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Test/smb_264 #1

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81d920e
add gitkeep
zcsun52 Jun 23, 2025
38190c8
Update requirements and launch files for object detection; specify ve…
zcsun52 Jun 23, 2025
20355fd
fix obj
zcsun52 Jun 23, 2025
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151 changes: 151 additions & 0 deletions object_detection/launch/debayer.launch.py
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from launch import LaunchDescription
from launch.actions import DeclareLaunchArgument, IncludeLaunchDescription, GroupAction
from launch.conditions import IfCondition
from launch.launch_description_sources import PythonLaunchDescriptionSource
from launch.substitutions import (
LaunchConfiguration,
EnvironmentVariable,
PathJoinSubstitution,
TextSubstitution,
)
from launch_ros.actions import Node
from launch_ros.substitutions import FindPackageShare
from ament_index_python.packages import get_package_share_directory
import os


def generate_launch_description():
# Declare all launch arguments
declared_arguments = [
DeclareLaunchArgument(
"smb_name",
default_value=EnvironmentVariable("SMB_NAME", default_value="smb261"),
description="Name of the SMB in the format smb26x (relevant for calibrations)",
),
DeclareLaunchArgument(
"gpu",
default_value="local",
description="Run on GPU? Options: 'local', 'remote' (default), 'off'",
choices=["local", "remote", "off"],
),
DeclareLaunchArgument(
"GPU_user",
default_value=EnvironmentVariable("USER"),
description="Username to use on the jetson xavier GPU",
),
DeclareLaunchArgument(
"input_camera_name",
default_value="/rgb_camera",
description="Name of the camera, i.e. topic prefix for camera stream and camera info",
),
DeclareLaunchArgument(
"debayer_image",
default_value="true",
description="Debayer the images (supplied in $input_camera_name/image_raw)",
),
DeclareLaunchArgument(
"lidar_topic",
default_value="/rslidar/points",
description="Topic containing the point cloud from the lidar",
),
DeclareLaunchArgument(
"object_detection_classes",
default_value="[0,24,25,28,32,39,41,45,46,47,56]",
description="List of the ids of classes for detection (COCO dataset)",
),
DeclareLaunchArgument(
"model_dir_path",
default_value=PathJoinSubstitution(
[
FindPackageShare("object_detection"),
"models",
]
),
description="path to the yolo model directory",
),
DeclareLaunchArgument(
"model", default_value="yolov5l6", description="yolo model name"
),
]

# Debayer the image (conditionally included)
debayer_image_group = GroupAction(
[
IncludeLaunchDescription(
PythonLaunchDescriptionSource(
PathJoinSubstitution(
[
FindPackageShare("object_detection"),
"launch",
"debayer.launch.py",
]
)
),
condition=IfCondition(LaunchConfiguration("debayer_image")),
launch_arguments={
"input_camera_name": LaunchConfiguration("input_camera_name")
},
)
]
)

# Object detection node

object_detection_group = GroupAction(
[
Node(
package="object_detection",
executable="object_detection_node.py",
name="object_detector",
output="screen",
parameters=[
# Input related
{
"camera_topic": PathJoinSubstitution(
[LaunchConfiguration("input_camera_name"), "image_raw"]
)
},
{
"camera_info_topic": PathJoinSubstitution(
[LaunchConfiguration("input_camera_name"), "camera_info"]
)
},
{"lidar_topic": LaunchConfiguration("lidar_topic")},
# Output related - load from file
{"project_object_points_to_image": True},
{"project_all_points_to_image": False},
{"object_detection_pos_topic": "object_positions"},
{"object_detection_output_image_topic": "detections_in_image"},
{"object_detection_point_clouds_topic": "detection_point_clouds"},
{"object_detection_info_topic": "detection_info"},
# Camera Lidar synchronization related
{"camera_lidar_sync_queue_size": 10},
{"camera_lidar_sync_slop": 0.1},
# Point Projector related
{
"project_config": [
TextSubstitution(text="projector_config_"),
LaunchConfiguration("smb_name"),
TextSubstitution(text=".yaml"),
]
},
# Object detection related
{"model": LaunchConfiguration("model")},
{"model_dir_path": LaunchConfiguration("model_dir_path")},
{"device": "0" if LaunchConfiguration("gpu") != "off" else "cpu"},
{"confident": 0.0},
{"iou": 0.1},
{"classes": LaunchConfiguration("object_detection_classes")},
{"multiple_instance": False},
# Object localization related
{"model_method": "hdbscan"},
{"ground_percentage": 25},
{"bb_contract_percentage": 10},
],
)
]
)

return LaunchDescription(
declared_arguments + [debayer_image_group, object_detection_group]
)
151 changes: 151 additions & 0 deletions object_detection/launch/object_detection_real.launch.py
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from launch import LaunchDescription
from launch.actions import DeclareLaunchArgument, IncludeLaunchDescription, GroupAction
from launch.conditions import IfCondition
from launch.launch_description_sources import PythonLaunchDescriptionSource
from launch.substitutions import (
LaunchConfiguration,
EnvironmentVariable,
PathJoinSubstitution,
TextSubstitution,
)
from launch_ros.actions import Node
from launch_ros.substitutions import FindPackageShare
from ament_index_python.packages import get_package_share_directory
import os


