31,
m["fy"],
m["fx"],
usemrf=cfg.usemrf,
usefather=cfg.usefather)
#models[idm]["ra"]=w[cumsize[idm+1]-1]
util.save("%s%d.model" % (testname, it), models)
if cfg.deform:
print m["df"]
if True:
print "Show model"
for idm, m in enumerate(models):
pylab.figure(100 + idm)
pylab.clf()
util.drawModel(m["ww"])
pylab.draw()
pylab.show()
pylab.savefig("%s_hog%d_cl%d.png" % (testname, it, idm))
if cfg.deform:
pylab.figure(110 + idm)
pylab.clf()
util.drawDeform(m["df"])
pylab.draw()
pylab.show()
pylab.savefig(
"%s_def%d_cl%d.png" % (testname, it, idm))
sts.report(testname + ".rpt.txt", "a", "Before Filtering")
#sort based on score
#sort=True
def detectflip(f,m,gtbbox=None,auxdir=".",hallucinate=1,initr=1,ratio=1,deform=False,bottomup=False,usemrf=False,numneg=0,thr=-2,posovr=0.7,minnegincl=0.5,small=True,show=False,cl=0,mythr=-10,nms=0.5,inclusion=False,usefather=True,mpos=1,useprior=False,K=1.0,occl=False,trunc=0):
"""Detect objects with RL flip
used for both test --> gtbbox=None
and trainig --> gtbbox = list of bounding boxes
"""
#build flip
pyrHOG2.setK(K)
m1=flip(m)
t=time.time()
if gtbbox!=None and gtbbox!=[] and useprior:
pr=f.buildPrior(gtbbox,m["fy"],m["fx"])
else:
pr=None
t=time.time()
f.resetHOG()
if deform:
if bottomup:
scr,pos=f.scanRCFLDefBU(m,initr=initr,ratio=ratio,small=small,usemrf=usemrf)
scr1,pos1=f.scanRCFLDefBU(m1,initr=initr,ratio=ratio,small=small,usemrf=usemrf)
else:
#scr,pos=f.scanRCFLDefThr(m,initr=initr,ratio=ratio,small=small,usemrf=usemrf,mythr=mythr)
scr,pos=f.scanRCFLDef(m,initr=initr,ratio=ratio,small=small,usemrf=usemrf,trunc=trunc)
#scr1,pos1=f.scanRCFLDefThr(m1,initr=initr,ratio=ratio,small=small,usemrf=usemrf,mythr=mythr)
scr1,pos1=f.scanRCFLDef(m1,initr=initr,ratio=ratio,small=small,usemrf=usemrf,trunc=trunc)
else:
scr,pos=f.scanRCFL(m,initr=initr,ratio=ratio,small=small,trunc=trunc)
scr1,pos1=f.scanRCFL(m1,initr=initr,ratio=ratio,small=small,trunc=trunc)
lr=[]
fscr=[]
for idl,l in enumerate(scr):
auxscr=numpy.zeros((l.shape[0],l.shape[1],2),numpy.float32)
auxscr[:,:,0]=scr[idl]
auxscr[:,:,1]=scr1[idl]
fscr.append(numpy.max(auxscr,2))
lr.append(numpy.argmax(auxscr,2))
if 0:
pylab.figure(101)
pylab.clf()
print auxscr[:,:,0]
print auxscr[:,:,1]
pylab.imshow(lr[-1])
pylab.show()
raw_input()
if deform:
tr=TreatDefRL(f,fscr,pos,pos1,lr,initr,m["fy"],m["fx"],occl=occl,trunc=trunc)
else:
tr=TreatRL(f,fscr,pos,pos1,lr,initr,m["fy"],m["fx"],occl=occl,trunc=trunc)
numhog=f.getHOG()
if gtbbox==None:
if show==True:
showlabel="Parts"
else:
showlabel=False
ref=0#enable TD+BU
if ref:
t1=time.time()
det=tr.doall(thr=thr,rank=100,refine=True,rawdet=False,cluster=False,show=False,inclusion=inclusion,cl=cl)
detR=[];detL=[]
for d in det:
if d["rl"]==1:
detR.append(d)
else:
detL.append(d)
samplesR=tr.goodsamples(detR,initr=initr,ratio=ratio)
samplesL=tr.goodsamples(detL,initr=initr,ratio=ratio)
