Merge remote-tracking branch 'origin/develop' into develop

# Conflicts:
#	supervision/annotators/core.py

.github/workflows/test-min.yml

@@ -45,7 +45,7 @@ jobs:
               python-dateutil==2.8.2 \
               PyYAML==5.3 \
               requests==2.26.0 \
-              scipy==1.9.0 \
+              scipy==1.10.0 \
               setuptools-scm==8.0.4 \
               six==1.16.0 \
               tomli==2.0.1 \

.gitignore

@@ -135,3 +135,24 @@ dmypy.json
 
 # Notebooks
 notebooks/
+
+# OSX folder attributes
+.DS_Store
+.AppleDouble
+.LSOverride
+
+# Thumbnails
+._*
+
+# Files that might appear on external disk
+.Spotlight-V100
+.Trashes
+
+# Windows
+Thumbs.db
+Desktop.ini
+
+# Linux
+*~
+.directory
+.Trash-*

.pre-commit-config.yaml

@@ -46,7 +46,7 @@ repos:
 
 
   -   repo: https://github.com/astral-sh/ruff-pre-commit
-      rev: v0.1.13
+      rev: v0.1.14
       hooks:
       -   id: ruff
           args: [--fix, --exit-non-zero-on-fix]

README.md

@@ -237,7 +237,7 @@ https://user-images.githubusercontent.com/26109316/207858600-ee862b22-0353-440b-
 
 https://github.com/roboflow/supervision/assets/26109316/c9436828-9fbf-4c25-ae8c-60e9c81b3900
 
-https://github.com/roboflow/supervision/assets/26109316/f84db7b5-79e2-4142-a1da-64daa43ce667
+https://github.com/roboflow/supervision/assets/26109316/3ac6982f-4943-4108-9b7f-51787ef1a69f
 
 ## 📚 documentation
 

docs/annotators.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 === "BoundingBox"
 
     ```python
@@ -120,7 +124,7 @@
 
     <div class="result" markdown>
 
-    ![circle-annotator-example](https://media.roboflow.com/supervision-annotator-examples/dot-annotator-example-purple.png){ align=center width="800" }
+    ![dot-annotator-example](https://media.roboflow.com/supervision-annotator-examples/dot-annotator-example-purple.png){ align=center width="800" }
 
     </div>
 
@@ -183,7 +187,28 @@
 
     <div class="result" markdown>
 
-    ![ellipse-annotator-example](https://media.roboflow.com/supervision-annotator-examples/halo-annotator-example-purple.png){ align=center width="800" }
+    ![halo-annotator-example](https://media.roboflow.com/supervision-annotator-examples/halo-annotator-example-purple.png){ align=center width="800" }
+
+    </div>
+
+=== "PercentageBar"
+
+    ```python
+    >>> import supervision as sv
+
+    >>> image = ...
+    >>> detections = sv.Detections(...)
+
+    >>> percentage_bar_annotator = sv.PercentageBarAnnotator()
+    >>> annotated_frame = percentage_bar_annotator.annotate(
+    ...     scene=image.copy(),
+    ...     detections=detections
+    ... )
+    ```
+
+    <div class="result" markdown>
+
+    ![percentage-bar-annotator-example](https://media.roboflow.com/supervision-annotator-examples/percentage-bar-annotator-example-purple.png){ align=center width="800" }
 
     </div>
 
@@ -348,7 +373,7 @@
 
     <div class="result" markdown>
 
-    ![trace-annotator-example](https://media.roboflow.com/supervision-annotator-examples/heat-map-annotator-example-purple.png){ align=center width="800" }
+    ![heat-map-annotator-example](https://media.roboflow.com/supervision-annotator-examples/heat-map-annotator-example-purple.png){ align=center width="800" }
 
     </div>
 
@@ -356,6 +381,10 @@
 
 :::supervision.annotators.core.BoundingBoxAnnotator
 
+## RoundBoxAnnotator
+
+:::supervision.annotators.core.RoundBoxAnnotator
+
 ## BoxCornerAnnotator
 
 :::supervision.annotators.core.BoxCornerAnnotator
@@ -384,6 +413,10 @@
 
 :::supervision.annotators.core.HaloAnnotator
 
+## PercentageBarAnnotator
+
+:::supervision.annotators.core.PercentageBarAnnotator
+
 ## HeatMapAnnotator
 
 :::supervision.annotators.core.HeatMapAnnotator
@@ -412,10 +445,6 @@
 
 :::supervision.annotators.core.TraceAnnotator
 
-## RoundBoxAnnotator
-
-:::supervision.annotators.core.RoundBoxAnnotator
-
 ## ColorLookup
 
 :::supervision.annotators.utils.ColorLookup

docs/assets.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 Supervision offers an assets download utility that allows you to download video files
 that you can use in your demos.
 

docs/classification/core.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 ## Classifications
 
 :::supervision.classification.core.Classifications

docs/datasets.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 !!! warning
 
     Dataset API is still fluid and may change. If you use Dataset API in your project until further notice, freeze the

docs/detection/core.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 ## Detections
 
 :::supervision.detection.core.Detections

docs/detection/tools/inference_slicer.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 ## InferenceSlicer
 
 :::supervision.detection.tools.inference_slicer.InferenceSlicer

docs/detection/tools/line_zone.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 ## LineZone
 
 :::supervision.detection.line_counter.LineZone

docs/detection/tools/polygon_zone.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 ## PolygonZone
 
 :::supervision.detection.tools.polygon_zone.PolygonZone

docs/detection/utils.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 ## box_iou_batch
 
 :::supervision.detection.utils.box_iou_batch

docs/draw/color.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 ## Color
 
 :::supervision.draw.color.Color

docs/draw/utils.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 ## draw_line
 
 :::supervision.draw.utils.draw_line

docs/geometry/core.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 ## Position
 
 :::supervision.geometry.core.Position

docs/how_to/detect_and_annotate.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 Supervision offers a streamlined solution to effortlessly annotate predictions from a
 range of object detection and segmentation models. This guide demonstrates how to
 execute inference using the YOLOv8 model with either the

docs/how_to/evaluate_model.md

@@ -1 +1,5 @@
+---
+comments: true
+---
+
 🚧 Page under construction.

docs/how_to/filter_detections.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 The advanced filtering capabilities of the `Detections` class offer users a versatile and efficient way to narrow down
 and refine object detections. This section outlines various filtering methods, including filtering by specific class
 or a set of classes, confidence, object area, bounding box area, relative area, box dimensions, and designated zones.

docs/how_to/process_video.md

@@ -1 +1,5 @@
+---
+comments: true
+---
+
 🚧 Page under construction.

docs/how_to/track_objects.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 Leverage Supervision's advanced capabilities for enhancing your video analysis by
 seamlessly [tracking](https://supervision.roboflow.com/trackers/) objects recognized by
 a multitude of object detection and segmentation models. This comprehensive guide will

docs/index.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 <div align="center">
   <p>
     <a align="center" href="" target="_blank">

docs/metrics/detection.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 !!! warning
 
