基础知识(十三)dlib python人脸检测 特征点定位

import  cv2
import  dlib
import numpy as np
#根据人脸框bbox，从一张完整图片裁剪出人脸
def getface():
    bgrImg = cv2.imread('1.jpg')
    print bgrImg.shape
    rgbImg = cv2.cvtColor(bgrImg, cv2.COLOR_BGR2RGB)

    detector=dlib.get_frontal_face_detector()
    #img = io.imread('1.jpg')
    faces = detector(rgbImg, 1)
    if len(faces) > 0:
    face=max(faces, key=lambda rect: rect.width() * rect.height())
    [x1,x2,y1,y2]=[face.left(),face.right(),face.top(),face.bottom()]

人脸特征点定位:需要先从网上下载预训练模型

http://sourceforge.net/projects/dclib/files/dlib/v18.10/shape_predictor_68_face_landmarks.dat.bz2

import  dlib
#根据人脸框bbox，从一张完整图片裁剪出人脸,并保存问文件名cropimgname
#如果未检测到人脸,那么返回false,否则返回true
face_detector=dlib.get_frontal_face_detector()
landmark_predictor=dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")

def geteye_rect(imgpath):
	bgrImg = cv2.imread(imgpath)
	if bgrImg is None:
		return False
	rgbImg = cv2.cvtColor(bgrImg, cv2.COLOR_BGR2RGB)
	facesrect = face_detector(rgbImg, 1)
	if len(facesrect) <=0:
		return False

	for k, d in enumerate(facesrect):
		shape = landmark_predictor(rgbImg, d)
		for i in range(68):
			pt=shape.part(i)
			plt.plot(pt.x,pt.y,'ro')
		plt.imshow(rgbImg)
		plt.show()