-
Notifications
You must be signed in to change notification settings - Fork 5.6k
/
webui.py
789 lines (660 loc) · 52.9 KB
/
webui.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
import gradio as gr
import random
import os
import json
import time
import shared
import modules.config
import fooocus_version
import modules.html
import modules.async_worker as worker
import modules.constants as constants
import modules.flags as flags
import modules.gradio_hijack as grh
import modules.style_sorter as style_sorter
import modules.meta_parser
import args_manager
import copy
import launch
from modules.sdxl_styles import legal_style_names
from modules.private_logger import get_current_html_path
from modules.ui_gradio_extensions import reload_javascript
from modules.auth import auth_enabled, check_auth
from modules.util import is_json
def get_task(*args):
args = list(args)
args.pop(0)
return worker.AsyncTask(args=args)
def generate_clicked(task: worker.AsyncTask):
import ldm_patched.modules.model_management as model_management
with model_management.interrupt_processing_mutex:
model_management.interrupt_processing = False
# outputs=[progress_html, progress_window, progress_gallery, gallery]
if len(task.args) == 0:
return
execution_start_time = time.perf_counter()
finished = False
yield gr.update(visible=True, value=modules.html.make_progress_html(1, 'Waiting for task to start ...')), \
gr.update(visible=True, value=None), \
gr.update(visible=False, value=None), \
gr.update(visible=False)
worker.async_tasks.append(task)
while not finished:
time.sleep(0.01)
if len(task.yields) > 0:
flag, product = task.yields.pop(0)
if flag == 'preview':
# help bad internet connection by skipping duplicated preview
if len(task.yields) > 0: # if we have the next item
if task.yields[0][0] == 'preview': # if the next item is also a preview
# print('Skipped one preview for better internet connection.')
continue
percentage, title, image = product
yield gr.update(visible=True, value=modules.html.make_progress_html(percentage, title)), \
gr.update(visible=True, value=image) if image is not None else gr.update(), \
gr.update(), \
gr.update(visible=False)
if flag == 'results':
yield gr.update(visible=True), \
gr.update(visible=True), \
gr.update(visible=True, value=product), \
gr.update(visible=False)
if flag == 'finish':
yield gr.update(visible=False), \
gr.update(visible=False), \
gr.update(visible=False), \
gr.update(visible=True, value=product)
finished = True
# delete Fooocus temp images, only keep gradio temp images
if args_manager.args.disable_image_log:
for filepath in product:
if isinstance(filepath, str) and os.path.exists(filepath):
os.remove(filepath)
execution_time = time.perf_counter() - execution_start_time
print(f'Total time: {execution_time:.2f} seconds')
return
reload_javascript()
title = f'Fooocus {fooocus_version.version}'
if isinstance(args_manager.args.preset, str):
title += ' ' + args_manager.args.preset
shared.gradio_root = gr.Blocks(title=title).queue()
with shared.gradio_root:
currentTask = gr.State(worker.AsyncTask(args=[]))
with gr.Row():
with gr.Column(scale=2):
with gr.Row():
progress_window = grh.Image(label='Preview', show_label=True, visible=False, height=768,
elem_classes=['main_view'])
progress_gallery = gr.Gallery(label='Finished Images', show_label=True, object_fit='contain',
height=768, visible=False, elem_classes=['main_view', 'image_gallery'])
progress_html = gr.HTML(value=modules.html.make_progress_html(32, 'Progress 32%'), visible=False,
elem_id='progress-bar', elem_classes='progress-bar')
gallery = gr.Gallery(label='Gallery', show_label=False, object_fit='contain', visible=True, height=768,
elem_classes=['resizable_area', 'main_view', 'final_gallery', 'image_gallery'],
elem_id='final_gallery')
with gr.Row(elem_classes='type_row'):
with gr.Column(scale=17):
prompt = gr.Textbox(show_label=False, placeholder="Type prompt here or paste parameters.", elem_id='positive_prompt',
container=False, autofocus=True, elem_classes='type_row', lines=1024)
default_prompt = modules.config.default_prompt
if isinstance(default_prompt, str) and default_prompt != '':
shared.gradio_root.load(lambda: default_prompt, outputs=prompt)
with gr.Column(scale=3, min_width=0):
generate_button = gr.Button(label="Generate", value="Generate", elem_classes='type_row', elem_id='generate_button', visible=True)
reset_button = gr.Button(label="Reconnect", value="Reconnect", elem_classes='type_row', elem_id='reset_button', visible=False)
load_parameter_button = gr.Button(label="Load Parameters", value="Load Parameters", elem_classes='type_row', elem_id='load_parameter_button', visible=False)
skip_button = gr.Button(label="Skip", value="Skip", elem_classes='type_row_half', elem_id='skip_button', visible=False)
stop_button = gr.Button(label="Stop", value="Stop", elem_classes='type_row_half', elem_id='stop_button', visible=False)
