def do_classify_weighted(cf, remote_cf, model, lastimage):
if remote_cf:
t = classify.classify_remote(model, lastimage, 0, remote_cf)
else:
t = classify.classify(model, lastimage, 0)
targets = dict(sorted(t.items(), key=lambda x: -x[1])[:cf['ntween']])
if cf['nsample'] < cf['ntween']:
ts = random.sample(targets.keys(), cf['nsample'])
ots = targets
targets = { t:ots[t] for t in ts }
print targets
return targets
def do_classify(cf, remote_cf, model, lastimage):
if cf['weighted']:
return do_classify_weighted(cf, remote_cf, model, lastimage)
targets = []
if remote_cf:
targets = classify.classify_remote(model, lastimage, cf['ntween'], remote_cf)
else:
targets = classify.classify(model, lastimage, cf['ntween'])
if cf['nsample'] < cf['ntween']:
targets = random.sample(targets, cf['nsample'])
print targets
return ','.join([ str(x) for x in targets ])
