CiaraRowles commited on
Commit
73ef227
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1 Parent(s): a7fa9a2

Update controlnet/callable_functions.py

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Files changed (1) hide show
  1. controlnet/callable_functions.py +6 -6
controlnet/callable_functions.py CHANGED
@@ -10,7 +10,7 @@ from transformers import AutoProcessor, SiglipVisionModel
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- def process_single_image(image_path, image=None):
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  # Set up model components
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  unet = UNet2DConditionModel.from_pretrained("runwayml/stable-diffusion-v1-5", subfolder="unet", torch_dtype=torch.float16, device="cuda")
@@ -19,7 +19,7 @@ def process_single_image(image_path, image=None):
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  stylecodes_model= stylecodes_model.to("cuda")
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- stylecodes_model.load_model("models/stylecodes_sd15_v1.bin")
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  # Load and preprocess image
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  if image is None:
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  image = Image.open(image_path).convert("RGB")
@@ -40,7 +40,7 @@ def process_single_image(image_path, image=None):
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  return code
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- def process_single_image_both_ways(image_path, prompt, num_inference_steps,image=None):
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  # Load and preprocess image
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  # Set up model components
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  unet = UNet2DConditionModel.from_pretrained("runwayml/stable-diffusion-v1-5", subfolder="unet", torch_dtype=torch.float16, device="cuda")
@@ -56,7 +56,7 @@ def process_single_image_both_ways(image_path, prompt, num_inference_steps,image
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  steps_offset=1,
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  )
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- stylecodes_model.load_model("models/stylecodes_sd15_v1.bin")
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  pipe = StableDiffusionPipelineXSv2.from_pretrained(
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  "runwayml/stable-diffusion-v1-5",
@@ -95,7 +95,7 @@ def process_single_image_both_ways(image_path, prompt, num_inference_steps,image
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  # Save the output image
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- def make_stylecode(image_path, image=None):
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  # Set up model components
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  unet = UNet2DConditionModel.from_pretrained("runwayml/stable-diffusion-v1-5", subfolder="unet", torch_dtype=torch.float16, device="cuda")
@@ -104,7 +104,7 @@ def make_stylecode(image_path, image=None):
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  stylecodes_model= stylecodes_model.to("cuda")
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- stylecodes_model.load_model("models/stylecodes_sd15_v1.bin")
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  # Load and preprocess image
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  if image is None:
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  image = Image.open(image_path).convert("RGB")
 
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+ def process_single_image(model,image_path, image=None):
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  # Set up model components
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  unet = UNet2DConditionModel.from_pretrained("runwayml/stable-diffusion-v1-5", subfolder="unet", torch_dtype=torch.float16, device="cuda")
 
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  stylecodes_model= stylecodes_model.to("cuda")
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+ stylecodes_model.load_model(model)
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  # Load and preprocess image
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  if image is None:
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  image = Image.open(image_path).convert("RGB")
 
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  return code
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+ def process_single_image_both_ways(model,image_path, prompt, num_inference_steps,image=None):
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  # Load and preprocess image
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  # Set up model components
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  unet = UNet2DConditionModel.from_pretrained("runwayml/stable-diffusion-v1-5", subfolder="unet", torch_dtype=torch.float16, device="cuda")
 
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  steps_offset=1,
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  )
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+ stylecodes_model.load_model(model)
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  pipe = StableDiffusionPipelineXSv2.from_pretrained(
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  "runwayml/stable-diffusion-v1-5",
 
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  # Save the output image
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+ def make_stylecode(model,image_path, image=None):
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  # Set up model components
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  unet = UNet2DConditionModel.from_pretrained("runwayml/stable-diffusion-v1-5", subfolder="unet", torch_dtype=torch.float16, device="cuda")
 
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  stylecodes_model= stylecodes_model.to("cuda")
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+ stylecodes_model.load_model(model)
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  # Load and preprocess image
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  if image is None:
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  image = Image.open(image_path).convert("RGB")