def stop_clicked(currentTask):
import ldm_patched.modules.model_management as model_management
currentTask.last_stop = 'stop'
if (currentTask.processing):
model_management.interrupt_current_processing()
return currentTask
def skip_clicked(currentTask):
import ldm_patched.modules.model_management as model_management
currentTask.last_stop = 'skip'
if (currentTask.processing):
model_management.interrupt_current_processing()
return currentTask
stop_button.click(stop_clicked, inputs=currentTask, outputs=currentTask, queue=False, show_progress=False, _js='cancelGenerateForever')
skip_button.click(skip_clicked, inputs=currentTask, outputs=currentTask, queue=False, show_progress=False)
with gr.Row(elem_classes='advanced_check_row'):
input_image_checkbox = gr.Checkbox(label='Input Image', value=False, container=False, elem_classes='min_check')
advanced_checkbox = gr.Checkbox(label='Advanced', value=modules.config.default_advanced_checkbox, container=False, elem_classes='min_check')
with gr.Row(visible=False) as image_input_panel:
with gr.Tabs():
with gr.TabItem(label='Upscale or Variation') as uov_tab:
with gr.Row():
with gr.Column():
uov_input_image = grh.Image(label='Image', source='upload', type='numpy', show_label=False)
with gr.Column():
uov_method = gr.Radio(label='Upscale or Variation:', choices=flags.uov_list, value=flags.disabled)
gr.HTML('<a href="https://github.com/lllyasviel/Fooocus/discussions/390" target="_blank">\U0001F4D4 Document</a>')
with gr.TabItem(label='Image Prompt') as ip_tab:
with gr.Row():
ip_images = []
ip_types = []
ip_stops = []
ip_weights = []
ip_ctrls = []
ip_ad_cols = []
for _ in range(flags.controlnet_image_count):
with gr.Column():
ip_image = grh.Image(label='Image', source='upload', type='numpy', show_label=False, height=300)
ip_images.append(ip_image)
ip_ctrls.append(ip_image)
with gr.Column(visible=False) as ad_col:
with gr.Row():
default_end, default_weight = flags.default_parameters[flags.default_ip]
ip_stop = gr.Slider(label='Stop At', minimum=0.0, maximum=1.0, step=0.001, value=default_end)
ip_stops.append(ip_stop)
ip_ctrls.append(ip_stop)
ip_weight = gr.Slider(label='Weight', minimum=0.0, maximum=2.0, step=0.001, value=default_weight)
ip_weights.append(ip_weight)
ip_ctrls.append(ip_weight)
ip_type = gr.Radio(label='Type', choices=flags.ip_list, value=flags.default_ip, container=False)
ip_types.append(ip_type)
ip_ctrls.append(ip_type)
ip_type.change(lambda x: flags.default_parameters[x], inputs=[ip_type], outputs=[ip_stop, ip_weight], queue=False, show_progress=False)
ip_ad_cols.append(ad_col)
ip_advanced = gr.Checkbox(label='Advanced', value=False, container=False)
gr.HTML('* \"Image Prompt\" is powered by Fooocus Image Mixture Engine (v1.0.1). <a href="https://github.com/lllyasviel/Fooocus/discussions/557" target="_blank">\U0001F4D4 Document</a>')
def ip_advance_checked(x):
return [gr.update(visible=x)] * len(ip_ad_cols) + \
[flags.default_ip] * len(ip_types) + \
[flags.default_parameters[flags.default_ip][0]] * len(ip_stops) + \
[flags.default_parameters[flags.default_ip][1]] * len(ip_weights)
ip_advanced.change(ip_advance_checked, inputs=ip_advanced,
outputs=ip_ad_cols + ip_types + ip_stops + ip_weights,
queue=False, show_progress=False)
with gr.TabItem(label='Inpaint or Outpaint') as inpaint_tab:
with gr.Row():
inpaint_input_image = grh.Image(label='Image', source='upload', type='numpy', tool='sketch', height=500, brush_color="#FFFFFF", elem_id='inpaint_canvas', show_label=False)
inpaint_mask_image = grh.Image(label='Mask Upload', source='upload', type='numpy', height=500, visible=False)
with gr.Row():
inpaint_additional_prompt = gr.Textbox(placeholder="Describe what you want to inpaint.", elem_id='inpaint_additional_prompt', label='Inpaint Additional Prompt', visible=False)
outpaint_selections = gr.CheckboxGroup(choices=['Left', 'Right', 'Top', 'Bottom'], value=[], label='Outpaint Direction')
inpaint_mode = gr.Dropdown(choices=modules.flags.inpaint_options, value=modules.flags.inpaint_option_default, label='Method')
example_inpaint_prompts = gr.Dataset(samples=modules.config.example_inpaint_prompts, label='Additional Prompt Quick List', components=[inpaint_additional_prompt], visible=False)
gr.HTML('* Powered by Fooocus Inpaint Engine <a href="https://github.com/lllyasviel/Fooocus/discussions/414" target="_blank">\U0001F4D4 Document</a>')
example_inpaint_prompts.click(lambda x: x[0], inputs=example_inpaint_prompts, outputs=inpaint_additional_prompt, show_progress=False, queue=False)
with gr.TabItem(label='Describe') as desc_tab:
with gr.Row():
with gr.Column():
desc_input_image = grh.Image(label='Image', source='upload', type='numpy', show_label=False)
with gr.Column():
desc_method = gr.Radio(
label='Content Type',
choices=[flags.desc_type_photo, flags.desc_type_anime],
