diff --git a/test/detection/test_lmm_florence_2.py b/test/detection/test_lmm_florence_2.py
index 4a5a0094..46d333c9 100644
--- a/test/detection/test_lmm_florence_2.py
+++ b/test/detection/test_lmm_florence_2.py
@@ -1,5 +1,5 @@
-from typing import List, Optional, Tuple
 from contextlib import ExitStack as DoesNotRaise
+from typing import Optional, Tuple
 
 import numpy as np
 import pytest
@@ -10,280 +10,489 @@ from supervision.detection.lmm import from_florence_2
 @pytest.mark.parametrize(
     "florence_result, resolution_wh, expected_results, exception",
     [
-        ( # Object detection: empty
-            {"<OD>":{
-                "bboxes": [],
-                "labels": []
-            }},
+        (  # Object detection: empty
+            {"<OD>": {"bboxes": [], "labels": []}},
             (10, 10),
-            (
-                np.array([], dtype=np.float32),
-                np.array([]),
-                None,
-                None
-            ),
-            DoesNotRaise()
+            (np.array([], dtype=np.float32), np.array([]), None, None),
+            DoesNotRaise(),
         ),
-        ( # Object detection: two detections
-            {"<OD>":{
-                "bboxes": [[4, 4, 6, 6], [5, 5, 7, 7]],
-                "labels": ["car", "door"]
-            }},
+        (  # Object detection: two detections
+            {
+                "<OD>": {
+                    "bboxes": [[4, 4, 6, 6], [5, 5, 7, 7]],
+                    "labels": ["car", "door"],
+                }
+            },
             (10, 10),
             (
                 np.array([[4, 4, 6, 6], [5, 5, 7, 7]], dtype=np.float32),
                 np.array(["car", "door"]),
                 None,
-                None
+                None,
             ),
-            DoesNotRaise()
+            DoesNotRaise(),
         ),
-
-        ( # Caption: unsupported
-            {"<CAPTION>": 'A green car parked in front of a yellow building.'},
+        (  # Caption: unsupported
+            {"<CAPTION>": "A green car parked in front of a yellow building."},
             (10, 10),
             None,
-            pytest.raises(ValueError)
+            pytest.raises(ValueError),
         ),
-        ( # Detailed Caption: unsupported
-            {"<DETAILED_CAPTION>": 'The image shows a blue Volkswagen Beetle parked '
-            'in front of a yellow building with two brown doors, surrounded by '
-            'trees and a clear blue sky.'},
-            (10, 10),
-            None,
-            pytest.raises(ValueError)
-        ),
-        ( # More Detailed Caption: unsupported
+        (  # Detailed Caption: unsupported
             {
-                "<MORE_DETAILED_CAPTION>": 'The image shows a vintage Volkswagen '
-                'Beetle car parked on a '
-                'cobblestone street in front of a yellow building with two wooden '
-                'doors. The car is painted in a bright turquoise color and has a '
-                'white stripe running along the side. It has two doors on either side '
-                'of the car, one on top of the other, and a small window on the '
-                'front. The building appears to be old and dilapidated, with peeling '
-                'paint and crumbling walls. The sky is blue and there are trees in '
-                'the background.'
+                "<DETAILED_CAPTION>": "The image shows a blue Volkswagen Beetle parked "
+                "in front of a yellow building with two brown doors, surrounded by "
+                "trees and a clear blue sky."
