人脸对齐

import cv2

import numpy

# 参考链接 https://blog.csdn.net/otengyue/article/details/79278572
import numpy as np

nor_coord5point = [[0.31556875000000000,0.4615741071428571],
                   [0.68262291666666670,0.4615741071428571],
                   [0.50026249999999990,0.6405053571428571],
                   [0.34947187500000004,0.8246919642857142],
                   [0.65343645833333330,0.8246919642857142]]

imgSize = [160, 160] #(w,h)

coord5point = np.multiply(nor_coord5point,imgSize)


# 人脸关键点 left eye ,right eye, nose , left mouse,right mouse
face_landmarks = [[51, 78],
                [100, 87],
                [71, 107],
                [46, 125],
                [80, 130],]



def transformation_from_points(points1, points2):
    points1 = points1.astype(numpy.float64)
    points2 = points2.astype(numpy.float64)
    c1 = numpy.mean(points1, axis=0)
    c2 = numpy.mean(points2, axis=0)
    points1 -= c1
    points2 -= c2
    s1 = numpy.std(points1)
    s2 = numpy.std(points2)
    points1 /= s1
    points2 /= s2
    U, S, Vt = numpy.linalg.svd(points1.T * points2)
    R = (U * Vt).T
    return numpy.vstack([numpy.hstack(((s2 / s1) * R,c2.T - (s2 / s1) * R * c1.T)),numpy.matrix([0., 0., 1.])])

def warp_im(img_im, orgi_landmarks,tar_landmarks):
    pts1 = numpy.float64(numpy.matrix([[point[0], point[1]] for point in orgi_landmarks]))
    pts2 = numpy.float64(numpy.matrix([[point[0], point[1]] for point in tar_landmarks]))
    M = transformation_from_points(pts1, pts2)
    dst = cv2.warpAffine(img_im, M[:2], (img_im.shape[1], img_im.shape[0]))
    return dst

def main():
    img_im = cv2.imread("./33.jpg")
    cv2.imshow('affine_img_im', img_im)
    dst = warp_im(img_im, face_landmarks, coord5point)
    cv2.imshow('affine', dst)
    # crop_im = dst[0:imgSize[0], 0:imgSize[1]]
    # cv2.imshow('affine_crop_im', crop_im)
if __name__=='__main__':
    main()
    cv2.waitKey()
    pass