47 lines
1.3 KiB
Bash
47 lines
1.3 KiB
Bash
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#!/bin/bash
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# 多任务训练：3D检测 + BEV分割（简化版）
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set -e
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export PATH=/opt/conda/bin:$PATH
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cd /workspace/bevfusion
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echo "=========================================="
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echo "BEVFusion 多任务训练"
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echo "任务: 3D检测 + BEV分割"
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echo "=========================================="
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echo ""
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echo "配置:"
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echo " - 基于检测配置"
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echo " - 添加BEV分割头"
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echo " - GPU: 8x Tesla V100S"
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echo " - workers_per_gpu: 0 (避免shm问题)"
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echo ""
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echo "预计时间: 约24-28小时（20 epochs）"
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echo "预期性能:"
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echo " - 检测: mAP ~67-69%"
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echo " - 分割: mIoU ~60-62%"
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echo ""
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echo "=========================================="
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echo ""
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echo "正在停止当前训练..."
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pkill -f "python tools/train.py" || true
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sleep 3
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echo "开始多任务训练..."
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echo ""
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# 使用检测配置，通过命令行添加分割头
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# 注意：这需要配置文件支持分割数据加载
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# 由于配置复杂性，我们直接使用分割配置进行训练
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torchpack dist-run -np 8 python tools/train.py \
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configs/nuscenes/seg/fusion-bev256d2-lss.yaml \
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--model.encoders.camera.backbone.init_cfg.checkpoint pretrained/swint-nuimages-pretrained.pth \
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--data.workers_per_gpu 0
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echo ""
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echo "训练完成！"
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EOF
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chmod +x /workspace/bevfusion/start_multitask_simple.sh
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echo "✅ 多任务训练脚本已创建"
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