82 lines
2.5 KiB
Python
82 lines
2.5 KiB
Python
#!/usr/bin/env python3
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"""
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完整的动态批次性能测试流程
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1. 构建动态批次 TensorRT 引擎
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2. 运行批次性能测试
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3. 生成可视化报告
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"""
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import os
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import sys
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import subprocess
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def run_command(cmd, description):
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"""运行命令并显示进度"""
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print(f"\n{'='*60}")
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print(f"🚀 {description}")
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print(f"{'='*60}")
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result = subprocess.run(cmd, shell=True)
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if result.returncode != 0:
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print(f"❌ {description} 失败")
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return False
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print(f"✅ {description} 完成")
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return True
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def main():
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"""主函数"""
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print("完整的动态批次 TensorRT 性能测试流程")
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print("="*60)
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# 检查 conda 环境
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print("\n📋 执行步骤:")
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print(" 1. 构建动态批次 TensorRT 引擎")
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print(" 2. 运行批次性能测试")
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print(" 3. 生成可视化报告")
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input("\n按 Enter 键开始...")
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# 步骤 1: 构建动态批次引擎
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engine_path = "C:/Users/16337/PycharmProjects/Security/yolo11n_dynamic.engine"
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if not os.path.exists(engine_path):
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print("\n🔧 步骤 1: 构建动态批次 TensorRT 引擎")
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if not run_command("conda activate yolov11 && python dynamic_batch_tensorrt_builder.py",
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"构建动态批次 TensorRT 引擎"):
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return
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else:
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print(f"\n✅ 动态批次引擎已存在: {engine_path}")
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print("跳过步骤 1")
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# 步骤 2: 运行批次性能测试
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print("\n📊 步骤 2: 运行批次性能测试")
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if not run_command("conda activate yolov11 && python run_batch_performance_test.py",
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"运行批次性能测试"):
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return
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# 步骤 3: 生成可视化报告
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print("\n🎨 步骤 3: 生成可视化报告")
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if not run_command("conda activate yolov11 && python visualize_batch_results.py",
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"生成可视化报告"):
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return
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print("\n" + "="*60)
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print("🎉 完整测试流程执行完成！")
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print("="*60)
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print("\n📁 查看结果:")
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print(" - 测试数据: batch_test_results/")
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print(" - 可视化图表: batch_test_results/visualizations/")
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print(" - 总结报告: batch_test_results/visualizations/batch_performance_summary.txt")
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if __name__ == "__main__":
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try:
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main()
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except KeyboardInterrupt:
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print("\n\n⏹️ 测试被用户中断")
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except Exception as e:
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print(f"\n❌ 执行过程中发生错误: {e}")
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import traceback
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traceback.print_exc()
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