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feat(perception_online_evaluator): add perception_online_evaluator (autowarefoundation#6493)
* feat(perception_evaluator): add perception_evaluator Signed-off-by: kosuke55 <kosuke.tnp@gmail.com> tmp Signed-off-by: kosuke55 <kosuke.tnp@gmail.com> update Signed-off-by: kosuke55 <kosuke.tnp@gmail.com> add Signed-off-by: kosuke55 <kosuke.tnp@gmail.com> add add update clean up Signed-off-by: kosuke55 <kosuke.tnp@gmail.com> change time horizon Signed-off-by: kosuke55 <kosuke.tnp@gmail.com> * fix build werror Signed-off-by: kosuke55 <kosuke.tnp@gmail.com> * fix topic name Signed-off-by: kosuke55 <kosuke.tnp@gmail.com> * clean up Signed-off-by: kosuke55 <kosuke.tnp@gmail.com> * rename to perception_online_evaluator Signed-off-by: kosuke55 <kosuke.tnp@gmail.com> * refactor: remove timer Signed-off-by: kosuke55 <kosuke.tnp@gmail.com> * feat: add test Signed-off-by: kosuke55 <kosuke.tnp@gmail.com> * fix: ci check Signed-off-by: kosuke55 <kosuke.tnp@gmail.com> --------- Signed-off-by: kosuke55 <kosuke.tnp@gmail.com>
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‎evaluator/perception_online_evaluator/CMakeLists.txt

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cmake_minimum_required(VERSION 3.14)
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project(perception_online_evaluator)
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find_package(autoware_cmake REQUIRED)
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autoware_package()
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find_package(pluginlib REQUIRED)
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find_package(glog REQUIRED)
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ament_auto_add_library(${PROJECT_NAME}_node SHARED
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src/metrics_calculator.cpp
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src/${PROJECT_NAME}_node.cpp
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src/metrics/deviation_metrics.cpp
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src/utils/marker_utils.cpp
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src/utils/objects_filtering.cpp
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)
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rclcpp_components_register_node(${PROJECT_NAME}_node
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PLUGIN "perception_diagnostics::PerceptionOnlineEvaluatorNode"
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EXECUTABLE ${PROJECT_NAME}
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)
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rclcpp_components_register_node(${PROJECT_NAME}_node
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PLUGIN "perception_diagnostics::MotionEvaluatorNode"
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EXECUTABLE motion_evaluator
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)
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target_link_libraries(${PROJECT_NAME}_node glog::glog)
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if(BUILD_TESTING)
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ament_add_ros_isolated_gtest(test_${PROJECT_NAME}
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test/test_perception_online_evaluator_node.cpp
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)
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target_link_libraries(test_${PROJECT_NAME}
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${PROJECT_NAME}_node
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)
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endif()
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ament_auto_package(
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INSTALL_TO_SHARE
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param
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launch
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)

‎evaluator/perception_online_evaluator/README.md

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# Perception Evaluator
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A node for evaluating the output of perception systems.
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## Purpose
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This module allows for the evaluation of how accurately perception results are generated without the need for annotations. It is capable of confirming performance and can evaluate results from a few seconds prior, enabling online execution.
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## Inner-workings / Algorithms
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- Calculates lateral deviation between the predicted path and the actual traveled trajectory.
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- Calculates lateral deviation between the smoothed traveled trajectory and the perceived position to evaluate the stability of lateral position recognition.
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- Calculates yaw deviation between the smoothed traveled trajectory and the perceived position to evaluate the stability of yaw recognition.
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## Inputs / Outputs
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| Name | Type | Description |
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| ----------------- | ------------------------------------------------------ | ------------------------------------------------- |
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| `~/input/objects` | `autoware_auto_perception_msgs::msg::PredictedObjects` | The predicted objects to evaluate. |
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| `~/metrics` | `diagnostic_msgs::msg::DiagnosticArray` | Diagnostic information about perception accuracy. |
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| `~/markers` | `visualization_msgs::msg::MarkerArray` | Visual markers for debugging and visualization. |
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## Parameters
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| Name | Type | Description |
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| --------------------------------- | ------------ | ------------------------------------------------------------------------------------------------ |
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| `selected_metrics` | List | Metrics to be evaluated, such as lateral deviation, yaw deviation, and predicted path deviation. |
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| `smoothing_window_size` | Integer | Determines the window size for smoothing path, should be an odd number. |
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| `prediction_time_horizons` | list[double] | Time horizons for prediction evaluation in seconds. |
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| `target_object.*.check_deviation` | bool | Whether to check deviation for specific object types (car, truck, etc.). |
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| `debug_marker.*` | bool | Debugging parameters for marker visualization (history path, predicted path, etc.). |
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## Assumptions / Known limits
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It is assumed that the current positions of PredictedObjects are reasonably accurate.
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## Future extensions / Unimplemented parts
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- Increase rate in recognition per class
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- Metrics for objects with strange physical behavior (e.g., going through a fence)
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- Metrics for splitting objects
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- Metrics for problems with objects that are normally stationary but move
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- Disappearing object metrics

‎evaluator/perception_online_evaluator/include/perception_online_evaluator/metrics/deviation_metrics.hpp

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// Copyright 2024 TIER IV, Inc.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#ifndef PERCEPTION_ONLINE_EVALUATOR__METRICS__DEVIATION_METRICS_HPP_
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#define PERCEPTION_ONLINE_EVALUATOR__METRICS__DEVIATION_METRICS_HPP_
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#include "perception_online_evaluator/stat.hpp"
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#include <autoware_auto_perception_msgs/msg/predicted_path.hpp>
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#include <geometry_msgs/msg/pose.hpp>
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#include <vector>
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namespace perception_diagnostics
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{
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namespace metrics
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{
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using autoware_auto_perception_msgs::msg::PredictedPath;
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using geometry_msgs::msg::Pose;
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/**
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* @brief calculate lateral deviation of the given path from the reference path
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* @param [in] ref_path reference path
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* @param [in] pred_path predicted path
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* @return calculated statistics
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*/
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double calcLateralDeviation(const std::vector<Pose> & ref_path, const Pose & target_pose);
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/**
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* @brief calculate yaw deviation of the given path from the reference path
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* @param [in] ref_path reference path
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* @param [in] pred_path predicted path
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* @return calculated statistics
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*/
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double calcYawDeviation(const std::vector<Pose> & ref_path, const Pose & target_pose);
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std::vector<double> calcPredictedPathDeviation(
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const std::vector<Pose> & ref_path, const PredictedPath & pred_path);
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} // namespace metrics
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} // namespace perception_diagnostics
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#endif // PERCEPTION_ONLINE_EVALUATOR__METRICS__DEVIATION_METRICS_HPP_

‎evaluator/perception_online_evaluator/include/perception_online_evaluator/metrics/metric.hpp

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// Copyright 2024 TIER IV, Inc.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#ifndef PERCEPTION_ONLINE_EVALUATOR__METRICS__METRIC_HPP_
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#define PERCEPTION_ONLINE_EVALUATOR__METRICS__METRIC_HPP_
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#include "perception_online_evaluator/stat.hpp"
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#include <iostream>
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#include <string>
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#include <unordered_map>
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#include <vector>
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namespace perception_diagnostics
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{
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/**
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* @brief Enumeration of trajectory metrics
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*/
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enum class Metric {
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lateral_deviation,
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yaw_deviation,
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predicted_path_deviation,
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SIZE,
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};
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using MetricStatMap = std::unordered_map<std::string, Stat<double>>;
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static const std::unordered_map<std::string, Metric> str_to_metric = {
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{"lateral_deviation", Metric::lateral_deviation},
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{"yaw_deviation", Metric::yaw_deviation},
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{"predicted_path_deviation", Metric::predicted_path_deviation}};
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static const std::unordered_map<Metric, std::string> metric_to_str = {
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{Metric::lateral_deviation, "lateral_deviation"},
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{Metric::yaw_deviation, "yaw_deviation"},
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{Metric::predicted_path_deviation, "predicted_path_deviation"}};
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// Metrics descriptions
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static const std::unordered_map<Metric, std::string> metric_descriptions = {
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{Metric::lateral_deviation, "Lateral_deviation[m]"},
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{Metric::yaw_deviation, "Yaw_deviation[rad]"},
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{Metric::predicted_path_deviation, "Predicted_path_deviation[m]"}};
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namespace details
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{
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static struct CheckCorrectMaps
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{
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CheckCorrectMaps()
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{
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if (
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str_to_metric.size() != static_cast<size_t>(Metric::SIZE) ||
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metric_to_str.size() != static_cast<size_t>(Metric::SIZE) ||
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metric_descriptions.size() != static_cast<size_t>(Metric::SIZE)) {
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std::cerr << "[metrics/metrics.hpp] Maps are not defined for all metrics: ";
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std::cerr << str_to_metric.size() << " " << metric_to_str.size() << " "
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<< metric_descriptions.size() << std::endl;
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}
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}
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} check;
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} // namespace details
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} // namespace perception_diagnostics
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#endif // PERCEPTION_ONLINE_EVALUATOR__METRICS__METRIC_HPP_

‎evaluator/perception_online_evaluator/include/perception_online_evaluator/metrics_calculator.hpp

