Merge branch 'master' of github.com:AUTOMATIC1111/stable-diffusion-webui into gamepad

1 files changed, 675 insertions, 722 deletions

diff --git a/modules/ui.py b/modules/ui.py
index 57ee0465..9f4cfda1 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -5,12 +5,12 @@ import mimetypes
 import os

 import platform

 import random

-import subprocess as sp

 import sys

 import tempfile

 import time

 import traceback

 from functools import partial, reduce

+import warnings

 

 import gradio as gr

 import gradio.routes

@@ -19,8 +19,9 @@ import numpy as np
 from PIL import Image, PngImagePlugin

 from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call

 

-from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru

-from modules.paths import script_path

+from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, postprocessing, ui_components, ui_common, ui_postprocessing

+from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML

+from modules.paths import script_path, data_path

 

 from modules.shared import opts, cmd_opts, restricted_opts

 

@@ -36,9 +37,12 @@ from modules import prompt_parser
 from modules.images import save_image

 from modules.sd_hijack import model_hijack

 from modules.sd_samplers import samplers, samplers_for_img2img

-import modules.textual_inversion.ui

+from modules.textual_inversion import textual_inversion

 import modules.hypernetworks.ui

 from modules.generation_parameters_copypaste import image_from_url_text

+import modules.extras

+

+warnings.filterwarnings("default" if opts.show_warnings else "ignore", category=UserWarning)

 

 # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI

 mimetypes.init()

@@ -71,6 +75,7 @@ css_hide_progressbar = """
 .wrap .m-12::before { content:"Loading..." }

 .wrap .z-20 svg { display:none!important; }

 .wrap .z-20::before { content:"Loading..." }

+.wrap.cover-bg .z-20::before { content:"" }

 .progress-bar { display:none!important; }

 .meta-text { display:none!important; }

 .meta-text-center { display:none!important; }

@@ -80,167 +85,24 @@ css_hide_progressbar = """
 # Important that they exactly match script.js for tooltip to work.

 random_symbol = '\U0001f3b2\ufe0f'  # 🎲️

 reuse_symbol = '\u267b\ufe0f'  # ♻️

-art_symbol = '\U0001f3a8'  # 🎨

 paste_symbol = '\u2199\ufe0f'  # ↙

-folder_symbol = '\U0001f4c2'  # 📂

 refresh_symbol = '\U0001f504'  # 🔄

 save_style_symbol = '\U0001f4be'  # 💾

 apply_style_symbol = '\U0001f4cb'  # 📋

 clear_prompt_symbol = '\U0001F5D1'  # 🗑️

+extra_networks_symbol = '\U0001F3B4'  # 🎴

+switch_values_symbol = '\U000021C5' # ⇅

 

 

 def plaintext_to_html(text):

-    text = "<p>" + "<br>\n".join([f"{html.escape(x)}" for x in text.split('\n')]) + "</p>"

-    return text

+    return ui_common.plaintext_to_html(text)

+

 

 def send_gradio_gallery_to_image(x):

     if len(x) == 0:

         return None

     return image_from_url_text(x[0])

 

-def save_files(js_data, images, do_make_zip, index):

-    import csv

-    filenames = []

-    fullfns = []

-

-    #quick dictionary to class object conversion. Its necessary due apply_filename_pattern requiring it

-    class MyObject:

-        def __init__(self, d=None):

-            if d is not None:

-                for key, value in d.items():

-                    setattr(self, key, value)

-

-    data = json.loads(js_data)

-

-    p = MyObject(data)

-    path = opts.outdir_save

-    save_to_dirs = opts.use_save_to_dirs_for_ui

-    extension: str = opts.samples_format

-    start_index = 0

-

-    if index > -1 and opts.save_selected_only and (index >= data["index_of_first_image"]):  # ensures we are looking at a specific non-grid picture, and we have save_selected_only

-

-        images = [images[index]]

-        start_index = index

-

-    os.makedirs(opts.outdir_save, exist_ok=True)

-

-    with open(os.path.join(opts.outdir_save, "log.csv"), "a", encoding="utf8", newline='') as file:

-        at_start = file.tell() == 0

-        writer = csv.writer(file)

-        if at_start:

-            writer.writerow(["prompt", "seed", "width", "height", "sampler", "cfgs", "steps", "filename", "negative_prompt"])

-

-        for image_index, filedata in enumerate(images, start_index):

-            image = image_from_url_text(filedata)

-

-            is_grid = image_index < p.index_of_first_image

-            i = 0 if is_grid else (image_index - p.index_of_first_image)

-

-            fullfn, txt_fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)

-

-            filename = os.path.relpath(fullfn, path)

-            filenames.append(filename)

-            fullfns.append(fullfn)

-            if txt_fullfn:

-                filenames.append(os.path.basename(txt_fullfn))

-                fullfns.append(txt_fullfn)

-

-        writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler_name"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]])

-

-    # Make Zip

-    if do_make_zip:

-        zip_filepath = os.path.join(path, "images.zip")

-

-        from zipfile import ZipFile

-        with ZipFile(zip_filepath, "w") as zip_file:

-            for i in range(len(fullfns)):

-                with open(fullfns[i], mode="rb") as f:

-                    zip_file.writestr(filenames[i], f.read())

-        fullfns.insert(0, zip_filepath)

-

-    return gr.File.update(value=fullfns, visible=True), '', '', plaintext_to_html(f"Saved: {filenames[0]}")

-

-

-

-

-def calc_time_left(progress, threshold, label, force_display):

-    if progress == 0:

-        return ""

-    else:

-        time_since_start = time.time() - shared.state.time_start

-        eta = (time_since_start/progress)

-        eta_relative = eta-time_since_start

-        if (eta_relative > threshold and progress > 0.02) or force_display:

-            if eta_relative > 3600:

-                return label + time.strftime('%H:%M:%S', time.gmtime(eta_relative))

-            elif eta_relative > 60:

-                return label + time.strftime('%M:%S',  time.gmtime(eta_relative))

-            else:

-                return label + time.strftime('%Ss',  time.gmtime(eta_relative))

-        else:

-            return ""

-

-

-def check_progress_call(id_part):

-    if shared.state.job_count == 0:

-        return "", gr_show(False), gr_show(False), gr_show(False)

-

-    progress = 0

-

-    if shared.state.job_count > 0:

-        progress += shared.state.job_no / shared.state.job_count

-    if shared.state.sampling_steps > 0:

-        progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps

-

-    time_left = calc_time_left( progress, 1, " ETA: ", shared.state.time_left_force_display )

-    if time_left != "":

-        shared.state.time_left_force_display = True

-

-    progress = min(progress, 1)

-

-    progressbar = ""

-    if opts.show_progressbar:

-        progressbar = f"""<div class='progressDiv'><div class='progress' style="overflow:visible;width:{progress * 100}%;white-space:nowrap;">{"&nbsp;" * 2 + str(int(progress*100))+"%" + time_left if progress > 0.01 else ""}</div></div>"""

-

-    image = gr_show(False)

-    preview_visibility = gr_show(False)

-

-    if opts.show_progress_every_n_steps != 0:

-        shared.state.set_current_image()

-        image = shared.state.current_image

-

-        if image is None:

-            image = gr.update(value=None)

-        else:

-            preview_visibility = gr_show(True)

-

-    if shared.state.textinfo is not None:

-        textinfo_result = gr.HTML.update(value=shared.state.textinfo, visible=True)

-    else:

-        textinfo_result = gr_show(False)

-

-    return f"<span id='{id_part}_progress_span' style='display: none'>{time.time()}</span><p>{progressbar}</p>", preview_visibility, image, textinfo_result

-

-

-def check_progress_call_initial(id_part):

-    shared.state.job_count = -1

-    shared.state.current_latent = None

-    shared.state.current_image = None

-    shared.state.textinfo = None

-    shared.state.time_start = time.time()

-    shared.state.time_left_force_display = False

-

-    return check_progress_call(id_part)

-

-

-def roll_artist(prompt):

-    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])

-    artist = random.choice([x for x in shared.artist_db.artists if x.category in allowed_cats])

-

-    return prompt + ", " + artist.name if prompt != '' else artist.name

-

-

 def visit(x, func, path=""):

     if hasattr(x, 'children'):

         for c in x.children:

@@ -259,56 +121,88 @@ def add_style(name: str, prompt: str, negative_prompt: str):
     # reserialize all styles every time we save them

     shared.prompt_styles.save_styles(shared.styles_filename)

 

-    return [gr.Dropdown.update(visible=True, choices=list(shared.prompt_styles.styles)) for _ in range(4)]

+    return [gr.Dropdown.update(visible=True, choices=list(shared.prompt_styles.styles)) for _ in range(2)]

 

 

-def apply_styles(prompt, prompt_neg, style1_name, style2_name):

-    prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, [style1_name, style2_name])

-    prompt_neg = shared.prompt_styles.apply_negative_styles_to_prompt(prompt_neg, [style1_name, style2_name])

+def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resize_y):

+    from modules import processing, devices

+

+    if not enable:

+        return ""

 

-    return [gr.Textbox.update(value=prompt), gr.Textbox.update(value=prompt_neg), gr.Dropdown.update(value="None"), gr.Dropdown.update(value="None")]

+    p = processing.StableDiffusionProcessingTxt2Img(width=width, height=height, enable_hr=True, hr_scale=hr_scale, hr_resize_x=hr_resize_x, hr_resize_y=hr_resize_y)

+

+    with devices.autocast():

+        p.init([""], [0], [0])

+

+    return f"resize: from <span class='resolution'>{p.width}x{p.height}</span> to <span class='resolution'>{p.hr_resize_x or p.hr_upscale_to_x}x{p.hr_resize_y or p.hr_upscale_to_y}</span>"

+

+

+def apply_styles(prompt, prompt_neg, styles):

+    prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, styles)

+    prompt_neg = shared.prompt_styles.apply_negative_styles_to_prompt(prompt_neg, styles)

+

+    return [gr.Textbox.update(value=prompt), gr.Textbox.update(value=prompt_neg), gr.Dropdown.update(value=[])]

+

+

+def process_interrogate(interrogation_function, mode, ii_input_dir, ii_output_dir, *ii_singles):

+    if mode in {0, 1, 3, 4}:

+        return [interrogation_function(ii_singles[mode]), None]

+    elif mode == 2:

+        return [interrogation_function(ii_singles[mode]["image"]), None]

+    elif mode == 5:

+        assert not shared.cmd_opts.hide_ui_dir_config, "Launched with --hide-ui-dir-config, batch img2img disabled"

+        images = shared.listfiles(ii_input_dir)

+        print(f"Will process {len(images)} images.")

