diff --git a/.gitignore b/.gitignore index 57a9243..2500adf 100644 --- a/.gitignore +++ b/.gitignore @@ -1,38 +1,38 @@ -# Build directories -build/ -bin/ -lib/ - -# IDE files -.vscode/ -.idea/ -*.swp -*.swo - -# Compiled files -*.o -*.so -*.a -*.dll -*.dylib - -# CMake files -CMakeCache.txt -CMakeFiles/ -cmake_install.cmake -compile_commands.json - -# TensorRT engine files -*.engine -*.plan - -# Python cache -__pycache__/ -*.py[cod] - -# Logs -*.log - -# System files -.DS_Store +# Build directories +build/ +bin/ +lib/ + +# IDE files +.vscode/ +.idea/ +*.swp +*.swo + +# Compiled files +*.o +*.so +*.a +*.dll +*.dylib + +# CMake files +CMakeCache.txt +CMakeFiles/ +cmake_install.cmake +compile_commands.json + +# TensorRT engine files +*.engine +*.plan + +# Python cache +__pycache__/ +*.py[cod] + +# Logs +*.log + +# System files +.DS_Store Thumbs.db \ No newline at end of file diff --git a/README.md b/README.md index f8ab627..cec1dd2 100644 --- a/README.md +++ b/README.md @@ -117,12 +117,15 @@ inference: engine_path: "/app/models/yolov8n.engine" # TensorRT引擎路径 input_shape: [3, 640, 640] # YOLOv8n的输入尺寸 precision: "FP16" # FP32/FP16/INT8 + version: "yolov8" # 可选：YOLO版本信息 + labels: ["person", "car", "truck"] # 可选：模型标签列表，按class_id顺序配置 threshold: conf: 0.5 nms: 0.45 gpu_id: 0 render: + enable: true # 控制是否启用渲染功能 window: name: "Detection Results" width: 1280 diff --git a/assistant_snippet_Hs+Hs+Hs+.txt b/assistant_snippet_Hs+Hs+Hs+.txt new file mode 100644 index 0000000..21ef619 --- /dev/null +++ b/assistant_snippet_Hs+Hs+Hs+.txt @@ -0,0 +1 @@ +1|[ERROR] Error parsing log config: yaml-cpp: error at line 60, column 1: bad conversion \ No newline at end of file diff --git a/assistant_snippet_Hs+Hs+Hs+H.txt b/assistant_snippet_Hs+Hs+Hs+H.txt new file mode 100644 index 0000000..17e0c8b --- /dev/null +++ b/assistant_snippet_Hs+Hs+Hs+H.txt @@ -0,0 +1,3 @@ +1|log: +2| level: info +3| save_path: \ No newline at end of file diff --git a/assistant_snippet_Hy+Hs2Iqxm.txt b/assistant_snippet_Hy+Hs2Iqxm.txt new file mode 100644 index 0000000..4d32233 --- /dev/null +++ b/assistant_snippet_Hy+Hs2Iqxm.txt @@ -0,0 +1,5 @@ +1|TEST_F(PipelineTest, Initialization) { +2| Pipeline pipeline(config_path_, true); // 使用测试模式 +3| ASSERT_TRUE(pipeline.init()); +4| EXPECT_TRUE(pipeline.isRunning()); +5|} \ No newline at end of file diff --git a/docs/api_reference.md b/docs/api_reference.md index 4a51e6b..08e4fc0 100644 --- a/docs/api_reference.md +++ b/docs/api_reference.md @@ -42,6 +42,66 @@ rtsp: - 默认值：30.0 - 说明：目标帧率，用于控制读取速度，设置为 0 则不限制帧率 +### YOLO 模型配置 +YOLO 模型相关配置位于配置文件的 `inference.model` 部分： + +```yaml +inference: + model: + onnx_path: "/app/models/yolov8n.onnx" # ONNX模型路径 + engine_path: "/app/models/yolov8n.engine" # TensorRT引擎路径 + input_shape: [3, 640, 640] # YOLOv8n的输入尺寸 + precision: "FP16" # FP32/FP16/INT8 + version: "yolov8" # 可选：YOLO版本信息 + labels: ["person", "car", "truck"] # 可选：模型标签列表 + threshold: + conf: 0.5 # 置信度阈值 + nms: 0.45 # NMS阈值 + gpu_id: 0 # GPU设备ID +``` + +#### 参数说明 +- `onnx_path`: ONNX模型文件路径，必须指定 +- `engine_path`: TensorRT引擎文件路径，必须指定 +- `input_shape`: + - 类型：整数数组 [channels, height, width] + - 默认值：[3, 640, 640] + - 说明：模型输入尺寸，必须与模型定义匹配 + +- `precision`: + - 类型：字符串 + - 默认值："FP16" + - 可选值：["FP32", "FP16", "INT8"] + - 说明：模型精度模式，影响推理速度和精度 + +- `version`: + - 类型：字符串 + - 默认值：空 + - 可选值：任意字符串 + - 说明：YOLO模型版本信息，用于记录和管理 + +- `labels`: + - 类型：字符串数组 + - 默认值：空 + - 说明：模型支持的标签列表，按class_id顺序排列 + +- `threshold.conf`: + - 类型：浮点数 + - 默认值：0.5 + - 范围：[0.0, 1.0] + - 说明：检测置信度阈值，低于此值的检测框会被过滤 + +- `threshold.nms`: + - 类型：浮点数 + - 默认值：0.45 + - 范围：[0.0, 1.0] + - 说明：非极大值抑制阈值，用于过滤重叠框 + +- `gpu_id`: + - 类型：整数 + - 默认值：0 + - 说明：使用的GPU设备ID + ## 类说明 ### RtspReader diff --git a/pipeline/common/config_parser.hpp b/pipeline/common/config_parser.hpp index 2e995dc..b286daa 100644 --- a/pipeline/common/config_parser.hpp +++ b/pipeline/common/config_parser.hpp @@ -34,10 +34,14 @@ struct ModelConfig { float nms{0.45f}; // NMS阈值 } threshold; int gpu_id{0}; // GPU设备ID + std::vector labels; // 可选：模型标签列表 + std::string version; // 可选：YOLO版本信息 }; // 渲染配置 struct RenderConfig { + bool enable{true}; // 控制是否启用渲染功能，默认启用 + // 窗口配置 struct { std::string name{"Detection Results"}; diff --git a/pipeline/common/pipeline.cpp b/pipeline/common/pipeline.cpp index c4128fd..3c9b7ed 100644 --- a/pipeline/common/pipeline.cpp +++ b/pipeline/common/pipeline.cpp @@ -11,6 +11,9 @@ namespace { renderer::RendererConfig convertToRendererConfig(const RenderConfig& config) { renderer::RendererConfig renderer_config; + // 转换渲染启用状态 + renderer_config.enable = config.enable; + // 转换窗口配置 renderer_config.window_name = config.window.name; renderer_config.window_width = config.window.width; diff --git a/pipeline/common/yaml_config_parser.cpp b/pipeline/common/yaml_config_parser.cpp index 60d9589..00526fc 100644 --- a/pipeline/common/yaml_config_parser.cpp +++ b/pipeline/common/yaml_config_parser.cpp @@ -1,467 +1,503 @@ -#include "yaml_config_parser.hpp" -#include "../common/logger.hpp" -#include -#include -#include - -namespace pipeline { - -bool YamlConfigParser::parse(const std::string& config_file) { - try { - Logger::info("Parsing config file: " + config_file); - yaml_config_ = YAML::LoadFile(config_file); - - // 解析各个配置部分 - if (!parseInputConfig(yaml_config_["input"])) { - Logger::error("Failed to parse input config"); - return false; - } - - if (!parseModelConfig(yaml_config_["inference"])) { - Logger::error("Failed to parse model config"); - return false; - } - - if (!parseRenderConfig(yaml_config_["render"])) { - Logger::error("Failed to parse render config"); - return false; - } - - if (!parseOutputConfig(yaml_config_["output"])) { - Logger::error("Failed to parse output config"); - return false; - } - - if (!parseLogConfig(yaml_config_["log"])) { - Logger::error("Failed to parse log config"); - return false; - } - - Logger::info("Successfully parsed all configurations"); - return true; - } catch (const YAML::Exception& e) { - Logger::error("YAML parsing error: " + std::string(e.what())); - return false; - } catch (const std::exception& e) { - Logger::error("Error in parse: " + std::string(e.what())); - return false; - } -} - -bool YamlConfigParser::validate() { - // 基本验证 - if (config_.input.sources.empty()) { - std::cerr << "Error: No input sources configured" << std::endl; - return false; - } - - // 验证输入源配置 - for (const auto& source : config_.input.sources) { - if (source.type.empty() || source.name.empty()) { - std::cerr << "Error: Input source missing type or name" << std::endl; - return false; - } - if (source.type == "rtsp" && source.url.empty()) { - std::cerr << "Error: RTSP source missing URL" << std::endl; - return false; - } - if (source.buffer_size <= 0) { - std::cerr << "Error: Invalid buffer size for source: " << source.name << std::endl; - return false; - } - } - - // 验证推理配置 - if (config_.inference.engine_path.empty()) { - std::cerr << "Error: Model engine path not specified" << std::endl; - return false; - } - if (config_.inference.input_shape.empty()) { - std::cerr << "Error: Model input shape not specified" << std::endl; - return false; - } - if (config_.inference.threshold.conf < 0.0f || config_.inference.threshold.conf > 1.0f) { - std::cerr << "Error: Invalid confidence threshold (must be between 0.0 and 1.0)" << std::endl; - return false; - } - if (config_.inference.threshold.nms < 0.0f || config_.inference.threshold.nms > 1.0f) { - std::cerr << "Error: Invalid NMS threshold (must be between 0.0 and 1.0)" << std::endl; - return false; - } - - // 验证渲染配置 - // 验证窗口配置 - if (config_.render.window.width <= 0 || config_.render.window.height <= 0) { - std::cerr << "Error: Invalid window dimensions" << std::endl; - return false; - } - if (config_.render.window.name.empty()) { - std::cerr << "Error: Window name not specified" << std::endl; - return false; - } - - // 验证默认样式 - if (config_.render.default_style.transparency < 0.0f || - config_.render.default_style.transparency > 1.0f) { - std::cerr << "Error: Invalid default style transparency (must be between 0.0 and 1.0)" << std::endl; - return false; - } - if (config_.render.default_style.box_thickness <= 0 || - config_.render.default_style.font_thickness <= 0) { - std::cerr << "Error: Invalid default style thickness values" << std::endl; - return false; - } - if (config_.render.default_style.font_scale <= 0.0) { - std::cerr << "Error: Invalid default style font scale" << std::endl; - return false; - } - - // 验证类别样式 - for (const auto& [class_name, style] : config_.render.class_styles) { - if (class_name.empty()) { - std::cerr << "Error: Empty class name in style configuration" << std::endl; - return false; - } - if (style.transparency < 0.0f || style.transparency > 1.0f) { - std::cerr << "Error: Invalid transparency for class " << class_name << std::endl; - return false; - } - if (style.box_thickness <= 0 || style.font_thickness <= 0) { - std::cerr << "Error: Invalid thickness values for class " << class_name << std::endl; - return false; - } - if (style.font_scale <= 0.0) { - std::cerr << "Error: Invalid font scale for class " << class_name << std::endl; - return false; - } - } - - // 验证性能指标配置 - if (config_.render.metrics.update_interval_ms <= 0) { - std::cerr << "Error: Invalid metrics update interval" << std::endl; - return false; - } - - // 验证输出配置 - for (const auto& target : config_.output.targets) { - if (target.type.empty() || target.name.empty()) { - std::cerr << "Error: Output target missing type or name" << std::endl; - return false; - } - if (target.type == "video") { - if (target.path.empty()) { - std::cerr << "Error: Video output target missing path" << std::endl; - return false; - } - if (target.fps <= 0) { - std::cerr << "Error: Invalid video output fps" << std::endl; - return false; - } - if (target.bitrate <= 0) { - std::cerr << "Error: Invalid video output bitrate" << std::endl; - return false; - } - if (target.codec.empty()) { - std::cerr << "Error: Video output codec not specified" << std::endl; - return false; - } - } - } - - // 验证日志配置 - if (config_.log.level.empty()) { - std::cerr << "Error: Log level not specified" << std::endl; - return