scrR,posR=f.scanRCFLDefBU(m,initr=initr,ratio=ratio,small=small,usemrf=usemrf,mysamples=samplesR)
scrL,posL=f.scanRCFLDefBU(m1,initr=initr,ratio=ratio,small=small,usemrf=usemrf,mysamples=samplesL)
lr=[];fscr=[]
for idl,l in enumerate(scrR):
auxscr=numpy.zeros((l.shape[0],l.shape[1],2),numpy.float32)
auxscr[:,:,0]=scrR[idl]
auxscr[:,:,1]=scrL[idl]
fscr.append(numpy.max(auxscr,2))
lr.append(numpy.argmax(auxscr,2))
print "Refine Time:",time.time()-t1
tr=TreatDefRL(f,fscr,posR,posL,lr,initr,m["fy"],m["fx"],occl=occl)
det=tr.doall(thr=thr,rank=100,refine=True,rawdet=False,cluster=nms,show=False,inclusion=inclusion,cl=cl)
else:
det=tr.doall(thr=thr,rank=100,refine=True,rawdet=False,cluster=nms,show=False,inclusion=inclusion,cl=cl)
dettime=time.time()-t
if show:
tr.show(det,parts=showlabel,thr=-1.0,maxnum=0)
print "Detect: %.3f"%(time.time()-t)
return tr,det,dettime,numhog
else:
best1,worste1=tr.doalltrain(gtbbox,thr=thr,rank=1000,show=show,mpos=mpos,numpos=1,posovr=posovr,numneg=numneg,minnegovr=0,minnegincl=minnegincl,cl=cl)
ipos=[];ineg=[]
if False and show and len(best1)>0:
import util
ds=tr.descr(best1,flip=False,usemrf=usemrf,usefather=usefather,k=K)
pylab.figure(120)
pylab.clf()
mm=tr.model(ds[0],0,len(m1["ww"]),31)
util.drawModel(mm["ww"])
pylab.show()
#raw_input()
print "Detect: %.3f"%(time.time()-t)
return tr,best1,worste1,ipos,ineg
dd.append(lowd)
rho = 0
models.append({
"ww": ww,
"rho": rho,
"df": dd,
"fy": ww[0].shape[0],
"fx": ww[0].shape[1]
})
if False:
print "Show model"
for idm, m in enumerate(models):
pylab.figure(100 + idm)
pylab.clf()
util.drawModel(m["ww"])
pylab.draw()
pylab.show()
raw_input()
#fulltrpos=[]
#fulltrposcl=[]
trneg = []
trpos = []
trposcl = []
dtrpos = {}
trnegcl = []
newtrneg = []
newtrnegcl = []
negratio = [-1]
posratio = [-1]
def detectflip(f,
m,
gtbbox=None,
auxdir=".",
hallucinate=1,
initr=1,
ratio=1,
deform=False,
bottomup=False,
usemrf=False,
numneg=0,
thr=-2,
posovr=0.7,
minnegincl=0.5,
small=True,
show=False,
cl=0,
mythr=-10,
nms=0.5,
inclusion=False,
usefather=True,
mpos=1,
useprior=False,
K=1.0,
occl=False,
trunc=0):
"""Detect objects with RL flip
used for both test --> gtbbox=None
and trainig --> gtbbox = list of bounding boxes
"""
#build flip
pyrHOG2.setK(K)
m1 = flip(m)
t = time.time()
if gtbbox != None and gtbbox != [] and useprior:
pr = f.buildPrior(gtbbox, m["fy"], m["fx"])
else:
pr = None
t = time.time()
f.resetHOG()
if deform:
if bottomup:
scr, pos = f.scanRCFLDefBU(m,
initr=initr,
ratio=ratio,
small=small,
usemrf=usemrf)
scr1, pos1 = f.scanRCFLDefBU(m1,
initr=initr,
ratio=ratio,
small=small,
usemrf=usemrf)
else:
#scr,pos=f.scanRCFLDefThr(m,initr=initr,ratio=ratio,small=small,usemrf=usemrf,mythr=mythr)
scr, pos = f.scanRCFLDef(m,
initr=initr,
ratio=ratio,
small=small,
usemrf=usemrf,
trunc=trunc)
