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 ])