def detectWrap(a):
t=time.time()
i=a[0]
imname=a[1]
bbox=a[2]
m=a[3]
cfg=a[4]
if cfg.show:
img=util.myimread(imname)
pylab.figure(10)
pylab.ioff()
pylab.clf()
pylab.axis("off")
pylab.imshow(img,interpolation="nearest",animated=True)
if bbox!=None:
gtbbox=[{"bbox":x} for x in bbox]
else:
gtbbox=None
f=pyrHOG2.pyrHOG(imname,interv=10,savedir=cfg.savedir+"/hog/",notload=not(cfg.loadfeat),notsave=not(cfg.savefeat),hallucinate=cfg.hallucinate,cformat=True)
res=pyrHOG2.detect(f,m,gtbbox,hallucinate=cfg.hallucinate,initr=cfg.initr,ratio=cfg.ratio,deform=cfg.deform,posovr=cfg.posovr,bottomup=cfg.bottomup,usemrf=cfg.usemrf,numneg=cfg.numneg,thr=cfg.thr,inclusion=cfg.inclusion,small=False,show=cfg.show,usefather=cfg.usefather,emptybb=True,useprior=cfg.useprior)
if cfg.show:
pylab.show()
# raw_input()
print "Detect Wrap:",time.time()-t
return res
def detectWrap(a):
i=a[0]
imname=a[1]
bbox=a[2]
models=a[3]
cfg=a[4]
if cfg.show:
img=util.myimread(imname)
pylab.figure(10)
pylab.ioff()
pylab.clf()
pylab.axis("off")
pylab.imshow(img,interpolation="nearest",animated=True)
if bbox!=None:
gtbbox=[{"bbox":x,"img":imname.split("/")[-1]} for x in bbox]
else:
gtbbox=None
notsave=False
#if cfg.__dict__.has_key("test"):
# notsave=cfg.test
f=pyrHOG2.pyrHOG(imname,interv=10,savedir=cfg.auxdir+"/hog/",notsave=not(cfg.savefeat),notload=not(cfg.loadfeat),hallucinate=cfg.hallucinate,cformat=True)
res=[]
for clm,m in enumerate(models):
res.append(pyrHOG2.detect(f,m,gtbbox,hallucinate=cfg.hallucinate,initr=cfg.initr,ratio=cfg.ratio,deform=cfg.deform,bottomup=cfg.bottomup,usemrf=cfg.usemrf,numneg=cfg.numneg,thr=cfg.thr,posovr=cfg.posovr,minnegincl=cfg.minnegincl,small=cfg.small,show=cfg.show,cl=clm,mythr=cfg.mythr,mpos=cfg.mpos,usefather=cfg.usefather,useprior=cfg.useprior,emptybb=False,K=cfg.k))
if cfg.show:
pylab.show()
return res
def detectWrap(a):
i=a[0]
imname=a[1]
bbox=a[2]
models=a[3]
cfg=a[4]
if cfg.show:
img=util.myimread(imname)
pylab.figure(10)
pylab.ioff()
pylab.clf()
pylab.axis("off")
pylab.imshow(img,interpolation="nearest",animated=True)
if bbox!=None:
gtbbox=[{"bbox":x} for x in bbox]
else:
gtbbox=None
notsave=False
#if cfg.__dict__.has_key("test"):
# notsave=cfg.test
f=pyrHOG2.pyrHOG(imname,interv=10,savedir=cfg.auxdir+"/hog/",notsave=not(cfg.savefeat),notload=not(cfg.loadfeat),hallucinate=cfg.hallucinate,cformat=True)
res=[]
for clm,m in enumerate(models):
res.append(pyrHOG2.detect(f,m,gtbbox,hallucinate=cfg.hallucinate,initr=cfg.initr,ratio=cfg.ratio,deform=cfg.deform,bottomup=cfg.bottomup,usemrf=cfg.usemrf,numneg=cfg.numneg,thr=cfg.thr,posovr=cfg.posovr,minnegincl=cfg.minnegincl,small=cfg.small,show=cfg.show,cl=clm,mythr=cfg.mythr,mpos=cfg.mpos,usefather=cfg.usefather,useprior=cfg.useprior,K=cfg.k))
if cfg.show:
pylab.show()
return res
def detectWrap(a):
t = time.time()
i = a[0]
imname = a[1]
bbox = a[2]
m = a[3]
cfg = a[4]
if cfg.show:
img = util.myimread(imname)
pylab.figure(10)
pylab.ioff()
pylab.clf()
pylab.axis("off")
pylab.imshow(img, interpolation="nearest", animated=True)
if bbox != None:
gtbbox = [{"bbox": x} for x in bbox]
else:
gtbbox = None
img = util.myimread(imname, resize=RSZ)
f = pyrHOG2.pyrHOG(img,
interv=10,
savedir=cfg.savedir + "/hog/",
