This repository has been archived by the owner on Aug 29, 2024. It is now read-only.
-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathui.py
1249 lines (996 loc) · 67.5 KB
/
ui.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
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
import datetime
import mimetypes
import os
import sys
from functools import reduce
import warnings
from contextlib import ExitStack
import gradio as gr
import gradio.utils
import numpy as np
from PIL import Image, PngImagePlugin # noqa: F401
from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
from modules import gradio_extensons, sd_schedulers # noqa: F401
from modules import sd_hijack, sd_models, script_callbacks, ui_extensions, deepbooru, extra_networks, ui_common, ui_postprocessing, progress, ui_loadsave, shared_items, ui_settings, timer, sysinfo, ui_checkpoint_merger, scripts, sd_samplers, processing, ui_extra_networks, ui_toprow, launch_utils
from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML, InputAccordion, ResizeHandleRow
from modules.paths import script_path
from modules.ui_common import create_refresh_button
from modules.ui_gradio_extensions import reload_javascript
from modules.shared import opts, cmd_opts
import modules.infotext_utils as parameters_copypaste
import modules.hypernetworks.ui as hypernetworks_ui
import modules.textual_inversion.ui as textual_inversion_ui
import modules.textual_inversion.textual_inversion as textual_inversion
import modules.shared as shared
from modules import prompt_parser
from modules.sd_hijack import model_hijack
from modules.infotext_utils import image_from_url_text, PasteField
create_setting_component = ui_settings.create_setting_component
warnings.filterwarnings("default" if opts.show_warnings else "ignore", category=UserWarning)
warnings.filterwarnings("default" if opts.show_gradio_deprecation_warnings else "ignore", category=gr.deprecation.GradioDeprecationWarning)
# 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()
mimetypes.add_type('application/javascript', '.js')
mimetypes.add_type('application/javascript', '.mjs')
# Likewise, add explicit content-type header for certain missing image types
mimetypes.add_type('image/webp', '.webp')
mimetypes.add_type('image/avif', '.avif')
if not cmd_opts.share and not cmd_opts.listen:
# fix gradio phoning home
gradio.utils.version_check = lambda: None
gradio.utils.get_local_ip_address = lambda: '127.0.0.1'
if cmd_opts.ngrok is not None:
import modules.ngrok as ngrok
print('ngrok authtoken detected, trying to connect...')
ngrok.connect(
cmd_opts.ngrok,
cmd_opts.port if cmd_opts.port is not None else 7860,
cmd_opts.ngrok_options
)
def gr_show(visible=True):
return {"visible": visible, "__type__": "update"}
sample_img2img = "assets/stable-samples/img2img/sketch-mountains-input.jpg"
sample_img2img = sample_img2img if os.path.exists(sample_img2img) else None
# Using constants for these since the variation selector isn't visible.
# Important that they exactly match script.js for tooltip to work.
random_symbol = '\U0001f3b2\ufe0f' # 🎲️
reuse_symbol = '\u267b\ufe0f' # ♻️
paste_symbol = '\u2199\ufe0f' # ↙
refresh_symbol = '\U0001f504' # 🔄
save_style_symbol = '\U0001f4be' # 💾
apply_style_symbol = '\U0001f4cb' # 📋
clear_prompt_symbol = '\U0001f5d1\ufe0f' # 🗑️
extra_networks_symbol = '\U0001F3B4' # 🎴
switch_values_symbol = '\U000021C5' # ⇅
restore_progress_symbol = '\U0001F300' # 🌀
detect_image_size_symbol = '\U0001F4D0' # 📐
plaintext_to_html = ui_common.plaintext_to_html
def send_gradio_gallery_to_image(x):
if len(x) == 0:
return None
return image_from_url_text(x[0])
def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resize_y):
if not enable:
return ""
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)
p.calculate_target_resolution()
return f"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 resize_from_to_html(width, height, scale_by):
target_width = int(width * scale_by)
target_height = int(height * scale_by)
if not target_width or not target_height:
return "no image selected"
return f"resize: from <span class='resolution'>{width}x{height}</span> to <span class='resolution'>{target_width}x{target_height}</span>"
