Welcome to MicroROS Robot repository

Face recognition tracking

Note: The VM and ROS-wifi image transfer module must be consistent with the microROS control board ROS_DOMAIN_ID and set the value to 20. You can check [MicroROS control board Parameter configuration] to set the microROS control board ROS_DOMAIN_ID. Check the tutorial Connecting to MicroROS Agents to see if the ids are the same.

1、Program specification

After running the program, when the face is displayed in the picture, when there is a box surrounding the face, the PTZ camera will follow the movement of the face and move.

2、Operation procedure

Program code reference path：

/home/yahboom/yahboomcar_ws/src/yahboom_esp32ai_car/yahboom_esp32ai_car/face_fllow.py

2.1、Start command

After entering the docker container, enter the terminal according to the actual vehicle type

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ros2 run yahboom_esp32ai_car face_fllow  

If the Angle of the camera is not at this Angle, please press CTRL+C to end the program and run again, this is because the network delay causes the Angle of sending the steering gear to lose packets

** If the camera picture image appears upside down , you need to see 3. Camera picture correction (must see)** document itself correction, the experiment is no longer described.

After the program starts, the following camera screen will appear，

When the face is recognized, the box is selected, and the two-dimensional head moves with the face, and the terminal prints the moving Angle

2.2、Dynamic parameter regulation

terminal input，

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ros2 run rqt_reconfigure rqt_reconfigure

After modifying the parameters, click the blank area of the GUI to write the parameter value. As can be seen from the figure above，

• faceTracker The main adjustment PID three parameters to make the head more sensitive

3、Core code

3.1、face_fllow .py

The principle of functional implementation is similar to that of object tracking, which is to calculate the rotation Angle of the steering gear according to the central coordinates of the target, and then release it to the chassis, and part of the code is put under,

​x

 cv.putText(frame, text, (20, 30), cv.FONT_HERSHEY_SIMPLEX, 0.9, (0, 0, 255), 1)
        face_patterns = cv2.CascadeClassifier('/home/yahboom/yahboomcar_ws/src/yahboom_esp32ai_car/yahboom_esp32ai_car/haarcascade_frontalface_default.xml')
        faces = face_patterns.detectMultiScale(frame , scaleFactor=1.1, minNeighbors=5, minSize=(100, 100))
        if len(faces)>0:
            for (x, y, w, h) in faces:
                m=x
                n=y
                cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
            self.execute(m,n)


 [x_Pid, y_Pid] = self.PID_controller.update([point_x - 320, point_y - 240])
        if self.img_flip == True:
            self.PWMServo_X += x_Pid
            self.PWMServo_Y += y_Pid
        else:
            self.PWMServo_X  -= x_Pid
            self.PWMServo_Y  += y_Pid

        if self.PWMServo_X  >= 40:
            self.PWMServo_X  = 40
        elif self.PWMServo_X  <= -40:
            self.PWMServo_X  = -40
        if self.PWMServo_Y >= 40:
            self.PWMServo_Y = 40
        elif self.PWMServo_Y <= -90:
            self.PWMServo_Y = -90