false; - } - if (config_.log.save_path.empty()) { - std::cerr << "Error: Log save path not specified" << std::endl; - return false; - } - - return true; -} - -bool YamlConfigParser::parseInputConfig(const YAML::Node& node) { - try { - // 解析输入源 - if (node["sources"]) { - for (const auto& source : node["sources"]) { - InputSourceConfig src_config; - src_config.type = source["type"].as(); - src_config.name = source["name"].as(); - if (source["url"]) { - src_config.url = source["url"].as(); - } - if (source["buffer_size"]) { - src_config.buffer_size = source["buffer_size"].as(); - } - // 解析输出目标列表 - if (source["outputs"]) { - src_config.outputs = source["outputs"].as>(); - } - config_.input.sources.push_back(src_config); - } - } - - // 解析批处理大小 - if (node["max_batch_size"]) { - config_.input.max_batch_size = node["max_batch_size"].as(); - } - - return true; - } catch (const YAML::Exception& e) { - Logger::error("Error parsing input config: " + std::string(e.what())); - return false; - } -} - -bool YamlConfigParser::parseModelConfig(const YAML::Node& node) { - try { - if (!node["model"]) { - Logger::error("Model configuration section not found"); - return false; - } - - const auto& model = node["model"]; - - // 检查必需的字段 - if (!model["onnx_path"]) { - Logger::error("ONNX path not specified in model config"); - return false; - } - if (!model["engine_path"]) { - Logger::error("Engine path not specified in model config"); - return false; - } - if (!model["input_shape"]) { - Logger::error("Input shape not specified in model config"); - return false; - } - - // 读取配置 - config_.inference.engine_path = model["engine_path"].as(); - config_.inference.input_shape = model["input_shape"].as>(); - config_.inference.precision = model["precision"] ? model["precision"].as() : "FP16"; - - // 读取阈值配置 - if (node["threshold"]) { - config_.inference.threshold.conf = node["threshold"]["conf"] ? - node["threshold"]["conf"].as() : 0.5f; - config_.inference.threshold.nms = node["threshold"]["nms"] ? - node["threshold"]["nms"].as() : 0.45f; - } - - // 读取GPU ID - config_.inference.gpu_id = node["gpu_id"] ? node["gpu_id"].as() : 0; - - // 打印读取的配置 - Logger::info("Loaded model configuration:"); - Logger::info(" Engine path: " + config_.inference.engine_path); - Logger::info(" Input shape: " + std::to_string(config_.inference.input_shape[0]) + "," + - std::to_string(config_.inference.input_shape[1]) + "," + - std::to_string(config_.inference.input_shape[2])); - Logger::info(" Precision: " + config_.inference.precision); - Logger::info(" GPU ID: " + std::to_string(config_.inference.gpu_id)); - Logger::info(" Confidence threshold: " + std::to_string(config_.inference.threshold.conf)); - Logger::info(" NMS threshold: " + std::to_string(config_.inference.threshold.nms)); - - return true; - } catch (const YAML::Exception& e) { - Logger::error("Failed to parse model config: " + std::string(e.what())); - return false; - } catch (const std::exception& e) { - Logger::error("Error in parseModelConfig: " + std::string(e.what())); - return false; - } -} - -bool YamlConfigParser::parseRenderConfig(const YAML::Node& node) { - try { - // 解析窗口配置 - if (node["window"]) { - const auto& window = node["window"]; - if (window["name"]) { - config_.render.window.name = window["name"].as(); - } - if (window["width"]) { - config_.render.window.width = window["width"].as(); - } - if (window["height"]) { - config_.render.window.height = window["height"].as(); - } - if (window["fullscreen"]) { - config_.render.window.fullscreen = window["fullscreen"].as(); - } - } - - // 解析默认样式 - if (node["default_style"]) { - const auto& style = node["default_style"]; - if (style["box_color"]) { - auto color = style["box_color"].as>(); - if (color.size() >= 3) { - config_.render.default_style.box_color = cv::Scalar(color[0], color[1], color[2]); - } - } - if (style["text_color"]) { - auto color = style["text_color"].as>(); - if (color.size() >= 3) { - config_.render.default_style.text_color = cv::Scalar(color[0], color[1], color[2]); - } - } - if (style["transparency"]) { - config_.render.default_style.transparency = style["transparency"].as(); - } - if (style["box_thickness"]) { - config_.render.default_style.box_thickness = style["box_thickness"].as(); - } - if (style["font_scale"]) { - config_.render.default_style.font_scale = style["font_scale"].as(); - } - if (style["font_thickness"]) { - config_.render.default_style.font_thickness = style["font_thickness"].as(); - } - } - - // 解析类别样式 - if (node["class_styles"]) { - for (const auto& class_style : node["class_styles"]) { - std::string class_name = class_style.first.as(); - const auto& style = class_style.second; - RenderConfig::ClassStyle class_config; - - if (style["box_color"]) { - auto color = style["box_color"].as>(); - if (color.size() >= 3) { - class_config.box_color = cv::Scalar(color[0], color[1], color[2]); - } - } - if (style["text_color"]) { - auto color = style["text_color"].as>(); - if (color.size() >= 3) { - class_config.text_color = cv::Scalar(color[0], color[1], color[2]); - } - } - if (style["transparency"]) { - class_config.transparency = style["transparency"].as(); - } - if (style["box_thickness"]) { - class_config.box_thickness = style["box_thickness"].as(); - } - if (style["font_scale"]) { - class_config.font_scale = style["font_scale"].as(); - } - if (style["font_thickness"]) { - class_config.font_thickness = style["font_thickness"].as(); - } - - config_.render.class_styles[class_name] = class_config; - } - } - - // 解析性能指标配置 - if (node["metrics"]) { - const auto& metrics = node["metrics"]; - if (metrics["show_fps"]) { - config_.render.metrics.show_fps = metrics["show_fps"].as(); - } - if (metrics["show_inference_time"]) { - config_.render.metrics.show_inference_time = metrics["show_inference_time"].as(); - } - if (metrics["show_gpu_usage"]) { - config_.render.metrics.show_gpu_usage = metrics["show_gpu_usage"].as(); - } - if (metrics["update_interval_ms"]) { - config_.render.metrics.update_interval_ms = metrics["update_interval_ms"].as(); - } - } - - return true; - } catch (const YAML::Exception& e) { - Logger::error("Error parsing render config: " + std::string(e.what())); - return false; - } -} - -bool YamlConfigParser::parseOutputConfig(const YAML::Node& node) { - try { - if (node["targets"]) { - for (const auto& target : node["targets"]) { - OutputTargetConfig target_config; - target_config.type = target["type"].as(); - target_config.name = target["name"].as(); - if (target["path"]) { - target_config.path = target["path"].as(); - } - if (target["fps"]) { - target_config.fps = target["fps"].as(); - } - if (target["codec"]) { - target_config.codec = target["codec"].as(); - } - if (target["bitrate"]) { - target_config.bitrate = target["bitrate"].as(); - } - config_.output.targets.push_back(target_config); - } - } - return true; - } catch (const YAML::Exception& e) { - return false; - } -} - -bool YamlConfigParser::parseLogConfig(const YAML::Node& node) { - try { - if (node["level"]) { - config_.log.level = node["level"].as(); - } - if (node["save_path"]) { - config_.log.save_path = node["save_path"].as(); - } - return true; - } catch (const YAML::Exception& e) { - return false; - } -} - -bool YamlConfigParser::parseRtspConfig(const YAML::Node& config, RtspReader::Config& rtsp_config) { - try { - auto rtsp_node = config["rtsp"]; - if (!rtsp_node) { - return false; - } - - // 设置默认值 - rtsp_config = RtspReader::Config(); - - // 读取配置 - if (rtsp_node["buffer_size"]) { - rtsp_config.buffer_size = rtsp_node["buffer_size"].as(); - } - if (rtsp_node["max_retry_count"]) { - rtsp_config.max_retry_count = rtsp_node["max_retry_count"].as(); - } - if (rtsp_node["retry_interval_ms"]) { - rtsp_config.retry_interval_ms = rtsp_node["retry_interval_ms"].as(); - } - if (rtsp_node["frame_timeout_ms"]) { - rtsp_config.frame_timeout_ms = rtsp_node["frame_timeout_ms"].as(); - } - if (rtsp_node["target_fps"]) { - rtsp_config.target_fps = rtsp_node["target_fps"].as(); - } - - return true; - } catch (const YAML::Exception& e) { - Logger::error("Error parsing RTSP config: " + std::string(e.what())); - return false; - } -} - -// 工厂函数实现 -std::unique_ptr createConfigParser() { - return std::make_unique(); -} - +#include "yaml_config_parser.hpp" +#include "../common/logger.hpp" +#include +#include +#include + +namespace pipeline { + +bool YamlConfigParser::parse(const std::string& config_file) { + try { + Logger::info("Parsing config file: " + config_file); + yaml_config_ = YAML::LoadFile(config_file); + + // 解析各个配置部分 + if (!parseInputConfig(yaml_config_["input"])) { + Logger::error("Failed to parse input config"); + return false; + } + + if (!parseModelConfig(yaml_config_["inference"])) { + Logger::error("Failed to parse model config"); + return false; + } + + if (!parseRenderConfig(yaml_config_["render"])) { + Logger::error("Failed to parse render config"); + return false; + } + + if (!parseOutputConfig(yaml_config_["output"])) { + Logger::error("Failed to parse output config"); + return false; + } + + if (!parseLogConfig(yaml_config_["log"])) { + Logger::error("Failed to parse log config"); + return false; + } + + Logger::info("Successfully parsed all configurations"); + return true; + } catch (const YAML::Exception& e) { + Logger::error("YAML parsing error: " + std::string(e.what())); + return false; + } catch (const std::exception& e) { + Logger::error("Error in parse: " + std::string(e.what())); + return false; + } +} + +bool YamlConfigParser::validate() { + // 基本验证 + if (config_.input.sources.empty()) { + std::cerr << "Error: No input sources configured" << std::endl; + return false; + } + + // 验证输入源配置 + for (const auto& source : config_.input.sources) { + if (source.type.empty() || source.name.empty()) { + std::cerr << "Error: Input source missing type or name" << std::endl; + return false; + } + if (source.type == "rtsp" && source.url.empty()) { + std::cerr << "Error: RTSP source missing URL" << std::endl; + return false; + } + if (source.buffer_size <= 0) { + std::cerr << "Error: Invalid buffer size for source: " << source.name << std::endl; + return false; + } + } + + // 验证推理配置 + if (config_.inference.engine_path.empty()) { + std::cerr << "Error: Model engine path not specified" << std::endl; + return false; + } + if (config_.inference.input_shape.empty()) { + std::cerr << "Error: Model input shape not specified" << std::endl; + return false; + } + if (config_.inference.threshold.conf < 0.0f || config_.inference.threshold.conf > 1.0f) { + std::cerr << "Error: Invalid confidence threshold (must be between 0.0 and 1.0)" << std::endl; + return false; + } + if (config_.inference.threshold.nms < 0.0f || config_.inference.threshold.nms > 1.0f) { + std::cerr << "Error: Invalid NMS threshold (must be between 0.0 and 1.0)" << std::endl; + return false; + } + + // 验证渲染配置 + // 验证窗口配置 + if (config_.render.window.width <= 0 || config_.render.window.height <= 0) { + std::cerr << "Error: Invalid window dimensions" << std::endl; + return false; + } + if (config_.render.window.name.empty()) { + std::cerr << "Error: Window name not specified" << std::endl; + return false; + } + + // 验证默认样式 + if (config_.render.default_style.transparency < 0.0f || + config_.render.default_style.transparency > 1.0f) { + std::cerr << "Error: Invalid default style transparency (must be between 0.0 and 1.0)" << std::endl; + return false; + } + if (config_.render.default_style.box_thickness <= 0 || + config_.render.default_style.font_thickness <= 0) { + std::cerr << "Error: Invalid default style thickness values" << std::endl; + return false; + } + if (config_.render.default_style.font_scale <= 0.0) { + std::cerr << "Error: Invalid default style font scale" << std::endl; + return false; + } + + // 验证类别样式 + for (const auto& [class_name, style] : config_.render.class_styles) { + if (class_name.empty()) { + std::cerr << "Error: Empty class name in style configuration" << std::endl; + return false; + } + if (style.transparency < 0.0f || style.transparency > 1.0f) { + std::cerr << "Error: Invalid transparency for class " << class_name << std::endl; + return false; + } + if (style.box_thickness <= 0 || style.font_thickness <= 0) { + std::cerr << "Error: Invalid thickness values for class " << class_name << std::endl; + return false; + } + if (style.font_scale <= 0.0) { + std::cerr << "Error: Invalid font scale for class " << class_name << std::endl; + return false; + } + } + + // 验证性能指标配置 + if (config_.render.metrics.update_interval_ms <= 0) { + std::cerr << "Error: Invalid metrics update interval" << std::endl; + return false; + } + + // 验证输出配置 + for (const auto& target : config_.output.targets) { + if (target.type.empty() || target.name.empty()) { + std::cerr << "Error: Output target missing type or name" << std::endl; + return false; + } + if (target.type == "video") { + if (target.path.empty()) { + std::cerr << "Error: Video output target missing path" << std::endl; + return false; + } + if (target.fps <= 0) { + std::cerr << "Error: Invalid video output fps" << std::endl; + return false; + } + if (target.bitrate <= 0) { + std::cerr << "Error: Invalid video output bitrate" << std::endl; + return false; + } + if (target.codec.empty()) { + std::cerr << "Error: Video output codec not specified" << std::endl; + return false; + } + } + } + + // 验证日志配置 + if (config_.log.level.empty()) { + std::cerr << "Error: Log level not specified" << std::endl; + return false; + } + if (config_.log.save_path.empty()) { + std::cerr << "Error: Log save path not specified" << std::endl; + return false; + } + + return true; +} + +bool YamlConfigParser::parseInputConfig(const YAML::Node& node) { + try { + // 解析输入源 + if (node["sources"]) { + for (const auto& source : node["sources"]) { + InputSourceConfig src_config; + src_config.type = source["type"].as(); + src_config.name = source["name"].as(); + if (source["url"]) { + src_config.url = source["url"].as(); + } + if (source["buffer_size"]) { + src_config.buffer_size = source["buffer_size"].as(); + } + // 解析输出目标列表 + if (source["outputs"]) { + src_config.outputs = source["outputs"].as>(); + } + config_.input.sources.push_back(src_config); + } + } + + // 解析批处理大小 + if (node["max_batch_size"]) { + config_.input.max_batch_size = node["max_batch_size"].as(); + } + + return true; + } catch (const YAML::Exception& e) { + Logger::error("Error parsing input config: " + std::string(e.what())); + return false; + } +} + +bool YamlConfigParser::parseModelConfig(const YAML::Node& node) { + try { + if (!node["model"]) { + Logger::error("Model configuration section not found"); + return false; + } + + const auto& model = node["model"]; + + // 检查必需的字段 + if (!model["onnx_path"]) { + Logger::error("ONNX path not specified in model config"); + return false; + } + if (!model["engine_path"]) { + Logger::error("Engine path not specified in model config"); + return false; + } + if (!model["input_shape"]) { + Logger::error("Input shape not specified in model config"); + return false; + } + + // 读取配置 + config_.inference.engine_path = model["engine_path"].as(); + config_.inference.input_shape = model["input_shape"].as>(); + config_.inference.precision = model["precision"] ? model["precision"].as() : "FP16"; + + // 读取可选的版本和标签配置 + if (model["version"]) { + config_.inference.version = model["version"].as(); + } + if (model["labels"]) { + config_.inference.labels = model["labels"].as>(); + } + + // 读取阈值配置 + if (node["threshold"]) { + config_.inference.threshold.conf = node["threshold"]["conf"] ? + node["threshold"]["conf"].as() : 0.5f; + config_.inference.threshold.nms = node["threshold"]["nms"] ? + node["threshold"]["nms"].as() : 0.45f; + } + + // 读取GPU设备ID + config_.inference.gpu_id = node["gpu_id"] ? node["gpu_id"].as() : 0; + + // 打印加载的配置信息 + Logger::info("Loaded model configuration:"); + Logger::info(" Engine path: " + config_.inference.engine_path); + Logger::info(" Input shape: " + std::to_string(config_.inference.input_shape[0]) + "," + + std::to_string(config_.inference.input_shape[1]) + "," + + std::to_string(config_.inference.input_shape[2])); + Logger::info(" Precision: " + config_.inference.precision); + Logger::info(" GPU ID: " + std::to_string(config_.inference.gpu_id)); + Logger::info(" Confidence threshold: " + std::to_string(config_.inference.threshold.conf)); + Logger::info(" NMS threshold: " + std::to_string(config_.inference.threshold.nms)); + if (!config_.inference.version.empty()) { + Logger::info(" Version: " + config_.inference.version); + } + if (!config_.inference.labels.empty()) { + std::string labels_str = " Labels: "; + for (const auto& label : config_.inference.labels) { + labels_str += label + ", "; + } + labels_str = labels_str.substr(0, labels_str.length() - 2); // 移除最后的", " + Logger::info(labels_str); + } + + return true; + } catch (const YAML::Exception& e) { + Logger::error("Error parsing model config: " + std::string(e.what())); + return false; + } +} + +bool YamlConfigParser::parseRenderConfig(const YAML::Node& node) { + try { + // 解析渲染启用状态 + if (node["enable"]) { + config_.render.enable = node["enable"].as(); + } + + // 解析窗口配置 + if (node["window"]) { + const auto& window = node["window"]; + if (window["name"]) { + config_.render.window.name = window["name"].as(); + } + if (window["width"]) { + config_.render.window.width = window["width"].as(); + } + if (window["height"]) { + config_.render.window.height = window["height"].as(); + } + if (window["fullscreen"]) { + config_.render.window.fullscreen = window["fullscreen"].as(); + } + } + + // 解析默认样式 + if (node["default_style"]) { + const auto& style = node["default_style"]; + if (style["box_color"]) { + auto color = style["box_color"].as>(); + if (color.size() >= 3) { + config_.render.default_style.box_color = cv::Scalar(color[0], color[1], color[2]); + } + } + if (style["text_color"]) { + auto color = style["text_color"].as>(); + if (color.size() >= 3) { + config_.render.default_style.text_color = cv::Scalar(color[0], color[1], color[2]); + } + } + if (style["transparency"]) { + config_.render.default_style.transparency = style["transparency"].as(); + } + if (style["box_thickness"]) { + config_.render.default_style.box_thickness = style["box_thickness"].as(); + } + if (style["font_scale"]) { + config_.render.default_style.font_scale = style["font_scale"].as(); + } + if (style["font_thickness"]) { + config_.render.default_style.font_thickness = style["font_thickness"].as(); + } + } + + // 解析类别样式 + if (node["class_styles"]) { + for (const auto& class_style : node["class_styles"]) { + std::string class_name = class_style.first.as(); + const auto& style = class_style.second; + RenderConfig::ClassStyle class_config; + + if (style["box_color"]) { + auto color = style["box_color"].as>(); + if (color.size() >= 3) { + class_config.box_color = cv::Scalar(color[0], color[1], color[2]); + } + } + if (style["text_color"]) { + auto color = style["text_color"].as>(); + if (color.size() >= 3) { + class_config.text_color = cv::Scalar(color[0], color[1], color[2]); + } + } + if (style["transparency"]) { + class_config.transparency = style["transparency"].as(); + } + if (style["box_thickness"]) { + class_config.box_thickness = style["box_thickness"].as(); + } + if (style["font_scale"]) { + class_config.font_scale = style["font_scale"].as(); + } + if (style["font_thickness"]) { + class_config.font_thickness = style["font_thickness"].as(); + } + + config_.render.class_styles[class_name] = class_config; + } + } + + // 解析性能指标配置 + if (node["metrics"]) { + const auto& metrics = node["metrics"]; + if (metrics["show_fps"]) { + config_.render.metrics.show_fps = metrics["show_fps"].as(); + } + if (metrics["show_inference_time"]) { + config_.render.metrics.show_inference_time = metrics["show_inference_time"].as(); + } + if (metrics["show_gpu_usage"]) { + config_.render.metrics.show_gpu_usage = metrics["show_gpu_usage"].as(); + } + if (metrics["update_interval_ms"]) { + config_.render.metrics.update_interval_ms = metrics["update_interval_ms"].as(); + } + } + + return true; + } catch (const YAML::Exception& e) { + Logger::error("Error parsing render config: " + std::string(e.what())); + return false; + } +} + +bool