使用dlib人脸关键点检测实现摄像头眼球和嘴巴内部轮廓彩色图片的代码

以下是使用dlib库进行人脸关键点检测，并获取眼球和嘴巴内部轮廓的彩色图片的代码示例：

import cv2
import dlib
import numpy as np

# 加载dlib的人脸检测器和关键点检测器
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor('shape_predictor_68_face_landmarks.dat')

# 读取摄像头
cap = cv2.VideoCapture(0)

while True:
    # 读取一帧图像
    ret, frame = cap.read()
    if not ret:
        break

    # 转换为灰度图像
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # 使用dlib的人脸检测器检测人脸
    faces = detector(gray)

    # 遍历检测到的人脸
    for face in faces:
        # 使用dlib的关键点检测器检测人脸关键点
        landmarks = predictor(gray, face)

        # 获取眼球和嘴巴内部轮廓的关键点坐标
        left_eye = np.array([(landmarks.part(36).x, landmarks.part(36).y),
                             (landmarks.part(37).x, landmarks.part(37).y),
                             (landmarks.part(38).x, landmarks.part(38).y),
                             (landmarks.part(39).x, landmarks.part(39).y),
                             (landmarks.part(40).x, landmarks.part(40).y),
                             (landmarks.part(41).x, landmarks.part(41).y)], np.int32)
        right_eye = np.array([(landmarks.part(42).x, landmarks.part(42).y),
                              (landmarks.part(43).x, landmarks.part(43).y),
                              (landmarks.part(44).x, landmarks.part(44).y),
                              (landmarks.part(45).x, landmarks.part(45).y),
                              (landmarks.part(46).x, landmarks.part(46).y),
                              (landmarks.part(47).x, landmarks.part(47).y)], np.int32)
        mouth = np.array([(landmarks.part(48).x, landmarks.part(48).y),
                          (landmarks.part(49).x, landmarks.part(49).y),
                          (landmarks.part(50).x, landmarks.part(50).y),
                          (landmarks.part(51).x, landmarks.part(51).y),
                          (landmarks.part(52).x, landmarks.part(52).y),
                          (landmarks.part(53).x, landmarks.part(53).y),
                          (landmarks.part(54).x, landmarks.part(54).y),
                          (landmarks.part(55).x, landmarks.part(55).y),
                          (landmarks.part(56).x, landmarks.part(56).y),
                          (landmarks.part(57).x, landmarks.part(57).y),
                          (landmarks.part(58).x, landmarks.part(58).y),
                          (landmarks.part(59).x, landmarks.part(59).y),
                          (landmarks.part(60).x, landmarks.part(60).y),
                          (landmarks.part(61).x, landmarks.part(61).y),
                          (landmarks.part(62).x, landmarks.part(62).y),
                          (landmarks.part(63).x, landmarks.part(63).y),
                          (landmarks.part(64).x, landmarks.part(64).y),
                          (landmarks.part(65).x, landmarks.part(65).y),
                          (landmarks.part(66).x, landmarks.part(66).y),
                          (landmarks.part(67).x, landmarks.part(67).y)], np.int32)

        # 使用关键点坐标绘制眼球和嘴巴内部轮廓的多边形
        cv2.fillPoly(frame, [left_eye], (0, 255, 0))
        cv2.fillPoly(frame, [right_eye], (0, 255, 0))
        cv2.fillPoly(frame, [mouth], (0, 0, 255))

    # 显示图像
    cv2.imshow('frame', frame)

    # 按下q键退出程序
    if cv2.waitKey(1) == ord('q'):
        break

# 释放摄像头和窗口
cap.release()
cv2.destroyAllWindows()

需要注意的是，在运行代码之前，需要先下载dlib的人脸关键点检测器模型文件shape_predictor_68_face_landmarks.dat，并将其放在与代码文件相同的目录下，才能正确运行。