-
import os, sys, pdb, numpy
-
from PIL import Image,ImageChops,ImageOps,ImageDraw
-
-
#parameters used for the CVPR paper
-
NCROPS = 10
-
NHOMO = 8
-
JPG=[70,50,30]
-
ROTS = [3,6,9,12,15]
-
SCALES=[1.5**0.5,1.5,1.5**1.5,1.5**2,1.5**2.5]
-
#parameters computed on ILSVRC10 dataset
-
lcolor = [ 381688.61379382 , 4881.28307136, 2316.10313483]
-
pcolor = [[-0.57848371, -0.7915924, 0.19681989],
-
[-0.5795621 , 0.22908373, -0.78206676],
-
[-0.57398987 , 0.56648223 , 0.59129816]]
-
-
#pre-generated gaussian values
-
alphas = [[0.004894 , 0.153527, -0.012182],
-
[-0.058978, 0.114067, -0.061488],
-
[0.002428, -0.003576, -0.125031]]
-
-
def gen_colorimetry(i):
-
p1r = pcolor[0][0]
-
p1g = pcolor[1][0]
-
p1b = pcolor[2][0]
-
p2r = pcolor[0][1]
-
p2g = pcolor[1][1]
-
p2b = pcolor[2][1]
-
p3r = pcolor[0][2]
-
p3g = pcolor[1][2]
-
p3b = pcolor[2][2]
-
-
l1 = numpy.sqrt(lcolor[0])
-
l2 = numpy.sqrt(lcolor[1])
-
l3 = numpy.sqrt(lcolor[2])
-
-
if i<=3:
-
alpha = alphas[i]
-
else:
-
numpy.random.seed(i*3)
-
alpha = numpy.random.randn(3,0,0.01)
-
a1 = alpha[0]
-
a2 = alpha[1]
-
a3 = alpha[2]
-
-
return (a1*l1*p1r + a2*l2*p2r + a3*l3*p3r,
-
a1*l1*p1g + a2*l2*p2g + a3*l3*p3g,
-
a1*l1*p1b + a2*l2*p2b + a3*l3*p3b)
-
-
def gen_crop(i,w,h):
-
numpy.random.seed(4*i)
-
x0 = numpy.random.random()*(w/4)
-
y0 = numpy.random.random()*(h/4)
-
x1 = w - numpy.random.random()*(w/4)
-
y1 = h - numpy.random.random()*(h/4)
-
-
return (int(x0),int(y0),int(x1),int(y1))
-
-
def gen_homo(i,w,h):
-
if i==0:
-
return (0,0,int(0.125*w),h,int(0.875*w),h,w,0)
-
elif i==1:
-
return (0,0,int(0.25*w),h,int(0.75*w),h,w,0)
-
elif i==2:
-
return (0,int(0.125*h),0,int(0.875*h),w,h,w,0)
-
elif i==3:
-
return (0,int(0.25*h),0,int(0.75*h),w,h,w,0)
-
elif i==4:
-
return (int(0.125*w),0,0,h,w,h,int(0.875*w),0)
-
elif i==5:
-
return (int(0.25*w),0,0,h,w,h,int(0.75*w),0)
-
elif i==6:
-
return (0,0,0,h,w,int(0.875*h),w,int(0.125*h))
-
elif i==7:
-
return (0,0,0,h,w,int(0.75*h),w,int(0.25*h))
-
else:
-
assert False
-
-
-
def rot(image,angle,fname):
-
white = Image.new('L',image.size,"white")
-
wr = white.rotate(angle,Image.NEAREST,expand=0)
-
im = image.rotate(angle,Image.BILINEAR,expand=0)
-
try:
-
image.paste(im,wr)
-
except ValueError:
-
print >>sys.stderr, 'error: image do not match '+fname
-
return image
-
-
def gen_corner(n, w, h):
-
x0 = 0
-
x1 = w
-
y0 = 0
-
y1 = h
-
-
rat = 256 - 227
-
-
if n == 0: #center
-
x0 = (rat*w)/(2*256.0)
-
y0 = (rat*h)/(2*256.0)
-
x1 = w - (rat*w)/(2*256.0)
-
y1 = h - (rat*h)/(2*256.0)
-
elif n == 1:
-
x0 = (rat*w)/256.0
-
y0 = (rat*h)/256.0
-
elif n == 2:
-
x1 = w - (rat*w)/256.0
-
y0 = (rat*h)/256.0
-
elif n == 3:
-
x1 = w - (rat*w)/256.0
-
y1 = h - (rat*h)/256.0
-
else:
-
assert n==4
-
x0 = (rat*w)/256.0
-
y1 = h - (rat*h)/256.0
-
-
return (int(x0),int(y0),int(x1),int(y1))
-
-
#the main fonction to call
-
#takes a image input path, a transformation and an output path and does the transformation
-
def gen_trans(imgfile,trans,outfile):
-
for trans in trans.split('*'):
-
image = Image.open(imgfile)
-
w,h = image.size
-