     Evaluation API is still fluid and may change. If you use Evaluation API in your project until further notice, freeze the

docs/theme/partials/comments.html

@@ -0,0 +1,51 @@
+{% if page.meta.comments %}
+<h2 id="__comments">{{ lang.t("meta.comments") }}</h2>
+
+<!-- Insert Giscus code snippet from https://giscus.app/ here -->
+<script src="https://giscus.app/client.js"
+        data-repo="roboflow/supervision"
+        data-repo-id="R_kgDOIhIiww"
+        data-category="Docs"
+        data-category-id="DIC_kwDOIhIiw84Ccet_"
+        data-mapping="pathname"
+        data-strict="0"
+        data-reactions-enabled="1"
+        data-emit-metadata="1"
+        data-input-position="top"
+        data-theme="preferred_color_scheme"
+        data-lang="en"
+        data-loading="lazy"
+        crossorigin="anonymous"
+        async>
+</script>
+
+<!-- Synchronize Giscus theme with palette -->
+<script>
+    var giscus = document.querySelector("script[src*=giscus]")
+
+    /* Set palette on initial load */
+    var palette = __md_get("__palette")
+    if (palette && typeof palette.color === "object") {
+      var theme = palette.color.scheme === "slate" ? "dark" : "light"
+      giscus.setAttribute("data-theme", theme)
+    }
+
+    /* Register event handlers after documented loaded */
+    document.addEventListener("DOMContentLoaded", function() {
+      var ref = document.querySelector("[data-md-component=palette]")
+      ref.addEventListener("change", function() {
+        var palette = __md_get("__palette")
+        if (palette && typeof palette.color === "object") {
+          var theme = palette.color.scheme === "slate" ? "dark" : "light"
+
+          /* Instruct Giscus to change theme */
+          var frame = document.querySelector(".giscus-frame")
+          frame.contentWindow.postMessage(
+            { giscus: { setConfig: { theme } } },
+            "https://giscus.app"
+          )
+        }
+      })
+    })
+</script>
+{% endif %}

docs/trackers.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 ## ByteTrack
 
 :::supervision.tracker.byte_tracker.core.ByteTrack

docs/utils/file.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 ## list_files_with_extensions
 
 :::supervision.utils.file.list_files_with_extensions

docs/utils/image.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 ## ImageSink
 
 :::supervision.utils.image.ImageSink

docs/utils/notebook.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 ## plot_image
 
 :::supervision.utils.notebook.plot_image

docs/utils/video.md

@@ -1,3 +1,7 @@
+---
+comments: true
+---
+
 ## VideoInfo
 
 :::supervision.utils.video.VideoInfo

examples/count_people_in_zone/.gitignore

@@ -3,3 +3,11 @@ data/*
 
 # But re-include all .json files
 !data/*.json
+
+*.pt
+*.pth
+*.mp4
+*.mov
+*.png
+*.jpg
+*.jpeg

examples/speed_estimation/.gitignore

@@ -1,2 +1,9 @@
 data/
 venv*/
+*.pt
+*.pth
+*.mp4
+*.mov
+*.png
+*.jpg
+*.jpeg

examples/speed_estimation/README.md

@@ -1,18 +1,24 @@
 # speed estimation
 
+[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/roboflow-ai/notebooks/blob/main/notebooks/how-to-estimate-vehicle-speed-with-computer-vision.ipynb)
+[![YouTube](https://badges.aleen42.com/src/youtube.svg)](https://youtu.be/uWP6UjDeZvY)
+
 ## 👋 hello
 
 This example performs speed estimation analysis using various object-detection models
 and ByteTrack - a simple yet effective online multi-object tracking method. It uses the
 supervision package for multiple tasks such as tracking, annotations, etc.
 
-https://github.com/roboflow/supervision/assets/26109316/0542fd3c-bb5f-475e-b96c-793560abeb18
+https://github.com/roboflow/supervision/assets/26109316/d50118c1-2ae4-458d-915a-5d860fd36f71
+
+> [!IMPORTANT]
+> Adjust the [`SOURCE`](https://github.com/roboflow/supervision/blob/e32b05a636dab2ea1f39299e529c4b22b8baa8da/examples/speed_estimation/ultralytics_example.py#L10)
+> and [`TARGET`](https://github.com/roboflow/supervision/blob/e32b05a636dab2ea1f39299e529c4b22b8baa8da/examples/speed_estimation/ultralytics_example.py#L15)
+> configuration if you plan to run a speed estimation script on your video file. Those must be adjusted separately for each camera view. You can learn more
+> from our YouTube [tutorial](https://youtu.be/uWP6UjDeZvY).
 
 ## 💻 install
 
-> [!NOTE]
-> YOLO-NAS is compatible with Python versions up to and including Python 3.10.
-
 - clone repository and navigate to example directory
 
