bump version from 0.26.0rc6 to 0.26.0rc7

fix: `UnboundLocalError` in `process_video`

.github/workflows/publish-docs.yml

@@ -34,13 +34,13 @@ jobs:
           fetch-depth: 0
 
       - name: 🐍 Install uv and set Python ${{ matrix.python-version }}
-        uses: astral-sh/setup-uv@4db96194c378173c656ce18a155ffc14a9fc4355 # v5.2.2
+        uses: astral-sh/setup-uv@d4b2f3b6ecc6e67c4457f6d3e41ec42d3d0fcb86 # v5.4.2
         with:
           python-version: ${{ matrix.python-version }}
 
       - name: 🔑 Create GitHub App token (mkdocs)
         id: mkdocs_token
-        uses: actions/create-github-app-token@c1a285145b9d317df6ced56c09f525b5c2b6f755 # v1.11.1
+        uses: actions/create-github-app-token@3ff1caaa28b64c9cc276ce0a02e2ff584f3900c5 # v2.0.2
         with:
           app-id: ${{ secrets.MKDOCS_APP_ID }}
           private-key: ${{ secrets.MKDOCS_PEM }}

.github/workflows/publish-pre-release.yml

@@ -29,7 +29,7 @@ jobs:
         uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
 
       - name: 🐍 Install uv and set Python version ${{ matrix.python-version }}
-        uses: astral-sh/setup-uv@4db96194c378173c656ce18a155ffc14a9fc4355 # v5.2.2
+        uses: astral-sh/setup-uv@d4b2f3b6ecc6e67c4457f6d3e41ec42d3d0fcb86 # v5.4.2
         with:
           python-version: ${{ matrix.python-version }}
 

.github/workflows/publish-release.yml

@@ -27,7 +27,7 @@ jobs:
         uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
 
       - name: 🐍 Install uv and set Python version ${{ matrix.python-version }}
-        uses: astral-sh/setup-uv@4db96194c378173c656ce18a155ffc14a9fc4355 # v5.2.2
+        uses: astral-sh/setup-uv@d4b2f3b6ecc6e67c4457f6d3e41ec42d3d0fcb86 # v5.4.2
         with:
           python-version: ${{ matrix.python-version }}
 
@@ -38,6 +38,6 @@ jobs:
           uv run twine check --strict dist/*
 
       - name: 🚀 Publish to PyPi
-        uses: pypa/gh-action-pypi-publish@67339c736fd9354cd4f8cb0b744f2b82a74b5c70 # v1.12.3
+        uses: pypa/gh-action-pypi-publish@76f52bc884231f62b9a034ebfe128415bbaabdfc # v1.12.4
         with:
           attestations: true

.github/workflows/publish-testpypi.yml

@@ -24,7 +24,7 @@ jobs:
         uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
 
       - name: 🐍 Install uv and set Python version ${{ matrix.python-version }}
-        uses: astral-sh/setup-uv@4db96194c378173c656ce18a155ffc14a9fc4355 # v5.2.2
+        uses: astral-sh/setup-uv@d4b2f3b6ecc6e67c4457f6d3e41ec42d3d0fcb86 # v5.4.2
         with:
           python-version: ${{ matrix.python-version }}
 

.github/workflows/test-doc.yml

@@ -24,7 +24,7 @@ jobs:
           fetch-depth: 0
 
       - name: 🐍 Install uv and set Python ${{ matrix.python-version }}
-        uses: astral-sh/setup-uv@4db96194c378173c656ce18a155ffc14a9fc4355 # v5.2.2
+        uses: astral-sh/setup-uv@d4b2f3b6ecc6e67c4457f6d3e41ec42d3d0fcb86 # v5.4.2
         with:
           python-version: ${{ matrix.python-version }}
 

.github/workflows/uv-test.yml

@@ -19,7 +19,7 @@ jobs:
         uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
 
       - name: 🐍 Install uv and set Python version ${{ matrix.python-version }}
-        uses: astral-sh/setup-uv@4db96194c378173c656ce18a155ffc14a9fc4355 # v5.2.2
+        uses: astral-sh/setup-uv@d4b2f3b6ecc6e67c4457f6d3e41ec42d3d0fcb86 # v5.4.2
         with:
           python-version: ${{ matrix.python-version }}
 

.pre-commit-config.yaml

@@ -25,14 +25,14 @@ repos:
       - id: mixed-line-ending
 
   -   repo: https://github.com/PyCQA/bandit
-      rev: '1.8.0'
+      rev: '1.8.3'
       hooks:
       -   id: bandit
           args: ["-c", "pyproject.toml"]
           additional_dependencies: ["bandit[toml]"]
 
   -   repo: https://github.com/astral-sh/ruff-pre-commit
-      rev: v0.8.6
+      rev: v0.11.6
       hooks:
       -   id: ruff
           args: [--fix, --exit-non-zero-on-fix]
@@ -48,7 +48,7 @@ repos:
   #       args: ["--number"]
 
