79 lines
2.1 KiB
Python
79 lines
2.1 KiB
Python
"""
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RTX 3050 TensorRT vs PyTorch 推理性能对比测试
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测试目标：
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- 对比 TensorRT 和 PyTorch 推理方式的性能差异
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- 评估最大同时接入摄像头路数
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- 测试单路与整体系统的最大稳定帧率
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- 生成详细的可视化分析报告
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测试环境：
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- GPU: RTX 3050 (8GB)
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- 模型: YOLOv8n
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- 分辨率: 320x320, 480x480
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- 精度: FP16, FP32
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"""
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import sys
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import os
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import json
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import time
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from pathlib import Path
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from datetime import datetime
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# 添加当前目录到路径
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sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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def main():
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print("=" * 80)
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print("RTX 3050 TensorRT vs PyTorch 推理性能对比测试")
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print("=" * 80)
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# 检查环境
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print("\n🔍 检查测试环境...")
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check_environment()
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# 运行对比测试
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print("\n🚀 开始对比测试...")
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run_comparison_tests()
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print("\n✅ 对比测试完成!")
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def check_environment():
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"""检查测试环境"""
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try:
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import torch
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print(f"✅ PyTorch: {torch.__version__}")
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if torch.cuda.is_available():
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print(f"✅ CUDA: {torch.version.cuda}")
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print(f"✅ GPU: {torch.cuda.get_device_name(0)}")
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print(f"✅ 显存: {torch.cuda.get_device_properties(0).total_memory // 1024**3}GB")
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else:
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print("❌ CUDA 不可用")
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except ImportError:
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print("❌ PyTorch 未安装")
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try:
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import tensorrt
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print(f"✅ TensorRT: {tensorrt.__version__}")
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except (ImportError, FileNotFoundError):
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print("⚠️ TensorRT: 不可用，将使用 Ultralytics 优化模式")
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try:
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import ultralytics
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print(f"✅ Ultralytics: {ultralytics.__version__}")
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except ImportError:
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print("❌ Ultralytics 未安装")
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def run_comparison_tests():
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"""运行对比测试"""
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from benchmark.comparison_runner import ComparisonRunner
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MODEL_PATH = "C:/Users/16337/PycharmProjects/Security_project/yolov8n.pt"
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OUTPUT_DIR = "./comparison_results"
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runner = ComparisonRunner(MODEL_PATH, OUTPUT_DIR)
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runner.run_full_comparison()
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if __name__ == "__main__":
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main() |