Foreign-Mirrors/Fooocus
1
0
Fork 0
mirror of https://github.com/lllyasviel/Fooocus.git synced 2026-08-16 13:13:16 +02:00
Code Issues Packages Projects Releases Wiki Activity

feat: add option to process uov either before or after enhance

Browse Source
This commit is contained in:
Manuel Schmid
2024-06-23 17:41:21 +02:00
parent 7ecaee8285
commit 1ef6367635
5 changed files with 85 additions and 37 deletions
Download Patch File Download Diff File Expand all files Collapse all files
modules/async_worker.py
+61 -33
View File
@@ -116,6 +116,7 @@ class AsyncTask:
self.enhance_input_image = args.pop()
self.enhance_checkbox = args.pop()
self.enhance_uov_method = args.pop()
self.enhance_uov_processing_order = args.pop()
self.enhance_ctrls = []
for _ in range(modules.config.default_enhance_tabs):
enhance_enabled = args.pop()
@@ -1018,6 +1019,45 @@ def worker():
del task_enhance['c'], task_enhance['uc'] # Save memory
return current_progress, imgs[0]
def enhance_upscale(all_steps, async_task, base_progress, callback, controlnet_canny_path, controlnet_cpds_path,
current_task_id, denoising_strength, done_steps_inpainting, done_steps_upscaling, enhance_steps,
final_scheduler_name, height, img, preparation_steps, switch, tiled, total_count, use_expansion,
use_style, use_synthetic_refiner, width):
# reset inpaint worker to prevent tensor size issues and not mix upscale and inpainting
inpaint_worker.current_task = None
current_task_id += 1
current_progress = int(base_progress + (100 - preparation_steps) / float(all_steps) * (done_steps_upscaling + done_steps_inpainting))
goals_enhance = []
img, skip_prompt_processing, steps = prepare_upscale(
async_task, goals_enhance, img, async_task.enhance_uov_method, async_task.performance_selection,
enhance_steps, current_progress)
steps, _, _, _ = apply_overrides(async_task, steps, height, width)
exception_result = ''
if len(goals_enhance) > 0:
try:
current_progress, img = process_enhance(
all_steps, async_task, callback, controlnet_canny_path,
controlnet_cpds_path, current_progress, current_task_id, denoising_strength, False,
'None', 0.0, 0.0, async_task.negative_prompt, async_task.prompt, final_scheduler_name,
goals_enhance, height, img, None, preparation_steps, steps, switch, tiled, total_count,
use_expansion, use_style, use_synthetic_refiner, width)
except ldm_patched.modules.model_management.InterruptProcessingException:
if async_task.last_stop == 'skip':
print('User skipped')
async_task.last_stop = False
# also skip all enhance steps for this image, but add the steps to the progress bar
if async_task.enhance_uov_processing_order == flags.enhancement_uov_before:
done_steps_inpainting += len(async_task.enhance_ctrls) * enhance_steps
exception_result = 'continue'
else:
print('User stopped')
exception_result = 'break'
finally:
done_steps_upscaling += steps
return current_task_id, done_steps_inpainting, done_steps_upscaling, img, exception_result
@torch.no_grad()
@torch.inference_mode()
def handler(async_task: AsyncTask):
@@ -1277,39 +1317,16 @@ def worker():
for img in images_to_enhance:
enhancement_image_start_time = time.perf_counter()
# upscale if not disabled or already in goals
if should_process_enhance_uov:
current_task_id += 1
current_progress = int(base_progress + (100 - preparation_steps) / float(all_steps) * (done_steps_upscaling + done_steps_inpainting))
goals_enhance = []
img, skip_prompt_processing, steps = prepare_upscale(async_task, goals_enhance, img,
async_task.enhance_uov_method,
async_task.performance_selection,
enhance_steps, current_progress)
steps, _, _, _ = apply_overrides(async_task, steps, height, width)
if len(goals_enhance) > 0:
try:
current_progress, img = process_enhance(
all_steps, async_task, callback, controlnet_canny_path,
controlnet_cpds_path, current_progress, current_task_id, denoising_strength, False,