   - repo: https://github.com/codespell-project/codespell
-    rev: v2.3.0
+    rev: v2.4.1
     hooks:
       - id: codespell
         additional_dependencies:

docs/detection/utils.md

@@ -95,6 +95,12 @@ status: new
 
 :::supervision.detection.utils.xyxy_to_xywh
 
+<div class="md-typeset">
+  <h2><a href="#supervision.detection.utils.xyxy_to_xcycarh">xyxy_to_xcycarh</a></h2>
+</div>
+
+:::supervision.detection.utils.xyxy_to_xcycarh
+
 <div class="md-typeset">
   <h2><a href="#supervision.detection.utils.xcycwh_to_xyxy">xcycwh_to_xyxy</a></h2>
 </div>

docs/javascripts/segment.js

@@ -0,0 +1,4 @@
+!function(){var i="analytics",analytics=window[i]=window[i]||[];if(!analytics.initialize)if(analytics.invoked)window.console&&console.error&&console.error("Segment snippet included twice.");else{analytics.invoked=!0;analytics.methods=["trackSubmit","trackClick","trackLink","trackForm","pageview","identify","reset","group","track","ready","alias","debug","page","screen","once","off","on","addSourceMiddleware","addIntegrationMiddleware","setAnonymousId","addDestinationMiddleware","register"];analytics.factory=function(e){return function(){if(window[i].initialized)return window[i][e].apply(window[i],arguments);var n=Array.prototype.slice.call(arguments);if(["track","screen","alias","group","page","identify"].indexOf(e)>-1){var c=document.querySelector("link[rel='canonical']");n.push({__t:"bpc",c:c&&c.getAttribute("href")||void 0,p:location.pathname,u:location.href,s:location.search,t:document.title,r:document.referrer})}n.unshift(e);analytics.push(n);return analytics}};for(var n=0;n<analytics.methods.length;n++){var key=analytics.methods[n];analytics[key]=analytics.factory(key)}analytics.load=function(key,n){var t=document.createElement("script");t.type="text/javascript";t.async=!0;t.setAttribute("data-global-segment-analytics-key",i);t.src="https://cdn.segment.com/analytics.js/v1/" + key + "/analytics.min.js";var r=document.getElementsByTagName("script")[0];r.parentNode.insertBefore(t,r);analytics._loadOptions=n};analytics._writeKey="rMvrPeZBJYyOPJSGCNhMlnTJb8VhFiWU";;analytics.SNIPPET_VERSION="5.2.0";
+  analytics.load("eohFog7VZiAhGJGEr5Sh7BM1mFKmUvDC");
+  document$.subscribe(analytics.page);
+  }}();

mkdocs.yml

@@ -149,9 +149,12 @@ plugins:
             group_by_category: true
             docstring_style: google
             show_symbol_type_heading: true
+            show_root_heading: True
             show_symbol_type_toc: true
             show_category_heading: true
-          domains: [std, py]
+          inventories:
+          - url: https://docs.python-requests.org/en/master/objects.inv
+            domains: [std, py]
   - git-committers:
       repository: roboflow/supervision
       branch: develop
@@ -176,10 +179,13 @@ markdown_extensions:
       check_paths: true
   - pymdownx.highlight:
       anchor_linenums: true
+      line_spans: __span
+      pygments_lang_class: true
 
 extra_javascript:
   - "javascripts/init_kapa_widget.js"
   - "javascripts/cookbooks-card.js"
+  - "javascripts/segment.js"
   - "https://cdnjs.cloudflare.com/ajax/libs/dompurify/3.0.8/purify.min.js"
 
 # Messages shown during document build

pyproject.toml

@@ -2,7 +2,7 @@
 name = "supervision"
 description = "A set of easy-to-use utils that will come in handy in any Computer Vision project"
 license = { text = "MIT" }
-version = "0.26.0rc4"
+version = "0.26.0rc7"
 readme = "README.md"
 requires-python = ">=3.8"
 authors = [
@@ -69,7 +69,7 @@ dev = [
 ]
 docs = [
     "mkdocs-material[imaging]>=9.5.5",
-    "mkdocstrings>=0.25.2,<0.27.0",
+    "mkdocstrings>=0.25.2,<0.30.0",
     "mkdocstrings-python>=1.10.9",
     "mike>=2.0.0",
     "mkdocs-jupyter>=0.24.3",

supervision/__init__.py

@@ -76,6 +76,7 @@ from supervision.detection.utils import (
     xcycwh_to_xyxy,
     xywh_to_xyxy,
     xyxy_to_polygons,
+    xyxy_to_xcycarh,
     xyxy_to_xywh,
 )
 from supervision.detection.vlm import LMM, VLM
@@ -225,5 +226,6 @@ __all__ = [
     "xcycwh_to_xyxy",
     "xywh_to_xyxy",
     "xyxy_to_polygons",
+    "xyxy_to_xyah",
     "xyxy_to_xywh",
 ]

