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Package symbol

lidar_apollo_cnn_seg_detect package from autoware_learn repo

amathutils_lib autoware_build_flags autoware_health_checker emergency_handler gnss lanelet2_extension libvectormap libwaypoint_follower map_file object_map op_planner op_ros_helpers op_simu op_utility ros_observer tvm_utility vector_map vector_map_server vehicle_sim_model autoware_connector ekf_localizer gnss_localizer image_processor imm_ukf_pda_track lidar_apollo_cnn_seg_detect lidar_euclidean_cluster_detect lidar_fake_perception lidar_kf_contour_track lidar_localizer lidar_naive_l_shape_detect lidar_point_pillars lidar_shape_estimation naive_motion_predict ndt_cpu ndt_gpu ndt_tku obj_db pcl_omp_registration pixel_cloud_fusion points_downsampler points_preprocessor pos_db range_vision_fusion road_occupancy_processor roi_object_filter trafficlight_recognizer twist_generator vel_pose_diff_checker vision_beyond_track vision_darknet_detect vision_lane_detect vision_segment_enet_detect vision_ssd_detect astar_search costmap_generator decision_maker dp_planner ff_waypoint_follower freespace_planner lane_planner lattice_planner ll2_global_planner mpc_follower op_global_planner op_local_planner op_simulation_package op_utilities pure_pursuit state_machine_lib twist_filter twist_gate way_planner waypoint_maker waypoint_planner autoware_quickstart_examples autoware_can_msgs autoware_config_msgs autoware_external_msgs autoware_lanelet2_msgs autoware_map_msgs autoware_msgs autoware_system_msgs tablet_socket_msgs vector_map_msgs carla_autoware_bridge gazebo_camera_description gazebo_imu_description lgsvl_simulator_bridge vehicle_gazebo_simulation_interface vehicle_gazebo_simulation_launcher wf_simulator autoware_bag_tools autoware_camera_lidar_calibrator autoware_launcher autoware_launcher_rviz calibration_publisher data_preprocessor graph_tools kitti_box_publisher kitti_launch kitti_player lanelet_aisan_converter log_tools map_tf_generator map_tools marker_downsampler mqtt_socket multi_lidar_calibrator oculus_socket pc2_downsampler rosbag_controller runtime_manager sound_player system_monitor tablet_socket twist2odom udon_socket vehicle_engage_panel vehicle_socket decision_maker_panel detected_objects_visualizer fastvirtualscan gazebo_world_description glviewer integrated_viewer points2image rosinterface autoware_rviz_plugins vehicle_description vehicle_model adi_driver as autoware_driveworks_gmsl_interface autoware_driveworks_interface vlg22c_cam custom_msgs garmin hokuyo javad_navsat_driver kvaser sick_lms5xx memsic_imu microstrain_driver nmea_navsat autoware_pointgrey_drivers sick_ldmrs_description sick_ldmrs_driver sick_ldmrs_laser sick_ldmrs_msgs sick_ldmrs_tools vectacam xsens_driver ymc ds4 ds4_driver ds4_msgs lanelet2 lanelet2_core lanelet2_examples lanelet2_io lanelet2_maps lanelet2_matching lanelet2_projection lanelet2_python lanelet2_routing lanelet2_traffic_rules lanelet2_validation mrt_cmake_modules

ROS Distro
github

Package Summary

Tags No category tags.
Version 1.12.0
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Description autoware.ai perf
Checkout URI https://github.com/is-whale/autoware_learn.git
VCS Type git
VCS Version 1.14
Last Updated 2025-03-14
Dev Status UNKNOWN
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The apollo cnn segmentation package

Additional Links

No additional links.

Maintainers

  • Kosuke Murakami

Authors

  • Kosuke Murakami

CNN LiDAR Baidu Object Segmenter

Autoware package based on Baidu’s object segmenter.

Pre requisites

Caffe distributable installed in your home (~/caffe/distribute).

$ cd
$ git clone https://github.com/BVLC/caffe
$ cd caffe

Follow instructions from Installing Caffe from source.

  • Use offical Make compilation procedure.
  • Do not use thirdparty CMake setup.

Compile and create distributable:

$ make
$ make distribute

Recompile Autoware to build the node.

The Pretrained model

Use this link to download the pretrained model from Baidu:

https://github.com/ApolloAuto/apollo/tree/v5.5.0/modules/perception/production/data/perception/lidar/models/cnnseg

These two files are needed:

  • deploy.prototxt
  • deploy.caffemodel

How to launch

  • From a sourced terminal:

Using rosrun: rosrun lidar_apollo_cnn_seg_detect lidar_apollo_cnn_seg_detect _network_definition_file:=/PATH/TO/FILE.prototxt _pretrained_model_file:=/PATH/TO/WEIGHTS.caffemodel _points_src:=/points_raw

Using launch file: roslaunch lidar_apollo_cnn_seg_detect lidar_apollo_cnn_seg_detect.launch network_definition_file:=/PATH/TO/FILE.prototxt pretrained_model_file:=/PATH/TO/WEIGHTS.caffemodel points_src:=/points_raw

  • From Runtime Manager:

Computing Tab -> Detection/ lidar_detector -> lidar_cnn_baidu_detect. Configure parameters using the [app] button.

Parameters

Parameter Type Description Default
network_definition_file String Path to the network definition file (prototxt)  
pretrained_model_file String Path to the Pretrained model (weights)  
points_src String Input topic Pointcloud. Default. /points_raw
score_threshold Double Minimum score required as given by the network to include the result (0.-1.) 0.6
use_gpu Bool Whether ot not to use a GPU device true
gpu_device_id Int GPU ID 0
width Int Width of the 2d cluster 512
height Int Height of the 2d cluster 512
range Int Range for the 2d cluster 60
use_constant_feature Bool Use constant model feature (8 features) false
normalize_lidar_intensity Bool Normalize the received lidar intensity data false

Outputs

Topic Type Description
/detection/lidar_detector/points_cluster sensor_msgs/PointCloud2 Colored PointCloud of the resulting detected objects
/detection/lidar_detector/objects autoware_msgs/DetectedObjetArray Array of Detected Objects in Autoware format

Notes

  • To display the results in Rviz objects_visualizer is required. (Launch file launches automatically this node).

  • Pre trained models can be downloaded from the Apollo project repository.

CHANGELOG

Changelog for package lidar_apollo_cnn_seg_detect

1.11.0 (2019-03-21)

  • [feature] Baidu's CNN based LiDAR segmentation (#1800)
    • Add build caffe

    • add include apollo files

    • add apollo cnn

    • calculating time

      • Cleaned node
    • Parametrized inputs

    • Works with custom caffe

      • Parameterized
    • Works with custom Caffe

    • Removed hard coded params

    • Cleaned up dependencies

    • Added bboxes, labels

    • Minor fixes

    • Custom input topic

    • Added UI, launch file, readme

    • Added Compatibility for Perception Cleanup

      • Added license messages
    • Updated readme

    • Added extra instructions

    • Fix markdown
  • Contributors: Abraham Monrroy Cano

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

No known dependants.

Launch files

  • launch/lidar_apollo_cnn_seg_detect.launch
      • network_definition_file
      • pretrained_model_file
      • points_src [default: /points_raw]
      • score_threshold [default: 0.6]
      • use_gpu [default: true]
      • gpu_device_id [default: 0]
      • width [default: 512]
      • height [default: 512]
      • range [default: 60]
      • use_constant_feature [default: false]
      • normalize_lidar_intensity [default: false]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged lidar_apollo_cnn_seg_detect at Robotics Stack Exchange

