diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index 75784ee8..dc88e9cc 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 from dataclasses import astuple, dataclass
-from typing import Any, Iterator, List, Optional, Tuple
+from typing import Any, Iterator, List, Optional, Tuple, Union
 
 import numpy as np
 
@@ -469,23 +469,43 @@ class Detections:
 
         raise ValueError(f"{anchor} is not supported.")
 
-    def __getitem__(self, index: np.ndarray) -> Detections:
-        if isinstance(index, np.ndarray) and (
-            index.dtype == bool or index.dtype == int
-        ):
-            return Detections(
-                xyxy=self.xyxy[index],
-                mask=self.mask[index] if self.mask is not None else None,
-                confidence=self.confidence[index]
-                if self.confidence is not None
-                else None,
-                class_id=self.class_id[index] if self.class_id is not None else None,
-                tracker_id=self.tracker_id[index]
-                if self.tracker_id is not None
-                else None,
-            )
-        raise TypeError(
-            f"Detections.__getitem__ not supported for index of type {type(index)}."
+    def __getitem__(
+        self, index: Union[int, slice, List[int], np.ndarray]
+    ) -> Detections:
+        """
+        Get a subset of the Detections object.
+
+        Args:
+            index (Union[int, slice, List[int], np.ndarray]): The index or indices of the subset of the Detections
+
+        Returns:
+            (Detections): A subset of the Detections object.
+
+        Example:
+            ```python
+            >>> import supervision as sv
+
+            >>> detections = sv.Detections(...)
+
+            >>> first_detection = detections[0]
+
+            >>> first_10_detections = detections[0:10]
+
+            >>> some_detections = detections[[0, 2, 4]]
+
+            >>> class_0_detections = detections[detections.class_id == 0]
+
+            >>> high_confidence_detections = detections[detections.confidence > 0.5]
+            ```
+        """
+        if isinstance(index, int):
+            index = [index]
+        return Detections(
+            xyxy=self.xyxy[index],
+            mask=self.mask[index] if self.mask is not None else None,
+            confidence=self.confidence[index] if self.confidence is not None else None,
+            class_id=self.class_id[index] if self.class_id is not None else None,
+            tracker_id=self.tracker_id[index] if self.tracker_id is not None else None,
         )
 
     @property
diff --git a/test/detection/test_core.py b/test/detection/test_core.py
index e24d802f..0ced48a0 100644
--- a/test/detection/test_core.py
+++ b/test/detection/test_core.py
@@ -28,13 +28,6 @@ DETECTIONS = Detections(
 )
 
 
-PREDICTIONS = np.array([
-        [       2254,         906,        2447,        1353,     0.90538,           0],
-        [       2049,        1133,        2226,        1371,     0.59002,          56],
-        [        727,        1224,         838,        1601,     0.51119,          39],
-    ], dtype=np.float32)
-
-
 def mock_detections(xyxy, confidence = None, class_id = None, tracker_id = None) -> Detections:
     return Detections(
         xyxy = np.array(xyxy, dtype=np.float32),
@@ -101,11 +94,108 @@ def mock_detections(xyxy, confidence = None, class_id = None, tracker_id = None)
             ),
             DoesNotRaise()
         ),  # take no detections
+        (
+            DETECTIONS,
+            [0, 2],
+            Detections(
+                xyxy=np.array([
+                    [       2254,         906,        2447,        1353],
+                    [        727,        1224,         838,        1601]
+                ], dtype=np.float32),
+                confidence=np.array([
+                    0.90538,
+                    0.51119
+                ], dtype=np.float32),
+                class_id=np.array([
+                    0,
+                    39
+                ], dtype=int)
+            ),
+            DoesNotRaise()
+        ),  # take only first and third detection using List[int] index
+        (
+            DETECTIONS,
+            np.array([0, 2]),
+            Detections(
+                xyxy=np.array([
+                    [       2254,         906,        2447,        1353],
+                    [        727,        1224,         838,        1601]
+                ], dtype=np.float32),
+                confidence=np.array([
+                    0.90538,
+                    0.51119
+                ], dtype=np.float32),
+                class_id=np.array([
+                    0,
+                    39
+                ], dtype=int)
+            ),
+            DoesNotRaise()
+        ),  # take only first and third detection using np.ndarray index
+        (
+            DETECTIONS,
+            0,
+            Detections(
+                xyxy=np.array([
+                    [       2254,         906,        2447,        1353]
+                ], dtype=np.float32),
+                confidence=np.array([
+                    0.90538
+                ], dtype=np.float32),
+                class_id=np.array([
+                    0
+                ], dtype=int)
+            ),
+            DoesNotRaise()
+        ),  # take only first detection by index
+        (
+            DETECTIONS,
+            slice(1, 3),
+            Detections(
+                xyxy=np.array([
+                    [       2049,        1133,        2226,        1371],
+                    [        727,        1224,         838,        1601]
+                ], dtype=np.float32),
+                confidence=np.array([
+                    0.59002,
+                    0.51119
+                ], dtype=np.float32),
+                class_id=np.array([
+                    56,
+                    39
+                ], dtype=int)
+            ),
+            DoesNotRaise()
+        ),  # take only first detection by index slice (1, 3)
+        (
+            DETECTIONS,
+            10,
+            None,
+            pytest.raises(IndexError)
+        ),  # index out of range
+        (
+            DETECTIONS,
+            [0, 2, 10],
+            None,
+            pytest.raises(IndexError)
+        ),  # index out of range
+        (
+            DETECTIONS,
+            np.array([0, 2, 10]),
+            None,
+            pytest.raises(IndexError)
+        ),
+        (
+            DETECTIONS,
+            np.array([True, True, True, True, True, True, True, True, True, True, True]),
+            None,
+            pytest.raises(IndexError)
+        )
     ]
 )
 def test_getitem(
         detections: Detections,
-        index: Union[int, slice, np.ndarray],
+        index:  Union[int, slice, List[int], np.ndarray],
         expected_result: Optional[Detections],
         exception: Exception
 ) -> None: