python视觉识别坐标_Python根据双眼的坐标对齐人脸

最近要做一个人脸识别的东西，可数据库的人脸图像还没有做对齐处理。所以需要自己做人脸对齐预处理。网上查了，发现已经有人做过了类似的脚本。直接拿过来用了，原地址在这：https://github.com/bytefish/facerec/blob/master/py/apps/scripts/crop_face.py   自己为了以后更改，加了一些注释。

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

"""

Created on Thu Jan 1 16:09:32 2015

@author: crw

"""

# 参数含义：

# CropFace(image, eye_left, eye_right, offset_pct, dest_sz)

# eye_left is the position of the left eye

# eye_right is the position of the right eye

# 比例的含义为：要保留的图像靠近眼镜的百分比，

# offset_pct is the percent of the image you want to keep next to the eyes (horizontal, vertical direction)

# 最后保留的图像的大小。

# dest_sz is the size of the output image

#

import sys,math,Image

# 计算两个坐标的距离

def Distance(p1,p2):

dx = p2[0]- p1[0]

dy = p2[1]- p1[1]

return math.sqrt(dx*dx+dy*dy)

# 根据参数，求仿射变换矩阵和变换后的图像。

def ScaleRotateTranslate(image, angle, center =None, new_center =None, scale =None, resample=Image.BICUBIC):

if (scale is None)and (center is None):

return image.rotate(angle=angle, resample=resample)

nx,ny = x,y = center

sx=sy=1.0

if new_center:

(nx,ny) = new_center

if scale:

(sx,sy) = (scale, scale)

cosine = math.cos(angle)

sine = math.sin(angle)

a = cosine/sx

b = sine/sx

c = x-nx*a-ny*b

d =-sine/sy

e = cosine/sy

f = y-nx*d-ny*e

return image.transform(image.size, Image.AFFINE, (a,b,c,d,e,f), resample=resample)

# 根据所给的人脸图像，眼睛坐标位置，偏移比例，输出的大小，来进行裁剪。

def CropFace(image, eye_left=(0,0), eye_right=(0,0), offset_pct=(0.2,0.2), dest_sz = (70,70)):

# calculate offsets in original image 计算在原始图像上的偏移。

offset_h = math.floor(float(offset_pct[0])*dest_sz[0])

offset_v = math.floor(float(offset_pct[1])*dest_sz[1])

# get the direction 计算眼睛的方向。

eye_direction = (eye_right[0]- eye_left[0], eye_right[1]- eye_left[1])

# calc rotation angle in radians 计算旋转的方向弧度。

rotation =-math.atan2(float(eye_direction[1]),float(eye_direction[0]))

# distance between them # 计算两眼之间的距离。

dist = Distance(eye_left, eye_right)

# calculate the reference eye-width 计算最后输出的图像两只眼睛之间的距离。

reference = dest_sz[0]-2.0*offset_h

# scale factor # 计算尺度因子。

scale =float(dist)/float(reference)

# rotate original around the left eye # 原图像绕着左眼的坐标旋转。

image = ScaleRotateTranslate(image, center=eye_left, angle=rotation)

# crop the rotated image # 剪切

crop_xy = (eye_left[0]- scale*offset_h, eye_left[1]- scale*offset_v) # 起点

crop_size = (dest_sz[0]*scale, dest_sz[1]*scale) # 大小

image = image.crop((int(crop_xy[0]),int(crop_xy[1]),int(crop_xy[0]+crop_size[0]),int(crop_xy[1]+crop_size[1])))

# resize it 重置大小

image = image.resize(dest_sz, Image.ANTIALIAS)

return image

if __name__ =="__main__":

image = Image.open("/media/crw/DataCenter/Dataset/CAS-PEAL-R1/POSE/000001/MY_000001_IEU+00_PD-22_EN_A0_D0_T0_BB_M0_R1_S0.tif")

leftx =117

lefty=287

rightx=187

righty= 288

CropFace(image, eye_left=(leftx,lefty), eye_right=(rightx,righty), offset_pct=(0.1,0.1), dest_sz=(200,200)).save("test_10_10_200_200.jpg")

CropFace(image, eye_left=(leftx,lefty), eye_right=(rightx,righty), offset_pct=(0.2,0.2), dest_sz=(200,200)).save("test_20_20_200_200.jpg")

CropFace(image, eye_left=(leftx,lefty), eye_right=(rightx,righty), offset_pct=(0.3,0.3), dest_sz=(200,200)).save("test_30_30_200_200.jpg")

CropFace(image, eye_left=(leftx,lefty), eye_right=(rightx,righty), offset_pct=(0.4,0.4), dest_sz=(200,200)).save("test_40_40_200_200.jpg")

CropFace(image, eye_left=(leftx,lefty), eye_right=(rightx,righty), offset_pct=(0.45,0.45), dest_sz=(200,200)).save("test_45_45_200_200.jpg")

CropFace(image, eye_left=(leftx,lefty), eye_right=(rightx,righty), offset_pct=(0.2,0.2)).save("test_20_20_70_70.jpg")

程序的结果：(图片采用Cas-Peal 数据库)