remove copy_pose in favor of pose.copy() from sign-language-processing/pose#148

Author: cleong110

pose_evaluation/metrics/base_pose_metric.py

@@ -1,5 +1,55 @@
+from typing import Iterable, List, cast, Union
 from pose_format import Pose
+from pose_evaluation.metrics.pose_processors import PoseProcessor
 
-from pose_evaluation.metrics.base import BaseMetric
+from pose_evaluation.metrics.base import BaseMetric, Signature
 
-PoseMetric = BaseMetric[Pose]
+
+class PoseMetricSignature(Signature):
+
+    def __init__(self, args: dict):
+        super().__init__(args)
+
+        self._abbreviated.update({"pose_preprocessers": "pre"})
+
+        pose_preprocessors = args.get("pose_preprocessers", None)
+        prep_string = ""
+        if pose_preprocessors is not None:
+            prep_string = (
+                "{" + "|".join([f"{prep}" for prep in pose_preprocessors]) + "}"
+            )
+
+        self.signature_info.update(
+            {"pose_preprocessers": prep_string if pose_preprocessors else None}
+        )
+
+
+class PoseMetric(BaseMetric[Pose]):
+    _SIGNATURE_TYPE = PoseMetricSignature
+
+    def __init__(
+        self,
+        name: str = "PoseMetric",
+        higher_is_better: bool = False,
+        pose_preprocessors: Union[None, List[PoseProcessor]] = None,
+    ):
+
+        super().__init__(name, higher_is_better)
+        if pose_preprocessors is None:
+            self.pose_preprocessers = []
+        else:
+            self.pose_preprocessers = pose_preprocessors
+
+    def score(self, hypothesis: Pose, reference: Pose) -> float:
+        hypothesis, reference = self.process_poses([hypothesis, reference])
+        return self.score(hypothesis, reference)
+
+    def process_poses(self, poses: Iterable[Pose]) -> List[Pose]:
+        poses = list(poses)
+        for preprocessor in self.pose_preprocessers:
+            preprocessor = cast(PoseProcessor, preprocessor)
+            poses = preprocessor.process_poses(poses)
+        return poses
+
+    def add_preprocessor(self, processor: PoseProcessor):
+        self.pose_preprocessers.append(processor)

pose_evaluation/utils/pose_utils.py

@@ -71,11 +71,6 @@ def pose_remove_legs(pose: Pose) -> Pose:
     return pose
 
 
-# TODO: remove, once https://github.com/sign-language-processing/pose/pull/148 is added to pip version
-def copy_pose(pose: Pose) -> Pose:
-    return pose.get_components([component.name for component in pose.header.components])
-
-
 def get_face_and_hands_from_pose(pose: Pose) -> Pose:
     # based on MediaPipe Holistic format.
     components_to_keep = [
@@ -96,7 +91,7 @@ def load_pose_file(pose_path: Path) -> Pose:
 def reduce_pose_components_and_points_to_intersection(
     poses: Iterable[Pose],
 ) -> List[Pose]:
-    poses = [copy_pose(pose) for pose in poses]
+    poses = [pose.copy() for pose in poses]
     component_names_for_each_pose = []
     point_dict_for_each_pose = []
     for pose in poses:
@@ -130,7 +125,7 @@ def reduce_pose_components_and_points_to_intersection(
 
 
 def zero_pad_shorter_poses(poses: Iterable[Pose]) -> List[Pose]:
-    poses = [copy_pose(pose) for pose in poses]
+    poses = [pose.copy() for pose in poses]
     # arrays = [pose.body.data for pose in poses]
 
     # first dimension is frames. Then People, joint-points, XYZ or XY
@@ -150,7 +145,7 @@ def zero_pad_shorter_poses(poses: Iterable[Pose]) -> List[Pose]:
 
 
 def set_masked_to_origin_position(pose: Pose) -> Pose:
-    pose = copy_pose(pose)
+    pose = pose.copy()
     # frames, person, keypoint, xyz
     data_copy  = ma.copy(pose.body.data)
     data_copy[data_copy.mask]=0

pose_evaluation/utils/test_pose_utils.py

@@ -74,7 +74,7 @@ def test_remove_specific_landmarks_mediapipe(
 
 def test_pose_copy(mediapipe_poses_test_data: List[Pose]):
     for pose in mediapipe_poses_test_data:
-        copy = copy_pose(pose)
+        copy = pose.copy()
 
         assert copy != pose  # Not the same object
         assert (
@@ -117,7 +117,7 @@ def test_reduce_pose_components_to_intersection(
     standard_mediapipe_components_dict: Dict[str, List[str]],
 ):
 
-    test_poses_with_one_reduced = [copy_pose(pose) for pose in mediapipe_poses_test_data]
+    test_poses_with_one_reduced = [pose.copy() for pose in mediapipe_poses_test_data]
 
     pose_with_only_face_and_hands_and_no_wrist = get_face_and_hands_from_pose(
         test_poses_with_one_reduced.pop()
@@ -226,7 +226,7 @@ def test_detect_format(
 
 def test_set_masked_to_origin_pos(mediapipe_poses_test_data: List[Pose]):
     # Create a copy of the original poses for comparison
-    originals = [copy_pose(pose) for pose in mediapipe_poses_test_data]
+    originals = [pose.copy() for pose in mediapipe_poses_test_data]
 
     # Apply the transformation
     poses = [set_masked_to_origin_position(pose) for pose in mediapipe_poses_test_data]
@@ -252,15 +252,15 @@ def test_set_masked_to_origin_pos(mediapipe_poses_test_data: List[Pose]):
 
 
 def test_hide_low_conf(mediapipe_poses_test_data: List[Pose]):
-    copies = [copy_pose(pose) for pose in mediapipe_poses_test_data]
+    copies = [pose.copy() for pose in mediapipe_poses_test_data]
     for pose, copy in zip(mediapipe_poses_test_data, copies):
         pose_hide_low_conf(pose, 1.0)
 
         assert np.array_equal(pose.body.confidence, copy.body.confidence) is False
 
 
 def test_zero_pad_shorter_poses(mediapipe_poses_test_data: List[Pose]):
-    copies = [copy_pose(pose) for pose in mediapipe_poses_test_data]
+    copies = [pose.copy() for pose in mediapipe_poses_test_data]
 
     max_len = max(len(pose.body.data) for pose in mediapipe_poses_test_data)
     padded_poses = zero_pad_shorter_poses(mediapipe_poses_test_data)