supervision/annotators/core.py

@@ -9,6 +9,7 @@ from PIL import Image, ImageDraw, ImageFont
 
 from supervision.annotators.base import BaseAnnotator, ImageType
 from supervision.annotators.utils import (
+    PENDING_TRACK_ID,
     ColorLookup,
     Trace,
     resolve_color,
@@ -1130,7 +1131,7 @@ class LabelAnnotator(BaseAnnotator):
         detections: Detections, custom_labels: Optional[List[str]]
     ) -> List[str]:
         if custom_labels is not None:
-            return custom_labels
+            return [str(label) for label in custom_labels]
 
         labels = []
         for idx in range(len(detections)):
@@ -1739,6 +1740,7 @@ class TraceAnnotator(BaseAnnotator):
                 "The `tracker_id` field is missing in the provided detections."
                 " See more: https://supervision.roboflow.com/latest/how_to/track_objects"
             )
+        detections = detections[detections.tracker_id != PENDING_TRACK_ID]
 
         self.trace.put(detections)
         for detection_idx in range(len(detections)):
@@ -1857,11 +1859,9 @@ class HeatMapAnnotator(BaseAnnotator):
         temp = temp.astype(np.uint8)
         if self.kernel_size is not None:
             temp = cv2.blur(temp, (self.kernel_size, self.kernel_size))
-        hsv = np.zeros(scene.shape)
+        hsv = np.full(scene.shape, 255, dtype=np.uint8)
         hsv[..., 0] = temp
-        hsv[..., 1] = 255
-        hsv[..., 2] = 255
-        temp = cv2.cvtColor(hsv.astype(np.uint8), cv2.COLOR_HSV2BGR)
+        temp = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
         mask = cv2.cvtColor(self.heat_mask.astype(np.uint8), cv2.COLOR_GRAY2BGR) > 0
         scene[mask] = cv2.addWeighted(temp, self.opacity, scene, 1 - self.opacity, 0)[
             mask

supervision/annotators/utils.py

@@ -7,6 +7,9 @@ from supervision.detection.core import Detections
 from supervision.draw.color import Color, ColorPalette
 from supervision.geometry.core import Position
 
+PENDING_TRACK_COLOR = Color.GREY
+PENDING_TRACK_ID = -1
+
 
 class ColorLookup(Enum):
     """
@@ -136,6 +139,8 @@ def resolve_color(
         detection_idx=detection_idx,
         color_lookup=color_lookup,
     )
+    if color_lookup == ColorLookup.TRACK and idx == PENDING_TRACK_ID:
+        return PENDING_TRACK_COLOR
     return get_color_by_index(color=color, idx=idx)
 
 

supervision/detection/core.py

@@ -715,7 +715,7 @@ class Detections:
         """
         if "error" in azure_result:
             raise ValueError(
-                f'Azure API returned an error {azure_result["error"]["message"]}'
+                f"Azure API returned an error {azure_result['error']['message']}"
             )
 
         xyxy, confidences, class_ids = [], [], []
@@ -1346,9 +1346,9 @@ class Detections:
         if len(self) == 0:
             return self
 
-        assert (
-            self.confidence is not None
-        ), "Detections confidence must be given for NMS to be executed."
+        assert self.confidence is not None, (
+            "Detections confidence must be given for NMS to be executed."
+        )
 
         if class_agnostic:
             predictions = np.hstack((self.xyxy, self.confidence.reshape(-1, 1)))
@@ -1402,9 +1402,9 @@ class Detections:
         if len(self) == 0:
             return self
 
-        assert (
-            self.confidence is not None
-        ), "Detections confidence must be given for NMM to be executed."
+        assert self.confidence is not None, (
+            "Detections confidence must be given for NMM to be executed."
+        )
 
         if class_agnostic:
             predictions = np.hstack((self.xyxy, self.confidence.reshape(-1, 1)))

supervision/detection/overlap_filter.py

@@ -226,8 +226,7 @@ def box_non_max_merge(
     for merge_group in merge_groups:
         if len(merge_group) == 0:
             raise ValueError(
-                f"Empty group detected when non-max-merging "
-                f"detections: {merge_groups}"
+                f"Empty group detected when non-max-merging detections: {merge_groups}"
             )
     return merge_groups
 

supervision/detection/utils.py

@@ -397,6 +397,56 @@ def xcycwh_to_xyxy(xcycwh: np.ndarray) -> np.ndarray:
     return xyxy
 