+        if ii_output_dir != "":

+            os.makedirs(ii_output_dir, exist_ok=True)

+        else:

+            ii_output_dir = ii_input_dir

+

+        for image in images:

+            img = Image.open(image)

+            filename = os.path.basename(image)

+            left, _ = os.path.splitext(filename)

+            print(interrogation_function(img), file=open(os.path.join(ii_output_dir, left + ".txt"), 'a'))

+

+        return [gr.update(), None]

 

 

 def interrogate(image):

     prompt = shared.interrogator.interrogate(image.convert("RGB"))

-

-    return gr_show(True) if prompt is None else prompt

+    return gr.update() if prompt is None else prompt

 

 

 def interrogate_deepbooru(image):

     prompt = deepbooru.model.tag(image)

-    return gr_show(True) if prompt is None else prompt

+    return gr.update() if prompt is None else prompt

 

 

-def create_seed_inputs():

-    with gr.Row():

-        with gr.Box():

-            with gr.Row(elem_id='seed_row'):

-                seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1)

-                seed.style(container=False)

-                random_seed = gr.Button(random_symbol, elem_id='random_seed')

-                reuse_seed = gr.Button(reuse_symbol, elem_id='reuse_seed')

+def create_seed_inputs(target_interface):

+    with FormRow(elem_id=target_interface + '_seed_row'):

+        seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1, elem_id=target_interface + '_seed')

+        seed.style(container=False)

+        random_seed = gr.Button(random_symbol, elem_id=target_interface + '_random_seed')

+        reuse_seed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_seed')

 

-        with gr.Box(elem_id='subseed_show_box'):

-            seed_checkbox = gr.Checkbox(label='Extra', elem_id='subseed_show', value=False)

+        with gr.Group(elem_id=target_interface + '_subseed_show_box'):

+            seed_checkbox = gr.Checkbox(label='Extra', elem_id=target_interface + '_subseed_show', value=False)

 

     # Components to show/hide based on the 'Extra' checkbox

     seed_extras = []

 

-    with gr.Row(visible=False) as seed_extra_row_1:

+    with FormRow(visible=False, elem_id=target_interface + '_subseed_row') as seed_extra_row_1:

         seed_extras.append(seed_extra_row_1)

-        with gr.Box():

-            with gr.Row(elem_id='subseed_row'):

-                subseed = gr.Number(label='Variation seed', value=-1)

-                subseed.style(container=False)

-                random_subseed = gr.Button(random_symbol, elem_id='random_subseed')

-                reuse_subseed = gr.Button(reuse_symbol, elem_id='reuse_subseed')

-        subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01)

-

-    with gr.Row(visible=False) as seed_extra_row_2:

+        subseed = gr.Number(label='Variation seed', value=-1, elem_id=target_interface + '_subseed')

+        subseed.style(container=False)

+        random_subseed = gr.Button(random_symbol, elem_id=target_interface + '_random_subseed')

+        reuse_subseed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_subseed')

+        subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=target_interface + '_subseed_strength')

+

+    with FormRow(visible=False) as seed_extra_row_2:

         seed_extras.append(seed_extra_row_2)

-        seed_resize_from_w = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from width", value=0)

-        seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from height", value=0)

+        seed_resize_from_w = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from width", value=0, elem_id=target_interface + '_seed_resize_from_w')

+        seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from height", value=0, elem_id=target_interface + '_seed_resize_from_h')

 

     random_seed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[seed])

     random_subseed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[subseed])

@@ -368,6 +262,8 @@ def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info:
 

 def update_token_counter(text, steps):

     try:

+        text, _ = extra_networks.parse_prompt(text)

+

         _, prompt_flat_list, _ = prompt_parser.get_multicond_prompt_list([text])

         prompt_schedules = prompt_parser.get_learned_conditioning_prompt_schedules(prompt_flat_list, steps)

 

@@ -378,45 +274,24 @@ def update_token_counter(text, steps):
 

     flat_prompts = reduce(lambda list1, list2: list1+list2, prompt_schedules)

     prompts = [prompt_text for step, prompt_text in flat_prompts]

-    tokens, token_count, max_length = max([model_hijack.tokenize(prompt) for prompt in prompts], key=lambda args: args[1])

-    style_class = ' class="red"' if (token_count > max_length) else ""

-    return f"<span {style_class}>{token_count}/{max_length}</span>"

+    token_count, max_length = max([model_hijack.get_prompt_lengths(prompt) for prompt in prompts], key=lambda args: args[0])

+    return f"<span class='gr-box gr-text-input'>{token_count}/{max_length}</span>"

 

 

 def create_toprow(is_img2img):

     id_part = "img2img" if is_img2img else "txt2img"

 

-    with gr.Row(elem_id="toprow"):

-        with gr.Column(scale=6):

+    with gr.Row(elem_id=f"{id_part}_toprow", variant="compact"):

+        with gr.Column(elem_id=f"{id_part}_prompt_container", scale=6):

             with gr.Row():

                 with gr.Column(scale=80):

                     with gr.Row():

-                        prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=2,

-                            placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)"

-                        )

+                        prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=3, placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)")

 

             with gr.Row():

                 with gr.Column(scale=80):

                     with gr.Row():

-                        negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2,

-                            placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)"

-                        )

-

-        with gr.Column(scale=1, elem_id="roll_col"):

-            roll = gr.Button(value=art_symbol, elem_id="roll", visible=len(shared.artist_db.artists) > 0)

-            paste = gr.Button(value=paste_symbol, elem_id="paste")

-            save_style = gr.Button(value=save_style_symbol, elem_id="style_create")

-            prompt_style_apply = gr.Button(value=apply_style_symbol, elem_id="style_apply")

-            clear_prompt_button = gr.Button(value=clear_prompt_symbol, elem_id=f"{id_part}_clear_prompt")

-            token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_token_counter")

-            token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button")

-

-            clear_prompt_button.click(

-                fn=lambda *x: x,

-                _js="confirm_clear_prompt",

-                inputs=[prompt, negative_prompt],

-                outputs=[prompt, negative_prompt],

-            )

+                        negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2, placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)")

 

         button_interrogate = None

         button_deepbooru = None

@@ -425,10 +300,10 @@ def create_toprow(is_img2img):
                 button_interrogate = gr.Button('Interrogate\nCLIP', elem_id="interrogate")

                 button_deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru")

 

-        with gr.Column(scale=1):

-            with gr.Row():

-                skip = gr.Button('Skip', elem_id=f"{id_part}_skip")

+        with gr.Column(scale=1, elem_id=f"{id_part}_actions_column"):

+            with gr.Row(elem_id=f"{id_part}_generate_box"):

                 interrupt = gr.Button('Interrupt', elem_id=f"{id_part}_interrupt")

+                skip = gr.Button('Skip', elem_id=f"{id_part}_skip")

                 submit = gr.Button('Generate', elem_id=f"{id_part}_generate", variant='primary')

 

                 skip.click(

@@ -443,37 +318,34 @@ def create_toprow(is_img2img):
                     outputs=[],

                 )

 

-            with gr.Row():

-                with gr.Column(scale=1, elem_id="style_pos_col"):

-                    prompt_style = gr.Dropdown(label="Style 1", elem_id=f"{id_part}_style_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())))

-                    prompt_style.save_to_config = True

+            with gr.Row(elem_id=f"{id_part}_tools"):

+                paste = ToolButton(value=paste_symbol, elem_id="paste")

+                clear_prompt_button = ToolButton(value=clear_prompt_symbol, elem_id=f"{id_part}_clear_prompt")

+                extra_networks_button = ToolButton(value=extra_networks_symbol, elem_id=f"{id_part}_extra_networks")

+                prompt_style_apply = ToolButton(value=apply_style_symbol, elem_id=f"{id_part}_style_apply")

+                save_style = ToolButton(value=save_style_symbol, elem_id=f"{id_part}_style_create")

+

+                token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_token_counter")

+                token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button")

+                negative_token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_negative_token_counter")

+                negative_token_button = gr.Button(visible=False, elem_id=f"{id_part}_negative_token_button")

+

+                clear_prompt_button.click(

+                    fn=lambda *x: x,

+                    _js="confirm_clear_prompt",

+                    inputs=[prompt, negative_prompt],

+                    outputs=[prompt, negative_prompt],

+                )

 

-                with gr.Column(scale=1, elem_id="style_neg_col"):

-                    prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())))

-                    prompt_style2.save_to_config = True

+            with gr.Row(elem_id=f"{id_part}_styles_row"):

+                prompt_styles = gr.Dropdown(label="Styles", elem_id=f"{id_part}_styles", choices=[k for k, v in shared.prompt_styles.styles.items()], value=[], multiselect=True)

+                create_refresh_button(prompt_styles, shared.prompt_styles.reload, lambda: {"choices": [k for k, v in shared.prompt_styles.styles.items()]}, f"refresh_{id_part}_styles")

 

-    return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button

+    return prompt, prompt_styles, negative_prompt, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, extra_networks_button, token_counter, token_button, negative_token_counter, negative_token_button

 

 

-def setup_progressbar(progressbar, preview, id_part, textinfo=None):

-    if textinfo is None:

-        textinfo = gr.HTML(visible=False)

-

-    check_progress = gr.Button('Check progress', elem_id=f"{id_part}_check_progress", visible=False)

-    check_progress.click(

-        fn=lambda: check_progress_call(id_part),

-        show_progress=False,

-        inputs=[],

-        outputs=[progressbar, preview, preview, textinfo],

-    )

-

-    check_progress_initial = gr.Button('Check progress (first)', elem_id=f"{id_part}_check_progress_initial", visible=False)

-    check_progress_initial.click(

-        fn=lambda: check_progress_call_initial(id_part),

-        show_progress=False,

-        inputs=[],

-        outputs=[progressbar, preview, preview, textinfo],

-    )

+def setup_progressbar(*args, **kwargs):

+    pass

 

 

 def apply_setting(key, value):

@@ -500,27 +372,13 @@ def apply_setting(key, value):
         return

 

     valtype = type(opts.data_labels[key].default)

-    oldval = opts.data[key]

+    oldval = opts.data.get(key, None)

     opts.data[key] = valtype(value) if valtype != type(None) else value

     if oldval != value and opts.data_labels[key].onchange is not None:

         opts.data_labels[key].onchange()

 

     opts.save(shared.config_filename)

-    return value

-

-

-def update_generation_info(args):

-    generation_info, html_info, img_index = args

-    try:

-        generation_info = json.loads(generation_info)

-        if img_index < 0 or img_index >= len(generation_info["infotexts"]):

-            return html_info

-        return plaintext_to_html(generation_info["infotexts"][img_index])

-    except Exception:

-        pass

-    # if the json parse or anything else fails, just return the old html_info

-    return html_info

-

+    return getattr(opts, key)

 

 def create_refresh_button(refresh_component, refresh_method, refreshed_args, elem_id):

     def refresh():

@@ -532,7 +390,7 @@ def create_refresh_button(refresh_component, refresh_method, refreshed_args, ele
 

         return gr.update(**(args or {}))

 

-    refresh_button = gr.Button(value=refresh_symbol, elem_id=elem_id)

+    refresh_button = ToolButton(value=refresh_symbol, elem_id=elem_id)

     refresh_button.click(

         fn=refresh,

         inputs=[],

@@ -542,89 +400,37 @@ def create_refresh_button(refresh_component, refresh_method, refreshed_args, ele
 

 

 def create_output_panel(tabname, outdir):

-    def open_folder(f):

-        if not os.path.exists(f):

-            print(f'Folder "{f}" does not exist. After you create an image, the folder will be created.')

-            return

-        elif not os.path.isdir(f):

-            print(f"""

-WARNING

-An open_folder request was made with an argument that is not a folder.

-This could be an error or a malicious attempt to run code on your computer.

