51 lines
1.8 KiB
Bash
Executable File
51 lines
1.8 KiB
Bash
Executable File
#!/bin/bash
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# Phase 4A: BEV 2x分辨率提升训练
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# 基于之前成功的训练脚本格式
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set -e
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export PATH=/opt/conda/bin:$PATH
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echo "========================================================================"
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echo "Phase 4A: BEV 2x分辨率提升训练"
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echo "========================================================================"
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echo "配置: BEV 0.15m分辨率 (2倍提升)"
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echo "Decoder: 4层完整版 [256, 256, 128, 128]"
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echo "从epoch_23.pth加载所有权重"
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echo "目标: 20 epochs"
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echo ""
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echo "关键改进:"
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echo " - BEV分辨率: 0.3m → 0.15m (720×720)"
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echo " - GT标签: 0.25m → 0.125m (800×800)"
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echo " - Decoder深度: 2层 → 4层"
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echo " - Deep Supervision: 启用"
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echo " - Dice Loss: 启用"
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echo ""
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echo "预期性能提升:"
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echo " - Stop Line IoU: 0.27 → 0.42+ (+55%)"
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echo " - Divider IoU: 0.19 → 0.35+ (+84%)"
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echo " - 整体mIoU: 0.41 → 0.54+ (+32%)"
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echo "========================================================================"
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echo ""
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# 创建日志文件
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LOG_FILE="phase4a_bev2x_$(date +%Y%m%d_%H%M%S).log"
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echo "开始训练..."
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echo "日志文件: $LOG_FILE"
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echo ""
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# 启动训练 - 使用与之前成功训练相同的格式
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/opt/conda/bin/torchpack dist-run -np 6 /opt/conda/bin/python tools/train.py \
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configs/nuscenes/det/transfusion/secfpn/camera+lidar/swint_v0p075/multitask_BEV2X_phase4a.yaml \
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--model.encoders.camera.backbone.init_cfg.checkpoint pretrained/swint-nuimages-pretrained.pth \
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--load_from runs/enhanced_from_epoch19/epoch_23.pth \
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--data.samples_per_gpu 1 \
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--data.workers_per_gpu 0 \
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2>&1 | tee "$LOG_FILE"
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echo ""
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echo "========================================================================"
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echo "训练完成！日志保存在: $LOG_FILE"
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echo "========================================================================"
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