TensorRT测试

run_complete_batch_test.py

@@ -0,0 +1,81 @@
+#!/usr/bin/env python3
+"""
+完整的动态批次性能测试流程
+1. 构建动态批次 TensorRT 引擎
+2. 运行批次性能测试
+3. 生成可视化报告
+"""
+
+import os
+import sys
+import subprocess
+
+def run_command(cmd, description):
+    """运行命令并显示进度"""
+    print(f"\n{'='*60}")
+    print(f"🚀 {description}")
+    print(f"{'='*60}")
+    
+    result = subprocess.run(cmd, shell=True)
+    
+    if result.returncode != 0:
+        print(f"❌ {description} 失败")
+        return False
+    
+    print(f"✅ {description} 完成")
+    return True
+
+def main():
+    """主函数"""
+    print("完整的动态批次 TensorRT 性能测试流程")
+    print("="*60)
+    
+    # 检查 conda 环境
+    print("\n📋 执行步骤:")
+    print("  1. 构建动态批次 TensorRT 引擎")
+    print("  2. 运行批次性能测试")
+    print("  3. 生成可视化报告")
+    
+    input("\n按 Enter 键开始...")
+    
+    # 步骤 1: 构建动态批次引擎
+    engine_path = "C:/Users/16337/PycharmProjects/Security/yolo11n_dynamic.engine"
+    
+    if not os.path.exists(engine_path):
+        print("\n🔧 步骤 1: 构建动态批次 TensorRT 引擎")
+        if not run_command("conda activate yolov11 && python dynamic_batch_tensorrt_builder.py",
+                          "构建动态批次 TensorRT 引擎"):
+            return
+    else:
+        print(f"\n✅ 动态批次引擎已存在: {engine_path}")
+        print("跳过步骤 1")
+    
+    # 步骤 2: 运行批次性能测试
+    print("\n📊 步骤 2: 运行批次性能测试")
+    if not run_command("conda activate yolov11 && python run_batch_performance_test.py",
+                      "运行批次性能测试"):
+        return
+    
+    # 步骤 3: 生成可视化报告
+    print("\n🎨 步骤 3: 生成可视化报告")
+    if not run_command("conda activate yolov11 && python visualize_batch_results.py",
+                      "生成可视化报告"):
+        return
+    
+    print("\n" + "="*60)
+    print("🎉 完整测试流程执行完成！")
+    print("="*60)
+    print("\n📁 查看结果:")
+    print("  - 测试数据: batch_test_results/")
+    print("  - 可视化图表: batch_test_results/visualizations/")
+    print("  - 总结报告: batch_test_results/visualizations/batch_performance_summary.txt")
+
+if __name__ == "__main__":
+    try:
+        main()
+    except KeyboardInterrupt:
+        print("\n\n⏹️ 测试被用户中断")
+    except Exception as e:
+        print(f"\n❌ 执行过程中发生错误: {e}")
+        import traceback
+        traceback.print_exc()