277 lines
7.8 KiB
Bash
Executable File
277 lines
7.8 KiB
Bash
Executable File
#!/bin/bash
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# BEVFusion 详细环境检查脚本（参考README.md）
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echo "=========================================="
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echo "BEVFusion 环境依赖检查"
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echo "参考：README.md Prerequisites"
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echo "=========================================="
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echo ""
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PASS=0
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FAIL=0
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# 检查函数
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check_pass() {
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echo " ✓ $1"
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((PASS++))
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}
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check_fail() {
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echo " ✗ $1"
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((FAIL++))
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}
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check_warn() {
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echo " ⚠ $1"
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}
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# 1. Python版本检查
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echo "[1/12] Python 版本 (需要 >= 3.8, < 3.9)"
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PYTHON_VERSION=$(python3 --version 2>&1 | awk '{print $2}')
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PYTHON_MAJOR=$(echo $PYTHON_VERSION | cut -d. -f1)
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PYTHON_MINOR=$(echo $PYTHON_VERSION | cut -d. -f2)
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if [ "$PYTHON_MAJOR" -eq 3 ] && [ "$PYTHON_MINOR" -eq 8 ]; then
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check_pass "Python $PYTHON_VERSION"
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else
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check_warn "Python $PYTHON_VERSION (推荐3.8.x)"
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fi
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# 2. PyTorch版本检查
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echo ""
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echo "[2/12] PyTorch 版本 (需要 >= 1.9, <= 1.10.2)"
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PYTORCH_VERSION=$(python3 -c "import torch; print(torch.__version__)" 2>/dev/null)
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if [ $? -eq 0 ]; then
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check_pass "PyTorch $PYTORCH_VERSION"
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# 检查CUDA
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CUDA_AVAILABLE=$(python3 -c "import torch; print(torch.cuda.is_available())" 2>/dev/null)
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if [ "$CUDA_AVAILABLE" = "True" ]; then
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GPU_COUNT=$(python3 -c "import torch; print(torch.cuda.device_count())" 2>/dev/null)
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check_pass "CUDA 可用，GPU数量: $GPU_COUNT"
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else
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check_fail "CUDA 不可用"
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fi
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else
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check_fail "PyTorch 未安装"
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fi
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# 3. torchpack检查
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echo ""
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echo "[3/12] torchpack (必需)"
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TORCHPACK_VERSION=$(python3 -c "import torchpack; print(torchpack.__version__)" 2>/dev/null)
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if [ $? -eq 0 ]; then
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check_pass "torchpack $TORCHPACK_VERSION"
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else
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check_fail "torchpack 未安装"
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echo " 安装: pip install torchpack"
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fi
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# 4. mmcv检查
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echo ""
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echo "[4/12] mmcv (需要 = 1.4.0)"
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MMCV_VERSION=$(python3 -c "import mmcv; print(mmcv.__version__)" 2>/dev/null)
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if [ $? -eq 0 ]; then
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if [ "$MMCV_VERSION" = "1.4.0" ]; then
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check_pass "mmcv $MMCV_VERSION"
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else
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check_warn "mmcv $MMCV_VERSION (推荐1.4.0)"
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fi
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else
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check_fail "mmcv 未安装"
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echo " 安装: pip install mmcv==1.4.0 mmcv-full==1.4.0"
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fi
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# 5. mmdet检查
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echo ""
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echo "[5/12] mmdetection (需要 = 2.20.0)"
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MMDET_VERSION=$(python3 -c "import mmdet; print(mmdet.__version__)" 2>/dev/null)
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if [ $? -eq 0 ]; then
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if [ "$MMDET_VERSION" = "2.20.0" ]; then
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check_pass "mmdetection $MMDET_VERSION"
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else
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check_warn "mmdetection $MMDET_VERSION (推荐2.20.0)"
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fi
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else
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check_fail "mmdetection 未安装"
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echo " 安装: pip install mmdet==2.20.0"
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fi
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# 6. OpenMPI和mpi4py检查
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echo ""
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echo "[6/12] OpenMPI 和 mpi4py (torchpack需要)"
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if command -v mpirun &> /dev/null; then
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OMPI_VERSION=$(mpirun --version 2>&1 | head -n 1)
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check_pass "OpenMPI: $OMPI_VERSION"
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else
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check_warn "OpenMPI 未安装（可选）"
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fi
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MPI4PY_VERSION=$(python3 -c "import mpi4py; print(mpi4py.__version__)" 2>/dev/null)
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if [ $? -eq 0 ]; then
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check_pass "mpi4py $MPI4PY_VERSION"
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else
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check_warn "mpi4py 未安装（可选）"
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fi
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# 7. Pillow检查
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echo ""
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echo "[7/12] Pillow (需要 = 8.4.0)"
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PILLOW_VERSION=$(python3 -c "from PIL import Image; import PIL; print(PIL.__version__)" 2>/dev/null)
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if [ $? -eq 0 ]; then
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if [ "$PILLOW_VERSION" = "8.4.0" ]; then
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check_pass "Pillow $PILLOW_VERSION"
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else
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check_warn "Pillow $PILLOW_VERSION (推荐8.4.0)"
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fi
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else
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check_fail "Pillow 未安装"
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fi
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# 8. nuscenes-devkit检查
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echo ""
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echo "[8/12] nuscenes-devkit (必需)"
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python3 -c "from nuscenes import NuScenes" 2>/dev/null
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if [ $? -eq 0 ]; then
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check_pass "nuscenes-devkit 已安装"
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else
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check_fail "nuscenes-devkit 未安装"
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echo " 安装: pip install nuscenes-devkit"