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, f"{left}.txt"), 'a', encoding='utf-8'))
return [gr.update(), None]
def interrogate(image):
prompt = shared.interrogator.interrogate(image.convert("RGB"))
return gr.update() if prompt is None else prompt
def interrogate_deepbooru(image):
prompt = deepbooru.model.tag(image)
return gr.update() if prompt is None else prompt
def connect_clear_prompt(button):
"""Given clear button, prompt, and token_counter objects, setup clear prompt button click event"""
button.click(
_js="clear_prompt",
fn=None,
inputs=[],
outputs=[],
)
def update_token_counter(text, steps, styles, *, is_positive=True):
params = script_callbacks.BeforeTokenCounterParams(text, steps, styles, is_positive=is_positive)
script_callbacks.before_token_counter_callback(params)
text = params.prompt
steps = params.steps
styles = params.styles
is_positive = params.is_positive
if shared.opts.include_styles_into_token_counters:
apply_styles = shared.prompt_styles.apply_styles_to_prompt if is_positive else shared.prompt_styles.apply_negative_styles_to_prompt
text = apply_styles(text, styles)
try:
text, _ = extra_networks.parse_prompt(text)
if is_positive:
_, prompt_flat_list, _ = prompt_parser.get_multicond_prompt_list([text])
else:
prompt_flat_list = [text]
prompt_schedules = prompt_parser.get_learned_conditioning_prompt_schedules(prompt_flat_list, steps)
except Exception:
# a parsing error can happen here during typing, and we don't want to bother the user with
# messages related to it in console
prompt_schedules = [[[steps, text]]]
flat_prompts = reduce(lambda list1, list2: list1+list2, prompt_schedules)
prompts = [prompt_text for step, prompt_text in flat_prompts]
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 update_negative_prompt_token_counter(*args):
return update_token_counter(*args, is_positive=False)
def setup_progressbar(*args, **kwargs):
pass
def apply_setting(key, value):
if value is None:
return gr.update()
if shared.cmd_opts.freeze_settings:
return gr.update()
# dont allow model to be swapped when model hash exists in prompt
if key == "sd_model_checkpoint" and opts.disable_weights_auto_swap:
return gr.update()
if key == "sd_model_checkpoint":
ckpt_info = sd_models.get_closet_checkpoint_match(value)
if ckpt_info is not None:
value = ckpt_info.title
else:
return gr.update()
comp_args = opts.data_labels[key].component_args
if comp_args and isinstance(comp_args, dict) and comp_args.get('visible') is False:
return
valtype = type(opts.data_labels[key].default)
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 getattr(opts, key)
def create_output_panel(tabname, outdir, toprow=None):
return ui_common.create_output_panel(tabname, outdir, toprow)
def ordered_ui_categories():
user_order = {x.strip(): i * 2 + 1 for i, x in enumerate(shared.opts.ui_reorder_list)}
for _, category in sorted(enumerate(shared_items.ui_reorder_categories()), key=lambda x: user_order.get(x[1], x[0] * 2 + 0)):
yield category
def create_override_settings_dropdown(tabname, row):
dropdown = gr.Dropdown([], label="Override settings", visible=False, elem_id=f"{tabname}_override_settings", multiselect=True)
dropdown.change(
fn=lambda x: gr.Dropdown.update(visible=bool(x)),
inputs=[dropdown],
outputs=[dropdown],
)
return dropdown
def create_ui():
import modules.img2img
import modules.txt2img
reload_javascript()
parameters_copypaste.reset()
settings = ui_settings.UiSettings()
settings.register_settings()
scripts.scripts_current = scripts.scripts_txt2img
scripts.scripts_txt2img.initialize_scripts(is_img2img=False)
with gr.Blocks(analytics_enabled=False) as txt2img_interface:
toprow = ui_toprow.Toprow(is_img2img=False, is_compact=shared.opts.compact_prompt_box)
dummy_component = gr.Label(visible=False)
extra_tabs = gr.Tabs(elem_id="txt2img_extra_tabs", elem_classes=["extra-networks"])
extra_tabs.__enter__()
with gr.Tab("Generation", id="txt2img_generation") as txt2img_generation_tab, ResizeHandleRow(equal_height=False):
with ExitStack() as stack:
if shared.opts.txt2img_settings_accordion:
stack.enter_context(gr.Accordion("Open for Settings", open=False))