No version for distro jazzy showing github. Known supported distros are highlighted in the buttons above.
Package symbol

lidar_apollo_cnn_seg_detect package from autoware_learn repo

amathutils_lib autoware_build_flags autoware_health_checker emergency_handler gnss lanelet2_extension libvectormap libwaypoint_follower map_file object_map op_planner op_ros_helpers op_simu op_utility ros_observer tvm_utility vector_map vector_map_server vehicle_sim_model autoware_connector ekf_localizer gnss_localizer image_processor imm_ukf_pda_track lidar_apollo_cnn_seg_detect lidar_euclidean_cluster_detect lidar_fake_perception lidar_kf_contour_track lidar_localizer lidar_naive_l_shape_detect lidar_point_pillars lidar_shape_estimation naive_motion_predict ndt_cpu ndt_gpu ndt_tku obj_db pcl_omp_registration pixel_cloud_fusion points_downsampler points_preprocessor pos_db range_vision_fusion road_occupancy_processor roi_object_filter trafficlight_recognizer twist_generator vel_pose_diff_checker vision_beyond_track vision_darknet_detect vision_lane_detect vision_segment_enet_detect vision_ssd_detect astar_search costmap_generator decision_maker dp_planner ff_waypoint_follower freespace_planner lane_planner lattice_planner ll2_global_planner mpc_follower op_global_planner op_local_planner op_simulation_package op_utilities pure_pursuit state_machine_lib twist_filter twist_gate way_planner waypoint_maker waypoint_planner autoware_quickstart_examples autoware_can_msgs autoware_config_msgs autoware_external_msgs autoware_lanelet2_msgs autoware_map_msgs autoware_msgs autoware_system_msgs tablet_socket_msgs vector_map_msgs carla_autoware_bridge gazebo_camera_description gazebo_imu_description lgsvl_simulator_bridge vehicle_gazebo_simulation_interface vehicle_gazebo_simulation_launcher wf_simulator autoware_bag_tools autoware_camera_lidar_calibrator autoware_launcher autoware_launcher_rviz calibration_publisher data_preprocessor graph_tools kitti_box_publisher kitti_launch kitti_player lanelet_aisan_converter log_tools map_tf_generator map_tools marker_downsampler mqtt_socket multi_lidar_calibrator oculus_socket pc2_downsampler rosbag_controller runtime_manager sound_player system_monitor tablet_socket twist2odom udon_socket vehicle_engage_panel vehicle_socket decision_maker_panel detected_objects_visualizer fastvirtualscan gazebo_world_description glviewer integrated_viewer points2image rosinterface autoware_rviz_plugins vehicle_description vehicle_model adi_driver as autoware_driveworks_gmsl_interface autoware_driveworks_interface vlg22c_cam custom_msgs garmin hokuyo javad_navsat_driver kvaser sick_lms5xx memsic_imu microstrain_driver nmea_navsat autoware_pointgrey_drivers sick_ldmrs_description sick_ldmrs_driver sick_ldmrs_laser sick_ldmrs_msgs sick_ldmrs_tools vectacam xsens_driver ymc ds4 ds4_driver ds4_msgs lanelet2 lanelet2_core lanelet2_examples lanelet2_io lanelet2_maps lanelet2_matching lanelet2_projection lanelet2_python lanelet2_routing lanelet2_traffic_rules lanelet2_validation mrt_cmake_modules

ROS Distro
github

Package Summary

Tags No category tags.
Version 1.12.0
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Description autoware.ai perf
Checkout URI https://github.com/is-whale/autoware_learn.git
VCS Type git
VCS Version 1.14
Last Updated 2025-03-14
Dev Status UNKNOWN
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The apollo cnn segmentation package

Additional Links

No additional links.

Maintainers

  • Kosuke Murakami

Authors

  • Kosuke Murakami

CNN LiDAR Baidu Object Segmenter

Autoware package based on Baidu’s object segmenter.

Pre requisites

Caffe distributable installed in your home (~/caffe/distribute).

$ cd
$ git clone https://github.com/BVLC/caffe
$ cd caffe

Follow instructions from Installing Caffe from source.

  • Use offical Make compilation procedure.
  • Do not use thirdparty CMake setup.

Compile and create distributable:

$ make
$ make distribute

Recompile Autoware to build the node.

The Pretrained model

Use this link to download the pretrained model from Baidu:

https://github.com/ApolloAuto/apollo/tree/v5.5.0/modules/perception/production/data/perception/lidar/models/cnnseg

These two files are needed:

  • deploy.prototxt
  • deploy.caffemodel

How to launch

  • From a sourced terminal:

Using rosrun: rosrun lidar_apollo_cnn_seg_detect lidar_apollo_cnn_seg_detect _network_definition_file:=/PATH/TO/FILE.prototxt _pretrained_model_file:=/PATH/TO/WEIGHTS.caffemodel _points_src:=/points_raw

Using launch file: roslaunch lidar_apollo_cnn_seg_detect lidar_apollo_cnn_seg_detect.launch network_definition_file:=/PATH/TO/FILE.prototxt pretrained_model_file:=/PATH/TO/WEIGHTS.caffemodel points_src:=/points_raw

  • From Runtime Manager:

Computing Tab -> Detection/ lidar_detector -> lidar_cnn_baidu_detect. Configure parameters using the [app] button.

Parameters

Parameter Type Description Default
network_definition_file String Path to the network definition file (prototxt)  
pretrained_model_file String Path to the Pretrained model (weights)  
points_src String Input topic Pointcloud. Default. /points_raw
score_threshold Double Minimum score required as given by the network to include the result (0.-1.) 0.6
use_gpu Bool Whether ot not to use a GPU device true
gpu_device_id Int GPU ID 0
width Int Width of the 2d cluster 512
height Int Height of the 2d cluster 512
range Int Range for the 2d cluster 60
use_constant_feature Bool Use constant model feature (8 features) false
normalize_lidar_intensity Bool Normalize the received lidar intensity data false

Outputs

Topic Type Description
/detection/lidar_detector/points_cluster sensor_msgs/PointCloud2 Colored PointCloud of the resulting detected objects
/detection/lidar_detector/objects autoware_msgs/DetectedObjetArray Array of Detected Objects in Autoware format

Notes

  • To display the results in Rviz objects_visualizer is required. (Launch file launches automatically this node).

  • Pre trained models can be downloaded from the Apollo project repository.

CHANGELOG

Changelog for package lidar_apollo_cnn_seg_detect

1.11.0 (2019-03-21)

  • [feature] Baidu's CNN based LiDAR segmentation (#1800)
    • Add build caffe

    • add include apollo files

    • add apollo cnn

    • calculating time

      • Cleaned node
    • Parametrized inputs

    • Works with custom caffe

      • Parameterized
    • Works with custom Caffe

    • Removed hard coded params

    • Cleaned up dependencies

    • Added bboxes, labels

    • Minor fixes

    • Custom input topic

    • Added UI, launch file, readme

    • Added Compatibility for Perception Cleanup

      • Added license messages
    • Updated readme

    • Added extra instructions

    • Fix markdown
  • Contributors: Abraham Monrroy Cano

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

No known dependants.

Launch files

  • launch/lidar_apollo_cnn_seg_detect.launch
      • network_definition_file
      • pretrained_model_file
      • points_src [default: /points_raw]
      • score_threshold [default: 0.6]
      • use_gpu [default: true]
      • gpu_device_id [default: 0]
      • width [default: 512]
      • height [default: 512]
      • range [default: 60]
      • use_constant_feature [default: false]
      • normalize_lidar_intensity [default: false]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged lidar_apollo_cnn_seg_detect at Robotics Stack Exchange

No version for distro kilted showing github. Known supported distros are highlighted in the buttons above.
Package symbol

lidar_apollo_cnn_seg_detect package from autoware_learn repo

amathutils_lib autoware_build_flags autoware_health_checker emergency_handler gnss lanelet2_extension libvectormap libwaypoint_follower map_file object_map op_planner op_ros_helpers op_simu op_utility ros_observer tvm_utility vector_map vector_map_server vehicle_sim_model autoware_connector ekf_localizer gnss_localizer image_processor imm_ukf_pda_track lidar_apollo_cnn_seg_detect lidar_euclidean_cluster_detect lidar_fake_perception lidar_kf_contour_track lidar_localizer lidar_naive_l_shape_detect lidar_point_pillars lidar_shape_estimation naive_motion_predict ndt_cpu ndt_gpu ndt_tku obj_db pcl_omp_registration pixel_cloud_fusion points_downsampler points_preprocessor pos_db range_vision_fusion road_occupancy_processor roi_object_filter trafficlight_recognizer twist_generator vel_pose_diff_checker vision_beyond_track vision_darknet_detect vision_lane_detect vision_segment_enet_detect vision_ssd_detect astar_search costmap_generator decision_maker dp_planner ff_waypoint_follower freespace_planner lane_planner lattice_planner ll2_global_planner mpc_follower op_global_planner op_local_planner op_simulation_package op_utilities pure_pursuit state_machine_lib twist_filter twist_gate way_planner waypoint_maker waypoint_planner autoware_quickstart_examples autoware_can_msgs autoware_config_msgs autoware_external_msgs autoware_lanelet2_msgs autoware_map_msgs autoware_msgs autoware_system_msgs tablet_socket_msgs vector_map_msgs carla_autoware_bridge gazebo_camera_description gazebo_imu_description lgsvl_simulator_bridge vehicle_gazebo_simulation_interface vehicle_gazebo_simulation_launcher wf_simulator autoware_bag_tools autoware_camera_lidar_calibrator autoware_launcher autoware_launcher_rviz calibration_publisher data_preprocessor graph_tools kitti_box_publisher kitti_launch kitti_player lanelet_aisan_converter log_tools map_tf_generator map_tools marker_downsampler mqtt_socket multi_lidar_calibrator oculus_socket pc2_downsampler rosbag_controller runtime_manager sound_player system_monitor tablet_socket twist2odom udon_socket vehicle_engage_panel vehicle_socket decision_maker_panel detected_objects_visualizer fastvirtualscan gazebo_world_description glviewer integrated_viewer points2image rosinterface autoware_rviz_plugins vehicle_description vehicle_model adi_driver as autoware_driveworks_gmsl_interface autoware_driveworks_interface vlg22c_cam custom_msgs garmin hokuyo javad_navsat_driver kvaser sick_lms5xx memsic_imu microstrain_driver nmea_navsat autoware_pointgrey_drivers sick_ldmrs_description sick_ldmrs_driver sick_ldmrs_laser sick_ldmrs_msgs sick_ldmrs_tools vectacam xsens_driver ymc ds4 ds4_driver ds4_msgs lanelet2 lanelet2_core lanelet2_examples lanelet2_io lanelet2_maps lanelet2_matching lanelet2_projection lanelet2_python lanelet2_routing lanelet2_traffic_rules lanelet2_validation mrt_cmake_modules

