}</p>\n" for x in text.split('\n')])
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return text
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def image_from_url_text(filedata):
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if type(filedata) == list:
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if len(filedata) == 0:
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return None
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filedata = filedata[0]
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if filedata.startswith("data:image/png;base64,"):
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filedata = filedata[len("data:image/png;base64,"):]
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filedata = base64.decodebytes(filedata.encode('utf-8'))
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image = Image.open(io.BytesIO(filedata))
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return image
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def send_gradio_gallery_to_image(x):
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if len(x) == 0:
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return None
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return image_from_url_text(x[0])
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def save_files(js_data, images):
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import csv
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os.makedirs(opts.outdir_save, exist_ok=True)
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filenames = []
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data = json.loads(js_data)
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with open(os.path.join(opts.outdir_save, "log.csv"), "a", encoding="utf8", newline='') as file:
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at_start = file.tell() == 0
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writer = csv.writer(file)
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if at_start:
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writer.writerow(["prompt", "seed", "width", "height", "sampler", "cfgs", "steps", "filename"])
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filename_base = str(int(time.time() * 1000))
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for i, filedata in enumerate(images):
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filename = filename_base + ("" if len(images) == 1 else "-" + str(i + 1)) + ".png"
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filepath = os.path.join(opts.outdir_save, filename)
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if filedata.startswith("data:image/png;base64,"):
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filedata = filedata[len("data:image/png;base64,"):]
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with open(filepath, "wb") as imgfile:
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imgfile.write(base64.decodebytes(filedata.encode('utf-8')))
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filenames.append(filename)
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writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler"], data["cfg_scale"], data["steps"], filenames[0]])
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return '', '', plaintext_to_html(f"Saved: {filenames[0]}")
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def wrap_gradio_call(func):
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def f(*args, **kwargs):
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t = time.perf_counter()
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try:
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res = list(func(*args, **kwargs))
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except Exception as e:
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print("Error completing request", file=sys.stderr)
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print("Arguments:", args, kwargs, file=sys.stderr)
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print(traceback.format_exc(), file=sys.stderr)
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res = [None, '', f"<div class='error'>{plaintext_to_html(type(e).__name__+': '+str(e))}</div>"]
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elapsed = time.perf_counter() - t
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# last item is always HTML
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res[-1] = res[-1] + f"<p class='performance'>Time taken: {elapsed:.2f}s</p>"
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shared.state.interrupted = False
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return tuple(res)
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return f
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def check_progress_call():
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if not opts.show_progressbar:
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return ""
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if shared.state.job_count == 0:
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return ""
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progress = shared.state.job_no / shared.state.job_count
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if shared.state.sampling_steps > 0:
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progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps
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progress = min(progress, 1)
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progressbar = f"""<div class='progressDiv'><div class='progress' style="width:{progress * 100}%">{str(int(progress*100))+"%" if progress > 0.01 else ""}</div></div>"""
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return f"<span style='display: none'>{time.time()}</span><p>{progressbar}</p>"
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def roll_artist(prompt):
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allowed_cats = set([x for x in shared.artist_db.categories() if len(opts.random_artist_categories)==0 or x in opts.random_artist_categories])
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artist = random.choice([x for x in shared.artist_db.artists if x.category in allowed_cats])
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return prompt + ", " + artist.name if prompt != '' else artist.name
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def visit(x, func, path=""):
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if hasattr(x, 'children'):
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for c in x.children:
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visit(c, func, path)
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elif x.label is not None:
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func(path + "/" + str(x.label), x)
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def create_ui(txt2img, img2img, run_extras, run_pnginfo):
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with gr.Blocks(analytics_enabled=False) as txt2img_interface:
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with gr.Row():
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prompt = gr.Textbox(label="Prompt", elem_id="txt2img_prompt", show_label=False, placeholder="Prompt", lines=1)
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negative_prompt = gr.Textbox(label="Negative prompt", elem_id="txt2img_negative_prompt", show_label=False, placeholder="Negative prompt", lines=1, visible=False)
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roll = gr.Button('Roll', elem_id="txt2img_roll", visible=len(shared.artist_db.artists) > 0)
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submit = gr.Button('Generate', elem_id="txt2img_generate", variant='primary')
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check_progress = gr.Button('Check progress', elem_id="check_progress", visible=False)
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with gr.Row().style(equal_height=False):
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with gr.Column(variant='panel'):
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steps = gr.Slider(minimum=1, maximum=150, step=1, label="Sampling Steps", value=20)
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sampler_index = gr.Radio(label='Sampling method', elem_id="txt2img_sampling", choices=[x.name for x in samplers], value=samplers[0].name, type="index")
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with gr.Row():
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use_gfpgan = gr.Checkbox(label='GFPGAN', value=False, visible=gfpgan.have_gfpgan)
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tiling = gr.Checkbox(label='Tiling', value=False)
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with gr.Row():
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batch_count = gr.Slider(minimum=1, maximum=cmd_opts.max_batch_count, step=1, label='Batch count', value=1)
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batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1)
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cfg_scale = gr.Slider(minimum=1.0, maximum=15.0, step=0.5, label='CFG Scale', value=7.0)
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with gr.Group():
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height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
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width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
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seed = gr.Number(label='Seed', value=-1)
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with gr.Group():
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custom_inputs = modules.scripts.scripts_txt2img.setup_ui(is_img2img=False)
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with gr.Column(variant='panel'):
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with gr.Group():
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txt2img_gallery = gr.Gallery(label='Output', elem_id='txt2img_gallery')
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with gr.Group():
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with gr.Row():
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save = gr.Button('Save')
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send_to_img2img = gr.Button('Send to img2img')
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send_to_inpaint = gr.Button('Send to inpaint')
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send_to_extras = gr.Button('Send to extras')
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interrupt = gr.Button('Interrupt')
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progressbar = gr.HTML(elem_id="progressbar")
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with gr.Group():
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html_info = gr.HTML()
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generation_info = gr.Textbox(visible=False)
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txt2img_args = dict(
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fn=txt2img,
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_js="submit",
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inputs=[
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prompt,
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negative_prompt,
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steps,
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sampler_index,
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use_gfpgan,
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tiling,
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batch_count,
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batch_size,
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cfg_scale,
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seed,
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height,
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width,
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] + custom_inputs,
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outputs=[
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txt2img_gallery,
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generation_info,
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html_info
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]
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)
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prompt.submit(**txt2img_args)
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submit.click(**txt2img_args)
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check_progress.click(
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fn=check_progress_call,
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inputs=[],
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outputs=[progressbar],
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)
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interrupt.click(
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fn=lambda: shared.state.interrupt(),
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inputs=[],
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outputs=[],
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)
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save.click(
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fn=wrap_gradio_call(save_files),
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inputs=[
