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@@ -60,9 +60,8 @@ class_queries_logits = outputs.class_queries_logits
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  masks_queries_logits = outputs.masks_queries_logits
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  # you can pass them to processor for postprocessing
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- result = processor.post_process_semantic_segmentation(outputs, target_sizes=[image.size[::-1]])[0]
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  # we refer to the demo notebooks for visualization (see "Resources" section in the Mask2Former docs)
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- predicted_semantic_map = result["segmentation"]
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  ```
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  For more code examples, we refer to the [documentation](https://huggingface.co/docs/transformers/master/en/model_doc/mask2former).
 
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  masks_queries_logits = outputs.masks_queries_logits
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  # you can pass them to processor for postprocessing
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+ predicted_semantic_map = processor.post_process_semantic_segmentation(outputs, target_sizes=[image.size[::-1]])[0]
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  # we refer to the demo notebooks for visualization (see "Resources" section in the Mask2Former docs)
 
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  ```
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  For more code examples, we refer to the [documentation](https://huggingface.co/docs/transformers/master/en/model_doc/mask2former).