value=flags.desc_type_photo)
desc_btn = gr.Button(value='Describe this Image into Prompt')
desc_image_size = gr.Textbox(label='Image Size and Recommended Size', elem_id='desc_image_size', visible=False)
gr.HTML('<a href="https://github.com/lllyasviel/Fooocus/discussions/1363" target="_blank">\U0001F4D4 Document</a>')
def trigger_show_image_properties(image):
value = modules.util.get_image_size_info(image, modules.flags.sdxl_aspect_ratios)
return gr.update(value=value, visible=True)
desc_input_image.upload(trigger_show_image_properties, inputs=desc_input_image,
outputs=desc_image_size, show_progress=False, queue=False)
with gr.TabItem(label='Metadata') as metadata_tab:
with gr.Column():
metadata_input_image = grh.Image(label='For images created by Fooocus', source='upload', type='filepath')
metadata_json = gr.JSON(label='Metadata')
metadata_import_button = gr.Button(value='Apply Metadata')
def trigger_metadata_preview(filepath):
parameters, metadata_scheme = modules.meta_parser.read_info_from_image(filepath)
results = {}
if parameters is not None:
results['parameters'] = parameters
if isinstance(metadata_scheme, flags.MetadataScheme):
results['metadata_scheme'] = metadata_scheme.value
return results
metadata_input_image.upload(trigger_metadata_preview, inputs=metadata_input_image,
outputs=metadata_json, queue=False, show_progress=True)
switch_js = "(x) => {if(x){viewer_to_bottom(100);viewer_to_bottom(500);}else{viewer_to_top();} return x;}"
down_js = "() => {viewer_to_bottom();}"
input_image_checkbox.change(lambda x: gr.update(visible=x), inputs=input_image_checkbox,
outputs=image_input_panel, queue=False, show_progress=False, _js=switch_js)
ip_advanced.change(lambda: None, queue=False, show_progress=False, _js=down_js)
current_tab = gr.Textbox(value='uov', visible=False)
uov_tab.select(lambda: 'uov', outputs=current_tab, queue=False, _js=down_js, show_progress=False)
inpaint_tab.select(lambda: 'inpaint', outputs=current_tab, queue=False, _js=down_js, show_progress=False)
ip_tab.select(lambda: 'ip', outputs=current_tab, queue=False, _js=down_js, show_progress=False)
desc_tab.select(lambda: 'desc', outputs=current_tab, queue=False, _js=down_js, show_progress=False)
metadata_tab.select(lambda: 'metadata', outputs=current_tab, queue=False, _js=down_js, show_progress=False)
with gr.Column(scale=1, visible=modules.config.default_advanced_checkbox) as advanced_column:
with gr.Tab(label='Setting'):
if not args_manager.args.disable_preset_selection:
preset_selection = gr.Dropdown(label='Preset',
choices=modules.config.available_presets,
value=args_manager.args.preset if args_manager.args.preset else "initial",
interactive=True)
performance_selection = gr.Radio(label='Performance',
choices=flags.Performance.list(),
value=modules.config.default_performance,
elem_classes=['performance_selection'])
with gr.Accordion(label='Aspect Ratios', open=False) as aspect_ratios_accordion:
aspect_ratios_selection = gr.Radio(label='Aspect Ratios', show_label=False,
choices=modules.config.available_aspect_ratios_labels,
value=modules.config.default_aspect_ratio,
info='width × height',
elem_classes='aspect_ratios')
def change_aspect_ratio(text):
import re
regex = re.compile('<.*?>')
cleaned_text = re.sub(regex, '', text)
return gr.update(label='Aspect Ratios ' + cleaned_text)
aspect_ratios_selection.change(change_aspect_ratio, inputs=aspect_ratios_selection, outputs=aspect_ratios_accordion, queue=False, show_progress=False)
shared.gradio_root.load(change_aspect_ratio, inputs=aspect_ratios_selection, outputs=aspect_ratios_accordion, queue=False, show_progress=False)
image_number = gr.Slider(label='Image Number', minimum=1, maximum=modules.config.default_max_image_number, step=1, value=modules.config.default_image_number)
output_format = gr.Radio(label='Output Format',
choices=flags.OutputFormat.list(),
value=modules.config.default_output_format)
negative_prompt = gr.Textbox(label='Negative Prompt', show_label=True, placeholder="Type prompt here.",
info='Describing what you do not want to see.', lines=2,
elem_id='negative_prompt',
value=modules.config.default_prompt_negative)
seed_random = gr.Checkbox(label='Random', value=True)
image_seed = gr.Textbox(label='Seed', value=0, max_lines=1, visible=False) # workaround for https://github.com/gradio-app/gradio/issues/5354
def random_checked(r):
return gr.update(visible=not r)
def refresh_seed(r, seed_string):
if r:
return random.randint(constants.MIN_SEED, constants.MAX_SEED)
else:
try:
seed_value = int(seed_string)
if constants.MIN_SEED <= seed_value <= constants.MAX_SEED:
return seed_value
except ValueError:
pass
return random.randint(constants.MIN_SEED, constants.MAX_SEED)
seed_random.change(random_checked, inputs=[seed_random], outputs=[image_seed],
queue=False, show_progress=False)
def update_history_link():