 
+def xyxy_to_xcycarh(xyxy: np.ndarray) -> np.ndarray:
+    """
+    Converts bounding box coordinates from `(x_min, y_min, x_max, y_max)`
+    into measurement space to format `(center x, center y, aspect ratio, height)`,
+    where the aspect ratio is `width / height`.
+
+    Args:
+        xyxy (np.ndarray): Bounding box in format `(x1, y1, x2, y2)`.
+            Expected shape is `(N, 4)`.
+    Returns:
+        np.ndarray: Bounding box in format
+            `(center x, center y, aspect ratio, height)`. Shape `(N, 4)`.
+
+    Examples:
+        ```python
+        import numpy as np
+        import supervision as sv
+
+        xyxy = np.array([
+            [10, 20, 40, 60],
+            [15, 25, 50, 70]
+        ])
+
+        sv.xyxy_to_xcycarh(xyxy=xyxy)
+        # array([
+        #     [25.  , 40.  ,  0.75, 40.  ],
+        #     [32.5 , 47.5 ,  0.77777778, 45.  ]
+        # ])
+        ```
+
+    """
+    if xyxy.size == 0:
+        return np.empty((0, 4), dtype=float)
+
+    x1, y1, x2, y2 = xyxy.T
+    width = x2 - x1
+    height = y2 - y1
+    center_x = x1 + width / 2
+    center_y = y1 + height / 2
+
+    aspect_ratio = np.divide(
+        width,
+        height,
+        out=np.zeros_like(width, dtype=float),
+        where=height != 0,
+    )
+    result = np.column_stack((center_x, center_y, aspect_ratio, height))
+    return result.astype(float)
+
+
 def mask_to_xyxy(masks: np.ndarray) -> np.ndarray:
     """
     Converts a 3D `np.array` of 2D bool masks into a 2D `np.array` of bounding boxes.

supervision/detection/vlm.py

@@ -294,18 +294,18 @@ def from_florence_2(
         return xyxy, labels, None, None
 
     if task in ["<REGION_TO_CATEGORY>", "<REGION_TO_DESCRIPTION>"]:
-        assert isinstance(
-            result, str
-        ), f"Expected string as <REGION_TO_CATEGORY> result, got {type(result)}"
+        assert isinstance(result, str), (
+            f"Expected string as <REGION_TO_CATEGORY> result, got {type(result)}"
+        )
 
         if result == "No object detected.":
             return np.empty((0, 4), dtype=np.float32), np.array([]), None, None
 
         pattern = re.compile(r"<loc_(\d+)><loc_(\d+)><loc_(\d+)><loc_(\d+)>")
         match = pattern.search(result)
-        assert (
-            match is not None
-        ), f"Expected string to end in location tags, but got {result}"
+        assert match is not None, (
+            f"Expected string to end in location tags, but got {result}"
+        )
 
         w, h = resolution_wh
         xyxy = np.array([match.groups()], dtype=np.float32)

supervision/draw/color.py

@@ -83,15 +83,16 @@ class Color:
         # Color(r=255, g=255, b=255)
         ```
 
-    | Constant   | Hex Code   | RGB              |
-    |------------|------------|------------------|
-    | `WHITE`    | `#FFFFFF`  | `(255, 255, 255)`|
-    | `BLACK`    | `#000000`  | `(0, 0, 0)`      |
-    | `RED`      | `#FF0000`  | `(255, 0, 0)`    |
-    | `GREEN`    | `#00FF00`  | `(0, 255, 0)`    |
-    | `BLUE`     | `#0000FF`  | `(0, 0, 255)`    |
-    | `YELLOW`   | `#FFFF00`  | `(255, 255, 0)`  |
-    | `ROBOFLOW` | `#A351FB`  | `(163, 81, 251)` |
+    | Constant   | Hex Code   | RGB               |
+    |------------|------------|-------------------|
+    | `WHITE`    | `#FFFFFF`  | `(255, 255, 255)` |
+    | `BLACK`    | `#000000`  | `(0, 0, 0)`       |
+    | `GREY`     | `#808080`  | `(128, 128, 128)` |
+    | `RED`      | `#FF0000`  | `(255, 0, 0)`     |
+    | `GREEN`    | `#00FF00`  | `(0, 255, 0)`     |
+    | `BLUE`     | `#0000FF`  | `(0, 0, 255)`     |
+    | `YELLOW`   | `#FFFF00`  | `(255, 255, 0)`   |
+    | `ROBOFLOW` | `#A351FB`  | `(163, 81, 251)`  |
     """
 
     r: int
@@ -235,6 +236,10 @@ class Color:
     def BLACK(cls) -> Color:
         return Color.from_hex("#000000")
 
+    @classproperty
+    def GREY(cls) -> Color:
+        return Color.from_hex("#808080")
+
     @classproperty
     def RED(cls) -> Color:
         return Color.from_hex("#FF0000")

supervision/keypoint/core.py

@@ -23,8 +23,8 @@ class KeyPoints:
     === "Ultralytics"
 
         Use [`sv.KeyPoints.from_ultralytics`](/latest/keypoint/core/#supervision.keypoint.core.KeyPoints.from_ultralytics)
-        method, which accepts [YOLOv8](https://github.com/ultralytics/ultralytics)
-        pose result.
+        method, which accepts [YOLOv8-pose](https://docs.ultralytics.com/models/yolov8/), [YOLO11-pose](https://docs.ultralytics.com/models/yolo11/)
+        [pose](https://docs.ultralytics.com/tasks/pose/) result.
 