-Requested path was: {f}

-""", file=sys.stderr)

-            return

-

-        if not shared.cmd_opts.hide_ui_dir_config:

-            path = os.path.normpath(f)

-            if platform.system() == "Windows":

-                os.startfile(path)

-            elif platform.system() == "Darwin":

-                sp.Popen(["open", path])

-            else:

-                sp.Popen(["xdg-open", path])

+    return ui_common.create_output_panel(tabname, outdir)

 

-    with gr.Column(variant='panel'):

-            with gr.Group():

-                result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery").style(grid=4)

 

-            generation_info = None

-            with gr.Column():

-                with gr.Row():

-                    if tabname != "extras":

-                        save = gr.Button('Save', elem_id=f'save_{tabname}')

+def create_sampler_and_steps_selection(choices, tabname):

+    if opts.samplers_in_dropdown:

+        with FormRow(elem_id=f"sampler_selection_{tabname}"):

+            sampler_index = gr.Dropdown(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")

+            steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling steps", value=20)

+    else:

+        with FormGroup(elem_id=f"sampler_selection_{tabname}"):

+            steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling steps", value=20)

+            sampler_index = gr.Radio(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")

 

-                    buttons = parameters_copypaste.create_buttons(["img2img", "inpaint", "extras"])

-                    button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder'

-                    open_folder_button = gr.Button(folder_symbol, elem_id=button_id)

+    return steps, sampler_index

 

-                open_folder_button.click(

-                    fn=lambda: open_folder(opts.outdir_samples or outdir),

-                    inputs=[],

-                    outputs=[],

-                )

 

-                if tabname != "extras":

-                    with gr.Row():

-                        do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)

+def ordered_ui_categories():

+    user_order = {x.strip(): i * 2 + 1 for i, x in enumerate(shared.opts.ui_reorder.split(","))}

 

-                    with gr.Row():

-                        download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)

-

-                    with gr.Group():

-                        html_info = gr.HTML()

-                        generation_info = gr.Textbox(visible=False)

-                        if tabname == 'txt2img' or tabname == 'img2img':

-                            generation_info_button = gr.Button(visible=False, elem_id=f"{tabname}_generation_info_button")

-                            generation_info_button.click(

-                                fn=update_generation_info,

-                                _js="(x, y) => [x, y, selected_gallery_index()]",

-                                inputs=[generation_info, html_info],

-                                outputs=[html_info],

-                                preprocess=False

-                            )

-

-                        save.click(

-                            fn=wrap_gradio_call(save_files),

-                            _js="(x, y, z, w) => [x, y, z, selected_gallery_index()]",

-                            inputs=[

-                                generation_info,

-                                result_gallery,

-                                do_make_zip,

-                                html_info,

-                            ],

-                            outputs=[

-                                download_files,

-                                html_info,

-                                html_info,

-                                html_info,

-                            ]

-                        )

-                else:

-                    html_info_x = gr.HTML()

-                    html_info = gr.HTML()

-                parameters_copypaste.bind_buttons(buttons, result_gallery, "txt2img" if tabname == "txt2img" else None)

-                return result_gallery, generation_info if tabname != "extras" else html_info_x, html_info

+    for i, category in sorted(enumerate(shared.ui_reorder_categories), key=lambda x: user_order.get(x[1], x[0] * 2 + 0)):

+        yield category

+

+

+def get_value_for_setting(key):

+    value = getattr(opts, key)

+

+    info = opts.data_labels[key]

+    args = info.component_args() if callable(info.component_args) else info.component_args or {}

+    args = {k: v for k, v in args.items() if k not in {'precision'}}

+

+    return gr.update(value=value, **args)

 

 

 def create_ui():

@@ -639,67 +445,98 @@ def create_ui():
     modules.scripts.scripts_txt2img.initialize_scripts(is_img2img=False)

 

     with gr.Blocks(analytics_enabled=False) as txt2img_interface:

-        txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _,txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False)

+        txt2img_prompt, txt2img_prompt_styles, txt2img_negative_prompt, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, extra_networks_button, token_counter, token_button, negative_token_counter, negative_token_button = create_toprow(is_img2img=False)

 

         dummy_component = gr.Label(visible=False)

-        txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False)

-

-

-

+        txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="binary", visible=False)

 

-        with gr.Row(elem_id='txt2img_progress_row'):

-            with gr.Column(scale=1):

-                pass

-

-            with gr.Column(scale=1):

-                progressbar = gr.HTML(elem_id="txt2img_progressbar")

-                txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False)

-                setup_progressbar(progressbar, txt2img_preview, 'txt2img')

+        with FormRow(variant='compact', elem_id="txt2img_extra_networks", visible=False) as extra_networks:

+            from modules import ui_extra_networks

+            extra_networks_ui = ui_extra_networks.create_ui(extra_networks, extra_networks_button, 'txt2img')

 

         with gr.Row().style(equal_height=False):

-            with gr.Column(variant='panel', elem_id="txt2img_settings"):

-                steps = gr.Slider(minimum=1, maximum=150, step=1, label="Sampling Steps", value=20)

-                sampler_index = gr.Radio(label='Sampling method', elem_id="txt2img_sampling", choices=[x.name for x in samplers], value=samplers[0].name, type="index")

-

-                with gr.Group():

-                    width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512)

-                    height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512)

-

-                with gr.Row():

-                    restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1)

-                    tiling = gr.Checkbox(label='Tiling', value=False)

-                    enable_hr = gr.Checkbox(label='Highres. fix', value=False)

-

-                with gr.Row(visible=False) as hr_options:

-                    firstphase_width = gr.Slider(minimum=0, maximum=1024, step=8, label="Firstpass width", value=0)

-                    firstphase_height = gr.Slider(minimum=0, maximum=1024, step=8, label="Firstpass height", value=0)

-                    denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7)

-

-                with gr.Row(equal_height=True):

-                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1)

-                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1)

-

-                cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0)

-

-                seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs()

-

-                with gr.Group():

-                    custom_inputs = modules.scripts.scripts_txt2img.setup_ui()

+            with gr.Column(variant='compact', elem_id="txt2img_settings"):

+                for category in ordered_ui_categories():

+                    if category == "sampler":

+                        steps, sampler_index = create_sampler_and_steps_selection(samplers, "txt2img")

+

+                    elif category == "dimensions":

+                        with FormRow():

+                            with gr.Column(elem_id="txt2img_column_size", scale=4):

+                                width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="txt2img_width")

+                                height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="txt2img_height")

+

+                            if opts.dimensions_and_batch_together:

+                                res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="txt2img_res_switch_btn")

+                                with gr.Column(elem_id="txt2img_column_batch"):

+                                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")

+                                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")

+

+                    elif category == "cfg":

+                        cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="txt2img_cfg_scale")

+

+                    elif category == "seed":

+                        seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('txt2img')

+

+                    elif category == "checkboxes":

+                        with FormRow(elem_id="txt2img_checkboxes", variant="compact"):

+                            restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="txt2img_restore_faces")

+                            tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling")

+                            enable_hr = gr.Checkbox(label='Hires. fix', value=False, elem_id="txt2img_enable_hr")

+                            hr_final_resolution = FormHTML(value="", elem_id="txtimg_hr_finalres", label="Upscaled resolution", interactive=False)

+

+                    elif category == "hires_fix":

+                        with FormGroup(visible=False, elem_id="txt2img_hires_fix") as hr_options:

+                            with FormRow(elem_id="txt2img_hires_fix_row1", variant="compact"):

+                                hr_upscaler = gr.Dropdown(label="Upscaler", elem_id="txt2img_hr_upscaler", choices=[*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]], value=shared.latent_upscale_default_mode)

+                                hr_second_pass_steps = gr.Slider(minimum=0, maximum=150, step=1, label='Hires steps', value=0, elem_id="txt2img_hires_steps")

+                                denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7, elem_id="txt2img_denoising_strength")

+

+                            with FormRow(elem_id="txt2img_hires_fix_row2", variant="compact"):

+                                hr_scale = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Upscale by", value=2.0, elem_id="txt2img_hr_scale")

+                                hr_resize_x = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize width to", value=0, elem_id="txt2img_hr_resize_x")

+                                hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y")

+

+                    elif category == "batch":

+                        if not opts.dimensions_and_batch_together:

+                            with FormRow(elem_id="txt2img_column_batch"):

+                                batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")

+                                batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")

+

+                    elif category == "scripts":

+                        with FormGroup(elem_id="txt2img_script_container"):

+                            custom_inputs = modules.scripts.scripts_txt2img.setup_ui()

+

+            hr_resolution_preview_inputs = [enable_hr, width, height, hr_scale, hr_resize_x, hr_resize_y]

+            for input in hr_resolution_preview_inputs:

+                input.change(

+                    fn=calc_resolution_hires,

+                    inputs=hr_resolution_preview_inputs,

+                    outputs=[hr_final_resolution],

+                    show_progress=False,

+                )

+                input.change(

+                    None,

+                    _js="onCalcResolutionHires",

+                    inputs=hr_resolution_preview_inputs,

+                    outputs=[],

+                    show_progress=False,

+                )

 

-            txt2img_gallery, generation_info, html_info = create_output_panel("txt2img", opts.outdir_txt2img_samples)

+            txt2img_gallery, generation_info, html_info, html_log = create_output_panel("txt2img", opts.outdir_txt2img_samples)

             parameters_copypaste.bind_buttons({"txt2img": txt2img_paste}, None, txt2img_prompt)

 

             connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)

             connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)

 

             txt2img_args = dict(

-                fn=wrap_gradio_gpu_call(modules.txt2img.txt2img),

+                fn=wrap_gradio_gpu_call(modules.txt2img.txt2img, extra_outputs=[None, '', '']),

                 _js="submit",

                 inputs=[

+                    dummy_component,

                     txt2img_prompt,

                     txt2img_negative_prompt,

-                    txt2img_prompt_style,

-                    txt2img_prompt_style2,

+                    txt2img_prompt_styles,

                     steps,

                     sampler_index,

                     restore_faces,

@@ -713,14 +550,18 @@ def create_ui():
                     width,

                     enable_hr,

                     denoising_strength,

-                    firstphase_width,

-                    firstphase_height,

+                    hr_scale,

+                    hr_upscaler,

+                    hr_second_pass_steps,

+                    hr_resize_x,

+                    hr_resize_y,

                 ] + custom_inputs,

 

                 outputs=[

                     txt2img_gallery,

                     generation_info,

-                    html_info

+                    html_info,

+                    html_log,

                 ],

                 show_progress=False,

             )

@@ -728,6 +569,8 @@ def create_ui():
             txt2img_prompt.submit(**txt2img_args)

             submit.click(**txt2img_args)

 

+            res_switch_btn.click(lambda w, h: (h, w), inputs=[width, height], outputs=[width, height])

+

             txt_prompt_img.change(

                 fn=modules.images.image_data,

                 inputs=[

@@ -743,17 +586,7 @@ def create_ui():
                 fn=lambda x: gr_show(x),

                 inputs=[enable_hr],

                 outputs=[hr_options],

-            )

-

-            roll.click(

-                fn=roll_artist,

-                _js="update_txt2img_tokens",

-                inputs=[

-                    txt2img_prompt,

-                ],

-                outputs=[

-                    txt2img_prompt,

-                ]

+                show_progress = False,

             )

 

             txt2img_paste_fields = [

@@ -774,8 +607,11 @@ def create_ui():
                 (denoising_strength, "Denoising strength"),

