Merge branch 'sign-language-processing:master' into master

src/python/pose_format/bin/pose_visualizer.py

@@ -3,24 +3,20 @@
 import argparse
 import os
 
-import numpy as np
 from pose_format import Pose
 from pose_format.pose_visualizer import PoseVisualizer
 from pose_format.utils.generic import pose_normalization_info
 
+from pose_format.utils.generic import normalize_pose_size
+
 
 def visualize_pose(pose_path: str, video_path: str, normalize=False):
     with open(pose_path, "rb") as f:
         pose = Pose.read(f.read())
 
     if normalize:
         pose = pose.normalize(pose_normalization_info(pose.header))
-
-        new_width = 500
-        shift = 1.25
-        shift_vec = np.full(shape=(pose.body.data.shape[-1]), fill_value=shift, dtype=np.float32)
-        pose.body.data = (pose.body.data + shift_vec) * new_width
-        pose.header.dimensions.height = pose.header.dimensions.width = int(new_width * shift * 2)
+        normalize_pose_size(pose)
 
     v = PoseVisualizer(pose)
 

src/python/pose_format/pose_visualizer.py

@@ -68,7 +68,7 @@ def _draw_frame(self, frame: ma.MaskedArray, frame_confidence: np.ndarray, img,
         thickness = self.thickness
         if self.thickness is None:
             thickness = round(math.sqrt(img.shape[0] * img.shape[1]) / 150)
-        radius = round(thickness / 2)
+        radius = math.ceil(thickness / 2)
 
         draw_operations = []
 

src/python/pose_format/utils/generic.py

@@ -9,6 +9,14 @@
 from pose_format.utils.openpose import OpenPose_Components
 
 
+def normalize_pose_size(pose: Pose, target_width: int = 512):
+    shift = 1.25
+    shoulder_width = (target_width / shift) / 2
+    shift_vec = np.full(shape=(pose.body.data.shape[-1]), fill_value=shift, dtype=np.float32)
+    pose.body.data = (pose.body.data + shift_vec) * shoulder_width
+    pose.header.dimensions.height = pose.header.dimensions.width = target_width
+
+
 def pose_hide_legs(pose: Pose):
     if pose.header.components[0].name == "POSE_LANDMARKS":
         point_names = ["KNEE", "ANKLE", "HEEL", "FOOT_INDEX"]

src/python/pose_format/utils/pose_converter.py

@@ -221,10 +221,13 @@ def convert_pose(pose: Pose, pose_components: List[PoseHeaderComponent]) -> Pose
     dims = min(len(pose_header.components[0].format), len(pose.header.components[0].format)) - 1
     for (c1, p1), (c2, p2) in mapping.items():
         p2 = tuple([p2]) if isinstance(p2, str) else p2
-        p2s = [pose.header._get_point_index(c2, p) for p in list(p2)]
-        p1_index = pose_header._get_point_index(c1, p1)
-        data[:, :, p1_index, :dims] = pose.body.data[:, :, p2s, :dims].mean(axis=2)
-        conf[:, :, p1_index] = pose.body.confidence[:, :, p2s].mean(axis=2)
+        try:
+            p2s = [pose.header._get_point_index(c2, p) for p in list(p2)]
+            p1_index = pose_header._get_point_index(c1, p1)
+            data[:, :, p1_index, :dims] = pose.body.data[:, :, p2s, :dims].mean(axis=2)
+            conf[:, :, p1_index] = pose.body.confidence[:, :, p2s].mean(axis=2)
+        except Exception as e:
+            print(f"Error in mapping {c1} {p1} to {c2} {p2}: {e}")
 
     pose_body = NumPyPoseBody(fps=pose.body.fps, data=data, confidence=conf)
 

src/python/pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "pose_format"
 description = "Library for viewing, augmenting, and handling .pose files"
-version = "0.6.2"
+version = "0.7.0"
 keywords = ["Pose Files", "Pose Interpolation", "Pose Augmentation"]
 authors = [
     { name = "Amit Moryossef", email = "amitmoryossef@gmail.com" },