stack.enter_context(gr.Column(variant='compact', elem_id="txt2img_settings"))
scripts.scripts_txt2img.prepare_ui()
for category in ordered_ui_categories():
if category == "prompt":
toprow.create_inline_toprow_prompts()
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")
with gr.Column(elem_id="txt2img_dimensions_row", scale=1, elem_classes="dimensions-tools"):
res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="txt2img_res_switch_btn", tooltip="Switch width/height")
if opts.dimensions_and_batch_together:
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":
with gr.Row():
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 == "checkboxes":
with FormRow(elem_classes="checkboxes-row", variant="compact"):
pass
elif category == "accordions":
with gr.Row(elem_id="txt2img_accordions", elem_classes="accordions"):
with InputAccordion(False, label="Hires. fix", elem_id="txt2img_hr") as enable_hr:
with enable_hr.extra():
hr_final_resolution = FormHTML(value="", elem_id="txtimg_hr_finalres", label="Upscaled resolution", interactive=False, min_width=0)
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")
with FormRow(elem_id="txt2img_hires_fix_row3", variant="compact", visible=opts.hires_fix_show_sampler) as hr_sampler_container:
hr_checkpoint_name = gr.Dropdown(label='Checkpoint', elem_id="hr_checkpoint", choices=["Use same checkpoint"] + modules.sd_models.checkpoint_tiles(use_short=True), value="Use same checkpoint")
create_refresh_button(hr_checkpoint_name, modules.sd_models.list_models, lambda: {"choices": ["Use same checkpoint"] + modules.sd_models.checkpoint_tiles(use_short=True)}, "hr_checkpoint_refresh")
hr_sampler_name = gr.Dropdown(label='Hires sampling method', elem_id="hr_sampler", choices=["Use same sampler"] + sd_samplers.visible_sampler_names(), value="Use same sampler")
hr_scheduler = gr.Dropdown(label='Hires schedule type', elem_id="hr_scheduler", choices=["Use same scheduler"] + [x.label for x in sd_schedulers.schedulers], value="Use same scheduler")
with FormRow(elem_id="txt2img_hires_fix_row4", variant="compact", visible=opts.hires_fix_show_prompts) as hr_prompts_container:
with gr.Column(scale=80):
with gr.Row():
hr_prompt = gr.Textbox(label="Hires prompt", elem_id="hires_prompt", show_label=False, lines=3, placeholder="Prompt for hires fix pass.\nLeave empty to use the same prompt as in first pass.", elem_classes=["prompt"])
with gr.Column(scale=80):
with gr.Row():
hr_negative_prompt = gr.Textbox(label="Hires negative prompt", elem_id="hires_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt for hires fix pass.\nLeave empty to use the same negative prompt as in first pass.", elem_classes=["prompt"])
with InputAccordion(False, label="Progressive Growing", elem_id="txt2img_progressive_growing") as enable_progressive_growing:
with FormRow(elem_id="txt2img_progressive_growing_row1", variant="compact"):
progressive_growing_min_scale = gr.Slider(minimum=0.1, maximum=1.0, step=0.05, label="Min Scale", value=0.25, elem_id="txt2img_progressive_growing_min_scale")
progressive_growing_max_scale = gr.Slider(minimum=0.1, maximum=1.0, step=0.05, label="Max Scale", value=1.0, elem_id="txt2img_progressive_growing_max_scale")
with FormRow(elem_id="txt2img_progressive_growing_row2", variant="compact"):
progressive_growing_steps = gr.Slider(minimum=2, maximum=10, step=1, label="Steps", value=4, elem_id="txt2img_progressive_growing_steps")
progressive_growing_refinement = gr.Checkbox(label="Enable Refinement", value=True, elem_id="txt2img_progressive_growing_refinement")
scripts.scripts_txt2img.setup_ui_for_section(category)
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 == "override_settings":
with FormRow(elem_id="txt2img_override_settings_row") as row:
override_settings = create_override_settings_dropdown('txt2img', row)
elif category == "scripts":
with FormGroup(elem_id="txt2img_script_container"):
custom_inputs = scripts.scripts_txt2img.setup_ui()
if category not in {"accordions"}:
scripts.scripts_txt2img.setup_ui_for_section(category)
hr_resolution_preview_inputs = [enable_hr, width, height, hr_scale, hr_resize_x, hr_resize_y]