                 (enable_hr, lambda d: "Denoising strength" in d),

                 (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)),

-                (firstphase_width, "First pass size-1"),

-                (firstphase_height, "First pass size-2"),

+                (hr_scale, "Hires upscale"),

+                (hr_upscaler, "Hires upscaler"),

+                (hr_second_pass_steps, "Hires steps"),

+                (hr_resize_x, "Hires resize-1"),

+                (hr_resize_y, "Hires resize-2"),

                 *modules.scripts.scripts_txt2img.infotext_fields

             ]

             parameters_copypaste.add_paste_fields("txt2img", None, txt2img_paste_fields)

@@ -792,98 +628,174 @@ def create_ui():
             ]

 

             token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[txt2img_prompt, steps], outputs=[token_counter])

+            negative_token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[txt2img_negative_prompt, steps], outputs=[negative_token_counter])

+

+            ui_extra_networks.setup_ui(extra_networks_ui, txt2img_gallery)

 

     modules.scripts.scripts_current = modules.scripts.scripts_img2img

     modules.scripts.scripts_img2img.initialize_scripts(is_img2img=True)

 

     with gr.Blocks(analytics_enabled=False) as img2img_interface:

-        img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,token_counter, token_button = create_toprow(is_img2img=True)

+        img2img_prompt, img2img_prompt_styles, img2img_negative_prompt, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste, extra_networks_button, token_counter, token_button, negative_token_counter, negative_token_button = create_toprow(is_img2img=True)

 

+        img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="binary", visible=False)

 

-        with gr.Row(elem_id='img2img_progress_row'):

-            img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False)

+        with FormRow(variant='compact', elem_id="img2img_extra_networks", visible=False) as extra_networks:

+            from modules import ui_extra_networks

+            extra_networks_ui_img2img = ui_extra_networks.create_ui(extra_networks, extra_networks_button, 'img2img')

 

-            with gr.Column(scale=1):

-                pass

-

-            with gr.Column(scale=1):

-                progressbar = gr.HTML(elem_id="img2img_progressbar")

-                img2img_preview = gr.Image(elem_id='img2img_preview', visible=False)

-                setup_progressbar(progressbar, img2img_preview, 'img2img')

+        with FormRow().style(equal_height=False):

+            with gr.Column(variant='compact', elem_id="img2img_settings"):

+                copy_image_buttons = []

+                copy_image_destinations = {}

 

-        with gr.Row().style(equal_height=False):

-            with gr.Column(variant='panel', elem_id="img2img_settings"):

+                def add_copy_image_controls(tab_name, elem):

+                    with gr.Row(variant="compact", elem_id=f"img2img_copy_to_{tab_name}"):

+                        gr.HTML("Copy image to: ", elem_id=f"img2img_label_copy_to_{tab_name}")

 

-                with gr.Tabs(elem_id="mode_img2img") as tabs_img2img_mode:

-                    with gr.TabItem('img2img', id='img2img'):

-                        init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_img2img_tool, image_mode="RGBA").style(height=480)

+                        for title, name in zip(['img2img', 'sketch', 'inpaint', 'inpaint sketch'], ['img2img', 'sketch', 'inpaint', 'inpaint_sketch']):

+                            if name == tab_name:

+                                gr.Button(title, interactive=False)

+                                copy_image_destinations[name] = elem

+                                continue

 

-                    with gr.TabItem('Inpaint', id='inpaint'):

-                        init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_inpaint_tool, image_mode="RGBA").style(height=480)

-                        init_img_with_mask_orig = gr.State(None)

+                            button = gr.Button(title)

+                            copy_image_buttons.append((button, name, elem))

 

-                        use_color_sketch = cmd_opts.gradio_inpaint_tool == "color-sketch"

-                        if use_color_sketch:

-                            def update_orig(image, state):

-                                if image is not None:

-                                    same_size = state is not None and state.size == image.size

-                                    has_exact_match = np.any(np.all(np.array(image) == np.array(state), axis=-1))

-                                    edited = same_size and has_exact_match

-                                    return image if not edited or state is None else state

+                with gr.Tabs(elem_id="mode_img2img"):

+                    with gr.TabItem('img2img', id='img2img', elem_id="img2img_img2img_tab") as tab_img2img:

+                        init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool="editor", image_mode="RGBA").style(height=480)

+                        add_copy_image_controls('img2img', init_img)

 

-                            init_img_with_mask.change(update_orig, [init_img_with_mask, init_img_with_mask_orig], init_img_with_mask_orig)

+                    with gr.TabItem('Sketch', id='img2img_sketch', elem_id="img2img_img2img_sketch_tab") as tab_sketch:

+                        sketch = gr.Image(label="Image for img2img", elem_id="img2img_sketch", show_label=False, source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA").style(height=480)

+                        add_copy_image_controls('sketch', sketch)

 

-                        init_img_inpaint = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_base")

-                        init_mask_inpaint = gr.Image(label="Mask", source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_mask")

+                    with gr.TabItem('Inpaint', id='inpaint', elem_id="img2img_inpaint_tab") as tab_inpaint:

+                        init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", image_mode="RGBA").style(height=480)

+                        add_copy_image_controls('inpaint', init_img_with_mask)

 

-                        with gr.Row():

-                            mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4)

-                            mask_alpha = gr.Slider(label="Mask transparency", interactive=use_color_sketch, visible=use_color_sketch)

+                    with gr.TabItem('Inpaint sketch', id='inpaint_sketch', elem_id="img2img_inpaint_sketch_tab") as tab_inpaint_color:

+                        inpaint_color_sketch = gr.Image(label="Color sketch inpainting", show_label=False, elem_id="inpaint_sketch", source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA").style(height=480)

+                        inpaint_color_sketch_orig = gr.State(None)

+                        add_copy_image_controls('inpaint_sketch', inpaint_color_sketch)

 

-                        with gr.Row():

-                            mask_mode = gr.Radio(label="Mask mode", show_label=False, choices=["Draw mask", "Upload mask"], type="index", value="Draw mask", elem_id="mask_mode")

-                            inpainting_mask_invert = gr.Radio(label='Masking mode', show_label=False, choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index")

+                        def update_orig(image, state):

+                            if image is not None:

+                                same_size = state is not None and state.size == image.size

+                                has_exact_match = np.any(np.all(np.array(image) == np.array(state), axis=-1))

+                                edited = same_size and has_exact_match

+                                return image if not edited or state is None else state

 

-                        inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='original', type="index")

+                        inpaint_color_sketch.change(update_orig, [inpaint_color_sketch, inpaint_color_sketch_orig], inpaint_color_sketch_orig)

 

-                        with gr.Row():

-                            inpaint_full_res = gr.Checkbox(label='Inpaint at full resolution', value=False)

-                            inpaint_full_res_padding = gr.Slider(label='Inpaint at full resolution padding, pixels', minimum=0, maximum=256, step=4, value=32)

+                    with gr.TabItem('Inpaint upload', id='inpaint_upload', elem_id="img2img_inpaint_upload_tab") as tab_inpaint_upload:

+                        init_img_inpaint = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil", elem_id="img_inpaint_base")

+                        init_mask_inpaint = gr.Image(label="Mask", source="upload", interactive=True, type="pil", elem_id="img_inpaint_mask")

 

-                    with gr.TabItem('Batch img2img', id='batch'):

+                    with gr.TabItem('Batch', id='batch', elem_id="img2img_batch_tab") as tab_batch:

                         hidden = '<br>Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else ''

-                        gr.HTML(f"<p class=\"text-gray-500\">Process images in a directory on the same machine where the server is running.<br>Use an empty output directory to save pictures normally instead of writing to the output directory.{hidden}</p>")

-                        img2img_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs)

-                        img2img_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs)

-

-                with gr.Row():

-                    resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", show_label=False, choices=["Just resize", "Crop and resize", "Resize and fill", "Just resize (latent upscale)"], type="index", value="Just resize")

-

-                steps = gr.Slider(minimum=1, maximum=150, step=1, label="Sampling Steps", value=20)

-                sampler_index = gr.Radio(label='Sampling method', choices=[x.name for x in samplers_for_img2img], value=samplers_for_img2img[0].name, type="index")

-

-                with gr.Group():

-                    width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")

-                    height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")

-

-                with gr.Row():

-                    restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1)

-                    tiling = gr.Checkbox(label='Tiling', value=False)

-

-                with gr.Row():

-                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1)

-                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1)

+                        gr.HTML(

+                            f"<p style='padding-bottom: 1em;' class=\"text-gray-500\">Process images in a directory on the same machine where the server is running." +

+                            f"<br>Use an empty output directory to save pictures normally instead of writing to the output directory." +

+                            f"<br>Add inpaint batch mask directory to enable inpaint batch processing."

+                            f"{hidden}</p>"

+                        )

+                        img2img_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, elem_id="img2img_batch_input_dir")

+                        img2img_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, elem_id="img2img_batch_output_dir")

+                        img2img_batch_inpaint_mask_dir = gr.Textbox(label="Inpaint batch mask directory (required for inpaint batch processing only)", **shared.hide_dirs, elem_id="img2img_batch_inpaint_mask_dir")

 

-                with gr.Group():

-                    cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0)

-                    denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75)

+                def copy_image(img):

+                    if isinstance(img, dict) and 'image' in img:

+                        return img['image']

 

-                seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs()

+                    return img

 

-                with gr.Group():

-                    custom_inputs = modules.scripts.scripts_img2img.setup_ui()

+                for button, name, elem in copy_image_buttons:

+                    button.click(

+                        fn=copy_image,

+                        inputs=[elem],

+                        outputs=[copy_image_destinations[name]],

+                    )

+                    button.click(

+                        fn=lambda: None,

+                        _js="switch_to_"+name.replace(" ", "_"),

+                        inputs=[],

+                        outputs=[],

+                    )

 

-            img2img_gallery, generation_info, html_info = create_output_panel("img2img", opts.outdir_img2img_samples)

+                with FormRow():

+                    resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", choices=["Just resize", "Crop and resize", "Resize and fill", "Just resize (latent upscale)"], type="index", value="Just resize")

+

+                for category in ordered_ui_categories():

+                    if category == "sampler":

+                        steps, sampler_index = create_sampler_and_steps_selection(samplers_for_img2img, "img2img")

+

+                    elif category == "dimensions":

+                        with FormRow():

+                            with gr.Column(elem_id="img2img_column_size", scale=4):

+                                width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")

+                                height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")

+

+                            if opts.dimensions_and_batch_together:

+                                res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="img2img_res_switch_btn")

+                                with gr.Column(elem_id="img2img_column_batch"):

+                                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")

+                                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")

+

+                    elif category == "cfg":

+                        with FormGroup():

+                            cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="img2img_cfg_scale")

+                            denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75, elem_id="img2img_denoising_strength")

+

+                    elif category == "seed":

+                        seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('img2img')

+

+                    elif category == "checkboxes":

+                        with FormRow(elem_id="img2img_checkboxes", variant="compact"):

+                            restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="img2img_restore_faces")

+                            tiling = gr.Checkbox(label='Tiling', value=False, elem_id="img2img_tiling")

+

+                    elif category == "batch":

+                        if not opts.dimensions_and_batch_together:

+                            with FormRow(elem_id="img2img_column_batch"):

+                                batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")

+                                batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")

+

+                    elif category == "scripts":

