pylab.figure(20)
pylab.ioff()
pylab.clf()
pylab.axis("off")
img = util.myimread(tsImages[ii]["name"])
pylab.imshow(img, interpolation="nearest", animated=True)
pylab.gca().set_ylim(0, img.shape[0])
pylab.gca().set_xlim(0, img.shape[1])
pylab.gca().set_ylim(pylab.gca().get_ylim()[::-1])
tr.show(nfuse, parts=showlabel, thr=-0.5, maxnum=10)
pylab.show()
del itr
#tp,fp,scr,tot=VOCpr.VOCprlistfastscore(tsImages,detlist,numim=cfg.maxpostest,show=False,ovr=0.5)
tp, fp, scr, tot = VOCpr.VOCprRecord(tsImages,
detlist,
show=False,
ovr=0.5)
pylab.figure(15)
pylab.clf()
rc, pr, ap = VOCpr.drawPrfast(tp, fp, tot)
pylab.draw()
pylab.show()
pylab.savefig("%s_ap%d.png" % (testname, it))
#util.savemat("%s_ap%d.mat"%(testname,it),{"tp":tp,"fp":fp,"scr":scr,"tot":tot,"rc":rc,"pr":pr,"ap":ap})
tinit = ((time.time() - initime) / 3600.0)
tpar = ((time.time() - partime) / 3600.0)
print "AP(it=", it, ")=", ap
print "Training Time: %.3f h" % (tinit)
rpres.report(testname + ".rpt.txt", "a", "Results")
print[x["scr"] for x in im[1]]
raw_input()
if False:
pylab.savefig("./video/detSCRBU/" +
tsImages[i]["name"].split("/")[-1].split(".")[0] +
".png")
#raw_input()
for l in im[1]:
detlist.append([
tsImages[i]["name"].split("/")[-1].split(".")[0], l["scr"],
l["bbox"][1], l["bbox"][0], l["bbox"][3], l["bbox"][2]
])
del itr
mypool.close()
tp, fp, scr, tot = VOCpr.VOCprRecord(
tsImages, detlist, show=False,
ovr=0.5) #solved a problem that was giving around 1-2 point less
pylab.figure(16)
pylab.clf()
fppi, miss, ap = VOCpr.drawMissRatePerImage(tp, fp, tot, len(tsImages))
pylab.draw()
pylab.show()
pylab.figure(15)
pylab.clf()
rc, pr, ap = VOCpr.drawPrfast(tp, fp, tot)
pylab.draw()
pylab.show()
#pylab.savefig("%s_ap%d_test.png"%(testname,it))
#pylab.savefig("%s_miss%d_test.png"%(testname,it))
tinit = ((time.time() - initime)) #/3600.0)
print "Average Detection Time:", numpy.mean(dettime)
def test(thr, cfg, it=9):
#cfg.test=True
import util
#it=it
models = util.load("%s%d.model" % (cfg.testname, it))
#skip occlusion
#for l in models:
# del l["occl"]
w = []
rho = []
cfg.mythr = thr
#for l in range(cfg.numcl):
# w.append(util.ModeltoW(models[l],cfg.usemrf,cfg.usefather,cfg.k,lastlev=1))
# rho.append(models[l]["rho"])
#cfg.mythr=cfg.mythr*numpy.mean([numpy.sum(x**2) for x in w])#-numpy.mean(rho)
#raw_input()
#cfg.mythr=cfg.mythr#-numpy.mean(rho)
if cfg.multipr == 1:
numcore = None
else:
numcore = cfg.multipr
mypool = Pool(numcore)
if cfg.cls == "inria":
if cfg.select == "pos":
tsImages = getRecord(InriaTestData(basepath=cfg.dbpath),
cfg.maxtest)
else:
tsImages = getRecord(InriaTestFullData(basepath=cfg.dbpath),
cfg.maxtest)
if select == "dir": #"." or select[0]=="/"
import glob
#lst=glob.glob("/home/marcopede/ivan/zebra/CVC_Zebra1/*.jpeg")[150:]
lst = glob.glob(
"/media/ca0567b8-ee6d-4590-8462-0d093addb4cf/video/*.png")
lst.sort()
lst = lst[3900:]
total = len(lst)
tsImages = numpy.zeros(total,
dtype=[("id", numpy.int32),
("name", object), ("bbox", list)])
for idl, l in enumerate(lst):
tsImages[idl]["id"] = idl
tsImages[idl]["name"] = l #l.split("/")[-1]
tsImages[idl]["bbox"] = None
else:
tsImages = getRecord(
VOC07Data(
select=cfg.select,
cl="%s_test.txt" % cfg.cls,
basepath=cfg.dbpath, #"/home/databases/",
usetr=True,
usedf=False),
cfg.maxtest)
elif cfg.cls == "cvc02":
#tsImages=getRecord(CVC02test(),cfg.maxtest)
tsImages = getRecord(
CVC02test(
basepath="/media/OS/data/DATASET-CVC-02/CVC-02-System/",