ROS Distro
github

Package Summary

Tags No category tags.
Version 1.12.0
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Description autoware.ai perf
Checkout URI https://github.com/is-whale/autoware_learn.git
VCS Type git
VCS Version 1.14
Last Updated 2025-03-14
Dev Status UNKNOWN
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The apollo cnn segmentation package

Additional Links

No additional links.

Maintainers

  • Kosuke Murakami

Authors

  • Kosuke Murakami

CNN LiDAR Baidu Object Segmenter

Autoware package based on Baidu’s object segmenter.

Pre requisites

Caffe distributable installed in your home (~/caffe/distribute).

$ cd
$ git clone https://github.com/BVLC/caffe
$ cd caffe

Follow instructions from Installing Caffe from source.

  • Use offical Make compilation procedure.
  • Do not use thirdparty CMake setup.

Compile and create distributable:

$ make
$ make distribute

Recompile Autoware to build the node.

The Pretrained model

Use this link to download the pretrained model from Baidu:

https://github.com/ApolloAuto/apollo/tree/v5.5.0/modules/perception/production/data/perception/lidar/models/cnnseg

These two files are needed:

  • deploy.prototxt
  • deploy.caffemodel

How to launch

  • From a sourced terminal:

Using rosrun: rosrun lidar_apollo_cnn_seg_detect lidar_apollo_cnn_seg_detect _network_definition_file:=/PATH/TO/FILE.prototxt _pretrained_model_file:=/PATH/TO/WEIGHTS.caffemodel _points_src:=/points_raw

Using launch file: roslaunch lidar_apollo_cnn_seg_detect lidar_apollo_cnn_seg_detect.launch network_definition_file:=/PATH/TO/FILE.prototxt pretrained_model_file:=/PATH/TO/WEIGHTS.caffemodel points_src:=/points_raw

  • From Runtime Manager:

Computing Tab -> Detection/ lidar_detector -> lidar_cnn_baidu_detect. Configure parameters using the [app] button.

Parameters

Parameter Type Description Default
network_definition_file String Path to the network definition file (prototxt)  
pretrained_model_file String Path to the Pretrained model (weights)  
points_src String Input topic Pointcloud. Default. /points_raw
score_threshold Double Minimum score required as given by the network to include the result (0.-1.) 0.6
use_gpu Bool Whether ot not to use a GPU device true
gpu_device_id Int GPU ID 0
width Int Width of the 2d cluster 512
height Int Height of the 2d cluster 512
range Int Range for the 2d cluster 60
use_constant_feature Bool Use constant model feature (8 features) false
normalize_lidar_intensity Bool Normalize the received lidar intensity data false

Outputs

Topic Type Description
/detection/lidar_detector/points_cluster sensor_msgs/PointCloud2 Colored PointCloud of the resulting detected objects
/detection/lidar_detector/objects autoware_msgs/DetectedObjetArray Array of Detected Objects in Autoware format

Notes

  • To display the results in Rviz objects_visualizer is required. (Launch file launches automatically this node).

  • Pre trained models can be downloaded from the Apollo project repository.

CHANGELOG

Changelog for package lidar_apollo_cnn_seg_detect

1.11.0 (2019-03-21)

  • [feature] Baidu's CNN based LiDAR segmentation (#1800)
    • Add build caffe

    • add include apollo files

    • add apollo cnn

    • calculating time

      • Cleaned node
    • Parametrized inputs

    • Works with custom caffe

      • Parameterized
    • Works with custom Caffe

    • Removed hard coded params

    • Cleaned up dependencies

    • Added bboxes, labels

    • Minor fixes

    • Custom input topic

    • Added UI, launch file, readme

    • Added Compatibility for Perception Cleanup

      • Added license messages
    • Updated readme

    • Added extra instructions

    • Fix markdown
  • Contributors: Abraham Monrroy Cano

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

No known dependants.

Launch files

  • launch/lidar_apollo_cnn_seg_detect.launch
      • network_definition_file
      • pretrained_model_file
      • points_src [default: /points_raw]
      • score_threshold [default: 0.6]
      • use_gpu [default: true]
      • gpu_device_id [default: 0]
      • width [default: 512]
      • height [default: 512]
      • range [default: 60]
      • use_constant_feature [default: false]
      • normalize_lidar_intensity [default: false]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged lidar_apollo_cnn_seg_detect at Robotics Stack Exchange

No version for distro rolling showing github. Known supported distros are highlighted in the buttons above.
Package symbol

lidar_apollo_cnn_seg_detect package from autoware_learn repo

amathutils_lib autoware_build_flags autoware_health_checker emergency_handler gnss lanelet2_extension libvectormap libwaypoint_follower map_file object_map op_planner op_ros_helpers op_simu op_utility ros_observer tvm_utility vector_map vector_map_server vehicle_sim_model autoware_connector ekf_localizer gnss_localizer image_processor imm_ukf_pda_track lidar_apollo_cnn_seg_detect lidar_euclidean_cluster_detect lidar_fake_perception lidar_kf_contour_track lidar_localizer lidar_naive_l_shape_detect lidar_point_pillars lidar_shape_estimation naive_motion_predict ndt_cpu ndt_gpu ndt_tku obj_db pcl_omp_registration pixel_cloud_fusion points_downsampler points_preprocessor pos_db range_vision_fusion road_occupancy_processor roi_object_filter trafficlight_recognizer twist_generator vel_pose_diff_checker vision_beyond_track vision_darknet_detect vision_lane_detect vision_segment_enet_detect vision_ssd_detect astar_search costmap_generator decision_maker dp_planner ff_waypoint_follower freespace_planner lane_planner lattice_planner ll2_global_planner mpc_follower op_global_planner op_local_planner op_simulation_package op_utilities pure_pursuit state_machine_lib twist_filter twist_gate way_planner waypoint_maker waypoint_planner autoware_quickstart_examples autoware_can_msgs autoware_config_msgs autoware_external_msgs autoware_lanelet2_msgs autoware_map_msgs autoware_msgs autoware_system_msgs tablet_socket_msgs vector_map_msgs carla_autoware_bridge gazebo_camera_description gazebo_imu_description lgsvl_simulator_bridge vehicle_gazebo_simulation_interface vehicle_gazebo_simulation_launcher wf_simulator autoware_bag_tools autoware_camera_lidar_calibrator autoware_launcher autoware_launcher_rviz calibration_publisher data_preprocessor graph_tools kitti_box_publisher kitti_launch kitti_player lanelet_aisan_converter log_tools map_tf_generator map_tools marker_downsampler mqtt_socket multi_lidar_calibrator oculus_socket pc2_downsampler rosbag_controller runtime_manager sound_player system_monitor tablet_socket twist2odom udon_socket vehicle_engage_panel vehicle_socket decision_maker_panel detected_objects_visualizer fastvirtualscan gazebo_world_description glviewer integrated_viewer points2image rosinterface autoware_rviz_plugins vehicle_description vehicle_model adi_driver as autoware_driveworks_gmsl_interface autoware_driveworks_interface vlg22c_cam custom_msgs garmin hokuyo javad_navsat_driver kvaser sick_lms5xx memsic_imu microstrain_driver nmea_navsat autoware_pointgrey_drivers sick_ldmrs_description sick_ldmrs_driver sick_ldmrs_laser sick_ldmrs_msgs sick_ldmrs_tools vectacam xsens_driver ymc ds4 ds4_driver ds4_msgs lanelet2 lanelet2_core lanelet2_examples lanelet2_io lanelet2_maps lanelet2_matching lanelet2_projection lanelet2_python lanelet2_routing lanelet2_traffic_rules lanelet2_validation mrt_cmake_modules

ROS Distro
github

Package Summary

Tags No category tags.
Version 1.12.0
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Description autoware.ai perf
Checkout URI https://github.com/is-whale/autoware_learn.git
VCS Type git
VCS Version 1.14
Last Updated 2025-03-14
Dev Status UNKNOWN
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The apollo cnn segmentation package

Additional Links

No additional links.

