[Datumaro] Fix mask to polygons warning (#1581)

* Fix message, add test
* update changelog

CHANGELOG.md

@@ -47,6 +47,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Fixed full COCO dataset import error with conflicting labels in keypoints and detection (https://github.com/opencv/cvat/pull/1548)
 - Fixed COCO keypoints skeleton parsing and saving (https://github.com/opencv/cvat/issues/1539)
 - `tf.placeholder() is not compatible with eager execution` exception for auto_segmentation (https://github.com/opencv/cvat/pull/1562)
+- Fixed a problem with mask to polygons conversion when polygons are too small (https://github.com/opencv/cvat/pull/1581)
 
 ### Security
 -

datumaro/datumaro/plugins/transforms.py

@@ -216,7 +216,7 @@ class MasksToPolygons(Transform, CliPlugin):
                     log.debug("[%s]: item %s: "
                         "Mask conversion to polygons resulted in too "
                         "small polygons, which were discarded" % \
-                        (self.NAME, item.id))
+                        (self._get_name(__class__), item.id))
                 annotations.extend(polygons)
             else:
                 annotations.append(ann)

datumaro/tests/test_transforms.py

@@ -1,3 +1,4 @@
+import logging as log
 import numpy as np
 
 from unittest import TestCase
@@ -65,6 +66,33 @@ class TransformsTest(TestCase):
         actual = transforms.MasksToPolygons(SrcExtractor())
         compare_datasets(self, DstExtractor(), actual)
 
+    def test_mask_to_polygons_small_polygons_message(self):
+        class SrcExtractor(Extractor):
+            def __iter__(self):
+                items = [
+                    DatasetItem(id=1, image=np.zeros((5, 10, 3)),
+                        annotations=[
+                            Mask(np.array([
+                                    [0, 0, 0],
+                                    [0, 1, 0],
+                                    [0, 0, 0],
+                                ]),
+                            ),
+                        ]
+                    ),
+                ]
+                return iter(items)
+
+        class DstExtractor(Extractor):
+            def __iter__(self):
+                return iter([ DatasetItem(id=1, image=np.zeros((5, 10, 3))), ])
+
+        with self.assertLogs(level=log.DEBUG) as logs:
+            actual = transforms.MasksToPolygons(SrcExtractor())
+
+            compare_datasets(self, DstExtractor(), actual)
+            self.assertRegex('\n'.join(logs.output), 'too small polygons')
+
     def test_polygons_to_masks(self):
         class SrcExtractor(Extractor):
             def __iter__(self):