Exemplo n.º 1
0
    pylab.figure()
    pylab.ioff()
    pylab.clf()
    pylab.axis("off")
    pylab.title(title)
    pylab.imshow(img,interpolation="nearest",animated=True) 

modelname="./data/INRIA/inria_bothfull";it=7
import sys
if len(sys.argv)>1:
    imname=sys.argv[1]
else:
    imname="test1.png"

#load the model
m=util2.load("%s%d.model"%(modelname,it))

import pylab

#show the model
if True:
    print "Show model"
    pylab.figure(100)
    pylab.clf()
    util2.drawModel(m["ww"])
    pylab.draw()

print "---- Image %s----"%imname
print
img=util2.myimread(imname)
#compute the HOG pyramid
Exemplo n.º 2
0
 #compute the hog pyramid
 f=pyrHOG2.pyrHOG(img,interv=10,savedir="",notsave=True,notload=True,hallucinate=cfg.hallucinate,cformat=True)
 #show the image
 fig=pylab.figure(20)
 pylab.ioff()
 axes=pylab.Axes(fig, [.0,.0,1.0,1.0]) 
 fig.add_axes(axes) 
 pylab.imshow(img,interpolation="nearest",animated=True)
     
 t=time.time()
 #for each class
 for ccls in cls:
     print
     print "Class: %s"%ccls
     #load the class model
     m=util2.load("%s%d.model"%(cfg.testname%ccls,7))
     res=[]
     t1=time.time()
     #for each aspect
     for clm,m in enumerate(m):
         #scan the image with left and right models
         res.append(pyrHOG2RL.detectflip(f,m,None,hallucinate=cfg.hallucinate,initr=cfg.initr,ratio=cfg.ratio,deform=cfg.deform,bottomup=cfg.bottomup,usemrf=cfg.usemrf,small=False,cl=clm))
     fuse=[]
     numhog=0
     #fuse the detections
     for mix in res:
         tr=mix[0]
         fuse+=mix[1]
         numhog+=mix[3]
     rfuse=tr.rank(fuse,maxnum=300)
     nfuse=tr.cluster(rfuse,ovr=0.3,inclusion=False)