radames commited on
Commit
43a9fe4
1 Parent(s): 7d67dc6

rename test

Browse files
Files changed (1) hide show
  1. pipelines/controlnetLoraSD15.py +11 -11
pipelines/controlnetLoraSD15.py CHANGED
@@ -45,12 +45,12 @@ class Pipeline:
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  field="textarea",
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  id="prompt",
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  )
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- model_id: str = Field(
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  "plasmo/woolitize",
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  title="Base Model",
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  values=list(base_models.keys()),
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  field="select",
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- id="model_id",
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  )
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  seed: int = Field(
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  2159232, min=0, title="Seed", field="seed", hide=True, id="seed"
@@ -150,20 +150,20 @@ class Pipeline:
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  self.pipes = {}
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  if args.safety_checker:
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- for model_id in base_models.keys():
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  pipe = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(
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- model_id,
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  controlnet=controlnet_canny,
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  )
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- self.pipes[model_id] = pipe
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  else:
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- for model_id in base_models.keys():
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  pipe = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(
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- model_id,
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  safety_checker=None,
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  controlnet=controlnet_canny,
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  )
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- self.pipes[model_id] = pipe
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  self.canny_torch = SobelOperator(device=device)
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@@ -199,10 +199,10 @@ class Pipeline:
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  def predict(self, params: "Pipeline.InputParams") -> Image.Image:
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  generator = torch.manual_seed(params.seed)
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- print(f"Using model: {params.model_id}")
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- pipe = self.pipes[params.model_id]
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- activation_token = base_models[params.model_id]
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  prompt = f"{activation_token} {params.prompt}"
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  prompt_embeds = pipe.compel_proc(prompt)
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  control_image = self.canny_torch(
 
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  field="textarea",
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  id="prompt",
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  )
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+ base_model_id: str = Field(
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  "plasmo/woolitize",
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  title="Base Model",
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  values=list(base_models.keys()),
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  field="select",
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+ id="base_model_id",
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  )
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  seed: int = Field(
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  2159232, min=0, title="Seed", field="seed", hide=True, id="seed"
 
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  self.pipes = {}
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  if args.safety_checker:
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+ for base_model_id in base_models.keys():
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  pipe = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(
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+ base_model_id,
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  controlnet=controlnet_canny,
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  )
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+ self.pipes[base_model_id] = pipe
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  else:
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+ for base_model_id in base_models.keys():
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  pipe = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(
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+ base_model_id,
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  safety_checker=None,
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  controlnet=controlnet_canny,
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  )
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+ self.pipes[base_model_id] = pipe
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  self.canny_torch = SobelOperator(device=device)
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  def predict(self, params: "Pipeline.InputParams") -> Image.Image:
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  generator = torch.manual_seed(params.seed)
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+ print(f"Using model: {params.base_model_id}")
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+ pipe = self.pipes[params.base_model_id]
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+ activation_token = base_models[params.base_model_id]
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  prompt = f"{activation_token} {params.prompt}"
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  prompt_embeds = pipe.compel_proc(prompt)
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  control_image = self.canny_torch(