         ```python
         import cv2
@@ -32,7 +32,7 @@ class KeyPoints:
         from ultralytics import YOLO
 
         image = cv2.imread(<SOURCE_IMAGE_PATH>)
-        model = YOLO('yolov8s-pose.pt')
+        model = YOLO('yolo11s-pose.pt')
 
         result = model(image)[0]
         key_points = sv.KeyPoints.from_ultralytics(result)

supervision/metrics/mean_average_recall.py

@@ -670,8 +670,7 @@ class MeanAverageRecallResult:
         ax.set_ylim(0, 1)
         ax.set_ylabel("Value", fontweight="bold")
         title = (
-            f"Mean Average Recall, by Object Size"
-            f"\n(target: {self.metric_target.value})"
+            f"Mean Average Recall, by Object Size\n(target: {self.metric_target.value})"
         )
         ax.set_title(title, fontweight="bold")
 

supervision/utils/video.py

@@ -7,6 +7,7 @@ from typing import Callable, Generator, Optional, Tuple
 
 import cv2
 import numpy as np
+from tqdm.auto import tqdm
 
 
 @dataclass
@@ -195,6 +196,9 @@ def process_video(
     source_path: str,
     target_path: str,
     callback: Callable[[np.ndarray, int], np.ndarray],
+    max_frames: Optional[int] = None,
+    show_progress: bool = False,
+    progress_message: str = "Processing video",
 ) -> None:
     """
     Process a video file by applying a callback function on each frame
@@ -207,6 +211,9 @@ def process_video(
             a numpy ndarray representation of a video frame and an
             int index of the frame and returns a processed numpy ndarray
             representation of the frame.
+        max_frames (Optional[int]): The maximum number of frames to process.
+        show_progress (bool): Whether to show a progress bar.
+        progress_message (str): The message to display in the progress bar.
 
     Examples:
         ```python
@@ -223,12 +230,29 @@ def process_video(
         ```
     """
     source_video_info = VideoInfo.from_video_path(video_path=source_path)
+    video_frames_generator = get_video_frames_generator(
+        source_path=source_path, end=max_frames
+    )
     with VideoSink(target_path=target_path, video_info=source_video_info) as sink:
+        total_frames = (
+            min(source_video_info.total_frames, max_frames)
+            if max_frames is not None
+            else source_video_info.total_frames
+        )
         for index, frame in enumerate(
-            get_video_frames_generator(source_path=source_path)
+            tqdm(
+                video_frames_generator,
+                total=total_frames,
+                disable=not show_progress,
+                desc=progress_message,
+            )
         ):
             result_frame = callback(frame, index)
             sink.write_frame(frame=result_frame)
+        else:
+            for index, frame in enumerate(video_frames_generator):
+                result_frame = callback(frame, index)
+                sink.write_frame(frame=result_frame)
 
 
 class FPSMonitor:

supervision/validators/__init__.py

@@ -54,7 +54,7 @@ def validate_confidence(confidence: Any, n: int) -> None:
 
 
 def validate_keypoint_confidence(confidence: Any, n: int, m: int) -> None:
-    expected_shape = f"({n,m})"
+    expected_shape = f"({n, m})"
     actual_shape = str(getattr(confidence, "shape", None))
 
     if confidence is not None:

test/detection/test_csv.py

@@ -408,8 +408,8 @@ def assert_csv_equal(file_name, expected_rows):
     with open(file_name, mode="r", newline="") as file:
         reader = csv.reader(file)
         for i, row in enumerate(reader):
-            assert (
-                [str(item) for item in expected_rows[i]] == row
-            ), f"Row in CSV didn't match expected output: {row} != {expected_rows[i]}"
+            assert [str(item) for item in expected_rows[i]] == row, (
+                f"Row in CSV didn't match expected output: {row} != {expected_rows[i]}"
+            )
 
     os.remove(file_name)

test/detection/test_json.py

@@ -242,8 +242,8 @@ def test_json_sink(
 def assert_json_equal(file_name, expected_rows):
     with open(file_name, "r") as file:
         data = json.load(file)
-        assert (
-            data == expected_rows
-        ), f"Data in JSON file didn't match expected output: {data} != {expected_rows}"
+        assert data == expected_rows, (
+            f"Data in JSON file didn't match expected output: {data} != {expected_rows}"
+        )
 
     os.remove(file_name)

test/detection/test_line_counter.py

@@ -250,12 +250,12 @@ def test_line_zone_one_detection_default_anchors(
         crossed_in_list.append(crossed_in[0])
         crossed_out_list.append(crossed_out[0])
 
-    assert (
-        crossed_in_list == expected_crossed_in
-    ), f"expected {expected_crossed_in}, got {crossed_in_list}"
-    assert (
-        crossed_out_list == expected_crossed_out
-    ), f"expected {expected_crossed_out}, got {crossed_out_list}"
+    assert crossed_in_list == expected_crossed_in, (
+        f"expected {expected_crossed_in}, got {crossed_in_list}"
+    )
+    assert crossed_out_list == expected_crossed_out, (
+        f"expected {expected_crossed_out}, got {crossed_out_list}"
+    )
 