images="/sequence-15/color/",
annotations="/sequence-15/annotations/",
), cfg.maxtest)
tsImagesFull = tsImages
elif cfg.cls == "ivan":
stest = 10000
#tsImages=getRecord(ImgFile("/media/OS/data/PVTRA101/CLEAR06_PVTRA101a01_502_Bbox.txt",imgpath="/media/OS/data/PVTRA101/images/"),stest+cfg.maxtest)[stest:]
#tsImages=getRecord(ImgFile("/media/OS/data/PVTRA101a19/GrTr_CLEAR06_PVTRA101a19.txt",imgpath="/media/OS/data/PVTRA101a19/CLEAR06_PVTRA101a19/",sort=True,amin=1000),cfg.maxtest)[:600]#[:1950]#the other frames do not have GT
#tsImages=getRecord(ImgFile("/media/OS/data/PVTRA101a19/GrTr_CLEAR06_PVTRA101a19_only12.txt",imgpath="/media/OS/data/PVTRA101a19/CLEAR06_PVTRA101a19/",sort=True,amin=100),cfg.maxtest)[:(1950/12)]#the other frames do not have GT
#tsImages=getRecord(ImgFile("/media/OS/data/PVTRA101a19/CLEAR06_PVTRA101a19_people_Celik_allfr.txt",imgpath="/media/OS/data/PVTRA101a19/CLEAR06_PVTRA101a19/",sort=True,amin=100),cfg.maxtest)#pedestrian
tsImages = getRecord(
ImgFile(
"/media/OS/data/PVTRA101a19/CLEAR06_PVTRA101a19_vehicles_Celik_allfr.txt",
imgpath="/media/OS/data/PVTRA101a19/CLEAR06_PVTRA101a19/",
sort=True,
amin=100), cfg.maxtest) #vechicles
#tsImages=getRecord(ImgFile("/media/OS/data/PVTRA101a19/CLEAR06_PVTRA101a19_PV_Celik_allfr.txt",imgpath="/media/OS/data/PVTRA101a19/CLEAR06_PVTRA101a19/",sort=True,amin=100),cfg.maxtest)#pedestrian+vechicles
tsImagesFull = tsImages
#mypool = Pool(numcore)
print "Test"
print "Pruning Threshold:", cfg.mythr
numhog = 0
initime = time.time()
detlist = []
mycfg = copy.copy(cfg)
mycfg.numneg = 0
mycfg.show = False
arg = [[i, tsImages[i]["name"], None, models, mycfg]
for i in range(len(tsImages))]
t = time.time()
if not (cfg.multipr):
itr = itertools.imap(detectWrap, arg)
else:
itr = mypool.imap(detectWrap, arg)
pylab.figure(20)
pylab.clf()
ax = pylab.subplot(111)
img = util.myimread(tsImages[0]["name"], resize=cfg.resize)
pylab.ioff()
axes = pylab.Axes(pylab.gcf(), [
.0, .0, 1.0, 1.0
]) # [left, bottom, width, height] where each value is between 0 and 1
pylab.gcf().add_axes(axes)
pylab.axis("off")
aim = pylab.imshow(img, interpolation="nearest", animated=True)
pylab.axis((0, img.shape[1], img.shape[0], 0))
pylab.draw()
pylab.show()
for ii, res in enumerate(itr):
totneg = 0
fuse = []
for mix in res:
tr = mix[0]
fuse += mix[1]
numhog += mix[3]
#for h in fuse:
# h["scr"]+=models[h["cl"]]["ra"]
rfuse = tr.rank(fuse, maxnum=300)
nfuse = tr.cluster(rfuse, ovr=cfg.ovrasp, inclusion=False)
#print "----Test Image %d----"%ii
print "----Test Image %s----" % tsImages[ii]["name"].split("/")[-1]
for idl, l in enumerate(nfuse):
#print "DET:",l["bbox"]
#raw_input()
#if l["bbox"][0]/cfg.resize<125:
# nfuse.pop(idl)
# continue
detlist.append([
tsImages[ii]["name"].split("/")[-1].split(".")[0], l["scr"],
l["bbox"][1] / cfg.resize, l["bbox"][0] / cfg.resize,
l["bbox"][3] / cfg.resize, l["bbox"][2] / cfg.resize
])
print "Detections:", len(nfuse)
if cfg.show:
if cfg.show == True:
showlabel = False #"Parts"#False#"Parts"
else:
showlabel = False
pylab.figure(20)
xx = pylab.gca()
del xx.texts[:]
del xx.lines[:]
#print pylab.gca().images
#pylab.ioff()
# axes=pylab.Axes(pylab.gcf(), [.0,.0,1.0,1.0]) # [left, bottom, width, height] where each value is between 0 and 1
# pylab.gcf().add_axes(axes)
# pylab.axis("off")
#img=util.myimread(tsImages[ii]["name"],resize=cfg.resize)
img = pylab.imread(
tsImages[ii]["name"]) #myimread has memory problems!!!!!!!
#pylab.clf()
aim.set_array(img)
#ims=pylab.imshow(img,interpolation="nearest",animated=True)
tr.show(nfuse, parts=showlabel, thr=0, maxnum=100)
pylab.axis((0, img.shape[1], img.shape[0], 0))
pylab.draw()
pylab.show()
#print ax.images
#raw_input()
showGT = True
if showGT:
bb = tsImages[ii]["bbox"]
for mbb in bb:
util.box(mbb[0], mbb[1], mbb[2], mbb[3], col='r', lw=2)
pylab.axis((0, img.shape[1], img.shape[0], 0))
pylab.draw()
#raw_input()
if select == "dir":
#RSZ=0.5
f = pylab.figure(11, figsize=(9, 5))
pylab.ioff()
pylab.clf()
axes = pylab.Axes(
f, [.0, .0, 1.0, 1.0]
) # [left, bottom, width, height] where each value is between 0 and 1
f.add_axes(axes)
img = util.myimread(tsImages[ii]["name"], resize=cfg.resize)
pylab.imshow(img, interpolation="nearest", animated=True)
#raw_input()
pylab.axis("off")
tr.show(nfuse, parts=True, thr=-0.99, scr=True)
pylab.axis((0, img.shape[1], img.shape[0], 0))
pylab.ion()
pylab.draw()
pylab.show()
#raw_input()
pylab.savefig(
"/media/ca0567b8-ee6d-4590-8462-0d093addb4cf/video/det/" +
tsImages[ii]["name"].split("/")[-1].split(".")[0] + ".png")
del itr
#tp,fp,scr,tot=VOCpr.VOCprlistfastscore(tsImages,detlist,numim=cfg.maxpostest,show=False,ovr=0.5)
#tp,fp,scr,tot=VOCpr.VOCprRecord_wrong(tsImages,detlist,show=False,ovr=0.5)
tp, fp, scr, tot = VOCpr.VOCprRecord(tsImages,
detlist,
show=False,
ovr=0.5)
pylab.figure(15)
pylab.clf()
rc, pr, ap = VOCpr.drawPrfast(tp, fp, tot)
pylab.figure(16)
pylab.clf()
fppi, miss, ap = VOCpr.drawMissRatePerImage(tp, fp, tot, len(tsImages))
pylab.draw()
pylab.show()
sfdsd
#pylab.savefig("%s_ap%d_test%s%.1f.png"%(testname,it,select,cfg.mythr))
tottime = ((time.time() - initime))
print "Threshold used:", cfg.mythr
print "Total number of HOG:", numhog
print "AP(it=", it, ")=", ap
print "Testing Time: %.3f s" % tottime #/3600.0)
#results={"det":detlist,"ap":ap,"tp":tp,"fp":fp,"pr":pr,"rc":rc,"numhog":numhog,"mythr":cfg.mythr,"time":tottime}
#util.savemat("%s_ap%d_test_thr_%.3f.mat"%(cfg.testname,it,cfg.mythr),results)
#util.save("%s_ap%d_test_thr_%.3f.dat"%(testname,it,cfg.mythr),results)
#util.savedetVOC(detlist,"%s_ap%d_test_thr_%.3f.txt"%(testname,it,cfg.mythr))
#fd=open("%s_ap%d_test%s.txt"%(cfg.testname,it,select),"a")
#fd.write("Threshold used:%f\n"%cfg.mythr)
#fd.write("Total number of HOG:%d\n"%numhog)
#fd.write("Average precision:%f\n"%ap)
#fd.write("Testing Time: %.3f s\n\n"%tottime)
#fd.close()
return ap, numhog
def test(thr, cfg):
#cfg.test=True
import util
it = 7
models = util.load("%s%d.model" % (cfg.testname, it))
w = []
rho = []
cfg.mythr = thr
#for l in range(cfg.numcl):
# w.append(util.ModeltoW(models[l],cfg.usemrf,cfg.usefather,cfg.k,lastlev=1))
# rho.append(models[l]["rho"])
#cfg.mythr=cfg.mythr*numpy.mean([numpy.sum(x**2) for x in w])#-numpy.mean(rho)
#raw_input()
#cfg.mythr=cfg.mythr#-numpy.mean(rho)
if cfg.multipr == 1:
numcore = None
else:
numcore = cfg.multipr
