+
diff --git a/docs/theme/index.html b/docs/theme/index.html
new file mode 100644
index 00000000..c65749cf
--- /dev/null
+++ b/docs/theme/index.html
@@ -0,0 +1,15 @@
+{% extends "main.html" %}
+{% block content %}
+{{ super() }}
+
+{% endblock %}
diff --git a/poetry.lock b/poetry.lock
index 63dc909c..a217883c 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,14 +1,14 @@
-# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.1 and should not be changed by hand.
[[package]]
name = "anyio"
-version = "4.2.0"
+version = "4.3.0"
description = "High level compatibility layer for multiple asynchronous event loop implementations"
optional = false
python-versions = ">=3.8"
files = [
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+ {file = "anyio-4.3.0-py3-none-any.whl", hash = "sha256:048e05d0f6caeed70d731f3db756d35dcc1f35747c8c403364a8332c630441b8"},
+ {file = "anyio-4.3.0.tar.gz", hash = "sha256:f75253795a87df48568485fd18cdd2a3fa5c4f7c5be8e5e36637733fce06fed6"},
]
[package.dependencies]
@@ -24,13 +24,13 @@ trio = ["trio (>=0.23)"]
[[package]]
name = "appnope"
-version = "0.1.3"
+version = "0.1.4"
description = "Disable App Nap on macOS >= 10.9"
optional = false
-python-versions = "*"
+python-versions = ">=3.6"
files = [
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- {file = "appnope-0.1.3.tar.gz", hash = "sha256:02bd91c4de869fbb1e1c50aafc4098827a7a54ab2f39d9dcba6c9547ed920e24"},
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[[package]]
@@ -127,6 +127,21 @@ six = ">=1.12.0"
astroid = ["astroid (>=1,<2)", "astroid (>=2,<4)"]
test = ["astroid (>=1,<2)", "astroid (>=2,<4)", "pytest"]
+[[package]]
+name = "astunparse"
+version = "1.6.3"
+description = "An AST unparser for Python"
+optional = false
+python-versions = "*"
+files = [
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+ {file = "astunparse-1.6.3.tar.gz", hash = "sha256:5ad93a8456f0d084c3456d059fd9a92cce667963232cbf763eac3bc5b7940872"},
+]
+
+[package.dependencies]
+six = ">=1.6.1,<2.0"
+wheel = ">=0.23.0,<1.0"
+
[[package]]
name = "async-lru"
version = "2.0.4"
@@ -253,13 +268,13 @@ virtualenv = ["virtualenv (>=20.0.35)"]
[[package]]
name = "cachetools"
-version = "5.3.2"
+version = "5.3.3"
description = "Extensible memoizing collections and decorators"
optional = false
python-versions = ">=3.7"
files = [
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- {file = "cachetools-5.3.2.tar.gz", hash = "sha256:086ee420196f7b2ab9ca2db2520aca326318b68fe5ba8bc4d49cca91add450f2"},
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]
[[package]]
@@ -305,13 +320,13 @@ test = ["flake8", "isort", "pytest"]
[[package]]
name = "certifi"
-version = "2023.11.17"
+version = "2024.2.2"
description = "Python package for providing Mozilla's CA Bundle."
optional = false
python-versions = ">=3.6"
files = [
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[[package]]
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@@ -676,43 +687,43 @@ test-no-images = ["pytest", "pytest-cov", "wurlitzer"]
[[package]]
name = "cryptography"
-version = "42.0.0"
+version = "42.0.5"
description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
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python-versions = ">=3.7"
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jupyter-server = ">=2.4.0,<3"
-jupyterlab = ">=4.0.2,<4.1"
+jupyterlab = ">=4.1.1,<4.2"
jupyterlab-server = ">=2.22.1,<3"
notebook-shim = ">=0.2,<0.3"
tornado = ">=6.2.0"
@@ -2415,13 +2488,13 @@ test = ["importlib-resources (>=5.0)", "ipykernel", "jupyter-server[test] (>=2.4
[[package]]
name = "notebook-shim"
-version = "0.2.3"
+version = "0.2.4"
description = "A shim layer for notebook traits and config"
optional = false
python-versions = ">=3.7"
files = [
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@@ -2483,12 +2556,31 @@ files = [
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]
+[package.dependencies]
+numpy = {version = ">=1.23.5", markers = "python_version >= \"3.11\""}
+
+[[package]]
+name = "opencv-python"
+version = "4.9.0.80"
+description = "Wrapper package for OpenCV python bindings."
+optional = true
+python-versions = ">=3.6"
+files = [
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- {version = ">=1.23.5", markers = "python_version >= \"3.11\""},
+ {version = ">=1.23.5", markers = "python_version >= \"3.11\" and python_version < \"3.12\""},
{version = ">=1.21.4", markers = "python_version >= \"3.10\" and platform_system == \"Darwin\" and python_version < \"3.11\""},
{version = ">=1.21.2", markers = "platform_system != \"Darwin\" and python_version >= \"3.10\" and python_version < \"3.11\""},
]
@@ -2509,25 +2601,44 @@ files = [
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]
+[package.dependencies]
+numpy = {version = ">=1.23.5", markers = "python_version >= \"3.11\""}
+
+[[package]]
+name = "opencv-python-headless"
+version = "4.9.0.80"
+description = "Wrapper package for OpenCV python bindings."
+optional = false
+python-versions = ">=3.6"
+files = [
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+ {file = "opencv_python_headless-4.9.0.80-cp37-abi3-macosx_10_16_x86_64.whl", hash = "sha256:2ea8a2edc4db87841991b2fbab55fc07b97ecb602e0f47d5d485bd75cee17c1a"},
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- {version = ">=1.23.5", markers = "python_version >= \"3.11\""},
+ {version = ">=1.23.5", markers = "python_version >= \"3.11\" and python_version < \"3.12\""},
{version = ">=1.21.4", markers = "python_version >= \"3.10\" and platform_system == \"Darwin\" and python_version < \"3.11\""},
{version = ">=1.21.2", markers = "platform_system != \"Darwin\" and python_version >= \"3.10\" and python_version < \"3.11\""},
]
[[package]]
name = "overrides"
-version = "7.6.0"
+version = "7.7.0"
description = "A decorator to automatically detect mismatch when overriding a method."
