Update ndx-pose for Lightning pose

pyproject.toml

@@ -128,7 +128,7 @@ video = [
     "opencv-python-headless>=4.8.1.78",
 ]
 lightningpose = [
-    "ndx-pose>=0.1.1",
+    "ndx-pose>=0.2",
     "neuroconv[video]",
 ]
 medpc = [

src/neuroconv/datainterfaces/behavior/lightningpose/lightningposedatainterface.py

@@ -40,9 +40,10 @@ def get_metadata_schema(self) -> dict:
                         description=dict(type="string"),
                         scorer=dict(type="string"),
                         source_software=dict(type="string", default="LightningPose"),
+                        camera_name=dict(type="string", default="CameraPoseEstimation"),
                     ),
                     patternProperties={
-                        "^(?!(name|description|scorer|source_software)$)[a-zA-Z0-9_]+$": dict(
+                        "^(?!(name|description|scorer|source_software|camera_name)$)[a-zA-Z0-9_]+$": dict(
                             title="PoseEstimationSeries",
                             type="object",
                             properties=dict(name=dict(type="string"), description=dict(type="string")),
@@ -80,22 +81,15 @@ def __init__(
         verbose : bool, default: True
             controls verbosity. ``True`` by default.
         """
-        from importlib.metadata import version
 
         # This import is to assure that the ndx_pose is in the global namespace when an pynwb.io object is created
         # For more detail, see https://github.com/rly/ndx-pose/issues/36
         import ndx_pose  # noqa: F401
-        from packaging import version as version_parse
 
         from neuroconv.datainterfaces.behavior.video.video_utils import (
             VideoCaptureContext,
         )
 
-        ndx_pose_version = version("ndx-pose")
-
-        if version_parse.parse(ndx_pose_version) >= version_parse.parse("0.2.0"):
-            raise ImportError("The ndx-pose version must be less than 0.2.0.")
-
         self._vc = VideoCaptureContext
 
         self.file_path = Path(file_path)
@@ -170,6 +164,7 @@ def get_metadata(self) -> DeepDict:
             description="Contains the pose estimation series for each keypoint.",
             scorer=self.scorer_name,
             source_software="LightningPose",
+            camera_name="CameraPoseEstimation",
         )
         for keypoint_name in self.keypoint_names:
             keypoint_name_without_spaces = keypoint_name.replace(" ", "")
@@ -206,7 +201,7 @@ def add_to_nwbfile(
             The description of how the confidence was computed, e.g., 'Softmax output of the deep neural network'.
         stub_test : bool, default: False
         """
-        from ndx_pose import PoseEstimation, PoseEstimationSeries
+        from ndx_pose import PoseEstimation, PoseEstimationSeries, Skeleton, Skeletons
 
         metadata_copy = deepcopy(metadata)
 
@@ -223,15 +218,14 @@ def add_to_nwbfile(
             original_video_name = str(self.original_video_file_path)
         else:
             original_video_name = metadata_copy["Behavior"]["Videos"][0]["name"]
-
-        pose_estimation_kwargs = dict(
-            name=pose_estimation_metadata["name"],
-            description=pose_estimation_metadata["description"],
-            source_software=pose_estimation_metadata["source_software"],
-            scorer=pose_estimation_metadata["scorer"],
-            original_videos=[original_video_name],
-            dimensions=[self.dimension],
-        )
+        camera_name = pose_estimation_metadata["camera_name"]
+        if camera_name in nwbfile.devices:
+            camera = nwbfile.devices[camera_name]
+        else:
+            camera = nwbfile.create_device(
+                name=camera_name,
+                description="Camera used for behavioral recording and pose estimation.",
+            )
 
         pose_estimation_data = self.pose_estimation_data if not stub_test else self.pose_estimation_data.head(n=10)
         timestamps = self.get_timestamps(stub_test=stub_test)
@@ -263,8 +257,28 @@ def add_to_nwbfile(
 
             pose_estimation_series.append(PoseEstimationSeries(**pose_estimation_series_kwargs))
 