mypool = Pool(numcore)
if cfg.cls == "inria":
if cfg.select == "pos":
tsImages = getRecord(InriaTestData(basepath=cfg.dbpath),
cfg.maxtest)
else:
tsImages = getRecord(InriaTestFullData(basepath=cfg.dbpath),
cfg.maxtest)
else:
tsImages = getRecord(
VOC07Data(
select=cfg.select,
cl="%s_test.txt" % cfg.cls,
basepath=cfg.dbpath, #"/home/databases/",
usetr=True,
usedf=False),
cfg.maxtest)
mypool = Pool(numcore)
print "Test"
print "Pruning Threshold:", cfg.mythr
numhog = 0
initime = time.time()
detlist = []
mycfg = copy.copy(cfg)
mycfg.numneg = 0
arg = [[i, tsImages[i]["name"], None, models, mycfg]
for i in range(len(tsImages))]
t = time.time()
if not (cfg.multipr):
itr = itertools.imap(detectWrap, arg)
else:
itr = mypool.imap(detectWrap, arg)
for ii, res in enumerate(itr):
totneg = 0
fuse = []
for mix in res:
tr = mix[0]
fuse += mix[1]
numhog += mix[3]
#for h in fuse:
# h["scr"]+=models[h["cl"]]["ra"]
rfuse = tr.rank(fuse, maxnum=300)
nfuse = tr.cluster(rfuse, ovr=0.3, inclusion=False)
print "----Test Image %d----" % ii
for l in nfuse:
detlist.append([
tsImages[ii]["name"].split("/")[-1].split(".")[0], l["scr"],
l["bbox"][1], l["bbox"][0], l["bbox"][3], l["bbox"][2]
])
print "Detections:", len(nfuse)
if cfg.show:
if cfg.show == True:
showlabel = "Parts"
else:
showlabel = False
pylab.figure(20)
pylab.ioff()
pylab.clf()
pylab.axis("off")
img = util.myimread(tsImages[ii]["name"])
pylab.imshow(img, interpolation="nearest", animated=True)
pylab.gca().set_ylim(0, img.shape[0])
pylab.gca().set_xlim(0, img.shape[1])
pylab.gca().set_ylim(pylab.gca().get_ylim()[::-1])
tr.show(nfuse, parts=showlabel, thr=-0.8, maxnum=10)
pylab.show()
#raw_input()
del itr
#tp,fp,scr,tot=VOCpr.VOCprlistfastscore(tsImages,detlist,numim=cfg.maxpostest,show=False,ovr=0.5)
#tp,fp,scr,tot=VOCpr.VOCprRecord_wrong(tsImages,detlist,show=False,ovr=0.5)
tp, fp, scr, tot = VOCpr.VOCprRecord(tsImages,
detlist,
show=False,
ovr=0.5)
pylab.figure(15)
pylab.clf()
rc, pr, ap = VOCpr.drawPrfast(tp, fp, tot)
pylab.draw()
pylab.show()
#pylab.savefig("%s_ap%d_test%s%.1f.png"%(testname,it,select,cfg.mythr))
tottime = ((time.time() - initime))
print "Threshold used:", cfg.mythr
print "Total number of HOG:", numhog
print "AP(it=", it, ")=", ap
print "Testing Time: %.3f s" % tottime #/3600.0)
#results={"det":detlist,"ap":ap,"tp":tp,"fp":fp,"pr":pr,"rc":rc,"numhog":numhog,"mythr":cfg.mythr,"time":tottime}
#util.savemat("%s_ap%d_test_thr_%.3f.mat"%(cfg.testname,it,cfg.mythr),results)
#util.save("%s_ap%d_test_thr_%.3f.dat"%(testname,it,cfg.mythr),results)
#util.savedetVOC(detlist,"%s_ap%d_test_thr_%.3f.txt"%(testname,it,cfg.mythr))
#fd=open("%s_ap%d_test%s.txt"%(cfg.testname,it,select),"a")
#fd.write("Threshold used:%f\n"%cfg.mythr)
#fd.write("Total number of HOG:%d\n"%numhog)
#fd.write("Average precision:%f\n"%ap)
#fd.write("Testing Time: %.3f s\n\n"%tottime)
#fd.close()
return ap, numhog
