sladro
e13cb3659c
- 创建基本项目结构和目录 - 添加CMake构建系统 - 实现基础的配置解析功能 - 添加YOLO推理框架支持 - 集成RTSP和视频流处理功能 - 添加性能监控和日志系统
113 lines
3.4 KiB
C++
113 lines
3.4 KiB
C++
#include <gtest/gtest.h>
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#include "render/frame_drawer.hpp"
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#include <opencv2/opencv.hpp>
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using namespace pipeline;
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class FrameDrawerTest : public ::testing::Test {
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protected:
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void SetUp() override {
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// 创建测试配置
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config_.window_name = "Frame Drawer Test";
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config_.window_width = 800;
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config_.window_height = 600;
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config_.fullscreen = false;
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config_.test_mode = true; // 启用测试模式
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// 创建测试图像
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test_frame_ = cv::Mat(480, 640, CV_8UC3, cv::Scalar(0, 0, 0));
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// 创建测试检测结果
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renderer::DetectionResult det;
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det.bbox = cv::Rect(100, 100, 200, 200);
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det.confidence = 0.95f;
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det.class_id = 1;
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det.label = "person";
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test_results_.push_back(det);
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// 创建测试性能指标
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metrics_.fps = 30.0f;
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metrics_.inference_time_ms = 33.3f;
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metrics_.gpu_usage_percent = 50.0f;
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}
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void TearDown() override {
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drawer_.cleanup();
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}
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renderer::RendererConfig config_;
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FrameDrawer drawer_;
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cv::Mat test_frame_;
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std::vector<renderer::DetectionResult> test_results_;
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PerformanceMetrics metrics_;
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};
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// 测试初始化
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TEST_F(FrameDrawerTest, Initialization) {
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EXPECT_TRUE(drawer_.init(config_));
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// 重复初始化应该返回true
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EXPECT_TRUE(drawer_.init(config_));
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}
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// 测试未初始化时的处理
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TEST_F(FrameDrawerTest, ProcessWithoutInit) {
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EXPECT_FALSE(drawer_.processFrame(test_frame_, test_results_, metrics_));
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}
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// 测试正常处理
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TEST_F(FrameDrawerTest, NormalProcessing) {
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ASSERT_TRUE(drawer_.init(config_));
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EXPECT_TRUE(drawer_.processFrame(test_frame_, test_results_, metrics_));
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}
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// 测试空检测结果的处理
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TEST_F(FrameDrawerTest, ProcessEmptyResults) {
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ASSERT_TRUE(drawer_.init(config_));
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std::vector<renderer::DetectionResult> empty_results;
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EXPECT_TRUE(drawer_.processFrame(test_frame_, empty_results, metrics_));
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}
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// 测试清理
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TEST_F(FrameDrawerTest, Cleanup) {
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ASSERT_TRUE(drawer_.init(config_));
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drawer_.cleanup();
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// 清理后处理应该失败
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EXPECT_FALSE(drawer_.processFrame(test_frame_, test_results_, metrics_));
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}
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// 测试不同尺寸的图像
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TEST_F(FrameDrawerTest, DifferentImageSizes) {
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ASSERT_TRUE(drawer_.init(config_));
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// 测试不同尺寸的图像
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std::vector<cv::Size> sizes = {
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cv::Size(320, 240),
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cv::Size(640, 480),
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cv::Size(1280, 720),
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cv::Size(1920, 1080)
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};
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for (const auto& size : sizes) {
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cv::Mat frame(size, CV_8UC3, cv::Scalar(0, 0, 0));
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EXPECT_TRUE(drawer_.processFrame(frame, test_results_, metrics_))
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<< "Failed to process frame of size " << size.width << "x" << size.height;
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}
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}
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// 测试边界情况
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TEST_F(FrameDrawerTest, EdgeCases) {
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ASSERT_TRUE(drawer_.init(config_));
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// 测试空图像
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cv::Mat empty_frame;
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EXPECT_FALSE(drawer_.processFrame(empty_frame, test_results_, metrics_));
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// 测试灰度图像
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cv::Mat gray_frame(480, 640, CV_8UC1, cv::Scalar(128));
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EXPECT_TRUE(drawer_.processFrame(gray_frame, test_results_, metrics_));
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}
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int main(int argc, char **argv) {
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testing::InitGoogleTest(&argc, argv);
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return RUN_ALL_TESTS();
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}
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