optional = false
python-versions = ">=3.6"
files = [
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[[package]]
@@ -2725,28 +2836,28 @@ files = [
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name = "platformdirs"
-version = "4.1.0"
+version = "4.2.0"
description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
optional = false
python-versions = ">=3.8"
files = [
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-test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4)", "pytest-cov (>=4.1)", "pytest-mock (>=3.11.1)"]
+docs = ["furo (>=2023.9.10)", "proselint (>=0.13)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.25.2)"]
+test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)"]
[[package]]
name = "pluggy"
-version = "1.3.0"
+version = "1.4.0"
description = "plugin and hook calling mechanisms for python"
optional = false
python-versions = ">=3.8"
files = [
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@@ -2773,13 +2884,13 @@ virtualenv = ">=20.10.0"
[[package]]
name = "prometheus-client"
-version = "0.19.0"
+version = "0.20.0"
description = "Python client for the Prometheus monitoring system."
optional = false
python-versions = ">=3.8"
files = [
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@@ -2945,13 +3056,13 @@ tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
[[package]]
name = "pytest"
-version = "8.0.0"
+version = "8.0.2"
description = "pytest: simple powerful testing with Python"
optional = false
python-versions = ">=3.8"
files = [
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@@ -3037,17 +3148,17 @@ files = [
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name = "pywinpty"
-version = "2.0.12"
+version = "2.0.13"
description = "Pseudo terminal support for Windows from Python."
optional = false
python-versions = ">=3.8"
files = [
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[[package]]
name = "six"
@@ -3743,13 +3843,13 @@ files = [
[[package]]
name = "sniffio"
-version = "1.3.0"
+version = "1.3.1"
description = "Sniff out which async library your code is running under"
optional = false
python-versions = ">=3.7"
files = [
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]
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@@ -3865,13 +3965,13 @@ files = [
[[package]]
name = "tox"
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description = "tox is a generic virtualenv management and test command line tool"
optional = false
python-versions = ">=3.8"
files = [
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[package.dependencies]
@@ -3960,13 +4060,13 @@ files = [
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name = "typing-extensions"
-version = "4.9.0"
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description = "Backported and Experimental Type Hints for Python 3.8+"
optional = false
python-versions = ">=3.8"
files = [
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@@ -3985,17 +4085,18 @@ dev = ["flake8", "flake8-annotations", "flake8-bandit", "flake8-bugbear", "flake
[[package]]
name = "urllib3"
-version = "2.1.0"
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description = "HTTP library with thread-safe connection pooling, file post, and more."
optional = false
python-versions = ">=3.8"
files = [
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socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
zstd = ["zstandard (>=0.18.0)"]
@@ -4015,13 +4116,13 @@ test = ["coverage", "flake8 (>=3.7)", "mypy", "pretend", "pytest"]
[[package]]
name = "virtualenv"
-version = "20.25.0"
+version = "20.25.1"
description = "Virtual Python Environment builder"
optional = false
python-versions = ">=3.7"
files = [
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[[package]]
name = "watchdog"
-version = "3.0.0"
+version = "4.0.0"
description = "Filesystem events monitoring"
optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
files = [
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[package.extras]
@@ -4172,4 +4275,4 @@ desktop = ["opencv-python"]
[metadata]
lock-version = "2.0"
python-versions = "^3.8"
-content-hash = "d635be9c5f61a2af5901d9ad00f31cdb714074ab5d5537e8280214d9d98aed64"
+content-hash = "8010232d55d2b5ad5dd5b0ab950ca0e417e705f105bd5331d2e44afb26151010"
diff --git a/pyproject.toml b/pyproject.toml
index 79ba1721..04a12f67 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -44,6 +44,7 @@ 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,<=4.66.2", optional = true }
+pillow = ">=9.4"
[tool.poetry.extras]
desktop = ["opencv-python"]
@@ -111,12 +112,12 @@ exclude = '''
[tool.ruff]
target-version = "py38"
# Enable pycodestyle (`E`) and Pyflakes (`F`) codes by default.
-select = ["E", "F"]
-ignore = []
+lint.select = ["E", "F"]
+lint.ignore = []
# Allow autofix for all enabled rules (when `--fix`) is provided.
-fixable = ["A", "B", "C", "D", "E", "F", "G", "I", "N", "Q", "S", "T", "W", "ANN", "ARG", "BLE", "COM", "DJ", "DTZ", "EM", "ERA", "EXE", "FBT", "ICN", "INP", "ISC", "NPY", "PD", "PGH", "PIE", "PL", "PT", "PTH", "PYI", "RET", "RSE", "RUF", "SIM", "SLF", "TCH", "TID", "TRY", "UP", "YTT"]
-unfixable = []
+lint.fixable = ["A", "B", "C", "D", "E", "F", "G", "I", "N", "Q", "S", "T", "W", "ANN", "ARG", "BLE", "COM", "DJ", "DTZ", "EM", "ERA", "EXE", "FBT", "ICN", "INP", "ISC", "NPY", "PD", "PGH", "PIE", "PL", "PT", "PTH", "PYI", "RET", "RSE", "RUF", "SIM", "SLF", "TCH", "TID", "TRY", "UP", "YTT"]
+lint.unfixable = []
# Exclude a variety of commonly ignored directories.
exclude = [
@@ -151,17 +152,17 @@ line-length = 88
indent-width = 4
# Allow unused variables when underscore-prefixed.
-dummy-variable-rgx = "^(_+|(_+[a-zA-Z0-9_]*[a-zA-Z0-9]+?))$"
+lint.dummy-variable-rgx = "^(_+|(_+[a-zA-Z0-9_]*[a-zA-Z0-9]+?))$"
-[tool.ruff.flake8-quotes]
+[tool.ruff.lint.flake8-quotes]
inline-quotes = "double"
multiline-quotes = "double"
docstring-quotes = "double"
-[tool.ruff.pydocstyle]
+[tool.ruff.lint.pydocstyle]
convention = "google"
-[tool.ruff.per-file-ignores]
+[tool.ruff.lint.per-file-ignores]
"__init__.py" = ["E402","F401"]
"supervision/assets/list.py" = ["E501"]
diff --git a/supervision/annotators/base.py b/supervision/annotators/base.py
index 515ee1c8..159ad556 100644
--- a/supervision/annotators/base.py
+++ b/supervision/annotators/base.py
@@ -1,11 +1,22 @@
from abc import ABC, abstractmethod
+from typing import TypeVar
import numpy as np
+from PIL import Image
from supervision.detection.core import Detections
+ImageType = TypeVar("ImageType", np.ndarray, Image.Image)
+"""
+An image of type `np.ndarray` or `PIL.Image.Image`.
+
+Unlike a `Union`, ensures the type remains consistent. If a function
+takes an `ImageType` argument and returns an `ImageType`, when you
+pass an `np.ndarray`, you will get an `np.ndarray` back.
