ChrisColeTech
parent
e268cd528b
commit
83d0935ec8
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@ -171,8 +171,6 @@ class AsyncTask:
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self.all_steps = None
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self.total_count = None
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self.current_async_task = None
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self.should_run = True
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self.should_skip = False
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async_tasks = []
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@ -1136,16 +1134,13 @@ def worker():
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def print_user_skipped(async_task):
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print('User skipped')
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async_task.last_stop = False
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async_task.should_skip = True
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progressbar(async_task, 0,
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'Image skipped')
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print(
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"\n\n⚠️ Image skipped ... ⚠️\n\n")
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time.sleep(0.1)
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def print_user_stopped(async_task):
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print('User stopped')
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async_task.should_run = False
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print(
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"\n\n 💥 Processing was interrupted by the user. Please try again. 💥\n\n ")
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@ -1211,14 +1206,6 @@ def worker():
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current_task_number,
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persist_image=True
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):
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if not async_task.should_run:
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stop_processing(async_task, async_task.processing_start_time)
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return
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if async_task.should_skip:
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return
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index = current_task_id
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progressbar(async_task, current_progress,
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@ -1335,32 +1322,23 @@ def worker():
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goals_enhance = ['inpaint']
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try:
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current_progress, img, enhance_prompt_processed, enhance_negative_prompt_processed = process_enhance(
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all_steps, async_task, callback, controlnet_canny_path, controlnet_cpds_path,
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current_progress, current_task_id, denoising_strength, enhance_inpaint_disable_initial_latent,
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enhance_inpaint_engine, enhance_inpaint_respective_field, enhance_inpaint_strength,
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enhance_prompt, enhance_negative_prompt, final_scheduler_name, goals_enhance, height, img, mask,
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preparation_steps, enhance_steps, switch, tiled, total_count, use_expansion, use_style,
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use_synthetic_refiner, width, persist_image=persist_image)
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async_task.enhance_stats[index] += 1
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current_progress, img, enhance_prompt_processed, enhance_negative_prompt_processed = process_enhance(
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all_steps, async_task, callback, controlnet_canny_path, controlnet_cpds_path,
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current_progress, current_task_id, denoising_strength, enhance_inpaint_disable_initial_latent,
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enhance_inpaint_engine, enhance_inpaint_respective_field, enhance_inpaint_strength,
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enhance_prompt, enhance_negative_prompt, final_scheduler_name, goals_enhance, height, img, mask,
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preparation_steps, enhance_steps, switch, tiled, total_count, use_expansion, use_style,
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use_synthetic_refiner, width, persist_image=persist_image)
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async_task.enhance_stats[index] += 1
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if (should_process_enhance_uov and async_task.enhance_uov_processing_order == flags.enhancement_uov_after
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and async_task.enhance_uov_prompt_type == flags.enhancement_uov_prompt_type_last_filled):
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if enhance_prompt_processed != '':
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last_enhance_prompt = enhance_prompt_processed
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if enhance_negative_prompt_processed != '':
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last_enhance_negative_prompt = enhance_negative_prompt_processed
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except ldm_patched.modules.model_management.InterruptProcessingException:
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if async_task.last_stop == 'skip':
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print_user_skipped(async_task)
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continue
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else:
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print_user_stopped(async_task)
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break
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if (should_process_enhance_uov and async_task.enhance_uov_processing_order == flags.enhancement_uov_after
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and async_task.enhance_uov_prompt_type == flags.enhancement_uov_prompt_type_last_filled):
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if enhance_prompt_processed != '':
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last_enhance_prompt = enhance_prompt_processed
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if enhance_negative_prompt_processed != '':
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last_enhance_negative_prompt = enhance_negative_prompt_processed
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finally:
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done_steps_inpainting += enhance_steps
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done_steps_inpainting += enhance_steps
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enhancement_task_time = time.perf_counter() - enhancement_task_start_time
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print(
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@ -1409,52 +1387,51 @@ def worker():
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use_synthetic_refiner
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):
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for index, file_name in enumerate(files):
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async_task.current_task_id = index
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try:
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async_task.current_task_id = index
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if not async_task.should_run:
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print_user_stopped(async_task)
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progressbar(async_task, 0,
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'Stopping ...')
