pyproject.toml

[project]
name = "labelplayground"
version = "0.1.0"
description = "Auto-labeling pipeline using OWLv2 + SAM2 for household object detection"
readme = "README.md"
requires-python = "==3.11.*"
license = { text = "MIT" }
authors = [{ name = "Erick Rosas" }]

dependencies = [
    # Deep learning — device-agnostic (CUDA / MPS / CPU)
    "torch>=2.2.0",
    "torchvision>=0.17.0",

    # Hugging Face — OWLv2 + SAM2 models & processors (Apache 2.0)
    "transformers>=4.45.0",  # SAM2 support added in 4.45

    # Computer vision
    "pillow>=10.3.0",
    "opencv-python>=4.9.0",  # mask → COCO polygon via cv2.findContours (SAM2)

    # Data & utilities
    "numpy>=1.26.0",
    "pydantic>=2.7.0",
    "pydantic-settings>=2.3.0",

    # CLI
    "click>=8.1.7",
    "tqdm>=4.66.0",

    # Environment
    "python-dotenv>=1.0.1",

    # Web UI
    "gradio>=6.0.0",
]

[project.scripts]
autolabel-detect = "scripts.run_detection:main"
autolabel-export = "scripts.export_coco:main"

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

[tool.hatch.build.targets.wheel]
packages = ["autolabel", "scripts"]