[Dataset manager] Fix import for MOTS format (#3612)

* Add group for shapes with same track_id

* Replace shift variable

* Use negative ids

* Add unit test

* Rename extra args

* Allow dots in image name for 3D formats

* Update changelog

* Revert changes in bindings

* Fix imports

CHANGELOG.md

@@ -37,6 +37,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 - Fixed multiple tasks moving (<https://github.com/openvinotoolkit/cvat/pull/3517>)
 - Fixed task creating CLI parameter (<https://github.com/openvinotoolkit/cvat/pull/3519>)
+- Fixed import for MOTS format (<https://github.com/openvinotoolkit/cvat/pull/3612>)
 
 ### Security
 

cvat/apps/dataset_manager/formats/mots.py

@@ -46,15 +46,27 @@ def _import(src_file, task_data):
 
         root_hint = find_dataset_root(dataset, task_data)
 
+        shift = 0
         for item in dataset:
             frame_number = task_data.abs_frame_id(
                 match_dm_item(item, task_data, root_hint=root_hint))
 
+            track_ids = set()
+
             for ann in item.annotations:
                 if ann.type != AnnotationType.polygon:
                     continue
 
                 track_id = ann.attributes['track_id']
+                group_id = track_id
+
+                if track_id in track_ids:
+                    # use negative id for tracks with the same id on the same frame
+                    shift -= 1
+                    track_id = shift
+                else:
+                    track_ids.add(track_id)
+
                 shape = task_data.TrackedShape(
                     type='polygon',
                     points=ann.points,
@@ -65,6 +77,7 @@ def _import(src_file, task_data):
                     frame=frame_number,
                     attributes=[],
                     source='manual',
+                    group=group_id
                 )
 
                 # build trajectories as lists of shapes in track dict

cvat/apps/dataset_manager/tests/test_formats.py

@@ -3,22 +3,27 @@
 #
 # SPDX-License-Identifier: MIT
 
-
-from io import BytesIO
+import numpy as np
 import os.path as osp
 import tempfile
 import zipfile
+from io import BytesIO
 
 import datumaro
+from datumaro.components.dataset import Dataset, DatasetItem
+from datumaro.components.extractor import Mask
+from django.contrib.auth.models import Group, User
 from PIL import Image
-from django.contrib.auth.models import User, Group
-from rest_framework.test import APITestCase, APIClient
+
 from rest_framework import status
+from rest_framework.test import APIClient, APITestCase
 
 import cvat.apps.dataset_manager as dm
 from cvat.apps.dataset_manager.annotation import AnnotationIR
-from cvat.apps.dataset_manager.bindings import TaskData, find_dataset_root, CvatTaskDataExtractor
+from cvat.apps.dataset_manager.bindings import (CvatTaskDataExtractor,
+                                                TaskData, find_dataset_root)
 from cvat.apps.dataset_manager.task import TaskAnnotation
+from cvat.apps.dataset_manager.util import make_zip_archive
 from cvat.apps.engine.models import Task
 
 
@@ -501,7 +506,6 @@ class TaskExportTest(_DbTestBase):
             self.assertTrue(frame.frame in range(6, 10))
         self.assertEqual(i + 1, 4)
 
-
 class FrameMatchingTest(_DbTestBase):
     def _generate_task_images(self, paths): # pylint: disable=no-self-use
         f = BytesIO()
@@ -598,9 +602,10 @@ class TaskAnnotationsImportTest(_DbTestBase):
         self._put_api_v1_task_id_annotations(task["id"], annotations)
         return annotations
 
-    def _generate_task_images(self, count, name="image"):
+    def _generate_task_images(self, count, name="image", **image_params):
         images = {
-            "client_files[%d]" % i: generate_image_file("image_%d.jpg" % i)
+            "client_files[%d]" % i: generate_image_file("%s_%d.jpg" % (name, i),
+                **image_params)
             for i in range(count)
         }
         images["image_quality"] = 75
@@ -916,3 +921,36 @@ class TaskAnnotationsImportTest(_DbTestBase):
                     self.skipTest("Format is disabled")
 
                 self._test_can_import_annotations(task, format_name)
+
+    def test_can_import_mots_annotations_with_splited_masks(self):
+        #https://github.com/openvinotoolkit/cvat/issues/3360
+
+        format_name = 'MOTS PNG 1.0'
+        source_dataset = Dataset.from_iterable([
+            DatasetItem(id='image_0',
+                annotations=[
+                    Mask(np.array([[1, 1, 1, 0, 1, 1, 1]] * 5),
+                    label=0, attributes={'track_id': 0})
+                ]
+            )
+        ], categories=['label_0'])
+
+        with tempfile.TemporaryDirectory() as temp_dir:
+            dataset_dir = osp.join(temp_dir, 'dataset')
+            source_dataset.export(dataset_dir, 'mots_png')
+            dataset_path = osp.join(temp_dir, 'annotations.zip')
+            make_zip_archive(dataset_dir, dataset_path)
+
+            images = self._generate_task_images(1, size=(5, 7))
+            task = {
+                'name': 'test',
+                "overlap": 0,
+                "segment_size": 100,
+                "labels": [{'name': 'label_0'}]
+            }
+            task.update()
+            task = self._create_task(task, images)
+
+            dm.task.import_task_annotations(task['id'], dataset_path, format_name)
+            self._test_can_import_annotations(task, format_name)
+