rename test
Browse files- 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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-
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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="
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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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@@ -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
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pipe = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(
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-
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controlnet=controlnet_canny,
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)
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-
self.pipes[
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else:
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-
for
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pipe = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(
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-
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safety_checker=None,
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controlnet=controlnet_canny,
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)
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-
self.pipes[
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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.
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-
pipe = self.pipes[params.
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-
activation_token = base_models[params.
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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(
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