Files changed (1) hide show
  1. app.py +4 -4
app.py CHANGED
@@ -4,7 +4,7 @@ from PIL import Image
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  from diffusers import AutoPipelineForText2Image, DDIMScheduler
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  from transformers import CLIPVisionModelWithProjection
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  import numpy as np
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- import spaces
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  image_encoder = CLIPVisionModelWithProjection.from_pretrained(
@@ -25,7 +25,7 @@ pipeline.set_ip_adapter_scale([0.7, 0.5])
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  pipeline.enable_model_cpu_offload()
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- @spaces.ZeroGPU
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  def transform_image(face_image):
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  generator = torch.Generator(device="cpu").manual_seed(0)
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@@ -39,7 +39,7 @@ def transform_image(face_image):
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  raise ValueError("Unsupported image format")
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  # Load the style image from the local path
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- style_image_path = "/content/soyjak2.jpeg"
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  style_image = Image.open(style_image_path)
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  # Perform the transformation
@@ -63,4 +63,4 @@ demo = gr.Interface(
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  )
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  demo.queue(max_size=20) # Configures the queue with a maximum size of 20
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- demo.launch()
 
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  from diffusers import AutoPipelineForText2Image, DDIMScheduler
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  from transformers import CLIPVisionModelWithProjection
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  import numpy as np
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+ import spaces
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  image_encoder = CLIPVisionModelWithProjection.from_pretrained(
 
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  pipeline.enable_model_cpu_offload()
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+ @spaces.GPU
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  def transform_image(face_image):
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  generator = torch.Generator(device="cpu").manual_seed(0)
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  raise ValueError("Unsupported image format")
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  # Load the style image from the local path
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+ style_image_path = "examples/soyjak2.jpg"
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  style_image = Image.open(style_image_path)
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  # Perform the transformation
 
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  )
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  demo.queue(max_size=20) # Configures the queue with a maximum size of 20
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+ demo.launch()