+                        with FormGroup(elem_id="img2img_script_container"):

+                            custom_inputs = modules.scripts.scripts_img2img.setup_ui()

+

+                    elif category == "inpaint":

+                        with FormGroup(elem_id="inpaint_controls", visible=False) as inpaint_controls:

+                            with FormRow():

+                                mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id="img2img_mask_blur")

+                                mask_alpha = gr.Slider(label="Mask transparency", visible=False, elem_id="img2img_mask_alpha")

+

+                            with FormRow():

+                                inpainting_mask_invert = gr.Radio(label='Mask mode', choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index", elem_id="img2img_mask_mode")

+

+                            with FormRow():

+                                inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='original', type="index", elem_id="img2img_inpainting_fill")

+

+                            with FormRow():

+                                with gr.Column():

+                                    inpaint_full_res = gr.Radio(label="Inpaint area", choices=["Whole picture", "Only masked"], type="index", value="Whole picture", elem_id="img2img_inpaint_full_res")

+

+                                with gr.Column(scale=4):

+                                    inpaint_full_res_padding = gr.Slider(label='Only masked padding, pixels', minimum=0, maximum=256, step=4, value=32, elem_id="img2img_inpaint_full_res_padding")

+

+                            def select_img2img_tab(tab):

+                                return gr.update(visible=tab in [2, 3, 4]), gr.update(visible=tab == 3),

+

+                            for i, elem in enumerate([tab_img2img, tab_sketch, tab_inpaint, tab_inpaint_color, tab_inpaint_upload, tab_batch]):

+                                elem.select(

+                                    fn=lambda tab=i: select_img2img_tab(tab),

+                                    inputs=[],

+                                    outputs=[inpaint_controls, mask_alpha],

+                                )

+

+            img2img_gallery, generation_info, html_info, html_log = create_output_panel("img2img", opts.outdir_img2img_samples)

             parameters_copypaste.bind_buttons({"img2img": img2img_paste}, None, img2img_prompt)

 

             connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)

@@ -900,35 +812,22 @@ def create_ui():
                 ]

             )

 

-            mask_mode.change(

-                lambda mode, img: {

-                    init_img_with_mask: gr_show(mode == 0),

-                    init_img_inpaint: gr_show(mode == 1),

-                    init_mask_inpaint: gr_show(mode == 1),

-                },

-                inputs=[mask_mode, init_img_with_mask],

-                outputs=[

-                    init_img_with_mask,

-                    init_img_inpaint,

-                    init_mask_inpaint,

-                ],

-            )

-

             img2img_args = dict(

-                fn=wrap_gradio_gpu_call(modules.img2img.img2img),

+                fn=wrap_gradio_gpu_call(modules.img2img.img2img, extra_outputs=[None, '', '']),

                 _js="submit_img2img",

                 inputs=[

                     dummy_component,

+                    dummy_component,

                     img2img_prompt,

                     img2img_negative_prompt,

-                    img2img_prompt_style,

-                    img2img_prompt_style2,

+                    img2img_prompt_styles,

                     init_img,

+                    sketch,

                     init_img_with_mask,

-                    init_img_with_mask_orig,

+                    inpaint_color_sketch,

+                    inpaint_color_sketch_orig,

                     init_img_inpaint,

                     init_mask_inpaint,

-                    mask_mode,

                     steps,

                     sampler_index,

                     mask_blur,

@@ -950,44 +849,48 @@ def create_ui():
                     inpainting_mask_invert,

                     img2img_batch_input_dir,

                     img2img_batch_output_dir,

+                    img2img_batch_inpaint_mask_dir

                 ] + custom_inputs,

                 outputs=[

                     img2img_gallery,

                     generation_info,

-                    html_info

+                    html_info,

+                    html_log,

                 ],

                 show_progress=False,

             )

 

+            interrogate_args = dict(

+                _js="get_img2img_tab_index",

+                inputs=[

+                    dummy_component,

+                    img2img_batch_input_dir,

+                    img2img_batch_output_dir,

+                    init_img,

+                    sketch,

+                    init_img_with_mask,

+                    inpaint_color_sketch,

+                    init_img_inpaint,

+                ],

+                outputs=[img2img_prompt, dummy_component],

+            )

+

             img2img_prompt.submit(**img2img_args)

             submit.click(**img2img_args)

+            res_switch_btn.click(lambda w, h: (h, w), inputs=[width, height], outputs=[width, height])

 

             img2img_interrogate.click(

-                fn=interrogate,

-                inputs=[init_img],

-                outputs=[img2img_prompt],

+                fn=lambda *args: process_interrogate(interrogate, *args),

+                **interrogate_args,

             )

 

             img2img_deepbooru.click(

-                fn=interrogate_deepbooru,

-                inputs=[init_img],

-                outputs=[img2img_prompt],

-            )

-

-

-            roll.click(

-                fn=roll_artist,

-                _js="update_img2img_tokens",

-                inputs=[

-                    img2img_prompt,

-                ],

-                outputs=[

-                    img2img_prompt,

-                ]

+                fn=lambda *args: process_interrogate(interrogate_deepbooru, *args),

+                **interrogate_args,

             )

 

             prompts = [(txt2img_prompt, txt2img_negative_prompt), (img2img_prompt, img2img_negative_prompt)]

-            style_dropdowns = [(txt2img_prompt_style, txt2img_prompt_style2), (img2img_prompt_style, img2img_prompt_style2)]

+            style_dropdowns = [txt2img_prompt_styles, img2img_prompt_styles]

             style_js_funcs = ["update_txt2img_tokens", "update_img2img_tokens"]

 

             for button, (prompt, negative_prompt) in zip([txt2img_save_style, img2img_save_style], prompts):

@@ -997,18 +900,21 @@ def create_ui():
                     # Have to pass empty dummy component here, because the JavaScript and Python function have to accept

                     # the same number of parameters, but we only know the style-name after the JavaScript prompt

                     inputs=[dummy_component, prompt, negative_prompt],

-                    outputs=[txt2img_prompt_style, img2img_prompt_style, txt2img_prompt_style2, img2img_prompt_style2],

+                    outputs=[txt2img_prompt_styles, img2img_prompt_styles],

                 )

 

-            for button, (prompt, negative_prompt), (style1, style2), js_func in zip([txt2img_prompt_style_apply, img2img_prompt_style_apply], prompts, style_dropdowns, style_js_funcs):

+            for button, (prompt, negative_prompt), styles, js_func in zip([txt2img_prompt_style_apply, img2img_prompt_style_apply], prompts, style_dropdowns, style_js_funcs):

                 button.click(

                     fn=apply_styles,

                     _js=js_func,

-                    inputs=[prompt, negative_prompt, style1, style2],

-                    outputs=[prompt, negative_prompt, style1, style2],

+                    inputs=[prompt, negative_prompt, styles],

+                    outputs=[prompt, negative_prompt, styles],

                 )

 

             token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter])

+            negative_token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[txt2img_negative_prompt, steps], outputs=[negative_token_counter])

+

+            ui_extra_networks.setup_ui(extra_networks_ui_img2img, img2img_gallery)

 

             img2img_paste_fields = [

                 (img2img_prompt, "Prompt"),

@@ -1035,86 +941,7 @@ def create_ui():
     modules.scripts.scripts_current = None

 

     with gr.Blocks(analytics_enabled=False) as extras_interface:

-        with gr.Row().style(equal_height=False):

-            with gr.Column(variant='panel'):

-                with gr.Tabs(elem_id="mode_extras"):

-                    with gr.TabItem('Single Image'):

-                        extras_image = gr.Image(label="Source", source="upload", interactive=True, type="pil")

-

-                    with gr.TabItem('Batch Process'):

-                        image_batch = gr.File(label="Batch Process", file_count="multiple", interactive=True, type="file")

-

-                    with gr.TabItem('Batch from Directory'):

-                        extras_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, placeholder="A directory on the same machine where the server is running.")

-                        extras_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, placeholder="Leave blank to save images to the default path.")

-                        show_extras_results = gr.Checkbox(label='Show result images', value=True)

-

-                submit = gr.Button('Generate', elem_id="extras_generate", variant='primary')

-

-                with gr.Tabs(elem_id="extras_resize_mode"):

-                    with gr.TabItem('Scale by'):

-                        upscaling_resize = gr.Slider(minimum=1.0, maximum=8.0, step=0.05, label="Resize", value=4)

-                    with gr.TabItem('Scale to'):

-                        with gr.Group():

-                            with gr.Row():

-                                upscaling_resize_w = gr.Number(label="Width", value=512, precision=0)

-                                upscaling_resize_h = gr.Number(label="Height", value=512, precision=0)

-                            upscaling_crop = gr.Checkbox(label='Crop to fit', value=True)

-

-                with gr.Group():

-                    extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")

-

-                with gr.Group():

-                    extras_upscaler_2 = gr.Radio(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")

-                    extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=1)

-

-                with gr.Group():

-                    gfpgan_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="GFPGAN visibility", value=0, interactive=modules.gfpgan_model.have_gfpgan)

-

-                with gr.Group():

-                    codeformer_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer visibility", value=0, interactive=modules.codeformer_model.have_codeformer)

-                    codeformer_weight = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer weight (0 = maximum effect, 1 = minimum effect)", value=0, interactive=modules.codeformer_model.have_codeformer)

-

-                with gr.Group():

-                    upscale_before_face_fix = gr.Checkbox(label='Upscale Before Restoring Faces', value=False)

-

-            result_images, html_info_x, html_info = create_output_panel("extras", opts.outdir_extras_samples)

-

-        submit.click(

-            fn=wrap_gradio_gpu_call(modules.extras.run_extras),

-            _js="get_extras_tab_index",

-            inputs=[

-                dummy_component,

-                dummy_component,

-                extras_image,

-                image_batch,

-                extras_batch_input_dir,

-                extras_batch_output_dir,

-                show_extras_results,

-                gfpgan_visibility,

-                codeformer_visibility,

-                codeformer_weight,

-                upscaling_resize,

-                upscaling_resize_w,

-                upscaling_resize_h,

-                upscaling_crop,

-                extras_upscaler_1,

-                extras_upscaler_2,

-                extras_upscaler_2_visibility,

-                upscale_before_face_fix,

-            ],

-            outputs=[

-                result_images,

-                html_info_x,

-                html_info,

-            ]

-        )

-        parameters_copypaste.add_paste_fields("extras", extras_image, None)

-

-        extras_image.change(

-            fn=modules.extras.clear_cache,

-            inputs=[], outputs=[]

-        )

+        ui_postprocessing.create_ui()

 

     with gr.Blocks(analytics_enabled=False) as pnginfo_interface:

         with gr.Row().style(equal_height=False):

@@ -1123,7 +950,7 @@ def create_ui():
 

             with gr.Column(variant='panel'):

                 html = gr.HTML()

-                generation_info = gr.Textbox(visible=False)

+                generation_info = gr.Textbox(visible=False, elem_id="pnginfo_generation_info")

                 html2 = gr.HTML()

                 with gr.Row():

                     buttons = parameters_copypaste.create_buttons(["txt2img", "img2img", "inpaint", "extras"])

@@ -1135,99 +962,141 @@ def create_ui():
             outputs=[html, generation_info, html2],

         )

 

+    def update_interp_description(value):

