opencv+python+dlib人脸关键点检测、实时检测

安装的是anaconde3、python3.7.3，3.7环境安装dlib太麻烦， 

在anaconde3中新建环境python3.6.8，

在3.6环境下安装dlib-19.6.1-cp36-cp36m-win_amd64.whl，下载地址：https://pypi.org/project/dlib/19.6.1/#files

vscode更改配置

其中shape_predictor_68_face_landmarks.dat官方训练数据下载地址:http://dlib.net/files/，里面还有5点模型。

效果图如下：

# _*_ coding:utf-8 _*_

import numpy as np
import cv2
import dlib

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

# cv2读取图像
img = cv2.imread("img/test3.jpg")

# 取灰度
img_gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)

# 人脸数rects
rects = detector(img_gray, 0)
for i in range(len(rects)):
    landmarks = np.matrix([[p.x, p.y] for p in predictor(img, rects[i]).parts()])
    for idx, point in enumerate(landmarks):
        # 68点的坐标
        pos = (point[0, 0], point[0, 1])

        # 利用cv2.circle给每个特征点画一个圈，共68个
        cv2.circle(img, pos, 2, color=(0, 255, 0))
        # 利用cv2.putText输出1-68
        font = cv2.FONT_HERSHEY_SIMPLEX
        cv2.putText(img, str(idx + 1), None, font, 0.8, (0, 0, 255), 1, cv2.LINE_AA)

cv2.namedWindow("img", 2)
cv2.imshow("img", img)
cv2.waitKey(0)

　摄像头实时检测：

# _*_ coding:utf-8 _*_

import numpy as np
import cv2
import dlib

cap = cv2.VideoCapture(0)
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor("data/shape_predictor_68_face_landmarks.dat")

while 1:
    ret, img = cap.read()
    # 取灰度
    img_gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
    # 人脸数rects
    rects = detector(img_gray, 0)
    for i in range(len(rects)):
        landmarks = np.matrix([[p.x, p.y] for p in predictor(img, rects[i]).parts()])
        for idx, point in enumerate(landmarks):
            # 68点的坐标
            pos = (point[0, 0], point[0, 1])

            # 利用cv2.circle给每个特征点画一个圈，共68个
            cv2.circle(img, pos, 2, color=(0, 255, 0))
            # 利用cv2.putText输出1-68
            font = cv2.FONT_HERSHEY_SIMPLEX
            cv2.putText(img, str(idx + 1), None, font, 0.8, (0, 0, 255), 1, cv2.LINE_AA)

    cv2.namedWindow("img", 2)
    cv2.imshow("img", img)
    if cv2.waitKey(1) & 0xFF == ord("q"):
        break