pyproject.toml

[build-system]
requires = ["setuptools>=42", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "rfdetr"
version = "1.7.0.rc0"
description = "RF-DETR"
readme = "README.md"
authors = [
    {name = "Roboflow, Inc", email = "develop@roboflow.com"}
]
license = {text = "Apache License 2.0"}
requires-python = ">=3.10"
classifiers = [
    "Development Status :: 4 - Beta",
    "Intended Audience :: Developers",
    "Intended Audience :: Education",
    "Intended Audience :: Science/Research",
    "License :: OSI Approved :: Apache Software License",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
    "Programming Language :: Python :: 3.12",
    "Programming Language :: Python :: 3.13",
    "Programming Language :: Python :: 3 :: Only",
    "Topic :: Software Development",
    "Topic :: Scientific/Engineering",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
    "Typing :: Typed",
    "Operating System :: POSIX",
    "Operating System :: Unix",
    "Operating System :: MacOS"
]
keywords = ["machine-learning", "deep-learning", "vision", "ML", "DL", "AI", "DETR", "RF-DETR", "Roboflow"]

dependencies = [
    "requests",                        # weight download from remote URLs
    "torch>=2.2.0",                    # core tensor ops and model forward pass
    "torchvision>=0.17.0",             # image transforms and ops (aligned with torch>=2.2.0)
    "tqdm",                            # progress bars during weight download
    "transformers>=5.1.0,<6.0.0",     # DINOv2 backbone loading
    "pydantic>=2.0,<3",               # ModelConfig / TrainConfig validation
    "supervision",                     # inference output (Detections, Masks)
    "pyDeprecate>=0.6,<0.8",             # deprecation warnings for legacy APIs; >=0.6 for deprecated_class
]

[project.optional-dependencies]
lora = [
    "peft",                            # LoRA backbone fine-tuning
]
train = [
    "peft",                            # LoRA backbone fine-tuning (available during training)
    "pytorch_lightning>=2.6,<3",
    "torchmetrics[detection]>=1.2",
    "faster-coco-eval>=1.7.2",
    "pycocotools",
    "scipy",
    "albumentations>=1.4.24,<3.0.0",
    "roboflow",
    "rf100vl",
]
onnx = [
    "onnx>=1.16.0,<1.20",
    "onnxsim<0.6.0",  # TODO: onnxsim 0.6.0+ hangs on install
    "onnx_graphsurgeon",
    "onnxruntime",
    "polygraphy",
]
trt = [
    "pycuda",
    "onnxruntime-gpu",
    "tensorrt>=8.6.1",
    "polygraphy",
]
tflite = [
    "onnx2tf>=1.26.0,<2.0.0",
    "flatbuffers>=23.5.26",
    "onnx>=1.16.0,<1.20",
    "tf-keras>=2.16.0",
    "tensorflow>=2.16.0",
]
kornia = [
    "kornia>=0.7,<1",              # GPU-side augmentation via on_after_batch_transfer
]
loggers = [
    "tensorboard>=2.13.0",
    "protobuf>=3.20.0,<4.0.0",  # Pins protobuf below 4.x to avoid TensorBoard descriptor crash with protobuf>=4 (see #844)
    "wandb",
    "mlflow",
    "clearml",
]
visual = [
    "matplotlib",
    "pandas",
    "seaborn",
]
cli = ["jsonargparse[signatures]>=4.27.7"]
plus = ["rfdetr_plus>=1.0.1, <2.0.0"]

[dependency-groups]
# TODO: Temporary: GPU runner only has CUDA 12.8 driver (12080); torch>=2.11 requires a newer driver.
#   Remove this group and the --group ci-gpu-pin references in CI once the driver is updated.
#   Does not affect users installing rfdetr from PyPI.
ci-gpu-pin = [
    "torch<2.11",
]

build = [
    "twine>=5.1.1",
    "wheel>=0.40",
    "build>=0.10"
]

tests = [
  "pytest>=7.2,<9",
  "pytest-cov>=4,<8",
  "pytest-xdist>=3.6,<4",
  "pytest-rerunfailures>=10,<15",
  "pytest-timeout>=2,<3",
  "pytest-doctestplus>=1.2,<2",
  "tomli>=2.0; python_version < '3.11'",
]

typing = [
    "mypy>=1.0",
    # mypy 1.19.x can crash while processing NumPy 2.4 symbols in strict mode.
    "numpy<2.4",
    "types-PyYAML",
    "types-requests",
    "types-tqdm",
]

docs = [
    "mkdocs-material[imaging]>=9.7",
    "mkdocstrings>=0.25.2,<0.30.0",
    "mkdocstrings-python>=1.10.9",
    "mike>=2.0.0",
    "mkdocs-jupyter>=0.24.3",
    "mkdocs-git-committers-plugin-2>=2.4.1",
    "mkdocs-git-revision-date-localized-plugin>=1.2.4",
    "tomli>=2.0; python_version < '3.11'",
]

[project.urls]
Homepage = "https://github.com/roboflow/rf-detr"

[project.scripts]
rfdetr = "rfdetr.cli:main"

