Update README.md

README.md

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

preprocessor_config.json

@@ -9,7 +9,7 @@
     0.4560000002384186,
     0.4059999883174896
   ],
-  "image_processor_type": "MaskFormerImageProcessor",
+  "image_processor_type": "Mask2FormerImageProcessor",
   "image_std": [
     0.2290000021457672,
     0.2239999920129776,