mirror of
https://github.com/vladmandic/automatic
synced 2026-09-20 01:31:13 +02:00
Vladimir Mandic
59 lines
2.8 KiB
Python
59 lines
2.8 KiB
Python
from pipelines.lumina_dimmo.lumina_dimoo import LuminaDiMOOPipeline
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from modules.logger import log
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class LuminaDiMOOTextPipeline(LuminaDiMOOPipeline):
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def __call__(self, prompt: list[str], height: int = 1024, width: int = 1024, num_inference_steps: int = 64, cfg_scale: float = 4.0, temperature: float = 1.0, painting_mode=None, painting_image=None, mask_h_ratio: float = 1.0, mask_w_ratio: float = 0.2, use_cache: bool = True, cache_ratio: float = 0.9, refresh_interval: int = 5, warmup_ratio: float = 0.3, **kwargs):
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if isinstance(prompt, list):
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prompt = prompt[0].strip()
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task = "text_to_image"
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log.debug(f'Base args: task={task} height={height} width={width} steps={num_inference_steps} cfg_scale={cfg_scale} temperature={temperature} painting_mode={painting_mode} mask_h_ratio={mask_h_ratio} mask_w_ratio={mask_w_ratio} use_cache={use_cache} cache_ratio={cache_ratio} refresh_interval={refresh_interval} warmup_ratio={warmup_ratio}')
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return super().__call__(
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prompt=prompt,
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task=task,
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height=height,
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width=width,
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num_inference_steps=num_inference_steps,
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cfg_scale=cfg_scale,
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temperature=temperature,
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painting_mode=painting_mode,
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painting_image=painting_image,
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mask_h_ratio=mask_h_ratio,
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mask_w_ratio=mask_w_ratio,
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use_cache=use_cache,
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cache_ratio=cache_ratio,
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refresh_interval=refresh_interval,
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warmup_ratio=warmup_ratio,
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**kwargs)
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class LuminaDiMOOImagePipeline(LuminaDiMOOPipeline):
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def __call__(self, prompt: list[str], image, num_inference_steps: int = 64, temperature: float = 1.0, cfg_scale: float = 2.5, cfg_img: float = 4.0, **kwargs):
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edit_types = ['dense', 'canny_pred', 'control', 'subject', 'edit', 'ref_transfer', 'multi_view']
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if isinstance(prompt, list):
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prompt = prompt[0].strip()
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task = "image_to_image"
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edit_type = 'default'
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ref_image = None
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for et in edit_types:
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if prompt.startswith(et):
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edit_type = et
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break
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if isinstance(image, list):
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if len(image) > 1:
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ref_image = image[1]
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if len(image) > 0:
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image = image[0]
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log.debug(f'Base args: task={task} edit_type={edit_type} steps={num_inference_steps} cfg_scale={cfg_scale} cfg_img={cfg_img} temperature={temperature} image={image} ref_image={ref_image}')
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return super().__call__(
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prompt=prompt,
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task=task,
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image=image,
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ref_image=ref_image,
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edit_type=edit_type,
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num_inference_steps=num_inference_steps,
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temperature=temperature,
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cfg_scale=cfg_scale,
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cfg_img=cfg_img,
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**kwargs)
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