树莓派上利用python+opencv+dlib实现嘴唇检测的实现

pip3 install opencv-python

pip3 install numpy

pip3 install cmake
pip3 install dlib

from gpiozero import LED
from time import sleep
from subprocess import check_call
import cv2
import numpy as np
import dlib

print(cv2.__version__)
def search_cap_num():
    for i in range(2000):
        cap = cv2.VideoCapture(i)
        cap_opened = cap.isOpened()
        if cap_opened == True:
            return i
        
cap_num = search_cap_num()
cap = cv2.VideoCapture(cap_num)

detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")

# 规定上嘴唇和下嘴唇连线的路径
lip_order_dlib = np.array([[48, 49, 50, 51, 52, 53, 54, 64, 63, 62, 61, 60, 48],
                           [48, 59, 58, 57, 56, 55, 54, 64, 65, 66, 67, 60, 48]]) - 48
lip_order_num = lip_order_dlib.shape[1]

while 1:
    landmarks_lip = []
    ret, frame = cap.read()
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    rects = detector(gray, 1)
    print('faces number:' + str(len(rects)))
    for (i, rect) in enumerate(rects):
        # 标记人脸中的68个landmark点
        landmarks = predictor(gray, rect)  
        for n in range(48, 68):
            x = landmarks.part(n).x
            y = landmarks.part(n).y
            landmarks_lip.append((x, y))
            # cv2.circle(img=img, center=(x, y), radius=3, color=(0, 255, 0), thickness=-1)
        for m in range(lip_order_num-1):
            cv2.line(frame, landmarks_lip[lip_order_dlib[0][m]], landmarks_lip[lip_order_dlib[0][m+1]], color=(0, 255, 0), thickness=2, lineType=8)
        for n in range(lip_order_num-1):
            cv2.line(frame, landmarks_lip[lip_order_dlib[1][n]], landmarks_lip[lip_order_dlib[1][n+1]], color=(0, 255, 0), thickness=2, lineType=8)
    cv2.imshow("face", frame)
    if cv2.waitKey(1) & 0xff == ord('q'):
        break
cap.release()
cv2.destroyAllWindows()
# check_call(['sudo', 'poweroff'])