123 lines
3.1 KiB
Bash
Executable File
123 lines
3.1 KiB
Bash
Executable File
#!/bin/bash
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#
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# 增强版多任务训练脚本
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# 训练BEVFusion with EnhancedBEVSegmentationHead
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#
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# 预期性能：
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# - 检测mAP: 65-68%
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# - 分割mIoU: 60-65% (vs 当前36%)
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#
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# 改进点：
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# 1. ASPP多尺度特征
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# 2. 通道+空间注意力
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# 3. 深层解码器(4层)
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# 4. Focal Loss修复(alpha=0.25)
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# 5. Dice Loss混合
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# 6. 类别权重平衡
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# 7. Deep supervision
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# 8. 分割损失权重3.0x
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set -e
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echo "=========================================="
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echo "BEVFusion 增强版多任务训练"
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echo "任务: 3D检测 + BEV分割（增强版）"
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echo "=========================================="
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echo ""
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# 配置
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CONFIG="configs/nuscenes/multitask/fusion-det-seg-swint-enhanced.yaml"
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NUM_GPUS=8
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WORK_DIR="runs/enhanced-multitask-$(date +%Y%m%d-%H%M%S)"
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LOG_FILE="training_enhanced_multitask_$(date +%Y%m%d_%H%M%S).log"
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echo "配置信息："
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echo " 配置文件: ${CONFIG}"
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echo " GPU数量: ${NUM_GPUS}"
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echo " 工作目录: ${WORK_DIR}"
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echo " 日志文件: ${LOG_FILE}"
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echo ""
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# 检查配置文件
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if [ ! -f "${CONFIG}" ]; then
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echo "错误: 配置文件不存在: ${CONFIG}"
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exit 1
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fi
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# 检查预训练权重
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PRETRAINED_SWINT="pretrained/swint-nuimages-pretrained.pth"
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PRETRAINED_LIDAR="pretrained/lidar-only-det.pth"
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if [ ! -f "${PRETRAINED_SWINT}" ]; then
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echo "警告: SwinT预训练权重不存在: ${PRETRAINED_SWINT}"
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echo "将从头开始训练camera encoder（不推荐）"
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fi
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if [ ! -f "${PRETRAINED_LIDAR}" ]; then
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echo "警告: LiDAR预训练权重不存在: ${PRETRAINED_LIDAR}"
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echo "将从头开始训练LiDAR encoder（不推荐）"
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fi
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echo ""
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echo "改进点："
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echo " ✅ ASPP多尺度特征提取"
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echo " ✅ 通道+空间注意力机制"
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echo " ✅ 深层解码器(4层)"
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echo " ✅ Focal Loss修复(alpha=0.25)"
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echo " ✅ Dice Loss混合(weight=0.5)"
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echo " ✅ 类别权重平衡(stop_line×4)"
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echo " ✅ Deep supervision"
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echo " ✅ 分割损失权重×3"
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echo ""
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echo "预期性能:"
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echo " - 检测mAP: 65-68%"
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echo " - 分割mIoU: 60-65%"
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echo " - 训练时间: ~4-5天"
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echo ""
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echo "=========================================="
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echo "开始训练..."
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echo "=========================================="
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echo ""
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# 构建训练命令
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TRAIN_CMD="torchpack dist-run -np ${NUM_GPUS} python tools/train.py ${CONFIG}"
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# 添加预训练权重
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if [ -f "${PRETRAINED_SWINT}" ]; then
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TRAIN_CMD="${TRAIN_CMD} --model.encoders.camera.backbone.init_cfg.checkpoint ${PRETRAINED_SWINT}"
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fi
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if [ -f "${PRETRAINED_LIDAR}" ]; then
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TRAIN_CMD="${TRAIN_CMD} --load_from ${PRETRAINED_LIDAR}"
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fi
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# 添加工作目录
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TRAIN_CMD="${TRAIN_CMD} --run-dir ${WORK_DIR}"
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# 输出训练命令
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echo "训练命令:"
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echo "${TRAIN_CMD}"
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echo ""
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# 执行训练（输出到文件和终端）
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eval "${TRAIN_CMD}" 2>&1 | tee "${LOG_FILE}"
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echo ""
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echo "=========================================="
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echo "训练完成！"
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echo "=========================================="
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echo ""
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echo "结果保存在:"
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echo " 工作目录: ${WORK_DIR}"
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echo " 日志文件: ${LOG_FILE}"
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echo ""
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echo "评估命令:"
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echo "torchpack dist-run -np ${NUM_GPUS} python tools/test.py \\"
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echo " ${CONFIG} \\"
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echo " ${WORK_DIR}/latest.pth \\"
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echo " --eval bbox map"
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echo ""
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