Fix bug in segmentation postprocessing (#20198)

* Fix post_process_instance_segmentation
* Add test for label fusing

tests/models/maskformer/test_feature_extraction_maskformer.py

@@ -589,3 +589,30 @@ class MaskFormerFeatureExtractionTest(FeatureExtractionSavingTestMixin, unittest
             self.assertEqual(
                 el["segmentation"].shape, (self.feature_extract_tester.height, self.feature_extract_tester.width)
             )
+
+    def test_post_process_label_fusing(self):
+        feature_extractor = self.feature_extraction_class(num_labels=self.feature_extract_tester.num_classes)
+        outputs = self.feature_extract_tester.get_fake_maskformer_outputs()
+
+        segmentation = feature_extractor.post_process_panoptic_segmentation(
+            outputs, threshold=0, mask_threshold=0, overlap_mask_area_threshold=0
+        )
+        unfused_segments = [el["segments_info"] for el in segmentation]
+
+        fused_segmentation = feature_extractor.post_process_panoptic_segmentation(
+            outputs, threshold=0, mask_threshold=0, overlap_mask_area_threshold=0, label_ids_to_fuse={1}
+        )
+        fused_segments = [el["segments_info"] for el in fused_segmentation]
+
+        for el_unfused, el_fused in zip(unfused_segments, fused_segments):
+            if len(el_unfused) == 0:
+                self.assertEqual(len(el_unfused), len(el_fused))
+                continue
+
+            # Get number of segments to be fused
+            fuse_targets = [1 for el in el_unfused if el["label_id"] in {1}]
+            num_to_fuse = 0 if len(fuse_targets) == 0 else sum(fuse_targets) - 1
+            # Expected number of segments after fusing
+            expected_num_segments = max([el["id"] for el in el_unfused]) - num_to_fuse
+            num_segments_fused = max([el["id"] for el in el_fused])
+            self.assertEqual(num_segments_fused, expected_num_segments)