+"""
+
class BaseAnnotator(ABC):
@abstractmethod
- def annotate(self, scene: np.ndarray, detections: Detections) -> np.ndarray:
+ def annotate(self, scene: ImageType, detections: Detections) -> ImageType:
pass
diff --git a/supervision/annotators/core.py b/supervision/annotators/core.py
index ea4b6bd4..50df9caa 100644
--- a/supervision/annotators/core.py
+++ b/supervision/annotators/core.py
@@ -4,8 +4,13 @@ from typing import List, Optional, Tuple, Union
import cv2
import numpy as np
-from supervision.annotators.base import BaseAnnotator
-from supervision.annotators.utils import ColorLookup, Trace, resolve_color
+from supervision.annotators.base import BaseAnnotator, ImageType
+from supervision.annotators.utils import (
+ ColorLookup,
+ Trace,
+ resolve_color,
+ scene_to_annotator_img_type,
+)
from supervision.config import CLASS_NAME_DATA_FIELD, ORIENTED_BOX_COORDINATES
from supervision.detection.core import Detections
from supervision.detection.utils import clip_boxes, mask_to_polygons
@@ -37,23 +42,26 @@ class BoundingBoxAnnotator(BaseAnnotator):
self.thickness: int = thickness
self.color_lookup: ColorLookup = color_lookup
+ @scene_to_annotator_img_type
def annotate(
self,
- scene: np.ndarray,
+ scene: ImageType,
detections: Detections,
custom_color_lookup: Optional[np.ndarray] = None,
- ) -> np.ndarray:
+ ) -> ImageType:
"""
Annotates the given scene with bounding boxes based on the provided detections.
Args:
- scene (np.ndarray): The image where bounding boxes will be drawn.
+ scene (ImageType): The image where bounding boxes will be drawn. `ImageType`
+ is a flexible type, accepting either `numpy.ndarray` or `PIL.Image.Image`.
detections (Detections): Object detections to annotate.
custom_color_lookup (Optional[np.ndarray]): Custom color lookup array.
Allows to override the default color mapping strategy.
Returns:
- The annotated image.
+ The annotated image, matching the type of `scene` (`numpy.ndarray`
+ or `PIL.Image.Image`)
Example:
```python
@@ -115,23 +123,27 @@ class OrientedBoxAnnotator(BaseAnnotator):
self.thickness: int = thickness
self.color_lookup: ColorLookup = color_lookup
+ @scene_to_annotator_img_type
def annotate(
self,
- scene: np.ndarray,
+ scene: ImageType,
detections: Detections,
custom_color_lookup: Optional[np.ndarray] = None,
- ) -> np.ndarray:
+ ) -> ImageType:
"""
Annotates the given scene with oriented bounding boxes based on the provided detections.
Args:
- scene (np.ndarray): The image where bounding boxes will be drawn.
+ scene (ImageType): The image where bounding boxes will be drawn.
+ `ImageType` is a flexible type, accepting either `numpy.ndarray`
+ or `PIL.Image.Image`.
detections (Detections): Object detections to annotate.
custom_color_lookup (Optional[np.ndarray]): Custom color lookup array.
Allows to override the default color mapping strategy.
Returns:
- The annotated image.
+ The annotated image, matching the type of `scene` (`numpy.ndarray`
+ or `PIL.Image.Image`)
Example:
```python
@@ -199,23 +211,27 @@ class MaskAnnotator(BaseAnnotator):
self.opacity = opacity
self.color_lookup: ColorLookup = color_lookup
+ @scene_to_annotator_img_type
def annotate(
self,
- scene: np.ndarray,
+ scene: ImageType,
detections: Detections,
custom_color_lookup: Optional[np.ndarray] = None,
- ) -> np.ndarray:
+ ) -> ImageType:
"""
Annotates the given scene with masks based on the provided detections.
Args:
- scene (np.ndarray): The image where masks will be drawn.
+ scene (ImageType): The image where masks will be drawn.
+ `ImageType` is a flexible type, accepting either `numpy.ndarray`
+ or `PIL.Image.Image`.
detections (Detections): Object detections to annotate.
custom_color_lookup (Optional[np.ndarray]): Custom color lookup array.
Allows to override the default color mapping strategy.
Returns:
- The annotated image.
+ The annotated image, matching the type of `scene` (`numpy.ndarray`
+ or `PIL.Image.Image`)
Example:
```python
@@ -282,23 +298,27 @@ class PolygonAnnotator(BaseAnnotator):
self.thickness: int = thickness
self.color_lookup: ColorLookup = color_lookup
+ @scene_to_annotator_img_type
def annotate(
self,
- scene: np.ndarray,
+ scene: ImageType,
detections: Detections,
custom_color_lookup: Optional[np.ndarray] = None,
- ) -> np.ndarray:
+ ) -> ImageType:
"""
Annotates the given scene with polygons based on the provided detections.
Args:
- scene (np.ndarray): The image where polygons will be drawn.
+ scene (ImageType): The image where polygons will be drawn.
+ `ImageType` is a flexible type, accepting either `numpy.ndarray`
+ or `PIL.Image.Image`.
detections (Detections): Object detections to annotate.
custom_color_lookup (Optional[np.ndarray]): Custom color lookup array.
Allows to override the default color mapping strategy.
Returns:
- The annotated image.
+ The annotated image, matching the type of `scene` (`numpy.ndarray`
+ or `PIL.Image.Image`)
Example:
```python
@@ -364,23 +384,27 @@ class ColorAnnotator(BaseAnnotator):
self.color_lookup: ColorLookup = color_lookup
self.opacity = opacity
+ @scene_to_annotator_img_type
def annotate(
self,
- scene: np.ndarray,
+ scene: ImageType,
detections: Detections,
custom_color_lookup: Optional[np.ndarray] = None,
- ) -> np.ndarray:
+ ) -> ImageType:
"""
Annotates the given scene with box masks based on the provided detections.
Args:
- scene (np.ndarray): The image where bounding boxes will be drawn.
+ scene (ImageType): The image where bounding boxes will be drawn.
+ `ImageType` is a flexible type, accepting either `numpy.ndarray`
+ or `PIL.Image.Image`.
detections (Detections): Object detections to annotate.
custom_color_lookup (Optional[np.ndarray]): Custom color lookup array.
Allows to override the default color mapping strategy.
Returns:
- The annotated image.
+ The annotated image, matching the type of `scene` (`numpy.ndarray`
+ or `PIL.Image.Image`)
Example:
```python
@@ -454,23 +478,27 @@ class HaloAnnotator(BaseAnnotator):
self.color_lookup: ColorLookup = color_lookup
self.kernel_size: int = kernel_size
+ @scene_to_annotator_img_type
def annotate(
self,
- scene: np.ndarray,
+ scene: ImageType,
detections: Detections,
custom_color_lookup: Optional[np.ndarray] = None,
- ) -> np.ndarray:
+ ) -> ImageType:
"""
Annotates the given scene with halos based on the provided detections.
Args:
- scene (np.ndarray): The image where masks will be drawn.
+ scene (ImageType): The image where masks will be drawn.
+ `ImageType` is a flexible type, accepting either `numpy.ndarray`
+ or `PIL.Image.Image`.
detections (Detections): Object detections to annotate.
custom_color_lookup (Optional[np.ndarray]): Custom color lookup array.
Allows to override the default color mapping strategy.
Returns:
- The annotated image.
+ The annotated image, matching the type of `scene` (`numpy.ndarray`
+ or `PIL.Image.Image`)
Example:
```python
@@ -548,23 +576,27 @@ class EllipseAnnotator(BaseAnnotator):
self.end_angle: int = end_angle
self.color_lookup: ColorLookup = color_lookup
+ @scene_to_annotator_img_type
def annotate(
self,
- scene: np.ndarray,
+ scene: ImageType,
detections: Detections,
custom_color_lookup: Optional[np.ndarray] = None,
- ) -> np.ndarray:
+ ) -> ImageType:
"""
Annotates the given scene with ellipses based on the provided detections.
Args:
- scene (np.ndarray): The image where ellipses will be drawn.
+ scene (ImageType): The image where ellipses will be drawn.
+ `ImageType` is a flexible type, accepting either `numpy.ndarray`
+ or `PIL.Image.Image`.
detections (Detections): Object detections to annotate.
custom_color_lookup (Optional[np.ndarray]): Custom color lookup array.
Allows to override the default color mapping strategy.
Returns:
- The annotated image.
+ The annotated image, matching the type of `scene` (`numpy.ndarray`
+ or `PIL.Image.Image`)
Example:
```python
@@ -635,23 +667,27 @@ class BoxCornerAnnotator(BaseAnnotator):
self.corner_length: int = corner_length
self.color_lookup: ColorLookup = color_lookup
+ @scene_to_annotator_img_type
def annotate(
self,
- scene: np.ndarray,
+ scene: ImageType,
detections: Detections,
custom_color_lookup: Optional[np.ndarray] = None,
- ) -> np.ndarray:
+ ) -> ImageType:
"""
Annotates the given scene with box corners based on the provided detections.
Args:
- scene (np.ndarray): The image where box corners will be drawn.
+ scene (ImageType): The image where box corners will be drawn.
+ `ImageType` is a flexible type, accepting either `numpy.ndarray`
+ or `PIL.Image.Image`.
detections (Detections): Object detections to annotate.
custom_color_lookup (Optional[np.ndarray]): Custom color lookup array.
Allows to override the default color mapping strategy.
Returns:
- The annotated image.
+ The annotated image, matching the type of `scene` (`numpy.ndarray`
+ or `PIL.Image.Image`)
Example:
```python
@@ -719,23 +755,27 @@ class CircleAnnotator(BaseAnnotator):
self.thickness: int = thickness
self.color_lookup: ColorLookup = color_lookup
+ @scene_to_annotator_img_type
def annotate(
self,
- scene: np.ndarray,
+ scene: ImageType,
detections: Detections,
custom_color_lookup: Optional[np.ndarray] = None,
- ) -> np.ndarray:
+ ) -> ImageType:
"""
Annotates the given scene with circles based on the provided detections.
Args:
- scene (np.ndarray): The image where box corners will be drawn.
+ scene (ImageType): The image where box corners will be drawn.
+ `ImageType` is a flexible type, accepting either `numpy.ndarray`
+ or `PIL.Image.Image`.
detections (Detections): Object detections to annotate.
custom_color_lookup (Optional[np.ndarray]): Custom color lookup array.
Allows to override the default color mapping strategy.
Returns:
- The annotated image.
+ The annotated image, matching the type of `scene` (`numpy.ndarray`
+ or `PIL.Image.Image`)
Example:
```python
@@ -805,23 +845,27 @@ class DotAnnotator(BaseAnnotator):
self.position: Position = position
self.color_lookup: ColorLookup = color_lookup
+ @scene_to_annotator_img_type
def annotate(
self,
- scene: np.ndarray,
+ scene: ImageType,
detections: Detections,
custom_color_lookup: Optional[np.ndarray] = None,
- ) -> np.ndarray:
+ ) -> ImageType:
"""
Annotates the given scene with dots based on the provided detections.
Args:
- scene (np.ndarray): The image where dots will be drawn.
+ scene (ImageType): The image where dots will be drawn.
+ `ImageType` is a flexible type, accepting either `numpy.ndarray`
+ or `PIL.Image.Image`.
detections (Detections): Object detections to annotate.
custom_color_lookup (Optional[np.ndarray]): Custom color lookup array.
Allows to override the default color mapping strategy.
Returns:
- The annotated image.
+ The annotated image, matching the type of `scene` (`numpy.ndarray`
+ or `PIL.Image.Image`)
Example:
```python
@@ -929,26 +973,44 @@ class LabelAnnotator:
center_x + text_w // 2,
center_y + text_h,
)
+ elif position == Position.CENTER_LEFT:
+ return (
+ center_x - text_w,
+ center_y - text_h // 2,
+ center_x,
+ center_y + text_h // 2,
+ )
+ elif position == Position.CENTER_RIGHT:
+ return (
+ center_x,
+ center_y - text_h // 2,
+ center_x + text_w,
+ center_y + text_h // 2,
+ )
+ @scene_to_annotator_img_type
def annotate(
self,
- scene: np.ndarray,
+ scene: ImageType,
detections: Detections,
labels: List[str] = None,
custom_color_lookup: Optional[np.ndarray] = None,
- ) -> np.ndarray:
+ ) -> ImageType:
"""
Annotates the given scene with labels based on the provided detections.
Args:
- scene (np.ndarray): The image where labels will be drawn.
+ scene (ImageType): The image where labels will be drawn.
+ `ImageType` is a flexible type, accepting either `numpy.ndarray`
+ or `PIL.Image.Image`.
detections (Detections): Object detections to annotate.
labels (List[str]): Optional. Custom labels for each detection.
custom_color_lookup (Optional[np.ndarray]): Custom color lookup array.
Allows to override the default color mapping strategy.
Returns:
- The annotated image.
+ The annotated image, matching the type of `scene` (`numpy.ndarray`
+ or `PIL.Image.Image`)
Example:
```python
@@ -1049,20 +1111,24 @@ class BlurAnnotator(BaseAnnotator):
"""
self.kernel_size: int = kernel_size
+ @scene_to_annotator_img_type
def annotate(
self,
- scene: np.ndarray,
+ scene: ImageType,
detections: Detections,
- ) -> np.ndarray:
+ ) -> ImageType:
"""
Annotates the given scene by blurring regions based on the provided detections.
Args:
- scene (np.ndarray): The image where blurring will be applied.
+ scene (ImageType): The image where blurring will be applied.
+ `ImageType` is a flexible type, accepting either `numpy.ndarray`
+ or `PIL.Image.Image`.
detections (Detections): Object detections to annotate.
Returns:
- The annotated image.
+ The annotated image, matching the type of `scene` (`numpy.ndarray`
+ or `PIL.Image.Image`)
Example:
```python
@@ -1130,24 +1196,28 @@ class TraceAnnotator:
self.thickness = thickness
self.color_lookup: ColorLookup = color_lookup
+ @scene_to_annotator_img_type
def annotate(
self,
- scene: np.ndarray,
+ scene: ImageType,
detections: Detections,
custom_color_lookup: Optional[np.ndarray] = None,
- ) -> np.ndarray:
+ ) -> ImageType:
"""
Draws trace paths on the frame based on the detection coordinates provided.
Args:
- scene (np.ndarray): The image on which the traces will be drawn.
+ scene (ImageType): The image on which the traces will be drawn.
+ `ImageType` is a flexible type, accepting either `numpy.ndarray`
+ or `PIL.Image.Image`.
detections (Detections): The detections which include coordinates for
which the traces will be drawn.
custom_color_lookup (Optional[np.ndarray]): Custom color lookup array.
Allows to override the default color mapping strategy.
Returns:
- The annotated image.
+ The annotated image, matching the type of `scene` (`numpy.ndarray`
+ or `PIL.Image.Image`)
Example:
```python
@@ -1233,16 +1303,20 @@ class HeatMapAnnotator:
self.top_hue = top_hue
self.low_hue = low_hue
- def annotate(self, scene: np.ndarray, detections: Detections) -> np.ndarray:
+ @scene_to_annotator_img_type
+ def annotate(self, scene: ImageType, detections: Detections) -> ImageType:
"""
Annotates the scene with a heatmap based on the provided detections.
Args:
- scene (np.ndarray): The image where the heatmap will be drawn.
+ scene (ImageType): The image where the heatmap will be drawn.
+ `ImageType` is a flexible type, accepting either `numpy.ndarray`
+ or `PIL.Image.Image`.
detections (Detections): Object detections to annotate.
Returns:
- Annotated image.
+ The annotated image, matching the type of `scene` (`numpy.ndarray`
+ or `PIL.Image.Image`)
Example:
```python
@@ -1305,21 +1379,25 @@ class PixelateAnnotator(BaseAnnotator):
"""
self.pixel_size: int = pixel_size
+ @scene_to_annotator_img_type
def annotate(
self,
- scene: np.ndarray,
+ scene: ImageType,
detections: Detections,
- ) -> np.ndarray:
+ ) -> ImageType:
"""
Annotates the given scene by pixelating regions based on the provided
detections.
Args:
- scene (np.ndarray): The image where pixelating will be applied.
+ scene (ImageType): The image where pixelating will be applied.
+ `ImageType` is a flexible type, accepting either `numpy.ndarray`
+ or `PIL.Image.Image`.
detections (Detections): Object detections to annotate.
Returns:
- The annotated image.
+ The annotated image, matching the type of `scene` (`numpy.ndarray`
+ or `PIL.Image.Image`)
Example:
```python
@@ -1389,23 +1467,27 @@ class TriangleAnnotator(BaseAnnotator):
self.position: Position = position
self.color_lookup: ColorLookup = color_lookup
+ @scene_to_annotator_img_type
def annotate(
self,
- scene: np.ndarray,
+ scene: ImageType,
detections: Detections,
custom_color_lookup: Optional[np.ndarray] = None,
- ) -> np.ndarray:
+ ) -> ImageType:
"""
Annotates the given scene with triangles based on the provided detections.
Args:
- scene (np.ndarray): The image where triangles will be drawn.
+ scene (ImageType): The image where triangles will be drawn.
+ `ImageType` is a flexible type, accepting either `numpy.ndarray`
+ or `PIL.Image.Image`.
detections (Detections): Object detections to annotate.
custom_color_lookup (Optional[np.ndarray]): Custom color lookup array.
Allows to override the default color mapping strategy.
Returns:
- np.ndarray: The annotated image.
+ The annotated image, matching the type of `scene` (`numpy.ndarray`
+ or `PIL.Image.Image`)
Example:
```python
@@ -1481,24 +1563,28 @@ class RoundBoxAnnotator(BaseAnnotator):
raise ValueError("roundness attribute must be float between (0, 1.0]")
self.roundness: float = roundness
+ @scene_to_annotator_img_type
def annotate(
self,
- scene: np.ndarray,
+ scene: ImageType,
detections: Detections,
custom_color_lookup: Optional[np.ndarray] = None,
- ) -> np.ndarray:
+ ) -> ImageType:
"""
Annotates the given scene with bounding boxes with rounded edges
based on the provided detections.
Args:
- scene (np.ndarray): The image where rounded bounding boxes will be drawn.
+ scene (ImageType): The image where rounded bounding boxes will be drawn.
+ `ImageType` is a flexible type, accepting either `numpy.ndarray`
+ or `PIL.Image.Image`.
detections (Detections): Object detections to annotate.
custom_color_lookup (Optional[np.ndarray]): Custom color lookup array.
Allows to override the default color mapping strategy.
Returns:
- The annotated image.
+ The annotated image, matching the type of `scene` (`numpy.ndarray`
+ or `PIL.Image.Image`)
Example:
```python
@@ -1614,20 +1700,23 @@ class PercentageBarAnnotator(BaseAnnotator):
if border_thickness is None:
self.border_thickness = int(0.15 * self.height)
+ @scene_to_annotator_img_type
def annotate(
self,
- scene: np.ndarray,
+ scene: ImageType,
detections: Detections,
custom_color_lookup: Optional[np.ndarray] = None,
custom_values: Optional[np.ndarray] = None,
- ) -> np.ndarray:
+ ) -> ImageType:
"""
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.
