diff --git a/docs/quickstart/apollo_2_0_hardware_system_installation_guide_v1.md b/docs/quickstart/apollo_2_0_hardware_system_installation_guide_v1.md index a02c2157db216e01e136cfa3606e1d2336ebfa10..17fb0df334aa49e978bcbb9ef890e5803440cba7 100644 --- a/docs/quickstart/apollo_2_0_hardware_system_installation_guide_v1.md +++ b/docs/quickstart/apollo_2_0_hardware_system_installation_guide_v1.md @@ -265,7 +265,7 @@ The 40 line LiDAR system **Pandora** is available from Hesai Photonics Technolog - 360° surrounding view with 4 mono cameras and long disatance front view with 1 color camera ![online](images/online_icon.png)Webpage for Hesai Pandora: -[http://www.hesaitech.com](http://www.hesaitech.com/pandora.html) +[http://www.hesaitech.com/pandora.html](http://www.hesaitech.com/pandora.html) ## Cameras @@ -817,7 +817,7 @@ Each Pandora includes a cable bundle to connect the LiDAR to the power supply, t ![Pandora_pin](images/Pandora_pinout_table.png) ![online_icon](images/online_icon.png)Pandora Manual can be found on this webpage: -[http://www.hesaitech.com](http://www.hesaitech.com/pandora.html) +[http://www.hesaitech.com/pandora.html](http://www.hesaitech.com/pandora.html) ### Installing the Cameras diff --git a/modules/perception/obstacle/camera/lane_post_process/cc_lane_post_processor/cc_lane_post_processor.cc b/modules/perception/obstacle/camera/lane_post_process/cc_lane_post_processor/cc_lane_post_processor.cc index d32095d9cd7ddac24c260fc02c45112293b50644..1c60e7c14639532f22b619c2105ef2d47667bdc0 100644 --- a/modules/perception/obstacle/camera/lane_post_process/cc_lane_post_processor/cc_lane_post_processor.cc +++ b/modules/perception/obstacle/camera/lane_post_process/cc_lane_post_processor/cc_lane_post_processor.cc @@ -349,11 +349,11 @@ bool CCLanePostProcessor::AddInstanceIntoLaneObjectImage( lane_object->longitude_end = std::max(lane_object->pos.back().y(), lane_object->longitude_end); - // ADEBUG << " point " << lane_object->point_num << " = " - // << "(" << lane_object->pos.back()(0) << ", " - // << lane_object->pos.back()(1) << "), " - // << "(" << lane_object->image_pos.back()(0) << ", " - // << lane_object->image_pos.back()(1) << ")"; + ADEBUG << " point " << lane_object->point_num << " = " + << "(" << lane_object->pos.back()(0) << ", " + << lane_object->pos.back()(1) << "), " + << "(" << lane_object->image_pos.back()(0) << ", " + << lane_object->image_pos.back()(1) << ")"; lane_object->point_num++; } @@ -370,17 +370,17 @@ bool CCLanePostProcessor::AddInstanceIntoLaneObjectImage( lane_object->longitude_end = std::max(lane_object->pos.back().y(), lane_object->longitude_end); - // ADEBUG << " point " << lane_object->point_num << " = " - // << "(" << lane_object->pos.back()(0) << ", " - // << lane_object->pos.back()(1) << "), " - // << "(" << lane_object->image_pos.back()(0) << ", " - // << lane_object->image_pos.back()(1) << ")"; + ADEBUG << " point " << lane_object->point_num << " = " + << "(" << lane_object->pos.back()(0) << ", " + << lane_object->pos.back()(1) << "), " + << "(" << lane_object->image_pos.back()(0) << ", " + << lane_object->image_pos.back()(1) << ")"; lane_object->point_num++; i_prev = i; } - // ADEBUG << "longitude_start = " << lane_object->longitude_start; - // ADEBUG << "longitude_end = " << lane_object->longitude_end; + ADEBUG << "longitude_start = " << lane_object->longitude_start; + ADEBUG << "longitude_end = " << lane_object->longitude_end; if (lane_object->point_num != lane_object->pos.size() || lane_object->point_num != lane_object->orie.size() || @@ -396,8 +396,8 @@ bool CCLanePostProcessor::AddInstanceIntoLaneObjectImage( } // fit polynomial model and compute lateral distance for lane object - // ADEBUG << "max_size_to_fit_straight_line = " - // << options_.frame.max_size_to_fit_straight_line; + ADEBUG << "max_size_to_fit_straight_line = " + << options_.frame.max_size_to_fit_straight_line; if (lane_object->point_num < 3 || lane_object->longitude_end - lane_object->longitude_start < options_.frame.max_size_to_fit_straight_line) { @@ -437,9 +437,9 @@ bool CCLanePostProcessor::GenerateLaneInstances(const cv::Mat &lane_map) { cv::Mat lane_mask; if (lane_map.type() == CV_32FC1) { // confidence heatmap - // ADEBUG << "confidence threshold = " << options_.lane_map_conf_thresh; - // ADEBUG << "lane map size = " - // << "(" << lane_map.cols << ", " << lane_map.rows << ")"; + ADEBUG << "confidence threshold = " << options_.lane_map_conf_thresh; + ADEBUG << "lane map size = " + << "(" << lane_map.cols << ", " << lane_map.rows << ")"; lane_mask.create(lane_map.rows, lane_map.cols, CV_8UC1); lane_mask.setTo(cv::Scalar(0)); for (int h = 0; h < lane_mask.rows; ++h) { @@ -461,7 +461,7 @@ bool CCLanePostProcessor::GenerateLaneInstances(const cv::Mat &lane_map) { vector cc_list; cc_generator_->FindConnectedComponents(lane_mask, &cc_list); - // ADEBUG << "number of connected components = " << cc_list.size(); + ADEBUG << "number of connected components = " << cc_list.size(); // 3. split CC and find inner edges int tot_inner_edge_count = 0; @@ -537,7 +537,7 @@ bool CCLanePostProcessor::Process(const cv::Mat &lane_map, bool is_right_lane_found = false; for (auto it = cur_lane_instances_->begin(); it != cur_lane_instances_->end(); ++it) { - // ADEBUG << "for lane instance " << it - cur_lane_instances_->begin(); + ADEBUG << "for lane instance " << it - cur_lane_instances_->begin(); if (is_left_lane_found && is_right_lane_found) { break; @@ -564,10 +564,10 @@ bool CCLanePostProcessor::Process(const cv::Mat &lane_map, is_right_lane_found = true; } - // ADEBUG << " lane object " << (*lane_objects)->back().GetSpatialLabel() - // << " has " << (*lane_objects)->back().pos.size() << " points: " - // << "lateral distance = " - // << (*lane_objects)->back().lateral_distance; + ADEBUG << " lane object " << (*lane_objects)->back().GetSpatialLabel() + << " has " << (*lane_objects)->back().pos.size() << " points: " + << "lateral distance = " + << (*lane_objects)->back().lateral_distance; } } else { @@ -798,7 +798,7 @@ bool CCLanePostProcessor::Process(const cv::Mat &lane_map, (*lane_objects)->resize(valid_lane_objects.size()); } -// ADEBUG << "number of lane objects = " << (*lane_objects)->size(); + ADEBUG << "number of lane objects = " << (*lane_objects)->size(); // if (options_.space_type != SpaceType::IMAGE) { // if (!CompensateLaneObjects((*lane_objects))) { // AERROR << "fail to compensate lane objects."; @@ -807,7 +807,7 @@ bool CCLanePostProcessor::Process(const cv::Mat &lane_map, // } EnrichLaneInfo((*lane_objects)); -// ADEBUG << "use_lane_history_: " << use_history_; + ADEBUG << "use_lane_history_: " << use_history_; if (use_history_) { // FilterWithLaneHistory(*lane_objects); std::vector is_valid(generated_lanes_->size(), false); @@ -1098,7 +1098,7 @@ bool CCLanePostProcessor::CompensateLaneObjects(LaneObjectsPtr lane_objects) { } if (!has_ego_lane_right) { -// ADEBUG << "add virtual lane R_0 ..."; + ADEBUG << "add virtual lane R_0 ..."; if (ego_lane_left_idx == -1) { AERROR << "failed to compensate right ego lane due to no left ego lane."; return false; diff --git a/modules/perception/obstacle/lidar/object_filter/low_object_filter/BUILD b/modules/perception/obstacle/lidar/object_filter/low_object_filter/BUILD index baa62306587f5c6f806a691a64b51b23f9bae3e1..9de6a79e1bfdbf56f8e4ed9d3ddd3e1e013b6770 100644 --- a/modules/perception/obstacle/lidar/object_filter/low_object_filter/BUILD +++ b/modules/perception/obstacle/lidar/object_filter/low_object_filter/BUILD @@ -1,7 +1,6 @@ load("//tools:cpplint.bzl", "cpplint") -_library( - +package(default_visibility = ["//visibility:public"]) cc_library( name = "low_object_filter",