#使用一个int来表示编号为0~511的patch

#其中这个int的二进制编码(0b876543210)则为对应的9个位置的黑白颜色

# [8] [7] [6]

# [5] [4] [3]

# [2] [1] [0]

#其中白色是0，黑色是1

#所以：0(0b000000000)~511(0b111111111)表示

# | | |███|

# | | ~ |███| （全白～全黑）

# | | |███|

# 比如：

# ███

# █ █

# ███ 对应的二进制为0b111101111=496 所以编号为495

#维持一个二维矩阵存n×n个编号，组成一幅细分后的二维码图

# 校准图案中心位置表(Alignment Pattern Locations Table)

#From http://www.thonky.com/qr-code-tutorial/alignment-pattern-locations

APLT=[

[], #version 0

[],

[6,18],

[6,22],

[6,26],

[6,30], #version 5

[6,34],

[6,22,38],

[6,24,42],

[6,26,46],

[6,28,50], #version 10

[6,30,54],

[6,32,58],

[6,34,62],

[6,26,46,66],

[6,26,48,70], #version 15

[6,26,50,74],

[6,30,54,78],

[6,30,56,82],

[6,30,58,86],

[6,34,62,90], #version 20

[6,28,50,72,94],

[6,26,50,74,98],

[6,30,54,78,102],

[6,28,54,80,106],

[6,32,58,84,110], #version 25

[6,30,58,86,114],

[6,34,62,90,118],

[6,26,50,74,98,122],

[6,30,54,78,102,126],

[6,26,52,78,104,130], #version 30

[6,30,56,82,108,134],

[6,34,60,86,112,138],

[6,30,58,86,114,142],

[6,34,62,90,118,146],

[6,30,54,78,102,126,150],#version 35

[6,24,50,76,102,128,154],

[6,28,54,80,106,132,158],

[6,32,58,84,110,136,162],

[6,26,54,82,110,138,166],

[6,30,58,86,114,142,170],#version 40

]

Rval=None

# 构造函数

def __init__(self,mat=None):

self.Length=0

self.Img=None

self.Mat=mat

if mat!=None:

self.setMat(mat)

pass

# 设置编号二维矩阵

def setMat(self, mat):

# 计算边长

self.Length=len(mat)

self.Mat=mat

self.Img=None

pass

# 生成图像

def makeImage(self):

#图片对象

self.Img=Image.new("1",(self.Length*3,self.Length*3))

for r in range(self.Length):

#对于每一行编号处理

for c in range(self.Length):

#对于每一个编号处理

sn=self.Mat[r][c]

if(sn>511):

print("[Error] In VQRPatch: Serial Number List Overflow!")

return -1

bStr=bin(sn)[2:]

#补全9位

while len(bStr)<9:

bStr='0'+bStr

#写入像素数据

startPointX=c*3

startPointY=r*3

bIndex=0

for y in range(3):

for x in range(3):

if bStr[bIndex]=='0':

#white

self.Img.putpixel((startPointX+x,startPointY+y),1)

else:

#black

self.Img.putpixel((startPointX+x,startPointY+y),0)

bIndex=bIndex+1

pass

def resizeImage(self,length):

if self.Img==None:

self.makeImage()

print("[VQRPatch] Resize to %sx%s" %(length,length))

self.Img=self.Img.resize((length,length))

pass

# 保存到文件

def saveImage(self,filepath):

if self.Img==None:

self.makeImage()

print("[VQRPatch] Save Image to %s" %(filepath))

self.Img.save(filepath)

pass

def addQRModules(self,Vdat):

modules=Vdat.CodeMat

## 增加位置探测图形(Position Detection Pattern) ##

#左上角

startPointR=0

startPointC=0

for r in range(8):

for c in range(8):

if modules[startPointR+r][startPointC+c]==1:

#black

self.Mat[startPointR+r][startPointC+c]=511

else:

#white

self.Mat[startPointR+r][startPointC+c]=0

#右上角

startPointR=0

startPointC=self.Length-1

for r in range(8):

for c in range(8):

if modules[startPointR+r][startPointC-c]==1:

#black

self.Mat[startPointR+r][startPointC-c]=511

else:

#white

self.Mat[startPointR+r][startPointC-c]=0

#左下角

startPointR=self.Length-1

startPointC=0

for r in range(8):

for c in range(8):

if modules[startPointR-r][startPointC+c]==1:

#black

self.Mat[startPointR-r][startPointC+c]=511

else:

#white

self.Mat[startPointR-r][startPointC+c]=0

## 增加对齐图形(Timing Pattern) ##

r=6

for c in range(self.Length):

if modules[r][c]==1:

#black

self.Mat[r][c]=511

else:

#white

self.Mat[r][c]=0

c=6

for r in range(self.Length):

if modules[r][c]==1:

#black

self.Mat[r][c]=511

else:

#white

self.Mat[r][c]=0

## 增加校准图形(Alignment Patterns) ##

v=Vdat.Version

APL=VQRPatch.APLT[v]

for centerR in APL:

for centerC in APL:

# foreach Alignment Patterns center(5*5)

for r in range(-2,3):

for c in range(-2,3):

if modules[centerR+r][centerC+c]==1:

#black

self.Mat[centerR+r][centerC+c]=511

else:

#white

self.Mat[centerR+r][centerC+c]=0

## 格式信息(Formation Information) ##

#左上

r=8

for c in range(9):

if modules[r][c]==1:

#black

self.Mat[r][c]=511

else:

#white

self.Mat[r][c]=0

c=8

for r in range(9):

if modules[r][c]==1:

#black

self.Mat[r][c]=511

else:

#white

self.Mat[r][c]=0

#右上

r=8

for c in range(self.Length-8,self.Length):

if modules[r][c]==1:

#black

self.Mat[r][c]=511

else:

#white

self.Mat[r][c]=0

#左下

c=8

for r in range(self.Length-8,self.Length):

if modules[r][c]==1:

#black

self.Mat[r][c]=511

else:

#white

self.Mat[r][c]=0

## 版本信息(Version Information) ##

#右上

for r in range(0,7):

for c in range(self.Length-11, self.Length-8):

if modules[r][c]==1:

#black

self.Mat[r][c]=511

else:

#white

self.Mat[r][c]=0

#左下

for r in range(self.Length-11,self.Length-8):

for c in range(0,7):

if modules[r][c]==1:

#black

self.Mat[r][c]=511

else:

#white

self.Mat[r][c]=0

pass

# 静态方法，求一个编号为sn的patch的可靠性，即P={pi=(Ipi,Cpi,ri)|i=0..512}中的ri

@staticmethod

def getReliability(SerialNumber):

if VQRPatch.Rval==None:

# first access, read database file

f=open("./PatchReliability.dat","rb")

VQRPatch.Rval= pickle.load(f)

f.close()

print("[VQRPatch] Done Loading Reliability Data")

return VQRPatch.Rval[SerialNumber]

pass

# 静态方法，求一个知道sn的patch的中心方块颜色

@staticmethod

def getCenterColor(SerialNumber):

bStr=bin(SerialNumber)[2:]

if(len(bStr)<5):

return 0

else:

for i in range(512):

li=[[i]]

vp=VQRPatch(li)

vp.makeImage()

vp.resizeImage(size)

vp.saveImage(dirpath+str(i)+".png")

size=512

ssimMap=[]

genAllPatches("./patches/",3)

for i in range(size):

imA=Image.open("./patches/"+str(i)+".png")

row=[]

for j in range(size):

imB=Image.open("./patches/"+str(j)+".png")

simVal=ssim.compute_ssim(imA,imB)

print("(%s %s): %s" %(i,j,simVal))

row.append(simVal)

ssimMap.append(row)

f=open("./PatchSSIM.dat","wb")

pickle.dump(ssimMap,f)

f.close()