Question

我已经使用伺服马达来倾斜以跟踪脸部但问题是伺服系统没有直接连接到覆盆子相反，我使用16通道adafruit pca9685来控制伺服器教授树莓派面部跟踪的所有教程均未使用此类渠道，因此我试图找出自己的实现方法

for frame in camera.capture_continuous(rawCapture, format = 'bgr', use_video_port = True):
        image = frame.array

        resized = cv2.resize(image, (320, 240))
        gray = cv2.cvtColor(resized,cv2.COLOR_BGR2GRAY)

        faces = face_cascade.detectMultiScale(gray, 1.1, 5)
        if len(faces) > 0:
            for (x, y, w, h) in faces:
                # Track(pan, tilt, Point(x + w/2.0, y+ h/2.0))
                break
        faces_resized = [(int(scale[0]*x), int(scale[1]*y), int(scale[0]*w), int(scale[1]*h)) for (x, y, w, h) in faces]
        for (x,y,w,h) in faces_resized:
            cv2.rectangle(image,(x,y),(x+w,y+h),(255,255,0),2)

对于这一部分，代码是绝对清晰的，可以很好地检测到人脸，但是我想使用它来跟踪和更改伺服电机的位置

我只需要实现它的代码我的adafruit板代码结构

            pwm.set_pwm(0, 0,cam_pan)
0 for index of channels 
0 min angle

cam_pan应该移动的角度

考虑到这些参数，我只想控制我的伺服/摆角的移动以相应地移动

我试图通过此方法控制电机

x = x + (w/2)
        y = y + (h/2)

        # Correct relative to center of image
        turn_x  = float(x - (FRAME_W/2))
        turn_y  = float(y - (FRAME_H/2))

        # Convert to percentage offset
        turn_x  /= float(FRAME_W/2)
        turn_y  /= float(FRAME_H/2)

        # Scale offset to degrees
    turn_x   = 2 # VFOV
    turn_y   = 2 # HFOV
    if x > turn_x:
        cam_pan  += -turn_x
        pwm.set_pwm(0, 0,cam_pan)
    elif x < turn_x:

        cam_pan  += +turn_x
        pwm.set_pwm(0, 0,cam_pan)

但伺服电机只是开始有点抽搐，这毫无用处

from picamera.array import PiRGBArray
from picamera import PiCamera
import time
import cv2
# from pisoc import *
import Adafruit_PCA9685
pwm = Adafruit_PCA9685.PCA9685()
FRAME_W = 180
FRAME_H = 100
cam_pan = 90
cam_tilt = 60

if __name__ == "__main__":

    camera = PiCamera()
    camera.resolution = (640, 480)
    camera.framerate = 32
    rawCapture = PiRGBArray(camera, size = camera.resolution)

    face_cascade = cv2.CascadeClassifier('/usr/local/share/OpenCV/lbpcascades/lbpcascade_frontalface.xml')

    scale = (camera.resolution[0]/320.0, camera.resolution[1]/240.0)

    time.sleep(0.1)

    for frame in camera.capture_continuous(rawCapture, format = 'bgr', use_video_port = True):
        image = frame.array

        resized = cv2.resize(image, (320, 240))
        gray = cv2.cvtColor(resized,cv2.COLOR_BGR2GRAY)

        faces = face_cascade.detectMultiScale(gray, 1.1, 5)
        if len(faces) > 0:
            for (x, y, w, h) in faces:
                # Track(pan, tilt, Point(x + w/2.0, y+ h/2.0))
                break
        faces_resized = [(int(scale[0]*x), int(scale[1]*y), int(scale[0]*w), int(scale[1]*h)) for (x, y, w, h) in faces]
        for (x,y,w,h) in faces_resized:
            cv2.rectangle(image,(x,y),(x+w,y+h),(255,255,0),2)
            # Track first face

            # Get the center of the face
            x = x + (w/2)
            y = y + (h/2)

            # Correct relative to center of image
            turn_x  = float(x - (FRAME_W/2))
            turn_y  = float(y - (FRAME_H/2))

            # Convert to percentage offset
            turn_x  /= float(FRAME_W/2)
            turn_y  /= float(FRAME_H/2)

            # Scale offset to degrees
        turn_x   = 2 # VFOV
        turn_y   = 2 # HFOV
        if x > turn_x:
            cam_pan  += -turn_x
            pwm.set_pwm(0, 0,cam_pan)
        elif x < turn_x:

            cam_pan  += +turn_x
            pwm.set_pwm(0, 0,cam_pan)
        # cam_tilt += turn_y


        # Clamp Pan/Tilt to 0 to 180 degrees
        # cam_pan = max(0,min(180,cam_pan))
        # cam_tilt = max(0,min(180,cam_tilt))

        # Update the servos
        # pwm.set_pwm(0, 0,cam_pan)

            # print(cam_pan-90, cam_tilt-90)
            #
            # # Clamp Pan/Tilt to 0 to 180 degrees
            # cam_pan = max(0,min(180,cam_pan))
            # # cam_tilt = max(0,min(180,cam_tilt))
            #
            # # Update the servos
            # pwm.set_pwm(0, 0,cam_pan)
            #
            # # pan(int(cam_pan-90))
            # # tilt(int(cam_tilt-90))

            break


        cv2.imshow("Result", image)
        key = cv2.waitKey(1) & 0xFF

        rawCapture.truncate(0)

        if key == ord('q') or key == 27:
            break

这是完整的代码

我不知道问题到底是什么我什至不确定问题是否出在代码部分但是我只想根据脸部改变

伺服电机无法正常使用倾斜仪进行面部跟踪

0 个答案: