[project]
name = "proxyclip-tpami"
version = "1.0.0"
description = "ProxyCLIP TPAMI - Open-Vocabulary Semantic Segmentation with CLIP"
readme = "../README.md"
requires-python = ">=3.9,<3.12"

dependencies = [
    # ============== PyTorch 核心 ==============
    # 注意: PyTorch 需要根据目标机器的 CUDA 版本单独安装
    # 这里不包含 torch/torchvision/torchaudio，需要在 setup 脚本中单独处理
    
    # ============== MMSeg 生态系统 ==============
    "mmcv==2.1.0",
    "mmengine==0.10.4",
    "mmsegmentation==1.2.2",
    
    # ============== CLIP & 视觉模型核心 ==============
    "ftfy>=6.1.0",
    "regex>=2024.0.0",
    "timm>=1.0.0",
    "einops>=0.8.0",
    "sentencepiece>=0.2.0",
    "protobuf>=3.20.0,<4.0.0",
    "huggingface-hub>=0.20.0",
    
    # ============== 图像处理 ==============
    "Pillow>=9.4.0",
    "opencv-python>=4.8.0",
    "numpy>=1.24.0,<2.0.0",
    "scipy>=1.10.0",
    "scikit-image>=0.18.0",
    
    # ============== 数据处理与工具 ==============
    "tqdm>=4.65.0",
    "PyYAML>=6.0",
    "openpyxl>=3.1.0",
    "pandas>=2.0.0",
    "addict>=2.4.0",
    "yapf>=0.40.0",
    
    # ============== 鲁棒性评估 ==============
    # imagecorruptions 本地安装
    
    # ============== 其他工具 ==============
    "termcolor>=2.0.0",
    "terminaltables>=3.1.0",
    "rich>=13.0.0",
]

[project.optional-dependencies]
dev = [
    "pytest>=7.0.0",
    "black>=24.0.0",
    "ruff>=0.1.0",
]

training = [
    "tensorboard>=2.15.0",
    "tensorboardX>=2.6.0",
    "pytorch-lightning>=2.0.0",
    "accelerate>=1.0.0",
]

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

[tool.uv]
# UV 特定配置
dev-dependencies = [
    "pytest>=7.0.0",
]

[tool.uv.sources]
# 如果需要从特定源安装包，可以在这里配置