   ```bash

examples/speed_estimation/requirements.txt

@@ -1,6 +1,6 @@
 supervision==0.18.0rc1
-tqdm
+tqdm==4.66.1
 requests
-ultralytics
-super-gradients
-inference
+ultralytics==8.0.237
+super-gradients==3.5.0
+inference==0.9.8

examples/speed_estimation/ultralytics_example.py

@@ -29,6 +29,9 @@ class ViewTransformer:
         self.m = cv2.getPerspectiveTransform(source, target)
 
     def transform_points(self, points: np.ndarray) -> np.ndarray:
+        if points.size == 0:
+            return points
+
         reshaped_points = points.reshape(-1, 1, 2).astype(np.float32)
         transformed_points = cv2.perspectiveTransform(reshaped_points, self.m)
         return transformed_points.reshape(-1, 2)

examples/traffic_analysis/.gitignore

@@ -1,2 +1,9 @@
 data/
 venv/
+*.pt
+*.pth
+*.mp4
+*.mov
+*.png
+*.jpg
+*.jpeg

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "supervision"
-version = "0.18.0rc2"
+version = "0.18.0rc3"
 description = "A set of easy-to-use utils that will come in handy in any Computer Vision project"
 authors = ["Piotr Skalski <piotr.skalski92@gmail.com>"]
 maintainers = ["Piotr Skalski <piotr.skalski92@gmail.com>"]
@@ -33,12 +33,15 @@ classifiers=[
 [tool.poetry.dependencies]
 python = "^3.8"
 numpy = ">=1.21.2"
-scipy =  ">=1.9.0"
+scipy = [
+    { version = "1.10.0", python = "<3.9" },
+    { version = "^1.10.0", python = ">=3.9" }
+]
 matplotlib = ">=3.5.0"
 pyyaml = ">=5.3"
 pillow = ">=9.4"
-opencv-python = { version = ">=4.5.5.64,<=4.8.1.78", optional = true }
-opencv-python-headless = ">=4.5.5.64,<=4.8.1.78"
+opencv-python = { version = ">=4.5.5.64", optional = true }
+opencv-python-headless = ">=4.5.5.64"
 requests = { version = ">=2.26.0,<=2.31.0", optional = true }
 tqdm = { version = ">=4.62.3,<=4.66.1", optional = true }
 defusedxml = "^0.7.1"
@@ -62,7 +65,7 @@ tox = "^4.11.4"
 
 
 [tool.poetry.group.docs.dependencies]
-mkdocs-material = "^9.1.4"
+mkdocs-material = {extras = ["imaging"], version = "^9.5.4"}
 mkdocstrings = {extras = ["python"], version = ">=0.20,<0.25"}
 
 

supervision/__init__.py

@@ -18,6 +18,7 @@ from supervision.annotators.core import (
     HeatMapAnnotator,
     LabelAnnotator,
     MaskAnnotator,
+    PercentageBarAnnotator,
     PixelateAnnotator,
     PolygonAnnotator,
     RoundBoxAnnotator,

supervision/annotators/core.py

@@ -21,7 +21,7 @@ class BoundingBoxAnnotator(BaseAnnotator):
 
     def __init__(
         self,
-        color: Union[Color, ColorPalette] = ColorPalette.default(),
+        color: Union[Color, ColorPalette] = ColorPalette.DEFAULT,
         thickness: int = 2,
         color_lookup: ColorLookup = ColorLookup.CLASS,
     ):
@@ -103,7 +103,7 @@ class MaskAnnotator(BaseAnnotator):
 
     def __init__(
         self,
-        color: Union[Color, ColorPalette] = ColorPalette.default(),
+        color: Union[Color, ColorPalette] = ColorPalette.DEFAULT,
         opacity: float = 0.5,
         color_lookup: ColorLookup = ColorLookup.CLASS,
     ):
@@ -186,7 +186,7 @@ class PolygonAnnotator(BaseAnnotator):
 
     def __init__(
         self,
-        color: Union[Color, ColorPalette] = ColorPalette.default(),
+        color: Union[Color, ColorPalette] = ColorPalette.DEFAULT,
         thickness: int = 2,
         color_lookup: ColorLookup = ColorLookup.CLASS,
     ):
@@ -268,7 +268,7 @@ class ColorAnnotator(BaseAnnotator):
 
     def __init__(
         self,
-        color: Union[Color, ColorPalette] = ColorPalette.default(),
+        color: Union[Color, ColorPalette] = ColorPalette.DEFAULT,
         opacity: float = 0.5,
         color_lookup: ColorLookup = ColorLookup.CLASS,
     ):
@@ -354,7 +354,7 @@ class HaloAnnotator(BaseAnnotator):
 
     def __init__(
         self,
-        color: Union[Color, ColorPalette] = ColorPalette.default(),
+        color: Union[Color, ColorPalette] = ColorPalette.DEFAULT,
         opacity: float = 0.8,
         kernel_size: int = 40,
         color_lookup: ColorLookup = ColorLookup.CLASS,
@@ -446,7 +446,7 @@ class EllipseAnnotator(BaseAnnotator):
 
     def __init__(
         self,
-        color: Union[Color, ColorPalette] = ColorPalette.default(),
+        color: Union[Color, ColorPalette] = ColorPalette.DEFAULT,
         thickness: int = 2,
         start_angle: int = -45,
         end_angle: int = 235,
@@ -536,7 +536,7 @@ class BoxCornerAnnotator(BaseAnnotator):
 
     def __init__(
         self,
-        color: Union[Color, ColorPalette] = ColorPalette.default(),
+        color: Union[Color, ColorPalette] = ColorPalette.DEFAULT,
         thickness: int = 4,
         corner_length: int = 15,
         color_lookup: ColorLookup = ColorLookup.CLASS,
@@ -622,7 +622,7 @@ class CircleAnnotator(BaseAnnotator):
 
     def __init__(
         self,
-        color: Union[Color, ColorPalette] = ColorPalette.default(),
+        color: Union[Color, ColorPalette] = ColorPalette.DEFAULT,
         thickness: int = 2,
         color_lookup: ColorLookup = ColorLookup.CLASS,
     ):
@@ -706,7 +706,7 @@ class DotAnnotator(BaseAnnotator):
 
     def __init__(
         self,
-        color: Union[Color, ColorPalette] = ColorPalette.default(),
+        color: Union[Color, ColorPalette] = ColorPalette.DEFAULT,
         radius: int = 4,
         position: Position = Position.CENTER,
         color_lookup: ColorLookup = ColorLookup.CLASS,
@@ -782,8 +782,8 @@ class LabelAnnotator:
 
     def __init__(
         self,
-        color: Union[Color, ColorPalette] = ColorPalette.default(),
-        text_color: Color = Color.black(),
+        color: Union[Color, ColorPalette] = ColorPalette.DEFAULT,
+        text_color: Color = Color.WHITE,
         text_scale: float = 0.5,
         text_thickness: int = 1,
         text_padding: int = 10,
@@ -1027,7 +1027,7 @@ class TraceAnnotator:
 
     def __init__(
         self,
-        color: Union[Color, ColorPalette] = ColorPalette.default(),
+        color: Union[Color, ColorPalette] = ColorPalette.DEFAULT,
         position: Position = Position.CENTER,
         trace_length: int = 30,
         thickness: int = 2,
@@ -1288,7 +1288,7 @@ class TriangleAnnotator(BaseAnnotator):
 
     def __init__(
         self,
-        color: Union[Color, ColorPalette] = ColorPalette.default(),
+        color: Union[Color, ColorPalette] = ColorPalette.DEFAULT,
         base: int = 10,
         height: int = 10,
         position: Position = Position.TOP_CENTER,
@@ -1378,7 +1378,7 @@ class RoundBoxAnnotator(BaseAnnotator):
 
     def __init__(
         self,
-        color: Union[Color, ColorPalette] = ColorPalette.default(),
+        color: Union[Color, ColorPalette] = ColorPalette.DEFAULT,
         thickness: int = 2,
         color_lookup: ColorLookup = ColorLookup.CLASS,
         roundness: float = 0.6,
@@ -1436,7 +1436,7 @@ class RoundBoxAnnotator(BaseAnnotator):
             ```
 
         ![round-box-annotator-example](https://media.roboflow.com/
-        supervision-annotator-examples/round-box-annotator-example.png)
+        supervision-annotator-examples/round-box-annotator-example-purple.png)
         """
 
         for detection_idx in range(len(detections)):
@@ -1496,3 +1496,177 @@ class RoundBoxAnnotator(BaseAnnotator):
                 )
 
         return scene
+
+
+class PercentageBarAnnotator(BaseAnnotator):
+    """
+    A class for drawing percentage bars on an image using provided detections.
+    """
+
+    def __init__(
+        self,
+        height: int = 16,
+        width: int = 80,
+        color: Union[Color, ColorPalette] = ColorPalette.DEFAULT,
+        border_color: Color = Color.BLACK,
+        position: Position = Position.TOP_CENTER,
+        color_lookup: ColorLookup = ColorLookup.CLASS,
+        border_thickness: int = None,
+    ):
+        """
+        Args:
+            height (int): The height in pixels of the percentage bar.
+            width (int): The width in pixels of the percentage bar.
+            color (Union[Color, ColorPalette]): The color or color palette to use for
+                annotating detections.
+            border_color (Color): The color of the border lines.
+            position (Position): The anchor position of drawing the percentage bar.
+            color_lookup (str): Strategy for mapping colors to annotations.
+                Options are `INDEX`, `CLASS`, `TRACK`.
+            border_thickness (int): The thickness of the border lines.
+        """
+        self.height: int = height
+        self.width: int = width
+        self.color: Union[Color, ColorPalette] = color
+        self.border_color: Color = border_color
+        self.position: Position = position
+        self.color_lookup: ColorLookup = color_lookup
+
+        if border_thickness is None:
+            self.border_thickness = int(0.15 * self.height)
+
+    def annotate(
+        self,
+        scene: np.ndarray,
+        detections: Detections,
+        custom_color_lookup: Optional[np.ndarray] = None,
+        custom_values: Optional[np.ndarray] = None,
+    ) -> np.ndarray:
+        """
+        Annotates the given scene with percentage bars based on the provided
+        detections. The percentage bars visually represent the confidence or custom
+        values associated with each detection.
+
+        Args:
+            scene (np.ndarray): The image where percentage bars will be drawn.
+            detections (Detections): Object detections to annotate.
+            custom_color_lookup (Optional[np.ndarray]): Custom color lookup array.
+                Allows to override the default color mapping strategy.
+            custom_values (Optional[np.ndarray]): Custom values array to use instead
+                of the default detection confidences. This array should have the
+                same length as the number of detections and contain a value between
+                0 and 1 (inclusive) for each detection, representing the percentage
+                to be displayed.
+
+        Returns:
+            The annotated image.
+
+        Example:
+            ```python
+            >>> import supervision as sv
+
+            >>> image = ...
+            >>> detections = sv.Detections(...)
+
+            >>> percentage_bar_annotator = sv.BoundingBoxAnnotator()
+            >>> annotated_frame = percentage_bar_annotator.annotate(
+            ...     scene=image.copy(),
+            ...     detections=detections
+            ... )
+            ```
+
+        ![percentage-bar-example](https://media.roboflow.com/
+        supervision-annotator-examples/percentage-bar-annotator-example-purple.png)
+        """
+        self.validate_custom_values(
+            custom_values=custom_values, detections_count=len(detections)
+        )
+        anchors = detections.get_anchors_coordinates(anchor=self.position)
+        for detection_idx in range(len(detections)):
+            anchor = anchors[detection_idx]
+            border_coordinates = self.calculate_border_coordinates(
+                anchor_xy=(int(anchor[0]), int(anchor[1])),
+                border_wh=(self.width, self.height),
+                position=self.position,
+            )
+            border_width = border_coordinates[1][0] - border_coordinates[0][0]