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// Copyright 2024 TIER IV, Inc.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#ifndef PERCEPTION_ONLINE_EVALUATOR__METRICS_CALCULATOR_HPP_
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#define PERCEPTION_ONLINE_EVALUATOR__METRICS_CALCULATOR_HPP_
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#include "perception_online_evaluator/metrics/deviation_metrics.hpp"
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#include "perception_online_evaluator/metrics/metric.hpp"
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#include "perception_online_evaluator/parameters.hpp"
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#include "perception_online_evaluator/stat.hpp"
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#include <rclcpp/time.hpp>
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#include "autoware_auto_perception_msgs/msg/predicted_objects.hpp"
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#include "geometry_msgs/msg/pose.hpp"
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#include <unique_identifier_msgs/msg/uuid.hpp>
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#include <algorithm>
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#include <map>
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#include <optional>
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#include <utility>
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#include <vector>
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namespace perception_diagnostics
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{
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using autoware_auto_perception_msgs::msg::PredictedObject;
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using autoware_auto_perception_msgs::msg::PredictedObjects;
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using geometry_msgs::msg::Point;
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using geometry_msgs::msg::Pose;
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using unique_identifier_msgs::msg::UUID;
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struct ObjectData
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{
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PredictedObject object;
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std::vector<std::pair<Pose, Pose>> path_pairs;
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std::vector<Pose> getPredictedPath() const
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{
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std::vector<Pose> path;
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path.resize(path_pairs.size());
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std::transform(
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path_pairs.begin(), path_pairs.end(), path.begin(),
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[](const std::pair<Pose, Pose> & pair) -> Pose { return pair.first; });
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return path;
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}
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std::vector<Pose> getHistoryPath() const
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{
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std::vector<Pose> path;
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path.resize(path_pairs.size());
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std::transform(
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path_pairs.begin(), path_pairs.end(), path.begin(),
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[](const std::pair<Pose, Pose> & pair) -> Pose { return pair.second; });
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return path;
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}
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};
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using ObjectDataMap = std::unordered_map<std::string, ObjectData>;
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// pair of history_path and smoothed_history_path for each object id
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using HistoryPathMap =
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std::unordered_map<std::string, std::pair<std::vector<Pose>, std::vector<Pose>>>;
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class MetricsCalculator
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{
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public:
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explicit MetricsCalculator(const std::shared_ptr<Parameters> & parameters)
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: parameters_(parameters){};
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/**
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* @brief calculate
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* @param [in] metric Metric enum value
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* @return map of string describing the requested metric and the calculated value
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*/
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std::optional<MetricStatMap> calculate(const Metric & metric) const;
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/**
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* @brief set the dynamic objects used to calculate obstacle metrics
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* @param [in] objects predicted objects
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*/
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void setPredictedObjects(const PredictedObjects & objects);
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HistoryPathMap getHistoryPathMap() const { return history_path_map_; }
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ObjectDataMap getDebugObjectData() const { return debug_target_object_; }
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private:
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std::shared_ptr<Parameters> parameters_;
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// Store predicted objects information and calculation results
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std::unordered_map<std::string, std::map<rclcpp::Time, PredictedObject>> object_map_;
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HistoryPathMap history_path_map_;
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rclcpp::Time current_stamp_;
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// debug
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mutable ObjectDataMap debug_target_object_;
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// Functions to calculate history path
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void updateHistoryPath();
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std::vector<Pose> averageFilterPath(
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const std::vector<Pose> & path, const size_t window_size) const;
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std::vector<Pose> generateHistoryPathWithPrev(
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const std::vector<Pose> & prev_history_path, const Pose & new_pose, const size_t window_size);
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// Update object data
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void updateObjects(
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const std::string uuid, const rclcpp::Time stamp, const PredictedObject & object);
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void deleteOldObjects(const rclcpp::Time stamp);
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// Calculate metrics
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MetricStatMap calcLateralDeviationMetrics(const PredictedObjects & objects) const;
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MetricStatMap calcYawDeviationMetrics(const PredictedObjects & objects) const;
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MetricStatMap calcPredictedPathDeviationMetrics(const PredictedObjects & objects) const;
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Stat<double> calcPredictedPathDeviationMetrics(
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const PredictedObjects & objects, const double time_horizon) const;
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bool hasPassedTime(const rclcpp::Time stamp) const;
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bool hasPassedTime(const std::string uuid, const rclcpp::Time stamp) const;
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double getTimeDelay() const;
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// Extract object
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rclcpp::Time getClosestStamp(const rclcpp::Time stamp) const;
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std::optional<PredictedObject> getObjectByStamp(
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const std::string uuid, const rclcpp::Time stamp) const;
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PredictedObjects getObjectsByStamp(const rclcpp::Time stamp) const;
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}; // class MetricsCalculator
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} // namespace perception_diagnostics
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#endif // PERCEPTION_ONLINE_EVALUATOR__METRICS_CALCULATOR_HPP_

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