notload=not (cfg.loadfeat),
notsave=not (cfg.savefeat),
hallucinate=cfg.hallucinate,
cformat=True)
res = pyrHOG2.detect(f,
m,
gtbbox,
hallucinate=cfg.hallucinate,
initr=cfg.initr,
ratio=cfg.ratio,
deform=cfg.deform,
posovr=cfg.posovr,
bottomup=cfg.bottomup,
usemrf=cfg.usemrf,
numneg=cfg.numneg,
thr=cfg.thr,
inclusion=cfg.inclusion,
small=cfg.small,
show=cfg.show,
usefather=cfg.usefather,
useprior=cfg.useprior,
nms=cfg.ovr,
K=cfg.k)
if cfg.show:
pylab.show()
# raw_input()
print "Detect Wrap:", time.time() - t
return res
def detectWrap(a):
i = a[0]
imname = a[1]
bbox = a[2]
models = a[3]
cfg = a[4]
if len(a) <= 5:
imageflip = False
else:
imageflip = a[5]
img = util.myimread(imname, resize=cfg.resize)
if imageflip:
img = util.myimread(imname, True, resize=cfg.resize)
if bbox != None:
bbox = util.flipBBox(img, bbox)
if bbox != None:
gtbbox = [{"bbox": x, "img": imname.split("/")[-1]} for x in bbox]
else:
gtbbox = None
if cfg.show:
img = util.myimread(imname, imageflip, resize=cfg.resize)
pylab.figure(10)
pylab.ioff()
pylab.clf()
pylab.axis("off")
pylab.imshow(img, interpolation="nearest", animated=True)
notsave = False
#if cfg.__dict__.has_key("test"):
# notsave=cfg.test
#f=pyrHOG2.pyrHOG(imname,interv=10,savedir=cfg.auxdir+"/hog/",notsave=not(cfg.savefeat),notload=not(cfg.loadfeat),hallucinate=cfg.hallucinate,cformat=True,flip=imageflip,resize=cfg.resize)
f = pyrHOG2.pyrHOG(img,
interv=10,
savedir=cfg.auxdir + "/hog/",
notsave=not (cfg.savefeat),
notload=not (cfg.loadfeat),
hallucinate=cfg.hallucinate,
cformat=True) #,flip=imageflip,resize=cfg.resize)
res = []
for clm, m in enumerate(models):
if cfg.useRL:
res.append(
pyrHOG2RL.detectflip(f,
m,
gtbbox,
hallucinate=cfg.hallucinate,
initr=cfg.initr,
ratio=cfg.ratio,
deform=cfg.deform,
bottomup=cfg.bottomup,
usemrf=cfg.usemrf,
numneg=cfg.numneg,
thr=cfg.thr,
posovr=cfg.posovr,
minnegincl=cfg.minnegincl,
small=cfg.small,
show=cfg.show,
cl=clm,
mythr=cfg.mythr,
mpos=cfg.mpos,
usefather=cfg.usefather,
useprior=cfg.useprior,
K=cfg.k))
else:
res.append(
pyrHOG2.detect(f,
m,
gtbbox,
hallucinate=cfg.hallucinate,
initr=cfg.initr,
ratio=cfg.ratio,
deform=cfg.deform,
bottomup=cfg.bottomup,
usemrf=cfg.usemrf,
numneg=cfg.numneg,
thr=cfg.thr,
posovr=cfg.posovr,
minnegincl=cfg.minnegincl,
small=cfg.small,
show=cfg.show,
cl=clm,
mythr=cfg.mythr,
mpos=cfg.mpos,
usefather=cfg.usefather,
useprior=cfg.useprior,
emptybb=False,
K=cfg.k))
if cfg.show:
pylab.draw()
pylab.show()
return res
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
f=pyrHOG2.pyrHOG(img,interv=10,savedir="",notload=True,notsave=True,hallucinate=True,cformat=True)
print
print "Complete search"
showImage(img,title="Complete search")
res=pyrHOG2.detect(f,m,bottomup=True,deform=True,usemrf=True,small=False,show=True)
pylab.axis((0,img.shape[1],img.shape[0],0))
dettime1=res[2]
numhog1=res[3]
print "Number of computed HOGs:",numhog1
print
print "Coarse-to-Fine search"
import pylab
showImage(img,title="Coarse-to-Fine")
res=pyrHOG2.detect(f,m,bottomup=False,deform=True,usemrf=True,small=False,show=True)
pylab.axis((0,img.shape[1],img.shape[0],0))
pylab.draw()
pylab.show()
dettime2=res[2]
numhog2=res[3]
print "Number of computed HOGs:",numhog2
