def process(options, collection, annotationName):
rootpath = options.rootpath
overwrite = options.overwrite
concepts = readConcepts(collection,annotationName,rootpath)
resultdir = os.path.join(rootpath, collection, "SimilarityIndex", "ngd")
todo = [x for x in concepts if not os.path.exists(os.path.join(resultdir,x+'.txt')) or overwrite]
if not todo:
printStatus(INFO, 'nothing to do')
return
fcs = FlickrContextSim(collection, rootpath=rootpath)
vob = fcs.vob
resultdir = os.path.join(rootpath, collection, "SimilarityIndex", "ngd")
printStatus(INFO, 'expanding tags for %s-%s -> %s' % (collection, annotationName, resultdir))
for concept in todo:
resultfile = os.path.join(resultdir, concept + '.txt')
vals = []
for tag in vob:
dist = fcs.computeNGD(concept, tag, img=1)
if dist < 10:
vals.append((tag,dist))
vals.sort(key=lambda v:v[1])
printStatus(INFO, '%s -> %s' % (concept, ' '.join([x[0] for x in vals[:3]])))
writeRankingResults(vals, resultfile)
def process(options, collection, annotationName):
rootpath = options.rootpath
overwrite = options.overwrite
concepts = readConcepts(collection, annotationName, rootpath)
resultdir = os.path.join(rootpath, collection, "SimilarityIndex", "ngd")
todo = [
x for x in concepts
if not os.path.exists(os.path.join(resultdir, x + '.txt')) or overwrite
]
if not todo:
printStatus(INFO, 'nothing to do')
return
fcs = FlickrContextSim(collection, rootpath=rootpath)
vob = fcs.vob
resultdir = os.path.join(rootpath, collection, "SimilarityIndex", "ngd")
printStatus(
INFO, 'expanding tags for %s-%s -> %s' %
(collection, annotationName, resultdir))
for concept in todo:
resultfile = os.path.join(resultdir, concept + '.txt')
vals = []
for tag in vob:
dist = fcs.computeNGD(concept, tag, img=1)
if dist < 10:
vals.append((tag, dist))
vals.sort(key=lambda v: v[1])
printStatus(INFO,
'%s -> %s' % (concept, ' '.join([x[0] for x in vals[:3]])))
writeRankingResults(vals, resultfile)
class AvgCombinedSim:
def __init__(self, collection, rootpath=ROOT_PATH):
self.wnsim = WordnetSim("wup")
self.fcsim = FlickrContextSim(collection, rootpath)
def compute(self, tagx, tagy, gamma=None, img=1):
fcs = self.fcsim.compute(tagx, tagy, gamma, img)
wns = self.wnsim.compute(tagx, tagy)
return (fcs + wns) * 0.5
class AvgCombinedSim:
def __init__(self, collection, rootpath=ROOT_PATH):
self.wnsim = WordnetSim("wup")
self.fcsim = FlickrContextSim(collection, rootpath)
def compute(self, tagx, tagy, gamma=None, img=1):
fcs = self.fcsim.compute(tagx, tagy, gamma, img)
wns = self.wnsim.compute(tagx, tagy)
return (fcs + wns) * 0.5
def __init__(self, collection, rootpath=ROOT_PATH):
self.wnsim = WordnetSim("wup")
self.fcsim = FlickrContextSim(collection, rootpath)
def __init__(self, collection, rootpath=ROOT_PATH):
self.wnsim = WordnetSim("wup")
self.fcsim = FlickrContextSim(collection, rootpath)
fcs = self.fcsim.compute(tagx, tagy, gamma, img)
wns = self.wnsim.compute(tagx, tagy)
return (fcs + wns) * 0.5
class MulCombinedSim(AvgCombinedSim):
def compute(self, tagx, tagy, gamma=None, img=1):
fcs = self.fcsim.compute(tagx, tagy, gamma, img)
wns = self.wnsim.compute(tagx, tagy)
return fcs * wns
if __name__ == "__main__":
collection = 'train10k'
fcs = FlickrContextSim(collection)
avgcos = AvgCombinedSim(collection)
mulcos = MulCombinedSim(collection)
wns = WordnetSim('wup')
tags = str.split(
'nature waterfall mountain 2012 bmw airshow jet airport beach food dog car cat animal street'
)
for tagx in tags:
for simclass in [wns, fcs, avgcos, mulcos]:
taglist = [(tagy, simclass.compute(tagx, tagy))
for tagy in tags] # fcs.vob]
taglist.sort(key=lambda v: v[1], reverse=True)
print '%s(%s)' % (simclass.__class__.__name__, tagx), ' '.join(
['%s %g' % (x[0], x[1]) for x in taglist[:10]])
print ''