YamlConfigParser::parseOutputConfig(const YAML::Node& node) { + try { + if (node["targets"]) { + for (const auto& target : node["targets"]) { + OutputTargetConfig target_config; + target_config.type = target["type"].as(); + target_config.name = target["name"].as(); + if (target["path"]) { + target_config.path = target["path"].as(); + } + if (target["fps"]) { + target_config.fps = target["fps"].as(); + } + if (target["codec"]) { + target_config.codec = target["codec"].as(); + } + if (target["bitrate"]) { + target_config.bitrate = target["bitrate"].as(); + } + config_.output.targets.push_back(target_config); + } + } + return true; + } catch (const YAML::Exception& e) { + return false; + } +} + +bool YamlConfigParser::parseLogConfig(const YAML::Node& node) { + try { + // 检查必需的字段 + if (!node["level"]) { + Logger::error("Log level not specified"); + return false; + } + if (!node["save_path"]) { + Logger::error("Log save path not specified"); + return false; + } + + // 读取配置 + std::string level = node["level"].as(); + // 验证日志级别是否有效 + if (level.empty() || (level != "debug" && level != "info" && level != "warn" && level != "error")) { + Logger::error("Invalid log level: " + level); + return false; + } + config_.log.level = level; + config_.log.save_path = node["save_path"].as(); + + return true; + } catch (const YAML::Exception& e) { + Logger::error("Error parsing log config: " + std::string(e.what())); + return false; + } +} + +bool YamlConfigParser::parseRtspConfig(const YAML::Node& config, RtspReader::Config& rtsp_config) { + try { + auto rtsp_node = config["rtsp"]; + if (!rtsp_node) { + return false; + } + + // 设置默认值 + rtsp_config = RtspReader::Config(); + + // 读取配置 + if (rtsp_node["buffer_size"]) { + rtsp_config.buffer_size = rtsp_node["buffer_size"].as(); + } + if (rtsp_node["max_retry_count"]) { + rtsp_config.max_retry_count = rtsp_node["max_retry_count"].as(); + } + if (rtsp_node["retry_interval_ms"]) { + rtsp_config.retry_interval_ms = rtsp_node["retry_interval_ms"].as(); + } + if (rtsp_node["frame_timeout_ms"]) { + rtsp_config.frame_timeout_ms = rtsp_node["frame_timeout_ms"].as(); + } + if (rtsp_node["target_fps"]) { + rtsp_config.target_fps = rtsp_node["target_fps"].as(); + } + + return true; + } catch (const YAML::Exception& e) { + Logger::error("Error parsing RTSP config: " + std::string(e.what())); + return false; + } +} + +// 工厂函数实现 +std::unique_ptr createConfigParser() { + return std::make_unique(); +} + } // namespace pipeline \ No newline at end of file diff --git a/pipeline/common/yaml_config_parser.hpp b/pipeline/common/yaml_config_parser.hpp index ab3cbb7..d9ab971 100644 --- a/pipeline/common/yaml_config_parser.hpp +++ b/pipeline/common/yaml_config_parser.hpp @@ -1,37 +1,37 @@ -#pragma once - -#include -#include -#include -#include -#include "../input/rtsp_reader.hpp" -#include "config_parser.hpp" - -namespace pipeline { - -class YamlConfigParser : public ConfigParser { -public: - YamlConfigParser() = default; - ~YamlConfigParser() override = default; - - bool parse(const std::string& config_file); - bool validate() override; - const PipelineConfig& getConfig() const override { return config_; } - - // 配置解析函数 - bool parseInputConfig(const YAML::Node& node); - bool parseModelConfig(const YAML::Node& node); - bool parseRenderConfig(const YAML::Node& node); - bool parseOutputConfig(const YAML::Node& node); - bool parseLogConfig(const YAML::Node& node); - bool parseRtspConfig(const YAML::Node& config, RtspReader::Config& rtsp_config); - - // 获取原始配置 - const YAML::Node& getYamlConfig() const { return yaml_config_; } - -private: - PipelineConfig config_; - YAML::Node yaml_config_; -}; - +#pragma once + +#include +#include +#include +#include +#include "../input/rtsp_reader.hpp" +#include "config_parser.hpp" + +namespace pipeline { + +class YamlConfigParser : public ConfigParser { +public: + YamlConfigParser() = default; + ~YamlConfigParser() override = default; + + bool parse(const std::string& config_file); + bool validate() override; + const PipelineConfig& getConfig() const override { return config_; } + + // 配置解析函数 + bool parseInputConfig(const YAML::Node& node); + bool parseModelConfig(const YAML::Node& node); + bool parseRenderConfig(const YAML::Node& node); + bool parseOutputConfig(const YAML::Node& node); + bool parseLogConfig(const YAML::Node& node); + bool parseRtspConfig(const YAML::Node& config, RtspReader::Config& rtsp_config); + + // 获取原始配置 + const YAML::Node& getYamlConfig() const { return yaml_config_; } + +private: + PipelineConfig config_; + YAML::Node yaml_config_; +}; + } // namespace pipeline \ No newline at end of file diff --git a/pipeline/configs/pipeline.yaml b/pipeline/configs/pipeline.yaml index 3b489b7..e966492 100644 --- a/pipeline/configs/pipeline.yaml +++ b/pipeline/configs/pipeline.yaml @@ -1,87 +1,90 @@ -# Pipeline配置文件 - -input: - sources: - - type: rtsp - name: "camera1" - url: "rtsp://10.0.0.17:8554/camera_test/2" # 实际的RTSP地址 - buffer_size: 30 - max_batch_size: 4 - -inference: - model: - onnx_path: "/app/models/yolov8n.onnx" # ONNX模型路径 - engine_path: "/app/models/yolov8n.engine" # TensorRT引擎路径 - input_shape: [3, 640, 640] # YOLOv8n的输入尺寸 - precision: "FP16" # FP32/FP16/INT8 - threshold: - conf: 0.5 - nms: 0.45 - gpu_id: 0 - -render: - window: - name: "Detection Results" - width: 1280 - height: 720 - fullscreen: false - - # 默认渲染样式 - default_style: - box_color: [0, 255, 0] # BGR格式，默认绿色 - text_color: [255, 255, 255] # BGR格式，默认白色 - transparency: 0.0 # 0.0-1.0，0表示不透明 - box_thickness: 2 - font_scale: 0.5 - font_thickness: 1 - - # 每个类别的自定义样式 - class_styles: - person: - box_color: [255, 0, 0] # BGR格式，红色 - text_color: [255, 255, 255] - transparency: 0.2 - box_thickness: 2 - font_scale: 0.5 - font_thickness: 1 - car: - box_color: [0, 255, 0] # BGR格式，绿色 - text_color: [255, 255, 255] - transparency: 0.2 - box_thickness: 2 - font_scale: 0.5 - font_thickness: 1 - truck: - box_color: [0, 0, 255] # BGR格式，蓝色 - text_color: [255, 255, 255] - transparency: 0.2 - box_thickness: 2 - font_scale: 0.5 - font_thickness: 1 - - # 性能指标显示设置 - metrics: - show_fps: true - show_inference_time: true - show_gpu_usage: true - update_interval_ms: 1000 - -output: - targets: - - type: "video" - name: "output_video" - path: "/output/result.mp4" # 输出MP4文件路径 - fps: 30 - codec: "h264" # 视频编码器 - bitrate: 4000000 # 4Mbps - - type: "rtsp" - name: "output_rtsp" - path: "rtsp://localhost:8554/live" # RTSP推流地址 - fps: 30 - codec: "h264" # 视频编码器 - bitrate: 4000000 # 4Mbps - -# 日志配置 -log: - level: "info" # debug/info/warn/error - save_path: "logs/" # 日志保存路径 +# Pipeline配置文件 + +input: + sources: + - type: rtsp + name: "camera1" + url: "rtsp://10.0.0.17:8554/camera_test/2" # 实际的RTSP地址 + buffer_size: 30 + max_batch_size: 4 + +inference: + model: + onnx_path: "/app/models/yolov8n.onnx" # ONNX模型路径 + engine_path: "/app/models/yolov8n.engine" # TensorRT引擎路径 + input_shape: [3, 640, 640] # YOLOv8n的输入尺寸 + precision: "FP16" # FP32/FP16/INT8 + version: "yolov8" # 可选：YOLO版本信息 + labels: ["person", "car", "truck"] # 可选：模型标签列表 + threshold: + conf: 0.5 + nms: 0.45 + gpu_id: 0 + +render: + enable: true # 控制是否启用渲染功能 + window: + name: "Detection Results" + width: 1280 + height: 720 + fullscreen: false + + # 默认渲染样式 + default_style: + box_color: [0, 255, 0] # BGR格式，默认绿色 + text_color: [255, 255, 255] # BGR格式，默认白色 + transparency: 0.0 # 0.0-1.0，0表示不透明 + box_thickness: 2 + font_scale: 0.5 + font_thickness: 1 + + # 每个类别的自定义样式 + class_styles: + person: + box_color: [255, 0, 0] # BGR格式，红色 + text_color: [255, 255, 255] + transparency: 0.2 + box_thickness: 2 + font_scale: 0.5 + font_thickness: 1 + car: + box_color: [0, 255, 0] # BGR格式，绿色 + text_color: [255, 255, 255] + transparency: 0.2 + box_thickness: 2 + font_scale: 0.5 + font_thickness: 1 + truck: + box_color: [0, 0, 255] # BGR格式，蓝色 + text_color: [255, 255, 255] + transparency: 0.2 + box_thickness: 2 + font_scale: 0.5 + font_thickness: 1 + + # 性能指标显示设置 + metrics: + show_fps: true + show_inference_time: true + show_gpu_usage: true + update_interval_ms: 1000 + +output: + targets: + - type: "video" + name: "output_video" + path: "/output/result.mp4" # 输出MP4文件路径 + fps: 30 + codec: "h264" # 视频编码器 + bitrate: 4000000 # 4Mbps + - type: "rtsp" + name: "output_rtsp" + path: "rtsp://localhost:8554/live" # RTSP推流地址 + fps: 30 + codec: "h264" # 视频编码器 + bitrate: 4000000 # 4Mbps + +# 日志配置 +log: + level: "info" # debug/info/warn/error + save_path: "logs/" # 日志保存路径 diff --git a/pipeline/render/renderer.cpp b/pipeline/render/renderer.cpp index 9bbc7c6..d78b41d 100644 --- a/pipeline/render/renderer.cpp +++ b/pipeline/render/renderer.cpp @@ -41,6 +41,14 @@ bool Renderer::render(const cv::Mat& frame, } try { + // 如果渲染功能被禁用，直接返回原始帧的副本 + if (!config_.enable) { + Logger::info("Rendering is disabled, returning original frame"); + last_frame_ = frame.clone(); + return true; + } + + Logger::info("Rendering is enabled, processing frame"); // 创建帧的副本用于绘制 cv::Mat display_frame = frame.clone(); diff --git a/pipeline/render/renderer.hpp b/pipeline/render/renderer.hpp index 256e6e4..92170a3 100644 --- a/pipeline/render/renderer.hpp +++ b/pipeline/render/renderer.hpp @@ -13,6 +13,7 @@ namespace renderer { // 添加renderer命名空间 // 渲染器配置结构 struct RendererConfig { + bool enable; // 控制是否启用渲染功能，从配置文件中读取 std::string window_name = "Detection Results"; int window_width = 1280; int window_height = 720; diff --git a/pipeline/renderer/renderer.cpp b/pipeline/renderer/renderer.cpp new file mode 100644 index 0000000..0519ecb --- /dev/null +++ b/pipeline/renderer/renderer.cpp @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/test_data/videos/raw.mp4 b/test_data/videos/raw.mp4 new file mode 100644 index 0000000..472a359 Binary files /dev/null and b/test_data/videos/raw.mp4 differ diff --git a/tests/CMakeLists.txt b/tests/CMakeLists.txt index d10afd5..4f2b9d4 100644 --- a/tests/CMakeLists.txt +++ b/tests/CMakeLists.txt @@ -6,6 +6,9 @@ find_package(OpenCV REQUIRED) find_package(yaml-cpp REQUIRED) find_package(CUDA REQUIRED) +# 设置测试配置文件路径 +set(TEST_CONFIG_PATH ${CMAKE_SOURCE_DIR}/pipeline/configs/pipeline.yaml) + function(add_test_target target_name source_file) add_executable(${target_name} ${source_file}) target_link_libraries(${target_name} @@ -28,7 +31,13 @@ function(add_test_target target_name source_file) ${CMAKE_SOURCE_DIR} ${TENSORRT_INCLUDE_DIRS} ) - add_test(NAME ${target_name} COMMAND ${target_name}) + target_compile_definitions(${target_name} + PRIVATE + TEST_CONFIG_PATH="${TEST_CONFIG_PATH}" + ) + add_test(NAME ${target_name} + COMMAND ${target_name} + WORKING_DIRECTORY ${CMAKE_SOURCE_DIR}) endfunction() # 添加测试可执行文件 diff --git a/tests/test_base.hpp b/tests/test_base.hpp new file mode 100644 index 0000000..7f315d8 --- /dev/null +++ b/tests/test_base.hpp @@ -0,0 +1,25 @@ +#pragma once + +#include +#include +#include + +#ifndef TEST_CONFIG_PATH +#define TEST_CONFIG_PATH "../pipeline/configs/pipeline.yaml" +#endif + +namespace pipeline { +namespace test { + +class TestBase : public ::testing::Test { +protected: + const std::string config_path = TEST_CONFIG_PATH; + + void SetUp() override { + // 确保pipeline.yaml存在 + ASSERT_TRUE(std::filesystem::exists(config_path)) << "pipeline.yaml not found at: " << config_path; + } +}; + +} // namespace test +} // namespace pipeline \ No newline at end of file diff --git a/tests/test_config_parser.cpp b/tests/test_config_parser.cpp index 96719bb..0e2474a 100644 --- a/tests/test_config_parser.cpp +++ b/tests/test_config_parser.cpp @@ -1,100 +1,183 @@ -#include -#include "pipeline/common/config_parser.hpp" - -using namespace pipeline; - -// 测试配置数据结构的默认值 -TEST(ConfigParserTest, DefaultValues) { - // 测试InputSourceConfig默认值 - InputSourceConfig input_source; - EXPECT_EQ(input_source.buffer_size, 30); - EXPECT_TRUE(input_source.type.empty()); - EXPECT_TRUE(input_source.name.empty()); - EXPECT_TRUE(input_source.url.empty()); - - // 测试InputConfig默认值 - InputConfig input; - EXPECT_EQ(input.max_batch_size, 4); - EXPECT_TRUE(input.sources.empty()); - - // 测试ModelConfig默认值 - ModelConfig model; - EXPECT_TRUE(model.engine_path.empty()); - EXPECT_EQ(model.input_shape, std::vector({3, 640, 640})); - EXPECT_EQ(model.precision, "FP16"); - EXPECT_FLOAT_EQ(model.threshold.conf, 0.5f); - EXPECT_FLOAT_EQ(model.threshold.nms, 0.45f); - EXPECT_EQ(model.gpu_id, 0); - - // 测试RenderConfig默认值 - RenderConfig render; - EXPECT_TRUE(render.draw_fps); - EXPECT_TRUE(render.class_colors.empty()); - EXPECT_EQ(render.line_thickness, 2); - EXPECT_FLOAT_EQ(render.font_scale, 0.5f); - - // 测试OutputTargetConfig默认值 - OutputTargetConfig output_target; - EXPECT_TRUE(output_target.type.empty()); - EXPECT_TRUE(output_target.name.empty()); - EXPECT_TRUE(output_target.path.empty()); - EXPECT_EQ(output_target.fps, 30); - EXPECT_EQ(output_target.codec, "h264"); - EXPECT_EQ(output_target.bitrate, 4000000); - - // 测试LogConfig默认值 - LogConfig log; - EXPECT_EQ(log.level, "info"); - EXPECT_EQ(log.save_path, "logs/"); -} - -// 测试配置数据结构的赋值 -TEST(ConfigParserTest, Assignment) { - // 测试InputSourceConfig赋值 - InputSourceConfig input_source; - input_source.type = "rtsp"; - input_source.name = "camera1"; - input_source.url = "rtsp://example.com"; - input_source.buffer_size = 50; - - EXPECT_EQ(input_source.type, "rtsp"); - EXPECT_EQ(input_source.name, "camera1"); - EXPECT_EQ(input_source.url, "rtsp://example.com"); - EXPECT_EQ(input_source.buffer_size, 50); - - // 测试完整Pipeline配置 - PipelineConfig config; - - // 设置输入配置 - config.input.max_batch_size = 8; - config.input.sources.push_back(input_source); - - // 设置推理配置 - config.inference.engine_path = "/path/to/model.engine"; - config.inference.precision = "FP32"; - config.inference.threshold.conf = 0.6f; - - // 设置渲染配置 - config.render.draw_fps = false; - config.render.line_thickness = 3; - - // 验证设置的值 - EXPECT_EQ(config.input.max_batch_size, 8); - EXPECT_EQ(config.input.sources.size(), 1); - EXPECT_EQ(config.inference.engine_path, "/path/to/model.engine"); - EXPECT_EQ(config.inference.precision, "FP32"); - EXPECT_FLOAT_EQ(config.inference.threshold.conf, 0.6f); - EXPECT_FALSE(config.render.draw_fps); - EXPECT_EQ(config.render.line_thickness, 3); -} - -// 测试颜色配置 -TEST(ConfigParserTest, ColorConfig) { - RenderConfig render; - render.class_colors["person"] = cv::Scalar(255, 0, 0); // BGR - render.class_colors["car"] = cv::Scalar(0, 255, 0); - - EXPECT_EQ(render.class_colors.size(), 2); - EXPECT_EQ(render.class_colors["person"], cv::Scalar(255, 0, 0)); - EXPECT_EQ(render.class_colors["car"], cv::Scalar(0, 255, 0)); -} +#include +#include "pipeline/common/config_parser.hpp" + +using namespace pipeline; + +// 测试配置数据结构的默认值 +TEST(ConfigParserTest, DefaultValues) { + // 测试InputSourceConfig默认值 + InputSourceConfig input_source; + EXPECT_EQ(input_source.buffer_size, 30); + EXPECT_TRUE(input_source.type.empty()); + EXPECT_TRUE(input_source.name.empty()); + EXPECT_TRUE(input_source.url.empty()); + EXPECT_TRUE(input_source.outputs.empty()); + + // 测试InputConfig默认值 + InputConfig input; + EXPECT_EQ(input.max_batch_size, 4); + EXPECT_TRUE(input.sources.empty()); + + // 测试ModelConfig默认值 + ModelConfig model; + EXPECT_TRUE(model.engine_path.empty()); + EXPECT_EQ(model.input_shape, std::vector({3, 640, 640})); + EXPECT_EQ(model.precision, "FP16"); + EXPECT_FLOAT_EQ(model.threshold.conf, 0.5f); + EXPECT_FLOAT_EQ(model.threshold.nms, 0.45f); + EXPECT_EQ(model.gpu_id, 0); + EXPECT_TRUE(model.labels.empty()); + EXPECT_TRUE(model.version.empty()); + + // 测试RenderConfig默认值 + RenderConfig render; + EXPECT_EQ(render.window.name, "Detection Results"); + EXPECT_EQ(render.window.width, 1280); + EXPECT_EQ(render.window.height, 720); + EXPECT_FALSE(render.window.fullscreen); + + // 测试默认渲染样式 + EXPECT_EQ(render.default_style.box_color, cv::Scalar(0, 255, 0)); + EXPECT_EQ(render.default_style.text_color, cv::Scalar(255, 255, 255)); + EXPECT_FLOAT_EQ(render.default_style.transparency, 0.0f); + EXPECT_EQ(render.default_style.box_thickness, 2); + EXPECT_DOUBLE_EQ(render.default_style.font_scale, 0.5); + EXPECT_EQ(render.default_style.font_thickness, 1); + + // 测试性能指标显示设置 + EXPECT_TRUE(render.metrics.show_fps); + EXPECT_TRUE(render.metrics.show_inference_time); + EXPECT_TRUE(render.metrics.show_gpu_usage); + EXPECT_EQ(render.metrics.update_interval_ms, 1000); + + // 测试OutputTargetConfig默认值 + OutputTargetConfig output_target; + EXPECT_TRUE(output_target.type.empty()); + EXPECT_TRUE(output_target.name.empty()); + EXPECT_TRUE(output_target.path.empty()); + EXPECT_EQ(output_target.fps, 30); + EXPECT_EQ(output_target.codec, "h264"); + EXPECT_EQ(output_target.bitrate, 4000000); + + // 测试LogConfig默认值 + LogConfig log; + EXPECT_EQ(log.level, "info"); + EXPECT_EQ(log.save_path, "logs/"); +} + +// 测试配置数据结构的赋值 +TEST(ConfigParserTest, Assignment) { + // 测试InputSourceConfig赋值 + InputSourceConfig input_source; + input_source.type = "rtsp"; + input_source.name = "camera1"; + input_source.url = "rtsp://example.com"; + input_source.buffer_size = 50; + input_source.outputs = {"output1", "output2"}; + + EXPECT_EQ(input_source.type, "rtsp"); + EXPECT_EQ(input_source.name, "camera1"); + EXPECT_EQ(input_source.url, "rtsp://example.com"); + EXPECT_EQ(input_source.buffer_size, 50); + EXPECT_EQ(input_source.outputs.size(), 2); + + // 测试完整Pipeline配置 + PipelineConfig config; + + // 设置输入配置 + config.input.max_batch_size = 8; + config.input.sources.push_back(input_source); + + // 设置推理配置 + config.inference.engine_path = "/path/to/model.engine"; + config.inference.precision = "FP32"; + config.inference.threshold.conf = 0.6f; + config.inference.labels = {"person", "car"}; + config.inference.version = "yolov8"; + + // 设置渲染配置 + RenderConfig::ClassStyle style; + style.box_color = cv::Scalar(255, 0, 0); + config.render.class_styles["person"] = style; + + // 验证设置的值 + EXPECT_EQ(config.input.max_batch_size, 8); + EXPECT_EQ(config.input.sources.size(), 1); + EXPECT_EQ(config.inference.engine_path, "/path/to/model.engine"); + EXPECT_EQ(config.inference.precision, "FP32"); + EXPECT_FLOAT_EQ(config.inference.threshold.conf, 0.6f); + EXPECT_EQ(config.inference.labels.size(), 2); + EXPECT_EQ(config.inference.version, "yolov8"); + EXPECT_EQ(config.render.class_styles.size(), 1); +} + +// 测试渲染样式配置 +TEST(ConfigParserTest, RenderStyleConfig) { + RenderConfig render; + + // 设置自定义样式 + RenderConfig::ClassStyle person_style; + person_style.box_color = cv::Scalar(255, 0, 0); // BGR + person_style.text_color = cv::Scalar(255, 255, 255); + person_style.transparency = 0.2f; + render.class_styles["person"] = person_style; + + // 验证样式设置 + EXPECT_EQ(render.class_styles.size(), 1); + EXPECT_EQ(render.class_styles["person"].box_color, cv::Scalar(255, 0, 0)); + EXPECT_EQ(render.class_styles["person"].text_color, cv::Scalar(255, 255, 255)); + EXPECT_FLOAT_EQ(render.class_styles["person"].transparency, 0.2f); +} + +// 测试模型标签和版本配置 +TEST(ConfigParserTest, ModelLabelsAndVersion) { + // 测试ModelConfig的新增字段默认值 + ModelConfig model; + EXPECT_TRUE(model.labels.empty()); + EXPECT_TRUE(model.version.empty()); + + // 测试标签配置 + model.labels = {"person", "car", "truck"}; + EXPECT_EQ(model.labels.size(), 3); + EXPECT_EQ(model.labels[0], "person"); + EXPECT_EQ(model.labels[1], "car"); + EXPECT_EQ(model.labels[2], "truck"); + + // 测试版本配置 + model.version = "yolov8"; + EXPECT_EQ(model.version, "yolov8"); + + // 测试完整Pipeline配置中的标签和版本 + PipelineConfig config; + config.inference.labels = {"person", "car", "truck"}; + config.inference.version = "yolov8"; + + EXPECT_EQ(config.inference.labels.size(), 3); + EXPECT_EQ(config.inference.version, "yolov8"); +} + +// 测试渲染样式与标签的匹配 +TEST(ConfigParserTest, RenderStyleLabelMapping) { + PipelineConfig config; + + // 设置模型标签 + config.inference.labels = {"person", "car", "truck"}; + + // 设置渲染样式 + RenderConfig::ClassStyle person_style; + person_style.box_color = cv::Scalar(255, 0, 0); // BGR + config.render.class_styles["person"] = person_style; + + RenderConfig::ClassStyle car_style; + car_style.box_color = cv::Scalar(0, 255, 0); + config.render.class_styles["car"] = car_style; + + // 验证标签和样式的匹配 + EXPECT_EQ(config.render.class_styles.count("person"), 1); + EXPECT_EQ(config.render.class_styles.count("car"), 1); + EXPECT_EQ(config.render.class_styles["person"].box_color, cv::Scalar(255, 0, 0)); + EXPECT_EQ(config.render.class_styles["car"].box_color, cv::Scalar(0, 