for component in hr_resolution_preview_inputs:
event = component.release if isinstance(component, gr.Slider) else component.change
event(
fn=calc_resolution_hires,
inputs=hr_resolution_preview_inputs,
outputs=[hr_final_resolution],
show_progress=False,
)
event(
None,
_js="onCalcResolutionHires",
inputs=hr_resolution_preview_inputs,
outputs=[],
show_progress=False,
)
output_panel = create_output_panel("txt2img", opts.outdir_txt2img_samples, toprow)
txt2img_inputs = [
dummy_component,
toprow.prompt,
toprow.negative_prompt,
toprow.ui_styles.dropdown,
batch_count,
batch_size,
cfg_scale,
height,
width,
enable_hr,
denoising_strength,
hr_scale,
hr_upscaler,
hr_second_pass_steps,
hr_resize_x,
hr_resize_y,
hr_checkpoint_name,
hr_sampler_name,
hr_scheduler,
hr_prompt,
hr_negative_prompt,
override_settings,
enable_progressive_growing,
progressive_growing_min_scale,
progressive_growing_max_scale,
progressive_growing_steps,
progressive_growing_refinement,
] + custom_inputs
txt2img_outputs = [
output_panel.gallery,
output_panel.generation_info,
output_panel.infotext,
output_panel.html_log,
]
txt2img_args = dict(
fn=wrap_gradio_gpu_call(modules.txt2img.txt2img, extra_outputs=[None, '', '']),
_js="submit",
inputs=txt2img_inputs,
outputs=txt2img_outputs,
show_progress=False,
)
toprow.prompt.submit(**txt2img_args)
toprow.submit.click(**txt2img_args)
output_panel.button_upscale.click(
fn=wrap_gradio_gpu_call(modules.txt2img.txt2img_upscale, extra_outputs=[None, '', '']),
_js="submit_txt2img_upscale",
inputs=txt2img_inputs[0:1] + [output_panel.gallery, dummy_component, output_panel.generation_info] + txt2img_inputs[1:],
outputs=txt2img_outputs,
show_progress=False,
)
res_switch_btn.click(fn=None, _js="function(){switchWidthHeight('txt2img')}", inputs=None, outputs=None, show_progress=False)
toprow.restore_progress_button.click(
fn=progress.restore_progress,
_js="restoreProgressTxt2img",
inputs=[dummy_component],
outputs=[
output_panel.gallery,
output_panel.generation_info,
output_panel.infotext,
output_panel.html_log,
],
show_progress=False,
)
txt2img_paste_fields = [
PasteField(toprow.prompt, "Prompt", api="prompt"),
PasteField(toprow.negative_prompt, "Negative prompt", api="negative_prompt"),
PasteField(cfg_scale, "CFG scale", api="cfg_scale"),
PasteField(width, "Size-1", api="width"),
PasteField(height, "Size-2", api="height"),
PasteField(batch_size, "Batch size", api="batch_size"),
PasteField(toprow.ui_styles.dropdown, lambda d: d["Styles array"] if isinstance(d.get("Styles array"), list) else gr.update(), api="styles"),
PasteField(denoising_strength, "Denoising strength", api="denoising_strength"),
PasteField(enable_hr, lambda d: "Denoising strength" in d and ("Hires upscale" in d or "Hires upscaler" in d or "Hires resize-1" in d), api="enable_hr"),
PasteField(hr_scale, "Hires upscale", api="hr_scale"),
PasteField(hr_upscaler, "Hires upscaler", api="hr_upscaler"),
PasteField(hr_second_pass_steps, "Hires steps", api="hr_second_pass_steps"),
PasteField(hr_resize_x, "Hires resize-1", api="hr_resize_x"),
PasteField(hr_resize_y, "Hires resize-2", api="hr_resize_y"),
PasteField(hr_checkpoint_name, "Hires checkpoint", api="hr_checkpoint_name"),
PasteField(hr_sampler_name, sd_samplers.get_hr_sampler_from_infotext, api="hr_sampler_name"),
PasteField(hr_scheduler, sd_samplers.get_hr_scheduler_from_infotext, api="hr_scheduler"),
PasteField(hr_sampler_container, lambda d: gr.update(visible=True) if d.get("Hires sampler", "Use same sampler") != "Use same sampler" or d.get("Hires checkpoint", "Use same checkpoint") != "Use same checkpoint" or d.get("Hires schedule type", "Use same scheduler") != "Use same scheduler" else gr.update()),
PasteField(hr_prompt, "Hires prompt", api="hr_prompt"),
PasteField(hr_negative_prompt, "Hires negative prompt", api="hr_negative_prompt"),
PasteField(hr_prompts_container, lambda d: gr.update(visible=True) if d.get("Hires prompt", "") != "" or d.get("Hires negative prompt", "") != "" else gr.update()),
*scripts.scripts_txt2img.infotext_fields
]
parameters_copypaste.add_paste_fields("txt2img", None, txt2img_paste_fields, override_settings)
parameters_copypaste.register_paste_params_button(parameters_copypaste.ParamBinding(
paste_button=toprow.paste, tabname="txt2img", source_text_component=toprow.prompt, source_image_component=None,
))
steps = scripts.scripts_txt2img.script('Sampler').steps
txt2img_preview_params = [
toprow.prompt,
toprow.negative_prompt,
steps,
scripts.scripts_txt2img.script('Sampler').sampler_name,
cfg_scale,
scripts.scripts_txt2img.script('Seed').seed,
width,
height,
]
toprow.ui_styles.dropdown.change(fn=wrap_queued_call(update_token_counter), inputs=[toprow.prompt, steps, toprow.ui_styles.dropdown], outputs=[toprow.token_counter])
toprow.ui_styles.dropdown.change(fn=wrap_queued_call(update_negative_prompt_token_counter), inputs=[toprow.negative_prompt, steps, toprow.ui_styles.dropdown], outputs=[toprow.negative_token_counter])
toprow.token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[toprow.prompt, steps, toprow.ui_styles.dropdown], outputs=[toprow.token_counter])
toprow.negative_token_button.click(fn=wrap_queued_call(update_negative_prompt_token_counter), inputs=[toprow.negative_prompt, steps, toprow.ui_styles.dropdown], outputs=[toprow.negative_token_counter])
extra_networks_ui = ui_extra_networks.create_ui(txt2img_interface, [txt2img_generation_tab], 'txt2img')
ui_extra_networks.setup_ui(extra_networks_ui, output_panel.gallery)
extra_tabs.__exit__()
scripts.scripts_current = scripts.scripts_img2img
scripts.scripts_img2img.initialize_scripts(is_img2img=True)
with gr.Blocks(analytics_enabled=False) as img2img_interface:
toprow = ui_toprow.Toprow(is_img2img=True, is_compact=shared.opts.compact_prompt_box)
extra_tabs = gr.Tabs(elem_id="img2img_extra_tabs", elem_classes=["extra-networks"])
extra_tabs.__enter__()
with gr.Tab("Generation", id="img2img_generation") as img2img_generation_tab, ResizeHandleRow(equal_height=False):
with ExitStack() as stack:
if shared.opts.img2img_settings_accordion:
stack.enter_context(gr.Accordion("Open for Settings", open=False))
stack.enter_context(gr.Column(variant='compact', elem_id="img2img_settings"))
copy_image_buttons = []
copy_image_destinations = {}
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}")
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
button = gr.Button(title)
copy_image_buttons.append((button, name, elem))
scripts.scripts_img2img.prepare_ui()
for category in ordered_ui_categories():
if category == "prompt":
toprow.create_inline_toprow_prompts()
if category == "image":
with gr.Tabs(elem_id="mode_img2img"):
img2img_selected_tab = gr.Number(value=0, visible=False)
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", height=opts.img2img_editor_height)
add_copy_image_controls('img2img', init_img)
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="RGB", height=opts.img2img_editor_height, brush_color=opts.img2img_sketch_default_brush_color)
add_copy_image_controls('sketch', sketch)
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", height=opts.img2img_editor_height, brush_color=opts.img2img_inpaint_mask_brush_color)
add_copy_image_controls('inpaint', init_img_with_mask)
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="RGB", height=opts.img2img_editor_height, brush_color=opts.img2img_inpaint_sketch_default_brush_color)
inpaint_color_sketch_orig = gr.State(None)
add_copy_image_controls('inpaint_sketch', inpaint_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
inpaint_color_sketch.change(update_orig, [inpaint_color_sketch, inpaint_color_sketch_orig], inpaint_color_sketch_orig)
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", image_mode="RGBA", elem_id="img_inpaint_mask")
with gr.TabItem('Batch', id='batch', elem_id="img2img_batch_tab") as tab_batch:
with gr.Tabs(elem_id="img2img_batch_source"):
img2img_batch_source_type = gr.Textbox(visible=False, value="upload")
with gr.TabItem('Upload', id='batch_upload', elem_id="img2img_batch_upload_tab") as tab_batch_upload:
img2img_batch_upload = gr.Files(label="Files", interactive=True, elem_id="img2img_batch_upload")
with gr.TabItem('From directory', id='batch_from_dir', elem_id="img2img_batch_from_dir_tab") as tab_batch_from_dir:
