Fix track interpolation in tasks with deleted frames

changelog.d/20250205_193041_mzhiltso_fix_server_track_interpolation.md

@@ -0,0 +1,4 @@
+### Fixed
+
+- Fixed invalid server-side track interpolation in tasks with deleted frames
+  (<https://github.com/cvat-ai/cvat/pull/9059>)

cvat/apps/dataset_manager/annotation.py

@@ -202,19 +202,26 @@ def clear_frames(self, frames: Container[int]):
     def to_shapes(self,
         end_frame: int,
         *,
-        included_frames: Optional[Sequence[int]] = None,
+        deleted_frames: Sequence[int] | None = None,
+        included_frames: Sequence[int] | None = None,
         include_outside: bool = False,
-        use_server_track_ids: bool = False
+        use_server_track_ids: bool = False,
     ) -> list:
         shapes = self.data.shapes
         tracks = TrackManager(self.data.tracks, dimension=self.dimension)
 
         if included_frames is not None:
             shapes = [s for s in shapes if s["frame"] in included_frames]
 
-        return shapes + tracks.to_shapes(end_frame,
-            included_frames=included_frames, include_outside=include_outside,
-            use_server_track_ids=use_server_track_ids
+        if deleted_frames is not None:
+            shapes = [s for s in shapes if s["frame"] not in deleted_frames]
+
+        return shapes + tracks.to_shapes(
+            end_frame,
+            included_frames=included_frames,
+            deleted_frames=deleted_frames,
+            include_outside=include_outside,
+            use_server_track_ids=use_server_track_ids,
         )
 
     def to_tracks(self):
@@ -464,6 +471,7 @@ def _modify_unmatched_object(self, obj, end_frame):
 class TrackManager(ObjectManager):
     def to_shapes(self, end_frame: int, *,
         included_frames: Optional[Sequence[int]] = None,
+        deleted_frames: Optional[Sequence[int]] = None,
         include_outside: bool = False,
         use_server_track_ids: bool = False
     ) -> list:
@@ -479,6 +487,7 @@ def to_shapes(self, end_frame: int, *,
                 self.dimension,
                 include_outside=include_outside,
                 included_frames=included_frames,
+                deleted_frames=deleted_frames,
             ):
                 shape["label_id"] = track["label_id"]
                 shape["group"] = track["group"]
@@ -498,10 +507,12 @@ def to_shapes(self, end_frame: int, *,
                 element_included_frames = set(track_shapes.keys())
                 if included_frames is not None:
                     element_included_frames = element_included_frames.intersection(included_frames)
-                element_shapes = track_elements.to_shapes(end_frame,
+                element_shapes = track_elements.to_shapes(
+                    end_frame,
                     included_frames=element_included_frames,
+                    deleted_frames=deleted_frames,
                     include_outside=True, # elements are controlled by the parent shape
-                    use_server_track_ids=use_server_track_ids
+                    use_server_track_ids=use_server_track_ids,
                 )
 
                 for shape in element_shapes:
@@ -588,10 +599,23 @@ def _modify_unmatched_object(self, obj, end_frame):
 
     @staticmethod
     def get_interpolated_shapes(
-        track, start_frame, end_frame, dimension, *,
+        track: dict,
+        start_frame: int,
+        end_frame: int,
+        dimension: DimensionType | str,
+        *,
         included_frames: Optional[Sequence[int]] = None,
+        deleted_frames: Optional[Sequence[int]] = None,
         include_outside: bool = False,
     ):
+        # If a task or contains deleted frames that contain track keyframes,
+        # these keyframes should be excluded from the interpolation.
+        # In jobs having specific frames included (e.g. GT jobs),
+        # deleted frames should not be confused with included frames during track interpolation.
+        # Deleted frames affect existing shapes in tracks.
+        # Included frames filter the resulting annotations after interpolation
+        # to produce the requested track frames.
+
         def copy_shape(source, frame, points=None, rotation=None):
             copied = source.copy()
             copied["attributes"] = faster_deepcopy(source["attributes"])
@@ -930,7 +954,7 @@ def propagate(shape, end_frame, *, included_frames=None):
         prev_shape = None
         for shape in sorted(track["shapes"], key=lambda shape: shape["frame"]):
             curr_frame = shape["frame"]
-            if included_frames is not None and curr_frame not in included_frames:
+            if deleted_frames is not None and curr_frame in deleted_frames:
                 continue
             if prev_shape and end_frame <= curr_frame:
                 # If we exceed the end_frame and there was a previous shape,
@@ -982,6 +1006,8 @@ def propagate(shape, end_frame, *, included_frames=None):
         shapes = [
             shape for shape in shapes
 
+            if deleted_frames is None or shape["frame"] not in deleted_frames
+
             # After interpolation there can be a finishing frame
             # outside of the task boundaries. Filter it out to avoid errors.
             # https://github.com/openvinotoolkit/cvat/issues/2827

cvat/apps/dataset_manager/bindings.py

@@ -508,8 +508,9 @@ def get_frame(idx):
                 self.stop + 1,
                 # Skip outside, deleted and excluded frames
                 included_frames=included_frames,
+                deleted_frames=self.deleted_frames.keys(),
                 include_outside=False,
-                use_server_track_ids=self._use_server_track_ids
+                use_server_track_ids=self._use_server_track_ids,
             ),
             key=lambda shape: shape.get("z_order", 0)
         ):
@@ -1307,8 +1308,9 @@ def get_frame(task_id: int, idx: int) -> ProjectData.Frame:
                 anno_manager.to_shapes(
                     task.data.size,
                     included_frames=task_included_frames,
+                    deleted_frames=set(f for t_id, f in self.deleted_frames if t_id ==  task.id),
                     include_outside=False,
-                    use_server_track_ids=self._use_server_track_ids
+                    use_server_track_ids=self._use_server_track_ids,
                 ),
                 key=lambda shape: shape.get("z_order", 0)
             ):