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mirror of https://github.com/vladmandic/automatic synced 2026-09-18 16:54:33 +02:00
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modular guiders and other stuff

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Signed-off-by: Vladimir Mandic <mandic00@live.com>
This commit is contained in:
Vladimir Mandic
2026-08-30 11:51:19 +02:00
parent 7f430aae4e
commit 34d9d304db
32 changed files with 300 additions and 298 deletions
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modules/processing_args.py
+7 -4
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@@ -31,6 +31,9 @@ def task_modular_kwargs(p, model):
if len(getattr(p, 'init_images', [])) > 0:
task_args['image'] = p.init_images
task_args['strength'] = p.denoising_strength
if (shared.sd_model_type == 'sdxl') and hasattr(model, 'register_to_config') and (model_cls not in sd_models.i2i_pipes):
model.register_to_config(requires_aesthetics_score = False)
mask_image = p.task_args.get('image_mask', None) or getattr(p, 'image_mask', None) or getattr(p, 'mask', None)
if mask_image is not None:
task_args['mask_image'] = mask_image
@@ -68,8 +71,8 @@ def task_specific_kwargs(p, model):
'width': width,
'height': height,
}
elif (task_type == sd_models.DiffusersTaskType.IMAGE_2_IMAGE or is_img2img_model) and len(getattr(p, 'init_images', [])) > 0:
if shared.sd_model_type == 'sdxl' and hasattr(model, 'register_to_config'):
elif (task_type == sd_models.DiffusersTaskType.IMAGE_2_IMAGE or task_type == sd_models.DiffusersTaskType.MODULAR or is_img2img_model) and (len(getattr(p, 'init_images', [])) > 0):
if (shared.sd_model_type == 'sdxl') and hasattr(model, 'register_to_config'):
if model_cls in sd_models.i2i_pipes:
pass
else:
@@ -115,7 +118,7 @@ def task_specific_kwargs(p, model):
'image': p.init_images,
'strength': p.denoising_strength,
}
elif (task_type == sd_models.DiffusersTaskType.INPAINTING or is_img2img_model) and len(getattr(p, 'init_images', [])) > 0:
elif (task_type == sd_models.DiffusersTaskType.INPAINTING or task_type == sd_models.DiffusersTaskType.MODULAR or is_img2img_model) and len(getattr(p, 'init_images', [])) > 0:
if shared.sd_model_type == 'sdxl' and hasattr(model, 'register_to_config'):
if model_cls in [sd_models.i2i_pipes]:
pass
@@ -255,7 +258,7 @@ def set_pipeline_args(p, model, prompts:list, negative_prompts:list, prompts_2:l
possible = get_params(model)
log.debug(f'Pipeline: cls={cls} possible={possible}')
debug_log(f'Pipeline: cls={cls} possible={possible}')
steps = kwargs.get("num_inference_steps", None) or len(getattr(p, 'timesteps', ['1']))
clip_skip = kwargs.pop("clip_skip", 1)