pyproject.toml

[project]
name = "ellipse-rcnn"
version = "0.2.2"
description = "An implementation of the Ellipse R-CNN object detection model in PyTorch, based on 'Ellipse R-CNN: Learning to Infer Elliptical Object from Clustering and Occlusion' by Dong et al."
authors = [
    { name = "Wouter Doppenberg", email = "wouterdoppenberg@gmail.com" }
]
license = { text = "MIT" }
requires-python = ">=3.12"
dependencies = [
    "torch>=2.5.1",
    "torchvision>=0.20.1",
]
keywords = ["ellipse", "rcnn", "deep learning", "computer vision", "PyTorch"]
homepage = "https://github.com/wdoppenberg/ellipse-rcnn"
repository = "https://github.com/wdoppenberg/ellipse-rcnn.git"
documentation = "https://github.com/wdoppenberg/ellipse-rcnn"
readme = "README.md"

[dependency-groups]
dev = [
    "jupyter>=1.1.1",
    "pre-commit>=4.0.1",
    "pyqt6>=6.8.0",
    "pytest>=8.3.4",
    "ruff>=0.8.4",
]

[project.scripts]

[project.optional-dependencies]
hf = [
    "huggingface-hub>=0.27.1",
    "safetensors>=0.5.2",
]
train = [
    "h5py>=3.12.1",
    "matplotlib>=3.10.0",
    "pandas>=2.2.3",
    "pytorch-lightning>=2.5.0.post0",
    "tensorboard>=2.18.0",
    "torch-tb-profiler>=0.4.3",
    "torchmetrics>=1.6.1",
    "typer>=0.15.1",
    "seaborn>=0.13.2",
]


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

[tool.ruff.lint.per-file-ignores]
"__init__.py" = ["F401"]
"test/**" = ["ARG", "S", "D", "ANN"]

[tool.ruff.lint.mccabe]
max-complexity = 10

[tool.ruff.lint.pydocstyle]
convention = "numpy"

[tool.mypy]
python_version = "3.12"
warn_return_any = true
warn_unused_configs = true