if args_manager.args.disable_image_log:
return gr.update(value='')
return gr.update(value=f'<a href="file={get_current_html_path(output_format)}" target="_blank">\U0001F4DA History Log</a>')
history_link = gr.HTML()
shared.gradio_root.load(update_history_link, outputs=history_link, queue=False, show_progress=False)
with gr.Tab(label='Style', elem_classes=['style_selections_tab']):
style_sorter.try_load_sorted_styles(
style_names=legal_style_names,
default_selected=modules.config.default_styles)
style_search_bar = gr.Textbox(show_label=False, container=False,
placeholder="\U0001F50E Type here to search styles ...",
value="",
label='Search Styles')
style_selections = gr.CheckboxGroup(show_label=False, container=False,
choices=copy.deepcopy(style_sorter.all_styles),
value=copy.deepcopy(modules.config.default_styles),
label='Selected Styles',
elem_classes=['style_selections'])
gradio_receiver_style_selections = gr.Textbox(elem_id='gradio_receiver_style_selections', visible=False)
shared.gradio_root.load(lambda: gr.update(choices=copy.deepcopy(style_sorter.all_styles)),
outputs=style_selections)
style_search_bar.change(style_sorter.search_styles,
inputs=[style_selections, style_search_bar],
outputs=style_selections,
queue=False,
show_progress=False).then(
lambda: None, _js='()=>{refresh_style_localization();}')
gradio_receiver_style_selections.input(style_sorter.sort_styles,
inputs=style_selections,
outputs=style_selections,
queue=False,
show_progress=False).then(
lambda: None, _js='()=>{refresh_style_localization();}')
with gr.Tab(label='Model'):
with gr.Group():
with gr.Row():
base_model = gr.Dropdown(label='Base Model (SDXL only)', choices=modules.config.model_filenames, value=modules.config.default_base_model_name, show_label=True)
refiner_model = gr.Dropdown(label='Refiner (SDXL or SD 1.5)', choices=['None'] + modules.config.model_filenames, value=modules.config.default_refiner_model_name, show_label=True)
refiner_switch = gr.Slider(label='Refiner Switch At', minimum=0.1, maximum=1.0, step=0.0001,
info='Use 0.4 for SD1.5 realistic models; '
'or 0.667 for SD1.5 anime models; '
'or 0.8 for XL-refiners; '
'or any value for switching two SDXL models.',
value=modules.config.default_refiner_switch,
visible=modules.config.default_refiner_model_name != 'None')
refiner_model.change(lambda x: gr.update(visible=x != 'None'),
inputs=refiner_model, outputs=refiner_switch, show_progress=False, queue=False)
with gr.Group():
lora_ctrls = []
for i, (enabled, filename, weight) in enumerate(modules.config.default_loras):
with gr.Row():
lora_enabled = gr.Checkbox(label='Enable', value=enabled,
elem_classes=['lora_enable', 'min_check'], scale=1)
lora_model = gr.Dropdown(label=f'LoRA {i + 1}',
choices=['None'] + modules.config.lora_filenames, value=filename,
elem_classes='lora_model', scale=5)
lora_weight = gr.Slider(label='Weight', minimum=modules.config.default_loras_min_weight,
maximum=modules.config.default_loras_max_weight, step=0.01, value=weight,
elem_classes='lora_weight', scale=5)
lora_ctrls += [lora_enabled, lora_model, lora_weight]
with gr.Row():
refresh_files = gr.Button(label='Refresh', value='\U0001f504 Refresh All Files', variant='secondary', elem_classes='refresh_button')
with gr.Tab(label='Advanced'):
guidance_scale = gr.Slider(label='Guidance Scale', minimum=1.0, maximum=30.0, step=0.01,
value=modules.config.default_cfg_scale,
info='Higher value means style is cleaner, vivider, and more artistic.')
sharpness = gr.Slider(label='Image Sharpness', minimum=0.0, maximum=30.0, step=0.001,
value=modules.config.default_sample_sharpness,
info='Higher value means image and texture are sharper.')
gr.HTML('<a href="https://github.com/lllyasviel/Fooocus/discussions/117" target="_blank">\U0001F4D4 Document</a>')
dev_mode = gr.Checkbox(label='Developer Debug Mode', value=False, container=False)
with gr.Column(visible=False) as dev_tools:
with gr.Tab(label='Debug Tools'):
adm_scaler_positive = gr.Slider(label='Positive ADM Guidance Scaler', minimum=0.1, maximum=3.0,
step=0.001, value=1.5, info='The scaler multiplied to positive ADM (use 1.0 to disable). ')
adm_scaler_negative = gr.Slider(label='Negative ADM Guidance Scaler', minimum=0.1, maximum=3.0,
step=0.001, value=0.8, info='The scaler multiplied to negative ADM (use 1.0 to disable). ')
adm_scaler_end = gr.Slider(label='ADM Guidance End At Step', minimum=0.0, maximum=1.0,
step=0.001, value=0.3,
info='When to end the guidance from positive/negative ADM. ')
refiner_swap_method = gr.Dropdown(label='Refiner swap method', value=flags.refiner_swap_method,
choices=['joint', 'separate', 'vae'])
adaptive_cfg = gr.Slider(label='CFG Mimicking from TSNR', minimum=1.0, maximum=30.0, step=0.01,
value=modules.config.default_cfg_tsnr,
info='Enabling Fooocus\'s implementation of CFG mimicking for TSNR '
'(effective when real CFG > mimicked CFG).')