-        pose_estimation_kwargs.update(
+        # Add Skeleton(s)
+        nodes = [keypoint_name.replace(" ", "") for keypoint_name in self.keypoint_names]
+        subject = nwbfile.subject if nwbfile.subject is not None else None
+        name = f"Skeleton{pose_estimation_name}"
+        skeleton = Skeleton(name=name, nodes=nodes, subject=subject)
+        if "Skeletons" in behavior.data_interfaces:
+            skeletons = behavior.data_interfaces["Skeletons"]
+            skeletons.add_skeletons(skeleton)
+        else:
+            skeletons = Skeletons(skeletons=[skeleton])
+            behavior.add(skeletons)
+
+        pose_estimation_kwargs = dict(
+            name=pose_estimation_metadata["name"],
+            description=pose_estimation_metadata["description"],
+            source_software=pose_estimation_metadata["source_software"],
+            scorer=pose_estimation_metadata["scorer"],
+            original_videos=[original_video_name],
+            dimensions=[self.dimension],
             pose_estimation_series=pose_estimation_series,
+            devices=[camera],
+            skeleton=skeleton,
         )
 
         if self.source_data["labeled_video_file_path"]:

tests/test_on_data/behavior/test_behavior_interfaces.py

@@ -42,14 +42,9 @@
 
 from importlib.metadata import version
 
-from packaging import version as version_parse
-
 ndx_pose_version = version("ndx-pose")
 
 
-@pytest.mark.skipif(
-    version_parse.parse(ndx_pose_version) >= version_parse.parse("0.2"), reason="ndx_pose version is smaller than 0.2"
-)
 class TestLightningPoseDataInterface(DataInterfaceTestMixin, TemporalAlignmentMixin):
     data_interface_cls = LightningPoseDataInterface
     interface_kwargs = dict(
@@ -94,6 +89,7 @@ def setup_metadata(self, request):
                 description="Contains the pose estimation series for each keypoint.",
                 scorer="heatmap_tracker",
                 source_software="LightningPose",
+                camera_name="CameraPoseEstimation",
             )
         )
         cls.expected_metadata[cls.pose_estimation_name].update(
@@ -165,9 +161,6 @@ def check_read_nwb(self, nwbfile_path: str):
                 assert_array_equal(pose_estimation_series.data[:], test_data[["x", "y"]].values)
 
 
-@pytest.mark.skipif(
-    version_parse.parse(ndx_pose_version) >= version_parse.parse("0.2"), reason="ndx_pose version is smaller than 0.2"
-)
 class TestLightningPoseDataInterfaceWithStubTest(DataInterfaceTestMixin, TemporalAlignmentMixin):
     data_interface_cls = LightningPoseDataInterface
     interface_kwargs = dict(

tests/test_on_data/behavior/test_lightningpose_converter.py

@@ -1,14 +1,10 @@
 import shutil
 import tempfile
 from datetime import datetime
-from importlib.metadata import version
 from pathlib import Path
 from warnings import warn
 
-import pytest
 from hdmf.testing import TestCase
-from packaging import version
-from packaging import version as version_parse
 from pynwb import NWBHDF5IO
 from pynwb.image import ImageSeries
 
@@ -19,12 +15,7 @@
 
 from ..setup_paths import BEHAVIOR_DATA_PATH
 
-ndx_pose_version = version("ndx-pose")
 
-
-@pytest.mark.skipif(
-    version_parse.parse(ndx_pose_version) >= version_parse.parse("0.2"), reason="ndx_pose version is smaller than 0.2"
-)
 class TestLightningPoseConverter(TestCase):
     @classmethod
     def setUpClass(cls) -> None:
@@ -73,6 +64,7 @@ def setUpClass(cls) -> None:
             description="Contains the pose estimation series for each keypoint.",
             scorer="heatmap_tracker",
             source_software="LightningPose",
+            camera_name="CameraPoseEstimation",
         )
 
         cls.pose_estimation_metadata.update(