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util2.py
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util2.py
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import cPickle
import numpy
import pylab
def myimread(imgname,flip=False,resize=None):
"""
read an image
"""
img=None
if imgname.split(".")[-1]=="png":
img=pylab.imread(imgname)
else:
img=numpy.ascontiguousarray(pylab.imread(imgname)[::-1])
if flip:
img=numpy.ascontiguousarray(img[:,::-1,:])
if resize!=None:
from scipy.misc import imresize
img=imresize(img,resize)
return img
def save(filename,obj,prt=2):
"""
save any python object
"""
fd=open(filename,"w")
cPickle.dump(obj,fd,prt)
fd.close()
def savemat(filename,dic):
"""
save an array in matlab format
"""
import scipy.io.matlab
fd=open(filename,"w")
scipy.io.matlab.savemat(filename,dic)
fd.close()
def load(filename):
"""
load any python object
"""
fd=open(filename,"r")
aux= cPickle.load(fd)
fd.close()
return aux
def loadmat(filename):
"""
load an array in matlab format
"""
import scipy.io.matlab
fd=open(filename,"r")
aux = scipy.io.matlab.loadmat(filename)
fd.close()
return aux
def drawModel(mfeat,mode="black",parts=True):
"""
draw the HOG weight of an object model
"""
col=["r","g","b"]
import drawHOG
lev=len(mfeat)
if mfeat[0].shape[0]>mfeat[0].shape[1]:
sy=1
sx=lev
else:
sy=lev
sx=1
for l in range(lev):
pylab.subplot(sy,sx,l+1)
if mode=="white":
drawHOG9(mfeat[l])
elif mode=="black":
img=drawHOG.drawHOG(mfeat[l])
pylab.axis("off")
pylab.imshow(img,cmap=pylab.cm.gray,interpolation="nearest")
if parts==True:
for x in range(0,2**l):
for y in range(0,2**l):
boxHOG(mfeat[0].shape[1]*x,mfeat[0].shape[0]*y,mfeat[0].shape[1],mfeat[0].shape[0],col[l],5-l)
def drawDeform(dfeat,mindef=0.001):
"""
draw the deformation weight of an object model
"""
from matplotlib.patches import Ellipse
lev=len(dfeat)
if 1:
sy=1
sx=lev
else:
sy=lev
sx=1
pylab.subplot(sy,sx,1)
x1=-0.5;x2=0.5
y1=-0.5;y2=0.5
pylab.fill([x1,x1,x2,x2,x1],[y1,y2,y2,y1,y1],"b", alpha=0.15, edgecolor="b",lw=1)
pylab.fill([x1,x1,x2,x2,x1],[y1,y2,y2,y1,y1],"r", alpha=0.15, edgecolor="r",lw=1)
wh=numpy.exp(-mindef/dfeat[0][0,0,0])/numpy.exp(1);hh=numpy.exp(-mindef/dfeat[0][0,0,1])/numpy.exp(1)
e=Ellipse(xy=[0,0], width=wh, height=hh , alpha=0.35)
col=numpy.array([wh*hh]*3).clip(0,1)
col[0]=0
e.set_facecolor(col)
pylab.axis("off")
pylab.gca().add_artist(e)
pylab.gca().set_ylim(-0.5,0.5)
pylab.gca().set_xlim(-0.5,0.5)
for l in range(1,lev):
pylab.subplot(sy,sx,l+1)
for ry in range(2**(l-1)):
for rx in range(2**(l-1)):
drawDef(dfeat[l][ry*2:(ry+1)*2,rx*2:(rx+1)*2,2:]*4**l,4*ry,4*rx,distr="child")
drawDef(dfeat[l][ry*2:(ry+1)*2,rx*2:(rx+1)*2,:2]*4**l,ry*2**(l),rx*2**(l),mindef=mindef,distr="father")
#pylab.gca().set_ylim(-0.5,(2.6)**l)
pylab.axis("off")
pylab.gca().set_ylim((2.6)**l,-0.5)
pylab.gca().set_xlim(-0.5,(2.6)**l)
def drawDef(dfeat,dy,dx,mindef=0.001,distr="father"):
"""
auxiliary funtion to draw recursive levels of deformation
"""
from matplotlib.patches import Ellipse
pylab.ioff()
if distr=="father":
py=[0,0,2,2];px=[0,2,0,2]
if distr=="child":
py=[0,1,1,2];px=[1,2,0,1]
ordy=[0,0,1,1];ordx=[0,1,0,1]
x1=-0.5+dx;x2=2.5+dx
y1=-0.5+dy;y2=2.5+dy
if distr=="father":
pylab.fill([x1,x1,x2,x2,x1],[y1,y2,y2,y1,y1],"r", alpha=0.15, edgecolor="b",lw=1)
for l in range(len(py)):
aux=dfeat[ordy[l],ordx[l],:].clip(-1,-mindef)
wh=numpy.exp(-mindef/aux[0])/numpy.exp(1);hh=numpy.exp(-mindef/aux[1])/numpy.exp(1)
e=Ellipse(xy=[(px[l]+dx),(py[l]+dy)], width=wh, height=hh, alpha=0.35)
x1=-0.75+dx+px[l];x2=0.75+dx+px[l]
y1=-0.76+dy+py[l];y2=0.75+dy+py[l]
col=numpy.array([wh*hh]*3).clip(0,1)
if distr=="father":
col[0]=0
e.set_facecolor(col)
pylab.gca().add_artist(e)
if distr=="father":
pylab.fill([x1,x1,x2,x2,x1],[y1,y2,y2,y1,y1],"b", alpha=0.15, edgecolor="b",lw=1)
def overlap(rect1,rect2):
"""
Calculate the overlap between two boxes
"""
dy1=abs(rect1[0]-rect1[2])+1
dx1=abs(rect1[1]-rect1[3])+1
dy2=abs(rect2[0]-rect2[2])+1
dx2=abs(rect2[1]-rect2[3])+1
a1=dx1*dy1
a2=dx2*dy2
ia=0
if rect1[2]>rect2[0] and rect2[2]>rect1[0] and rect1[3]>rect2[1] and rect2[3]>rect1[1]:
xx1 = max(rect1[1], rect2[1]);
yy1 = max(rect1[0], rect2[0]);
xx2 = min(rect1[3], rect2[3]);
yy2 = min(rect1[2], rect2[2]);
ia=(xx2-xx1+1)*(yy2-yy1+1)
return ia/float(a1+a2-ia)
def inclusion(rect1,rect2):
"""
Calculate the intersection percentage between two rectangles
Note that it is not anymore symmetric
"""
dy1=abs(rect1[0]-rect1[2])+1
dx1=abs(rect1[1]-rect1[3])+1
dy2=abs(rect2[0]-rect2[2])+1
dx2=abs(rect2[1]-rect2[3])+1
a1=dx1*dy1
a2=dx2*dy2
ia=0
if rect1[2]>rect2[0] and rect2[2]>rect1[0] and rect1[3]>rect2[1] and rect2[3]>rect1[1]:
xx1 = max(rect1[1], rect2[1]);
yy1 = max(rect1[0], rect2[0]);
xx2 = min(rect1[3], rect2[3]);
yy2 = min(rect1[2], rect2[2]);
ia=(xx2-xx1+1)*(yy2-yy1+1)
return ia/float(a1)
def boxHOG(px,py,dx,dy,col,lw):
"""
bbox one the HOG weights
"""
k=1
d=15
pylab.plot([px*d+0-k,px*d+0-k],[py*d+0-k,py*d+dy*d-k],col,lw=lw)
pylab.plot([px*d+0-k,px*d+dx*d-k],[py*d+0-k,py*d+0-k],col,lw=lw)
pylab.plot([px*d+dx*15-k,px*d+dx*d-k],[py*d+0-k,py*d+dy*d-k],col,lw=lw)
pylab.plot([px*d+0-k,px*d+dx*d-k],[py*d+dy*d-k,py*d+dy*d-k],col,lw=lw)
pylab.axis("image")
def box(p1y,p1x,p2y,p2x,col='b',lw=1):
"""
plot a bbox with the given coordinates
"""
pylab.plot([p1x,p1x,p2x,p2x,p1x],[p1y,p2y,p2y,p1y,p1y],col,lw=lw)