+        interp_description_css = "<p style='margin-bottom: 2.5em'>{}</p>"

+        interp_descriptions = {

+            "No interpolation": interp_description_css.format("No interpolation will be used. Requires one model; A. Allows for format conversion and VAE baking."),

+            "Weighted sum": interp_description_css.format("A weighted sum will be used for interpolation. Requires two models; A and B. The result is calculated as A * (1 - M) + B * M"),

+            "Add difference": interp_description_css.format("The difference between the last two models will be added to the first. Requires three models; A, B and C. The result is calculated as A + (B - C) * M")

+        }

+        return interp_descriptions[value]

+

     with gr.Blocks(analytics_enabled=False) as modelmerger_interface:

         with gr.Row().style(equal_height=False):

-            with gr.Column(variant='panel'):

-                gr.HTML(value="<p>A merger of the two checkpoints will be generated in your <b>checkpoint</b> directory.</p>")

+            with gr.Column(variant='compact'):

+                interp_description = gr.HTML(value=update_interp_description("Weighted sum"), elem_id="modelmerger_interp_description")

 

-                with gr.Row():

+                with FormRow(elem_id="modelmerger_models"):

                     primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)")

+                    create_refresh_button(primary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_A")

+

                     secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary model (B)")

+                    create_refresh_button(secondary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_B")

+

                     tertiary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_tertiary_model_name", label="Tertiary model (C)")

-                custom_name = gr.Textbox(label="Custom Name (Optional)")

-                interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3)

-                interp_method = gr.Radio(choices=["Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method")

+                    create_refresh_button(tertiary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_C")

 

-                with gr.Row():

-                    checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format")

-                    save_as_half = gr.Checkbox(value=False, label="Save as float16")

+                custom_name = gr.Textbox(label="Custom Name (Optional)", elem_id="modelmerger_custom_name")

+                interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3, elem_id="modelmerger_interp_amount")

+                interp_method = gr.Radio(choices=["No interpolation", "Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method", elem_id="modelmerger_interp_method")

+                interp_method.change(fn=update_interp_description, inputs=[interp_method], outputs=[interp_description])

 

-                modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary')

+                with FormRow():

+                    checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format", elem_id="modelmerger_checkpoint_format")

+                    save_as_half = gr.Checkbox(value=False, label="Save as float16", elem_id="modelmerger_save_as_half")

 

-            with gr.Column(variant='panel'):

-                submit_result = gr.Textbox(elem_id="modelmerger_result", show_label=False)

+                with FormRow():

+                    with gr.Column():

+                        config_source = gr.Radio(choices=["A, B or C", "B", "C", "Don't"], value="A, B or C", label="Copy config from", type="index", elem_id="modelmerger_config_method")

+

+                    with gr.Column():

+                        with FormRow():

+                            bake_in_vae = gr.Dropdown(choices=["None"] + list(sd_vae.vae_dict), value="None", label="Bake in VAE", elem_id="modelmerger_bake_in_vae")

+                            create_refresh_button(bake_in_vae, sd_vae.refresh_vae_list, lambda: {"choices": ["None"] + list(sd_vae.vae_dict)}, "modelmerger_refresh_bake_in_vae")

+

+                with FormRow():

+                    discard_weights = gr.Textbox(value="", label="Discard weights with matching name", elem_id="modelmerger_discard_weights")

+

+                with gr.Row():

+                    modelmerger_merge = gr.Button(elem_id="modelmerger_merge", value="Merge", variant='primary')

 

-    sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings()

+            with gr.Column(variant='compact', elem_id="modelmerger_results_container"):

+                with gr.Group(elem_id="modelmerger_results_panel"):

+                    modelmerger_result = gr.HTML(elem_id="modelmerger_result", show_label=False)

 

     with gr.Blocks(analytics_enabled=False) as train_interface:

         with gr.Row().style(equal_height=False):

             gr.HTML(value="<p style='margin-bottom: 0.7em'>See <b><a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\">wiki</a></b> for detailed explanation.</p>")

 

-        with gr.Row().style(equal_height=False):

+        with gr.Row(variant="compact").style(equal_height=False):

             with gr.Tabs(elem_id="train_tabs"):

 

                 with gr.Tab(label="Create embedding"):

-                    new_embedding_name = gr.Textbox(label="Name")

-                    initialization_text = gr.Textbox(label="Initialization text", value="*")

-                    nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1)

-                    overwrite_old_embedding = gr.Checkbox(value=False, label="Overwrite Old Embedding")

+                    new_embedding_name = gr.Textbox(label="Name", elem_id="train_new_embedding_name")

+                    initialization_text = gr.Textbox(label="Initialization text", value="*", elem_id="train_initialization_text")

+                    nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1, elem_id="train_nvpt")

+                    overwrite_old_embedding = gr.Checkbox(value=False, label="Overwrite Old Embedding", elem_id="train_overwrite_old_embedding")

 

                     with gr.Row():

                         with gr.Column(scale=3):

                             gr.HTML(value="")

 

                         with gr.Column():

-                            create_embedding = gr.Button(value="Create embedding", variant='primary')

+                            create_embedding = gr.Button(value="Create embedding", variant='primary', elem_id="train_create_embedding")

 

                 with gr.Tab(label="Create hypernetwork"):

-                    new_hypernetwork_name = gr.Textbox(label="Name")

-                    new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "1024", "320", "640", "1280"])

-                    new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'")

-                    new_hypernetwork_activation_func = gr.Dropdown(value="linear", label="Select activation function of hypernetwork. Recommended : Swish / Linear(none)", choices=modules.hypernetworks.ui.keys)

-                    new_hypernetwork_initialization_option = gr.Dropdown(value = "Normal", label="Select Layer weights initialization. Recommended: Kaiming for relu-like, Xavier for sigmoid-like, Normal otherwise", choices=["Normal", "KaimingUniform", "KaimingNormal", "XavierUniform", "XavierNormal"])

-                    new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization")

-                    new_hypernetwork_use_dropout = gr.Checkbox(label="Use dropout")

-                    overwrite_old_hypernetwork = gr.Checkbox(value=False, label="Overwrite Old Hypernetwork")

+                    new_hypernetwork_name = gr.Textbox(label="Name", elem_id="train_new_hypernetwork_name")

+                    new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "1024", "320", "640", "1280"], elem_id="train_new_hypernetwork_sizes")

+                    new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'", elem_id="train_new_hypernetwork_layer_structure")

+                    new_hypernetwork_activation_func = gr.Dropdown(value="linear", label="Select activation function of hypernetwork. Recommended : Swish / Linear(none)", choices=modules.hypernetworks.ui.keys, elem_id="train_new_hypernetwork_activation_func")

+                    new_hypernetwork_initialization_option = gr.Dropdown(value = "Normal", label="Select Layer weights initialization. Recommended: Kaiming for relu-like, Xavier for sigmoid-like, Normal otherwise", choices=["Normal", "KaimingUniform", "KaimingNormal", "XavierUniform", "XavierNormal"], elem_id="train_new_hypernetwork_initialization_option")

+                    new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization", elem_id="train_new_hypernetwork_add_layer_norm")

+                    new_hypernetwork_use_dropout = gr.Checkbox(label="Use dropout", elem_id="train_new_hypernetwork_use_dropout")

+                    new_hypernetwork_dropout_structure = gr.Textbox("0, 0, 0", label="Enter hypernetwork Dropout structure (or empty). Recommended : 0~0.35 incrementing sequence: 0, 0.05, 0.15", placeholder="1st and last digit must be 0 and values should be between 0 and 1. ex:'0, 0.01, 0'")

+                    overwrite_old_hypernetwork = gr.Checkbox(value=False, label="Overwrite Old Hypernetwork", elem_id="train_overwrite_old_hypernetwork")

 

                     with gr.Row():

                         with gr.Column(scale=3):

                             gr.HTML(value="")

 

                         with gr.Column():

-                            create_hypernetwork = gr.Button(value="Create hypernetwork", variant='primary')

+                            create_hypernetwork = gr.Button(value="Create hypernetwork", variant='primary', elem_id="train_create_hypernetwork")

 

                 with gr.Tab(label="Preprocess images"):

-                    process_src = gr.Textbox(label='Source directory')

-                    process_dst = gr.Textbox(label='Destination directory')

-                    process_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512)

-                    process_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512)

-                    preprocess_txt_action = gr.Dropdown(label='Existing Caption txt Action', value="ignore", choices=["ignore", "copy", "prepend", "append"])

+                    process_src = gr.Textbox(label='Source directory', elem_id="train_process_src")

+                    process_dst = gr.Textbox(label='Destination directory', elem_id="train_process_dst")

+                    process_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_process_width")

+                    process_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_process_height")

+                    preprocess_txt_action = gr.Dropdown(label='Existing Caption txt Action', value="ignore", choices=["ignore", "copy", "prepend", "append"], elem_id="train_preprocess_txt_action")

 

                     with gr.Row():

-                        process_flip = gr.Checkbox(label='Create flipped copies')

-                        process_split = gr.Checkbox(label='Split oversized images')

-                        process_focal_crop = gr.Checkbox(label='Auto focal point crop')

-                        process_caption = gr.Checkbox(label='Use BLIP for caption')

-                        process_caption_deepbooru = gr.Checkbox(label='Use deepbooru for caption', visible=True)

+                        process_flip = gr.Checkbox(label='Create flipped copies', elem_id="train_process_flip")

+                        process_split = gr.Checkbox(label='Split oversized images', elem_id="train_process_split")

+                        process_focal_crop = gr.Checkbox(label='Auto focal point crop', elem_id="train_process_focal_crop")

+                        process_multicrop = gr.Checkbox(label='Auto-sized crop', elem_id="train_process_multicrop")

+                        process_caption = gr.Checkbox(label='Use BLIP for caption', elem_id="train_process_caption")

+                        process_caption_deepbooru = gr.Checkbox(label='Use deepbooru for caption', visible=True, elem_id="train_process_caption_deepbooru")

 

                     with gr.Row(visible=False) as process_split_extra_row:

-                        process_split_threshold = gr.Slider(label='Split image threshold', value=0.5, minimum=0.0, maximum=1.0, step=0.05)

-                        process_overlap_ratio = gr.Slider(label='Split image overlap ratio', value=0.2, minimum=0.0, maximum=0.9, step=0.05)

+                        process_split_threshold = gr.Slider(label='Split image threshold', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_split_threshold")

+                        process_overlap_ratio = gr.Slider(label='Split image overlap ratio', value=0.2, minimum=0.0, maximum=0.9, step=0.05, elem_id="train_process_overlap_ratio")

 

                     with gr.Row(visible=False) as process_focal_crop_row:

-                        process_focal_crop_face_weight = gr.Slider(label='Focal point face weight', value=0.9, minimum=0.0, maximum=1.0, step=0.05)

-                        process_focal_crop_entropy_weight = gr.Slider(label='Focal point entropy weight', value=0.15, minimum=0.0, maximum=1.0, step=0.05)

-                        process_focal_crop_edges_weight = gr.Slider(label='Focal point edges weight', value=0.5, minimum=0.0, maximum=1.0, step=0.05)

-                        process_focal_crop_debug = gr.Checkbox(label='Create debug image')

-

+                        process_focal_crop_face_weight = gr.Slider(label='Focal point face weight', value=0.9, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_face_weight")

+                        process_focal_crop_entropy_weight = gr.Slider(label='Focal point entropy weight', value=0.15, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_entropy_weight")

+                        process_focal_crop_edges_weight = gr.Slider(label='Focal point edges weight', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_edges_weight")

+                        process_focal_crop_debug = gr.Checkbox(label='Create debug image', elem_id="train_process_focal_crop_debug")

+                    

+                    with gr.Column(visible=False) as process_multicrop_col:

+                        gr.Markdown('Each image is center-cropped with an automatically chosen width and height.')