clip_skip = gr.Slider(label='CLIP Skip', minimum=1, maximum=10, step=1,
value=modules.config.default_clip_skip,
info='Bypass CLIP layers to avoid overfitting (use 1 to disable).')
sampler_name = gr.Dropdown(label='Sampler', choices=flags.sampler_list,
value=modules.config.default_sampler)
scheduler_name = gr.Dropdown(label='Scheduler', choices=flags.scheduler_list,
value=modules.config.default_scheduler)
vae_name = gr.Dropdown(label='VAE', choices=[modules.flags.default_vae] + modules.config.vae_filenames,
value=modules.config.default_vae, show_label=True)
generate_image_grid = gr.Checkbox(label='Generate Image Grid for Each Batch',
info='(Experimental) This may cause performance problems on some computers and certain internet conditions.',
value=False)
overwrite_step = gr.Slider(label='Forced Overwrite of Sampling Step',
minimum=-1, maximum=200, step=1,
value=modules.config.default_overwrite_step,
info='Set as -1 to disable. For developer debugging.')
overwrite_switch = gr.Slider(label='Forced Overwrite of Refiner Switch Step',
minimum=-1, maximum=200, step=1,
value=modules.config.default_overwrite_switch,
info='Set as -1 to disable. For developer debugging.')
overwrite_width = gr.Slider(label='Forced Overwrite of Generating Width',
minimum=-1, maximum=2048, step=1, value=-1,
info='Set as -1 to disable. For developer debugging. '
'Results will be worse for non-standard numbers that SDXL is not trained on.')
overwrite_height = gr.Slider(label='Forced Overwrite of Generating Height',
minimum=-1, maximum=2048, step=1, value=-1,
info='Set as -1 to disable. For developer debugging. '
'Results will be worse for non-standard numbers that SDXL is not trained on.')
overwrite_vary_strength = gr.Slider(label='Forced Overwrite of Denoising Strength of "Vary"',
minimum=-1, maximum=1.0, step=0.001, value=-1,
info='Set as negative number to disable. For developer debugging.')
overwrite_upscale_strength = gr.Slider(label='Forced Overwrite of Denoising Strength of "Upscale"',
minimum=-1, maximum=1.0, step=0.001, value=-1,
info='Set as negative number to disable. For developer debugging.')
disable_preview = gr.Checkbox(label='Disable Preview', value=modules.config.default_black_out_nsfw,
interactive=not modules.config.default_black_out_nsfw,
info='Disable preview during generation.')
disable_intermediate_results = gr.Checkbox(label='Disable Intermediate Results',
value=modules.config.default_performance == flags.Performance.EXTREME_SPEED.value,
interactive=modules.config.default_performance != flags.Performance.EXTREME_SPEED.value,
info='Disable intermediate results during generation, only show final gallery.')
disable_seed_increment = gr.Checkbox(label='Disable seed increment',
info='Disable automatic seed increment when image number is > 1.',
value=False)
read_wildcards_in_order = gr.Checkbox(label="Read wildcards in order", value=False)
black_out_nsfw = gr.Checkbox(label='Black Out NSFW',
value=modules.config.default_black_out_nsfw,
interactive=not modules.config.default_black_out_nsfw,
info='Use black image if NSFW is detected.')
black_out_nsfw.change(lambda x: gr.update(value=x, interactive=not x),
inputs=black_out_nsfw, outputs=disable_preview, queue=False,
show_progress=False)
if not args_manager.args.disable_metadata:
save_metadata_to_images = gr.Checkbox(label='Save Metadata to Images', value=modules.config.default_save_metadata_to_images,
info='Adds parameters to generated images allowing manual regeneration.')
metadata_scheme = gr.Radio(label='Metadata Scheme', choices=flags.metadata_scheme, value=modules.config.default_metadata_scheme,
info='Image Prompt parameters are not included. Use png and a1111 for compatibility with Civitai.',
visible=modules.config.default_save_metadata_to_images)
save_metadata_to_images.change(lambda x: gr.update(visible=x), inputs=[save_metadata_to_images], outputs=[metadata_scheme],
queue=False, show_progress=False)
with gr.Tab(label='Control'):
debugging_cn_preprocessor = gr.Checkbox(label='Debug Preprocessors', value=False,
info='See the results from preprocessors.')
skipping_cn_preprocessor = gr.Checkbox(label='Skip Preprocessors', value=False,
info='Do not preprocess images. (Inputs are already canny/depth/cropped-face/etc.)')
