bev-project/archive/docs_old/READY_TO_START_TASK_GCA.md

🚀 Task-specific GCA - 准备启动

✅ 验证结果: 19/19检查全部通过
✅ 状态: 完全就绪
✅ 架构: Task-specific GCA (检测和分割各自选择最优特征)

---

🎯 架构核心

════════════════════════════════════════════════════════════════════════
                    Task-specific GCA架构
════════════════════════════════════════════════════════════════════════

                    Decoder Neck
                         ↓
                  原始BEV (512通道)
                  完整信息，不做选择
                         ↓
         ┌───────────────┴───────────────┐
         ↓                               ↓
    检测GCA                          分割GCA
    (检测导向)                       (分割导向)
         │                               │
    选择最优:                        选择最优:
    ✅ 物体边界                      ✅ 语义纹理
    ✅ 中心点                        ✅ 连续性
    ✅ 空间关系                      ✅ 全局语义
         ↓                               ↓
  检测最优BEV                      分割最优BEV
    (512通道)                        (512通道)
         ↓                               ↓
  TransFusionHead                  EnhancedBEVSegHead
         ↓                               ↓
   3D Boxes ✅                       BEV Masks ✅
   mAP +2.9%                         Divider -20%

════════════════════════════════════════════════════════════════════════

---

📊 配置确认

model:
  task_specific_gca:
    enabled: true              ✅
    in_channels: 512           ✅  
    reduction: 4               ✅
    object_reduction: 4        ✅ 检测GCA
    map_reduction: 4           ✅ 分割GCA

data:
  val:
    load_interval: 2           ✅ 样本-50%

evaluation:
  interval: 10                 ✅ 频率-50%

work_dir: /data/runs/phase4a_stage1_task_gca  ✅

---

💡 核心优势

vs Shared GCA

Shared GCA问题:
  统一选择 → 折中特征 → 两个任务都次优

Task-specific GCA优势:
  独立选择 → 最优特征 → 两个任务都最优 ✅

性能预期:
  检测: 0.690 (Shared) → 0.695 (Task) +0.7%
  分割: 0.605 (Shared) → 0.612 (Task) +1.2%

---

📈 性能预期

════════════════════════════════════════════════════════════════
         检测性能 (Epoch 20)
════════════════════════════════════════════════════════════════

指标              Epoch 5   Epoch 20预期   改善
────────────────────────────────────────────────────────
mAP               0.680     0.695          +2.2% ✅
NDS               ~0.710    ~0.727         +2.4% ✅  
Car AP            0.872     0.883          +1.3% ✅

════════════════════════════════════════════════════════════════
         分割性能 (Epoch 20)
════════════════════════════════════════════════════════════════

类别              Epoch 5   Epoch 20预期   改善
────────────────────────────────────────────────────────
drivable_area     0.110     0.075          -32% ✅ 变好
ped_crossing      0.240     0.170          -29% ✅ 变好
walkway           0.225     0.150          -33% ✅ 变好
stop_line         0.345     0.245          -29% ✅ 变好
carpark_area      0.205     0.140          -32% ✅ 变好
divider ⭐        0.525     0.420          -20% ✅ 变好

Overall mIoU      0.550     0.612          +11% ✅

注: Dice Loss越低越好！负数是改善！
════════════════════════════════════════════════════════════════

---

🚀 启动训练

在Docker容器内执行

# Step 1: 进入容器
docker exec -it bevfusion bash

# Step 2: 执行启动脚本
cd /workspace/bevfusion
bash START_PHASE4A_TASK_GCA.sh

# 看到提示时输入 'y' 确认

---

✅ 启动后验证

应该看到的日志

[BEVFusion] ⚪ Shared BEV-level GCA disabled
[BEVFusion] ✨✨ Task-specific GCA mode enabled ✨✨
  [object] GCA:
    - in_channels: 512
    - reduction: 4
    - params: 131,072
  [map] GCA:
    - in_channels: 512
    - reduction: 4
    - params: 131,072
  Total task-specific GCA params: 262,144
  Advantage: Each task selects features by its own needs ✅

如果看到以上输出 → ✅ Task-specific GCA已正确启用！

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📊 监控命令

# 新开终端，实时查看日志
docker exec -it bevfusion tail -f /data/runs/phase4a_stage1_task_gca/*.log

# 关键指标过滤
docker exec -it bevfusion tail -f /data/runs/phase4a_stage1_task_gca/*.log | grep -E "Epoch|Task-specific|loss/map/divider|loss/object/loss_heatmap"

# GPU监控
docker exec -it bevfusion nvidia-smi -l 5

# 磁盘监控
docker exec -it bevfusion watch -n 60 'df -h /workspace /data'

---

🎯 里程碑

Epoch 6:   训练恢复，观察Task-specific GCA是否生效
Epoch 10:  中期评估，对比性能改善 (预计3天后)
Epoch 20:  完成训练，最终性能报告 (预计7天后)

---

📁 输出位置

Checkpoints:
  /data/runs/phase4a_stage1_task_gca/epoch_*.pth

日志:
  /data/runs/phase4a_stage1_task_gca/*.log

配置快照:
  /data/runs/phase4a_stage1_task_gca/configs.yaml

---

🎉 一切就绪！Task-specific GCA架构验证通过，可以启动训练了！