+                        with gr.Row():

+                            process_multicrop_mindim = gr.Slider(minimum=64, maximum=2048, step=8, label="Dimension lower bound", value=384, elem_id="train_process_multicrop_mindim")

+                            process_multicrop_maxdim = gr.Slider(minimum=64, maximum=2048, step=8, label="Dimension upper bound", value=768, elem_id="train_process_multicrop_maxdim")

+                        with gr.Row():

+                            process_multicrop_minarea = gr.Slider(minimum=64*64, maximum=2048*2048, step=1, label="Area lower bound", value=64*64, elem_id="train_process_multicrop_minarea")

+                            process_multicrop_maxarea = gr.Slider(minimum=64*64, maximum=2048*2048, step=1, label="Area upper bound", value=640*640, elem_id="train_process_multicrop_maxarea")

+                        with gr.Row():

+                            process_multicrop_objective = gr.Radio(["Maximize area", "Minimize error"], value="Maximize area", label="Resizing objective", elem_id="train_process_multicrop_objective")

+                            process_multicrop_threshold = gr.Slider(minimum=0, maximum=1, step=0.01, label="Error threshold", value=0.1, elem_id="train_process_multicrop_threshold")

+   

                     with gr.Row():

                         with gr.Column(scale=3):

                             gr.HTML(value="")

 

                         with gr.Column():

                             with gr.Row():

-                                interrupt_preprocessing = gr.Button("Interrupt")

-                            run_preprocess = gr.Button(value="Preprocess", variant='primary')

+                                interrupt_preprocessing = gr.Button("Interrupt", elem_id="train_interrupt_preprocessing")

+                            run_preprocess = gr.Button(value="Preprocess", variant='primary', elem_id="train_run_preprocess")

 

                     process_split.change(

                         fn=lambda show: gr_show(show),

@@ -1241,54 +1110,74 @@ def create_ui():
                         outputs=[process_focal_crop_row],

                     )

 

+                    process_multicrop.change(

+                        fn=lambda show: gr_show(show),

+                        inputs=[process_multicrop],

+                        outputs=[process_multicrop_col],

+                    )

+

+                def get_textual_inversion_template_names():

+                    return sorted([x for x in textual_inversion.textual_inversion_templates])

+

                 with gr.Tab(label="Train"):

                     gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images <a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\" style=\"font-weight:bold;\">[wiki]</a></p>")

-                    with gr.Row():

+                    with FormRow():

                         train_embedding_name = gr.Dropdown(label='Embedding', elem_id="train_embedding", choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))

                         create_refresh_button(train_embedding_name, sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings, lambda: {"choices": sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())}, "refresh_train_embedding_name")

-                    with gr.Row():

+

                         train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=[x for x in shared.hypernetworks.keys()])

                         create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted([x for x in shared.hypernetworks.keys()])}, "refresh_train_hypernetwork_name")

-                    with gr.Row():

-                        embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005")

-                        hypernetwork_learn_rate = gr.Textbox(label='Hypernetwork Learning rate', placeholder="Hypernetwork Learning rate", value="0.00001")

-

-                    batch_size = gr.Number(label='Batch size', value=1, precision=0)

-                    gradient_step = gr.Number(label='Gradient accumulation steps', value=1, precision=0)

-                    dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images")

-                    log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")

-                    template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"))

-                    training_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512)

-                    training_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512)

-                    steps = gr.Number(label='Max steps', value=100000, precision=0)

-                    create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0)

-                    save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0)

-                    save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True)

-                    preview_from_txt2img = gr.Checkbox(label='Read parameters (prompt, etc...) from txt2img tab when making previews', value=False)

-                    with gr.Row():

-                        shuffle_tags = gr.Checkbox(label="Shuffle tags by ',' when creating prompts.", value=False)

-                        tag_drop_out = gr.Slider(minimum=0, maximum=1, step=0.1, label="Drop out tags when creating prompts.", value=0)

-                    with gr.Row():

-                        latent_sampling_method = gr.Radio(label='Choose latent sampling method', value="once", choices=['once', 'deterministic', 'random'])

+

+                    with FormRow():

+                        embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005", elem_id="train_embedding_learn_rate")

+                        hypernetwork_learn_rate = gr.Textbox(label='Hypernetwork Learning rate', placeholder="Hypernetwork Learning rate", value="0.00001", elem_id="train_hypernetwork_learn_rate")

+                    

+                    with FormRow():

+                        clip_grad_mode = gr.Dropdown(value="disabled", label="Gradient Clipping", choices=["disabled", "value", "norm"])

+                        clip_grad_value = gr.Textbox(placeholder="Gradient clip value", value="0.1", show_label=False)

+

+                    with FormRow():

+                        batch_size = gr.Number(label='Batch size', value=1, precision=0, elem_id="train_batch_size")

+                        gradient_step = gr.Number(label='Gradient accumulation steps', value=1, precision=0, elem_id="train_gradient_step")

+

+                    dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images", elem_id="train_dataset_directory")

+                    log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion", elem_id="train_log_directory")

+

+                    with FormRow():

+                        template_file = gr.Dropdown(label='Prompt template', value="style_filewords.txt", elem_id="train_template_file", choices=get_textual_inversion_template_names())

+                        create_refresh_button(template_file, textual_inversion.list_textual_inversion_templates, lambda: {"choices": get_textual_inversion_template_names()}, "refrsh_train_template_file")

+

+                    training_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_training_width")

+                    training_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_training_height")

+                    varsize = gr.Checkbox(label="Do not resize images", value=False, elem_id="train_varsize")

+                    steps = gr.Number(label='Max steps', value=100000, precision=0, elem_id="train_steps")

+

+                    with FormRow():

+                        create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0, elem_id="train_create_image_every")

+                        save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0, elem_id="train_save_embedding_every")

+

+                    save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True, elem_id="train_save_image_with_stored_embedding")

+                    preview_from_txt2img = gr.Checkbox(label='Read parameters (prompt, etc...) from txt2img tab when making previews', value=False, elem_id="train_preview_from_txt2img")

+

+                    shuffle_tags = gr.Checkbox(label="Shuffle tags by ',' when creating prompts.", value=False, elem_id="train_shuffle_tags")

+                    tag_drop_out = gr.Slider(minimum=0, maximum=1, step=0.1, label="Drop out tags when creating prompts.", value=0, elem_id="train_tag_drop_out")

+

+                    latent_sampling_method = gr.Radio(label='Choose latent sampling method', value="once", choices=['once', 'deterministic', 'random'], elem_id="train_latent_sampling_method")

 

                     with gr.Row():

-                        interrupt_training = gr.Button(value="Interrupt")

-                        train_hypernetwork = gr.Button(value="Train Hypernetwork", variant='primary')

-                        train_embedding = gr.Button(value="Train Embedding", variant='primary')

+                        train_embedding = gr.Button(value="Train Embedding", variant='primary', elem_id="train_train_embedding")

+                        interrupt_training = gr.Button(value="Interrupt", elem_id="train_interrupt_training")

+                        train_hypernetwork = gr.Button(value="Train Hypernetwork", variant='primary', elem_id="train_train_hypernetwork")

 

                 params = script_callbacks.UiTrainTabParams(txt2img_preview_params)

 

                 script_callbacks.ui_train_tabs_callback(params)

 

-            with gr.Column():

-                progressbar = gr.HTML(elem_id="ti_progressbar")

+            with gr.Column(elem_id='ti_gallery_container'):

                 ti_output = gr.Text(elem_id="ti_output", value="", show_label=False)

-

                 ti_gallery = gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(grid=4)

-                ti_preview = gr.Image(elem_id='ti_preview', visible=False)

                 ti_progress = gr.HTML(elem_id="ti_progress", value="")

                 ti_outcome = gr.HTML(elem_id="ti_error", value="")

-                setup_progressbar(progressbar, ti_preview, 'ti', textinfo=ti_progress)

 

         create_embedding.click(

             fn=modules.textual_inversion.ui.create_embedding,

@@ -1315,7 +1204,8 @@ def create_ui():
                 new_hypernetwork_activation_func,

                 new_hypernetwork_initialization_option,

                 new_hypernetwork_add_layer_norm,

-                new_hypernetwork_use_dropout

+                new_hypernetwork_use_dropout,

+                new_hypernetwork_dropout_structure

             ],

             outputs=[

                 train_hypernetwork_name,

@@ -1328,6 +1218,7 @@ def create_ui():
             fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]),

             _js="start_training_textual_inversion",

             inputs=[

+                dummy_component,

                 process_src,

                 process_dst,

                 process_width,

@@ -1344,6 +1235,13 @@ def create_ui():
                 process_focal_crop_entropy_weight,

                 process_focal_crop_edges_weight,

                 process_focal_crop_debug,

+                process_multicrop,

+                process_multicrop_mindim,

+                process_multicrop_maxdim,

+                process_multicrop_minarea,

+                process_multicrop_maxarea,

+                process_multicrop_objective,

+                process_multicrop_threshold,

             ],

             outputs=[

                 ti_output,

@@ -1355,6 +1253,7 @@ def create_ui():
             fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.train_embedding, extra_outputs=[gr.update()]),

             _js="start_training_textual_inversion",

             inputs=[

+                dummy_component,

                 train_embedding_name,

                 embedding_learn_rate,

                 batch_size,

@@ -1363,7 +1262,10 @@ def create_ui():
                 log_directory,

                 training_width,

                 training_height,

+                varsize,

                 steps,

+                clip_grad_mode,

+                clip_grad_value,

                 shuffle_tags,

                 tag_drop_out,

                 latent_sampling_method,

@@ -1384,6 +1286,7 @@ def create_ui():
             fn=wrap_gradio_gpu_call(modules.hypernetworks.ui.train_hypernetwork, extra_outputs=[gr.update()]),

             _js="start_training_textual_inversion",

             inputs=[

+                dummy_component,

                 train_hypernetwork_name,

                 hypernetwork_learn_rate,

                 batch_size,

@@ -1392,7 +1295,10 @@ def create_ui():
                 log_directory,

                 training_width,

                 training_height,

+                varsize,

                 steps,

+                clip_grad_mode,

+                clip_grad_value,

                 shuffle_tags,

                 tag_drop_out,

                 latent_sampling_method,

@@ -1447,7 +1353,7 @@ def create_ui():
                 res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {}))

                 create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key)

             else:

-                with gr.Row(variant="compact"):

+                with FormRow():

                     res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {}))

                     create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key)

         else:

@@ -1489,44 +1395,44 @@ def create_ui():
 

         opts.save(shared.config_filename)

 

-        return gr.update(value=value), opts.dumpjson()

+        return get_value_for_setting(key), opts.dumpjson()

 

     with gr.Blocks(analytics_enabled=False) as settings_interface:

-        settings_submit = gr.Button(value="Apply settings", variant='primary')