             },
             (10, 10),
             None,
-            pytest.raises(ValueError)
+            pytest.raises(ValueError),
         ),
-
-        ( # Caption to Phrase Grounding: empty
-            {"<CAPTION_TO_PHRASE_GROUNDING>":{
-                "bboxes": [],
-                "labels": []
-            }},
-            (10, 10),
-            (
-                np.array([], dtype=np.float32),
-                np.array([]),
-                None,
-                None
-            ),
-            DoesNotRaise()
-        ),
-        ( # Caption to Phrase Grounding: two detections
-            {"<CAPTION_TO_PHRASE_GROUNDING>":{
-                "bboxes": [[4, 4, 6, 6], [5, 5, 7, 7]],
-                "labels": ["a green car", "a yellow building"]
-            }},
-            (10, 10),
-            (
-                np.array([[4, 4, 6, 6], [5, 5, 7, 7]], dtype=np.float32),
-                np.array(["a green car", "a yellow building"]),
-                None,
-                None
-            ),
-            DoesNotRaise()
-        ),
-
-        ( # Dense Region caption: empty
-            {"<DENSE_REGION_CAPTION>":{
-                "bboxes": [],
-                "labels": []
-            }},
-            (10, 10),
-            (
-                np.array([], dtype=np.float32),
-                np.array([]),
-                None,
-                None
-            ),
-            DoesNotRaise()
-        ),
-        ( # Caption to Phrase Grounding: two detections
-            {"<DENSE_REGION_CAPTION>":{
-                "bboxes": [[4, 4, 6, 6], [5, 5, 7, 7]],
-                "labels": ["a green car", "a yellow building"]
-            }},
-            (10, 10),
-            (
-                np.array([[4, 4, 6, 6], [5, 5, 7, 7]], dtype=np.float32),
-                np.array(["a green car", "a yellow building"]),
-                None,
-                None
-            ),
-            DoesNotRaise()
-        ),
-
-        ( # Region proposal
-            {"<REGION_PROPOSAL>":{
-                "bboxes": [[4, 4, 6, 6], [5, 5, 7, 7]],
-                "labels": ["", ""]
-            }},
-            (10, 10),
-            (
-                np.array([[4, 4, 6, 6], [5, 5, 7, 7]], dtype=np.float32),
-                None,
-                None,
-                None
-            ),
-            DoesNotRaise()
-        ),
-
-        ( # Referring Expression Segmentation
-            {"<REFERRING_EXPRESSION_SEGMENTATION>":{
-                "polygons": [[[1, 1, 2, 1, 2, 2, 1, 2]]],
-                "labels": [""]
-            }},
-            (10, 10),
-            (
-                np.array([[1., 1., 2., 2.]], dtype=np.float32),
-                None,
-                np.array([[
-                    [False, False, False, False, False, False, False, False, False, False],
-                    [False,  True,  True, False, False, False, False, False, False, False],
-                    [False,  True,  True, False, False, False, False, False, False, False],
-                    [False, False, False, False, False, False, False, False, False, False],
-                    [False, False, False, False, False, False, False, False, False, False],
-                    [False, False, False, False, False, False, False, False, False, False],
-                    [False, False, False, False, False, False, False, False, False, False],
-                    [False, False, False, False, False, False, False, False, False, False],
-                    [False, False, False, False, False, False, False, False, False, False],
-                    [False, False, False, False, False, False, False, False, False, False]
-                ]]),
-                None
-            ),
-            DoesNotRaise()
-        ),
-
-        ( # Referring Expression Segmentation
-            {"<REFERRING_EXPRESSION_SEGMENTATION>":{
-                "polygons": [[[1, 1, 2, 1, 2, 2, 1, 2]]],
-                "labels": [""]
-            }},
-            (10, 10),
-            (
-                np.array([[1., 1., 2., 2.]], dtype=np.float32),
-                None,
-                np.array([[
-                    [False, False, False, False, False, False, False, False, False, False],
-                    [False,  True,  True, False, False, False, False, False, False, False],
-                    [False,  True,  True, False, False, False, False, False, False, False],
-                    [False, False, False, False, False, False, False, False, False, False],
-                    [False, False, False, False, False, False, False, False, False, False],
-                    [False, False, False, False, False, False, False, False, False, False],
-                    [False, False, False, False, False, False, False, False, False, False],
-                    [False, False, False, False, False, False, False, False, False, False],
-                    [False, False, False, False, False, False, False, False, False, False],
-                    [False, False, False, False, False, False, False, False, False, False]
-                ]]),
-                None
-            ),
-            DoesNotRaise()
-        ),
-
-        ( # OCR: unsupported
-            {"<OCR>": 'A'},
+        (  # More Detailed Caption: unsupported
+            {
+                "<MORE_DETAILED_CAPTION>": "The image shows a vintage Volkswagen "
+                "Beetle car parked on a "
+                "cobblestone street in front of a yellow building with two wooden "
+                "doors. The car is painted in a bright turquoise color and has a "
+                "white stripe running along the side. It has two doors on either side "
+                "of the car, one on top of the other, and a small window on the "
+                "front. The building appears to be old and dilapidated, with peeling "
+                "paint and crumbling walls. The sky is blue and there are trees in "
+                "the background."
