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pyproject.toml
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pyproject.toml
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[tool.poetry]
name = "fast-plate-ocr"
version = "0.1.6"
description = "Fast & Lightweight OCR for vehicle license plates."
authors = ["ankandrew <61120139+ankandrew@users.noreply.github.com>"]
readme = "README.md"
repository = "https://github.com/ankandrew/fast-plate-ocr/"
documentation = "https://ankandrew.github.io/fast-plate-ocr"
keywords = ["plate-recognition", "license-plate-recognition", "license-plate-ocr"]
license = "MIT"
classifiers = [
"Typing :: Typed",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Science/Research",
"Operating System :: OS Independent",
"Topic :: Software Development",
"Topic :: Scientific/Engineering",
"Topic :: Software Development :: Libraries",
"Topic :: Software Development :: Build Tools",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
"Topic :: Software Development :: Libraries :: Python Modules",
]
[tool.poetry.dependencies]
python = "^3.10"
# Packages required for doing inference
numpy = ">=1.20"
onnxruntime = ">=1.4.0"
opencv-python = "*"
pyyaml = ">=5.1"
tqdm = "*"
rich = "*"
# By default, we install onnx CPU runtime
# Since onnxruntime-gpu depends on CUDA, don't install on macOS
onnxruntime-gpu = { version = ">=1.4.0", markers = "sys_platform != 'darwin'", optional = true}
# Training packages are optional
albumentations = { version = "*", optional = true }
click = { version = "*", optional = true }
keras = { version = ">=3.1.1", optional = true }
matplotlib = { version = "*", optional = true }
pandas = { version = "*", optional = true }
pydantic = { version = "^2.0.0", optional = true }
tensorboard = { version = "*", optional = true }
tensorflow = { version = "*", optional = true }
tf2onnx = { version = "*", optional = true }
torch = { version = "*", optional = true }
# Optional packages for creating the docs
mkdocs-material = { version = "*", optional = true }
mkdocstrings = {version = "*", extras = ["python"], optional = true}
mike = { version = "*", optional = true }
onnxsim = { version = ">0.4.10", optional = true }
[tool.poetry.extras]
inference-gpu = ["onnxruntime-gpu"]
train = [
"albumentations",
"click",
"keras",
"matplotlib",
"pandas",
"pydantic",
"tensorboard",
"tensorflow",
"tf2onnx",
"torch",
"onnxsim",
]
docs = ["mkdocs-material", "mkdocstrings", "mike"]
[tool.poetry.group.test.dependencies]
pytest = "*"
[tool.poetry.group.dev.dependencies]
mypy = "*"
ruff = "*"
pandas-stubs = "^2.2.0.240218"
pylint = "*"
types-pyyaml = "^6.0.12.20240311"
[tool.poetry.scripts]
fast_plate_ocr = "fast_plate_ocr.cli.cli:main_cli"
[tool.ruff]
line-length = 100
target-version = "py310"
[tool.ruff.lint]
select = [
# pycodestyle
"E",
"W",
# Pyflakes
"F",
# pep8-naming
"N",
# pyupgrade
"UP",
# flake8-bugbear
"B",
# flake8-simplify
"SIM",
# flake8-unused-arguments
"ARG",
# Pylint
"PL",
# Perflint
"PERF",
# Ruff-specific rules
"RUF",
# pandas-vet
"PD",
]
ignore = ["N812", "PLR2004", "PD011"]
fixable = ["ALL"]
unfixable = []
[tool.ruff.lint.pylint]
max-args = 8
[tool.ruff.format]
line-ending = "lf"
[tool.mypy]
disable_error_code = "import-untyped"
[tool.pylint.typecheck]
generated-members = ["cv2.*"]
signature-mutators = [
"click.decorators.option",
"click.decorators.argument",
"click.decorators.version_option",
"click.decorators.help_option",
"click.decorators.pass_context",
"click.decorators.confirmation_option"
]
[tool.pylint.format]
max-line-length = 100
[tool.pylint."messages control"]
disable = ["missing-class-docstring", "missing-function-docstring"]
[tool.pylint.design]
max-args = 8
min-public-methods = 1
[tool.pylint.basic]
no-docstring-rgx = "^__|^test_"
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"