mixing_image_prompt_and_vary_upscale = gr.Checkbox(label='Mixing Image Prompt and Vary/Upscale',
value=False)
mixing_image_prompt_and_inpaint = gr.Checkbox(label='Mixing Image Prompt and Inpaint',
value=False)
controlnet_softness = gr.Slider(label='Softness of ControlNet', minimum=0.0, maximum=1.0,
step=0.001, value=0.25,
info='Similar to the Control Mode in A1111 (use 0.0 to disable). ')
with gr.Tab(label='Canny'):
canny_low_threshold = gr.Slider(label='Canny Low Threshold', minimum=1, maximum=255,
step=1, value=64)
canny_high_threshold = gr.Slider(label='Canny High Threshold', minimum=1, maximum=255,
step=1, value=128)
with gr.Tab(label='Inpaint'):
debugging_inpaint_preprocessor = gr.Checkbox(label='Debug Inpaint Preprocessing', value=False)
inpaint_disable_initial_latent = gr.Checkbox(label='Disable initial latent in inpaint', value=False)
inpaint_engine = gr.Dropdown(label='Inpaint Engine',
value=modules.config.default_inpaint_engine_version,
choices=flags.inpaint_engine_versions,
info='Version of Fooocus inpaint model')
inpaint_strength = gr.Slider(label='Inpaint Denoising Strength',
minimum=0.0, maximum=1.0, step=0.001, value=1.0,
info='Same as the denoising strength in A1111 inpaint. '
'Only used in inpaint, not used in outpaint. '
'(Outpaint always use 1.0)')
inpaint_respective_field = gr.Slider(label='Inpaint Respective Field',
minimum=0.0, maximum=1.0, step=0.001, value=0.618,
info='The area to inpaint. '
'Value 0 is same as "Only Masked" in A1111. '
'Value 1 is same as "Whole Image" in A1111. '
'Only used in inpaint, not used in outpaint. '
'(Outpaint always use 1.0)')
inpaint_erode_or_dilate = gr.Slider(label='Mask Erode or Dilate',
minimum=-64, maximum=64, step=1, value=0,
info='Positive value will make white area in the mask larger, '
'negative value will make white area smaller.'
'(default is 0, always process before any mask invert)')
inpaint_mask_upload_checkbox = gr.Checkbox(label='Enable Mask Upload', value=False)
invert_mask_checkbox = gr.Checkbox(label='Invert Mask', value=False)
inpaint_mask_color = gr.ColorPicker(label='Inpaint brush color', value='#FFFFFF', elem_id='inpaint_brush_color')
inpaint_ctrls = [debugging_inpaint_preprocessor, inpaint_disable_initial_latent, inpaint_engine,
inpaint_strength, inpaint_respective_field,
inpaint_mask_upload_checkbox, invert_mask_checkbox, inpaint_erode_or_dilate]
inpaint_mask_upload_checkbox.change(lambda x: gr.update(visible=x),
inputs=inpaint_mask_upload_checkbox,
outputs=inpaint_mask_image, queue=False,
show_progress=False)
inpaint_mask_color.change(lambda x: gr.update(brush_color=x), inputs=inpaint_mask_color,
outputs=inpaint_input_image,
queue=False, show_progress=False)
with gr.Tab(label='FreeU'):
freeu_enabled = gr.Checkbox(label='Enabled', value=False)
freeu_b1 = gr.Slider(label='B1', minimum=0, maximum=2, step=0.01, value=1.01)
freeu_b2 = gr.Slider(label='B2', minimum=0, maximum=2, step=0.01, value=1.02)
freeu_s1 = gr.Slider(label='S1', minimum=0, maximum=4, step=0.01, value=0.99)
freeu_s2 = gr.Slider(label='S2', minimum=0, maximum=4, step=0.01, value=0.95)
freeu_ctrls = [freeu_enabled, freeu_b1, freeu_b2, freeu_s1, freeu_s2]
def dev_mode_checked(r):
return gr.update(visible=r)
dev_mode.change(dev_mode_checked, inputs=[dev_mode], outputs=[dev_tools],
queue=False, show_progress=False)
def refresh_files_clicked():
modules.config.update_files()
results = [gr.update(choices=modules.config.model_filenames)]
results += [gr.update(choices=['None'] + modules.config.model_filenames)]
results += [gr.update(choices=['None'] + modules.config.vae_filenames)]
if not args_manager.args.disable_preset_selection:
results += [gr.update(choices=modules.config.available_presets)]
for i in range(modules.config.default_max_lora_number):
results += [gr.update(interactive=True),
gr.update(choices=['None'] + modules.config.lora_filenames), gr.update()]
return results
refresh_files_output = [base_model, refiner_model, vae_name]
if not args_manager.args.disable_preset_selection:
refresh_files_output += [preset_selection]
refresh_files.click(refresh_files_clicked, [], refresh_files_output + lora_ctrls,
queue=False, show_progress=False)
state_is_generating = gr.State(False)
load_data_outputs = [advanced_checkbox, image_number, prompt, negative_prompt, style_selections,
performance_selection, overwrite_step, overwrite_switch, aspect_ratios_selection,
overwrite_width, overwrite_height, guidance_scale, sharpness, adm_scaler_positive,
adm_scaler_negative, adm_scaler_end, refiner_swap_method, adaptive_cfg, clip_skip,
base_model, refiner_model, refiner_switch, sampler_name, scheduler_name, vae_name,
seed_random, image_seed, generate_button, load_parameter_button] + freeu_ctrls + lora_ctrls
if not args_manager.args.disable_preset_selection:
def preset_selection_change(preset, is_generating):
preset_content = modules.config.try_get_preset_content(preset) if preset != 'initial' else {}
preset_prepared = modules.meta_parser.parse_meta_from_preset(preset_content)
default_model = preset_prepared.get('base_model')
previous_default_models = preset_prepared.get('previous_default_models', [])
checkpoint_downloads = preset_prepared.get('checkpoint_downloads', {})