if trans=="plain":
-
image.save(outfile,"JPEG",quality=100)
-
elif trans=="flip":
-
ImageOps.mirror(image).save(outfile,"JPEG",quality=100)
-
elif trans.startswith("crop"):
-
c = int(trans[4:])
-
image.crop(gen_crop(c,w,h)).save(outfile,"JPEG",quality=100)
-
elif trans.startswith("homo"):
-
c = int(trans[4:])
-
image.transform((w,h),Image.QUAD,
-
gen_homo(c,w,h),
-
Image.BILINEAR).save(outfile,"JPEG",quality=100)
-
elif trans.startswith("jpg"):
-
image.save(outfile,quality=int(trans[3:]))
-
elif trans.startswith("scale"):
-
scale = SCALES[int(trans.replace("scale",""))]
-
image.resize((int(w/scale),int(h/scale)),Image.BILINEAR).save(outfile,"JPEG",quality=100)
-
elif trans.startswith('color'):
-
(dr,dg,db) = gen_colorimetry(int(trans[5]))
-
table = numpy.tile(numpy.arange(256),(3))
-
table[ :256]+= (int)(dr)
-
table[256:512]+= (int)(dg)
-
table[512: ]+= (int)(db)
-
image.convert("RGB").point(table).save(outfile,"JPEG",quality=100)
-
elif trans.startswith('rot-'):
-
angle =int(trans[4:])
-
for i in range(angle):
-
image = rot(image,-1,outfile)
-
image.save(outfile,"JPEG",quality=100)
-
elif trans.startswith('rot'):
-
angle =int(trans[3:])
-
for i in range(angle):
-
image = rot(image,1,outfile)
-
image.save(outfile,"JPEG",quality=100)
-
elif trans.startswith('corner'):
-
i = int(trans[6:])
-
image.crop(gen_corner(i,w,h)).save(outfile,"JPEG",quality=100)
-
else:
-
assert False, "Unrecognized transformation: "+trans
-
imgfile = outfile # in case we iterate
-
-
-
#Our 41 transformations used in the CVPR paper
-
def get_all_trans():
-
# transformations = (["plain","flip"]
-
# # +["crop%d"%i for i in range(NCROPS)]
-
# # +["homo%d"%i for i in range(NHOMO)]
-
# +["jpg%d"%i for i in JPG]
-
# +["scale0","scale1","scale2","scale3","scale4"]
-
# +["color%d"%i for i in range(3)]
-
# # +["rot-%d"%i for i in ROTS]
-
# # +["rot%d"%i for i in ROTS]
-
# )+["scale0","scale1","scale2","scale3","scale4"]
-
transformations=(["plain"]
-
+ ["jpg%d" % i for i in JPG]
-
+ ["scale0", "scale1", "scale2", "scale3", "scale4"]
-
+ ["color%d" % i for i in range(3)])
-
return transformations
-
-
#transformations used at test time in deep architectures
-
def get_deep_trans():
-
return ['corner0','corner1','corner2','corner3','corner4','corner0*flip','corner1*flip','corner2*flip','corner3*flip','corner4*flip']
-
-
if __name__=="__main__":
-
inputpath = sys.argv[1]
-
name = [name for name in os.listdir(inputpath) if os.path.isfile(os.path.join(inputpath,name))]
-
#img_input = sys.argv[1]
-
outpath = sys.argv[2]
-
if len(sys.argv)>= 4:
-
trans = sys.argv[3]
-
if not trans.startswith("["):
-
trans = [trans]
-
else:
-
trans = eval(trans)
-
else:
-
trans = get_all_trans()
-
print "Generating transformations and storing in %s"%(outpath)
-
for k in name:
-
for t in trans:
-
img_input=inputpath+'\\'+k
-
gen_trans(img_input,t,outpath+'\\%s_%s.jpg'%(".".join(img_input.split("\\")[-1].split(".")[:-1]),t))
-
#gen_trans(k, t, outpath + '\\%s_%s.jpg' % (".".join(k.split(".")[:-1]), t))
-
print "Finished. Transformations generated: %s"%(" ".join(trans))