Maintainers

  • Kosuke Murakami

Authors

  • Kosuke Murakami

CNN LiDAR Baidu Object Segmenter

Autoware package based on Baidu’s object segmenter.

Pre requisites

Caffe distributable installed in your home (~/caffe/distribute).

$ cd
$ git clone https://github.com/BVLC/caffe
$ cd caffe

Follow instructions from Installing Caffe from source.

  • Use offical Make compilation procedure.
  • Do not use thirdparty CMake setup.

Compile and create distributable:

$ make
$ make distribute

Recompile Autoware to build the node.

The Pretrained model

Use this link to download the pretrained model from Baidu:

https://github.com/ApolloAuto/apollo/tree/v5.5.0/modules/perception/production/data/perception/lidar/models/cnnseg

These two files are needed:

  • deploy.prototxt
  • deploy.caffemodel

How to launch

  • From a sourced terminal:

Using rosrun: rosrun lidar_apollo_cnn_seg_detect lidar_apollo_cnn_seg_detect _network_definition_file:=/PATH/TO/FILE.prototxt _pretrained_model_file:=/PATH/TO/WEIGHTS.caffemodel _points_src:=/points_raw

Using launch file: roslaunch lidar_apollo_cnn_seg_detect lidar_apollo_cnn_seg_detect.launch network_definition_file:=/PATH/TO/FILE.prototxt pretrained_model_file:=/PATH/TO/WEIGHTS.caffemodel points_src:=/points_raw

  • From Runtime Manager:

Computing Tab -> Detection/ lidar_detector -> lidar_cnn_baidu_detect. Configure parameters using the [app] button.

Parameters

Parameter Type Description Default
network_definition_file String Path to the network definition file (prototxt)  
pretrained_model_file String Path to the Pretrained model (weights)  
points_src String Input topic Pointcloud. Default. /points_raw
score_threshold Double Minimum score required as given by the network to include the result (0.-1.) 0.6
use_gpu Bool Whether ot not to use a GPU device true
gpu_device_id Int GPU ID 0
width Int Width of the 2d cluster 512
height Int Height of the 2d cluster 512
range Int Range for the 2d cluster 60
use_constant_feature Bool Use constant model feature (8 features) false
normalize_lidar_intensity Bool Normalize the received lidar intensity data false

Outputs

Topic Type Description
/detection/lidar_detector/points_cluster sensor_msgs/PointCloud2 Colored PointCloud of the resulting detected objects
/detection/lidar_detector/objects autoware_msgs/DetectedObjetArray Array of Detected Objects in Autoware format

Notes

  • To display the results in Rviz objects_visualizer is required. (Launch file launches automatically this node).

  • Pre trained models can be downloaded from the Apollo project repository.

CHANGELOG

Changelog for package lidar_apollo_cnn_seg_detect

1.11.0 (2019-03-21)

  • [feature] Baidu's CNN based LiDAR segmentation (#1800)
    • Add build caffe

    • add include apollo files

    • add apollo cnn

    • calculating time

      • Cleaned node
    • Parametrized inputs

    • Works with custom caffe

      • Parameterized
    • Works with custom Caffe

    • Removed hard coded params

    • Cleaned up dependencies

    • Added bboxes, labels

    • Minor fixes

    • Custom input topic

    • Added UI, launch file, readme

    • Added Compatibility for Perception Cleanup

      • Added license messages
    • Updated readme

    • Added extra instructions

    • Fix markdown
  • Contributors: Abraham Monrroy Cano

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

No known dependants.

Launch files

  • launch/lidar_apollo_cnn_seg_detect.launch
      • network_definition_file
      • pretrained_model_file
      • points_src [default: /points_raw]
      • score_threshold [default: 0.6]
      • use_gpu [default: true]
      • gpu_device_id [default: 0]
      • width [default: 512]
      • height [default: 512]
      • range [default: 60]
      • use_constant_feature [default: false]
      • normalize_lidar_intensity [default: false]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged lidar_apollo_cnn_seg_detect at Robotics Stack Exchange

Package symbol

lidar_apollo_cnn_seg_detect package from autoware_learn repo

amathutils_lib autoware_build_flags autoware_health_checker emergency_handler gnss lanelet2_extension libvectormap libwaypoint_follower map_file object_map op_planner op_ros_helpers op_simu op_utility ros_observer tvm_utility vector_map vector_map_server vehicle_sim_model autoware_connector ekf_localizer gnss_localizer image_processor imm_ukf_pda_track lidar_apollo_cnn_seg_detect lidar_euclidean_cluster_detect lidar_fake_perception lidar_kf_contour_track lidar_localizer lidar_naive_l_shape_detect lidar_point_pillars lidar_shape_estimation naive_motion_predict ndt_cpu ndt_gpu ndt_tku obj_db pcl_omp_registration pixel_cloud_fusion points_downsampler points_preprocessor pos_db range_vision_fusion road_occupancy_processor roi_object_filter trafficlight_recognizer twist_generator vel_pose_diff_checker vision_beyond_track vision_darknet_detect vision_lane_detect vision_segment_enet_detect vision_ssd_detect astar_search costmap_generator decision_maker dp_planner ff_waypoint_follower freespace_planner lane_planner lattice_planner ll2_global_planner mpc_follower op_global_planner op_local_planner op_simulation_package op_utilities pure_pursuit state_machine_lib twist_filter twist_gate way_planner waypoint_maker waypoint_planner autoware_quickstart_examples autoware_can_msgs autoware_config_msgs autoware_external_msgs autoware_lanelet2_msgs autoware_map_msgs autoware_msgs autoware_system_msgs tablet_socket_msgs vector_map_msgs carla_autoware_bridge gazebo_camera_description gazebo_imu_description lgsvl_simulator_bridge vehicle_gazebo_simulation_interface vehicle_gazebo_simulation_launcher wf_simulator autoware_bag_tools autoware_camera_lidar_calibrator autoware_launcher autoware_launcher_rviz calibration_publisher data_preprocessor graph_tools kitti_box_publisher kitti_launch kitti_player lanelet_aisan_converter log_tools map_tf_generator map_tools marker_downsampler mqtt_socket multi_lidar_calibrator oculus_socket pc2_downsampler rosbag_controller runtime_manager sound_player system_monitor tablet_socket twist2odom udon_socket vehicle_engage_panel vehicle_socket decision_maker_panel detected_objects_visualizer fastvirtualscan gazebo_world_description glviewer integrated_viewer points2image rosinterface autoware_rviz_plugins vehicle_description vehicle_model adi_driver as autoware_driveworks_gmsl_interface autoware_driveworks_interface vlg22c_cam custom_msgs garmin hokuyo javad_navsat_driver kvaser sick_lms5xx memsic_imu microstrain_driver nmea_navsat autoware_pointgrey_drivers sick_ldmrs_description sick_ldmrs_driver sick_ldmrs_laser sick_ldmrs_msgs sick_ldmrs_tools vectacam xsens_driver ymc ds4 ds4_driver ds4_msgs lanelet2 lanelet2_core lanelet2_examples lanelet2_io lanelet2_maps lanelet2_matching lanelet2_projection lanelet2_python lanelet2_routing lanelet2_traffic_rules lanelet2_validation mrt_cmake_modules

ROS Distro
github

Package Summary

Tags No category tags.
Version 1.12.0
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Description autoware.ai perf
Checkout URI https://github.com/is-whale/autoware_learn.git
VCS Type git
VCS Version 1.14
Last Updated 2025-03-14
Dev Status UNKNOWN
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The apollo cnn segmentation package

Additional Links

No additional links.

Maintainers

  • Kosuke Murakami

Authors

  • Kosuke Murakami

CNN LiDAR Baidu Object Segmenter

Autoware package based on Baidu’s object segmenter.

Pre requisites

Caffe distributable installed in your home (~/caffe/distribute).

$ cd
$ git clone https://github.com/BVLC/caffe
$ cd caffe

Follow instructions from Installing Caffe from source.

  • Use offical Make compilation procedure.
  • Do not use thirdparty CMake setup.

Compile and create distributable:

$ make
$ make distribute

Recompile Autoware to build the node.

The Pretrained model

Use this link to download the pretrained model from Baidu:

https://github.com/ApolloAuto/apollo/tree/v5.5.0/modules/perception/production/data/perception/lidar/models/cnnseg

These two files are needed:

  • deploy.prototxt
  • deploy.caffemodel

How to launch

  • From a sourced terminal:

Using rosrun: rosrun lidar_apollo_cnn_seg_detect lidar_apollo_cnn_seg_detect _network_definition_file:=/PATH/TO/FILE.prototxt _pretrained_model_file:=/PATH/TO/WEIGHTS.caffemodel _points_src:=/points_raw

Using launch file: roslaunch lidar_apollo_cnn_seg_detect lidar_apollo_cnn_seg_detect.launch network_definition_file:=/PATH/TO/FILE.prototxt pretrained_model_file:=/PATH/TO/WEIGHTS.caffemodel points_src:=/points_raw

  • From Runtime Manager:

Computing Tab -> Detection/ lidar_detector -> lidar_cnn_baidu_detect. Configure parameters using the [app] button.

Parameters

Parameter Type Description Default
network_definition_file String Path to the network definition file (prototxt)  
pretrained_model_file String Path to the Pretrained model (weights)  
points_src String Input topic Pointcloud. Default. /points_raw
score_threshold Double Minimum score required as given by the network to include the result (0.-1.) 0.6
use_gpu Bool Whether ot not to use a GPU device true
gpu_device_id Int GPU ID 0
width Int Width of the 2d cluster 512
height Int Height of the 2d cluster 512
range Int Range for the 2d cluster 60
use_constant_feature Bool Use constant model feature (8 features) false
normalize_lidar_intensity Bool Normalize the received lidar intensity data false

Outputs

Topic Type Description
/detection/lidar_detector/points_cluster sensor_msgs/PointCloud2 Colored PointCloud of the resulting detected objects
/detection/lidar_detector/objects autoware_msgs/DetectedObjetArray Array of Detected Objects in Autoware format

Notes

  • To display the results in Rviz objects_visualizer is required. (Launch file launches automatically this node).

  • Pre trained models can be downloaded from the Apollo project repository.

CHANGELOG

Changelog for package lidar_apollo_cnn_seg_detect

1.11.0 (2019-03-21)

  • [feature] Baidu's CNN based LiDAR segmentation (#1800)
    • Add build caffe

    • add include apollo files

    • add apollo cnn

    • calculating time

      • Cleaned node
    • Parametrized inputs

    • Works with custom caffe

      • Parameterized
    • Works with custom Caffe

    • Removed hard coded params

    • Cleaned up dependencies

    • Added bboxes, labels

    • Minor fixes

    • Custom input topic

    • Added UI, launch file, readme

    • Added Compatibility for Perception Cleanup

      • Added license messages
    • Updated readme

    • Added extra instructions

    • Fix markdown
  • Contributors: Abraham Monrroy Cano

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

No known dependants.

Launch files

  • launch/lidar_apollo_cnn_seg_detect.launch
      • network_definition_file
      • pretrained_model_file
      • points_src [default: /points_raw]
      • score_threshold [default: 0.6]
      • use_gpu [default: true]
      • gpu_device_id [default: 0]
      • width [default: 512]
      • height [default: 512]
      • range [default: 60]
      • use_constant_feature [default: false]
      • normalize_lidar_intensity [default: false]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged lidar_apollo_cnn_seg_detect at Robotics Stack Exchange

No version for distro galactic showing github. Known supported distros are highlighted in the buttons above.
Package symbol

lidar_apollo_cnn_seg_detect package from autoware_learn repo

amathutils_lib autoware_build_flags autoware_health_checker emergency_handler gnss lanelet2_extension libvectormap libwaypoint_follower map_file object_map op_planner op_ros_helpers op_simu op_utility ros_observer tvm_utility vector_map vector_map_server vehicle_sim_model autoware_connector ekf_localizer gnss_localizer image_processor imm_ukf_pda_track lidar_apollo_cnn_seg_detect lidar_euclidean_cluster_detect lidar_fake_perception lidar_kf_contour_track lidar_localizer lidar_naive_l_shape_detect lidar_point_pillars lidar_shape_estimation naive_motion_predict ndt_cpu ndt_gpu ndt_tku obj_db pcl_omp_registration pixel_cloud_fusion points_downsampler points_preprocessor pos_db range_vision_fusion road_occupancy_processor roi_object_filter trafficlight_recognizer twist_generator vel_pose_diff_checker vision_beyond_track vision_darknet_detect vision_lane_detect vision_segment_enet_detect vision_ssd_detect astar_search costmap_generator decision_maker dp_planner ff_waypoint_follower freespace_planner lane_planner lattice_planner ll2_global_planner mpc_follower op_global_planner op_local_planner op_simulation_package op_utilities pure_pursuit state_machine_lib twist_filter twist_gate way_planner waypoint_maker waypoint_planner autoware_quickstart_examples autoware_can_msgs autoware_config_msgs autoware_external_msgs autoware_lanelet2_msgs autoware_map_msgs autoware_msgs autoware_system_msgs tablet_socket_msgs vector_map_msgs carla_autoware_bridge gazebo_camera_description gazebo_imu_description lgsvl_simulator_bridge vehicle_gazebo_simulation_interface vehicle_gazebo_simulation_launcher wf_simulator autoware_bag_tools autoware_camera_lidar_calibrator autoware_launcher autoware_launcher_rviz calibration_publisher data_preprocessor graph_tools kitti_box_publisher kitti_launch kitti_player lanelet_aisan_converter log_tools map_tf_generator map_tools marker_downsampler mqtt_socket multi_lidar_calibrator oculus_socket pc2_downsampler rosbag_controller runtime_manager sound_player system_monitor tablet_socket twist2odom udon_socket vehicle_engage_panel vehicle_socket decision_maker_panel detected_objects_visualizer fastvirtualscan gazebo_world_description glviewer integrated_viewer points2image rosinterface autoware_rviz_plugins vehicle_description vehicle_model adi_driver as autoware_driveworks_gmsl_interface autoware_driveworks_interface vlg22c_cam custom_msgs garmin hokuyo javad_navsat_driver kvaser sick_lms5xx memsic_imu microstrain_driver nmea_navsat autoware_pointgrey_drivers sick_ldmrs_description sick_ldmrs_driver sick_ldmrs_laser sick_ldmrs_msgs sick_ldmrs_tools vectacam xsens_driver ymc ds4 ds4_driver ds4_msgs lanelet2 lanelet2_core lanelet2_examples lanelet2_io lanelet2_maps lanelet2_matching lanelet2_projection lanelet2_python lanelet2_routing lanelet2_traffic_rules lanelet2_validation mrt_cmake_modules

ROS Distro
github

Package Summary

Tags No category tags.
Version 1.12.0
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Description autoware.ai perf
Checkout URI https://github.com/is-whale/autoware_learn.git
VCS Type git
VCS Version 1.14
Last Updated 2025-03-14
Dev Status UNKNOWN
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The apollo cnn segmentation package

Additional Links

No additional links.

Maintainers

  • Kosuke Murakami

Authors

  • Kosuke Murakami

CNN LiDAR Baidu Object Segmenter

Autoware package based on Baidu’s object segmenter.

Pre requisites

Caffe distributable installed in your home (~/caffe/distribute).

$ cd
$ git clone https://github.com/BVLC/caffe
$ cd caffe

Follow instructions from Installing Caffe from source.

  • Use offical Make compilation procedure.
  • Do not use thirdparty CMake setup.

Compile and create distributable:

$ make
$ make distribute

Recompile Autoware to build the node.

The Pretrained model

Use this link to download the pretrained model from Baidu:

https://github.com/ApolloAuto/apollo/tree/v5.5.0/modules/perception/production/data/perception/lidar/models/cnnseg

These two files are needed:

  • deploy.prototxt
  • deploy.caffemodel

How to launch

  • From a sourced terminal:

Using rosrun: rosrun lidar_apollo_cnn_seg_detect lidar_apollo_cnn_seg_detect _network_definition_file:=/PATH/TO/FILE.prototxt _pretrained_model_file:=/PATH/TO/WEIGHTS.caffemodel _points_src:=/points_raw

Using launch file: roslaunch lidar_apollo_cnn_seg_detect lidar_apollo_cnn_seg_detect.launch network_definition_file:=/PATH/TO/FILE.prototxt pretrained_model_file:=/PATH/TO/WEIGHTS.caffemodel points_src:=/points_raw

  • From Runtime Manager:

Computing Tab -> Detection/ lidar_detector -> lidar_cnn_baidu_detect. Configure parameters using the [app] button.