+ scene (ImageType): The image where percentage bars will be drawn.
+ `ImageType` is a flexible type, accepting either `numpy.ndarray`
+ or `PIL.Image.Image`.
detections (Detections): Object detections to annotate.
custom_color_lookup (Optional[np.ndarray]): Custom color lookup array.
Allows to override the default color mapping strategy.
@@ -1638,7 +1727,8 @@ class PercentageBarAnnotator(BaseAnnotator):
to be displayed.
Returns:
- The annotated image.
+ The annotated image, matching the type of `scene` (`numpy.ndarray`
+ or `PIL.Image.Image`)
Example:
```python
@@ -1647,7 +1737,7 @@ class PercentageBarAnnotator(BaseAnnotator):
image = ...
detections = sv.Detections(...)
- percentage_bar_annotator = sv.BoundingBoxAnnotator()
+ percentage_bar_annotator = sv.PercentageBarAnnotator()
annotated_frame = percentage_bar_annotator.annotate(
scene=image.copy(),
detections=detections
diff --git a/supervision/annotators/utils.py b/supervision/annotators/utils.py
index e206c8cb..ed0070f0 100644
--- a/supervision/annotators/utils.py
+++ b/supervision/annotators/utils.py
@@ -1,8 +1,12 @@
from enum import Enum
+from functools import wraps
from typing import Optional, Union
+import cv2
import numpy as np
+from PIL import Image
+from supervision.annotators.base import ImageType
from supervision.detection.core import Detections
from supervision.draw.color import Color, ColorPalette
from supervision.geometry.core import Position
@@ -119,3 +123,28 @@ class Trace:
def get(self, tracker_id: int) -> np.ndarray:
return self.xy[self.tracker_id == tracker_id]
+
+
+def scene_to_annotator_img_type(annotate_func):
+ """
+ Decorates `BaseAnnotator.annotate` implementations, converts scene to
+ an image type used internally by the annotators, converts back when annotation
+ is complete.
+ """
+
+ @wraps(annotate_func)
+ def wrapper(self, scene: ImageType, *args, **kwargs):
+ if isinstance(scene, np.ndarray):
+ return annotate_func(self, scene, *args, **kwargs)
+
+ if isinstance(scene, Image.Image):
+ scene = np.array(scene)
+ scene = cv2.cvtColor(scene, cv2.COLOR_RGB2BGR)
+ annotated = annotate_func(self, scene, *args, **kwargs)
+ annotated = cv2.cvtColor(annotated, cv2.COLOR_BGR2RGB)
+ annotated = Image.fromarray(annotated)
+ return annotated
+
+ raise ValueError(f"Unsupported image type: {type(scene)}")
+
+ return wrapper
diff --git a/supervision/detection/annotate.py b/supervision/detection/annotate.py
index f1a42797..a8df0a57 100644
--- a/supervision/detection/annotate.py
+++ b/supervision/detection/annotate.py
@@ -1,8 +1,9 @@
from typing import List, Optional, Union
import cv2
-import numpy as np
+from supervision.annotators.base import ImageType
+from supervision.annotators.utils import scene_to_annotator_img_type
from supervision.detection.core import Detections
from supervision.draw.color import Color, ColorPalette
from supervision.utils.internal import deprecated
@@ -45,18 +46,21 @@ class BoxAnnotator:
self.text_thickness: int = text_thickness
self.text_padding: int = text_padding
+ @scene_to_annotator_img_type
def annotate(
self,
- scene: np.ndarray,
+ scene: ImageType,
detections: Detections,
labels: Optional[List[str]] = None,
skip_label: bool = False,
- ) -> np.ndarray:
+ ) -> ImageType:
"""
Draws bounding boxes on the frame using the detections provided.
Args:
- scene (np.ndarray): The image on which the bounding boxes will be drawn
+ scene (ImageType): The image on which the bounding boxes will be drawn.
+ `ImageType` is a flexible type, accepting either `numpy.ndarray`
+ or `PIL.Image.Image`.
detections (Detections): The detections for which the
bounding boxes will be drawn
labels (Optional[List[str]]): An optional list of labels
@@ -64,7 +68,8 @@ class BoxAnnotator:
corresponding `class_id` will be used as label.
skip_label (bool): Is set to `True`, skips bounding box label annotation.
Returns:
- np.ndarray: The image with the bounding boxes drawn on it
+ ImageType: The image with the bounding boxes drawn on it, matching the
+ type of `scene` (`numpy.ndarray` or `PIL.Image.Image`)
Example:
```python
diff --git a/supervision/detection/core.py b/supervision/detection/core.py
index e727426b..f170563c 100644
--- a/supervision/detection/core.py
+++ b/supervision/detection/core.py
@@ -487,7 +487,9 @@ class Detections:
)
if np.asarray(xyxy).shape[0] == 0:
- return cls.empty()
+ empty_detection = cls.empty()
+ empty_detection.data = {CLASS_NAME_DATA_FIELD: np.empty(0)}
+ return empty_detection
return cls(
xyxy=xyxy,
diff --git a/supervision/detection/tools/polygon_zone.py b/supervision/detection/tools/polygon_zone.py
index c6f5b80e..d7f22835 100644
--- a/supervision/detection/tools/polygon_zone.py
+++ b/supervision/detection/tools/polygon_zone.py
@@ -1,5 +1,5 @@
from dataclasses import replace
-from typing import Optional, Tuple
+from typing import Iterable, Optional, Tuple
import cv2
import numpy as np
@@ -10,6 +10,7 @@ from supervision.draw.color import Color
from supervision.draw.utils import draw_polygon, draw_text
from supervision.geometry.core import Position
from supervision.geometry.utils import get_polygon_center
+from supervision.utils.internal import deprecated_parameter
class PolygonZone:
@@ -20,21 +21,32 @@ class PolygonZone:
polygon (np.ndarray): A polygon represented by a numpy array of shape
`(N, 2)`, containing the `x`, `y` coordinates of the points.
frame_resolution_wh (Tuple[int, int]): The frame resolution (width, height)
- triggering_position (Position): The position within the bounding
- box that triggers the zone (default: Position.BOTTOM_CENTER)
+ triggering_anchors (Iterable[sv.Position]): A list of positions specifying
+ which anchors of the detections bounding box to consider when deciding on
+ whether the detection fits within the PolygonZone
+ (default: (sv.Position.BOTTOM_CENTER,)).
