通过人脸关键点实现眼睛和嘴巴识别代码

以下是使用Python和OpenCV库实现通过人脸关键点实现眼睛和嘴巴识别的示例代码：

import cv2

# 加载人脸检测器和关键点检测器
face_detector = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
keypoint_detector = cv2.face.createFacemarkLBF()
keypoint_detector.loadModel("lbfmodel.yaml")

# 打开摄像头
cap = cv2.VideoCapture(0)

while True:
    ret, frame = cap.read()
    if not ret:
        break

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

    # 检测人脸
    faces = face_detector.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5)

    # 检测人脸关键点
    ok, keypoints = keypoint_detector.fit(gray, faces)

    # 绘制人脸关键点
    for i, face_keypoints in enumerate(keypoints):
        for x, y in face_keypoints[0]:
            cv2.circle(frame, (x, y), 1, (0, 255, 0), -1)

        # 根据人脸关键点定位眼睛和嘴巴
        left_eye = face_keypoints[0][36:42]
        right_eye = face_keypoints[0][42:48]
        mouth = face_keypoints[0][48:68]

        # 计算眼睛和嘴巴的状态
        left_eye_open = is_eye_open(left_eye)
        right_eye_open = is_eye_open(right_eye)
        mouth_open = is_mouth_open(mouth)

        # 根据状态绘制不同的框和文本
        if left_eye_open and right_eye_open:
            cv2.rectangle(frame, (faces[i][0], faces[i][1]), (faces[i][0]+faces[i][2], faces[i][1]+faces[i][3]), (0, 255, 0), 2)
            cv2.putText(frame, "Eyes open", (faces[i][0], faces[i][1] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
        else:
            cv2.rectangle(frame, (faces[i][0], faces[i][1]), (faces[i][0]+faces[i][2], faces[i][1]+faces[i][3]), (0, 0, 255), 2)
            cv2.putText(frame, "Eyes closed", (faces[i][0], faces[i][1] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)

        if mouth_open:
            cv2.rectangle(frame, (faces[i][0], faces[i][1]), (faces[i][0]+faces[i][2], faces[i][1]+faces[i][3]), (0, 255, 0), 2)
            cv2.putText(frame, "Mouth open", (faces[i][0], faces[i][1] + faces[i][3] + 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
        else:
            cv2.rectangle(frame, (faces[i][0], faces[i][1]), (faces[i][0]+faces[i][2], faces[i][1]+faces[i][3]), (0, 0, 255), 2)
            cv2.putText(frame, "Mouth closed", (faces[i][0], faces[i][1] + faces[i][3] + 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)

    cv2.imshow("frame", frame)
    if cv2.waitKey(1) == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

上述代码中使用了`haarcascade_frontalface_default.xml`和`lbfmodel.yaml`文件，分别用于人脸检测和人脸关键点检测。在绘制人脸关键点时，使用了`cv2.circle`函数绘制圆形，并根据关键点的位置和状态绘制不同的框和文本。具体的眼睛和嘴巴状态计算函数`is_eye_open`和`is_mouth_open`可以自行实现。