downstream/ProxyCLIP_TPAMI/env_setup/setup_env.sh

#!/bin/bash
# =====================================================
# ProxyCLIP TPAMI - 一键环境配置脚本
# =====================================================
# 使用方法:
#   chmod +x setup_env.sh
#   ./setup_env.sh [--cuda-version 11.8|12.1|12.4] [--env-name proxyclip_tpami]
# =====================================================

set -e  # 遇到错误立即退出

# 默认参数
CUDA_VERSION="11.8"
ENV_NAME="proxyclip_tpami"
PYTHON_VERSION="3.10"
USE_UV=true

# 解析命令行参数
while [[ $# -gt 0 ]]; do
    case $1 in
        --cuda-version)
            CUDA_VERSION="$2"
            shift 2
            ;;
        --env-name)
            ENV_NAME="$2"
            shift 2
            ;;
        --python-version)
            PYTHON_VERSION="$2"
            shift 2
            ;;
        --no-uv)
            USE_UV=false
            shift
            ;;
        -h|--help)
            echo "Usage: ./setup_env.sh [OPTIONS]"
            echo ""
            echo "Options:"
            echo "  --cuda-version    CUDA version (11.8, 12.1, 12.4). Default: 11.8"
            echo "  --env-name        Environment name. Default: proxyclip_tpami"
            echo "  --python-version  Python version. Default: 3.10"
            echo "  --no-uv           Use pip instead of uv"
            echo "  -h, --help        Show this help message"
            exit 0
            ;;
        *)
            echo "Unknown option: $1"
            exit 1
            ;;
    esac
done

# 获取脚本所在目录和项目根目录
SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
PROJECT_ROOT="$( cd "$SCRIPT_DIR/.." && pwd )"

echo "=============================================="
echo "ProxyCLIP TPAMI 环境配置"
echo "=============================================="
echo "CUDA 版本: $CUDA_VERSION"
echo "环境名称: $ENV_NAME"
echo "Python 版本: $PYTHON_VERSION"
echo "项目根目录: $PROJECT_ROOT"
echo "=============================================="

# Step 1: 检查并安装 uv (如果选择使用 uv)
if $USE_UV; then
    if ! command -v uv &> /dev/null; then
        echo "[Step 1] 安装 uv..."
        curl -LsSf https://astral.sh/uv/install.sh | sh
        export PATH="$HOME/.cargo/bin:$PATH"
    else
        echo "[Step 1] uv 已安装"
    fi
fi

# Step 2: 创建虚拟环境
echo "[Step 2] 创建虚拟环境 $ENV_NAME..."
cd "$PROJECT_ROOT"

if $USE_UV; then
    # 使用 uv 创建虚拟环境
    uv venv ".venv_$ENV_NAME" --python "$PYTHON_VERSION"
    source ".venv_$ENV_NAME/bin/activate"
else
    # 使用 conda 创建环境
    if command -v conda &> /dev/null; then
        conda create -n "$ENV_NAME" python="$PYTHON_VERSION" -y
        source "$(conda info --base)/etc/profile.d/conda.sh"
        conda activate "$ENV_NAME"
    else
        echo "错误: 未安装 conda，请先安装 conda 或使用 uv"
        exit 1
    fi
fi

# Step 3: 安装 PyTorch
echo "[Step 3] 安装 PyTorch (CUDA $CUDA_VERSION)..."
case $CUDA_VERSION in
    "11.8")
        if $USE_UV; then
            uv pip install torch==2.0.0 torchvision==0.15.1 --index-url https://download.pytorch.org/whl/cu118
        else
            pip install torch==2.0.0 torchvision==0.15.1 --index-url https://download.pytorch.org/whl/cu118
        fi
        ;;
    "12.1")
        if $USE_UV; then
            uv pip install torch==2.1.0 torchvision==0.16.0 --index-url https://download.pytorch.org/whl/cu121
        else
            pip install torch==2.1.0 torchvision==0.16.0 --index-url https://download.pytorch.org/whl/cu121
        fi
        ;;
    "12.4")
        if $USE_UV; then
            uv pip install torch==2.4.0 torchvision==0.19.0 --index-url https://download.pytorch.org/whl/cu124
        else
            pip install torch==2.4.0 torchvision==0.19.0 --index-url https://download.pytorch.org/whl/cu124
        fi
        ;;
    *)
        echo "不支持的 CUDA 版本: $CUDA_VERSION"
        echo "支持的版本: 11.8, 12.1, 12.4"
        exit 1
        ;;
esac

# Step 4: 安装核心依赖
echo "[Step 4] 安装核心依赖..."
if $USE_UV; then
    uv pip install -r "$SCRIPT_DIR/requirements.txt"
else
    pip install -r "$SCRIPT_DIR/requirements.txt"
fi

# Step 5: 安装本地包
echo "[Step 5] 安装本地包..."

# 安装 clipself (open_clip 修改版)
if [ -d "$PROJECT_ROOT/clipself" ]; then
    echo "  - 安装 clipself..."
    cd "$PROJECT_ROOT/clipself"
    if $USE_UV; then
        uv pip install -e .
    else
        pip install -e .
    fi
fi

# 安装 segment_anything
if [ -d "$PROJECT_ROOT/segment_anything" ]; then
    echo "  - 安装 segment_anything..."
    cd "$PROJECT_ROOT/segment_anything"
    if $USE_UV; then
        uv pip install -e .
    else
        pip install -e .
    fi
fi

# 安装 imagecorruptions (鲁棒性测试)
if [ -d "$PROJECT_ROOT/imagecorruptions" ]; then
    echo "  - 安装 imagecorruptions..."
    cd "$PROJECT_ROOT/imagecorruptions"
    if $USE_UV; then
        uv pip install -e .
    else
        pip install -e .
    fi
fi

cd "$PROJECT_ROOT"

# Step 6: 验证安装
echo "[Step 6] 验证安装..."
python -c "
import torch
import torchvision
import mmcv
import mmseg
import open_clip
print('=' * 50)
print('环境验证成功!')
print('=' * 50)
print(f'PyTorch: {torch.__version__}')
print(f'TorchVision: {torchvision.__version__}')
print(f'CUDA available: {torch.cuda.is_available()}')
if torch.cuda.is_available():
    print(f'CUDA version: {torch.version.cuda}')
    print(f'GPU: {torch.cuda.get_device_name(0)}')
print(f'MMCV: {mmcv.__version__}')
print(f'MMSeg: {mmseg.__version__}')
print('=' * 50)
"

echo ""
echo "=============================================="
echo "环境配置完成!"
echo "=============================================="
if $USE_UV; then
    echo "激活环境: source .venv_$ENV_NAME/bin/activate"
else
    echo "激活环境: conda activate $ENV_NAME"
fi
echo ""
echo "运行测试: python eval.py --config configs/proxyclip/cfg_ade20k.py"
echo "=============================================="