+
+            value = (
+                custom_values[detection_idx]
+                if custom_values is not None
+                else detections.confidence[detection_idx]
+            )
+
+            color = resolve_color(
+                color=self.color,
+                detections=detections,
+                detection_idx=detection_idx,
+                color_lookup=self.color_lookup
+                if custom_color_lookup is None
+                else custom_color_lookup,
+            )
+            cv2.rectangle(
+                img=scene,
+                pt1=border_coordinates[0],
+                pt2=(
+                    border_coordinates[0][0] + int(border_width * value),
+                    border_coordinates[1][1],
+                ),
+                color=color.as_bgr(),
+                thickness=-1,
+            )
+            cv2.rectangle(
+                img=scene,
+                pt1=border_coordinates[0],
+                pt2=border_coordinates[1],
+                color=self.border_color.as_bgr(),
+                thickness=self.border_thickness,
+            )
+        return scene
+
+    @staticmethod
+    def calculate_border_coordinates(
+        anchor_xy: Tuple[int, int], border_wh: Tuple[int, int], position: Position
+    ) -> Tuple[Tuple[int, int], Tuple[int, int]]:
+        cx, cy = anchor_xy
+        width, height = border_wh
+
+        if position == Position.TOP_LEFT:
+            return (cx - width, cy - height), (cx, cy)
+        elif position == Position.TOP_CENTER:
+            return (cx - width // 2, cy), (cx + width // 2, cy - height)
+        elif position == Position.TOP_RIGHT:
+            return (cx, cy), (cx + width, cy - height)
+        elif position == Position.CENTER_LEFT:
+            return (cx - width, cy - height // 2), (cx, cy + height // 2)
+        elif position == Position.CENTER or position == Position.CENTER_OF_MASS:
+            return (
+                (cx - width // 2, cy - height // 2),
+                (cx + width // 2, cy + height // 2),
+            )
+        elif position == Position.CENTER_RIGHT:
+            return (cx, cy - height // 2), (cx + width, cy + height // 2)
+        elif position == Position.BOTTOM_LEFT:
+            return (cx - width, cy), (cx, cy + height)
+        elif position == Position.BOTTOM_CENTER:
+            return (cx - width // 2, cy), (cx + width // 2, cy + height)
+        elif position == Position.BOTTOM_RIGHT:
+            return (cx, cy), (cx + width, cy + height)
+
+    @staticmethod
+    def validate_custom_values(
+        custom_values: Optional[Union[np.ndarray, List[float]]], detections_count: int
+    ) -> None:
+        if custom_values is not None:
+            if not isinstance(custom_values, (np.ndarray, list)):
+                raise TypeError(
+                    "custom_values must be either a numpy array or a list of floats."
+                )
+
+            if len(custom_values) != detections_count:
+                raise ValueError(
+                    "The length of custom_values must match the number of detections."
+                )
+
+            if not all(0 <= value <= 1 for value in custom_values):
+                raise ValueError("All values in custom_values must be between 0 and 1.")

supervision/detection/annotate.py

@@ -26,9 +26,9 @@ class BoxAnnotator:
 
     def __init__(
         self,
-        color: Union[Color, ColorPalette] = ColorPalette.default(),
+        color: Union[Color, ColorPalette] = ColorPalette.DEFAULT,
         thickness: int = 2,
-        text_color: Color = Color.black(),
+        text_color: Color = Color.BLACK,
         text_scale: float = 0.5,
         text_thickness: int = 1,
         text_padding: int = 10,

supervision/detection/line_counter.py

@@ -1,11 +1,11 @@
-from typing import Dict, Optional, Tuple
+from typing import Dict, Iterable, Optional, Tuple
 
 import cv2
 import numpy as np
 
 from supervision.detection.core import Detections
 from supervision.draw.color import Color
-from supervision.geometry.core import Point, Rect, Vector
+from supervision.geometry.core import Point, Position, Rect, Vector
 
 
 class LineZone:
@@ -26,16 +26,71 @@ class LineZone:
             to outside.
     """
 
-    def __init__(self, start: Point, end: Point):
+    def __init__(
+        self,
+        start: Point,
+        end: Point,
+        triggering_anchors: Iterable[Position] = (
+            Position.TOP_LEFT,
+            Position.TOP_RIGHT,
+            Position.BOTTOM_LEFT,
+            Position.BOTTOM_RIGHT,
+        ),
+    ):
         """
         Args:
             start (Point): The starting point of the line.
             end (Point): The ending point of the line.
+            triggering_anchors (List[sv.Position]): A list of positions
+                specifying which anchors of the detections bounding box
+                to consider when deciding on whether the detection
+                has passed the line counter or not. By default, this
+                contains the four corners of the detection's bounding box
         """
         self.vector = Vector(start=start, end=end)
+        self.limits = self.calculate_region_of_interest_limits(vector=self.vector)
         self.tracker_state: Dict[str, bool] = {}
         self.in_count: int = 0
         self.out_count: int = 0
+        self.triggering_anchors = triggering_anchors
+
+    @staticmethod
+    def calculate_region_of_interest_limits(vector: Vector) -> Tuple[Vector, Vector]:
+        magnitude = vector.magnitude
+
+        if magnitude == 0:
+            raise ValueError("The magnitude of the vector cannot be zero.")
+
+        delta_x = vector.end.x - vector.start.x
+        delta_y = vector.end.y - vector.start.y
+
+        unit_vector_x = delta_x / magnitude
+        unit_vector_y = delta_y / magnitude
+
+        perpendicular_vector_x = -unit_vector_y
+        perpendicular_vector_y = unit_vector_x
+
+        start_region_limit = Vector(
+            start=vector.start,
+            end=Point(
+                x=vector.start.x + perpendicular_vector_x,
+                y=vector.start.y + perpendicular_vector_y,
+            ),
+        )
+        end_region_limit = Vector(
+            start=vector.end,
+            end=Point(
+                x=vector.end.x - perpendicular_vector_x,
+                y=vector.end.y - perpendicular_vector_y,
+            ),
+        )
+        return start_region_limit, end_region_limit
+
+    @staticmethod
+    def is_point_in_limits(point: Point, limits: Tuple[Vector, Vector]) -> bool:
+        cross_product_1 = limits[0].cross_product(point)
+        cross_product_2 = limits[1].cross_product(point)
+        return (cross_product_1 > 0) == (cross_product_2 > 0)
 
     def trigger(self, detections: Detections) -> Tuple[np.ndarray, np.ndarray]:
         """
@@ -54,20 +109,35 @@ class LineZone:
         crossed_in = np.full(len(detections), False)
         crossed_out = np.full(len(detections), False)
 
-        for i, (xyxy, tracker_id) in enumerate(
-            zip(detections.xyxy, detections.tracker_id)
-        ):
+        if len(detections) == 0:
+            return crossed_in, crossed_out
+
+        all_anchors = np.array(
+            [
+                detections.get_anchors_coordinates(anchor)
+                for anchor in self.triggering_anchors
+            ]
+        )
+
+        for i, tracker_id in enumerate(detections.tracker_id):
             if tracker_id is None:
                 continue
 
-            x1, y1, x2, y2 = xyxy
-            anchors = [
-                Point(x=x1, y=y1),
-                Point(x=x1, y=y2),
-                Point(x=x2, y=y1),
-                Point(x=x2, y=y2),
+            box_anchors = [Point(x=x, y=y) for x, y in all_anchors[:, i, :]]
+
+            in_limits = all(
+                [
+                    self.is_point_in_limits(point=anchor, limits=self.limits)
+                    for anchor in box_anchors
+                ]
+            )
+
+            if not in_limits:
+                continue
+
+            triggers = [
+                self.vector.cross_product(point=anchor) > 0 for anchor in box_anchors
             ]
-            triggers = [self.vector.is_in(point=anchor) for anchor in anchors]
 
             if len(set(triggers)) == 2:
                 continue
@@ -96,9 +166,9 @@ class LineZoneAnnotator:
     def __init__(
         self,
         thickness: float = 2,
-        color: Color = Color.white(),
+        color: Color = Color.WHITE,
         text_thickness: float = 2,
-        text_color: Color = Color.black(),
+        text_color: Color = Color.BLACK,
         text_scale: float = 0.5,
         text_offset: float = 1.5,
         text_padding: int = 10,

supervision/detection/tools/polygon_zone.py

@@ -90,7 +90,7 @@ class PolygonZoneAnnotator:
         zone: PolygonZone,
         color: Color,
         thickness: int = 2,
-        text_color: Color = Color.black(),
+        text_color: Color = Color.BLACK,
         text_scale: float = 0.5,
         text_thickness: int = 1,
         text_padding: int = 10,

supervision/draw/color.py

@@ -3,26 +3,56 @@ from __future__ import annotations
 from dataclasses import dataclass
 from typing import List, Tuple
 
+import matplotlib.pyplot as plt
+
+from supervision.utils.internal import classproperty, deprecated
+
 DEFAULT_COLOR_PALETTE = [
-    "#a351fb",
-    "#e6194b",
-    "#3cb44b",
-    "#ffe119",
-    "#0082c8",
-    "#f58231",
-    "#911eb4",
-    "#46f0f0",
-    "#f032e6",
-    "#d2f53c",
-    "#fabebe",
-    "#008080",
-    "#e6beff",
-    "#aa6e28",
-    "#fffac8",
-    "#800000",
-    "#aaffc3",
+    "A351FB",
+    "FF4040",
+    "FFA1A0",
+    "FF7633",
+    "FFB633",
+    "D1D435",
+    "4CFB12",
+    "94CF1A",
+    "40DE8A",
+    "1B9640",
+    "00D6C1",
+    "2E9CAA",
+    "00C4FF",
+    "364797",
+    "6675FF",
+    "0019EF",
+    "863AFF",
+    "530087",
+    "CD3AFF",
+    "FF97CA",
+    "FF39C9",
 ]
 
+LEGACY_COLOR_PALETTE = [
+    "#A351FB",
+    "#E6194B",
+    "#3CB44B",
+    "#FFE119",
+    "#0082C8",
+    "#F58231",
+    "#911EB4",
+    "#46F0F0",
+    "#F032E6",
+    "#D2F53C",
+    "#FABEBE",
+    "#008080",
+    "#E6BEFF",
+    "#AA6E28",
+    "#FFFAC8",
+    "#800000",
+    "#AAFFC3",
+]
+
+ROBOFLOW_COLOR_PALETTE = ["C28DFC", "A351FB", "8315F9", "6706CE", "5905B3", "4D049A"]
+
 
 def _validate_color_hex(color_hex: str):
     color_hex = color_hex.lstrip("#")
@@ -37,10 +67,31 @@ class Color:
     """
     Represents a color in RGB format.
 
+    This class provides methods to work with colors, including creating colors from hex
+    codes, converting colors to hex strings, RGB tuples, and BGR tuples.
+
     Attributes:
-        r (int): Red channel.
-        g (int): Green channel.
-        b (int): Blue channel.
+        r (int): Red channel value (0-255).
+        g (int): Green channel value (0-255).
+        b (int): Blue channel value (0-255).
+
+    Example:
+        ```python
+        import supervision as sv
+
+        sv.Color.WHITE
+        # 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)` |
     """
 