 
 @pytest.mark.parametrize(
@@ -415,12 +415,12 @@ def test_line_zone_one_detection(
         crossed_in_list.append(crossed_in[0])
         crossed_out_list.append(crossed_out[0])
 
-    assert (
-        crossed_in_list == expected_crossed_in
-    ), f"expected {expected_crossed_in}, got {crossed_in_list}"
-    assert (
-        crossed_out_list == expected_crossed_out
-    ), f"expected {expected_crossed_out}, got {crossed_out_list}"
+    assert crossed_in_list == expected_crossed_in, (
+        f"expected {expected_crossed_in}, got {crossed_in_list}"
+    )
+    assert crossed_out_list == expected_crossed_out, (
+        f"expected {expected_crossed_out}, got {crossed_out_list}"
+    )
 
 
 @pytest.mark.parametrize(
@@ -600,12 +600,12 @@ def test_line_zone_one_detection_long_horizon(
         crossed_in_list.append(crossed_in[0])
         crossed_out_list.append(crossed_out[0])
 
-    assert (
-        crossed_in_list == expected_crossed_in
-    ), f"expected {expected_crossed_in}, got {crossed_in_list}"
-    assert (
-        crossed_out_list == expected_crossed_out
-    ), f"expected {expected_crossed_out}, got {crossed_out_list}"
+    assert crossed_in_list == expected_crossed_in, (
+        f"expected {expected_crossed_in}, got {crossed_in_list}"
+    )
+    assert crossed_out_list == expected_crossed_out, (
+        f"expected {expected_crossed_out}, got {crossed_out_list}"
+    )
 
 
 @pytest.mark.parametrize(

test/detection/test_utils.py

@@ -21,6 +21,7 @@ from supervision.detection.utils import (
     scale_boxes,
     xcycwh_to_xyxy,
     xywh_to_xyxy,
+    xyxy_to_xcycarh,
     xyxy_to_xywh,
 )
 
@@ -389,13 +390,13 @@ def test_process_roboflow_result(
         )
         for key in result[5]:
             if isinstance(result[5][key], np.ndarray):
-                assert np.array_equal(
-                    result[5][key], expected_result[5][key]
-                ), f"Mismatch in arrays for key {key}"
+                assert np.array_equal(result[5][key], expected_result[5][key]), (
+                    f"Mismatch in arrays for key {key}"
+                )
             else:
-                assert (
-                    result[5][key] == expected_result[5][key]
-                ), f"Mismatch in non-array data for key {key}"
+                assert result[5][key] == expected_result[5][key], (
+                    f"Mismatch in non-array data for key {key}"
+                )
 
 
 @pytest.mark.parametrize(
@@ -1042,13 +1043,13 @@ def test_merge_data(
 
         for key in result:
             if isinstance(result[key], np.ndarray):
-                assert np.array_equal(
-                    result[key], expected_result[key]
-                ), f"Mismatch in arrays for key {key}"
+                assert np.array_equal(result[key], expected_result[key]), (
+                    f"Mismatch in arrays for key {key}"
+                )
             else:
-                assert (
-                    result[key] == expected_result[key]
-                ), f"Mismatch in non-array data for key {key}"
+                assert result[key] == expected_result[key], (
+                    f"Mismatch in non-array data for key {key}"
+                )
 
 
 @pytest.mark.parametrize(
@@ -1215,13 +1216,13 @@ def test_get_data_item(
         result = get_data_item(data=data, index=index)
         for key in result:
             if isinstance(result[key], np.ndarray):
-                assert np.array_equal(
-                    result[key], expected_result[key]
-                ), f"Mismatch in arrays for key {key}"
+                assert np.array_equal(result[key], expected_result[key]), (
+                    f"Mismatch in arrays for key {key}"
+                )
             else:
-                assert (
-                    result[key] == expected_result[key]
-                ), f"Mismatch in non-array data for key {key}"
+                assert result[key] == expected_result[key], (
+                    f"Mismatch in non-array data for key {key}"
+                )
 
 
 @pytest.mark.parametrize(
@@ -1405,6 +1406,57 @@ def test_xyxy_to_xywh(xyxy: np.ndarray, expected_result: np.ndarray) -> None:
     np.testing.assert_array_equal(result, expected_result)
 
