GonzaloMG commited on
Commit
dbb5354
1 Parent(s): e2bd985

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +2 -3
app.py CHANGED
@@ -36,7 +36,7 @@ unet = UNet2DConditionModel.from_pretrained(checkpoint_path, subfolder="
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  vae = AutoencoderKL.from_pretrained(checkpoint_path, subfolder="vae")
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  text_encoder = CLIPTextModel.from_pretrained(checkpoint_path, subfolder="text_encoder")
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  tokenizer = CLIPTokenizer.from_pretrained(checkpoint_path, subfolder="tokenizer")
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- scheduler = DDIMScheduler.from_pretrained(checkpoint_path, timestep_spacing=timestep_spacing, subfolder="scheduler")
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  pipe = MarigoldPipeline.from_pretrained(pretrained_model_name_or_path = checkpoint_path,
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  unet=unet,
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  vae=vae,
@@ -123,8 +123,7 @@ with gr.Blocks(css=css) as demo:
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  # Save the colored depth map
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  tmp_colored_depth = tempfile.NamedTemporaryFile(suffix='.png', delete=False)
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  depth_colored.save(tmp_colored_depth.name)
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-
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- print("Dummy predictions complete, returning results.")
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  return [(image, depth_colored), tmp_gray_depth.name, tmp_colored_depth.name]
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  # h, w = image.shape[:2]
 
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  vae = AutoencoderKL.from_pretrained(checkpoint_path, subfolder="vae")
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  text_encoder = CLIPTextModel.from_pretrained(checkpoint_path, subfolder="text_encoder")
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  tokenizer = CLIPTokenizer.from_pretrained(checkpoint_path, subfolder="tokenizer")
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+ scheduler = DDIMScheduler.from_pretrained(checkpoint_path, timestep_spacing="trailing", subfolder="scheduler")
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  pipe = MarigoldPipeline.from_pretrained(pretrained_model_name_or_path = checkpoint_path,
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  unet=unet,
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  vae=vae,
 
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  # Save the colored depth map
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  tmp_colored_depth = tempfile.NamedTemporaryFile(suffix='.png', delete=False)
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  depth_colored.save(tmp_colored_depth.name)
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+
 
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  return [(image, depth_colored), tmp_gray_depth.name, tmp_colored_depth.name]
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  # h, w = image.shape[:2]