pyproject.toml

[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

[project]
name = "albumentationsx"

version = "2.4.9"

description = "Fast, flexible, and advanced augmentation library for deep learning, computer vision, and medical imaging. Albumentations offers a wide range of transformations for both 2D (images, masks, bboxes, keypoints) and 3D (volume data, volumetric masks, keypoints) data, with optimized performance and seamless integration into ML workflows. Available under AGPL-3.0-only or a commercial license with agreed coverage for your team, products, and deployments."
readme = "README.md"
keywords = [
  "2D augmentation",
  "3D augmentation",
  "aerial photography",
  "anomaly detection",

  "artificial intelligence",

  "autonomous driving",
  "bounding boxes",
  "classification",
  "computer vision",
  "computer vision library",
  "data augmentation",

  "data preprocessing",
  "data science",
  "deep learning",
  "deep learning library",

  "depth estimation",
  "face recognition",
  "fast augmentation",
  "image augmentation",
  "image processing",
  "image transformation",
  "images",
  "instance segmentation",
  "keras",
  "keypoint detection",
  "keypoints",
  "machine learning",
  "machine learning tools",
  "masks",
  "medical imaging",
  "microscopy",
  "object counting",
  "object detection",
  "optimized performance",
  "panoptic segmentation",
  "pose estimation",
  "python library",
  "pytorch",
  "quality inspection",

  "real-time processing",

  "robotics vision",
  "satellite imagery",
  "semantic segmentation",
  "tensorflow",
  "volumetric data",
  "volumetric masks",

]
license = "AGPL-3.0-only"
license-files = [
  "LICENSE",
  "LICENSING.md",
  "THIRD_PARTY_NOTICES.md",
  "THIRD_PARTY_LICENSES/MIT-Albumentations-2.0.8.txt",
]

maintainers = [ { name = "Vladimir Iglovikov" } ]

authors = [ { name = "Vladimir Iglovikov" } ]
requires-python = ">=3.10"

classifiers = [
  "Development Status :: 5 - Production/Stable",

  "Intended Audience :: Developers",
  "Intended Audience :: Healthcare Industry",
  "Intended Audience :: Information Technology",

  "Intended Audience :: Science/Research",

  "Operating System :: OS Independent",

  "Programming Language :: Python",
  "Programming Language :: Python :: 3 :: Only",
  "Programming Language :: Python :: 3.10",
  "Programming Language :: Python :: 3.11",
  "Programming Language :: Python :: 3.12",
  "Programming Language :: Python :: 3.13",
  "Programming Language :: Python :: 3.14",
  "Topic :: Scientific/Engineering",
  "Topic :: Scientific/Engineering :: Artificial Intelligence",
  "Topic :: Scientific/Engineering :: Astronomy",
  "Topic :: Scientific/Engineering :: Atmospheric Science",

  "Topic :: Scientific/Engineering :: Bio-Informatics",
  "Topic :: Scientific/Engineering :: Image Processing",
  "Topic :: Scientific/Engineering :: Physics",
  "Topic :: Scientific/Engineering :: Visualization",
  "Topic :: Software Development :: Libraries",
  "Topic :: Software Development :: Libraries :: Python Modules",

  "Typing :: Typed",
]

dependencies = [
  "albucore==0.2.18",
  "numkong>=7.8.0",
  "numpy>=2.2.6",
  "pydantic>=2.12.4",
  "pyyaml>=6.0.3",
  "scipy>=1.15.3",
  "typing-extensions>=4.9.0",
]

[project.optional-dependencies]
contrib = ["opencv-contrib-python>=5.0.0.93"]
contrib-headless = ["opencv-contrib-python-headless>=5.0.0.93"]
gui = ["opencv-python>=5.0.0.93"]
headless = ["opencv-python-headless>=5.0.0.93"]
hub = ["huggingface-hub"]
pillow = ["pillow"]
pyvips = ["pyvips[binary]"]
text = ["pillow"]

[tool.uv.sources]
torch = { index = "pytorch-cpu" }

[[tool.uv.index]]
name = "pytorch-cpu"
url = "https://download.pytorch.org/whl/cpu"
explicit = true

[dependency-groups]
ci-test = [
  "albu-spec>=0.0.6",
  "deepdiff>=9.1.0",
  "defusedxml>=0.7.1",
  "eval-type-backport>=0.4.0",
  "huggingface-hub>=1.27.0",
  "hypothesis>=6.165.5",
  "opencv-python-headless>=5.0.0.93",
  "pillow>=12.3.0",
  "pyvips[binary]>=3.1.1",
  "pytest>=9.1.1",
  "pytest-mock>=3.15.1",
  "pytest-randomly>=4.1.0",
  "pytest-xdist>=3.8.0",
  "pytz>=2026.3.post1",
  "requests>=2.34.2",
  "scikit-image>=0.25.2",
  "scikit-learn>=1.7.2",
  "tomli>=2.4.1",
]
ci-quality = [
  "defusedxml>=0.7.1",
  "google-docstring-parser>=0.0.11",
  "hypothesis>=6.165.5",
  "opencv-python-headless>=5.0.0.93",
  "packaging>=26.3",
  "pillow>=12.3.0",
  "pre-commit>=4.6.2",
  "pytest>=9.1.1",
  "ruff>=0.16.2",
  "tomli>=2.4.1",
]
ci-types = [
  "mypy>=2.3.0",
  "opencv-python-headless>=5.0.0.93",
  "pre-commit>=4.6.2",
  "pyrefly>=1.2.0",
  "types-PyYAML>=6.0.12.20260724",
  "types-setuptools>=84.0.0.20260812",
]
ci-security = [
  "pip-audit>=2.10.1",
  "zizmor>=1.29.0",
]
ci-package = [
  "pytest>=9.1.1",
  "twine>=7.0.0",
]
ci-benchmark = [
  "asv",
  "opencv-python-headless>=5.0.0.93",
]
ci-release = [
  { include-group = "ci-benchmark" },
  { include-group = "ci-test" },
  { include-group = "ci-package" },
  { include-group = "ci-security" },
  "cyclonedx-bom>=7.3.1",
]
ci-torch-cpu = [
  "torch>=2.13.0",
]
dev = [
  { include-group = "ci-test" },
  { include-group = "ci-quality" },
  { include-group = "ci-types" },
  { include-group = "ci-security" },
  { include-group = "ci-package" },
  { include-group = "ci-benchmark" },
  { include-group = "ci-release" },
]

[project.urls]
Homepage = "https://albumentations.ai"
Documentation = "https://albumentations.ai/docs/"
"Commercial Licensing" = "https://albumentations.ai/pricing"
Repository = "https://github.com/albumentations-team/AlbumentationsX"
Changelog = "https://github.com/albumentations-team/AlbumentationsX/releases"
Discord = "https://discord.gg/AKPrrDYNAt"
"Bug Tracker" = "https://github.com/albumentations-team/AlbumentationsX/issues"

[tool.hatch.build.targets.wheel]
packages = ["albumentations"]

[tool.hatch.build]
exclude = [
  "CLA.md",
  "tests",
  "tools",
  "benchmark",
  "docs",
  "legal",
  "THIRD_PARTY_LICENSES/OFL-1.1.txt",
  ".github",
  ".codex",
  "conda.recipe",
]

[tool.ruff]
target-version = "py310"

line-length = 120
indent-width = 4

exclude = [
  ".bzr",
  ".direnv",
  ".eggs",
  ".git",
  ".git-rewrite",
  ".hg",
  ".ipynb_checkpoints",
  ".mypy_cache",
  ".nox",
  ".pants.d",
  ".pyenv",
  ".pytest_cache",
  ".pytype",
  ".ruff_cache",
  ".svn",
  ".tox",
  ".venv",
  ".vscode",
  "__pypackages__",
  "_build",
  "buck-out",
  "build",
  "dist",
  "node_modules",
  "setup.py",
  "site",
  "site-packages",
  "venv",
]

format.indent-style = "space"
format.quote-style = "double"
format.line-ending = "auto"
format.skip-magic-trailing-comma = false
lint.select = [ "ALL" ]
lint.ignore = [
  "ANN001",
  "ANN204",
  "ANN401",
  "ARG001",
  "ARG002",
  "B006",
  "B008",
  "B027",
  "COM812",
  "CPY001",  # The repository carries one canonical AGPL notice instead of per-module copyright headers.
  "D102",    # We handle method docstrings with custom hook
  "D104",
  "D105",
  "D106",
  "D107",
  "D203",
  "D205",
  "D213",
  "D400",
  "D401",
  "D404",
  "D415",
  "EM101",
  "EM102",
  "F403",
  "FBT001",
  "FBT002",
  "FBT003",
  "G004",
  "PLC0415",
  "PLR0913",
  "PLR0917", # Preserve the positional compatibility of existing public transforms and functional APIs.
  "PLR2004",
  "S310",
  "S311",
  "S608",
  "TC001",
  "TC002",
  "TC003",
  "TRY003",
]

lint.per-file-ignores."albumentations/augmentations/mixing/functional.py" = ["E501"]
lint.per-file-ignores."tools/*" = [
  "ANN201",
  "D100",
  "D101",
  "D103",
  "INP001",
  "SLF001",
  "T201",
]
lint.per-file-ignores."tests/*" = [
  "A001",
  "A002",
  "ANN",
  "ARG005",
  "B017",
  "B904",
  "BLE001",
  "C401",
  "C408",
  "C901",
  "D100",
  "D101",
  "D103",
  "D417",
  "E501",
  "ERA001",
  "F811",
  "INP001",
  "N802",
  "N803",
  "N806",
  "N812",
  "NPY002",
  "PERF401",
  "PGH003",
  "PLR0912",
  "PT006",
  "PT007",
  "PT011",
  "PT018",
  "PT030",
  "PT031",
  "RUF003",
  "RUF005",
  "RUF059",
  "S101",
  "S105",
  "S324",
  "SIM102",
  "SIM108",
  "SIM117",
  "SLF001",
  "T201",
]

[tool.mypy]
plugins = [ "pydantic.mypy" ]

python_version = "3.10"
ignore_missing_imports = true
follow_imports = "silent"
warn_redundant_casts = true
warn_unused_ignores = true
disallow_any_generics = true
check_untyped_defs = true
no_implicit_reexport = true
disable_error_code = [ "valid-type" ]

disallow_untyped_defs = true

# Strict checking for the instance-binding boundary modules so the StackedMasks4D NewType brand
# (and other structural contracts in Compose's transform loop / mixing transforms) keep being
# enforced at typecheck time. Any apply_to_masks override that returns a raw np.ndarray instead
# of StackedMasks4D will break CI here via the default [return-value] / [assignment] errors.
# warn_return_any is intentionally NOT enabled because numpy's typing returns Any from most ops,
# which would drown the StackedMasks4D signal in unrelated noise.
[[tool.mypy.overrides]]
module = [
  "albumentations.core.composition",
  "albumentations.augmentations.mixing.transforms",
  "albumentations.augmentations.mixing.functional",
  "albumentations.augmentations.geometric.transforms",
  "albumentations.augmentations.geometric.flip",
  "albumentations.augmentations.crops.transforms",
  "albumentations.pytorch.transforms",
]
strict_equality = true
warn_unused_ignores = true

[tool.pyrefly]
python-version = "3.10"
project-includes = ["albumentations"]
ignore-missing-imports = [
  "PIL",
  "PIL.Image",
  "huggingface_hub",
  "huggingface_hub.utils",
  "pyvips",
  "torch",
  "torch.utils.data",
]
project-excludes = [
  "**/__pycache__",
  ".venv",
  "build",
  "dist",
]

[tool.pydocstyle]

lint.explicit-preview-rules = true
lint.fixable = [ "ALL" ]
lint.unfixable = [  ]
lint.dummy-variable-rgx = "^(_+|(_+[a-zA-Z0-9_]*[a-zA-Z0-9]+?))$"
lint.pydocstyle.convention = "google"
lint.pydocstyle.ignore-magic-methods = true

[tool.albumentations.maintainers]
emeritus = [
  "Alexander Buslaev",
  "Alex Parinov",
  "Eugene Khvedchenya",
  "Mikhail Druzhinin",
]

[tool.pydantic-mypy]
init_forbid_extra = true
init_typed = true
warn_required_dynamic_aliases = true

[tool.codeflash]
# All paths are relative to this pyproject.toml's directory.
module-root = "albumentations"
tests-root = "tests"
test-framework = "pytest"
ignore-paths = [  ]
formatter-cmds = [ "ruff check --exit-zero --fix $file", "ruff format $file" ]

[tool.pytest.ini_options]
minversion = "9.0"
testpaths = ["tests"]
python_files = ["test_*.py"]
python_classes = ["Test*"]
python_functions = ["test_*"]
addopts = [
    "--strict-markers",
    "--tb=short",
    "--strict-config",
]
markers = [
    "slow: marks tests as slow (deselect with '-m \"not slow\"')",
    "pytorch: tests that require the PyTorch dependency profile",
    "obb: tests for oriented bounding boxes",
    "property: property-based invariant tests",
    "regression: transform regression harness tests",
]
filterwarnings = [
    "ignore::UserWarning",
    "ignore::DeprecationWarning:torch.*",
    "ignore::pytest_benchmark.logger.PytestBenchmarkWarning",
]

# Legacy/alternate config key for google-docstring-parser (same package).
[tool.google_docstring_parser]
paths = [ "albumentations" ]
require_param_types = true
exclude_files = [ "__init__.py" ]
verbose = false
check_references = true

# Pre-commit hook check-google-docstrings reads this section (see package README).
# Public transform preview metadata is checked separately in tests/test_docstrings.py.
# Each physical line must be <= 120 chars (ruff E501); do not disable E501 or use # noqa: E501.
# See .codex/skills/docstring-deep-dive and docs/contributing/coding_guidelines.md.
[tool.docstring_checker]
paths = [ "albumentations" ]
require_param_types = true
check_references = true
check_type_consistency = true
exclude_files = [ "__init__.py" ]
verbose = false

[tool.ax-rules.rules]
coding-guidance = true
docstring-format = true
naming-conflicts = true
public-transform-docstrings = true
readme-transform-docs = true