255, 0)); + + // 验证未配置样式的标签使用默认样式 + EXPECT_EQ(config.render.class_styles.count("truck"), 0); +} diff --git a/tests/test_output_manager.cpp b/tests/test_output_manager.cpp index 670860f..afd67ad 100644 --- a/tests/test_output_manager.cpp +++ b/tests/test_output_manager.cpp @@ -152,103 +152,100 @@ TEST_F(OutputManagerTest, ResourceManagement) { TEST_F(OutputManagerTest, ConcurrentWrite) { OutputManager manager; - // 添加多个视频输出目标 - for (int i = 0; i < 3; ++i) { - auto config = createVideoConfig("test_video_" + std::to_string(i)); - ASSERT_TRUE(manager.addTarget(config)); - } + // 添加两个视频输出目标 + auto video_config1 = createVideoConfig("test_video_concurrent1"); + ASSERT_TRUE(manager.addTarget(video_config1)); - // 创建多个线程同时写入 - std::vector threads; - for (int i = 0; i < 3; ++i) { - threads.emplace_back([&manager, this, i]() { - std::string source = "source_" + std::to_string(i); - std::vector targets = {"test_video_" + std::to_string(i)}; - EXPECT_TRUE(manager.addSourceTargetMapping(source, targets)); - for (int j = 0; j < 10; ++j) { - EXPECT_TRUE(manager.writeFrames(source, test_frame_)); - std::this_thread::sleep_for(std::chrono::milliseconds(10)); - } - }); - } + auto video_config2 = createVideoConfig("test_video_concurrent2"); + ASSERT_TRUE(manager.addTarget(video_config2)); - // 等待所有线程完成 - for (auto& thread : threads) { - thread.join(); - } + // 添加源到目标的映射 + ASSERT_TRUE(manager.addSourceTargetMapping("source1", {"test_video_concurrent1"})); + ASSERT_TRUE(manager.addSourceTargetMapping("source2", {"test_video_concurrent2"})); + + // 创建两个线程同时写入不同的输出目标 + std::thread t1([&]() { + for (int i = 0; i < 10; ++i) { + EXPECT_TRUE(manager.writeFrames("source1", test_frame_)); + std::this_thread::sleep_for(std::chrono::milliseconds(10)); + } + }); + + std::thread t2([&]() { + for (int i = 0; i < 10; ++i) { + EXPECT_TRUE(manager.writeFrames("source2", test_frame_)); + std::this_thread::sleep_for(std::chrono::milliseconds(10)); + } + }); + + // 等待线程完成 + t1.join(); + t2.join(); + + // 验证输出文件存在 + ASSERT_TRUE(fs::exists(video_config1.path)); + ASSERT_TRUE(fs::exists(video_config2.path)); +} + +// 测试一个输入源映射到多个输出目标 +TEST_F(OutputManagerTest, MultipleTargetsMapping) { + OutputManager manager; + + // 添加多个输出目标 + auto video_config1 = createVideoConfig("test_video_multi1"); + ASSERT_TRUE(manager.addTarget(video_config1)); + + auto video_config2 = createVideoConfig("test_video_multi2"); + ASSERT_TRUE(manager.addTarget(video_config2)); + + auto video_config3 = createVideoConfig("test_video_multi3"); + ASSERT_TRUE(manager.addTarget(video_config3)); + + // 将一个输入源映射到多个输出目标 + std::vector targets = { + "test_video_multi1", + "test_video_multi2", + "test_video_multi3" + }; + ASSERT_TRUE(manager.addSourceTargetMapping("source_multi", targets)); + + // 写入帧到所有映射的目标 + ASSERT_TRUE(manager.writeFrames("source_multi", test_frame_)); // 验证所有输出文件都存在 - for (int i = 0; i < 3; ++i) { - std::string path = test_dir_ + "/test_video_" + std::to_string(i) + ".mp4"; - EXPECT_TRUE(fs::exists(path)); - } + ASSERT_TRUE(fs::exists(video_config1.path)); + ASSERT_TRUE(fs::exists(video_config2.path)); + ASSERT_TRUE(fs::exists(video_config3.path)); } -// 测试配置验证 -TEST_F(OutputManagerTest, ConfigValidation) { +// 测试FPS参数边界值 +TEST_F(OutputManagerTest, FpsBoundaryTest) { OutputManager manager; - // 测试无效的类型 - { - OutputTargetConfig config; - config.type = "invalid"; - config.name = "test_invalid"; - EXPECT_FALSE(manager.addTarget(config)); - } + // 测试FPS为0 + auto config_fps_zero = createVideoConfig("test_video_fps_zero"); + config_fps_zero.fps = 0; + EXPECT_FALSE(manager.addTarget(config_fps_zero)); - // 测试空路径 - { - OutputTargetConfig config; - config.type = "video"; - config.name = "test_empty_path"; - config.path = ""; - EXPECT_FALSE(manager.addTarget(config)); - } + // 测试FPS为负数 + auto config_fps_negative = createVideoConfig("test_video_fps_negative"); + config_fps_negative.fps = -30; + EXPECT_FALSE(manager.addTarget(config_fps_negative)); - // 测试无效的帧率 - { - OutputTargetConfig config; - config.type = "video"; - config.name = "test_invalid_fps"; - config.path = test_dir_ + "/test.mp4"; - config.fps = 0; - EXPECT_FALSE(manager.addTarget(config)); - } + // 测试FPS为最小有效值 + auto config_fps_min = createVideoConfig("test_video_fps_min"); + config_fps_min.fps = 1; + EXPECT_TRUE(manager.addTarget(config_fps_min)); - // 测试无效的比特率 - { - OutputTargetConfig config; - config.type = "video"; - config.name = "test_invalid_bitrate"; - config.path = test_dir_ + "/test.mp4"; - config.bitrate = -1; - EXPECT_FALSE(manager.addTarget(config)); - } -} - -// 测试状态查询 -TEST_F(OutputManagerTest, StatusQuery) { - OutputManager manager; + // 测试FPS为正常值 + auto config_fps_normal = createVideoConfig("test_video_fps_normal"); + config_fps_normal.fps = 60; + EXPECT_TRUE(manager.addTarget(config_fps_normal)); - // 添加视频输出目标 - auto video_config = createVideoConfig("test_video_status"); - ASSERT_TRUE(manager.addTarget(video_config)); - - // 测试目标状态查询 - std::string error_msg; - EXPECT_TRUE(manager.getTargetStatus("test_video_status", error_msg)); - EXPECT_TRUE(error_msg.empty()); - - // 测试不存在的目标 - EXPECT_FALSE(manager.getTargetStatus("non_existent", error_msg)); - EXPECT_FALSE(error_msg.empty()); - - // 写入一些帧后检查状态 - for (int i = 0; i < 10; ++i) { - EXPECT_TRUE(manager.writeFrames("test_video_status", test_frame_)); - } - EXPECT_TRUE(manager.getTargetStatus("test_video_status", error_msg)); - EXPECT_TRUE(error_msg.empty()); + // 验证正常FPS的输出是否工作 + ASSERT_TRUE(manager.addSourceTargetMapping("source_fps", {"test_video_fps_normal"})); + ASSERT_TRUE(manager.writeFrames("source_fps", test_frame_)); + ASSERT_TRUE(fs::exists(config_fps_normal.path)); } } // namespace pipeline \ No newline at end of file diff --git a/tests/test_pipeline.cpp b/tests/test_pipeline.cpp index 595ccc0..4f6cf0b 100644 --- a/tests/test_pipeline.cpp +++ b/tests/test_pipeline.cpp @@ -3,16 +3,218 @@ #include #include #include "pipeline/common/pipeline.hpp" +#include "pipeline/common/yaml_config_parser.hpp" namespace fs = std::filesystem; +namespace pipeline { class PipelineTest : public ::testing::Test { protected: - void SetUp() override; - void TearDown() override; + void SetUp() override { + // 创建测试目录 + test_dir_ = "/tmp/test_pipeline"; + if (fs::exists(test_dir_)) { + fs::remove_all(test_dir_); + } + fs::create_directories(test_dir_); + + // 创建日志目录 + log_dir_ = test_dir_ + "/logs"; + fs::create_directories(log_dir_); + + // 创建测试视频 + video_path_ = test_dir_ + "/test_video.mp4"; + createTestVideo(video_path_); + + // 创建配置文件 + config_path_ = test_dir_ + "/config.yaml"; + createTestConfig(config_path_); + } + + void TearDown() override { + // 只在测试成功时删除文件 + if (!::testing::Test::HasFailure() && fs::exists(test_dir_)) { + fs::remove_all(test_dir_); + } + } + void createTestVideo(const std::string& path) { + cv::Mat frame(480, 640, CV_8UC3, cv::Scalar(0, 0, 0)); + cv::VideoWriter writer(path, cv::VideoWriter::fourcc('a', 'v', 'c', '1'), 30, frame.size()); + for (int i = 0; i < 30; ++i) { + cv::putText(frame, "Frame " + std::to_string(i), cv::Point(50, 50), + cv::FONT_HERSHEY_SIMPLEX, 1.0, cv::Scalar(255, 255, 255), 2); + writer.write(frame); + } + writer.release(); + } + + void createTestConfig(const std::string& path) { + std::ofstream config_file(path); + + // 输入配置 + config_file << "input:\n"; + config_file << " max_batch_size: 1\n"; + config_file << " sources:\n"; + config_file << " - type: video\n"; + config_file << " name: test_video\n"; + config_file << " url: " << video_path_ << "\n"; + config_file << " buffer_size: 30\n"; + config_file << " outputs: [output_video]\n"; + config_file << "\n"; + + // 推理配置 + config_file << "inference:\n"; + config_file << " model:\n"; + config_file << " onnx_path: /app/models/yolov8n.onnx\n"; + config_file << " engine_path: /app/models/yolov8n.engine\n"; + config_file << " input_shape: [3, 640, 640]\n"; + config_file << " precision: FP16\n"; + config_file << " threshold:\n"; + config_file << " conf: 0.5\n"; + config_file << " nms: 0.45\n"; + config_file << " gpu_id: 0\n"; + config_file << "\n"; + + // 渲染配置 + config_file << "render:\n"; + config_file << " enable: true\n"; + config_file << " window:\n"; + config_file << " name: Detection Results\n"; + config_file << " width: 1280\n"; + config_file << " height: 720\n"; + config_file << " fullscreen: false\n"; + config_file << " default_style:\n"; + config_file << " box_color: [0, 255, 0]\n"; + config_file << " text_color: [255, 255, 255]\n"; + config_file << " transparency: 0.0\n"; + config_file << " box_thickness: 2\n"; + config_file << " font_scale: 0.5\n"; + config_file << " font_thickness: 1\n"; + config_file << " class_styles:\n"; + config_file << " person:\n"; + config_file << " box_color: [0, 255, 0]\n"; + config_file << " text_color: [255, 255, 255]\n"; + config_file << " transparency: 0.0\n"; + config_file << " box_thickness: 2\n"; + config_file << " font_scale: 0.5\n"; + config_file << " font_thickness: 1\n"; + config_file << " metrics:\n"; + config_file << " show_fps: true\n"; + config_file << " show_inference_time: true\n"; + config_file << " show_gpu_usage: true\n"; + config_file << " update_interval_ms: 1000\n"; + config_file << "\n"; + + // 输出配置 + config_file << "output:\n"; + config_file << " targets:\n"; + config_file << " - type: video\n"; + config_file << " name: output_video\n"; + config_file << " path: " << test_dir_ << "/output.mp4\n"; + config_file << " fps: 30\n"; + config_file << " codec: h264\n"; + config_file << " bitrate: 4000000\n"; + config_file << "\n"; + + // 日志配置 + config_file << "log:\n"; + config_file << " level: info\n"; + config_file << " save_path: " << log_dir_ << "\n\n"; + + config_file.close(); + } + std::string test_dir_; std::string video_path_; std::string config_path_; std::string log_dir_; }; + +// 测试配置加载 +TEST_F(PipelineTest, ConfigLoading) { + YamlConfigParser parser; + ASSERT_TRUE(parser.parse(config_path_)); + + const auto& config = parser.getConfig(); + + // 验证输入配置 + EXPECT_EQ(config.input.max_batch_size, 1); + EXPECT_EQ(config.input.sources.size(), 