-        result = gr.HTML()

+        with gr.Row():

+            with gr.Column(scale=6):

+                settings_submit = gr.Button(value="Apply settings", variant='primary', elem_id="settings_submit")

+            with gr.Column():

+                restart_gradio = gr.Button(value='Reload UI', variant='primary', elem_id="settings_restart_gradio")

 

-        settings_cols = 3

-        items_per_col = int(len(opts.data_labels) * 0.9 / settings_cols)

+        result = gr.HTML(elem_id="settings_result")

 

         quicksettings_names = [x.strip() for x in opts.quicksettings.split(",")]

-        quicksettings_names = set(x for x in quicksettings_names if x != 'quicksettings')

+        quicksettings_names = {x: i for i, x in enumerate(quicksettings_names) if x != 'quicksettings'}

 

         quicksettings_list = []

 

-        cols_displayed = 0

-        items_displayed = 0

         previous_section = None

-        column = None

-        with gr.Row(elem_id="settings").style(equal_height=False):

+        current_tab = None

+        current_row = None

+        with gr.Tabs(elem_id="settings"):

             for i, (k, item) in enumerate(opts.data_labels.items()):

                 section_must_be_skipped = item.section[0] is None

 

                 if previous_section != item.section and not section_must_be_skipped:

-                    if cols_displayed < settings_cols and (items_displayed >= items_per_col or previous_section is None):

-                        if column is not None:

-                            column.__exit__()

+                    elem_id, text = item.section

 

-                        column = gr.Column(variant='panel')

-                        column.__enter__()

+                    if current_tab is not None:

+                        current_row.__exit__()

+                        current_tab.__exit__()

 

-                        items_displayed = 0

-                        cols_displayed += 1

+                    gr.Group()

+                    current_tab = gr.TabItem(elem_id="settings_{}".format(elem_id), label=text)

+                    current_tab.__enter__()

+                    current_row = gr.Column(variant='compact')

+                    current_row.__enter__()

 

                     previous_section = item.section

 

-                    elem_id, text = item.section

-                    gr.HTML(elem_id="settings_header_text_{}".format(elem_id), value='<h1 class="gr-button-lg">{}</h1>'.format(text))

-

                 if k in quicksettings_names and not shared.cmd_opts.freeze_settings:

                     quicksettings_list.append((i, k, item))

                     components.append(dummy_component)

@@ -1536,15 +1442,20 @@ def create_ui():
                     component = create_setting_component(k)

                     component_dict[k] = component

                     components.append(component)

-                    items_displayed += 1

 

-        with gr.Row():

-            request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications")

-            download_localization = gr.Button(value='Download localization template', elem_id="download_localization")

+            if current_tab is not None:

+                current_row.__exit__()

+                current_tab.__exit__()

 

-        with gr.Row():

-            reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary')

-            restart_gradio = gr.Button(value='Restart Gradio and Refresh components (Custom Scripts, ui.py, js and css only)', variant='primary')

+            with gr.TabItem("Actions"):

+                request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications")

+                download_localization = gr.Button(value='Download localization template', elem_id="download_localization")

+                reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary', elem_id="settings_reload_script_bodies")

+

+            with gr.TabItem("Licenses"):

+                gr.HTML(shared.html("licenses.html"), elem_id="licenses")

+

+            gr.Button(value="Show all pages", elem_id="settings_show_all_pages")

 

         request_notifications.click(

             fn=lambda: None,

@@ -1581,9 +1492,6 @@ def create_ui():
             outputs=[],

         )

 

-        if column is not None:

-            column.__exit__()

-

     interfaces = [

         (txt2img_interface, "txt2img", "txt2img"),

         (img2img_interface, "img2img", "img2img"),

@@ -1602,8 +1510,8 @@ def create_ui():
         with open(cssfile, "r", encoding="utf8") as file:

             css += file.read() + "\n"

 

-    if os.path.exists(os.path.join(script_path, "user.css")):

-        with open(os.path.join(script_path, "user.css"), "r", encoding="utf8") as file:

+    if os.path.exists(os.path.join(data_path, "user.css")):

+        with open(os.path.join(data_path, "user.css"), "r", encoding="utf8") as file:

             css += file.read() + "\n"

 

     if not cmd_opts.no_progressbar_hiding:

@@ -1616,8 +1524,8 @@ def create_ui():
     interfaces += [(extensions_interface, "Extensions", "extensions")]

 

     with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion") as demo:

-        with gr.Row(elem_id="quicksettings"):

-            for i, k, item in quicksettings_list:

+        with gr.Row(elem_id="quicksettings", variant="compact"):

+            for i, k, item in sorted(quicksettings_list, key=lambda x: quicksettings_names.get(x[1], x[0])):

                 component = create_setting_component(k, is_quicksettings=True)

                 component_dict[k] = component

 

@@ -1632,6 +1540,10 @@ def create_ui():
         if os.path.exists(os.path.join(script_path, "notification.mp3")):

             audio_notification = gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False)

 

+        footer = shared.html("footer.html")

+        footer = footer.format(versions=versions_html())

+        gr.HTML(footer, elem_id="footer")

+

         text_settings = gr.Textbox(elem_id="settings_json", value=lambda: opts.dumpjson(), visible=False)

         settings_submit.click(

             fn=wrap_gradio_call(run_settings, extra_outputs=[gr.update()]),

@@ -1651,7 +1563,7 @@ def create_ui():
         component_keys = [k for k in opts.data_labels.keys() if k in component_dict]

 

         def get_settings_values():

-            return [getattr(opts, key) for key in component_keys]

+            return [get_value_for_setting(key) for key in component_keys]

 

         demo.load(

             fn=get_settings_values,

@@ -1666,12 +1578,15 @@ def create_ui():
                 print("Error loading/saving model file:", file=sys.stderr)

                 print(traceback.format_exc(), file=sys.stderr)

                 modules.sd_models.list_models()  # to remove the potentially missing models from the list

-                return ["Error loading/saving model file. It doesn't exist or the name contains illegal characters"] + [gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(3)]

+                return [*[gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(4)], f"Error merging checkpoints: {e}"]

             return results

 

+        modelmerger_merge.click(fn=lambda: '', inputs=[], outputs=[modelmerger_result])

         modelmerger_merge.click(

-            fn=modelmerger,

+            fn=wrap_gradio_gpu_call(modelmerger, extra_outputs=lambda: [gr.update() for _ in range(4)]),

+            _js='modelmerger',

             inputs=[

+                dummy_component,

                 primary_model_name,

                 secondary_model_name,

                 tertiary_model_name,

@@ -1680,13 +1595,16 @@ def create_ui():
                 save_as_half,

                 custom_name,

                 checkpoint_format,

+                config_source,

+                bake_in_vae,

+                discard_weights,

             ],

             outputs=[

-                submit_result,

                 primary_model_name,

                 secondary_model_name,

                 tertiary_model_name,

                 component_dict['sd_model_checkpoint'],

+                modelmerger_result,

             ]

         )

 

@@ -1718,13 +1636,16 @@ def create_ui():
             if saved_value is None:

                 ui_settings[key] = getattr(obj, field)

             elif condition and not condition(saved_value):

-                print(f'Warning: Bad ui setting value: {key}: {saved_value}; Default value "{getattr(obj, field)}" will be used instead.')

+                pass

+

+                # this warning is generally not useful;

+                # print(f'Warning: Bad ui setting value: {key}: {saved_value}; Default value "{getattr(obj, field)}" will be used instead.')

             else:

                 setattr(obj, field, saved_value)

                 if init_field is not None:

                     init_field(saved_value)

 

-        if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number] and x.visible:

+        if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number, gr.Dropdown] and x.visible:

             apply_field(x, 'visible')

 

         if type(x) == gr.Slider:

@@ -1745,43 +1666,46 @@ def create_ui():
         if type(x) == gr.Number:

             apply_field(x, 'value')

 

-        # Since there are many dropdowns that shouldn't be saved,

-        # we only mark dropdowns that should be saved.

-        if type(x) == gr.Dropdown and getattr(x, 'save_to_config', False):

-            apply_field(x, 'value', lambda val: val in x.choices, getattr(x, 'init_field', None))

-            apply_field(x, 'visible')

+        if type(x) == gr.Dropdown:

+            def check_dropdown(val):

+                if getattr(x, 'multiselect', False):

+                    return all([value in x.choices for value in val])

+                else:

+                    return val in x.choices

+

+            apply_field(x, 'value', check_dropdown, getattr(x, 'init_field', None))

 

     visit(txt2img_interface, loadsave, "txt2img")

     visit(img2img_interface, loadsave, "img2img")

     visit(extras_interface, loadsave, "extras")

     visit(modelmerger_interface, loadsave, "modelmerger")

+    visit(train_interface, loadsave, "train")

 

     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)

 

+    # Required as a workaround for change() event not triggering when loading values from ui-config.json

+    interp_description.value = update_interp_description(interp_method.value)

+

     return demo

 

 

 def reload_javascript():

-    with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile:

-        javascript = f'<script>{jsfile.read()}</script>'

-

-    scripts_list = modules.scripts.list_scripts("javascript", ".js")

-

-    for basedir, filename, path in scripts_list:

-        with open(path, "r", encoding="utf8") as jsfile:

-            javascript += f"\n<!-- {filename} --><script>{jsfile.read()}</script>"

+    head = f'<script type="text/javascript" src="file={os.path.abspath("script.js")}"></script>\n'

 

+    inline = f"{localization.localization_js(shared.opts.localization)};"

     if cmd_opts.theme is not None:

-        javascript += f"\n<script>set_theme('{cmd_opts.theme}');</script>\n"

+        inline += f"set_theme('{cmd_opts.theme}');"

+

+    for script in modules.scripts.list_scripts("javascript", ".js"):

+        head += f'<script type="text/javascript" src="file={script.path}"></script>\n'

 

-    javascript += f"\n<script>{localization.localization_js(shared.opts.localization)}</script>"

+    head += f'<script type="text/javascript">{inline}</script>\n'

 

     def template_response(*args, **kwargs):

         res = shared.GradioTemplateResponseOriginal(*args, **kwargs)

-        res.body = res.body.replace(

-            b'</head>', f'{javascript}</head>'.encode("utf8"))

+        res.body = res.body.replace(b'</head>', f'{head}</head>'.encode("utf8"))

         res.init_headers()

         return res

 

@@ -1790,3 +1714,32 @@ def reload_javascript():
 

 if not hasattr(shared, 'GradioTemplateResponseOriginal'):

     shared.GradioTemplateResponseOriginal = gradio.routes.templates.TemplateResponse

+

+

+def versions_html():

+    import torch

+    import launch

+

+    python_version = ".".join([str(x) for x in sys.version_info[0:3]])

+    commit = launch.commit_hash()

+    short_commit = commit[0:8]

+

+    if shared.xformers_available:

+        import xformers

+        xformers_version = xformers.__version__

+    else:

+        xformers_version = "N/A"

+

+    return f"""

+python: <span title="{sys.version}">{python_version}</span>

+ • 

+torch: {torch.__version__}

+ • 

+xformers: {xformers_version}

+ • 

+gradio: {gr.__version__}

+ • 

+commit: <a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui/commit/{commit}">{short_commit}</a>

+ • 

+checkpoint: <a id="sd_checkpoint_hash">N/A</a>

+"""