     r: int
@@ -59,9 +110,11 @@ class Color:
             Color: Instance representing the color.
 
         Example:
-            ```
-            >>> Color.from_hex('#ff00ff')
-            Color(r=255, g=0, b=255)
+            ```python
+            import supervision as sv
+
+            sv.Color.from_hex('#ff00ff')
+            # Color(r=255, g=0, b=255)
             ```
         """
         _validate_color_hex(color_hex)
@@ -79,9 +132,11 @@ class Color:
             str: The hexadecimal color string.
 
         Example:
-            ```
-            >>> Color(r=255, g=0, b=255).as_hex()
-            '#ff00ff'
+            ```python
+            import supervision as sv
+
+            sv.Color(r=255, g=255, b=0).as_hex()
+            # '#ffff00'
             ```
         """
         return f"#{self.r:02x}{self.g:02x}{self.b:02x}"
@@ -94,9 +149,11 @@ class Color:
             Tuple[int, int, int]: RGB tuple.
 
         Example:
-            ```
-            >>> color.as_rgb()
-            (255, 0, 255)
+            ```python
+            import supervision as sv
+
+            sv.Color(r=255, g=255, b=0).as_rgb()
+            # (255, 255, 0)
             ```
         """
         return self.r, self.g, self.b
@@ -109,30 +166,80 @@ class Color:
             Tuple[int, int, int]: BGR tuple.
 