Parameters

Parameter Type Description Default
network_definition_file String Path to the network definition file (prototxt)  
pretrained_model_file String Path to the Pretrained model (weights)  
points_src String Input topic Pointcloud. Default. /points_raw
score_threshold Double Minimum score required as given by the network to include the result (0.-1.) 0.6
use_gpu Bool Whether ot not to use a GPU device true
gpu_device_id Int GPU ID 0
width Int Width of the 2d cluster 512
height Int Height of the 2d cluster 512
range Int Range for the 2d cluster 60
use_constant_feature Bool Use constant model feature (8 features) false
normalize_lidar_intensity Bool Normalize the received lidar intensity data false

Outputs

Topic Type Description
/detection/lidar_detector/points_cluster sensor_msgs/PointCloud2 Colored PointCloud of the resulting detected objects
/detection/lidar_detector/objects autoware_msgs/DetectedObjetArray Array of Detected Objects in Autoware format

Notes

  • To display the results in Rviz objects_visualizer is required. (Launch file launches automatically this node).

  • Pre trained models can be downloaded from the Apollo project repository.

CHANGELOG

Changelog for package lidar_apollo_cnn_seg_detect

1.11.0 (2019-03-21)

  • [feature] Baidu's CNN based LiDAR segmentation (#1800)
    • Add build caffe

    • add include apollo files

    • add apollo cnn

    • calculating time

      • Cleaned node
    • Parametrized inputs

    • Works with custom caffe

      • Parameterized
    • Works with custom Caffe

    • Removed hard coded params

    • Cleaned up dependencies

    • Added bboxes, labels

    • Minor fixes

    • Custom input topic

    • Added UI, launch file, readme

    • Added Compatibility for Perception Cleanup

      • Added license messages
    • Updated readme

    • Added extra instructions

    • Fix markdown
  • Contributors: Abraham Monrroy Cano

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

No known dependants.

Launch files

  • launch/lidar_apollo_cnn_seg_detect.launch
      • network_definition_file
      • pretrained_model_file
      • points_src [default: /points_raw]
      • score_threshold [default: 0.6]
      • use_gpu [default: true]
      • gpu_device_id [default: 0]
      • width [default: 512]
      • height [default: 512]
      • range [default: 60]
      • use_constant_feature [default: false]
      • normalize_lidar_intensity [default: false]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged lidar_apollo_cnn_seg_detect at Robotics Stack Exchange

No version for distro iron showing github. Known supported distros are highlighted in the buttons above.
Package symbol

lidar_apollo_cnn_seg_detect package from autoware_learn repo

amathutils_lib autoware_build_flags autoware_health_checker emergency_handler gnss lanelet2_extension libvectormap libwaypoint_follower map_file object_map op_planner op_ros_helpers op_simu op_utility ros_observer tvm_utility vector_map vector_map_server vehicle_sim_model autoware_connector ekf_localizer gnss_localizer image_processor imm_ukf_pda_track lidar_apollo_cnn_seg_detect lidar_euclidean_cluster_detect lidar_fake_perception lidar_kf_contour_track lidar_localizer lidar_naive_l_shape_detect lidar_point_pillars lidar_shape_estimation naive_motion_predict ndt_cpu ndt_gpu ndt_tku obj_db pcl_omp_registration pixel_cloud_fusion points_downsampler points_preprocessor pos_db range_vision_fusion road_occupancy_processor roi_object_filter trafficlight_recognizer twist_generator vel_pose_diff_checker vision_beyond_track vision_darknet_detect vision_lane_detect vision_segment_enet_detect vision_ssd_detect astar_search costmap_generator decision_maker dp_planner ff_waypoint_follower freespace_planner lane_planner lattice_planner ll2_global_planner mpc_follower op_global_planner op_local_planner op_simulation_package op_utilities pure_pursuit state_machine_lib twist_filter twist_gate way_planner waypoint_maker waypoint_planner autoware_quickstart_examples autoware_can_msgs autoware_config_msgs autoware_external_msgs autoware_lanelet2_msgs autoware_map_msgs autoware_msgs autoware_system_msgs tablet_socket_msgs vector_map_msgs carla_autoware_bridge gazebo_camera_description gazebo_imu_description lgsvl_simulator_bridge vehicle_gazebo_simulation_interface vehicle_gazebo_simulation_launcher wf_simulator autoware_bag_tools autoware_camera_lidar_calibrator autoware_launcher autoware_launcher_rviz calibration_publisher data_preprocessor graph_tools kitti_box_publisher kitti_launch kitti_player lanelet_aisan_converter log_tools map_tf_generator map_tools marker_downsampler mqtt_socket multi_lidar_calibrator oculus_socket pc2_downsampler rosbag_controller runtime_manager sound_player system_monitor tablet_socket twist2odom udon_socket vehicle_engage_panel vehicle_socket decision_maker_panel detected_objects_visualizer fastvirtualscan gazebo_world_description glviewer integrated_viewer points2image rosinterface autoware_rviz_plugins vehicle_description vehicle_model adi_driver as autoware_driveworks_gmsl_interface autoware_driveworks_interface vlg22c_cam custom_msgs garmin hokuyo javad_navsat_driver kvaser sick_lms5xx memsic_imu microstrain_driver nmea_navsat autoware_pointgrey_drivers sick_ldmrs_description sick_ldmrs_driver sick_ldmrs_laser sick_ldmrs_msgs sick_ldmrs_tools vectacam xsens_driver ymc ds4 ds4_driver ds4_msgs lanelet2 lanelet2_core lanelet2_examples lanelet2_io lanelet2_maps lanelet2_matching lanelet2_projection lanelet2_python lanelet2_routing lanelet2_traffic_rules lanelet2_validation mrt_cmake_modules

ROS Distro
github

Package Summary

Tags No category tags.
Version 1.12.0
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Description autoware.ai perf
Checkout URI https://github.com/is-whale/autoware_learn.git
VCS Type git
VCS Version 1.14
Last Updated 2025-03-14
Dev Status UNKNOWN
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The apollo cnn segmentation package

Additional Links

No additional links.

Maintainers

  • Kosuke Murakami

Authors

  • Kosuke Murakami

CNN LiDAR Baidu Object Segmenter

Autoware package based on Baidu’s object segmenter.

Pre requisites

Caffe distributable installed in your home (~/caffe/distribute).

$ cd
$ git clone https://github.com/BVLC/caffe
$ cd caffe

Follow instructions from Installing Caffe from source.

  • Use offical Make compilation procedure.
  • Do not use thirdparty CMake setup.

Compile and create distributable:

$ make
$ make distribute

Recompile Autoware to build the node.

The Pretrained model

Use this link to download the pretrained model from Baidu:

https://github.com/ApolloAuto/apollo/tree/v5.5.0/modules/perception/production/data/perception/lidar/models/cnnseg

These two files are needed:

  • deploy.prototxt
  • deploy.caffemodel

How to launch

  • From a sourced terminal:

Using rosrun: rosrun lidar_apollo_cnn_seg_detect lidar_apollo_cnn_seg_detect _network_definition_file:=/PATH/TO/FILE.prototxt _pretrained_model_file:=/PATH/TO/WEIGHTS.caffemodel _points_src:=/points_raw

Using launch file: roslaunch lidar_apollo_cnn_seg_detect lidar_apollo_cnn_seg_detect.launch network_definition_file:=/PATH/TO/FILE.prototxt pretrained_model_file:=/PATH/TO/WEIGHTS.caffemodel points_src:=/points_raw

  • From Runtime Manager:

Computing Tab -> Detection/ lidar_detector -> lidar_cnn_baidu_detect. Configure parameters using the [app] button.

Parameters

Parameter Type Description Default
network_definition_file String Path to the network definition file (prototxt)  
pretrained_model_file String Path to the Pretrained model (weights)  
points_src String Input topic Pointcloud. Default. /points_raw
score_threshold Double Minimum score required as given by the network to include the result (0.-1.) 0.6
use_gpu Bool Whether ot not to use a GPU device true
gpu_device_id Int GPU ID 0
width Int Width of the 2d cluster 512
height Int Height of the 2d cluster 512
range Int Range for the 2d cluster 60
use_constant_feature Bool Use constant model feature (8 features) false
normalize_lidar_intensity Bool Normalize the received lidar intensity data false

Outputs

Topic Type Description
/detection/lidar_detector/points_cluster sensor_msgs/PointCloud2 Colored PointCloud of the resulting detected objects
/detection/lidar_detector/objects autoware_msgs/DetectedObjetArray Array of Detected Objects in Autoware format

Notes

  • To display the results in Rviz objects_visualizer is required. (Launch file launches automatically this node).

  • Pre trained models can be downloaded from the Apollo project repository.

CHANGELOG

Changelog for package lidar_apollo_cnn_seg_detect

1.11.0 (2019-03-21)

  • [feature] Baidu's CNN based LiDAR segmentation (#1800)
    • Add build caffe

    • add include apollo files

    • add apollo cnn

    • calculating time

      • Cleaned node
    • Parametrized inputs

    • Works with custom caffe

      • Parameterized
    • Works with custom Caffe

    • Removed hard coded params

    • Cleaned up dependencies

    • Added bboxes, labels

    • Minor fixes

    • Custom input topic

    • Added UI, launch file, readme

    • Added Compatibility for Perception Cleanup

      • Added license messages
    • Updated readme

    • Added extra instructions

    • Fix markdown
  • Contributors: Abraham Monrroy Cano

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

No known dependants.

Launch files

  • launch/lidar_apollo_cnn_seg_detect.launch
      • network_definition_file
      • pretrained_model_file
      • points_src [default: /points_raw]
      • score_threshold [default: 0.6]
      • use_gpu [default: true]
      • gpu_device_id [default: 0]
      • width [default: 512]
      • height [default: 512]
      • range [default: 60]
      • use_constant_feature [default: false]
      • normalize_lidar_intensity [default: false]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged lidar_apollo_cnn_seg_detect at Robotics Stack Exchange

No version for distro melodic showing github. Known supported distros are highlighted in the buttons above.
Package symbol

lidar_apollo_cnn_seg_detect package from autoware_learn repo

amathutils_lib autoware_build_flags autoware_health_checker emergency_handler gnss lanelet2_extension libvectormap libwaypoint_follower map_file object_map op_planner op_ros_helpers op_simu op_utility ros_observer tvm_utility vector_map vector_map_server vehicle_sim_model autoware_connector ekf_localizer gnss_localizer image_processor imm_ukf_pda_track lidar_apollo_cnn_seg_detect lidar_euclidean_cluster_detect lidar_fake_perception lidar_kf_contour_track lidar_localizer lidar_naive_l_shape_detect lidar_point_pillars lidar_shape_estimation naive_motion_predict ndt_cpu ndt_gpu ndt_tku obj_db pcl_omp_registration pixel_cloud_fusion points_downsampler points_preprocessor pos_db range_vision_fusion road_occupancy_processor roi_object_filter trafficlight_recognizer twist_generator vel_pose_diff_checker vision_beyond_track vision_darknet_detect vision_lane_detect vision_segment_enet_detect vision_ssd_detect astar_search costmap_generator decision_maker dp_planner ff_waypoint_follower freespace_planner lane_planner lattice_planner ll2_global_planner mpc_follower op_global_planner op_local_planner op_simulation_package op_utilities pure_pursuit state_machine_lib twist_filter twist_gate way_planner waypoint_maker waypoint_planner autoware_quickstart_examples autoware_can_msgs autoware_config_msgs autoware_external_msgs autoware_lanelet2_msgs autoware_map_msgs autoware_msgs autoware_system_msgs tablet_socket_msgs vector_map_msgs carla_autoware_bridge gazebo_camera_description gazebo_imu_description lgsvl_simulator_bridge vehicle_gazebo_simulation_interface vehicle_gazebo_simulation_launcher wf_simulator autoware_bag_tools autoware_camera_lidar_calibrator autoware_launcher autoware_launcher_rviz calibration_publisher data_preprocessor graph_tools kitti_box_publisher kitti_launch kitti_player lanelet_aisan_converter log_tools map_tf_generator map_tools marker_downsampler mqtt_socket multi_lidar_calibrator oculus_socket pc2_downsampler rosbag_controller runtime_manager sound_player system_monitor tablet_socket twist2odom udon_socket vehicle_engage_panel vehicle_socket decision_maker_panel detected_objects_visualizer fastvirtualscan gazebo_world_description glviewer integrated_viewer points2image rosinterface autoware_rviz_plugins vehicle_description vehicle_model adi_driver as autoware_driveworks_gmsl_interface autoware_driveworks_interface vlg22c_cam custom_msgs garmin hokuyo javad_navsat_driver kvaser sick_lms5xx memsic_imu microstrain_driver nmea_navsat autoware_pointgrey_drivers sick_ldmrs_description sick_ldmrs_driver sick_ldmrs_laser sick_ldmrs_msgs sick_ldmrs_tools vectacam xsens_driver ymc ds4 ds4_driver ds4_msgs lanelet2 lanelet2_core lanelet2_examples lanelet2_io lanelet2_maps lanelet2_matching lanelet2_projection lanelet2_python lanelet2_routing lanelet2_traffic_rules lanelet2_validation mrt_cmake_modules

ROS Distro
github

Package Summary

Tags No category tags.
Version 1.12.0
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Description autoware.ai perf
Checkout URI https://github.com/is-whale/autoware_learn.git
VCS Type git
VCS Version 1.14
Last Updated 2025-03-14
Dev Status UNKNOWN
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The apollo cnn segmentation package

Additional Links

No additional links.

Maintainers

  • Kosuke Murakami

Authors

  • Kosuke Murakami

CNN LiDAR Baidu Object Segmenter

Autoware package based on Baidu’s object segmenter.

Pre requisites

Caffe distributable installed in your home (~/caffe/distribute).

$ cd
$ git clone https://github.com/BVLC/caffe
$ cd caffe

Follow instructions from Installing Caffe from source.

  • Use offical Make compilation procedure.
  • Do not use thirdparty CMake setup.

Compile and create distributable:

$ make
$ make distribute

Recompile Autoware to build the node.

The Pretrained model

Use this link to download the pretrained model from Baidu:

https://github.com/ApolloAuto/apollo/tree/v5.5.0/modules/perception/production/data/perception/lidar/models/cnnseg

These two files are needed:

  • deploy.prototxt
  • deploy.caffemodel

How to launch

  • From a sourced terminal:

Using rosrun: rosrun lidar_apollo_cnn_seg_detect lidar_apollo_cnn_seg_detect _network_definition_file:=/PATH/TO/FILE.prototxt _pretrained_model_file:=/PATH/TO/WEIGHTS.caffemodel _points_src:=/points_raw

Using launch file: roslaunch lidar_apollo_cnn_seg_detect lidar_apollo_cnn_seg_detect.launch network_definition_file:=/PATH/TO/FILE.prototxt pretrained_model_file:=/PATH/TO/WEIGHTS.caffemodel points_src:=/points_raw

  • From Runtime Manager:

Computing Tab -> Detection/ lidar_detector -> lidar_cnn_baidu_detect. Configure parameters using the [app] button.

Parameters

Parameter Type Description Default
network_definition_file String Path to the network definition file (prototxt)  
pretrained_model_file String Path to the Pretrained model (weights)  
points_src String Input topic Pointcloud. Default. /points_raw
score_threshold Double Minimum score required as given by the network to include the result (0.-1.) 0.6
use_gpu Bool Whether ot not to use a GPU device true
gpu_device_id Int GPU ID 0
width Int Width of the 2d cluster 512
height Int Height of the 2d cluster 512
range Int Range for the 2d cluster 60
use_constant_feature Bool Use constant model feature (8 features) false
normalize_lidar_intensity Bool Normalize the received lidar intensity data false

Outputs

Topic Type Description
/detection/lidar_detector/points_cluster sensor_msgs/PointCloud2 Colored PointCloud of the resulting detected objects
/detection/lidar_detector/objects autoware_msgs/DetectedObjetArray Array of Detected Objects in Autoware format

Notes

  • To display the results in Rviz objects_visualizer is required. (Launch file launches automatically this node).

  • Pre trained models can be downloaded from the Apollo project repository.

CHANGELOG

Changelog for package lidar_apollo_cnn_seg_detect

1.11.0 (2019-03-21)

  • [feature] Baidu's CNN based LiDAR segmentation (#1800)
    • Add build caffe

    • add include apollo files

    • add apollo cnn

    • calculating time

      • Cleaned node
    • Parametrized inputs

    • Works with custom caffe

      • Parameterized
    • Works with custom Caffe

    • Removed hard coded params

    • Cleaned up dependencies

    • Added bboxes, labels

    • Minor fixes

    • Custom input topic

    • Added UI, launch file, readme

    • Added Compatibility for Perception Cleanup

      • Added license messages
    • Updated readme

    • Added extra instructions

    • Fix markdown
  • Contributors: Abraham Monrroy Cano

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

No known dependants.