1); + EXPECT_EQ(config.input.sources[0].type, "video"); + EXPECT_EQ(config.input.sources[0].name, "test_video"); + EXPECT_EQ(config.input.sources[0].url, video_path_); + + // 验证推理配置 + EXPECT_EQ(config.inference.engine_path, "/app/models/yolov8n.engine"); + EXPECT_EQ(config.inference.input_shape, std::vector({3, 640, 640})); + EXPECT_EQ(config.inference.precision, "FP16"); + + // 验证输出配置 + EXPECT_EQ(config.output.targets.size(), 1); + EXPECT_EQ(config.output.targets[0].type, "video"); + EXPECT_EQ(config.output.targets[0].name, "output_video"); +} + +// 测试Pipeline初始化 +TEST_F(PipelineTest, Initialization) { + Pipeline pipeline(config_path_, true); // 使用测试模式 + ASSERT_TRUE(pipeline.init()); + ASSERT_TRUE(pipeline.start()); + EXPECT_TRUE(pipeline.isRunning()); + pipeline.stop(); + pipeline.wait(); +} + +// 测试Pipeline运行 +TEST_F(PipelineTest, Running) { + Pipeline pipeline(config_path_, true); // 使用测试模式 + ASSERT_TRUE(pipeline.init()); + + // 运行一段时间 + ASSERT_TRUE(pipeline.start()); + std::this_thread::sleep_for(std::chrono::seconds(2)); + pipeline.stop(); + pipeline.wait(); + + // 验证输出文件是否生成 + std::string output_path = test_dir_ + "/output.mp4"; + EXPECT_TRUE(fs::exists(output_path)); + EXPECT_GT(fs::file_size(output_path), 0); +} + +// 测试错误处理 +TEST_F(PipelineTest, ErrorHandling) { + // 测试无效的配置文件 + Pipeline pipeline_invalid("invalid_config.yaml", true); + EXPECT_FALSE(pipeline_invalid.init()); + + // 测试无效的引擎路径 + std::string invalid_config_path = test_dir_ + "/invalid_config.yaml"; + std::ofstream config_file(invalid_config_path); + config_file << "inference:\n"; + config_file << " model:\n"; + config_file << " onnx_path: /app/models/yolov8n.onnx\n"; + config_file << " engine_path: invalid_engine_path\n"; + config_file << " input_shape: [3, 640, 640]\n"; + config_file.close(); + + Pipeline pipeline_invalid_engine(invalid_config_path, true); + EXPECT_FALSE(pipeline_invalid_engine.init()); +} + +// 测试资源管理 +TEST_F(PipelineTest, ResourceManagement) { + { + Pipeline pipeline(config_path_, true); + ASSERT_TRUE(pipeline.init()); + ASSERT_TRUE(pipeline.start()); + std::this_thread::sleep_for(std::chrono::seconds(1)); + // 不调用stop,让析构函数处理 + } + + // 验证资源是否正确释放 + EXPECT_TRUE(fs::exists(test_dir_ + "/output.mp4")); +} + +} // namespace pipeline diff --git a/tests/test_renderer.cpp b/tests/test_renderer.cpp index d9c5b6c..8e80035 100644 --- a/tests/test_renderer.cpp +++ b/tests/test_renderer.cpp @@ -13,6 +13,7 @@ protected: config_.window_height = 600; config_.fullscreen = false; config_.test_mode = true; // 启用测试模式 + config_.enable = true; // 默认启用渲染 // 创建测试图像 test_frame_ = cv::Mat(480, 640, CV_8UC3, cv::Scalar(0, 0, 0)); @@ -51,6 +52,30 @@ protected: return true; } + // 辅助函数：比较两个BGR图像是否相同 + bool compareBGRImages(const cv::Mat& img1, const cv::Mat& img2) { + if (img1.size() != img2.size() || img1.type() != img2.type()) { + std::cout << "Image size or type mismatch" << std::endl; + std::cout << "img1: " << img1.size() << " type: " << img1.type() << std::endl; + std::cout << "img2: " << img2.size() << " type: " << img2.type() << std::endl; + return false; + } + cv::Mat diff; + cv::absdiff(img1, img2, diff); + std::vector channels; + cv::split(diff, channels); + + // 检查每个通道的差异 + for (size_t i = 0; i < channels.size(); ++i) { + int nonZero = cv::countNonZero(channels[i]); + if (nonZero > 0) { + std::cout << "Channel " << i << " has " << nonZero << " different pixels" << std::endl; + return false; + } + } + return true; + } + renderer::RendererConfig config_; Renderer renderer_; cv::Mat test_frame_; @@ -143,6 +168,54 @@ TEST_F(RendererTest, EdgeCases) { EXPECT_TRUE(renderer_.render(gray_frame, test_results_, metrics_)); } +// 测试禁用渲染功能 +TEST_F(RendererTest, DisabledRendering) { + // 禁用渲染 + config_.enable = false; + ASSERT_TRUE(renderer_.init(config_)); + + // 创建一个有颜色的测试帧 + cv::Mat colored_frame(480, 640, CV_8UC3, cv::Scalar(255, 0, 0)); // 蓝色帧 + + // 渲染应该成功，但不会绘制任何检测结果 + EXPECT_TRUE(renderer_.render(colored_frame, test_results_, metrics_)); + + // 获取渲染后的帧 + cv::Mat rendered_frame = renderer_.getLastFrame(); + + // 验证帧未被修改（没有绘制检测框和文本） + EXPECT_TRUE(!rendered_frame.empty()); + EXPECT_EQ(rendered_frame.size(), colored_frame.size()); + + // 检查帧的内容是否与原始帧相同 + EXPECT_TRUE(compareBGRImages(rendered_frame, colored_frame)); +} + +// 测试启用和禁用渲染的切换 +TEST_F(RendererTest, ToggleRendering) { + // 创建一个有颜色的测试帧 + cv::Mat colored_frame(480, 640, CV_8UC3, cv::Scalar(255, 0, 0)); // 蓝色帧 + + // 先启用渲染 + config_.enable = true; + ASSERT_TRUE(renderer_.init(config_)); + EXPECT_TRUE(renderer_.render(colored_frame, test_results_, metrics_)); + cv::Mat rendered_frame_enabled = renderer_.getLastFrame(); + + // 验证检测结果被绘制（帧应该被修改） + EXPECT_FALSE(compareBGRImages(rendered_frame_enabled, colored_frame)); + + // 禁用渲染 + renderer_.cleanup(); // 先清理现有的渲染器 + config_.enable = false; + ASSERT_TRUE(renderer_.init(config_)); + EXPECT_TRUE(renderer_.render(colored_frame, test_results_, metrics_)); + cv::Mat rendered_frame_disabled = renderer_.getLastFrame(); + + // 验证帧未被修改 + EXPECT_TRUE(compareBGRImages(rendered_frame_disabled, colored_frame)); +} + int main(int argc, char **argv) { testing::InitGoogleTest(&argc, argv); return RUN_ALL_TESTS(); diff --git a/tests/test_video_reader.cpp b/tests/test_video_reader.cpp index f69e057..78fe970 100644 --- a/tests/test_video_reader.cpp +++ b/tests/test_video_reader.cpp @@ -1,5 +1,6 @@ #include #include "pipeline/input/video_reader.hpp" +#include "test_base.hpp" #include #include #include @@ -8,9 +9,10 @@ using namespace pipeline; -class VideoReaderTest : public ::testing::Test { +class VideoReaderTest : public test::TestBase { protected: void SetUp() override { + test::TestBase::SetUp(); // 调用基类的SetUp // 创建测试视频文件 createTestVideo("test_video.mp4"); } diff --git a/tests/test_yaml_config.cpp b/tests/test_yaml_config.cpp index 4956e0b..28f0f3f 100644 --- a/tests/test_yaml_config.cpp +++ b/tests/test_yaml_config.cpp @@ -1,367 +1,186 @@ -#include -#include "pipeline/common/yaml_config_parser.hpp" -#include -#include - -using namespace pipeline; - -class YamlConfigTest : public ::testing::Test { -protected: - void SetUp() override { - // 创建测试配置文件 - std::ofstream test_config("test_config.yaml"); - test_config << R"( -input: - sources: - - type: rtsp - name: camera1 - url: rtsp://example.com/stream1 - buffer_size: 30 - max_batch_size: 4 - -inference: - model: - onnx_path: /path/to/model.onnx - engine_path: /path/to/model.engine - input_shape: [3, 640, 640] - precision: FP16 - threshold: - conf: 0.5 - nms: 0.45 - gpu_id: 0 - -render: - window: - name: "Detection Results" - width: 1280 - height: 720 - fullscreen: false - - default_style: - box_color: [0, 255, 0] - text_color: [255, 255, 255] - transparency: 0.0 - box_thickness: 2 - font_scale: 0.5 - font_thickness: 1 - - class_styles: - person: - box_color: [255, 0, 0] - text_color: [255, 255, 255] - transparency: 0.2 - box_thickness: 2 - font_scale: 0.5 - font_thickness: 1 - car: - box_color: [0, 255, 0] - text_color: [255, 255, 255] - transparency: 0.2 - box_thickness: 2 - font_scale: 0.5 - font_thickness: 1 - - metrics: - show_fps: true - show_inference_time: true - show_gpu_usage: true - update_interval_ms: 1000 - -output: - targets: - - type: video - name: output1 - path: /path/to/output.mp4 - fps: 30 - codec: h264 - bitrate: 4000000 - -log: - level: info - save_path: logs/ -)"; - test_config.close(); - } - - void TearDown() override { - // 清理测试文件 - std::filesystem::remove("test_config.yaml"); - std::filesystem::remove("invalid_config.yaml"); - } -}; - -TEST_F(YamlConfigTest, LoadConfig) { - auto parser = createConfigParser(); - ASSERT_TRUE(parser->parse("test_config.yaml")); - - const auto& config = parser->getConfig(); - - // 验证输入配置 - ASSERT_EQ(config.input.sources.size(), 1); - EXPECT_EQ(config.input.sources[0].type, "rtsp"); - EXPECT_EQ(config.input.sources[0].name, "camera1"); - EXPECT_EQ(config.input.sources[0].url, "rtsp://example.com/stream1"); - EXPECT_EQ(config.input.sources[0].buffer_size, 30); - EXPECT_EQ(config.input.max_batch_size, 4); - - // 验证推理配置 - EXPECT_EQ(config.inference.engine_path, "/path/to/model.engine"); - ASSERT_EQ(config.inference.input_shape.size(), 3); - EXPECT_EQ(config.inference.input_shape[0], 3); - EXPECT_EQ(config.inference.input_shape[1], 640); - EXPECT_EQ(config.inference.input_shape[2], 640); - EXPECT_EQ(config.inference.precision, "FP16"); - EXPECT_FLOAT_EQ(config.inference.threshold.conf, 0.5f); - EXPECT_FLOAT_EQ(config.inference.threshold.nms, 0.45f); - EXPECT_EQ(config.inference.gpu_id, 0); - - // 验证渲染配置 - // 窗口配置 - EXPECT_EQ(config.render.window.name, "Detection Results"); - EXPECT_EQ(config.render.window.width, 1280); - EXPECT_EQ(config.render.window.height, 720); - EXPECT_FALSE(config.render.window.fullscreen); - - // 默认样式 - EXPECT_EQ(config.render.default_style.box_color, cv::Scalar(0, 255, 0)); - EXPECT_EQ(config.render.default_style.text_color, cv::Scalar(255, 255, 255)); - EXPECT_FLOAT_EQ(config.render.default_style.transparency, 0.0f); - EXPECT_EQ(config.render.default_style.box_thickness, 2); - EXPECT_DOUBLE_EQ(config.render.default_style.font_scale, 0.5); - EXPECT_EQ(config.render.default_style.font_thickness, 1); - - // 类别样式 - ASSERT_EQ(config.render.class_styles.size(), 2); - const auto& person_style = config.render.class_styles.at("person"); - EXPECT_EQ(person_style.box_color, cv::Scalar(255, 0, 0)); - EXPECT_EQ(person_style.text_color, cv::Scalar(255, 255, 255)); - EXPECT_FLOAT_EQ(person_style.transparency, 0.2f); - - const auto& car_style = config.render.class_styles.at("car"); - EXPECT_EQ(car_style.box_color, cv::Scalar(0, 255, 0)); - EXPECT_EQ(car_style.text_color, cv::Scalar(255, 255, 255)); - EXPECT_FLOAT_EQ(car_style.transparency, 0.2f); - - // 性能指标配置 - EXPECT_TRUE(config.render.metrics.show_fps); - EXPECT_TRUE(config.render.metrics.show_inference_time); - EXPECT_TRUE(config.render.metrics.show_gpu_usage); - EXPECT_EQ(config.render.metrics.update_interval_ms, 1000); - - // 验证输出配置 - ASSERT_EQ(config.output.targets.size(), 1); - EXPECT_EQ(config.output.targets[0].type, "video"); - EXPECT_EQ(config.output.targets[0].name, "output1"); - EXPECT_EQ(config.output.targets[0].path, "/path/to/output.mp4"); - EXPECT_EQ(config.output.targets[0].fps, 