+            },
             (10, 10),
             None,
-            pytest.raises(ValueError)
+            pytest.raises(ValueError),
         ),
-
-        ( # OCR with Region: obb boxes
-            {"<OCR_WITH_REGION>":{
-                "quad_boxes": [[2, 2, 6, 4, 5, 6, 1, 5], [4, 4, 5, 5, 4, 6, 3, 5]],
-                "labels": ["some text", "other text"]
-            }},
+        (  # Caption to Phrase Grounding: empty
+            {"<CAPTION_TO_PHRASE_GROUNDING>": {"bboxes": [], "labels": []}},
+            (10, 10),
+            (np.array([], dtype=np.float32), np.array([]), None, None),
+            DoesNotRaise(),
+        ),
+        (  # Caption to Phrase Grounding: two detections
+            {
+                "<CAPTION_TO_PHRASE_GROUNDING>": {
+                    "bboxes": [[4, 4, 6, 6], [5, 5, 7, 7]],
+                    "labels": ["a green car", "a yellow building"],
+                }
+            },
+            (10, 10),
+            (
+                np.array([[4, 4, 6, 6], [5, 5, 7, 7]], dtype=np.float32),
+                np.array(["a green car", "a yellow building"]),
+                None,
+                None,
+            ),
+            DoesNotRaise(),
+        ),
+        (  # Dense Region caption: empty
+            {"<DENSE_REGION_CAPTION>": {"bboxes": [], "labels": []}},
+            (10, 10),
+            (np.array([], dtype=np.float32), np.array([]), None, None),
+            DoesNotRaise(),
+        ),
+        (  # Caption to Phrase Grounding: two detections
+            {
+                "<DENSE_REGION_CAPTION>": {
+                    "bboxes": [[4, 4, 6, 6], [5, 5, 7, 7]],
+                    "labels": ["a green car", "a yellow building"],
+                }
+            },
+            (10, 10),
+            (
+                np.array([[4, 4, 6, 6], [5, 5, 7, 7]], dtype=np.float32),
+                np.array(["a green car", "a yellow building"]),
+                None,
+                None,
+            ),
+            DoesNotRaise(),
+        ),
+        (  # Region proposal
+            {
+                "<REGION_PROPOSAL>": {
+                    "bboxes": [[4, 4, 6, 6], [5, 5, 7, 7]],
+                    "labels": ["", ""],
+                }
+            },
+            (10, 10),
+            (
+                np.array([[4, 4, 6, 6], [5, 5, 7, 7]], dtype=np.float32),
+                None,
+                None,
+                None,
+            ),
+            DoesNotRaise(),
+        ),
+        (  # Referring Expression Segmentation
+            {
+                "<REFERRING_EXPRESSION_SEGMENTATION>": {
+                    "polygons": [[[1, 1, 2, 1, 2, 2, 1, 2]]],
+                    "labels": [""],
+                }
+            },
+            (10, 10),
+            (
+                np.array([[1.0, 1.0, 2.0, 2.0]], dtype=np.float32),
+                None,
+                np.array(
+                    [
+                        [
+                            [
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                            ],
+                            [
+                                False,
+                                True,
+                                True,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                            ],
+                            [
+                                False,
+                                True,
+                                True,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                            ],
+                            [
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                            ],
+                            [
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                            ],
+                            [
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                            ],
+                            [
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                            ],
+                            [
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                            ],
+                            [
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                            ],
+                            [
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                            ],
+                        ]
+                    ]
+                ),
+                None,
+            ),
+            DoesNotRaise(),
+        ),
+        (  # Referring Expression Segmentation
+            {
+                "<REFERRING_EXPRESSION_SEGMENTATION>": {
+                    "polygons": [[[1, 1, 2, 1, 2, 2, 1, 2]]],
+                    "labels": [""],
+                }
+            },
+            (10, 10),
+            (
+                np.array([[1.0, 1.0, 2.0, 2.0]], dtype=np.float32),
+                None,
+                np.array(
+                    [
+                        [
+                            [
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                            ],
+                            [
+                                False,
+                                True,
+                                True,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                            ],
+                            [
+                                False,
+                                True,
+                                True,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                            ],
+                            [