Launch files

  • launch/lidar_apollo_cnn_seg_detect.launch
      • network_definition_file
      • pretrained_model_file
      • points_src [default: /points_raw]
      • score_threshold [default: 0.6]
      • use_gpu [default: true]
      • gpu_device_id [default: 0]
      • width [default: 512]
      • height [default: 512]
      • range [default: 60]
      • use_constant_feature [default: false]
      • normalize_lidar_intensity [default: false]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged lidar_apollo_cnn_seg_detect at Robotics Stack Exchange

No version for distro noetic showing github. Known supported distros are highlighted in the buttons above.
Package symbol

lidar_apollo_cnn_seg_detect package from autoware_learn repo

amathutils_lib autoware_build_flags autoware_health_checker emergency_handler gnss lanelet2_extension libvectormap libwaypoint_follower map_file object_map op_planner op_ros_helpers op_simu op_utility ros_observer tvm_utility vector_map vector_map_server vehicle_sim_model autoware_connector ekf_localizer gnss_localizer image_processor imm_ukf_pda_track lidar_apollo_cnn_seg_detect lidar_euclidean_cluster_detect lidar_fake_perception lidar_kf_contour_track lidar_localizer lidar_naive_l_shape_detect lidar_point_pillars lidar_shape_estimation naive_motion_predict ndt_cpu ndt_gpu ndt_tku obj_db pcl_omp_registration pixel_cloud_fusion points_downsampler points_preprocessor pos_db range_vision_fusion road_occupancy_processor roi_object_filter trafficlight_recognizer twist_generator vel_pose_diff_checker vision_beyond_track vision_darknet_detect vision_lane_detect vision_segment_enet_detect vision_ssd_detect astar_search costmap_generator decision_maker dp_planner ff_waypoint_follower freespace_planner lane_planner lattice_planner ll2_global_planner mpc_follower op_global_planner op_local_planner op_simulation_package op_utilities pure_pursuit state_machine_lib twist_filter twist_gate way_planner waypoint_maker waypoint_planner autoware_quickstart_examples autoware_can_msgs autoware_config_msgs autoware_external_msgs autoware_lanelet2_msgs autoware_map_msgs autoware_msgs autoware_system_msgs tablet_socket_msgs vector_map_msgs carla_autoware_bridge gazebo_camera_description gazebo_imu_description lgsvl_simulator_bridge vehicle_gazebo_simulation_interface vehicle_gazebo_simulation_launcher wf_simulator autoware_bag_tools autoware_camera_lidar_calibrator autoware_launcher autoware_launcher_rviz calibration_publisher data_preprocessor graph_tools kitti_box_publisher kitti_launch kitti_player lanelet_aisan_converter log_tools map_tf_generator map_tools marker_downsampler mqtt_socket multi_lidar_calibrator oculus_socket pc2_downsampler rosbag_controller runtime_manager sound_player system_monitor tablet_socket twist2odom udon_socket vehicle_engage_panel vehicle_socket decision_maker_panel detected_objects_visualizer fastvirtualscan gazebo_world_description glviewer integrated_viewer points2image rosinterface autoware_rviz_plugins vehicle_description vehicle_model adi_driver as autoware_driveworks_gmsl_interface autoware_driveworks_interface vlg22c_cam custom_msgs garmin hokuyo javad_navsat_driver kvaser sick_lms5xx memsic_imu microstrain_driver nmea_navsat autoware_pointgrey_drivers sick_ldmrs_description sick_ldmrs_driver sick_ldmrs_laser sick_ldmrs_msgs sick_ldmrs_tools vectacam xsens_driver ymc ds4 ds4_driver ds4_msgs lanelet2 lanelet2_core lanelet2_examples lanelet2_io lanelet2_maps lanelet2_matching lanelet2_projection lanelet2_python lanelet2_routing lanelet2_traffic_rules lanelet2_validation mrt_cmake_modules

ROS Distro
github

Package Summary

Tags No category tags.
Version 1.12.0
License BSD
Build type CATKIN
Use RECOMMENDED

Repository Summary

Description autoware.ai perf
Checkout URI https://github.com/is-whale/autoware_learn.git
VCS Type git
VCS Version 1.14
Last Updated 2025-03-14
Dev Status UNKNOWN
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The apollo cnn segmentation package

Additional Links

No additional links.

Maintainers

  • Kosuke Murakami

Authors

  • Kosuke Murakami

CNN LiDAR Baidu Object Segmenter

Autoware package based on Baidu’s object segmenter.

Pre requisites

Caffe distributable installed in your home (~/caffe/distribute).

$ cd
$ git clone https://github.com/BVLC/caffe
$ cd caffe

Follow instructions from Installing Caffe from source.

  • Use offical Make compilation procedure.
  • Do not use thirdparty CMake setup.

Compile and create distributable:

$ make
$ make distribute

Recompile Autoware to build the node.

The Pretrained model

Use this link to download the pretrained model from Baidu:

https://github.com/ApolloAuto/apollo/tree/v5.5.0/modules/perception/production/data/perception/lidar/models/cnnseg

These two files are needed:

  • deploy.prototxt
  • deploy.caffemodel

How to launch

  • From a sourced terminal:

Using rosrun: rosrun lidar_apollo_cnn_seg_detect lidar_apollo_cnn_seg_detect _network_definition_file:=/PATH/TO/FILE.prototxt _pretrained_model_file:=/PATH/TO/WEIGHTS.caffemodel _points_src:=/points_raw

Using launch file: roslaunch lidar_apollo_cnn_seg_detect lidar_apollo_cnn_seg_detect.launch network_definition_file:=/PATH/TO/FILE.prototxt pretrained_model_file:=/PATH/TO/WEIGHTS.caffemodel points_src:=/points_raw

  • From Runtime Manager:

Computing Tab -> Detection/ lidar_detector -> lidar_cnn_baidu_detect. Configure parameters using the [app] button.

Parameters

Parameter Type Description Default
network_definition_file String Path to the network definition file (prototxt)  
pretrained_model_file String Path to the Pretrained model (weights)  
points_src String Input topic Pointcloud. Default. /points_raw
score_threshold Double Minimum score required as given by the network to include the result (0.-1.) 0.6
use_gpu Bool Whether ot not to use a GPU device true
gpu_device_id Int GPU ID 0
width Int Width of the 2d cluster 512
height Int Height of the 2d cluster 512
range Int Range for the 2d cluster 60
use_constant_feature Bool Use constant model feature (8 features) false
normalize_lidar_intensity Bool Normalize the received lidar intensity data false

Outputs

Topic Type Description
/detection/lidar_detector/points_cluster sensor_msgs/PointCloud2 Colored PointCloud of the resulting detected objects
/detection/lidar_detector/objects autoware_msgs/DetectedObjetArray Array of Detected Objects in Autoware format

Notes

  • To display the results in Rviz objects_visualizer is required. (Launch file launches automatically this node).

  • Pre trained models can be downloaded from the Apollo project repository.

CHANGELOG

Changelog for package lidar_apollo_cnn_seg_detect

1.11.0 (2019-03-21)

  • [feature] Baidu's CNN based LiDAR segmentation (#1800)
    • Add build caffe

    • add include apollo files

    • add apollo cnn

    • calculating time

      • Cleaned node
    • Parametrized inputs

    • Works with custom caffe

      • Parameterized
    • Works with custom Caffe

    • Removed hard coded params

    • Cleaned up dependencies

    • Added bboxes, labels

    • Minor fixes

    • Custom input topic

    • Added UI, launch file, readme

    • Added Compatibility for Perception Cleanup

      • Added license messages
    • Updated readme

    • Added extra instructions

    • Fix markdown
  • Contributors: Abraham Monrroy Cano

Package Dependencies

System Dependencies

No direct system dependencies.

Dependant Packages

No known dependants.

Launch files

  • launch/lidar_apollo_cnn_seg_detect.launch
      • network_definition_file
      • pretrained_model_file
      • points_src [default: /points_raw]
      • score_threshold [default: 0.6]
      • use_gpu [default: true]
      • gpu_device_id [default: 0]
      • width [default: 512]
      • height [default: 512]
      • range [default: 60]
      • use_constant_feature [default: false]
      • normalize_lidar_intensity [default: false]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged lidar_apollo_cnn_seg_detect at Robotics Stack Exchange