'None', 0.0, 0.0, async_task.negative_prompt, async_task.prompt, final_scheduler_name,
goals_enhance, height, img, None, preparation_steps, steps, switch, tiled, total_count,
use_expansion, use_style, use_synthetic_refiner, width)
except ldm_patched.modules.model_management.InterruptProcessingException:
if async_task.last_stop == 'skip':
print('User skipped')
async_task.last_stop = False
# also skip all enhance steps for this image, but add the steps to the progress bar
done_steps_inpainting += len(async_task.enhance_ctrls) * enhance_steps
continue
else:
print('User stopped')
break
finally:
done_steps_upscaling += steps
if should_process_enhance_uov and async_task.enhance_uov_processing_order == flags.enhancement_uov_before:
current_task_id, done_steps_inpainting, done_steps_upscaling, img, exception_result = enhance_upscale(
all_steps, async_task, base_progress, callback, controlnet_canny_path, controlnet_cpds_path,
current_task_id, denoising_strength, done_steps_inpainting, done_steps_upscaling, enhance_steps,
final_scheduler_name, height, img, preparation_steps, switch, tiled, total_count, use_expansion,
use_style, use_synthetic_refiner, width)
if exception_result == 'continue':
continue
elif exception_result == 'break':
break
# inpaint for all other tabs
for enhance_mask_dino_prompt_text, enhance_prompt, enhance_negative_prompt, enhance_mask_model, enhance_mask_sam_model, enhance_mask_text_threshold, enhance_mask_box_threshold, enhance_mask_sam_max_detections, enhance_inpaint_disable_initial_latent, enhance_inpaint_engine, enhance_inpaint_strength, enhance_inpaint_respective_field, enhance_inpaint_erode_or_dilate, enhance_mask_invert in async_task.enhance_ctrls:
@@ -1379,6 +1396,17 @@ def worker():
enhancement_task_time = time.perf_counter() - enhancement_task_start_time
print(f'Enhancement time: {enhancement_task_time:.2f} seconds')
if should_process_enhance_uov and async_task.enhance_uov_processing_order == flags.enhancement_uov_after:
current_task_id, done_steps_inpainting, done_steps_upscaling, img, exception_result = enhance_upscale(
all_steps, async_task, base_progress, callback, controlnet_canny_path, controlnet_cpds_path,
current_task_id, denoising_strength, done_steps_inpainting, done_steps_upscaling, enhance_steps,
final_scheduler_name, height, img, preparation_steps, switch, tiled, total_count, use_expansion,
use_style, use_synthetic_refiner, width)
if exception_result == 'continue':
continue
elif exception_result == 'break':
break
enhancement_image_time = time.perf_counter() - enhancement_image_start_time
print(f'Enhancement image time: {enhancement_image_time:.2f} seconds')
modules/config.py
+6
View File
@@ -515,6 +515,12 @@ default_enhance_tabs = get_config_item_or_set_default(
validator=lambda x: isinstance(x, int) and 1 <= x <= 5,
expected_type=int
)
enhance_uov_processing_order = get_config_item_or_set_default(
key='default_enhance_uov_processing_order',
default_value=modules.flags.enhancement_uov_before,
validator=lambda x: x in modules.flags.enhancement_uov_processing_order,
expected_type=int
)
default_sam_max_detections = get_config_item_or_set_default(
key='default_sam_max_detections',
default_value=0,
modules/flags.py
+9
View File
@@ -12,6 +12,15 @@ uov_list = [
disabled, subtle_variation, strong_variation, upscale_15, upscale_2, upscale_fast
]
enhancement_uov_before = "before"
enhancement_uov_before_label = "Before First Enhancement"
enhancement_uov_after = "after"
enhancement_uov_after_label = "After Last Enhancement"
enhancement_uov_processing_order = [
(enhancement_uov_before_label, enhancement_uov_before),
(enhancement_uov_after_label, enhancement_uov_after)
]
CIVITAI_NO_KARRAS = ["euler", "euler_ancestral", "heun", "dpm_fast", "dpm_adaptive", "ddim", "uni_pc"]
# fooocus: a1111 (Civitai)