🕵️‍♂️ Object Detection

Once the planner is set up and the real SMB is running, you can begin experimenting with object detection. Ensure that the object_detection package is built. If it isn’t, use the following command:

# On the SMB
catkin build object_detection   

Source the workspace again and launch the SMB launch file.

# On the SMB
roslaunch smb smb.launch

# If you see the message "First IMU Received",
# everything started without any problem

Next, launch the object detection locally with these parameters for the real robot:

• model_path="": Don’t set this parameter if you want to use the pre-installed model. If you have a downloaded model, specify its path.
• model="yolov5l6": Selects the pre-installed YOLOv5 model.
• object_detection_classes="[0,1,2,10]": Populate this list with the IDs of objects added to the real scene. If you leave this empty, it will try to detect the following objects [0,24, 25, 28, 32, 39, 41, 45, 46, 47, 56] from the dataset. To see what numbers correspond to what items, check out the Artefact Detection Tutorial page and look for the YOLOv5 Supported Object Classes section. The example [0, 1, 2, 10] corresponds to person, bicycle, car, and fire hydrant.

To launch the detection pipeline locally, run:

# On the SMB
roslaunch object_detection object_detection.launch object_detection_classes:="[0,1,2,10]"

To view the bounding boxes and get more information about the detections use the following two commands:

# On the host
rosrun rqt_image_view rqt_image_view

Then select the following topic to see the bounding boxes in the image:

/object_detector/detections_in_image

To get more information like position, classification, etc. subscribe to or echo the following topic:

# On the host
rostopic echo /object_detector/detection_info

For more information, please check out the Artefact Detection Tutorial.