Foreign-Mirrors/Fooocus
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Merge branch 'develop' into lora-reference-parsing

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This commit is contained in:
Manuel Schmid
2024-05-18 17:00:25 +02:00
committed by GitHub
parent f4fc21d05d 3a55e7e391
commit eebfcac83f
31 changed files with 734 additions and 100 deletions
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modules/async_worker.py
+36 -15
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@@ -43,7 +43,8 @@ def worker():
import fooocus_version
import args_manager
from modules.sdxl_styles import apply_style, fooocus_expansion, apply_arrays
from extras.censor import censor_batch, censor_single
from modules.sdxl_styles import apply_style, get_random_style, apply_wildcards, fooocus_expansion, apply_arrays, random_style_name
from modules.private_logger import log
from extras.expansion import safe_str
from modules.util import (remove_empty_str, HWC3, resize_image, get_image_shape_ceil, set_image_shape_ceil,
@@ -69,10 +70,14 @@ def worker():
print(f'[Fooocus] {text}')
async_task.yields.append(['preview', (number, text, None)])
def yield_result(async_task, imgs, do_not_show_finished_images=False):
def yield_result(async_task, imgs, black_out_nsfw, censor=True, do_not_show_finished_images=False, progressbar_index=13):
if not isinstance(imgs, list):
imgs = [imgs]
if censor and (modules.config.default_black_out_nsfw or black_out_nsfw):
progressbar(async_task, progressbar_index, 'Checking for NSFW content ...')
imgs = censor_batch(imgs)
async_task.results = async_task.results + imgs
if do_not_show_finished_images:
@@ -161,12 +166,14 @@ def worker():
disable_preview = args.pop()
disable_intermediate_results = args.pop()
disable_seed_increment = args.pop()
black_out_nsfw = args.pop()
adm_scaler_positive = args.pop()
adm_scaler_negative = args.pop()
adm_scaler_end = args.pop()
adaptive_cfg = args.pop()
sampler_name = args.pop()
scheduler_name = args.pop()
vae_name = args.pop()
overwrite_step = args.pop()
overwrite_switch = args.pop()
overwrite_width = args.pop()
@@ -432,7 +439,7 @@ def worker():
pipeline.refresh_everything(refiner_model_name=refiner_model_name, base_model_name=base_model_name,
loras=loras, base_model_additional_loras=base_model_additional_loras,
use_synthetic_refiner=use_synthetic_refiner)
use_synthetic_refiner=use_synthetic_refiner, vae_name=vae_name)
progressbar(async_task, 3, 'Processing prompts ...')
tasks = []
@@ -453,8 +460,12 @@ def worker():
positive_basic_workloads = []
negative_basic_workloads = []
task_styles = style_selections.copy()
if use_style:
for s in style_selections:
for i, s in enumerate(task_styles):
if s == random_style_name:
s = get_random_style(task_rng)
task_styles[i] = s
p, n = apply_style(s, positive=task_prompt)
positive_basic_workloads = positive_basic_workloads + p
negative_basic_workloads = negative_basic_workloads + n
@@ -482,6 +493,7 @@ def worker():
negative_top_k=len(negative_basic_workloads),
log_positive_prompt='\n'.join([task_prompt] + task_extra_positive_prompts),
log_negative_prompt='\n'.join([task_negative_prompt] + task_extra_negative_prompts),
styles=task_styles
))
if use_expansion:
@@ -576,8 +588,11 @@ def worker():
if direct_return:
d = [('Upscale (Fast)', 'upscale_fast', '2x')]
if modules.config.default_black_out_nsfw or black_out_nsfw:
progressbar(async_task, 100, 'Checking for NSFW content ...')
uov_input_image = censor_single(uov_input_image)
uov_input_image_path = log(uov_input_image, d, output_format=output_format)
yield_result(async_task, uov_input_image_path, do_not_show_finished_images=True)
yield_result(async_task, uov_input_image_path, black_out_nsfw, False, do_not_show_finished_images=True)
return
tiled = True
@@ -641,8 +656,7 @@ def worker():
)
if debugging_inpaint_preprocessor:
yield_result(async_task, inpaint_worker.current_task.visualize_mask_processing(),
do_not_show_finished_images=True)
yield_result(async_task, inpaint_worker.current_task.visualize_mask_processing(), black_out_nsfw, do_not_show_finished_images=True)
return
progressbar(async_task, 13, 'VAE Inpaint encoding ...')
