Update README.md
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README.md
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@@ -51,6 +51,7 @@ 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 feature_extractor for postprocessing
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predicted_semantic_map = feature_extractor.post_process_semantic_segmentation(outputs, target_sizes=[image.size[::-1]])[0]
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```
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masks_queries_logits = outputs.masks_queries_logits
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# you can pass them to feature_extractor for postprocessing
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# we refer to the demo notebooks for visualization (see "Resources" section in the MaskFormer docs)
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predicted_semantic_map = feature_extractor.post_process_semantic_segmentation(outputs, target_sizes=[image.size[::-1]])[0]
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```
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