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generation_info,
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txt2img_gallery,
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],
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outputs=[
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html_info,
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html_info,
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html_info,
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]
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)
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roll.click(
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fn=roll_artist,
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inputs=[
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prompt,
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],
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outputs=[
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prompt
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]
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)
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with gr.Blocks(analytics_enabled=False) as img2img_interface:
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with gr.Row():
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prompt = gr.Textbox(label="Prompt", elem_id="img2img_prompt", show_label=False, placeholder="Prompt", lines=1)
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submit = gr.Button('Generate', elem_id="img2img_generate", variant='primary')
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check_progress = gr.Button('Check progress', elem_id="check_progress", visible=False)
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with gr.Row().style(equal_height=False):
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with gr.Column(variant='panel'):
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with gr.Group():
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switch_mode = gr.Radio(label='Mode', elem_id="img2img_mode", choices=['Redraw whole image', 'Inpaint a part of image', 'Loopback', 'SD upscale'], value='Redraw whole image', type="index", show_label=False)
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init_img = gr.Image(label="Image for img2img", source="upload", interactive=True, type="pil")
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init_img_with_mask = gr.Image(label="Image for inpainting with mask", elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", visible=False)
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resize_mode = gr.Radio(label="Resize mode", show_label=False, choices=["Just resize", "Crop and resize", "Resize and fill"], type="index", value="Just resize")
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steps = gr.Slider(minimum=1, maximum=150, step=1, label="Sampling Steps", value=20)
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sampler_index = gr.Radio(label='Sampling method', choices=[x.name for x in samplers_for_img2img], value=samplers_for_img2img[0].name, type="index")
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mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, visible=False)
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inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='fill', type="index", visible=False)
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with gr.Row():
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inpaint_full_res = gr.Checkbox(label='Inpaint at full resolution', value=False, visible=False)
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inpainting_mask_invert = gr.Radio(label='Masking mode', choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index", visible=False)
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with gr.Row():
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use_gfpgan = gr.Checkbox(label='GFPGAN', value=False, visible=gfpgan.have_gfpgan)
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tiling = gr.Checkbox(label='Tiling', value=False)
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sd_upscale_overlap = gr.Slider(minimum=0, maximum=256, step=16, label='Tile overlap', value=64, visible=False)
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with gr.Row():
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sd_upscale_upscaler_name = gr.Radio(label='Upscaler', choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index", visible=False)
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with gr.Row():
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batch_count = gr.Slider(minimum=1, maximum=cmd_opts.max_batch_count, step=1, label='Batch count', value=1)
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batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1)
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with gr.Group():
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cfg_scale = gr.Slider(minimum=1.0, maximum=15.0, step=0.5, label='CFG Scale', value=7.0)
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denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising Strength', value=0.75)
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with gr.Group():
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height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
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width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
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seed = gr.Number(label='Seed', value=-1)
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with gr.Group():
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custom_inputs = modules.scripts.scripts_img2img.setup_ui(is_img2img=True)
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with gr.Column(variant='panel'):
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with gr.Group():
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img2img_gallery = gr.Gallery(label='Output', elem_id='img2img_gallery')
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with gr.Group():
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with gr.Row():
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interrupt = gr.Button('Interrupt')
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save = gr.Button('Save')
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img2img_send_to_extras = gr.Button('Send to extras')
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progressbar = gr.HTML(elem_id="progressbar")
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with gr.Group():
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html_info = gr.HTML()
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generation_info = gr.Textbox(visible=False)