embeddings_downloads = preset_prepared.get('embeddings_downloads', {})
lora_downloads = preset_prepared.get('lora_downloads', {})
preset_prepared['base_model'], preset_prepared['lora_downloads'] = launch.download_models(
default_model, previous_default_models, checkpoint_downloads, embeddings_downloads, lora_downloads)
if 'prompt' in preset_prepared and preset_prepared.get('prompt') == '':
del preset_prepared['prompt']
return modules.meta_parser.load_parameter_button_click(json.dumps(preset_prepared), is_generating)
preset_selection.change(preset_selection_change, inputs=[preset_selection, state_is_generating], outputs=load_data_outputs, queue=False, show_progress=True) \
.then(fn=style_sorter.sort_styles, inputs=style_selections, outputs=style_selections, queue=False, show_progress=False)
performance_selection.change(lambda x: [gr.update(interactive=not flags.Performance.has_restricted_features(x))] * 11 +
[gr.update(visible=not flags.Performance.has_restricted_features(x))] * 1 +
[gr.update(interactive=not flags.Performance.has_restricted_features(x), value=flags.Performance.has_restricted_features(x))] * 1,
inputs=performance_selection,
outputs=[
guidance_scale, sharpness, adm_scaler_end, adm_scaler_positive,
adm_scaler_negative, refiner_switch, refiner_model, sampler_name,
scheduler_name, adaptive_cfg, refiner_swap_method, negative_prompt, disable_intermediate_results
], queue=False, show_progress=False)
output_format.input(lambda x: gr.update(output_format=x), inputs=output_format)
advanced_checkbox.change(lambda x: gr.update(visible=x), advanced_checkbox, advanced_column,
queue=False, show_progress=False) \
.then(fn=lambda: None, _js='refresh_grid_delayed', queue=False, show_progress=False)
def inpaint_mode_change(mode):
assert mode in modules.flags.inpaint_options
# inpaint_additional_prompt, outpaint_selections, example_inpaint_prompts,
# inpaint_disable_initial_latent, inpaint_engine,
# inpaint_strength, inpaint_respective_field
if mode == modules.flags.inpaint_option_detail:
return [
gr.update(visible=True), gr.update(visible=False, value=[]),
gr.Dataset.update(visible=True, samples=modules.config.example_inpaint_prompts),
False, 'None', 0.5, 0.0
]
if mode == modules.flags.inpaint_option_modify:
return [
gr.update(visible=True), gr.update(visible=False, value=[]),
gr.Dataset.update(visible=False, samples=modules.config.example_inpaint_prompts),
True, modules.config.default_inpaint_engine_version, 1.0, 0.0
]
return [
gr.update(visible=False, value=''), gr.update(visible=True),
gr.Dataset.update(visible=False, samples=modules.config.example_inpaint_prompts),
False, modules.config.default_inpaint_engine_version, 1.0, 0.618
]
inpaint_mode.input(inpaint_mode_change, inputs=inpaint_mode, outputs=[
inpaint_additional_prompt, outpaint_selections, example_inpaint_prompts,
inpaint_disable_initial_latent, inpaint_engine,
inpaint_strength, inpaint_respective_field
], show_progress=False, queue=False)
ctrls = [currentTask, generate_image_grid]
ctrls += [
prompt, negative_prompt, style_selections,
performance_selection, aspect_ratios_selection, image_number, output_format, image_seed,
read_wildcards_in_order, sharpness, guidance_scale
]
ctrls += [base_model, refiner_model, refiner_switch] + lora_ctrls
ctrls += [input_image_checkbox, current_tab]
ctrls += [uov_method, uov_input_image]
ctrls += [outpaint_selections, inpaint_input_image, inpaint_additional_prompt, inpaint_mask_image]
ctrls += [disable_preview, disable_intermediate_results, disable_seed_increment, black_out_nsfw]
ctrls += [adm_scaler_positive, adm_scaler_negative, adm_scaler_end, adaptive_cfg, clip_skip]
ctrls += [sampler_name, scheduler_name, vae_name]
ctrls += [overwrite_step, overwrite_switch, overwrite_width, overwrite_height, overwrite_vary_strength]
ctrls += [overwrite_upscale_strength, mixing_image_prompt_and_vary_upscale, mixing_image_prompt_and_inpaint]
ctrls += [debugging_cn_preprocessor, skipping_cn_preprocessor, canny_low_threshold, canny_high_threshold]
ctrls += [refiner_swap_method, controlnet_softness]
ctrls += freeu_ctrls
ctrls += inpaint_ctrls
if not args_manager.args.disable_metadata:
ctrls += [save_metadata_to_images, metadata_scheme]
ctrls += ip_ctrls
def parse_meta(raw_prompt_txt, is_generating):
loaded_json = None
if is_json(raw_prompt_txt):
loaded_json = json.loads(raw_prompt_txt)
if loaded_json is None:
if is_generating:
return gr.update(), gr.update(), gr.update()
else:
return gr.update(), gr.update(visible=True), gr.update(visible=False)
return json.dumps(loaded_json), gr.update(visible=False), gr.update(visible=True)
prompt.input(parse_meta, inputs=[prompt, state_is_generating], outputs=[prompt, generate_button, load_parameter_button], queue=False, show_progress=False)
load_parameter_button.click(modules.meta_parser.load_parameter_button_click, inputs=[prompt, state_is_generating], outputs=load_data_outputs, queue=False, show_progress=False)
def trigger_metadata_import(filepath, state_is_generating):
parameters, metadata_scheme = modules.meta_parser.read_info_from_image(filepath)
if parameters is None:
print('Could not find metadata in the image!')