[tool.setuptools.packages.find]
where = ["src"]
include = ["rfdetr*"]

[tool.setuptools]
include-package-data = false

[tool.setuptools.package-data]
rfdetr = ["py.typed", "models/backbone/dinov2_configs/*.json"]

[tool.ruff]
fix = true
line-length = 120
target-version = "py310"

[tool.ruff.lint]
select = [
    "E",  # pycodestyle errors
    "W",  # pycodestyle warnings
    "F",  # pyflakes
    "I",  # isort
    "N",  # pep8-naming: lowercase variables (N806) and arguments (N803)
]
extend-select = [
    "RUF100",  # yesqa
]
ignore = [
    "E722",  # todo: Do not use bare `except`
]

[tool.ruff.lint.per-file-ignores]
"notebooks/*.py" = ["E402"]  # cell-local imports are intentional in percent-format scripts

[tool.pytest.ini_options]
addopts = [
    "-v",                   # verbose output
    "--color=yes",          # colored output
    "--doctest-plus",       # run doctests from all modules (pytest-doctestplus)
]
pythonpath = ["src"]
markers = [
    "gpu: tests that require GPU or are slow on CPU",
    "flaky: tests that may fail due to nondeterminism",
    "tflite: tests requiring onnx2tf and TFLite dependencies",
]
filterwarnings = [
    # pytest-xdist workers close their channel before teardown completes;
    # this is a known false-positive that does not affect test results.
    "ignore::pluggy.PluggyTeardownRaisedWarning",
]

[tool.codespell]
skip = "*.pth"

[tool.mypy]
python_version = "3.10"
ignore_missing_imports = false
explicit_package_bases = true
strict = true
mypy_path = "src"
exclude = [
  "^docs/(hooks|scripts)/",
]
overrides = [
  { module = [
    "tests.*",
    "einops", "einops.*",
    "matplotlib", "matplotlib.*",
    "pandas", "pandas.*",
    "seaborn", "seaborn.*",
  ], ignore_errors = true },
  { module = [
    "torchvision", "torchvision.*",
    "pycocotools", "pycocotools.*",
    "timm", "timm.*",
    "einops", "einops.*",
    "deprecate", "deprecate.*",
    "matplotlib", "matplotlib.*",
    "pandas", "pandas.*",
    "requests", "requests.*",
    "seaborn", "seaborn.*",
    "tqdm", "tqdm.*",
    "kornia", "kornia.*",
    "onnx", "onnx.*",
    "onnx2tf", "onnx2tf.*",
    "tflite_runtime", "tflite_runtime.*",
    "tensorflow", "tensorflow.*",
  ], ignore_missing_imports = true },
  # Modules with pre-existing type errors — ignored until incrementally fixed.
  { module = [
    "rfdetr",
    "rfdetr._namespace",
    "rfdetr.assets.model_weights",
    "rfdetr.config",
    "rfdetr.datasets._develop",
    "rfdetr.datasets.coco",
    "rfdetr.datasets.save_grids",
    "rfdetr.datasets.synthetic",
    "rfdetr.datasets.transforms",
    "rfdetr.datasets.yolo",
    "rfdetr.detr",
    "rfdetr.evaluation.coco_eval",
    "rfdetr.evaluation.matching",
    "rfdetr.export._onnx.exporter",
    "rfdetr.export._onnx.symbolic",
    "rfdetr.export.benchmark",
    "rfdetr.export.main",
    "rfdetr.export.tensorrt",
    "rfdetr.models.backbone",
    "rfdetr.models.backbone.backbone",
    "rfdetr.models.backbone.base",
    "rfdetr.models.backbone.dinov2",
    "rfdetr.models.backbone.dinov2_with_windowed_attn",
    "rfdetr.models.backbone.projector",
    "rfdetr.models.criterion",
    "rfdetr.models.heads.detection",
    "rfdetr.models.heads.segmentation",
    "rfdetr.models.lwdetr",
    "rfdetr.models.math",
    "rfdetr.models.matcher",
    "rfdetr.models.ops.functions.ms_deform_attn_func",
    "rfdetr.models.ops.modules.ms_deform_attn",
    "rfdetr.models.position_encoding",
    "rfdetr.models.postprocess",
    "rfdetr.models.transformer",
    "rfdetr.models.weights",
    "rfdetr.platform",
    "rfdetr.platform.downloads",
    "rfdetr.platform.models",
    "rfdetr.training.callbacks.best_model",
    "rfdetr.training.callbacks.coco_eval",
    "rfdetr.training.callbacks.drop_schedule",
    "rfdetr.training.callbacks.ema",
    "rfdetr.training.cli",
    "rfdetr.training.drop_schedule",
    "rfdetr.training.model_ema",
    "rfdetr.training.module_data",
    "rfdetr.training.module_model",
    "rfdetr.training.trainer",
    "rfdetr.utilities.distributed",
    "rfdetr.utilities.logger",
    "rfdetr.utilities.state_dict",
    "rfdetr.utilities.tensors",
    "rfdetr.variants",
  ], ignore_errors = true },
]