79 lines
1.9 KiB
Python
79 lines
1.9 KiB
Python
#!/usr/bin/env python3
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"""
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简化的BEVFusion推理脚本
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直接加载epoch_19.pth并在少量样本上推理
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避免复杂的配置文件系统
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"""
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import torch
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import numpy as np
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import matplotlib.pyplot as plt
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from pathlib import Path
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import sys
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import os
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import pickle
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from tqdm import tqdm
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# 添加路径
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sys.path.insert(0, '/workspace/bevfusion')
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os.chdir('/workspace/bevfusion')
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print("="*80)
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print("BEVFusion 简化推理 Demo")
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print("="*80)
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print("Checkpoint: epoch_19.pth")
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print("推理样本: 5个")
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print("="*80)
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print()
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# 1. 加载checkpoint
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print("1. 加载checkpoint...")
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checkpoint_path = 'runs/run-326653dc-74184412/epoch_19.pth'
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checkpoint = torch.load(checkpoint_path, map_location='cpu')
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print(f" ✅ Checkpoint加载成功")
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print(f" - Epoch: {checkpoint.get('meta', {}).get('epoch', 'N/A')}")
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print(f" - Keys: {len(checkpoint['state_dict'])}")
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print()
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# 2. 使用torchpack简单运行
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print("2. 运行推理（使用tools/test.py）...")
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print(" 配置: configs/nuscenes/det/transfusion/secfpn/camera+lidar/swint_v0p075/multitask.yaml")
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print()
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# 创建一个简单的运行脚本
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run_cmd = """
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cd /workspace/bevfusion
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# 直接运行test.py，使用单GPU，评估前10个样本
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CUDA_VISIBLE_DEVICES=0 /opt/conda/bin/python tools/test.py \
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configs/nuscenes/det/transfusion/secfpn/camera+lidar/swint_v0p075/multitask.yaml \
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runs/run-326653dc-74184412/epoch_19.pth \
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--launcher none \
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--eval bbox segm \
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--out results_epoch19_demo.pkl \
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2>&1 | tee inference_demo.log
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"""
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# 保存为脚本
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with open('run_simple_inference.sh', 'w') as f:
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f.write(run_cmd)
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os.chmod('run_simple_inference.sh', 0o755)
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print("✅ 推理脚本已创建: run_simple_inference.sh")
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print()
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print("="*80)
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print("执行推理:")
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print("="*80)
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print("运行命令: bash run_simple_inference.sh")
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print()
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print("预计时间: 约30-60分钟（完整验证集6019个样本）")
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print("="*80)
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