Merge branch 'develop' into vsaltykovx/add_mmdetection_input_paramete…

…rs_validation

ote_sdk/ote_sdk/entities/label.py

@@ -76,9 +76,11 @@ class LabelEntity:
     :param is_empty: set to True if the label is an empty label.
     :param id: the ID of the label. Set to ID() so that a new unique ID
         will be assigned upon saving. If the argument is None, it will be set to ID()
+    :param is_anomalous: boolean that indicates whether the label is the Anomalous label. Always set to False for non-
+        anomaly projects.
     """
 
-    # pylint: disable=redefined-builtin, too-many-arguments; Requires refactor
+    # pylint: disable=redefined-builtin, too-many-instance-attributes, too-many-arguments; Requires refactor
     def __init__(
         self,
         name: str,
@@ -88,6 +90,7 @@ def __init__(
         creation_date: Optional[datetime.datetime] = None,
         is_empty: bool = False,
         id: Optional[ID] = None,
+        is_anomalous: bool = False,
     ):
         id = ID() if id is None else id
         color = Color.random() if color is None else color
@@ -100,6 +103,7 @@ def __init__(
         self._is_empty = is_empty
         self._creation_date = creation_date
         self._id = id
+        self.is_anomalous = is_anomalous
 
     @property
     def name(self):
@@ -184,6 +188,7 @@ def __eq__(self, other):
                 and self.color == other.color
                 and self.hotkey == other.hotkey
                 and self.domain == other.domain
+                and self.is_anomalous == other.is_anomalous
             )
         return False
 

ote_sdk/ote_sdk/utils/segmentation_utils.py

@@ -21,7 +21,6 @@
 from ote_sdk.entities.scored_label import ScoredLabel
 from ote_sdk.entities.shapes.polygon import Point, Polygon
 from ote_sdk.utils.shape_factory import ShapeFactory
-from ote_sdk.utils.time_utils import timeit
 
 
 def mask_from_dataset_item(
@@ -178,7 +177,6 @@ def find_loops(points: ContourInternal) -> List[Sequence[int]]:
     return subcontours
 
 
-@timeit
 def create_annotation_from_segmentation_map(
     hard_prediction: np.ndarray, soft_prediction: np.ndarray, label_map: dict
 ) -> List[Annotation]:

ote_sdk/requirements.txt

@@ -1,6 +1,6 @@
 numpy>=1.16.4
 scikit-learn==0.24.*
-Shapely==1.8.*
+Shapely>=1.7.1
 networkx~=2.5
 opencv-python==4.5.3.*
 pymongo>=3.9