hidden = '<br>Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else ''
gr.HTML(
"<p style='padding-bottom: 1em;' 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." +
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")
tab_batch_upload.select(fn=lambda: "upload", inputs=[], outputs=[img2img_batch_source_type])
tab_batch_from_dir.select(fn=lambda: "from dir", inputs=[], outputs=[img2img_batch_source_type])
with gr.Accordion("PNG info", open=False):
img2img_batch_use_png_info = gr.Checkbox(label="Append png info to prompts", elem_id="img2img_batch_use_png_info")
img2img_batch_png_info_dir = gr.Textbox(label="PNG info directory", **shared.hide_dirs, placeholder="Leave empty to use input directory", elem_id="img2img_batch_png_info_dir")
img2img_batch_png_info_props = gr.CheckboxGroup(["Prompt", "Negative prompt", "Seed", "CFG scale", "Sampler", "Steps", "Model hash"], label="Parameters to take from png info", info="Prompts from png info will be appended to prompts set in ui.")
img2img_tabs = [tab_img2img, tab_sketch, tab_inpaint, tab_inpaint_color, tab_inpaint_upload, tab_batch]
for i, tab in enumerate(img2img_tabs):
tab.select(fn=lambda tabnum=i: tabnum, inputs=[], outputs=[img2img_selected_tab])
def copy_image(img):
if isinstance(img, dict) and 'image' in img:
return img['image']
return img
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=f"switch_to_{name.replace(' ', '_')}",
inputs=[],
outputs=[],
)
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")
elif category == "dimensions":
with FormRow():
with gr.Column(elem_id="img2img_column_size", scale=4):
selected_scale_tab = gr.Number(value=0, visible=False)
with gr.Tabs():
with gr.Tab(label="Resize to", elem_id="img2img_tab_resize_to") as tab_scale_to:
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")
with gr.Column(elem_id="img2img_dimensions_row", scale=1, elem_classes="dimensions-tools"):
res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="img2img_res_switch_btn", tooltip="Switch width/height")
detect_image_size_btn = ToolButton(value=detect_image_size_symbol, elem_id="img2img_detect_image_size_btn", tooltip="Auto detect size from img2img")
with gr.Tab(label="Resize by", elem_id="img2img_tab_resize_by") as tab_scale_by:
scale_by = gr.Slider(minimum=0.05, maximum=4.0, step=0.05, label="Scale", value=1.0, elem_id="img2img_scale")
with FormRow():
scale_by_html = FormHTML(resize_from_to_html(0, 0, 0.0), elem_id="img2img_scale_resolution_preview")
gr.Slider(label="Unused", elem_id="img2img_unused_scale_by_slider")
button_update_resize_to = gr.Button(visible=False, elem_id="img2img_update_resize_to")
on_change_args = dict(
fn=resize_from_to_html,
_js="currentImg2imgSourceResolution",
inputs=[dummy_component, dummy_component, scale_by],
outputs=scale_by_html,
show_progress=False,
)
scale_by.release(**on_change_args)
button_update_resize_to.click(**on_change_args)
tab_scale_to.select(fn=lambda: 0, inputs=[], outputs=[selected_scale_tab])
tab_scale_by.select(fn=lambda: 1, inputs=[], outputs=[selected_scale_tab])
if opts.dimensions_and_batch_together:
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 == "denoising":
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 == "cfg":
with gr.Row():
cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="img2img_cfg_scale")
image_cfg_scale = gr.Slider(minimum=0, maximum=3.0, step=0.05, label='Image CFG Scale', value=1.5, elem_id="img2img_image_cfg_scale", visible=False)
elif category == "checkboxes":
with FormRow(elem_classes="checkboxes-row", variant="compact"):
pass
elif category == "accordions":
with gr.Row(elem_id="img2img_accordions", elem_classes="accordions"):
scripts.scripts_img2img.setup_ui_for_section(category)
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 == "override_settings":
with FormRow(elem_id="img2img_override_settings_row") as row:
override_settings = create_override_settings_dropdown('img2img', row)
elif category == "scripts":
with FormGroup(elem_id="img2img_script_container"):
custom_inputs = 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")
if category not in {"accordions"}:
scripts.scripts_img2img.setup_ui_for_section(category)