         Example:
-            ```
-            >>> color.as_bgr()
-            (255, 0, 255)
+            ```python
+            import supervision as sv
+
+            sv.Color(r=255, g=255, b=0).as_bgr()
+            # (0, 255, 255)
             ```
         """
         return self.b, self.g, self.r
 
+    @classproperty
+    def WHITE(cls):
+        return Color.from_hex("#FFFFFF")
+
+    @classproperty
+    def BLACK(cls):
+        return Color.from_hex("#000000")
+
+    @classproperty
+    def RED(cls):
+        return Color.from_hex("#FF0000")
+
+    @classproperty
+    def GREEN(cls):
+        return Color.from_hex("#00FF00")
+
+    @classproperty
+    def BLUE(cls):
+        return Color.from_hex("#0000FF")
+
+    @classproperty
+    def YELLOW(cls):
+        return Color.from_hex("#FFFF00")
+
+    @classproperty
+    def ROBOFLOW(cls):
+        return Color.from_hex("#A351FB")
+
     @classmethod
+    @deprecated(
+        "`Color.white()` is deprecated and will be removed in "
+        "`supervision-0.20.0`. Use `Color.WHITE` instead."
+    )
     def white(cls) -> Color:
         return Color.from_hex(color_hex="#ffffff")
 
     @classmethod
+    @deprecated(
+        "`Color.black()` is deprecated and will be removed in "
+        "`supervision-0.20.0`. Use `Color.BLACK` instead."
+    )
     def black(cls) -> Color:
         return Color.from_hex(color_hex="#000000")
 
     @classmethod
+    @deprecated(
+        "`Color.red()` is deprecated and will be removed in "
+        "`supervision-0.20.0`. Use `Color.RED` instead."
+    )
     def red(cls) -> Color:
         return Color.from_hex(color_hex="#ff0000")
 
     @classmethod
+    @deprecated(
+        "`Color.green()` is deprecated and will be removed in "
+        "`supervision-0.20.0`. Use `Color.GREEN` instead."
+    )
     def green(cls) -> Color:
         return Color.from_hex(color_hex="#00ff00")
 
     @classmethod
+    @deprecated(
+        "`Color.blue()` is deprecated and will be removed in "
+        "`supervision-0.20.0`. Use `Color.BLUE` instead."
+    )
     def blue(cls) -> Color:
         return Color.from_hex(color_hex="#0000ff")
 
@@ -141,7 +248,57 @@ class Color:
 class ColorPalette:
     colors: List[Color]
 
+    @classproperty
+    def DEFAULT(cls) -> ColorPalette:
+        """
+        Returns a default color palette.
+
+        Returns:
+            ColorPalette: A ColorPalette instance with default colors.
+
+        Example:
+            ```python
+            import supervision as sv
+
+            sv.ColorPalette.DEFAULT
+            # ColorPalette(colors=[Color(r=255, g=64, b=64), Color(r=255, g=161, b=160), ...])
+            ```
+
+        ![default-color-palette](https://media.roboflow.com/
+        supervision-annotator-examples/default-color-palette.png)
+        """  # noqa: E501 // docs
+        return ColorPalette.from_hex(color_hex_list=DEFAULT_COLOR_PALETTE)
+
+    @classproperty
+    def ROBOFLOW(cls) -> ColorPalette:
+        """
+        Returns a Roboflow color palette.
+
+        Returns:
+            ColorPalette: A ColorPalette instance with Roboflow colors.
+
+        Example:
+            ```python
+            import supervision as sv
+
+            sv.ColorPalette.ROBOFLOW
+            # ColorPalette(colors=[Color(r=194, g=141, b=252), Color(r=163, g=81, b=251), ...])
+            ```
+
+        ![roboflow-color-palette](https://media.roboflow.com/
+        supervision-annotator-examples/roboflow-color-palette.png)
+        """  # noqa: E501 // docs
+        return ColorPalette.from_hex(color_hex_list=ROBOFLOW_COLOR_PALETTE)
+
+    @classproperty
+    def LEGACY(cls) -> ColorPalette:
+        return ColorPalette.from_hex(color_hex_list=LEGACY_COLOR_PALETTE)
+
     @classmethod
+    @deprecated(
+        "`ColorPalette.default()` is deprecated and will be removed in "
+        "`supervision-0.20.0`. Use `Color.DEFAULT` instead."
+    )
     def default(cls) -> ColorPalette:
         """
         Returns a default color palette.
@@ -150,11 +307,13 @@ class ColorPalette:
             ColorPalette: A ColorPalette instance with default colors.
 
         Example:
+            ```python
+            import supervision as sv
+
+            sv.ColorPalette.default()
+            # ColorPalette(colors=[Color(r=255, g=64, b=64), Color(r=255, g=161, b=160), ...])
             ```
-            >>> ColorPalette.default()
-            ColorPalette(colors=[Color(r=255, g=0, b=0), Color(r=0, g=255, b=0), ...])
-            ```
-        """
+        """  # noqa: E501 // docs
         return ColorPalette.from_hex(color_hex_list=DEFAULT_COLOR_PALETTE)
 
     @classmethod
@@ -169,14 +328,46 @@ class ColorPalette:
             ColorPalette: A ColorPalette instance.
 
         Example:
-            ```
-            >>> ColorPalette.from_hex(['#ff0000', '#00ff00', '#0000ff'])
-            ColorPalette(colors=[Color(r=255, g=0, b=0), Color(r=0, g=255, b=0), ...])
+            ```python
+            import supervision as sv
+
+            sv.ColorPalette.from_hex(['#ff0000', '#00ff00', '#0000ff'])
+            # ColorPalette(colors=[Color(r=255, g=0, b=0), Color(r=0, g=255, b=0), ...])
             ```
         """
         colors = [Color.from_hex(color_hex) for color_hex in color_hex_list]
         return cls(colors)
 
+    @classmethod
+    def from_matplotlib(cls, palette_name: str, color_count: int) -> ColorPalette:
+        """
+        Create a ColorPalette instance from a Matplotlib color palette.
+
+        Args:
+            palette_name (str): Name of the Matplotlib palette.
+            color_count (int): Number of colors to sample from the palette.
+
+        Returns:
+            ColorPalette: A ColorPalette instance.
+
+        Example:
+            ```python
+            import supervision as sv
+
+            sv.ColorPalette.from_matplotlib('viridis', 5)
+            # ColorPalette(colors=[Color(r=68, g=1, b=84), Color(r=59, g=82, b=139), ...])
+            ```
+
+        ![visualized_color_palette](https://media.roboflow.com/
+        supervision-annotator-examples/visualized_color_palette.png)
+        """  # noqa: E501 // docs
+        mpl_palette = plt.get_cmap(palette_name, color_count)
+        colors = [
+            Color(int(r * 255), int(g * 255), int(b * 255))
+            for r, g, b, _ in mpl_palette.colors
+        ]
+        return cls(colors)
+
     def by_idx(self, idx: int) -> Color:
         """
         Return the color at a given index in the palette.
@@ -188,9 +379,12 @@ class ColorPalette:
             Color: Color at the given index.
 
