Overall Detection

1. Course Content

• Run example programs, use the mediapipe framework to detect the overall body, including face, hands, and torso.

2. Program Startup

For Raspberry Pi 5 users, if the ROS container is not started, you need to start the container first,

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bringup_m3

Open a terminal inside the container,

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exec_m3

• Start the example program

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ros2 launch m3_bringup mediapipe_demo.launch.py demo:=Holistic

• After the program runs, as shown in the figure below, the detected overall points will be displayed on the right side of the image

3. Source Code Analysis

• Program code path:

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~/yahboomM3_ws/code_ws/src/m3_common_demo/m3_common_demo/mediapipe/03_Holistic.py

• Import the required library files,

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import rclpy
from rclpy.node import Node
from geometry_msgs.msg import Point
import mediapipe as mp
import cv2 as cv
import numpy as np
import time
import os
from cv_bridge import CvBridge
from sensor_msgs.msg import Image
from arm_msgs.msg import ArmJoints
import cv2
print("import done")

Initialize data and define publishers and subscribers,

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    def __init__(self, name,staticMode=False, landmarks=True, detectionCon=0.5, trackingCon=0.5):
        super().__init__(name)
        #Parameter declaration and acquisition
        self.declare_parameter('rgb_topic','/ascamera_hp60c/camera_publisher/rgb0/image')
        rgb_topic=self.get_parameter("rgb_topic").get_parameter_value().string_value
        self.mpHolistic = mp.solutions.holistic
        self.mpFaceMesh = mp.solutions.face_mesh
        self.mpHands = mp.solutions.hands
        self.mpPose = mp.solutions.pose
        self.mpDraw = mp.solutions.drawing_utils
        self.mpholistic = self.mpHolistic.Holistic(
            static_image_mode=staticMode,
            smooth_landmarks=landmarks,
            min_detection_confidence=detectionCon,
            min_tracking_confidence=trackingCon)
        self.lmDrawSpec = mp.solutions.drawing_utils.DrawingSpec(color=(0, 0, 255), thickness=-1, circle_radius=3)
        self.drawSpec = mp.solutions.drawing_utils.DrawingSpec(color=(0, 255, 0), thickness=2, circle_radius=2)
        #create a publisher
        self.rgb_bridge = CvBridge()
​

Color image callback function,

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def get_RGBImageCallBack(self,msg):
    #Use CvBridge to convert color image message data to image data
    rgb_image = self.rgb_bridge.imgmsg_to_cv2(msg, "bgr8")
    #Pass the obtained image to the defined findHolistic function, draw=False means not drawing joint points on the original color image
 Posture Detection
Facial Landmark Detection