# the code below is meant to update the resolution label after the image in the image selection UI has changed.
# as it is now the event keeps firing continuously for inpaint edits, which ruins the page with constant requests.
# I assume this must be a gradio bug and for now we'll just do it for non-inpaint inputs.
for component in [init_img, sketch]:
component.change(fn=lambda: None, _js="updateImg2imgResizeToTextAfterChangingImage", inputs=[], outputs=[], show_progress=False)
def select_img2img_tab(tab):
return gr.update(visible=tab in [2, 3, 4]), gr.update(visible=tab == 3),
for i, elem in enumerate(img2img_tabs):
elem.select(
fn=lambda tab=i: select_img2img_tab(tab),
inputs=[],
outputs=[inpaint_controls, mask_alpha],
)
output_panel = create_output_panel("img2img", opts.outdir_img2img_samples, toprow)
img2img_args = dict(
fn=wrap_gradio_gpu_call(modules.img2img.img2img, extra_outputs=[None, '', '']),
_js="submit_img2img",
inputs=[
dummy_component,
dummy_component,
toprow.prompt,
toprow.negative_prompt,
toprow.ui_styles.dropdown,
init_img,
sketch,
init_img_with_mask,
inpaint_color_sketch,
inpaint_color_sketch_orig,
init_img_inpaint,
init_mask_inpaint,
mask_blur,
mask_alpha,
inpainting_fill,
batch_count,
batch_size,
cfg_scale,
image_cfg_scale,
denoising_strength,
selected_scale_tab,
height,
width,
scale_by,
resize_mode,
inpaint_full_res,
inpaint_full_res_padding,
inpainting_mask_invert,
img2img_batch_input_dir,
img2img_batch_output_dir,
img2img_batch_inpaint_mask_dir,
override_settings,
img2img_batch_use_png_info,
img2img_batch_png_info_props,
img2img_batch_png_info_dir,
img2img_batch_source_type,
img2img_batch_upload,
] + custom_inputs,
outputs=[
output_panel.gallery,
output_panel.generation_info,
output_panel.infotext,
output_panel.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=[toprow.prompt, dummy_component],
)
toprow.prompt.submit(**img2img_args)
toprow.submit.click(**img2img_args)
res_switch_btn.click(fn=None, _js="function(){switchWidthHeight('img2img')}", inputs=None, outputs=None, show_progress=False)
detect_image_size_btn.click(
fn=lambda w, h, _: (w or gr.update(), h or gr.update()),
_js="currentImg2imgSourceResolution",
inputs=[dummy_component, dummy_component, dummy_component],
outputs=[width, height],
show_progress=False,
)
toprow.restore_progress_button.click(
fn=progress.restore_progress,
_js="restoreProgressImg2img",
inputs=[dummy_component],
outputs=[
output_panel.gallery,
output_panel.generation_info,
output_panel.infotext,
output_panel.html_log,
],
show_progress=False,
)
toprow.button_interrogate.click(
fn=lambda *args: process_interrogate(interrogate, *args),
**interrogate_args,
)
toprow.button_deepbooru.click(
fn=lambda *args: process_interrogate(interrogate_deepbooru, *args),
**interrogate_args,
)
steps = scripts.scripts_img2img.script('Sampler').steps
toprow.ui_styles.dropdown.change(fn=wrap_queued_call(update_token_counter), inputs=[toprow.prompt, steps, toprow.ui_styles.dropdown], outputs=[toprow.token_counter])
toprow.ui_styles.dropdown.change(fn=wrap_queued_call(update_negative_prompt_token_counter), inputs=[toprow.negative_prompt, steps, toprow.ui_styles.dropdown], outputs=[toprow.negative_token_counter])
toprow.token_button.click(fn=update_token_counter, inputs=[toprow.prompt, steps, toprow.ui_styles.dropdown], outputs=[toprow.token_counter])
toprow.negative_token_button.click(fn=wrap_queued_call(update_negative_prompt_token_counter), inputs=[toprow.negative_prompt, steps, toprow.ui_styles.dropdown], outputs=[toprow.negative_token_counter])
