235 lines
8.4 KiB
Python
235 lines
8.4 KiB
Python
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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OpenCV后端优化验证脚本
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测试DirectShow后端相对于MSMF的性能提升
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"""
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import sys
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import os
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import time
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import logging
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# 添加项目路径
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sys.path.append(os.path.dirname(os.path.abspath(__file__)))
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from devices.camera_manager import CameraManager
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from devices.utils.config_manager import ConfigManager
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# 配置日志
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(levelname)s - %(message)s'
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)
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logger = logging.getLogger(__name__)
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def test_backend_performance(backend_name, test_name):
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"""
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测试指定后端的性能
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Args:
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backend_name: 后端名称 (directshow, msmf)
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test_name: 测试名称
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Returns:
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dict: 性能数据
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"""
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print(f"\n{'='*60}")
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print(f"📷 测试 {test_name} 后端性能")
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print(f"{'='*60}")
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# 创建配置管理器并设置后端
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config_manager = ConfigManager()
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# 获取原始配置
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original_config = config_manager.get_device_config('camera')
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# 设置测试后端
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test_config = {
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'backend': backend_name
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}
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config_manager.set_camera_config(test_config)
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try:
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# 创建相机管理器
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camera = CameraManager(None, config_manager)
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# 测试初始化性能
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start_time = time.time()
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success = camera.initialize()
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total_time = (time.time() - start_time) * 1000
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if success:
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print(f"✅ 相机初始化成功: {total_time:.1f}ms")
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# 获取实际后端信息
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if camera.cap:
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backend_info = camera.cap.getBackendName() if hasattr(camera.cap, 'getBackendName') else 'Unknown'
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actual_width = int(camera.cap.get(cv2.CAP_PROP_FRAME_WIDTH))
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actual_height = int(camera.cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
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actual_fps = camera.cap.get(cv2.CAP_PROP_FPS)
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print(f"🎯 实际后端: {backend_info}")
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print(f"📐 实际分辨率: {actual_width}x{actual_height}@{actual_fps:.1f}fps")
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# 测试首帧获取
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frame_start = time.time()
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ret, frame = camera.cap.read() if camera.cap else (False, None)
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frame_time = (time.time() - frame_start) * 1000
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if ret and frame is not None:
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print(f"🖼️ 首帧获取: {frame_time:.1f}ms, 帧大小: {frame.shape}")
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else:
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print(f"❌ 首帧获取失败")
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frame_time = -1
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# 测试连续帧性能
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print(f"🎬 测试连续帧获取性能...")
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frame_times = []
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for i in range(10):
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frame_start = time.time()
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ret, frame = camera.cap.read() if camera.cap else (False, None)
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if ret:
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frame_times.append((time.time() - frame_start) * 1000)
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time.sleep(0.01) # 小延迟
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if frame_times:
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avg_frame_time = sum(frame_times) / len(frame_times)
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min_frame_time = min(frame_times)
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max_frame_time = max(frame_times)
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print(f"📈 连续帧性能: 平均 {avg_frame_time:.1f}ms, 最快 {min_frame_time:.1f}ms, 最慢 {max_frame_time:.1f}ms")
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else:
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avg_frame_time = -1
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print(f"❌ 连续帧测试失败")
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# 清理资源
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camera.cleanup()
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print(f"🧹 相机资源已释放")
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return {
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'backend': backend_name,
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'success': True,
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'init_time': total_time,
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'first_frame_time': frame_time,
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'avg_frame_time': avg_frame_time,
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'backend_info': backend_info if camera.cap else 'Unknown',
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'resolution': f"{actual_width}x{actual_height}@{actual_fps:.1f}fps" if camera.cap else "未知"
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}
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else:
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print(f"❌ 初始化失败")
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return {
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'backend': backend_name,
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'success': False,
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'init_time': total_time,
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'first_frame_time': -1,
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'avg_frame_time': -1,
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'backend_info': 'Failed',
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'resolution': "失败"
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}
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except Exception as e:
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print(f"❌ 测试异常: {e}")
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return {
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'backend': backend_name,
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'success': False,
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'init_time': -1,
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'first_frame_time': -1,
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'avg_frame_time': -1,
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'backend_info': 'Exception',
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'resolution': "异常",
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'error': str(e)
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}
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finally:
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# 恢复原始配置
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try:
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restore_config = {
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'backend': original_config['backend']
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}
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config_manager.set_camera_config(restore_config)
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except Exception as e:
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print(f"⚠️ 恢复配置失败: {e}")
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def main():
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"""
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主函数：测试不同后端的性能
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"""
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print("\n" + "="*80)
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print("🚀 OpenCV后端性能优化验证")
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print("="*80)
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# 测试用例
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test_cases = [
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('directshow', 'DirectShow (推荐)'),
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('msmf', 'MSMF (默认)')
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]
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results = []
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# 执行测试
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for backend, name in test_cases:
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result = test_backend_performance(backend, name)
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results.append(result)
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time.sleep(1) # 测试间隔
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# 汇总结果
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print(f"\n\n{'='*80}")
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print(f"📊 后端性能优化验证汇总")
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print(f"{'='*80}")
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# 表格头
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print(f"{'后端':<12} {'状态':<8} {'初始化':<12} {'首帧':<12} {'连续帧':<12} {'实际后端':<15}")
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print("-" * 80)
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successful_results = [r for r in results if r['success']]
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for result in results:
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status = "✅成功" if result['success'] else "❌失败"
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init_time = f"{result['init_time']:.1f}ms" if result['init_time'] > 0 else "失败"
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first_frame = f"{result['first_frame_time']:.1f}ms" if result['first_frame_time'] > 0 else "失败"
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avg_frame = f"{result['avg_frame_time']:.1f}ms" if result['avg_frame_time'] > 0 else "失败"
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backend_info = result['backend_info'][:14] if len(result['backend_info']) > 14 else result['backend_info']
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print(f"{result['backend']:<12} {status:<8} {init_time:<12} {first_frame:<12} {avg_frame:<12} {backend_info:<15}")
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# 性能分析
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if len(successful_results) >= 2:
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print(f"\n📈 性能分析:")
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# 找到最快的后端
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fastest = min(successful_results, key=lambda x: x['init_time'])
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slowest = max(successful_results, key=lambda x: x['init_time'])
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print(f"🏆 最快后端: {fastest['backend']} - {fastest['init_time']:.1f}ms")
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print(f"🐌 最慢后端: {slowest['backend']} - {slowest['init_time']:.1f}ms")
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if fastest['init_time'] > 0 and slowest['init_time'] > 0:
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improvement = ((slowest['init_time'] - fastest['init_time']) / slowest['init_time']) * 100
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print(f"💡 性能提升: {improvement:.1f}% (使用最快后端)")
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print(f"\n📋 详细性能对比:")
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for result in successful_results:
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if result != fastest:
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slowdown = ((result['init_time'] - fastest['init_time']) / fastest['init_time']) * 100
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print(f" {result['backend']}: 比最快后端慢 {slowdown:.1f}% ({result['init_time']:.1f}ms vs {fastest['init_time']:.1f}ms)")
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print(f"\n🎯 建议:")
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if successful_results:
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fastest = min(successful_results, key=lambda x: x['init_time'])
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print(f"✅ 推荐使用 {fastest['backend']} 后端以获得最佳性能")
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print(f"📝 配置建议: 在配置文件中设置 backend = {fastest['backend']}")
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if fastest['init_time'] > 5000:
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print(f"⚠️ 性能评级: 需要优化 (> 5秒)")
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elif fastest['init_time'] > 2000:
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print(f"⚠️ 性能评级: 一般 (2-5秒)")
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else:
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print(f"✅ 性能评级: 良好 (< 2秒)")
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else:
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print(f"❌ 所有后端测试失败，请检查相机连接")
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print(f"\n{'='*80}")
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print(f"测试完成")
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print(f"{'='*80}")
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if __name__ == "__main__":
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import cv2 # 需要导入cv2用于相机操作
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main()
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