diff --git a/src/facebias/detectors/__init__.py b/src/facebias/detectors/__init__.py
index e659dac..b25d35e 100644
--- a/src/facebias/detectors/__init__.py
+++ b/src/facebias/detectors/__init__.py
@@ -1,8 +1,13 @@
 # -*- coding: utf-8 -*-
 
+import logging
 from abc import ABC, abstractmethod
+from collections import OrderedDict
 
 import numpy as np
+from facebias import FaceBox
+
+logger = logging.getLogger("facebias")
 
 
 class NoFaceDetectedError(Exception):
@@ -20,7 +25,38 @@ class BaseFaceDetector(ABC):
     and perform face detection, whenever a call to `predict` is performed."""
 
     @abstractmethod
-    def detect(self, im) -> np.ndarray:
+    def detect(self, im: np.ndarray) -> np.ndarray:
         """Detects faces in image `im`. Throws `NoFaceDetectedError`
         if `im` has no valid face(s)."""
         pass
+
+
+def get_face_boxes(
+        ims: dict[str, np.ndarray],
+        detector: BaseFaceDetector,
+        num_faces: int=1
+) -> OrderedDict[str, list[FaceBox]]:
+    """
+    Parameters
+    ----------
+    ims: dict[str, np.ndarray],
+    detector: BaseDetector,
+    num_faces: int | 1
+
+    Returns
+    -------
+    all_boxes: OrderedDict[str, list[FaceBox]]
+
+    """
+    all_boxes: OrderedDict[str, list[FaceBox]] = OrderedDict()
+    for p, im in ims.items():
+        boxes = detector.detect(im)
+        if len(boxes) > num_faces:
+            name = "face" if num_faces == 1 else "faces"
+            logger.warning(
+                f"Should only have {num_faces} {name} per image."
+                " Ignoring all others."
+            )
+
+        all_boxes[p] = boxes[:num_faces]
+    return all_boxes