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Update README.md

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@@ -46,20 +46,16 @@ inputs = processor(
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  return_tensors="pt",
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  )
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- # Remove Patch Offsets from inputs — only used later for post-processing.
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- patch_offsets = inputs.pop("patch_offsets")
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-
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  with torch.inference_mode():
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  outputs = model(**inputs)
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  # Prepare the original image size in the format (height, width)
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- original_image_sizes = [(image.height, image.width)]
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  # Post-process the model outputs to get final segmentation prediction
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  preds = processor.post_process_semantic_segmentation(
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  outputs,
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- patch_offsets=patch_offsets,
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- original_image_sizes=original_image_sizes,
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  )
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  # Visualize the segmentation mask
 
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  return_tensors="pt",
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  )
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  with torch.inference_mode():
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  outputs = model(**inputs)
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  # Prepare the original image size in the format (height, width)
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+ target_sizes = [(image.height, image.width)]
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  # Post-process the model outputs to get final segmentation prediction
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  preds = processor.post_process_semantic_segmentation(
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  outputs,
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+ target_sizes=target_sizes,
 
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  )
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  # Visualize the segmentation mask