#scr1,pos1=f.scanRCFLDefThr(m1,initr=initr,ratio=ratio,small=small,usemrf=usemrf,mythr=mythr)
scr1, pos1 = f.scanRCFLDef(m1,
initr=initr,
ratio=ratio,
small=small,
usemrf=usemrf,
trunc=trunc)
else:
scr, pos = f.scanRCFL(m,
initr=initr,
ratio=ratio,
small=small,
trunc=trunc)
scr1, pos1 = f.scanRCFL(m1,
initr=initr,
ratio=ratio,
small=small,
trunc=trunc)
lr = []
fscr = []
for idl, l in enumerate(scr):
auxscr = numpy.zeros((l.shape[0], l.shape[1], 2), numpy.float32)
auxscr[:, :, 0] = scr[idl]
auxscr[:, :, 1] = scr1[idl]
fscr.append(numpy.max(auxscr, 2))
lr.append(numpy.argmax(auxscr, 2))
if 0:
pylab.figure(101)
pylab.clf()
print auxscr[:, :, 0]
print auxscr[:, :, 1]
pylab.imshow(lr[-1])
pylab.show()
raw_input()
if deform:
tr = TreatDefRL(f,
fscr,
pos,
pos1,
lr,
initr,
m["fy"],
m["fx"],
occl=occl,
trunc=trunc)
else:
tr = TreatRL(f,
fscr,
pos,
pos1,
lr,
initr,
m["fy"],
m["fx"],
occl=occl,
trunc=trunc)
numhog = f.getHOG()
if gtbbox == None:
if show == True:
showlabel = "Parts"
else:
showlabel = False
ref = 0 #enable TD+BU
if ref:
t1 = time.time()
det = tr.doall(thr=thr,
rank=100,
refine=True,
rawdet=False,
cluster=False,
show=False,
inclusion=inclusion,
cl=cl)
detR = []
detL = []
for d in det:
if d["rl"] == 1:
detR.append(d)
else:
detL.append(d)
samplesR = tr.goodsamples(detR, initr=initr, ratio=ratio)
samplesL = tr.goodsamples(detL, initr=initr, ratio=ratio)
scrR, posR = f.scanRCFLDefBU(m,
initr=initr,
ratio=ratio,
small=small,
usemrf=usemrf,
mysamples=samplesR)
scrL, posL = f.scanRCFLDefBU(m1,
initr=initr,
ratio=ratio,
small=small,
usemrf=usemrf,
mysamples=samplesL)
lr = []
fscr = []
for idl, l in enumerate(scrR):
auxscr = numpy.zeros((l.shape[0], l.shape[1], 2),
numpy.float32)
auxscr[:, :, 0] = scrR[idl]
auxscr[:, :, 1] = scrL[idl]
fscr.append(numpy.max(auxscr, 2))
lr.append(numpy.argmax(auxscr, 2))
print "Refine Time:", time.time() - t1
tr = TreatDefRL(f,
fscr,
posR,
posL,
lr,
initr,
m["fy"],
m["fx"],
occl=occl)
det = tr.doall(thr=thr,
rank=100,
refine=True,
rawdet=False,
cluster=nms,
show=False,
inclusion=inclusion,
cl=cl)
else:
det = tr.doall(thr=thr,
rank=100,
refine=True,
rawdet=False,
cluster=nms,
show=False,
inclusion=inclusion,
cl=cl)
dettime = time.time() - t
if show:
tr.show(det, parts=showlabel, thr=-1.0, maxnum=0)
print "Detect: %.3f" % (time.time() - t)
return tr, det, dettime, numhog
else:
best1, worste1 = tr.doalltrain(gtbbox,
thr=thr,
rank=1000,
show=show,
mpos=mpos,
numpos=1,
posovr=posovr,
numneg=numneg,
minnegovr=0,
minnegincl=minnegincl,
cl=cl)
ipos = []
ineg = []
if False and show and len(best1) > 0:
import util
ds = tr.descr(best1,
flip=False,
usemrf=usemrf,
usefather=usefather,
k=K)
pylab.figure(120)
pylab.clf()
mm = tr.model(ds[0], 0, len(m1["ww"]), 31)
util.drawModel(mm["ww"])
pylab.show()
#raw_input()
print "Detect: %.3f" % (time.time() - t)
return tr, best1, worste1, ipos, ineg