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break
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# Build full path to the file
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image = grh.Image(type='numpy')._format_image(Image.open(
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file_name))
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image = HWC3(image)
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if async_task.should_skip:
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print_user_skipped(async_task)
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async_task.should_skip = False
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continue
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# Add the image to the list
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images_to_enhance = [image]
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# Build full path to the file
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image = grh.Image(type='numpy')._format_image(Image.open(
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file_name))
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image = HWC3(image)
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_, height, width = image.shape # Unpack the shape into C, H, W
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# Add the image to the list
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images_to_enhance = [image]
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_, height, width = image.shape # Unpack the shape into C, H, W
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yield_result(async_task, image, current_progress, async_task.black_out_nsfw, False,
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async_task.disable_intermediate_results)
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enhance_images(
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images_to_enhance,
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async_task,
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0,
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current_progress,
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all_steps,
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height,
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width,
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bulk_enhance_callback,
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controlnet_canny_path,
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controlnet_cpds_path,
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denoising_strength,
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final_scheduler_name,
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preparation_steps,
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switch,
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tiled,
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use_expansion,
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use_style,
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use_synthetic_refiner,
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0
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)
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yield_result(async_task, image, current_progress, async_task.black_out_nsfw, False,
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async_task.disable_intermediate_results)
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enhance_images(
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images_to_enhance,
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async_task,
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0,
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current_progress,
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all_steps,
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height,
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width,
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bulk_enhance_callback,
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controlnet_canny_path,
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controlnet_cpds_path,
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denoising_strength,
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final_scheduler_name,
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preparation_steps,
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switch,
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tiled,
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use_expansion,
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use_style,
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use_synthetic_refiner,
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0
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)
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except ldm_patched.modules.model_management.InterruptProcessingException:
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if async_task.last_stop == 'skip':
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print_user_skipped(async_task)
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continue
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else:
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print_user_stopped(async_task)
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stop_processing(
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async_task, async_task.processing_start_time)
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break
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@torch.no_grad()
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@torch.inference_mode()
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@ -1694,34 +1671,40 @@ def worker():
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images_to_enhance = []
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if 'enhance' in goals:
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async_task.image_number = 1
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images_to_enhance = [async_task.enhance_input_image]
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height, width, _ = async_task.enhance_input_image.shape
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# input image already provided, processing is skipped
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steps = 0
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yield_result(async_task, async_task.enhance_input_image, current_progress, async_task.black_out_nsfw, False,
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async_task.disable_intermediate_results)
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enhance_images(
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images_to_enhance,
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async_task,
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0,
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current_progress,
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all_steps,
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height,
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width,
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bulk_enhance_callback,
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controlnet_canny_path,
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controlnet_cpds_path,
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denoising_strength,
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final_scheduler_name,
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preparation_steps,
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switch,
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tiled,
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use_expansion,
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use_style,
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use_synthetic_refiner,
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0
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)
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try:
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async_task.image_number = 1
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images_to_enhance = [async_task.enhance_input_image]
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height, width, _ = async_task.enhance_input_image.shape
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# input image already provided, processing is skipped
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steps = 0
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yield_result(async_task, async_task.enhance_input_image, current_progress, async_task.black_out_nsfw, False,
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async_task.disable_intermediate_results)
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enhance_images(
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images_to_enhance,
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async_task,
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0,
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current_progress,
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all_steps,
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height,
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width,
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bulk_enhance_callback,
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controlnet_canny_path,
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controlnet_cpds_path,
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denoising_strength,
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final_scheduler_name,
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preparation_steps,
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switch,
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tiled,
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use_expansion,
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use_style,
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use_synthetic_refiner,
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0
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)
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except ldm_patched.modules.model_management.InterruptProcessingException:
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if async_task.last_stop == 'skip':
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print_user_skipped(async_task)
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else:
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print_user_stopped(async_task)
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if 'bulk_enhance_files' in goals:
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files = []
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@ -1797,7 +1780,7 @@ def worker():
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progressbar(async_task, current_progress,
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f'Preparing task {current_task_id + 1}/{async_task.image_number} ...')
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current_task_number = current_task_id + 1
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inpaint_worker.current_task = None
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setup(async_task, current_task_number)
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patch_samplers(async_task)
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execution_start_time = time.perf_counter()
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try:
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@ -1856,6 +1839,38 @@ def worker():
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stop_processing(async_task, processing_start_time)
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return
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def setup(async_task: AsyncTask, current_task_number):
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base_model_additional_loras = []
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current_progress = 0
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tasks = []
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use_synthetic_refiner = False
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if fooocus_expansion in async_task.style_selections:
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use_expansion = True
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async_task.style_selections.remove(fooocus_expansion)
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else:
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use_expansion = False
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controlnet_canny_path = None
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controlnet_cpds_path = None
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clip_vision_path, ip_negative_path, ip_adapter_path, ip_adapter_face_path = None, None, None, None
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use_style = len(async_task.style_selections) > 0
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# Load or unload CNs
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progressbar(async_task, current_progress, 'Loading control models ...')
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pipeline.refresh_controlnets(
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[controlnet_canny_path, controlnet_cpds_path])
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ip_adapter.load_ip_adapter(
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clip_vision_path, ip_negative_path, ip_adapter_path)
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ip_adapter.load_ip_adapter(
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clip_vision_path, ip_negative_path, ip_adapter_face_path)
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inpaint_worker.current_task = None
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loras = async_task.loras
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tasks, use_expansion, loras, current_progress = process_prompt(async_task, async_task.prompt, async_task.negative_prompt,
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base_model_additional_loras, 1,
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async_task.disable_seed_increment, use_expansion, use_style,
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use_synthetic_refiner, current_progress, advance_progress=True)
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apply_patch_settings(async_task)
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return
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while True:
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time.sleep(0.01)
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if len(async_tasks) > 0:
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2
webui.py
2
webui.py
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@ -199,7 +199,6 @@ with shared.gradio_root:
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def stop_clicked(currentTask):
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import ldm_patched.modules.model_management as model_management
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currentTask.last_stop = 'stop'
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currentTask.should_run = False
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print(
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"\n\n⚠️ Stopping. Please wait ... ⚠️\n\n")
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if (currentTask.processing):
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@ -209,7 +208,6 @@ with shared.gradio_root:
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def skip_clicked(currentTask):
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import ldm_patched.modules.model_management as model_management
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currentTask.last_stop = 'skip'
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currentTask.should_skip = True
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print(
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"\n\n⚠️ Skipping. Please wait ... ⚠️\n\n")
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if (currentTask.processing):
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