         Example:
-            ```
-            >>> color_palette.by_idx(1)
-            Color(r=0, g=255, b=0)
+            ```python
+            import supervision as sv
+
+            color_palette = sv.ColorPalette.from_hex(['#ff0000', '#00ff00', '#0000ff'])
+            color_palette.by_idx(1)
+            # Color(r=0, g=255, b=0)
             ```
         """
         if idx < 0:

supervision/draw/utils.py

@@ -105,7 +105,7 @@ def draw_text(
     scene: np.ndarray,
     text: str,
     text_anchor: Point,
-    text_color: Color = Color.black(),
+    text_color: Color = Color.BLACK,
     text_scale: float = 0.5,
     text_thickness: int = 1,
     text_padding: int = 10,

supervision/geometry/core.py

@@ -2,6 +2,7 @@ from __future__ import annotations
 
 from dataclasses import dataclass
 from enum import Enum
+from math import sqrt
 from typing import Tuple
 
 
@@ -43,13 +44,38 @@ class Vector:
     start: Point
     end: Point
 
-    def is_in(self, point: Point) -> bool:
-        v1 = Vector(self.start, self.end)
-        v2 = Vector(self.start, point)
-        cross_product = (v1.end.x - v1.start.x) * (v2.end.y - v2.start.y) - (
-            v1.end.y - v1.start.y
-        ) * (v2.end.x - v2.start.x)
-        return cross_product < 0
+    @property
+    def magnitude(self) -> float:
+        """
+        Calculate the magnitude (length) of the vector.
+
+        Returns:
+            float: The magnitude of the vector.
+        """
+        dx = self.end.x - self.start.x
+        dy = self.end.y - self.start.y
+        return sqrt(dx**2 + dy**2)
+
+    def cross_product(self, point: Point) -> float:
+        """
+        Calculate the 2D cross product (also known as the vector product or outer
+        product) of the vector and a point, treated as vectors in 2D space.
+
+        Args:
+            point (Point): The point to be evaluated, treated as the endpoint of a
+                vector originating from the 'start' of the main vector.
+
+        Returns:
+            float: The scalar value of the cross product. It is positive if 'point'
+                lies to the left of the vector (when moving from 'start' to 'end'),
+                negative if it lies to the right, and 0 if it is collinear with the
+                vector.
+        """
+        dx_vector = self.end.x - self.start.x
+        dy_vector = self.end.y - self.start.y
+        dx_point = point.x - self.start.x
+        dy_point = point.y - self.start.y
+        return (dx_vector * dy_point) - (dy_vector * dx_point)
 
 
 @dataclass

supervision/utils/internal.py

@@ -16,3 +16,29 @@ def deprecated(reason: str):
         return wrapper
 
     return decorator
+
+
+class classproperty(property):
+    """
+    A decorator that combines @classmethod and @property.
+    It allows a method to be accessed as a property of the class,
+    rather than an instance, similar to a classmethod.
+
+    Usage:
+        @classproperty
+        def my_method(cls):
+            ...
+    """
+
+    def __get__(self, owner_self: object, owner_cls: type) -> object:
+        """
+        Override the __get__ method to return the result of the function call.
+
+        Args:
+        owner_self: The instance through which the attribute was accessed, or None.
+        owner_cls: The class through which the attribute was accessed.
+
+        Returns:
+        The result of calling the function stored in 'fget' with 'owner_cls'.
+        """
+        return self.fget(owner_cls)

test/detection/test_line_counter.py

@@ -0,0 +1,72 @@
+from contextlib import ExitStack as DoesNotRaise
+from typing import Optional, Tuple
+
+import pytest
+
+from supervision import LineZone
+from supervision.geometry.core import Point, Vector
+
+
+@pytest.mark.parametrize(
+    "vector, expected_result, exception",
+    [
+        (
+            Vector(start=Point(x=0.0, y=0.0), end=Point(x=0.0, y=0.0)),
+            None,
+            pytest.raises(ValueError),
+        ),
+        (
+            Vector(start=Point(x=1.0, y=1.0), end=Point(x=1.0, y=1.0)),
+            None,
+            pytest.raises(ValueError),
+        ),
+        (
+            Vector(start=Point(x=0.0, y=0.0), end=Point(x=0.0, y=4.0)),
+            (
+                Vector(start=Point(x=0.0, y=0.0), end=Point(x=-1.0, y=0.0)),
+                Vector(start=Point(x=0.0, y=4.0), end=Point(x=1.0, y=4.0)),
+            ),
+            DoesNotRaise(),
+        ),
+        (
+            Vector(Point(0.0, 0.0), Point(4.0, 0.0)),
+            (
+                Vector(start=Point(x=0.0, y=0.0), end=Point(x=0.0, y=1.0)),
+                Vector(start=Point(x=4.0, y=0.0), end=Point(x=4.0, y=-1.0)),
+            ),
+            DoesNotRaise(),
+        ),
+        (
+            Vector(Point(0.0, 0.0), Point(3.0, 4.0)),
+            (
+                Vector(start=Point(x=0, y=0), end=Point(x=-0.8, y=0.6)),
+                Vector(start=Point(x=3, y=4), end=Point(x=3.8, y=3.4)),
+            ),
+            DoesNotRaise(),
+        ),
+        (
+            Vector(Point(0.0, 0.0), Point(4.0, 3.0)),
+            (
+                Vector(start=Point(x=0, y=0), end=Point(x=-0.6, y=0.8)),
+                Vector(start=Point(x=4, y=3), end=Point(x=4.6, y=2.2)),
+            ),
+            DoesNotRaise(),
+        ),
+        (
+            Vector(Point(0.0, 0.0), Point(3.0, -4.0)),
+            (
+                Vector(start=Point(x=0, y=0), end=Point(x=0.8, y=0.6)),
+                Vector(start=Point(x=3, y=-4), end=Point(x=2.2, y=-4.6)),
+            ),
+            DoesNotRaise(),
+        ),
+    ],
+)
+def test_calculate_region_of_interest_limits(
+    vector: Vector,
+    expected_result: Optional[Tuple[Vector, Vector]],
+    exception: Exception,
+) -> None:
+    with exception:
+        result = LineZone.calculate_region_of_interest_limits(vector=vector)
+        assert result == expected_result

test/draw/test_color.py

@@ -9,13 +9,13 @@ from supervision.draw.color import Color
 @pytest.mark.parametrize(
     "color_hex, expected_result, exception",
     [
-        ("fff", Color.white(), DoesNotRaise()),
-        ("#fff", Color.white(), DoesNotRaise()),
-        ("ffffff", Color.white(), DoesNotRaise()),
-        ("#ffffff", Color.white(), DoesNotRaise()),
-        ("f00", Color.red(), DoesNotRaise()),
-        ("0f0", Color.green(), DoesNotRaise()),
-        ("00f", Color.blue(), DoesNotRaise()),
+        ("fff", Color.WHITE, DoesNotRaise()),
+        ("#fff", Color.WHITE, DoesNotRaise()),
+        ("ffffff", Color.WHITE, DoesNotRaise()),
+        ("#ffffff", Color.WHITE, DoesNotRaise()),
+        ("f00", Color.RED, DoesNotRaise()),
+        ("0f0", Color.GREEN, DoesNotRaise()),
+        ("00f", Color.BLUE, DoesNotRaise()),
         ("#808000", Color(r=128, g=128, b=0), DoesNotRaise()),
         ("", None, pytest.raises(ValueError)),
         ("00", None, pytest.raises(ValueError)),
@@ -35,11 +35,11 @@ def test_color_from_hex(
 @pytest.mark.parametrize(
     "color, expected_result, exception",
     [
-        (Color.white(), "#ffffff", DoesNotRaise()),
-        (Color.black(), "#000000", DoesNotRaise()),
-        (Color.red(), "#ff0000", DoesNotRaise()),
-        (Color.green(), "#00ff00", DoesNotRaise()),
-        (Color.blue(), "#0000ff", DoesNotRaise()),
+        (Color.WHITE, "#ffffff", DoesNotRaise()),
+        (Color.BLACK, "#000000", DoesNotRaise()),
+        (Color.RED, "#ff0000", DoesNotRaise()),
+        (Color.GREEN, "#00ff00", DoesNotRaise()),
+        (Color.BLUE, "#0000ff", DoesNotRaise()),
         (Color(r=128, g=128, b=0), "#808000", DoesNotRaise()),
     ],
 )