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                            ],
+                            [
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                            ],
+                            [
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                            ],
+                            [
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                            ],
+                            [
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                            ],
+                            [
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                            ],
+                            [
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                                False,
+                            ],
+                        ]
+                    ]
+                ),
+                None,
+            ),
+            DoesNotRaise(),
+        ),
+        (  # OCR: unsupported
+            {"<OCR>": "A"},
+            (10, 10),
+            None,
+            pytest.raises(ValueError),
+        ),
+        (  # OCR with Region: obb boxes
+            {
+                "<OCR_WITH_REGION>": {
+                    "quad_boxes": [[2, 2, 6, 4, 5, 6, 1, 5], [4, 4, 5, 5, 4, 6, 3, 5]],
+                    "labels": ["some text", "other text"],
+                }
+            },
             (10, 10),
             (
                 np.array([[1, 2, 6, 6], [3, 4, 5, 6]], dtype=np.float32),
                 np.array(["some text", "other text"]),
                 None,
-                np.array([[[2, 2], [6, 4], [5, 6], [1, 5]], [[4, 4], [5, 5], [4, 6], [3, 5]]])
+                np.array(
+                    [[[2, 2], [6, 4], [5, 6], [1, 5]], [[4, 4], [5, 5], [4, 6], [3, 5]]]
+                ),
             ),
-            DoesNotRaise()
+            DoesNotRaise(),
         ),
-
-        ( # Open Vocabulary Detection
-            {"<OPEN_VOCABULARY_DETECTION>":{
-                "bboxes": [[4, 4, 6, 6], [5, 5, 7, 7]],
-                "bboxes_labels": ["cat", "cat"],
-                "polygon": [],
-                "polygons_labels": []
-            }},
+        (  # Open Vocabulary Detection
+            {
+                "<OPEN_VOCABULARY_DETECTION>": {
+                    "bboxes": [[4, 4, 6, 6], [5, 5, 7, 7]],
+                    "bboxes_labels": ["cat", "cat"],
+                    "polygon": [],
+                    "polygons_labels": [],
+                }
+            },
             (10, 10),
             (
                 np.array([[4, 4, 6, 6], [5, 5, 7, 7]], dtype=np.float32),
                 np.array(["cat", "cat"]),
                 None,
-                None
-            ),
-            DoesNotRaise()
-        ),
-
-        ( # Region to Category: empty
-            {'<REGION_TO_CATEGORY>': 'No object detected.'},
-            (10, 10),
-            (
-                np.empty((0, 4), dtype=np.float32),
-                np.array([]),
                 None,
-                None
             ),
-            DoesNotRaise()
+            DoesNotRaise(),
         ),
-        ( # Region to Category: detected
-            {'<REGION_TO_CATEGORY>': 'some object category<loc_3><loc_4><loc_5><loc_6>'},
+        (  # Region to Category: empty
+            {"<REGION_TO_CATEGORY>": "No object detected."},
+            (10, 10),
+            (np.empty((0, 4), dtype=np.float32), np.array([]), None, None),
+            DoesNotRaise(),
+        ),
+        (  # Region to Category: detected
+            {
+                "<REGION_TO_CATEGORY>": "some object category<loc_3><loc_4><loc_5><loc_6>"
+            },
             (10, 10),
             (
                 np.array([[3, 4, 5, 6]], dtype=np.float32),
                 np.array(["some object category"]),
                 None,
-                None
-            ),
-            DoesNotRaise()
-        ),
-        ( # Region to Description: empty
-            {'<REGION_TO_DESCRIPTION>': 'No object detected.'},
-            (10, 10),
-            (
-                np.empty((0, 4), dtype=np.float32),
-                np.array([]),
                 None,
-                None
             ),
-            DoesNotRaise()
+            DoesNotRaise(),
         ),
-        ( # Region to Description: detected
-            {'<REGION_TO_DESCRIPTION>': 'some description<loc_3><loc_4><loc_5><loc_6>'},
+        (  # Region to Description: empty
+            {"<REGION_TO_DESCRIPTION>": "No object detected."},
+            (10, 10),
+            (np.empty((0, 4), dtype=np.float32), np.array([]), None, None),
+            DoesNotRaise(),
+        ),
+        (  # Region to Description: detected
+            {"<REGION_TO_DESCRIPTION>": "some description<loc_3><loc_4><loc_5><loc_6>"},
             (10, 10),
             (
                 np.array([[3, 4, 5, 6]], dtype=np.float32),
                 np.array(["some description"]),
                 None,
-                None
+                None,
             ),
-            DoesNotRaise()
-        )
-    ])
+            DoesNotRaise(),
+        ),
+    ],
+)
 def test_florence_2(
     florence_result: dict,
     resolution_wh: Tuple[int, int],
-    expected_results: Tuple[np.ndarray, Optional[np.ndarray], Optional[np.ndarray], Optional[np.ndarray]],
-    exception: Exception
+    expected_results: Tuple[
+        np.ndarray, Optional[np.ndarray], Optional[np.ndarray], Optional[np.ndarray]
+    ],
+    exception: Exception,
 ) -> None:
     with exception:
         result = from_florence_2(florence_result, resolution_wh)