Fix export of masks with holes (cvat-ai#188)

* Fix export of masks with holes in polygons (background class should not introduce a new instance)

* update changelog

CHANGELOG.md

@@ -20,6 +20,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 -
 
 ### Fixed
+- Instance masks of `background` class no more introduce an instance (<https://github.com/openvinotoolkit/datumaro/pull/188>)
 - Added support for label attributes in Datumaro format (<https://github.com/openvinotoolkit/datumaro/pull/192>)
 
 ### Security

datumaro/components/extractor.py

@@ -264,11 +264,15 @@ def from_instance_masks(instance_masks,
         class_map = [0]
 
         m, idx, instance_id, class_id = next(it)
+        if not class_id:
+            idx = 0
         index_mask = make_index_mask(m, idx)
         instance_map.append(instance_id)
         class_map.append(class_id)
 
         for m, idx, instance_id, class_id in it:
+            if not class_id:
+                idx = 0
             index_mask = np.where(m, idx, index_mask)
             instance_map.append(instance_id)
             class_map.append(class_id)

tests/test_voc_format.py

@@ -21,6 +21,7 @@
 from datumaro.plugins.voc_format.importer import VocImporter
 from datumaro.components.dataset import Dataset
 from datumaro.util.image import Image
+from datumaro.util.mask_tools import load_mask
 from datumaro.util.test_utils import (TestDir, compare_datasets,
     test_save_and_load)
 
@@ -628,6 +629,25 @@ def categories(self):
                 partial(VocConverter.convert, label_map=label_map),
                 test_dir, target_dataset=DstExtractor())
 
+    def test_background_masks_dont_introduce_instances_but_cover_others(self):
+        dataset = Dataset.from_iterable([
+            DatasetItem(1, image=np.zeros((4, 1, 1)), annotations=[
+                Mask([1, 1, 1, 1], label=1, attributes={'z_order': 1}),
+                Mask([0, 0, 1, 1], label=2, attributes={'z_order': 2}),
+                Mask([0, 0, 1, 1], label=0, attributes={'z_order': 3}),
+            ])
+        ], categories=['background', 'a', 'b'])
+
+        with TestDir() as test_dir:
+            VocConverter.convert(dataset, test_dir, apply_colormap=False)
+
+            cls_mask = load_mask(
+                osp.join(test_dir, 'SegmentationClass', '1.png'))
+            inst_mask = load_mask(
+                osp.join(test_dir, 'SegmentationObject', '1.png'))
+            self.assertTrue(np.array_equal([0, 1], np.unique(cls_mask)))
+            self.assertTrue(np.array_equal([0, 1], np.unique(inst_mask)))
+
     def test_can_save_dataset_with_image_info(self):
         class TestExtractor(TestExtractorBase):
             def __iter__(self):