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def apply_mode(mode):
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is_classic = mode == 0
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is_inpaint = mode == 1
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is_loopback = mode == 2
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is_upscale = mode == 3
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return {
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init_img: gr_show(not is_inpaint),
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init_img_with_mask: gr_show(is_inpaint),
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mask_blur: gr_show(is_inpaint),
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inpainting_fill: gr_show(is_inpaint),
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batch_count: gr_show(not is_upscale),
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batch_size: gr_show(not is_loopback),
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sd_upscale_upscaler_name: gr_show(is_upscale),
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sd_upscale_overlap: gr_show(is_upscale),
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inpaint_full_res: gr_show(is_inpaint),
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inpainting_mask_invert: gr_show(is_inpaint),
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}
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switch_mode.change(
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apply_mode,
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inputs=[switch_mode],
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outputs=[
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init_img,
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init_img_with_mask,
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mask_blur,
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inpainting_fill,
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batch_count,
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batch_size,
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sd_upscale_upscaler_name,
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sd_upscale_overlap,
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inpaint_full_res,
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inpainting_mask_invert,
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]
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)
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img2img_args = dict(
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fn=img2img,
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_js="submit",
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inputs=[
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prompt,
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init_img,
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init_img_with_mask,
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steps,
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sampler_index,
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mask_blur,
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inpainting_fill,
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use_gfpgan,
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tiling,
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switch_mode,
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batch_count,
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batch_size,
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cfg_scale,
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denoising_strength,
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seed,
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height,
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width,
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resize_mode,
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sd_upscale_upscaler_name,
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sd_upscale_overlap,
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inpaint_full_res,
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inpainting_mask_invert,
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] + custom_inputs,
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outputs=[
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img2img_gallery,
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generation_info,
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html_info
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]
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)
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prompt.submit(**img2img_args)
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submit.click(**img2img_args)
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check_progress.click(
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fn=check_progress_call,
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inputs=[],
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outputs=[progressbar],
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)
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interrupt.click(
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fn=lambda: shared.state.interrupt(),
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inputs=[],
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outputs=[],
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)
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save.click(
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fn=wrap_gradio_call(save_files),
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inputs=[
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generation_info,
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img2img_gallery,
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],
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outputs=[
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html_info,
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html_info,
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html_info,
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]
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)
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send_to_img2img.click(
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fn=lambda x: image_from_url_text(x),
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_js="extract_image_from_gallery",
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inputs=[txt2img_gallery],
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outputs=[init_img],
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)
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send_to_inpaint.click(