 
+@pytest.mark.parametrize(
+    "xyxy, expected_result",
+    [
+        # Empty and zero cases
+        (np.array([]).reshape(0, 4), np.array([]).reshape(0, 4)),  # empty array
+        (
+            np.array([[0, 0, 0, 0]]),
+            np.array([[0, 0, 0.0, 0]]),
+        ),  # zero size bounding box
+        (
+            np.array([[10, 10, 10, 10]]),
+            np.array([[10, 10, 0.0, 0]]),
+        ),  # point (x1=x2, y1=y2)
+        # Zero width/height cases
+        (np.array([[50, 50, 80, 50]]), np.array([[65, 50, 0.0, 0]])),  # zero height
+        (np.array([[50, 50, 50, 80]]), np.array([[50, 65, 0.0, 30]])),  # zero width
+        # Standard cases
+        (np.array([[10, 20, 40, 60]]), np.array([[25, 40, 0.75, 40]])),  # standard case
+        (
+            np.array([[-30, -40, -10, -20]]),
+            np.array([[-20, -30, 1.0, 20]]),
+        ),  # all negative values
+        (
+            np.array([[0.1, 0.2, 0.4, 0.6]]),
+            np.array([[0.25, 0.4, 0.75, 0.4]]),
+        ),  # values between 0-1
+        # Different aspect ratios
+        (
+            np.array([[10, 20, 50, 100]]),
+            np.array([[30, 60, 0.5, 80]]),
+        ),  # tall rectangle (height > width)
+        (
+            np.array([[20, 10, 100, 50]]),
+            np.array([[60, 30, 2.0, 40]]),
+        ),  # wide rectangle (width > height)
+        (
+            np.array([[50, 50, 150, 150]]),
+            np.array([[100, 100, 1.0, 100]]),
+        ),  # height == width
+        # Multiple boxes in one array
+        (
+            np.array([[0, 0, 0, 0], [10, 20, 40, 60]]),
+            np.array([[0, 0, 0.0, 0], [25, 40, 0.75, 40]]),
+        ),  # one zero-sized box and one normal box
+    ],
+)
+def test_xyxy_to_xcycarh(xyxy: np.ndarray, expected_result: np.ndarray) -> None:
+    result = xyxy_to_xcycarh(xyxy)
+    np.testing.assert_allclose(result, expected_result)
+
+
 @pytest.mark.parametrize(
     "xcycwh, expected_result",
     [

test/detection/tools/test_inference_slicer.py

@@ -180,6 +180,6 @@ def test_generate_offset(
     )
 
     # Verify that the generated offsets match the expected offsets
-    assert np.array_equal(
-        offsets, expected_offsets
-    ), f"Expected {expected_offsets}, got {offsets}"
+    assert np.array_equal(offsets, expected_offsets), (
+        f"Expected {expected_offsets}, got {offsets}"
+    )

test/utils/test_conversion.py

@@ -22,15 +22,15 @@ def test_ensure_cv2_image_for_processing_when_pillow_image_submitted(
         param_a: int,
         param_b: str,
     ) -> np.ndarray:
-        assert np.allclose(
-            image, empty_cv2_image
-        ), "Expected conversion to OpenCV image to happen"
-        assert (
-            param_a == param_a_value
-        ), f"Parameter a expected to be {param_a_value} in target function"
-        assert (
-            param_b == param_b_value
-        ), f"Parameter b expected to be {param_b_value} in target function"
+        assert np.allclose(image, empty_cv2_image), (
+            "Expected conversion to OpenCV image to happen"
+        )
+        assert param_a == param_a_value, (
+            f"Parameter a expected to be {param_a_value} in target function"
+        )
+        assert param_b == param_b_value, (
+            f"Parameter b expected to be {param_b_value} in target function"
+        )
         return image
 
     # when
@@ -61,15 +61,15 @@ def test_ensure_cv2_image_for_processing_when_cv2_image_submitted(
         param_a: int,
         param_b: str,
     ) -> np.ndarray:
-        assert np.allclose(
-            image, empty_cv2_image
-        ), "Expected conversion to OpenCV image to happen"
-        assert (
-            param_a == param_a_value
-        ), f"Parameter a expected to be {param_a_value} in target function"
-        assert (
-            param_b == param_b_value
-        ), f"Parameter b expected to be {param_b_value} in target function"
+        assert np.allclose(image, empty_cv2_image), (
+            "Expected conversion to OpenCV image to happen"
+        )
+        assert param_a == param_a_value, (
+            f"Parameter a expected to be {param_a_value} in target function"
+        )
+        assert param_b == param_b_value, (
+            f"Parameter b expected to be {param_b_value} in target function"
+        )
         return image
 
     # when
@@ -91,9 +91,9 @@ def test_cv2_to_pillow(
 
     # then
     difference = ImageChops.difference(result, empty_pillow_image)
-    assert (
-        difference.getbbox() is None
-    ), "Conversion to PIL.Image expected not to change the content of image"
+    assert difference.getbbox() is None, (
+        "Conversion to PIL.Image expected not to change the content of image"
+    )
 
 
 def test_pillow_to_cv2(
@@ -103,9 +103,9 @@ def test_pillow_to_cv2(
     result = pillow_to_cv2(image=empty_pillow_image)
 