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fi
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# 9. tqdm检查
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echo ""
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echo "[9/12] tqdm (必需)"
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python3 -c "import tqdm" 2>/dev/null
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if [ $? -eq 0 ]; then
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check_pass "tqdm 已安装"
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else
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check_fail "tqdm 未安装"
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echo " 安装: pip install tqdm"
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fi
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# 10. 自定义CUDA算子检查
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echo ""
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echo "[10/12] 自定义CUDA算子 (需要运行 python setup.py develop)"
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python3 -c "from mmdet3d.ops import bev_pool_v2" 2>/dev/null
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if [ $? -eq 0 ]; then
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check_pass "BEV Pool 算子已编译"
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else
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check_fail "BEV Pool 算子未编译"
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echo " 运行: cd /workspace/bevfusion && python3 setup.py develop"
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fi
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python3 -c "from mmdet3d.ops import Voxelization" 2>/dev/null
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if [ $? -eq 0 ]; then
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check_pass "Voxelization 算子已编译"
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else
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check_fail "Voxelization 算子未编译"
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fi
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python3 -c "from mmdet3d.ops.spconv import SparseConv3d" 2>/dev/null
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if [ $? -eq 0 ]; then
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check_pass "Sparse Conv 算子已编译"
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else
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check_fail "Sparse Conv 算子未编译"
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fi
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# 11. 数据集检查
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echo ""
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echo "[11/12] nuScenes 数据集"
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DATA_ROOT="data/nuscenes"
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if [ -d "$DATA_ROOT" ]; then
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check_pass "数据集目录存在"
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# 检查关键文件
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if [ -f "$DATA_ROOT/nuscenes_infos_train.pkl" ]; then
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check_pass "训练数据info文件"
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else
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check_fail "nuscenes_infos_train.pkl 缺失"
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fi
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if [ -f "$DATA_ROOT/nuscenes_infos_val.pkl" ]; then
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check_pass "验证数据info文件"
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else
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check_fail "nuscenes_infos_val.pkl 缺失"
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fi
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if [ -d "$DATA_ROOT/samples" ]; then
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SAMPLE_COUNT=$(find "$DATA_ROOT/samples" -type f | wc -l)
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check_pass "samples目录 ($SAMPLE_COUNT 文件)"
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else
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check_fail "samples目录缺失"
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fi
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else
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check_fail "数据集目录不存在: $DATA_ROOT"
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echo " 参考README.md的Data Preparation部分"
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fi
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# 12. 预训练模型检查
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echo ""
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echo "[12/12] 预训练模型"
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PRETRAIN_DIR="pretrained"
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if [ -d "$PRETRAIN_DIR" ]; then
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check_pass "预训练模型目录存在"
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# 检查关键模型
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if [ -f "$PRETRAIN_DIR/swint-nuimages-pretrained.pth" ]; then
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SIZE=$(du -h "$PRETRAIN_DIR/swint-nuimages-pretrained.pth" | cut -f1)
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check_pass "swint-nuimages-pretrained.pth ($SIZE)"
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else
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check_warn "swint-nuimages-pretrained.pth 缺失"
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fi
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if [ -f "$PRETRAIN_DIR/lidar-only-det.pth" ]; then
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SIZE=$(du -h "$PRETRAIN_DIR/lidar-only-det.pth" | cut -f1)
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check_pass "lidar-only-det.pth ($SIZE)"
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else
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check_warn "lidar-only-det.pth 缺失"
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fi
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else
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check_warn "预训练模型目录不存在"
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echo " 运行: ./tools/download_pretrained.sh"
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fi
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# 总结
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echo ""
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echo "=========================================="
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echo "检查完成"
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echo "通过: $PASS 项"
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echo "失败: $FAIL 项"
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echo "=========================================="
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if [ $FAIL -eq 0 ]; then
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echo ""
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echo "✓ 环境配置完整，可以开始训练！"
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echo ""
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echo "训练命令示例："
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echo " # 3D检测"
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echo " torchpack dist-run -np 8 python3 tools/train.py \\"
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echo " configs/nuscenes/det/transfusion/secfpn/camera+lidar/swint_v0p075/convfuser.yaml \\"
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echo " --model.encoders.camera.backbone.init_cfg.checkpoint pretrained/swint-nuimages-pretrained.pth \\"
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echo " --load_from pretrained/lidar-only-det.pth"
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echo ""
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echo " # BEV分割"
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echo " torchpack dist-run -np 8 python3 tools/train.py \\"
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echo " configs/nuscenes/seg/fusion-bev256d2-lss.yaml \\"
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echo " --model.encoders.camera.backbone.init_cfg.checkpoint pretrained/swint-nuimages-pretrained.pth"
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exit 0
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else
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echo ""
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echo "⚠ 发现 $FAIL 个问题，请先解决后再训练"
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echo ""
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echo "常见解决方案："
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echo "1. 安装缺失的包："
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echo " pip install torchpack mmcv==1.4.0 mmcv-full==1.4.0 mmdet==2.20.0"
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echo " pip install nuscenes-devkit tqdm Pillow==8.4.0"
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echo ""
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echo "2. 编译自定义算子："
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echo " cd /workspace/bevfusion"
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echo " python3 setup.py develop"
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echo ""
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echo "3. 准备数据集："
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echo " 参考README.md的Data Preparation部分"
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exit 1
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fi
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