parsed_parameters = {}
else:
metadata_parser = modules.meta_parser.get_metadata_parser(metadata_scheme)
parsed_parameters = metadata_parser.parse_json(parameters)
return modules.meta_parser.load_parameter_button_click(parsed_parameters, state_is_generating)
metadata_import_button.click(trigger_metadata_import, inputs=[metadata_input_image, state_is_generating], outputs=load_data_outputs, queue=False, show_progress=True) \
.then(style_sorter.sort_styles, inputs=style_selections, outputs=style_selections, queue=False, show_progress=False)
generate_button.click(lambda: (gr.update(visible=True, interactive=True), gr.update(visible=True, interactive=True), gr.update(visible=False, interactive=False), [], True),
outputs=[stop_button, skip_button, generate_button, gallery, state_is_generating]) \
.then(fn=refresh_seed, inputs=[seed_random, image_seed], outputs=image_seed) \
.then(fn=get_task, inputs=ctrls, outputs=currentTask) \
.then(fn=generate_clicked, inputs=currentTask, outputs=[progress_html, progress_window, progress_gallery, gallery]) \
.then(lambda: (gr.update(visible=True, interactive=True), gr.update(visible=False, interactive=False), gr.update(visible=False, interactive=False), False),
outputs=[generate_button, stop_button, skip_button, state_is_generating]) \
.then(fn=update_history_link, outputs=history_link) \
.then(fn=lambda: None, _js='playNotification').then(fn=lambda: None, _js='refresh_grid_delayed')
reset_button.click(lambda: [worker.AsyncTask(args=[]), False, gr.update(visible=True, interactive=True)] +
[gr.update(visible=False)] * 6 +
[gr.update(visible=True, value=[])],
outputs=[currentTask, state_is_generating, generate_button,
reset_button, stop_button, skip_button,
progress_html, progress_window, progress_gallery, gallery],
queue=False)
for notification_file in ['notification.ogg', 'notification.mp3']:
if os.path.exists(notification_file):
gr.Audio(interactive=False, value=notification_file, elem_id='audio_notification', visible=False)
break
def trigger_describe(mode, img):
if mode == flags.desc_type_photo:
from extras.interrogate import default_interrogator as default_interrogator_photo
return default_interrogator_photo(img), ["Fooocus V2", "Fooocus Enhance", "Fooocus Sharp"]
if mode == flags.desc_type_anime:
from extras.wd14tagger import default_interrogator as default_interrogator_anime
return default_interrogator_anime(img), ["Fooocus V2", "Fooocus Masterpiece"]
return mode, ["Fooocus V2"]
desc_btn.click(trigger_describe, inputs=[desc_method, desc_input_image],
outputs=[prompt, style_selections], show_progress=True, queue=True)
if args_manager.args.enable_describe_uov_image:
def trigger_uov_describe(mode, img, prompt):
# keep prompt if not empty
if prompt == '':
return trigger_describe(mode, img)
return gr.update(), gr.update()
uov_input_image.upload(trigger_uov_describe, inputs=[desc_method, uov_input_image, prompt],
outputs=[prompt, style_selections], show_progress=True, queue=True)
def dump_default_english_config():
from modules.localization import dump_english_config
dump_english_config(grh.all_components)
# dump_default_english_config()
shared.gradio_root.launch(
inbrowser=args_manager.args.in_browser,
server_name=args_manager.args.listen,
server_port=args_manager.args.port,
share=args_manager.args.share,
auth=check_auth if (args_manager.args.share or args_manager.args.listen) and auth_enabled else None,
allowed_paths=[modules.config.path_outputs],
blocked_paths=[constants.AUTH_FILENAME]
)