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fn=lambda x: image_from_url_text(x),
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_js="extract_image_from_gallery",
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inputs=[txt2img_gallery],
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outputs=[init_img_with_mask],
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)
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with gr.Blocks(analytics_enabled=False) as extras_interface:
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with gr.Row().style(equal_height=False):
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with gr.Column(variant='panel'):
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with gr.Group():
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image = gr.Image(label="Source", source="upload", interactive=True, type="pil")
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upscaling_resize = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Resize", value=2)
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with gr.Group():
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extras_upscaler_1 = gr.Radio(label='Upscaler 1', choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
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with gr.Group():
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extras_upscaler_2 = gr.Radio(label='Upscaler 2', choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
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extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=1)
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with gr.Group():
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gfpgan_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="GFPGAN strength", value=0, interactive=gfpgan.have_gfpgan)
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submit = gr.Button('Generate', elem_id="extras_generate", variant='primary')
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|
|
with gr.Column(variant='panel'):
|
|
result_image = gr.Image(label="Result")
|
|
html_info_x = gr.HTML()
|
|
html_info = gr.HTML()
|
|
|
|
extras_args = dict(
|
|
fn=run_extras,
|
|
inputs=[
|
|
image,
|
|
gfpgan_strength,
|
|
upscaling_resize,
|
|
extras_upscaler_1,
|
|
extras_upscaler_2,
|
|
extras_upscaler_2_visibility,
|
|
],
|
|
outputs=[
|
|
result_image,
|
|
html_info_x,
|
|
html_info,
|
|
]
|
|
)
|
|
|
|
submit.click(**extras_args)
|
|
|
|
send_to_extras.click(
|
|
fn=lambda x: image_from_url_text(x),
|
|
_js="extract_image_from_gallery",
|
|
inputs=[txt2img_gallery],
|
|
outputs=[image],
|
|
)
|
|
|
|
img2img_send_to_extras.click(
|
|
fn=lambda x: image_from_url_text(x),
|
|
_js="extract_image_from_gallery",
|
|
inputs=[img2img_gallery],
|
|
outputs=[image],
|
|
)
|
|
|
|
pnginfo_interface = gr.Interface(
|
|
wrap_gradio_call(run_pnginfo),
|
|
inputs=[
|
|
gr.Image(label="Source", source="upload", interactive=True, type="pil"),
|
|
],
|
|
outputs=[
|
|
gr.HTML(),
|
|
gr.HTML(),
|
|
gr.HTML(),
|
|
],
|
|
allow_flagging="never",
|
|
analytics_enabled=False,
|
|
)
|
|
|
|
def create_setting_component(key):
|
|
def fun():
|
|
return opts.data[key] if key in opts.data else opts.data_labels[key].default
|
|
|
|
info = opts.data_labels[key]
|
|
t = type(info.default)
|
|
|
|
if info.component is not None:
|
|
item = info.component(label=info.label, value=fun, **(info.component_args or {}))
|
|
elif t == str:
|
|
item = gr.Textbox(label=info.label, value=fun, lines=1)
|
|
elif t == int:
|
|
item = gr.Number(label=info.label, value=fun)
|
|
elif t == bool:
|
|
item = gr.Checkbox(label=info.label, value=fun)
|
|
else:
|
|
raise Exception(f'bad options item type: {str(t)} for key {key}')
|
|
|
|
return item
|
|
|
|
def run_settings(*args):
|
|
up = []
|
|
|
|
for key, value, comp in zip(opts.data_labels.keys(), args, settings_interface.input_components):
|
|
opts.data[key] = value
|
|
up.append(comp.update(value=value))
|
|
|
|
opts.save(shared.config_filename)
|
|
|
|
return 'Settings saved.', '', ''
|
|
|
|
settings_interface = gr.Interface(
|
|
run_settings,
|
|
inputs=[create_setting_component(key) for key in opts.data_labels.keys()],
|
|
outputs=[
|
|
gr.Textbox(label='Result'),
|
|
gr.HTML(),
|
|
gr.HTML(),
|
|
],
|
|
title=None,
|
|
description=None,
|
|
allow_flagging="never",
|
|
analytics_enabled=False,
|
|
)
|
|
|
|
interfaces = [
|
|
(txt2img_interface, "txt2img"),
|
|
(img2img_interface, "img2img"),
|
|
(extras_interface, "Extras"),
|
|
(pnginfo_interface, "PNG Info"),
|
|
(settings_interface, "Settings"),
|
|
]
|
|
|
|
with open(os.path.join(script_path, "style.css"), "r", encoding="utf8") as file:
|
|
css = file.read()
|
|
|
|
if not cmd_opts.no_progressbar_hiding:
|
|
css += css_hide_progressbar
|
|
|
|
demo = gr.TabbedInterface(
|
|
interface_list=[x[0] for x in interfaces],
|
|
tab_names=[x[1] for x in interfaces],
|
|
analytics_enabled=False,
|
|
css=css,
|
|
)
|
|
|
|
ui_config_file = os.path.join(modules.paths.script_path, 'ui-config.json')
|
|
ui_settings = {}
|
|
settings_count = len(ui_settings)
|
|
error_loading = False
|
|
|
|
try:
|
|
if os.path.exists(ui_config_file):
|
|
with open(ui_config_file, "r", encoding="utf8") as file:
|
|
ui_settings = json.load(file)
|
|
except Exception:
|
|
error_loading = True
|
|
print("Error loading settings:", file=sys.stderr)
|
|
print(traceback.format_exc(), file=sys.stderr)
|
|
|
|
def loadsave(path, x):
|
|
def apply_field(obj, field, condition=None):
|
|
key = path + "/" + field
|
|
|
|
saved_value = ui_settings.get(key, None)
|
|
if saved_value is None:
|
|
ui_settings[key] = getattr(obj, field)
|
|
elif condition is None or condition(saved_value):
|
|
setattr(obj, field, saved_value)
|
|
|
|
if type(x) == gr.Slider:
|
|
apply_field(x, 'value')
|
|
apply_field(x, 'minimum')
|
|
apply_field(x, 'maximum')
|
|
apply_field(x, 'step')
|
|
|
|
if type(x) == gr.Radio:
|
|
apply_field(x, 'value', lambda val: val in x.choices)
|
|
|
|
visit(txt2img_interface, loadsave, "txt2img")
|
|
visit(img2img_interface, loadsave, "img2img")
|
|
|
|
if not error_loading and (not os.path.exists(ui_config_file) or settings_count != len(ui_settings)):
|
|
with open(ui_config_file, "w", encoding="utf8") as file:
|
|
json.dump(ui_settings, file, indent=4)
|
|
|
|
return demo
|
|
|
|
|
|
with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile:
|
|
javascript = jsfile.read()
|
|
|
|
|
|
def template_response(*args, **kwargs):
|
|
res = gradio_routes_templates_response(*args, **kwargs)
|
|
res.body = res.body.replace(b'</head>', f'<script>{javascript}</script></head>'.encode("utf8"))
|
|
res.init_headers()
|
|
return res
|
|
|
|
|
|
gradio_routes_templates_response = gradio.routes.templates.TemplateResponse
|
|
gradio.routes.templates.TemplateResponse = template_response
|