Improve speed

backend/algorithm_subprocesses/5.15/doctor_identity_package/infer_doctor_from_video.py

@@ -43,6 +43,23 @@ POSE_LITE_URL = (
 POSE_LITE_NAME = "pose_landmarker_lite.task"
 
 
+def build_pose_landmarker(
+    model_path: Path,
+    *,
+    min_pose_detection_confidence: float = 0.3,
+) -> PoseLandmarker:
+    """Headless/Docker-safe: force CPU delegate (avoids libGLESv2 GPU path)."""
+    opts = PoseLandmarkerOptions(
+        base_options=BaseOptions(
+            model_asset_path=str(model_path),
+            delegate=BaseOptions.Delegate.CPU,
+        ),
+        running_mode=VisionRunningMode.IMAGE,
+        min_pose_detection_confidence=min_pose_detection_confidence,
+    )
+    return PoseLandmarker.create_from_options(opts)
+
+
 def parse_args() -> argparse.Namespace:
     parser = argparse.ArgumentParser(
         description="Input mp4 -> middle 10s pose crop -> doctor identity",
@@ -282,12 +299,7 @@ def main() -> int:
 
     try:
         model_path = _ensure_pose_lite_model(THIS_DIR / ".mediapipe_models")
-        opts = PoseLandmarkerOptions(
-            base_options=BaseOptions(model_asset_path=str(model_path)),
-            running_mode=VisionRunningMode.IMAGE,
-            min_pose_detection_confidence=0.3,
-        )
-        landmarker = PoseLandmarker.create_from_options(opts)
+        landmarker = build_pose_landmarker(model_path, min_pose_detection_confidence=0.3)
         try:
             best_crop = pick_best_person_crop(
                 video_path=args.video,

backend/algorithm_subprocesses/5.15/src/orchestrator.py

@@ -57,14 +57,12 @@ def _infer_doctor_text(args: Namespace, video_path: Path) -> str:
     try:
         doctor_mod = _load_doctor_module(script_path)
         model_path = doctor_mod._ensure_pose_lite_model(script_path.parent / ".mediapipe_models")
-        opts = doctor_mod.PoseLandmarkerOptions(
-            base_options=doctor_mod.BaseOptions(model_asset_path=str(model_path)),
-            running_mode=doctor_mod.VisionRunningMode.IMAGE,
+        landmarker = doctor_mod.build_pose_landmarker(
+            model_path,
             min_pose_detection_confidence=float(
                 args.doctor_identity_pose_min_detection_confidence
             ),
         )
-        landmarker = doctor_mod.PoseLandmarker.create_from_options(opts)
         try:
             best_crop = doctor_mod.pick_best_person_crop(
                 video_path=video_path,