python采集⼈脸_python利⽤dlib获取⼈脸的68个landmark (1) 单⼈脸情况
import cv2
import dlib
path = "1.jpg"
img = cv2.imread(path)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
#⼈脸检测画框
detector = _frontal_face_detector()
# 获取⼈脸关键点检测器
predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")
#获取⼈脸框位置信息
dets = detector(gray, 1)#1表⽰采样(upsample)次数 0识别的⼈脸少点,1识别的多点,2识别的更多,⼩脸也可以识别
for face in dets:
shape = predictor(img, face) # 寻⼈脸的68个标定点
# 遍历所有点，打印出其坐标，并圈出来
for pt in shape.parts():
pt_pos = (pt.x, pt.y)
cv2.circle(img, pt_pos, 2, (0, 0, 255), 1)#img, center, radius, color, thickness
cv2.imshow("image", img)
cv2.waitKey(0)
cv2.destroyAllWindows()
(2) 多⼈脸情况
import cv2
import dlib
path1 = "zxc.jpg"
img = cv2.imread(path1)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
#⼈脸检测画框
detector = _frontal_face_detector()
# 获取⼈脸关键点检测器
predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")
python怎么读取dat文件
#获取⼈脸框位置信息
dets = detector(gray, 1)#1表⽰采样(upsample)次数 0识别的⼈脸少点,1识别的多点,2识别的更多,⼩脸也可以识别
for i in range(len(dets)):
shape = predictor(img, dets[i]) # 寻⼈脸的68个标定点
# 遍历所有点，打印出其坐标，并圈出来
for pt in shape.parts():
pt_pos = (pt.x, pt.y)
cv2.circle(img, pt_pos, 2, (0, 0, 255), 1)#img, center, radius, color, thickness
cv2.imshow("image", img)
cv2.waitKey(0)#等待键盘输⼊
cv2.destroyAllWindows()
(3) 获取电脑摄像头实时识别标定
import cv2
import dlib
import numpy as np
cap = cv2.VideoCapture(0)#打开笔记本的内置摄像头，若参数是视频⽂件路径则打开视频
cap.isOpened()
def key_points(img):
points_keys = []
PREDICTOR_PATH = "shape_predictor_68_face_landmarks.dat"
detector = _frontal_face_detector()
predictor = dlib.shape_predictor(PREDICTOR_PATH)
rects = detector(img,1)
for i in range(len(rects)):
landmarks = np.matrix([[p.x,p.y] for p in predictor(img,rects[i]).parts()])
for point in landmarks:
pos = (point[0,0],point[0,1])
points_keys.append(pos)
cv2.circle(img,pos,2,(255,0,0),-1)
return img
while(True):
ret, frame = ad()#按帧读取视频，ret,frame是ad()⽅法的两个返回值。其中ret是布尔值，如果读取帧是正确的则返回True，如果⽂件读取到结尾，它的返回值就为False。frame就是每⼀帧的图像，是个三维矩阵。
# gray = cv2.cvtColor(frame)
face_key = key_points(frame)
cv2.imshow('frame',face_key)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cv2.destroyAllWindows()#关闭所有图像窗⼝
以上就是本⽂的全部内容，希望对⼤家的学习有所帮助，也希望⼤家多多⽀持我们。本⽂标题: python利⽤dlib获取⼈脸的68个landmark

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