current_count (int): The current count of detected objects within the zone
mask (np.ndarray): The 2D bool mask for the polygon zone
"""
+ @deprecated_parameter(
+ old_parameter="triggering_position",
+ new_parameter="triggering_anchors",
+ map_function=lambda x: [x],
+ warning_message="`{old_parameter}` in `{function_name}` is deprecated and will "
+ "be remove in `supervision-0.23.0`. Use '{new_parameter}' "
+ "instead.",
+ )
def __init__(
self,
polygon: np.ndarray,
frame_resolution_wh: Tuple[int, int],
- triggering_position: Position = Position.BOTTOM_CENTER,
+ triggering_anchors: Iterable[Position] = (Position.BOTTOM_CENTER,),
):
self.polygon = polygon.astype(int)
self.frame_resolution_wh = frame_resolution_wh
- self.triggering_position = triggering_position
+ self.triggering_anchors = triggering_anchors
+
self.current_count = 0
width, height = frame_resolution_wh
@@ -59,10 +71,20 @@ class PolygonZone:
xyxy=detections.xyxy, resolution_wh=self.frame_resolution_wh
)
clipped_detections = replace(detections, xyxy=clipped_xyxy)
- clipped_anchors = np.ceil(
- clipped_detections.get_anchors_coordinates(anchor=self.triggering_position)
- ).astype(int)
- is_in_zone = self.mask[clipped_anchors[:, 1], clipped_anchors[:, 0]]
+ all_clipped_anchors = np.array(
+ [
+ np.ceil(clipped_detections.get_anchors_coordinates(anchor)).astype(int)
+ for anchor in self.triggering_anchors
+ ]
+ )
+
+ is_in_zone = (
+ self.mask[all_clipped_anchors[:, :, 1], all_clipped_anchors[:, :, 0]]
+ .transpose()
+ .astype(bool)
+ )
+ is_in_zone = np.all(is_in_zone, axis=1)
+
self.current_count = int(np.sum(is_in_zone))
return is_in_zone.astype(bool)
@@ -83,6 +105,7 @@ class PolygonZoneAnnotator:
font (int): The font type for the text on the polygon,
default is cv2.FONT_HERSHEY_SIMPLEX
center (Tuple[int, int]): The center of the polygon for text placement
+ display_in_zone_count (bool): Show the label of the zone or not. Default is True
"""
def __init__(
@@ -94,6 +117,7 @@ class PolygonZoneAnnotator:
text_scale: float = 0.5,
text_thickness: int = 1,
text_padding: int = 10,
+ display_in_zone_count: bool = True,
):
self.zone = zone
self.color = color
@@ -104,6 +128,7 @@ class PolygonZoneAnnotator:
self.text_padding = text_padding
self.font = cv2.FONT_HERSHEY_SIMPLEX
self.center = get_polygon_center(polygon=zone.polygon)
+ self.display_in_zone_count = display_in_zone_count
def annotate(self, scene: np.ndarray, label: Optional[str] = None) -> np.ndarray:
"""
@@ -124,16 +149,17 @@ class PolygonZoneAnnotator:
thickness=self.thickness,
)
- annotated_frame = draw_text(
- scene=annotated_frame,
- text=str(self.zone.current_count) if label is None else label,
- text_anchor=self.center,
- background_color=self.color,
- text_color=self.text_color,
- text_scale=self.text_scale,
- text_thickness=self.text_thickness,
- text_padding=self.text_padding,
- text_font=self.font,
- )
+ if self.display_in_zone_count:
+ annotated_frame = draw_text(
+ scene=annotated_frame,
+ text=str(self.zone.current_count) if label is None else label,
+ text_anchor=self.center,
+ background_color=self.color,
+ text_color=self.text_color,
+ text_scale=self.text_scale,
+ text_thickness=self.text_thickness,
+ text_padding=self.text_padding,
+ text_font=self.font,
+ )
return annotated_frame
diff --git a/supervision/detection/tools/smoother.py b/supervision/detection/tools/smoother.py
index 593b2a8f..f58f3299 100644
--- a/supervision/detection/tools/smoother.py
+++ b/supervision/detection/tools/smoother.py
@@ -115,4 +115,8 @@ class DetectionsSmoother:
if track is not None:
tracked_detections.append(track)
- return Detections.merge(tracked_detections)
+ detections = Detections.merge(tracked_detections)
+ if len(detections) == 0:
+ detections.tracker_id = np.array([], dtype=int)
+
+ return detections
diff --git a/supervision/detection/utils.py b/supervision/detection/utils.py
index f411df28..3302d5f3 100644
--- a/supervision/detection/utils.py
+++ b/supervision/detection/utils.py
@@ -59,8 +59,11 @@ def box_iou_batch(boxes_true: np.ndarray, boxes_detection: np.ndarray) -> np.nda
return area_inter / (area_true[:, None] + area_detection - area_inter)
-def mask_iou_batch(masks_true: np.ndarray, masks_detection: np.ndarray) -> np.ndarray:
+def _mask_iou_batch_split(
+ masks_true: np.ndarray, masks_detection: np.ndarray
+) -> np.ndarray:
"""
+ Internal function.
Compute Intersection over Union (IoU) of two sets of masks -
`masks_true` and `masks_detection`.
@@ -74,9 +77,9 @@ def mask_iou_batch(masks_true: np.ndarray, masks_detection: np.ndarray) -> np.nd
intersection_area = np.logical_and(masks_true[:, None], masks_detection).sum(
axis=(2, 3)
)
+
masks_true_area = masks_true.sum(axis=(1, 2))
masks_detection_area = masks_detection.sum(axis=(1, 2))
-
union_area = masks_true_area[:, None] + masks_detection_area - intersection_area
return np.divide(
@@ -87,6 +90,52 @@ def mask_iou_batch(masks_true: np.ndarray, masks_detection: np.ndarray) -> np.nd
)
+def mask_iou_batch(
+ masks_true: np.ndarray,
+ masks_detection: np.ndarray,
+ memory_limit: int = 1024 * 5,
+) -> np.ndarray:
+ """
+ Compute Intersection over Union (IoU) of two sets of masks -
+ `masks_true` and `masks_detection`.
+
+ Args:
+ masks_true (np.ndarray): 3D `np.ndarray` representing ground-truth masks.
+ masks_detection (np.ndarray): 3D `np.ndarray` representing detection masks.
+ memory_limit (int, optional): memory limit in MB, default is 1024 * 5 MB (5GB).
+
+ Returns:
+ np.ndarray: Pairwise IoU of masks from `masks_true` and `masks_detection`.
+ """
+ memory = (
+ masks_true.shape[0]
+ * masks_true.shape[1]
+ * masks_true.shape[2]
+ * masks_detection.shape[0]
+ / 1024
+ / 1024
+ )
+ if memory <= memory_limit:
+ return _mask_iou_batch_split(masks_true, masks_detection)
+
+ ious = []
+ step = max(
+ memory_limit
+ * 1024
+ * 1024
+ // (
+ masks_detection.shape[0]
+ * masks_detection.shape[1]
+ * masks_detection.shape[2]
+ ),
+ 1,
+ )
+ for i in range(0, masks_true.shape[0], step):
+ ious.append(_mask_iou_batch_split(masks_true[i : i + step], masks_detection))
+
+ return np.vstack(ious)
+
+
def resize_masks(masks: np.ndarray, max_dimension: int = 640) -> np.ndarray:
"""
Resize all masks in the array to have a maximum dimension of max_dimension,
diff --git a/supervision/utils/internal.py b/supervision/utils/internal.py
index 031f5be1..0bd5efd7 100644
--- a/supervision/utils/internal.py
+++ b/supervision/utils/internal.py
@@ -1,5 +1,77 @@
import functools
import warnings
+from typing import Callable
+
+
+def deprecated_parameter(
+ old_parameter: str,
+ new_parameter: str,
+ map_function: Callable = lambda x: x,
+ warning_message: str = "Warning: '{old_parameter}' in '{function_name}' is "
+ "deprecated: use '{new_parameter}' instead.",
+ **message_kwargs,
+):
+ """
+ A decorator to mark a function's parameter as deprecated and issue a warning when
+ used.
+
+ Parameters:
+ old_parameter (str): The name of the deprecated parameter.
+ new_parameter (str): The name of the parameter that should be used instead.
+ map_function (Callable, optional): A function used to map the value of the old
+ parameter to the new parameter. Defaults to the identity function.
+ warning_message (str, optional): The warning message to be displayed when the
+ deprecated parameter is used. Defaults to a generic warning message with
+ placeholders for the old parameter, new parameter, and function name.
+ **message_kwargs: Additional keyword arguments that can be used to customize
+ the warning message.
+
+ Returns:
+ Callable: A decorator function that can be applied to mark a function's
+ parameter as deprecated.
+
+ Examples:
+ ```python
+ @deprecated_parameter(
+ old_parameter=
,
+ new_parameter=
+ )
+ def example_function():
+ pass
+
+ # call function using deprecated parameter
+ example_function(=)
+ ```
+ """
+
+ def decorator(func):
+ @functools.wraps(func)
+ def wrapper(*args, **kwargs):
+ if old_parameter in kwargs:
+ if args and hasattr(args[0], "__class__"):
+ class_name = args[0].__class__.__name__
+ function_name = f"{class_name}.{func.__name__}"
+ else:
+ function_name = func.__name__
+
+ warnings.warn(
+ message=warning_message.format(
+ function_name=function_name,
+ old_parameter=old_parameter,
+ new_parameter=new_parameter,
+ **message_kwargs,
+ ),
+ category=DeprecationWarning,
+ stacklevel=2,
+ )
+
+ kwargs[new_parameter] = map_function(kwargs.pop(old_parameter))
+
+ return func(*args, **kwargs)
+
+ return wrapper
+
+ return decorator
def deprecated(reason: str):
diff --git a/test/detection/test_polygonzone.py b/test/detection/test_polygonzone.py
new file mode 100644
index 00000000..2aae955f
--- /dev/null
+++ b/test/detection/test_polygonzone.py
@@ -0,0 +1,92 @@
+from contextlib import ExitStack as DoesNotRaise
+from test.test_utils import mock_detections
+
+import numpy as np
+import pytest
+
+import supervision as sv
+
+DETECTION_BOXES = np.array(
+ [
+ [35.0, 35.0, 65.0, 65.0],
+ [60.0, 60.0, 90.0, 90.0],
+ [85.0, 85.0, 115.0, 115.0],
+ [110.0, 110.0, 140.0, 140.0],
+ [135.0, 135.0, 165.0, 165.0],
+ [160.0, 160.0, 190.0, 190.0],
+ [185.0, 185.0, 215.0, 215.0],
+ [210.0, 210.0, 240.0, 240.0],
+ [235.0, 235.0, 265.0, 265.0],
+ ],
+ dtype=np.float32,
+)
+
+DETECTIONS = mock_detections(
+ xyxy=DETECTION_BOXES, class_id=np.array([0, 0, 0, 0, 0, 0, 0, 0, 0])
+)
+
+POLYGON = np.array([[100, 100], [200, 100], [200, 200], [100, 200]])
+FRAME_RESOLUTION = (300, 300)
+
+
+@pytest.mark.parametrize(
+ "detections, polygon_zone, expected_results, exception",
+ [
+ (
+ DETECTIONS,
+ sv.PolygonZone(
+ POLYGON,
+ FRAME_RESOLUTION,
+ triggering_anchors=(
+ sv.Position.TOP_LEFT,
+ sv.Position.TOP_RIGHT,
+ sv.Position.BOTTOM_LEFT,
+ sv.Position.BOTTOM_RIGHT,
+ ),
+ ),
+ np.array(
+ [False, False, False, True, True, True, False, False, False], dtype=bool
+ ),
+ DoesNotRaise(),
+ ), # Test all four corners
+ (
+ DETECTIONS,
+ sv.PolygonZone(
+ POLYGON,
+ FRAME_RESOLUTION,
+ ),
+ np.array(
+ [False, False, True, True, True, True, False, False, False], dtype=bool
+ ),
+ DoesNotRaise(),
+ ), # Test default behaviour when no anchors are provided
+ (
+ DETECTIONS,
+ sv.PolygonZone(
+ POLYGON, FRAME_RESOLUTION, triggering_position=sv.Position.BOTTOM_CENTER
+ ),
+ np.array(
+ [False, False, True, True, True, True, False, False, False], dtype=bool
+ ),
+ DoesNotRaise(),
+ ), # Test default behaviour with deprecated api.
+ (
+ sv.Detections.empty(),
+ sv.PolygonZone(
+ POLYGON,
+ FRAME_RESOLUTION,
+ ),
+ np.array([], dtype=bool),
+ DoesNotRaise(),
+ ), # Test empty detections
+ ],
+)
+def test_polygon_zone_trigger(
+ detections: sv.Detections,
+ polygon_zone: sv.PolygonZone,
+ expected_results: np.ndarray,
+ exception: Exception,
+) -> None:
+ with exception:
+ in_zone = polygon_zone.trigger(detections)
+ assert np.all(in_zone == expected_results)