-
# -*- coding=utf-8 -*-
-
import os
-
import sys
-
import shutil
-
from xml.dom.minidom import Document
-
from xml.etree.ElementTree import ElementTree,Element
-
import xml.dom.minidom
-
JPG=[70,50,30]
-
SCALES=[1.5**0.5,1.5,1.5**1.5,1.5**2,1.5**2.5]
-
-
#产生变换后的xml文件
-
def gen_xml(xml_input,trans,outfile):
-
for trans in trans.split('*'):
-
if trans=="plain" or trans.startswith("jpg") or trans.startswith('color'):#如果是这几种变换，直接修改xml文件名就好
-
dom = xml.dom.minidom.parse(xml_input)
-
root = dom.documentElement
-
filenamelist = root.getElementsByTagName('filename')
-
filename = filenamelist[0]
-
c = str(filename.firstChild.data)
-
d = ".".join(outfile.split("\\")[-1].split(".")[:-1]) + '.jpg'
-
filename.firstChild.data = d
-
f = open(outfile, 'w')
-
dom.writexml(f, encoding='utf-8')
-
elif trans.startswith("scale"):#对于尺度变换，xml文件信息也需要改变
-
scale = SCALES[int(trans.replace("scale", ""))]
-
dom=xml.dom.minidom.parse(xml_input)
-
root=dom.documentElement
-
filenamelist=root.getElementsByTagName('filename')
-
filename=filenamelist[0]
-
c=str(filename.firstChild.data)
-
d=".".join(outfile.split("\\")[-1].split(".")[:-1])+'.jpg'
-
filename.firstChild.data=d
-
heightlist = root.getElementsByTagName('height')
-
height = heightlist[0]
-
a = int(height.firstChild.data)
-
b = str(int(a / scale))
-
height.firstChild.data = b
-
widthlist=root.getElementsByTagName('width')
-
width=widthlist[0]
-
a = int(width.firstChild.data)
-
b = str(int(a / scale))
-
width.firstChild.data=b
-
objectlist=root.getElementsByTagName('xmin')
-
for object in objectlist:
-
a=int(object.firstChild.data)
-
b=str(int(a/scale))
-
object.firstChild.data=b
-
objectlist = root.getElementsByTagName('ymin')
-
for object in objectlist:
-
a = int(object.firstChild.data)
-
b = str(int(a / scale))
-
object.firstChild.data = b
-
objectlist = root.getElementsByTagName('xmax')
-
for object in objectlist:
-
a = int(object.firstChild.data)
-
b = str(int(a / scale))
-
object.firstChild.data = b
-
objectlist = root.getElementsByTagName('ymax')
-
for object in objectlist:
-
a = int(object.firstChild.data)
-
b = str(int(a / scale))
-
object.firstChild.data = b
-
f=open(outfile,'w')
-
dom.writexml(f,encoding='utf-8')
-
else:
-
assert False, "Unrecognized transformation: "+trans
-
-
#产生各种变换名
-
def get_all_trans():
-
transformations=(["plain"]
-
+ ["jpg%d" % i for i in JPG]
-
+ ["scale0", "scale1", "scale2", "scale3", "scale4"]
-
+ ["color%d" % i for i in range(3)])
-
return transformations
-
-
if __name__=="__main__":
-
inputpath = sys.argv[1]
-
name = [name for name in os.listdir(inputpath) if os.path.isfile(os.path.join(inputpath,name))]
-
outpath = sys.argv[2]
-
if len(sys.argv)>= 4:
-
trans = sys.argv[3]
-
if not trans.startswith("["):
-
trans = [trans]
-
else:
-
trans = eval(trans)
-
else:
-
trans = get_all_trans()
-
print "Generating transformations and storing in %s"%(outpath)
-
for k in name:
-
for t in trans:
-
xml_input=inputpath+'\\'+k
-
gen_xml(xml_input,t,outpath+'\\%s_%s.xml'%(".".join(xml_input.split("\\")[-1].split(".")[:-1]),t))
