UPDATE: Removed SplineAnnotator and added smooth flag for TraceAnnotator

supervision/__init__.py

@@ -28,7 +28,6 @@ from supervision.annotators.core import (
     PolygonAnnotator,
     RichLabelAnnotator,
     RoundBoxAnnotator,
-    SplineAnnotator,
     TraceAnnotator,
     TriangleAnnotator,
 )

supervision/annotators/core.py

@@ -1821,6 +1821,7 @@ class TraceAnnotator(BaseAnnotator):
         position: Position = Position.CENTER,
         trace_length: int = 30,
         thickness: int = 2,
+        smooth: int = 0,
         color_lookup: ColorLookup = ColorLookup.CLASS,
     ):
         """
@@ -1832,12 +1833,14 @@ class TraceAnnotator(BaseAnnotator):
             trace_length (int): The maximum length of the trace in terms of historical
                 points. Defaults to `30`.
             thickness (int): The thickness of the trace lines. Defaults to `2`.
+            smooth (int): The smoothing factor of the trace lines. Defaults to `0`
             color_lookup (ColorLookup): Strategy for mapping colors to annotations.
                 Options are `INDEX`, `CLASS`, `TRACK`.
         """
         self.color: Color | ColorPalette = color
         self.trace = Trace(max_size=trace_length, anchor=position)
         self.thickness = thickness
+        self.smooth = smooth
         self.color_lookup: ColorLookup = color_lookup
 
     @ensure_cv2_image_for_annotation
@@ -1909,103 +1912,13 @@ class TraceAnnotator(BaseAnnotator):
                 else custom_color_lookup,
             )
             xy = self.trace.get(tracker_id=tracker_id)
-
-            if len(xy) > 1:
-                scene = cv2.polylines(
-                    scene,
-                    [xy.astype(np.int32)],
-                    False,
-                    color=color.as_bgr(),
-                    thickness=self.thickness,
-                )
-        return scene
-
-
-class SplineAnnotator(BaseAnnotator):
-    """
-    A class for drawing trace paths on an image based on detection coordinates.
-
-    !!! warning
-
-        This annotator uses the `sv.Detections.tracker_id`. Read
-        [here](/latest/trackers/) to learn how to plug
-        tracking into your inference pipeline.
-    """
-
-    def __init__(
-        self,
-        color: Color | ColorPalette = ColorPalette.DEFAULT,
-        position: Position = Position.CENTER,
-        trace_length: int = 30,
-        thickness: int = 2,
-        smoothing_factor: int = 20,
-        spline_order: int = 3,
-        color_lookup: ColorLookup = ColorLookup.CLASS,
-    ):
-        """
-        Args:
-            color (Union[Color, ColorPalette]): The color to draw the spline, can be
-                a single color or a color palette.
-            position (Position): The position of the spline.
-                Defaults to `CENTER`.
-            trace_length (int): The maximum length of the spline in terms of historical
-                points. Defaults to `30`.
-            thickness (int): The thickness of the spline lines. Defaults to `2`.
-            smoothing_factor (int): The smoothing factor of the spline.
-            spline_order (int): The order of the spline. Use odd numbers that are
-                between 1 <= x <= 5.
-            color_lookup (ColorLookup): Strategy for mapping colors to annotations.
-                Options are `INDEX`, `CLASS`, `TRACK`.
-        """
-        self.color: Color | ColorPalette = color
-        self.trace = Trace(max_size=trace_length, anchor=position)
-        self.thickness = thickness
-        self.smoothing_factor = smoothing_factor
-        self.color_lookup: ColorLookup = color_lookup
-
-        if spline_order % 2 == 0 or spline_order < 1 or spline_order > 5:
-            raise ValueError("Spline order must be an odd number between 1 and 5.")
-        self.spline_order = spline_order
-
-    @ensure_cv2_image_for_annotation
-    def annotate(
-        self,
-        scene: ImageType,
-        detections: Detections,
-        custom_color_lookup: np.ndarray | None = None,
-    ) -> ImageType:
-        assert isinstance(scene, np.ndarray)
-
-        if detections.tracker_id is None:
-            raise ValueError(
-                "The `tracker_id` field is missing in the provided detections."
-                " See more: https://supervision.roboflow.com/latest/how_to/track_objects"
-            )
-
-        detections = detections[detections.tracker_id != PENDING_TRACK_ID]
-
-        self.trace.put(detections)
-
-        for detection_idx in range(len(detections)):
-            tracker_id = int(detections.tracker_id[detection_idx])
-            color = resolve_color(
-                color=self.color,
-                detections=detections,
-                detection_idx=detection_idx,
-                color_lookup=self.color_lookup
-                if custom_color_lookup is None
-                else custom_color_lookup,
-            )
-            xy = self.trace.get(tracker_id=tracker_id)
-            spline_points = None
+            spline_points = xy.astype(np.int32)
 
             if len(xy) > 3:
                 x, y = xy[:, 0], xy[:, 1]
-                tck, u = splprep([x, y], s=self.smoothing_factor, k=self.spline_order)
+                tck, u = splprep([x, y], s=self.smooth)
                 x_new, y_new = splev(np.linspace(0, 1, 100), tck)
                 spline_points = np.stack([x_new, y_new], axis=1).astype(np.int32)
-            else:
-                spline_points = xy.astype(np.int32)
 
             if len(xy) > 1:
                 scene = cv2.polylines(