     # then
-    assert np.allclose(
-        result, empty_cv2_image
-    ), "Conversion to OpenCV image expected not to change the content of image"
+    assert np.allclose(result, empty_cv2_image), (
+        "Conversion to OpenCV image expected not to change the content of image"
+    )
 
 
 def test_images_to_cv2_when_empty_input_provided() -> None:
@@ -128,9 +128,9 @@ def test_images_to_cv2_when_only_cv2_images_provided(
     # then
     assert len(result) == 5, "Expected the same number of output element as input ones"
     for result_element in result:
-        assert (
-            result_element is empty_cv2_image
-        ), "Expected CV images not to be touched by conversion"
+        assert result_element is empty_cv2_image, (
+            "Expected CV images not to be touched by conversion"
+        )
 
 
 def test_images_to_cv2_when_only_pillow_images_provided(
@@ -146,9 +146,9 @@ def test_images_to_cv2_when_only_pillow_images_provided(
     # then
     assert len(result) == 5, "Expected the same number of output element as input ones"
     for result_element in result:
-        assert np.allclose(
-            result_element, empty_cv2_image
-        ), "Output images expected to be equal to empty OpenCV image"
+        assert np.allclose(result_element, empty_cv2_image), (
+            "Output images expected to be equal to empty OpenCV image"
+        )
 
 
 def test_images_to_cv2_when_mixed_input_provided(
@@ -163,9 +163,9 @@ def test_images_to_cv2_when_mixed_input_provided(
 
     # then
     assert len(result) == 2, "Expected the same number of output element as input ones"
-    assert np.allclose(
-        result[0], empty_cv2_image
-    ), "PIL image should be converted to OpenCV one, equal to example empty image"
-    assert (
-        result[1] is empty_cv2_image
-    ), "Expected CV images not to be touched by conversion"
+    assert np.allclose(result[0], empty_cv2_image), (
+        "PIL image should be converted to OpenCV one, equal to example empty image"
+    )
+    assert result[1] is empty_cv2_image, (
+        "Expected CV images not to be touched by conversion"
+    )

test/utils/test_image.py

@@ -21,9 +21,9 @@ def test_resize_image_for_opencv_image() -> None:
     )
 
     # then
-    assert np.allclose(
-        result, expected_result
-    ), "Expected output shape to be (w, h): (1024, 768)"
+    assert np.allclose(result, expected_result), (
+        "Expected output shape to be (w, h): (1024, 768)"
+    )
 
 
 def test_resize_image_for_pillow_image() -> None:
@@ -41,9 +41,9 @@ def test_resize_image_for_pillow_image() -> None:
     # then
     assert result.size == (1024, 768), "Expected output shape to be (w, h): (1024, 768)"
     difference = ImageChops.difference(result, expected_result)
-    assert (
-        difference.getbbox() is None
-    ), "Expected no difference in resized image content as the image is all zeros"
+    assert difference.getbbox() is None, (
+        "Expected no difference in resized image content as the image is all zeros"
+    )
 
 
 def test_letterbox_image_for_opencv_image() -> None:
@@ -95,9 +95,9 @@ def test_letterbox_image_for_pillow_image() -> None:
         1024,
     ), "Expected output shape to be (w, h): (1024, 1024)"
     difference = ImageChops.difference(result, expected_result)
-    assert (
-        difference.getbbox() is None
-    ), "Expected padding to be added top and bottom with padding added top and bottom"
+    assert difference.getbbox() is None, (
+        "Expected padding to be added top and bottom with padding added top and bottom"
+    )
 
 
 def test_create_tiles_with_one_image(

uv.lock

@@ -1,4 +1,5 @@
 version = 1
+revision = 1
 requires-python = ">=3.8"
 resolution-markers = [
     "python_full_version >= '3.12' and sys_platform == 'darwin'",
@@ -4828,7 +4829,7 @@ wheels = [
 
 [[package]]
 name = "supervision"
-version = "0.26.0rc3"
+version = "0.26.0rc4"
 source = { editable = "." }
 dependencies = [
     { name = "defusedxml" },
@@ -4894,7 +4895,7 @@ requires-dist = [
     { name = "mkdocs-git-revision-date-localized-plugin", marker = "extra == 'docs'", specifier = ">=1.2.4" },
     { name = "mkdocs-jupyter", marker = "extra == 'docs'", specifier = ">=0.24.3" },
     { name = "mkdocs-material", extras = ["imaging"], marker = "extra == 'docs'", specifier = ">=9.5.5" },
-    { name = "mkdocstrings", marker = "extra == 'docs'", specifier = ">=0.25.2,<0.27.0" },
+    { name = "mkdocstrings", marker = "extra == 'docs'", specifier = ">=0.25.2,<0.29.0" },
     { name = "mkdocstrings-python", marker = "extra == 'docs'", specifier = ">=1.10.9" },
     { name = "nbconvert", marker = "extra == 'dev'", specifier = ">=7.14.2" },
     { name = "notebook", marker = "extra == 'dev'", specifier = ">=6.5.3,<8.0.0" },
@@ -4911,6 +4912,7 @@ requires-dist = [
     { name = "twine", marker = "extra == 'build'", specifier = ">=5.1.1,<7.0.0" },
     { name = "wheel", marker = "extra == 'build'", specifier = ">=0.40,<0.46" },
 ]
+provides-extras = ["metrics", "dev", "docs", "build"]
 
 [[package]]
 name = "terminado"