test/geometry/test_core.py

@@ -0,0 +1,59 @@
+import pytest
+
+from supervision.geometry.core import Point, Vector
+
+
+@pytest.mark.parametrize(
+    "vector, point, expected_result",
+    [
+        (Vector(start=Point(x=0, y=0), end=Point(x=5, y=5)), Point(x=-1, y=1), 10.0),
+        (Vector(start=Point(x=0, y=0), end=Point(x=5, y=5)), Point(x=6, y=6), 0.0),
+        (Vector(start=Point(x=0, y=0), end=Point(x=5, y=5)), Point(x=3, y=6), 15.0),
+        (Vector(start=Point(x=5, y=5), end=Point(x=0, y=0)), Point(x=-1, y=1), -10.0),
+        (Vector(start=Point(x=5, y=5), end=Point(x=0, y=0)), Point(x=6, y=6), 0.0),
+        (Vector(start=Point(x=5, y=5), end=Point(x=0, y=0)), Point(x=3, y=6), -15.0),
+        (Vector(start=Point(x=0, y=0), end=Point(x=1, y=0)), Point(x=0, y=0), 0.0),
+        (Vector(start=Point(x=0, y=0), end=Point(x=1, y=0)), Point(x=0, y=-1), -1.0),
+        (Vector(start=Point(x=0, y=0), end=Point(x=1, y=0)), Point(x=0, y=1), 1.0),
+        (Vector(start=Point(x=1, y=0), end=Point(x=0, y=0)), Point(x=0, y=0), 0.0),
+        (Vector(start=Point(x=1, y=0), end=Point(x=0, y=0)), Point(x=0, y=-1), 1.0),
+        (Vector(start=Point(x=1, y=0), end=Point(x=0, y=0)), Point(x=0, y=1), -1.0),
+        (Vector(start=Point(x=1, y=1), end=Point(x=1, y=3)), Point(x=0, y=0), 2.0),
+        (Vector(start=Point(x=1, y=1), end=Point(x=1, y=3)), Point(x=1, y=4), 0.0),
+        (Vector(start=Point(x=1, y=1), end=Point(x=1, y=3)), Point(x=2, y=4), -2.0),
+        (Vector(start=Point(x=1, y=3), end=Point(x=1, y=1)), Point(x=0, y=0), -2.0),
+        (Vector(start=Point(x=1, y=3), end=Point(x=1, y=1)), Point(x=1, y=4), 0.0),
+        (Vector(start=Point(x=1, y=3), end=Point(x=1, y=1)), Point(x=2, y=4), 2.0),
+    ],
+)
+def test_vector_cross_product(
+    vector: Vector, point: Point, expected_result: float
+) -> None:
+    result = vector.cross_product(point=point)
+    assert result == expected_result
+
+
+@pytest.mark.parametrize(
+    "vector, expected_result",
+    [
+        (Vector(start=Point(x=0, y=0), end=Point(x=0, y=0)), 0.0),
+        (Vector(start=Point(x=1, y=0), end=Point(x=0, y=0)), 1.0),
+        (Vector(start=Point(x=0, y=1), end=Point(x=0, y=0)), 1.0),
+        (Vector(start=Point(x=0, y=0), end=Point(x=1, y=0)), 1.0),
+        (Vector(start=Point(x=0, y=0), end=Point(x=0, y=1)), 1.0),
+        (Vector(start=Point(x=-1, y=0), end=Point(x=0, y=0)), 1.0),
+        (Vector(start=Point(x=0, y=-1), end=Point(x=0, y=0)), 1.0),
+        (Vector(start=Point(x=0, y=0), end=Point(x=-1, y=0)), 1.0),
+        (Vector(start=Point(x=0, y=0), end=Point(x=0, y=-1)), 1.0),
+        (Vector(start=Point(x=0, y=0), end=Point(x=3, y=4)), 5.0),
+        (Vector(start=Point(x=0, y=0), end=Point(x=-3, y=4)), 5.0),
+        (Vector(start=Point(x=0, y=0), end=Point(x=3, y=-4)), 5.0),
+        (Vector(start=Point(x=0, y=0), end=Point(x=-3, y=-4)), 5.0),
+        (Vector(start=Point(x=0, y=0), end=Point(x=4, y=3)), 5.0),
+        (Vector(start=Point(x=3, y=4), end=Point(x=0, y=0)), 5.0),
+        (Vector(start=Point(x=4, y=3), end=Point(x=0, y=0)), 5.0),
+    ],
+)
+def test_vector_magnitude(vector: Vector, expected_result: float) -> None:
+    result = vector.magnitude
+    assert result == expected_result

test/geometry/test_dataclasses.py

@@ -1,31 +0,0 @@
-import pytest
-
-from supervision.geometry.core import Point, Vector
-
-
-@pytest.mark.parametrize(
-    "vector, point, expected_result",
-    [
-        (Vector(start=Point(x=0, y=0), end=Point(x=5, y=5)), Point(x=-1, y=1), False),
-        (Vector(start=Point(x=0, y=0), end=Point(x=5, y=5)), Point(x=6, y=6), False),
-        (Vector(start=Point(x=0, y=0), end=Point(x=5, y=5)), Point(x=3, y=6), False),
-        (Vector(start=Point(x=5, y=5), end=Point(x=0, y=0)), Point(x=-1, y=1), True),
-        (Vector(start=Point(x=5, y=5), end=Point(x=0, y=0)), Point(x=6, y=6), False),
-        (Vector(start=Point(x=5, y=5), end=Point(x=0, y=0)), Point(x=3, y=6), True),
-        (Vector(start=Point(x=0, y=0), end=Point(x=1, y=0)), Point(x=0, y=0), False),
-        (Vector(start=Point(x=0, y=0), end=Point(x=1, y=0)), Point(x=0, y=-1), True),
-        (Vector(start=Point(x=0, y=0), end=Point(x=1, y=0)), Point(x=0, y=1), False),
-        (Vector(start=Point(x=1, y=0), end=Point(x=0, y=0)), Point(x=0, y=0), False),
-        (Vector(start=Point(x=1, y=0), end=Point(x=0, y=0)), Point(x=0, y=-1), False),
-        (Vector(start=Point(x=1, y=0), end=Point(x=0, y=0)), Point(x=0, y=1), True),
-        (Vector(start=Point(x=1, y=1), end=Point(x=1, y=3)), Point(x=0, y=0), False),
-        (Vector(start=Point(x=1, y=1), end=Point(x=1, y=3)), Point(x=1, y=4), False),
-        (Vector(start=Point(x=1, y=1), end=Point(x=1, y=3)), Point(x=2, y=4), True),
-        (Vector(start=Point(x=1, y=3), end=Point(x=1, y=1)), Point(x=0, y=0), True),
-        (Vector(start=Point(x=1, y=3), end=Point(x=1, y=1)), Point(x=1, y=4), False),
-        (Vector(start=Point(x=1, y=3), end=Point(x=1, y=1)), Point(x=2, y=4), False),
-    ],
-)
-def test_vector_is_in(vector: Vector, point: Point, expected_result: bool) -> None:
-    result = vector.is_in(point=point)
-    assert result == expected_result