30); - EXPECT_EQ(config.output.targets[0].codec, "h264"); - EXPECT_EQ(config.output.targets[0].bitrate, 4000000); - - // 验证日志配置 - EXPECT_EQ(config.log.level, "info"); - EXPECT_EQ(config.log.save_path, "logs/"); -} - -TEST_F(YamlConfigTest, InvalidConfig) { - auto parser = createConfigParser(); - - // 测试不存在的文件 - EXPECT_FALSE(parser->parse("non_existent.yaml")); - - // 创建无效的配置文件 - std::ofstream invalid_config("invalid_config.yaml"); - invalid_config << R"( -input: - sources: [] # 空的输入源列表，这应该是无效的 -)"; - invalid_config.close(); - - // 测试无效的配置 - EXPECT_FALSE(parser->parse("invalid_config.yaml")); -} - -TEST_F(YamlConfigTest, InvalidConfigs) { - auto parser = createConfigParser(); - - // 测试各种无效配置场景 - std::vector> invalid_configs = { - // 空输入源 - {R"( -input: - sources: [] -inference: - model: - engine_path: /path/to/model.engine - input_shape: [3, 640, 640] - )", "空输入源"}, - - // 无效的输入源配置 - {R"( -input: - sources: - - type: rtsp - name: "" # 空名称 - url: rtsp://example.com/stream1 -inference: - model: - engine_path: /path/to/model.engine - input_shape: [3, 640, 640] - )", "无效的输入源名称"}, - - // 无效的推理配置 - {R"( -input: - sources: - - type: rtsp - name: camera1 - url: rtsp://example.com/stream1 -inference: - model: - engine_path: "" # 空引擎路径 - input_shape: [3, 640, 640] - )", "无效的引擎路径"}, - - // 无效的渲染配置 - {R"( -input: - sources: - - type: rtsp - name: camera1 - url: rtsp://example.com/stream1 -inference: - model: - engine_path: /path/to/model.engine - input_shape: [3, 640, 640] -render: - window: - name: "Detection Results" - width: -1 # 无效的窗口尺寸 - height: 720 - )", "无效的窗口尺寸"}, - - // 无效的样式配置 - {R"( -input: - sources: - - type: rtsp - name: camera1 - url: rtsp://example.com/stream1 -inference: - model: - engine_path: /path/to/model.engine - input_shape: [3, 640, 640] -render: - window: - name: "Detection Results" - width: 1280 - height: 720 - default_style: - transparency: 2.0 # 无效的透明度 - )", "无效的样式透明度"}, - - // 无效的输出配置 - {R"( -input: - sources: - - type: rtsp - name: camera1 - url: rtsp://example.com/stream1 -inference: - model: - engine_path: /path/to/model.engine - input_shape: [3, 640, 640] -output: - targets: - - type: video - name: output1 - path: "" # 空输出路径 - fps: 30 - )", "无效的输出路径"}, - - // 无效的日志配置 - {R"( -input: - sources: - - type: rtsp - name: camera1 - url: rtsp://example.com/stream1 -inference: - model: - engine_path: /path/to/model.engine - input_shape: [3, 640, 640] -log: - level: "" # 空日志级别 - save_path: logs/ - )", "无效的日志级别"} - }; - - for (const auto& [config_str, desc] : invalid_configs) { - std::ofstream config_file("invalid_config.yaml"); - config_file << config_str; - config_file.close(); - - EXPECT_FALSE(parser->parse("invalid_config.yaml")) << "应该检测到无效配置: " << desc; - std::filesystem::remove("invalid_config.yaml"); - } -} - -TEST_F(YamlConfigTest, ValidateThresholds) { - auto parser = createConfigParser(); - - // 测试阈值验证 - std::string config_str = R"( -input: - sources: - - type: rtsp - name: camera1 - url: rtsp://example.com/stream1 -inference: - model: - engine_path: /path/to/model.engine - input_shape: [3, 640, 640] - threshold: - conf: 1.5 # 无效的置信度阈值 - nms: 0.45 - )"; - - std::ofstream config_file("invalid_threshold.yaml"); - config_file << config_str; - config_file.close(); - - EXPECT_FALSE(parser->parse("invalid_threshold.yaml")); - std::filesystem::remove("invalid_threshold.yaml"); -} - -TEST_F(YamlConfigTest, ValidateClassStyles) { - auto parser = createConfigParser(); - - // 测试类别样式验证 - std::string config_str = R"( -input: - sources: - - type: rtsp - name: camera1 - url: rtsp://example.com/stream1 -inference: - model: - engine_path: /path/to/model.engine - input_shape: [3, 640, 640] -render: - window: - name: "Detection Results" - width: 1280 - height: 720 - class_styles: - "": # 空类别名称 - box_color: [255, 0, 0] - text_color: [255, 255, 255] - transparency: 0.2 - )"; - - std::ofstream config_file("invalid_class_style.yaml"); - config_file << config_str; - config_file.close(); - - EXPECT_FALSE(parser->parse("invalid_class_style.yaml")); - std::filesystem::remove("invalid_class_style.yaml"); +#include +#include "pipeline/common/yaml_config_parser.hpp" +#include "test_base.hpp" +#include +#include + +using namespace pipeline; + +class YamlConfigTest : public test::TestBase { +protected: + void SetUp() override { + test::TestBase::SetUp(); // 调用基类的SetUp + } +}; + +TEST_F(YamlConfigTest, LoadConfig) { + auto parser = createConfigParser(); + ASSERT_TRUE(parser->parse(config_path)); + + const auto& config = parser->getConfig(); + + // 验证输入配置 + ASSERT_EQ(config.input.sources.size(), 1); + EXPECT_EQ(config.input.sources[0].type, "rtsp"); + EXPECT_EQ(config.input.sources[0].name, "camera1"); + EXPECT_EQ(config.input.sources[0].url, "rtsp://10.0.0.17:8554/camera_test/2"); + EXPECT_EQ(config.input.sources[0].buffer_size, 30); + EXPECT_EQ(config.input.max_batch_size, 4); + + // 验证推理配置 + EXPECT_EQ(config.inference.engine_path, "/app/models/yolov8n.engine"); + ASSERT_EQ(config.inference.input_shape.size(), 3); + EXPECT_EQ(config.inference.input_shape[0], 3); + EXPECT_EQ(config.inference.input_shape[1], 640); + EXPECT_EQ(config.inference.input_shape[2], 640); + EXPECT_EQ(config.inference.precision, "FP16"); + EXPECT_FLOAT_EQ(config.inference.threshold.conf, 0.5f); + EXPECT_FLOAT_EQ(config.inference.threshold.nms, 0.45f); + EXPECT_EQ(config.inference.gpu_id, 0); + EXPECT_EQ(config.inference.version, "yolov8"); + ASSERT_EQ(config.inference.labels.size(), 3); + EXPECT_EQ(config.inference.labels[0], "person"); + EXPECT_EQ(config.inference.labels[1], "car"); + EXPECT_EQ(config.inference.labels[2], "truck"); + + // 验证渲染配置 + EXPECT_TRUE(config.render.enable); + EXPECT_EQ(config.render.window.name, "Detection Results"); + EXPECT_EQ(config.render.window.width, 1280); + EXPECT_EQ(config.render.window.height, 720); + EXPECT_FALSE(config.render.window.fullscreen); + + // 默认样式 + EXPECT_EQ(config.render.default_style.box_color, cv::Scalar(0, 255, 0)); + EXPECT_EQ(config.render.default_style.text_color, cv::Scalar(255, 255, 255)); + EXPECT_FLOAT_EQ(config.render.default_style.transparency, 0.0f); + EXPECT_EQ(config.render.default_style.box_thickness, 2); + EXPECT_DOUBLE_EQ(config.render.default_style.font_scale, 0.5); + EXPECT_EQ(config.render.default_style.font_thickness, 1); + + // 类别样式 + ASSERT_EQ(config.render.class_styles.size(), 3); + const auto& person_style = config.render.class_styles.at("person"); + EXPECT_EQ(person_style.box_color, cv::Scalar(255, 0, 0)); + EXPECT_EQ(person_style.text_color, cv::Scalar(255, 255, 255)); + EXPECT_FLOAT_EQ(person_style.transparency, 0.2f); + + const auto& car_style = config.render.class_styles.at("car"); + EXPECT_EQ(car_style.box_color, cv::Scalar(0, 255, 0)); + EXPECT_EQ(car_style.text_color, cv::Scalar(255, 255, 255)); + EXPECT_FLOAT_EQ(car_style.transparency, 0.2f); + + const auto& truck_style = config.render.class_styles.at("truck"); + EXPECT_EQ(truck_style.box_color, cv::Scalar(0, 0, 255)); + EXPECT_EQ(truck_style.text_color, cv::Scalar(255, 255, 255)); + EXPECT_FLOAT_EQ(truck_style.transparency, 0.2f); + + // 性能指标配置 + EXPECT_TRUE(config.render.metrics.show_fps); + EXPECT_TRUE(config.render.metrics.show_inference_time); + EXPECT_TRUE(config.render.metrics.show_gpu_usage); + EXPECT_EQ(config.render.metrics.update_interval_ms, 1000); + + // 验证输出配置 + ASSERT_EQ(config.output.targets.size(), 2); + EXPECT_EQ(config.output.targets[0].type, "video"); + EXPECT_EQ(config.output.targets[0].name, "output_video"); + EXPECT_EQ(config.output.targets[0].path, "/output/result.mp4"); + EXPECT_EQ(config.output.targets[0].fps, 30); + EXPECT_EQ(config.output.targets[0].codec, "h264"); + EXPECT_EQ(config.output.targets[0].bitrate, 4000000); + + EXPECT_EQ(config.output.targets[1].type, "rtsp"); + EXPECT_EQ(config.output.targets[1].name, "output_rtsp"); + EXPECT_EQ(config.output.targets[1].path, "rtsp://localhost:8554/live"); + EXPECT_EQ(config.output.targets[1].fps, 30); + EXPECT_EQ(config.output.targets[1].codec, "h264"); + EXPECT_EQ(config.output.targets[1].bitrate, 4000000); + + // 验证日志配置 + EXPECT_EQ(config.log.level, "info"); + EXPECT_EQ(config.log.save_path, "logs/"); +} + +TEST_F(YamlConfigTest, InvalidConfig) { + auto parser = createConfigParser(); + + // 测试不存在的文件 + EXPECT_FALSE(parser->parse("non_existent.yaml")); +} + +TEST_F(YamlConfigTest, InvalidConfigs) { + auto parser = createConfigParser(); + + // 创建一个临时的无效配置文件用于测试 + std::ofstream invalid_config("invalid_config.yaml"); + invalid_config << R"( +input: + sources: [] # 空的输入源列表，这应该是无效的 +)"; + invalid_config.close(); + + EXPECT_FALSE(parser->parse("invalid_config.yaml")); + std::filesystem::remove("invalid_config.yaml"); +} + +TEST_F(YamlConfigTest, ValidateThresholds) { + auto parser = createConfigParser(); + + // 创建一个临时的无效阈值配置文件用于测试 + std::ofstream config_file("invalid_threshold.yaml"); + config_file << R"( +input: + sources: + - type: rtsp + name: "camera1" + url: "rtsp://10.0.0.17:8554/camera_test/2" +inference: + model: + onnx_path: "/app/models/yolov8n.onnx" + engine_path: "/app/models/yolov8n.engine" + input_shape: [3, 640, 640] + precision: "FP16" + threshold: + conf: 1.5 # 无效的置信度阈值 + nms: 0.45 + )"; + config_file.close(); + + EXPECT_FALSE(parser->parse("invalid_threshold.yaml")); + std::filesystem::remove("invalid_threshold.yaml"); +} + +TEST_F(YamlConfigTest, ValidateClassStyles) { + auto parser = createConfigParser(); + + // 创建一个临时的无效类别样式配置文件用于测试 + std::ofstream config_file("invalid_class_style.yaml"); + config_file << R"( +input: + sources: + - type: rtsp + name: "camera1" + url: "rtsp://10.0.0.17:8554/camera_test/2" +inference: + model: + onnx_path: "/app/models/yolov8n.onnx" + engine_path: "/app/models/yolov8n.engine" + input_shape: [3, 640, 640] + precision: "FP16" +render: + window: + name: "Detection Results" + width: 1280 + height: 720 + class_styles: + "": # 空类别名称 + box_color: [255, 0, 0] + text_color: [255, 255, 255] + transparency: 0.2 + )"; + config_file.close(); + + EXPECT_FALSE(parser->parse("invalid_class_style.yaml")); + std::filesystem::remove("invalid_class_style.yaml"); } \ No newline at end of file