def generate_launch_description():
# Declare all launch arguments
declared_arguments = [
DeclareLaunchArgument(
"smb_name",
default_value=EnvironmentVariable("SMB_NAME", default_value="smb261"),
description="Name of the SMB in the format smb26x (relevant for calibrations)",
),
DeclareLaunchArgument(
"gpu",
default_value="local",
description="Run on GPU? Options: 'local', 'remote' (default), 'off'",
choices=["local", "remote", "off"],
),
DeclareLaunchArgument(
"GPU_user",
default_value=EnvironmentVariable("USER"),
description="Username to use on the jetson xavier GPU",
),
DeclareLaunchArgument(
"input_camera_name",
default_value="/rgb_camera",
description="Name of the camera, i.e. topic prefix for camera stream and camera info",
),
DeclareLaunchArgument(
"debayer_image",
default_value="false",
description="Debayer the images (supplied in $input_camera_name/image_raw)",
),
DeclareLaunchArgument(
"lidar_topic",
default_value="/rslidar/points",
description="Topic containing the point cloud from the lidar",
),
DeclareLaunchArgument(
"object_detection_classes",
default_value="[0,24,25,28,32,39,41,45,46,47,56]",
description="List of the ids of classes for detection (COCO dataset)",
),
DeclareLaunchArgument(
"model_dir_path",
default_value=PathJoinSubstitution(
[
FindPackageShare("object_detection"),
"models",
]
),
description="path to the yolo model directory",
),
DeclareLaunchArgument(
"model", default_value="yolov5l6", description="yolo model name"
),
]

# Debayer the image (conditionally included)
debayer_image_group = GroupAction(
[
IncludeLaunchDescription(
PythonLaunchDescriptionSource(
PathJoinSubstitution(
[
FindPackageShare("object_detection"),
"launch",
"debayer.launch.py",
]
)
),
condition=IfCondition(LaunchConfiguration("debayer_image")),
launch_arguments=[
("input_camera_name", LaunchConfiguration("input_camera_name"))
],
)
]
)

# Object detection node

object_detection_group = GroupAction(
[
Node(
package="object_detection",
executable="object_detection_node.py",
name="object_detector",
output="screen",
parameters=[
# Input related
{
"camera_topic": PathJoinSubstitution(
[LaunchConfiguration("input_camera_name"), "image_debayered"]
)
},
{
"camera_info_topic": PathJoinSubstitution(
[LaunchConfiguration("input_camera_name"), "camera_info"]
)
},
{"lidar_topic": LaunchConfiguration("lidar_topic")},
# Output related - load from file
{"project_object_points_to_image": True},
{"project_all_points_to_image": False},
{"object_detection_pos_topic": "object_positions"},
{"object_detection_output_image_topic": "detections_in_image"},
{"object_detection_point_clouds_topic": "detection_point_clouds"},
{"object_detection_info_topic": "detection_info"},
# Camera Lidar synchronization related
{"camera_lidar_sync_queue_size": 10},
{"camera_lidar_sync_slop": 0.1},
# Point Projector related
{
"project_config": [
TextSubstitution(text="projector_config_"),
LaunchConfiguration("smb_name"),
TextSubstitution(text=".yaml"),
]
},
# Object detection related
{"model": LaunchConfiguration("model")},
{"model_dir_path": LaunchConfiguration("model_dir_path")},
{"device": "0" if LaunchConfiguration("gpu") != "off" else "cpu"},
{"confident": 0.0},
{"iou": 0.1},
{"classes": LaunchConfiguration("object_detection_classes")},
{"multiple_instance": False},
# Object localization related
{"model_method": "hdbscan"},
{"ground_percentage": 25},
{"bb_contract_percentage": 10},
],
)
]
)

return LaunchDescription(
declared_arguments + [debayer_image_group, object_detection_group]
)
Empty file added object_detection/models/.gitkeep
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30 changes: 13 additions & 17 deletions requirements.txt
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# pip install -r requirements.txt

# Base ----------------------------------------
matplotlib>=3.8.0
numpy==1.26.0
opencv-python>=4.8.0
Pillow>=10.0.0
PyYAML>=6.0.1
requests>=2.31.0
scipy>=1.11.0
torch>=2.1.0
torchvision>=0.16.0
tqdm>=4.65.0
matplotlib==3.7.5
numpy==1.23.5
opencv-python==4.10.0.84
pillow==10.4.0
PyYAML==5.3.1
requests==2.32.4
scipy==1.10.1
tqdm==4.67.1


# detection
yolov5
yolov5==7.0.14

# Logging -------------------------------------
tensorboard>=2.15.0
tensorboard==2.14.0

# Plotting ------------------------------------
pandas>=2.1.0
seaborn>=0.13.0
pandas==2.0.3
seaborn==0.13.2

hdbscan>=0.8.33

thop # FLOPs computation
hdbscan==0.8.40