diff --git a/client/models/pose_detection/routines.py b/client/models/pose_detection/routines.py
index fb167ac..b5678e5 100644
--- a/client/models/pose_detection/routines.py
+++ b/client/models/pose_detection/routines.py
@@ -1,68 +1,21 @@
 """Routines that can be integrated into a main control flow."""
 
 from importlib import resources
-from typing import Callable, Mapping
 
-import cv2
-import mediapipe as mp
-from mediapipe.framework import calculator_pb2
-from mediapipe.python._framework_bindings.packet import Packet
 from mediapipe.tasks.python.core.base_options import BaseOptions
 from mediapipe.tasks.python.vision import RunningMode
-from mediapipe.tasks.python.vision.core.vision_task_running_mode import (
-    VisionTaskRunningMode,
-)
 from mediapipe.tasks.python.vision.pose_landmarker import (
-    PoseLandmarker,
     PoseLandmarkerOptions,
 )
 
 from models.pose_detection.landmarking import AnnotatedImage, display_landmarking
+from models.pose_detection.trackers import DebugPostureTracker
 
 POSE_LANDMARKER_FILE = resources.files("models.resources").joinpath(
     "pose_landmarker_lite.task"
 )
 
 
-class DebugPostureTracker(PoseLandmarker):
-    """Handles routines for a Debugging Posture Tracker.
-
-    Attributes:
-        annotated_image: Mutable container for an image which may be mutated asynchronously.
-    """
-
-    def __init__(
-        self,
-        graph_config: calculator_pb2.CalculatorGraphConfig,
-        running_mode: VisionTaskRunningMode,
-        packet_callback: Callable[[Mapping[str, Packet]], None],
-    ) -> None:
-        super().__init__(graph_config, running_mode, packet_callback)
-        self.annotated_image = AnnotatedImage()
-        self._video_capture = cv2.VideoCapture(0)
-
-    def track_posture(self) -> None:
-        """Get frame from video capture device and process with pose model, then posture
-        algorithm. Print debugging info and display landmark annotated frame.
-        """
-        success, frame = self._video_capture.read()
-        if not success:
-            return
-
-        frame_timestamp_ms = self._video_capture.get(cv2.CAP_PROP_POS_MSEC)
-        mp_image = mp.Image(image_format=mp.ImageFormat.SRGB, data=frame)
-        self.detect_async(mp_image, int(frame_timestamp_ms))
-
-        cv2.imshow("input", frame)
-        if self.annotated_image.data is not None:
-            cv2.imshow("output", self.annotated_image.data)
-
-    def __exit__(self, unused_exc_type, unused_exc_value, unused_traceback) -> None:
-        self._video_capture.release()
-        cv2.destroyAllWindows()
-        super().__exit__(unused_exc_type, unused_exc_value, unused_traceback)
-
-
 def create_debug_posture_tracker() -> DebugPostureTracker:
     """Handles config of livestreamed input and model loading.
 
diff --git a/client/models/pose_detection/trackers.py b/client/models/pose_detection/trackers.py
new file mode 100644
index 0000000..4f4974c
--- /dev/null
+++ b/client/models/pose_detection/trackers.py
@@ -0,0 +1,53 @@
+from typing import Callable, Mapping
+
+import cv2
+import mediapipe as mp
+from mediapipe.framework import calculator_pb2
+from mediapipe.python._framework_bindings.packet import Packet
+from mediapipe.tasks.python.vision.core.vision_task_running_mode import (
+    VisionTaskRunningMode,
+)
+from mediapipe.tasks.python.vision.pose_landmarker import (
+    PoseLandmarker,
+)
+
+from models.pose_detection.landmarking import AnnotatedImage
+
+
+class DebugPostureTracker(PoseLandmarker):
+    """Handles routines for a Debugging Posture Tracker.
+
+    Attributes:
+        annotated_image: Mutable container for an image which may be mutated asynchronously.
+    """
+
+    def __init__(
+        self,
+        graph_config: calculator_pb2.CalculatorGraphConfig,
+        running_mode: VisionTaskRunningMode,
+        packet_callback: Callable[[Mapping[str, Packet]], None],
+    ) -> None:
+        super().__init__(graph_config, running_mode, packet_callback)
+        self.annotated_image = AnnotatedImage()
+        self._video_capture = cv2.VideoCapture(0)
+
+    def track_posture(self) -> None:
+        """Get frame from video capture device and process with pose model, then posture
+        algorithm. Print debugging info and display landmark annotated frame.
+        """
+        success, frame = self._video_capture.read()
+        if not success:
+            return
+
+        frame_timestamp_ms = self._video_capture.get(cv2.CAP_PROP_POS_MSEC)
+        mp_image = mp.Image(image_format=mp.ImageFormat.SRGB, data=frame)
+        self.detect_async(mp_image, int(frame_timestamp_ms))
+
+        cv2.imshow("input", frame)
+        if self.annotated_image.data is not None:
+            cv2.imshow("output", self.annotated_image.data)
+
+    def __exit__(self, unused_exc_type, unused_exc_value, unused_traceback) -> None:
+        self._video_capture.release()
+        cv2.destroyAllWindows()
+        super().__exit__(unused_exc_type, unused_exc_value, unused_traceback)