@@ -705,7 +719,7 @@ def worker():
cn_img = HWC3(cn_img)
task[0] = core.numpy_to_pytorch(cn_img)
if debugging_cn_preprocessor:
yield_result(async_task, cn_img, do_not_show_finished_images=True)
yield_result(async_task, cn_img, black_out_nsfw, do_not_show_finished_images=True)
return
for task in cn_tasks[flags.cn_cpds]:
cn_img, cn_stop, cn_weight = task
@@ -717,7 +731,7 @@ def worker():
cn_img = HWC3(cn_img)
task[0] = core.numpy_to_pytorch(cn_img)
if debugging_cn_preprocessor:
yield_result(async_task, cn_img, do_not_show_finished_images=True)
yield_result(async_task, cn_img, black_out_nsfw, do_not_show_finished_images=True)
return
for task in cn_tasks[flags.cn_ip]:
cn_img, cn_stop, cn_weight = task
@@ -728,7 +742,7 @@ def worker():
task[0] = ip_adapter.preprocess(cn_img, ip_adapter_path=ip_adapter_path)
if debugging_cn_preprocessor:
yield_result(async_task, cn_img, do_not_show_finished_images=True)
yield_result(async_task, cn_img, black_out_nsfw, do_not_show_finished_images=True)
return
for task in cn_tasks[flags.cn_ip_face]:
cn_img, cn_stop, cn_weight = task
@@ -742,7 +756,7 @@ def worker():
task[0] = ip_adapter.preprocess(cn_img, ip_adapter_path=ip_adapter_face_path)
if debugging_cn_preprocessor:
yield_result(async_task, cn_img, do_not_show_finished_images=True)
yield_result(async_task, cn_img, black_out_nsfw, do_not_show_finished_images=True)
return
all_ip_tasks = cn_tasks[flags.cn_ip] + cn_tasks[flags.cn_ip_face]
@@ -842,11 +856,17 @@ def worker():
imgs = [inpaint_worker.current_task.post_process(x) for x in imgs]
img_paths = []
if modules.config.default_black_out_nsfw or black_out_nsfw:
progressbar(async_task, int(15.0 + 85.0 * float((current_task_id + 1) * steps) / float(all_steps)),
'Checking for NSFW content ...')
imgs = censor_batch(imgs)
for x in imgs:
d = [('Prompt', 'prompt', task['log_positive_prompt']),
('Negative Prompt', 'negative_prompt', task['log_negative_prompt']),
('Fooocus V2 Expansion', 'prompt_expansion', task['expansion']),
('Styles', 'styles', str(raw_style_selections)),
('Styles', 'styles', str(task['styles'] if not use_expansion else [fooocus_expansion] + task['styles'])),
('Performance', 'performance', performance_selection.value)]
if performance_selection.steps() != steps:
@@ -873,6 +893,7 @@ def worker():
d.append(('Sampler', 'sampler', sampler_name))
d.append(('Scheduler', 'scheduler', scheduler_name))
d.append(('VAE', 'vae', vae_name))
d.append(('Seed', 'seed', str(task['task_seed'])))
if freeu_enabled:
@@ -887,12 +908,12 @@ def worker():
metadata_parser = modules.meta_parser.get_metadata_parser(metadata_scheme)
metadata_parser.set_data(task['log_positive_prompt'], task['positive'],
task['log_negative_prompt'], task['negative'],
steps, base_model_name, refiner_model_name, loras)
steps, base_model_name, refiner_model_name, loras, vae_name)
d.append(('Metadata Scheme', 'metadata_scheme', metadata_scheme.value if save_metadata_to_images else save_metadata_to_images))
d.append(('Version', 'version', 'Fooocus v' + fooocus_version.version))
img_paths.append(log(x, d, metadata_parser, output_format))
img_paths.append(log(x, d, metadata_parser, output_format, task))
yield_result(async_task, img_paths, do_not_show_finished_images=len(tasks) == 1 or disable_intermediate_results)
yield_result(async_task, img_paths, black_out_nsfw, False, do_not_show_finished_images=len(tasks) == 1 or disable_intermediate_results)
except ldm_patched.modules.model_management.InterruptProcessingException as e:
if async_task.last_stop == 'skip':
print('User skipped')