img2img_paste_fields = [
(toprow.prompt, "Prompt"),
(toprow.negative_prompt, "Negative prompt"),
(cfg_scale, "CFG scale"),
(image_cfg_scale, "Image CFG scale"),
(width, "Size-1"),
(height, "Size-2"),
(batch_size, "Batch size"),
(toprow.ui_styles.dropdown, lambda d: d["Styles array"] if isinstance(d.get("Styles array"), list) else gr.update()),
(denoising_strength, "Denoising strength"),
(mask_blur, "Mask blur"),
(inpainting_mask_invert, 'Mask mode'),
(inpainting_fill, 'Masked content'),
(inpaint_full_res, 'Inpaint area'),
(inpaint_full_res_padding, 'Masked area padding'),
*scripts.scripts_img2img.infotext_fields
]
parameters_copypaste.add_paste_fields("img2img", init_img, img2img_paste_fields, override_settings)
parameters_copypaste.add_paste_fields("inpaint", init_img_with_mask, img2img_paste_fields, override_settings)
parameters_copypaste.register_paste_params_button(parameters_copypaste.ParamBinding(
paste_button=toprow.paste, tabname="img2img", source_text_component=toprow.prompt, source_image_component=None,
))
extra_networks_ui_img2img = ui_extra_networks.create_ui(img2img_interface, [img2img_generation_tab], 'img2img')
ui_extra_networks.setup_ui(extra_networks_ui_img2img, output_panel.gallery)
extra_tabs.__exit__()
scripts.scripts_current = None
with gr.Blocks(analytics_enabled=False) as extras_interface:
ui_postprocessing.create_ui()
with gr.Blocks(analytics_enabled=False) as pnginfo_interface:
with ResizeHandleRow(equal_height=False):
with gr.Column(variant='panel'):
image = gr.Image(elem_id="pnginfo_image", label="Source", source="upload", interactive=True, type="pil")
with gr.Column(variant='panel'):
html = gr.HTML()
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"])
for tabname, button in buttons.items():
parameters_copypaste.register_paste_params_button(parameters_copypaste.ParamBinding(
paste_button=button, tabname=tabname, source_text_component=generation_info, source_image_component=image,
))
image.change(
fn=wrap_gradio_call(modules.extras.run_pnginfo),
inputs=[image],
outputs=[html, generation_info, html2],
)
modelmerger_ui = ui_checkpoint_merger.UiCheckpointMerger()
with gr.Blocks(analytics_enabled=False) as train_interface:
with gr.Row(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 ResizeHandleRow(variant="compact", equal_height=False):
with gr.Tabs(elem_id="train_tabs"):
with gr.Tab(label="Create embedding", id="create_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', elem_id="train_create_embedding")
with gr.Tab(label="Create hypernetwork", id="create_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=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', elem_id="train_create_hypernetwork")
def get_textual_inversion_template_names():
return sorted(textual_inversion.textual_inversion_templates)
with gr.Tab(label="Train", id="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 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")
train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=sorted(shared.hypernetworks))
create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted(shared.hypernetworks)}, "refresh_train_hypernetwork_name")
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")
use_weight = gr.Checkbox(label="Use PNG alpha channel as loss weight", value=False, elem_id="use_weight")
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")