bev-project/archive_scripts/start_phase4a_v2.sh

#!/bin/bash
set -e

export PATH=/opt/conda/bin:$PATH
export LD_LIBRARY_PATH=/opt/conda/lib:/usr/local/cuda/lib64:$LD_LIBRARY_PATH
cd /workspace/bevfusion

echo "Phase 4A: BEV 2x训练 - 启动中..."

# 直接使用python而不是torchpack
nohup python -m torch.distributed.launch --nproc_per_node=6 --master_port=29500 \
    tools/train.py \
    configs/nuscenes/det/transfusion/secfpn/camera+lidar/swint_v0p075/multitask_BEV2X_phase4a.yaml \
    --launcher pytorch \
    --model.encoders.camera.backbone.init_cfg.checkpoint=pretrained/swint-nuimages-pretrained.pth \
    --load_from runs/enhanced_from_epoch19/epoch_23.pth \
    --run-dir runs/phase4a_bev2x \
    > phase4a_bev2x.log 2>&1 &

echo "✅ 训练已启动，PID: $!"
echo "日志: phase4a_bev2x.log"
-												Complete project state snapshot: Phase 4B RMT-PPAD Integration

🎯 Training Status:
- Current Epoch: 2/10 (13.3% complete)
- Segmentation Dice: 0.9594
- Detection IoU: 0.5742
- Training stable with 8 GPUs

🔧 Technical Achievements:
- ✅ RMT-PPAD Transformer segmentation decoder integrated
- ✅ Task-specific GCA architecture optimized
- ✅ Multi-scale feature fusion (180×180, 360×360, 600×600)
- ✅ Adaptive scale weight learning implemented
- ✅ BEVFusion multi-task framework enhanced

📊 Performance Highlights:
- Divider segmentation: 0.9793 Dice (excellent)
- Pedestrian crossing: 0.9812 Dice (excellent)
- Stop line: 0.9812 Dice (excellent)
- Carpark area: 0.9802 Dice (excellent)
- Walkway: 0.9401 Dice (good)
- Drivable area: 0.8959 Dice (good)

🛠️ Code Changes Included:
- Enhanced BEVFusion model (bevfusion.py)
- RMT-PPAD integration modules (rmtppad_integration.py)
- Transformer segmentation head (enhanced_transformer.py)
- GCA module optimizations (gca.py)
- Configuration updates (Phase 4B configs)
- Training scripts and automation tools
- Comprehensive documentation and analysis reports

📅 Snapshot Date: Fri Nov 14 09:06:09 UTC 2025
📍 Environment: Docker container
🎯 Phase: RMT-PPAD Integration Complete

											
										
										
											2025-11-14 17:06:09 +08:00
+								#!/bin/bash
 								set -e
 								export PATH=/opt/conda/bin:$PATH
 								export LD_LIBRARY_PATH=/opt/conda/lib:/usr/local/cuda/lib64:$LD_LIBRARY_PATH
 								cd /workspace/bevfusion
 								echo "Phase 4A: BEV 2x训练 - 启动中..."
 								# 直接使用python而不是torchpack
 								nohup python -m torch.distributed.launch --nproc_per_node=6 --master_port=29500 \
 								    tools/train.py \
 								    configs/nuscenes/det/transfusion/secfpn/camera+lidar/swint_v0p075/multitask_BEV2X_phase4a.yaml \
 								    --launcher pytorch \
 								    --model.encoders.camera.backbone.init_cfg.checkpoint=pretrained/swint-nuimages-pretrained.pth \
 								    --load_from runs/enhanced_from_epoch19/epoch_23.pth \
 								    --run-dir runs/phase4a_bev2x \
 								    > phase4a_bev2x.log 2>&1 &
 								echo "✅ 训练已启动，PID: $!"
 								echo "日志: phase4a_bev2x.log"