注意点：

1. dlib.get_frontal_face_detector( ) 获取人脸检测器
2. dlib.shape_predictor( ) 预测人脸关键点

人脸关键点模型，下载地址：
http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2.

face_landmark_detection.py

# 1 加入库
import cv2
import matplotlib.pyplot as plt
import dlib

# 2 读取一张图片
image = cv2.imread("Tom2.jpeg")

# 3 调用人脸检测器
detector = dlib.get_frontal_face_detector()

# 4 加载预测关键点模型（68个关键点）
predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")

# 5 灰度转换
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# 6 人脸检测
faces = detector(gray, 1)

# 7 循环，遍历每一张人脸，给人脸绘制矩形框和关键点
for face in faces: #(x, y, w, h)
    # 8 绘制矩形框
    cv2.rectangle(image, (face.left(), face.top()), (face.right(), face.bottom()), (0,255,0), 5)

    # 9 预测关键点
    shape = predictor(image, face)

    # 10 获取到关键点坐标
    for pt in shape.parts():
        # 获取横纵坐标
        pt_position = (pt.x, pt.y)
        # 11 绘制关键点坐标
        cv2.circle(image, pt_position, 2, (0, 0, 255), -1)

# 12 显示整个效果图
plt.imshow(image)
plt.axis("off")
plt.show()

face_landmark_detection_video.py

# 1 加入库
import cv2
import dlib

# 2 打开摄像头
capture = cv2.VideoCapture(0)

# 3 获取人脸检测器
detector = dlib.get_frontal_face_detector()

# 4 获取人脸关键点检测模型
predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")

while True:
    # 5 读取视频流
    ret, frame = capture.read()
    # 6 灰度转换
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    # 7 人脸检测
    faces = detector(gray, 1)
    # 8 绘制每张人脸的矩形框和关键点
    for face in faces:
        # 8.1 绘制矩形框
        cv2.rectangle(frame, (face.left(), face.top()), (face.right(), face.bottom()), (0,255,0), 3)
        # 8.2 检测到关键点
        shape = predictor(gray, face)
        # 8.3 获取关键点的坐标
        for pt in shape.parts():
            # 每个点的坐标
            pt_position = (pt.x, pt.y)
            # 8.4 绘制关键点
            cv2.circle(frame, pt_position, 3, (255,0,0), -1)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
    # 9 显示效果
    cv2.imshow("face detection landmark", frame)
capture.release()
cv2.destroyAllWindows()

• 基于face_recognition进行人脸关键点检测

1. face_recognition 使用世界上最简单的人脸识别工具，它使用dlib最先进的人脸识别技术构建而成，并具有深度学习功能。

（1）Github 地址：https://github.com/ageitgey/face_recognition
（2）官方指南：
https://face-recognition.readthedocs.io/en/latest/readme.html
（3）源码实现：
https://face-recognition.readthedocs.io/en/latest/face_recognition.html
（4）安装：

pip install face_recognition

face_landmark_rg.py

# 1 加入库
import face_recognition
import cv2
import matplotlib.pyplot as plt

# 2 方法：显示图片
def show_image(image, title):
    plt.title(title)
    plt.imshow(image)
    plt.axis("off")

# 3 方法：绘制Landmars关键点
def show_landmarks(image, landmarks):
    for landmarks_dict in landmarks:
        for landmarks_key in landmarks_dict.keys():
            for point in landmarks_dict[landmarks_key]:
                cv2.circle(image, point, 2, (0,0,255), -1)
    return image
# 4 主函数
def main():
    # 5 读取图片
    image = cv2.imread("Tom.jpeg")
    # 6 图片灰度转换
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    # 7 调用face_recognition库中的方法：face_landmarks()
    face_marks = face_recognition.face_landmarks(gray, None, "large")
    print(face_marks)
    # 8 绘制关键点
    img_result = show_landmarks(image.copy(), face_marks)
    # 9 创建画布
    plt.figure(figsize=(9,6))
    plt.suptitle("Face Landmarks with face_recognition", fontsize=14, fontweight="bold")
    # 10 显示整体效果
    show_image(img_result, "landmarks")

    plt.show()

if __name__ == '__main__':
    main()