Merge pull request #485 from superannotateai/1247_get_annotations_per_frame

1247 get annotations per frame

Author: VaghinakDev

src/superannotate/lib/app/analytics/aggregators.py

@@ -172,6 +172,20 @@ def aggregate_annotations_as_df(self):
         elif self.project_type == constances.ProjectType.DOCUMENT.name:
             return self.aggregate_document_annotations_as_df(annotation_paths)
 
+    def __add_attributes_to_raws(self, raws, attributes, element_raw):
+        for attribute_id, attribute in enumerate(attributes):
+            attribute_raw = copy.copy(element_raw)
+            attribute_raw.attributeId = attribute_id
+            attribute_raw.attributeGroupName = attribute.get(
+                "groupName"
+            )
+            attribute_raw.attributeName = attribute.get("name")
+            raws.append(attribute_raw)
+        if not attributes:
+            raws.append(element_raw)
+
+        return raws
+
     def aggregate_video_annotations_as_df(self, annotation_paths: List[str]):
         raws = []
         for annotation_path in annotation_paths:
@@ -226,6 +240,9 @@ def aggregate_video_annotations_as_df(self, annotation_paths: List[str]):
                 )
                 instance_raw.pointLabels = instance["meta"].get("pointLabels")
                 parameters = instance.get("parameters", [])
+                if instance_raw.type == 'tag':
+                    attributes = instance["meta"].get("attributes",[])
+                    raws = self.__add_attributes_to_raws(raws, attributes, instance_raw)
                 for parameter_id, parameter in enumerate(parameters):
                     parameter_raw = copy.copy(instance_raw)
                     parameter_raw.parameterId = parameter_id
@@ -237,16 +254,7 @@ def aggregate_video_annotations_as_df(self, annotation_paths: List[str]):
                         timestamp_raw.timestampId = timestamp_id
                         timestamp_raw.meta = self.MAPPERS[instance_type](timestamp)
                         attributes = timestamp.get("attributes", [])
-                        for attribute_id, attribute in enumerate(attributes):
-                            attribute_raw = copy.copy(timestamp_raw)
-                            attribute_raw.attributeId = attribute_id
-                            attribute_raw.attributeGroupName = attribute.get(
-                                "groupName"
-                            )
-                            attribute_raw.attributeName = attribute.get("name")
-                            raws.append(attribute_raw)
-                        if not attributes:
-                            raws.append(timestamp_raw)
+                        raws = self.__add_attributes_to_raws(raws, attributes, timestamp_raw)
                     if not timestamps:
                         raws.append(parameter_raw)
                 if not parameters:

src/superannotate/lib/core/video_convertor.py

@@ -99,6 +99,7 @@ def pairwise(data: list):
         next(b, None)
         return zip(a, b)
 
+
     def get_median(self, annotations: List[dict]) -> dict:
         if len(annotations) >= 1:
             return annotations[0]
@@ -180,14 +181,15 @@ def _process(self):
             annotation_type = instance["meta"]["type"]
             class_name = instance["meta"].get("className")
             class_id = instance["meta"].get("classId", -1)
-            for parameter in instance["parameters"]:
+            for parameter in instance.get("parameters", []):
                 frames_mapping = defaultdict(list)
                 interpolated_frames = {}
                 for timestamp in parameter["timestamps"]:
                     frames_mapping[
                         int(math.ceil(timestamp["timestamp"] / self.ratio))
                     ].append(timestamp)
                 frames_mapping = self.merge_first_frame(frames_mapping)
+
                 for from_frame_no, to_frame_no in self.pairwise(sorted(frames_mapping)):
                     last_frame_no = to_frame_no
                     from_frame, to_frame = (
@@ -227,7 +229,9 @@ def _process(self):
                             keyframe=True,
                         )
                 if frames_mapping and not interpolated_frames:
-                    median = self.get_median(frames_mapping[1])
+                    key = set(frames_mapping.keys()).pop()
+                    median = self.get_median(frames_mapping[key])
+
                     interpolated_frames[1] = Annotation(
                         instanceId=instance_id,
                         type=annotation_type,